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Does protein structure depend on phylogeny?

Does protein structure depend on phylogeny?


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Proteins have two basic secondary structure forms - beta strand and alpha helix. Do these depend on the organism or do the two forms exist for every protein?

For tertiary and quaternary structure: do such motifs depend on the position or does each organism have a specific form of protein structure?


Beta sheets and alpha helix are secondary structures that are simply very common to proteins. Their formation depends on the Amino acids that make up particular stretch in the primary sequence. For example alanines in a row will naturally tend to twist up into a alpha helix in water (medium matters). There are no hard and set rules to determine Tert. Structure or quart (aside from modeling but you have to validate in the end so its not entire end case)


Protein Structure and Function

1-2 Genes and Proteins [Full Text] [PDF]
- There is a linear relationship between the DNA base sequence of a gene and the amino-acid sequence of the protein it encodes
- The organization of the genetic code reflects the chemical grouping of the amino-acids

1-3 The Peptide Bond [Full Text] [PDF]
- Proteins are linear polymers of amino acids connected by amide bonds
- The properties of the peptide bond have important effects on the stability and flexibility of polypeptide chains in water

1-4 Bonds that Stabilize Folded Proteins [Full Text] [PDF]
- Folded proteins are stabilized mainly by weak noncovalent interactions
- The hydrogen-bonding properties of water have important effects on protein stability

1-5 Importance and Determinants of Secondary Structure [Full Text] [PDF]
- Folded proteins have segments of regular conformation
- The arrangement of secondary structure elements provides a convenient way of classifying types of folds
- Steric constraints dictate the possible types of secondary structure
- The simplest secondary structure element is the beta turn

1-6 Properties of the Alpha Helix [Full Text] [PDF]
- Alpha helices are versatile cylindrical structures stabilized by a network of backbone hydrogen bonds
- Alpha helices can be amphipathic, with one polar and one nonpolar face
- Collagen and polyproline helices have special properties

1-7 Properties of the Beta Sheet [Full Text] [PDF]
- Beta sheets are extended structures that sometimes form barrels
- Amphipathic beta sheets are found on the surfaces of proteins

1-8 Prediction of Secondary Structure [Full Text] [PDF]
- Certain amino acids are more usually found in alpha helices, others in beta sheets

1-9 Folding [Full Text] [PDF]
- The folded structure of a protein is directly determined by its primary structure
- Competition between self-interactions and interactions with water drives protein folding
- Computational prediction of folding is not yet reliable
- Helical membrane proteins may fold by condensation of preformed secondary structure elements in the bilayer

1-10 Tertiary Structure [Full Text] [PDF]
- The condensing of multiple secondary structural elements leads to tertiary structure
- Bound water molecules on the surface of a folded protein are an important part of the structure
- Tertiary structure is stabilized by efficient packing of atoms in the protein interior

1-11 Membrane Protein Structure [Full Text] [PDF]
- The principles governing the structures of integral membrane proteins are the same as those for water-soluble proteins and lead to formation of the same secondary structure elements

1-12 Protein Stability: Weak Interactions and Flexibility [Full Text] [PDF]
- The folded protein is a thermodynamic compromise
- Protein structure can be disrupted by a variety of agents
- The marginal stability of protein tertiary structure allows proteins to be flexible

1-13 Protein Stability: Post-Translational Modifications [Full Text] [PDF]
- Covalent bonds can add stability to tertiary structure
- Post-translational modification can alter both the tertiary structure and the stability of a protein

1-14 The Protein Domain [Full Text] [PDF]
- Globular proteins are composed of structural domains
- Domains have hydrophobic cores
- Multidomain proteins probably evolved by the fusion of genes that once coded for separate proteins

1-15 The Universe of Protein Structures [Full Text] [PDF]
- The number of protein folds is large but limited
- Protein structures are modular and proteins can be grouped into families on the basis of the domains they contain
- The modular nature of protein structure allows for sequence insertions and deletions

1-16 Protein Motifs [Full Text] [PDF]
- Protein motifs may be defined by their primary sequence or by the arrangement of secondary structure elements
- Identifying motifs from sequence is not straightforward

1-17 Alpha Domains and Beta Domains [Full Text] [PDF]
- Protein domains can be classified according to their secondary structural elements
- Two common motifs for alpha domains are the four-helix bundle and the globin fold
- Beta domains contain strands connected in two distinct ways
- Antiparallel beta sheets can form barrels and sandwiches

1-18 Alpha/Beta, Alpha+Beta and Cross-Linked Domains [Full Text] [PDF]
- In alpha/beta domains each strand of parallel beta sheet is usually connected to the next by an alpha helix
- There are two major families of alpha/beta domains: barrels and twists
- Alpha+beta domains have independent helical motifs packed against a beta sheet
- Metal ions and disulfide bridges form cross-links in irregular domains

1-19 Quaternary Structure: General Principles [Full Text] [PDF]
- Many proteins are composed of more than one polypeptide chain
- All specific intermolecular interactions depend on complementarity

1-20 Quaternary Structure: Intermolecular Interfaces [Full Text] [PDF]
- All types of protein-stabilizing interactions contribute to the formation of intermolecular interfaces
- Inappropriate quaternary interactions can have dramatic functional consequences

1-21 Quaternary Structure: Geometry [Full Text] [PDF]
- Protein assemblies built of identical subunits are usually symmetric

1-22 Protein Flexibility [Full Text] [PDF]
- Proteins are flexible molecules
- Conformational fluctuations in domain structure tend to be local
- Protein motions involve groups of non-bonded as well as covalently bonded atoms
- Triggered conformational changes can cause large movements of side chains, loops, or domains

Chapter 2: From Structure to Function [PDF] Back to top
2-0 Overview: The Structural Basis of Protein Function [Full Text] [PDF]
- There are many levels of protein function
- There are four fundamental biochemical functions of proteins

2-1 Recognition, Complementarity and Active Sites [Full Text] [PDF]
- Protein functions such as molecular recognition and catalysis depend on complementarity
- Molecular recognition depends on specialized microenvironments that result from protein tertiary structure
- Specialized microenvironments at binding sites contribute to catalysis

2-2 Flexibility and Protein Function [Full Text] [PDF]
- The flexibility of tertiary structure allows proteins to adapt to their ligands
- Protein flexibility is essential for biochemical function
- The degree of flexibility varies in proteins with different functions

2-3 Location of Binding Sites [Full Text] [PDF]
- Binding sites for macromolecules on a protein's surface can be concave, convex, or flat
- Binding sites for small ligands are clefts, pockets or cavities
- Catalytic sites often occur at domain and subunit interfaces

2-4 Nature of Binding Sites [Full Text] [PDF]
- Binding sites generally have a higher than average amount of exposed hydrophobic surface
- Binding sites for small molecules are usually concave and partly hydrophobic
- Weak interactions can lead to an easy exchange of partners
- Displacement of water also drives binding events
- Contributions to binding affinity can sometimes be distinguished from contributions to binding specificity

2-5 Functional Properties of Structural Proteins [Full Text] [PDF]
- Proteins as frameworks, connectors and scaffolds
- Some structural proteins only form stable assemblies
- Some catalytic proteins can also have a structural role
- Some structural proteins serve as scaffolds

2-6 Catalysis: Overview [Full Text] [PDF]
- Catalysts accelerate the rate of a chemical reaction without changing its overall equilibrium
- Catalysis usually requires more than one factor
- Catalysis is reducing the activation-energy barrier to a reaction

2-7 Active-Site Geometry [Full Text] [PDF]
- Reactive groups in enzyme active sites are optimally positioned to interact with the substrate

2-8 Proximity and Ground-State Destabilization [Full Text] [PDF]
- Some active sites chiefly promote proximity
- Some active sites destabilize ground states

2-9 Stabilization of Transition States and Exclusion of Water [Full Text] [PDF]
- Some active sites primarily stabilize transition states
- Many active sites must protect their substrates from water, but must be accessible at the same time

2-10 Redox Reactions [Full Text] [PDF]
- A relatively small number of chemical reactions account for most biological transformations
- Oxidation/reduction reactions involve the transfer of electrons and often require specific cofactors

2-11 Addition/Elimination, Hydrolysis and Decarboxylation [Full Text] [PDF]
- Addition reactions add atoms or chemical groups to double bonds, while elimination reactions remove them to form double bonds
- Esters, amides and acetals are cleaved by reaction with water their formation requires removal of water
- Loss of carbon dioxide is a common strategy for removing a single carbon atom from a molecule

2-13 Cofactors [Full Text] [PDF]
- Many active sites use cofactors to assist catalysis

2-15 Multifunctional Enzymes [Full Text] [PDF]
- Some enzymes can catalyze more than one reaction
- Some bifunctional enzymes have only one active site
- Some bifunctional enzymes contain two active sites

2-16 Multifunctional Enzymes with Tunnels [Full Text] [PDF]
- Some bifunctional enzymes shuttle unstable intermediates through a tunnel connecting the active sites
- Trifunctional enzymes can shuttle intermediates over huge distances
- Some enzymes also have non-enzymatic functions

Chapter 3: Control of Protein Function [PDF] Back to top
3-0 Overview: Mechanisms of Regulation [Full Text] [PDF]
- Protein function in living cells is precisely regulated
- Proteins can be targeted to specific compartments and complexes
- Protein activity can be regulated by binding of an effector and by covalent modification
- Protein activity may be regulated by protein quantity and lifetime
- A single protein may be subject to many regulatory influences

3-1 Protein Interaction Domains [Full Text] [PDF]
- The flow of information within the cell is regulated and integrated by the combinatorial use of small protein domains that recognize specific ligands

3-2 Regulation by Location [Full Text] [PDF]
- Protein function in the cell is context-dependent
- There are several ways of targeting proteins in cells

3-3 Control by pH and the Redox Environment [Full Text] [PDF]
- Protein function is modulated by the environment in which the protein operates
- Changes in redox environment can greatly affect protein structure and function
- Changes in pH can drastically alter protein structure and function

3-4 Effector Ligands: Competitive Binding and Cooperativity [Full Text] [PDF]
- Protein function can be controlled by effector ligands that bind competitively to ligand-binding or active sites
- Cooperative binding by effector ligands amplifies their effects

3-5 Effector Ligands: Conformational Change and Allostery [Full Text] [PDF]
- Effector molecules can cause conformational changes at distant sites
- ATCase is an allosteric enzyme with regulatory and active sites on different subunits
- Disruption of function does not necessarily mean that the active site or ligand-binding site has been disrupted
- Binding of gene regulatory proteins to DNA is often controlled by ligand-induced conformational changes

3-6 Protein Switches Based on Nucleotide Hydrolysis [Full Text] [PDF]
- Conformational changes driven by nucleotide binding and hydrolysis are the basis for switching and motor properties of proteins
- All nucleotide switch proteins have some common structural and functional features

3-7 GTPase Switches: Small Signaling G Proteins [Full Text] [PDF]
- The switching cycle of nucleotide hydrolysis and exchange in G proteins is modulated by the binding of other proteins

3-8 GTPase Switches: Signal Relay by Heterotrimeric GTPases [Full Text] [PDF]
- Heterotrimeric G proteins relay and amplify extracellular signals from a receptor to an intracellular signaling pathway

3-9 GTPase Switches: Protein Synthesis [Full Text] [PDF]
- EF-Tu is activated by binding to the ribosome, which thereby signals it to release its bound tRNA

3-10 Motor Protein Switches [Full Text] [PDF]
- Myosin and kinesin are ATP-dependent nucleotide switches that move along actin filaments and microtubules respectively

3-11 Regulation by Degradation [Full Text] [PDF]
- Protein function can be controlled by protein lifetime
- Proteins are targeted to proteasomes for degradation

3-12 Control of Protein Function by Phosphorylation [Full Text] [PDF]
- Protein function can be controlled by covalent modification
- Phosphorylation is the most important covalent switch mechanism for the control of protein function

3-13 Regulation of Signaling Protein Kinases: Activation Mechanism [Full Text] [PDF]
- Protein kinases are themselves controlled by phosphorylation
- Src kinases both activate and inhibit themselves

3-15 Two-Component Signaling Systems in Bacteria [Full Text] [PDF]
- Two-component signal carriers employ a small conformational change that is driven by covalent attachment of a phosphate group

3-16 Control by Proteolysis: Activation of Precursors [Full Text] [PDF]
- Limited proteolysis can activate enzymes
- Polypeptide hormones are produced by limited proteolysis

3-17 Protein Splicing: Autoproteolysis by Inteins [Full Text] [PDF]
- Some proteins contain self-excising inteins
- The mechanism of autocatalysis is similar for inteins from unicellular organisms and metazoan Hedgehog protein

3-18 Glycosylation [Full Text] [PDF]
- Glycosylation can change the properties of a protein and provide recognition sites

3-19 Protein Targeting by Lipid Modifications [Full Text] [PDF]
- Covalent attachment of lipids targets proteins to membranes and other proteins
- The GTPases that direct intracellular membrane traffic are reversibly associated with internal membranes of the cell

3-20 Methylation, N-acetylation, Sumoylation and Nitrosylation [Full Text] [PDF]
- Fundamental biological processes can also be regulated by other post-translational modifications of proteins

Chapter 4: From Sequence to Function [PDF] Back to top
4-0 Overview: From Sequence to Function in the Age of Genomics [Full Text] [PDF]
- Genomics is making an increasing contribution to the study of protein structure and function

4-1 Sequence Alignment and Comparison [Full Text] [PDF]
- Sequence comparison provides a measure of the relationship between genes
- Alignment is the first step in determining whether two sequences are similar to each other
- Multiple alignments and phylogenetic trees

4-2 Protein Profiling [Full Text] [PDF]
- Structural data can help sequence comparison find related proteins
- Sequence and structural motifs and patterns can identify proteins with similar biochemical functions
- Protein-family profiles can be generated from multiple alignments of protein families for which representative structures are known

4-3 Deriving Function from Sequence [Full Text] [PDF]
- Sequence information is increasing exponentially
- In some cases function can be inferred from sequence

4-4 Experimental Tools for Probing Protein Function [Full Text] [PDF]
- Gene function can sometimes be established experimentally without information from protein structure or sequence homology

4-5 Divergent and Convergent Evolution [Full Text] [PDF]
- Evolution has produced a relatively limited number of protein folds and catalytic mechanisms
- Proteins that differ in sequence and structure may have converged to similar active sites, catalytic mechanisms and biochemical function
- Proteins with low sequence similarity but very similar overall structure and active sites are likely to be homologous
- Convergent and divergent evolution are sometimes difficult to distinguish
- Divergent evolution can produce proteins with sequence and structural similarity but different functions

4-6 Structure from Sequence: Homology Modeling [Full Text] [PDF]
- Structure can be derived from sequence by reference to known protein folds and protein structures
- Homology modeling is used to deduce the structure of a sequence with reference to the structure of a close homolog

4-7 Structure from Sequence: Profile-Based Threading and "Rosetta" [Full Text] [PDF]
- Profile-based threading tries to predict the structure of a sequence even if no sequence homologs are known
- The Rosetta method attempts to predict protein structure from sequence without the aid of a homologous sequence or structure

4-8 Deducing Function from Structure: Protein Superfamilies [Full Text] [PDF]
- Members of a structural superfamily often have related biochemical functions
- The four superfamilies of serine proteases are examples of convergent evolution
- Very closely related protein families can have completely different biochemical and biological functions

4-9 Strategies for Identifying Binding Sites [Full Text] [PDF]
- Binding sites can sometimes be located in three-dimensional structures by purely computational means
- Experimental means of locating binding sites are at present more accurate than computational methods

4-10 Strategies for Identifying Catalytic Residues [Full Text] [PDF]
- Site-directed mutagenesis can identify residues involved in binding or catalysis
- Active-site residues in a structure can sometimes be recognized computationally by their geometry
- Docking programs model the binding of ligands

4-11 TIM Barrels: One Structure with Diverse Functions [Full Text] [PDF]
- Knowledge of a protein's structure does not necessarily make it possible to predict its biochemical or cellular functions

4-12 PLP Enzymes: Diverse Structures with One Function [Full Text] [PDF]
- A protein's biochemical function and catalytic mechanism do not necessarily predict its three-dimensional structure

4-13 Moonlighting: Proteins with More than One Function [Full Text] [PDF]
- In multicellular organisms, multifunctional proteins help expand the number of protein functions that can be derived from relatively small genomes

4-14 Chameleon Sequences: One Sequence with More than One Fold [Full Text] [PDF]
- Some amino-acid sequences can assume different secondary structures in different structural contexts

4-16 Functions for Uncharacterized Genes: Galactonate Dehydratase [Full Text] [PDF]
- Determining biochemical function from sequence and structure becomes more accurate as more family members are identified
- Alignments based on conservation of residues that carry out the same active-site chemistry can identify more family members than sequence comparisons alone
- In well studied model organisms, information from genetics and cell biology can help identify the substrate of an "unknown" enzyme and the actual reaction catalyzed

4-17 Starting from Scratch: A Gene Product of Unknown Function [Full Text] [PDF]
- Function cannot always be determined from sequence, even with the aid of structural information and chemical intuition

Chapter 5: Structure Determination [PDF] Back to top
5-1 The Interpretation of Structural Information [Full Text] [PDF]
- Experimentally determined protein structures are the result of the interpretation of different types of data
- Both the accuracy and the precision of a structure can vary
- The information content of a structure is determined by its resolution

5-2 Structure Determination by X-Ray Crystallography and NMR [Full Text] [PDF]
- Protein crystallography involves summing the scattered X-ray waves from a macromolecular crystal
- NMR spectroscopy involves determining internuclear distances by measuring perturbations between assigned resonances from atoms in the protein in solution

5-3 Quality and Representation of Crystal and NMR Structures [Full Text] [PDF]
- The quality of a finished structure depends largely on the amount of data collected
- Different conventions for representing the structures of proteins are useful for different purposes


Keywords

Coronaviruses pose serious health threats to humans and other animals. From 2002 to 2003, severe acute respiratory syndrome coronavirus (SARS-CoV) infected 8,000 people, with a fatality rate of ∼10% (1–4). Since 2012, Middle East respiratory syndrome coronavirus (MERS-CoV) has infected more than 1,700 people, with a fatality rate of ∼36% (5, 6). Since 2013, porcine epidemic diarrhea coronavirus (PEDV) has swept throughout the United States, causing an almost 100% fatality rate in piglets and wiping out more than 10% of America's pig population in less than a year (7–9). In general, coronaviruses cause widespread respiratory, gastrointestinal, and central nervous system diseases in humans and other animals, threatening human health and causing economic loss (10, 11). Coronaviruses are capable of adapting to new environments through mutation and recombination with relative ease and hence are programmed to alter host range and tissue tropism efficiently (12–14). Therefore, health threats from coronaviruses are constant and long-term. Understanding the virology of coronaviruses and controlling their spread have important implications for global health and economic stability.

Coronaviruses belong to the family Coronaviridae in the order Nidovirales (10, 11). They can be classified into four genera: Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus (Figure 1a). Among them, alpha- and betacoronaviruses infect mammals, gammacoronaviruses infect avian species, and deltacoronaviruses infect both mammalian and avian species. Representative alphacoronaviruses include human coronavirus NL63 (HCoV-NL63), porcine transmissible gastroenteritis coronavirus (TGEV), PEDV, and porcine respiratory coronavirus (PRCV). Representative betacoronaviruses include SARS-CoV, MERS-CoV, bat coronavirus HKU4, mouse hepatitis coronavirus (MHV), bovine coronavirus (BCoV), and human coronavirus OC43. Representative gamma- and deltacoronaviruses include avian infectious bronchitis coronavirus (IBV) and porcine deltacoronavirus (PdCV), respectively. Coronaviruses are large, enveloped, positive-stranded RNA viruses. They have the largest genome among all RNA viruses, typically ranging from 27 to 32 kb. The genome is packed inside a helical capsid formed by the nucleocapsid protein (N) and further surrounded by an envelope. Associated with the viral envelope are at least three structural proteins: The membrane protein (M) and the envelope protein (E) are involved in virus assembly, whereas the spike protein (S) mediates virus entry into host cells. Some coronaviruses also encode an envelope-associated hemagglutinin-esterase protein (HE). Among these structural proteins, the spike forms large protrusions from the virus surface, giving coronaviruses the appearance of having crowns (hence their name corona in Latin means crown) (Figures 1b and 2a). In addition to mediating virus entry, the spike is a critical determinant of viral host range and tissue tropism and a major inducer of host immune responses.

The coronavirus spike contains three segments: a large ectodomain, a single-pass transmembrane anchor, and a short intracellular tail (Figure 1b,c). The ectodomain consists of a receptor-binding subunit S1 and a membrane-fusion subunit S2. Electron microscopy studies revealed that the spike is a clove-shaped trimer with three S1 heads and a trimeric S2 stalk (15–18) (Figures 1b and 2a). During virus entry, S1 binds to a receptor on the host cell surface for viral attachment, and S2 fuses the host and viral membranes, allowing viral genomes to enter host cells. Receptor binding and membrane fusion are the initial and critical steps in the coronavirus infection cycle they also serve as primary targets for human inventions. In this article, I review the structure and function of coronavirus spikes and discuss their evolution.


Characteristics of Epstein-Barr virus envelope protein gp42

Epstein-Barr virus (EBV) glycoprotein 42 (gp42) is a membrane protein essential for fusion and entry of EBV into host B-lymphocytes. Gp42 is a member of the protein-fold family C-type lectin or lectin-like domains (CLECT or CTLD) and specifically is classified as a natural-killer receptor (NKR)-like CLECT. Literature review and phylogenetic comparison show that EBV gp42 shares a common structure with other NKR-like CLECTs and possibly with many viral CTLDs, but does not appear to exhibit some common binding characteristics of many CTLDs, such as features required for calcium binding. The flexible N-terminal region adjacent to the CTLD fold is important for binding to other EBV glycoproteins and for a cleavage site that is necessary for infection of host cells. From structural studies of gp42 unbound and bound to receptor and extensive mutational analysis, a general model of how gp42 triggers membrane fusion utilizing both the flexible N-terminal region and the CTLD domain has emerged.

Figures

Overlay of the HLA class II-bound and unbound structures of EBV gp42. Bound…

Rooted phylogenetic cladogram of viral…

Rooted phylogenetic cladogram of viral CTLDs. Gamma herpesvirus CTLDs are grouped (green branch).…

Structure of EBVgp42 bound to…

Structure of EBVgp42 bound to HLA class II (PDB identification number 1KG0) with…


Does protein structure depend on phylogeny? - Biology

I hope soon to move these software listings webpages to a Github archive, and invite others to help contribute to them and maintain them.

Here are 392 phylogeny packages and 54 free web servers, (almost) all that I know about. It is an attempt to be completely comprehensive. I have not made any attempt to exclude programs that do not meet some standard of quality or importance. Updates to these pages are made roughly monthly. Here is a "waiting list" of new programs waiting to have their full entries constructed. Many of the programs in these pages are available on the web, and some of the older ones are also available from ftp server machines.

The programs listed below include both free and non-free ones in some cases I do not know whether a program is free. I have listed as free those that I knew were free for the others you have to ask their distributor. Usually when I say that a program is downloadable from a web site, this means that it is available free.

Email addresses in these pages have had the @ symbol replaced by (at) and also surrounded by invisible confusing tags and blank characters in hopes of foiling spambots that harvest email addresses.

Owing to past NSF support of these pages, I am required to note that any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation (NSF supported these pages from 1995-2003).

L ist of packages arranged .

Phylogeny programs formerly listed here but no longer distributed

  • General-purpose packages
  • Parsimony programs
  • Distance matrix methods
  • Computation of distances
  • Maximum likelihood methods
  • Bayesian inference methods
  • Quartets methods
  • Artificial-intelligence and genetic algorithms methods
  • Invariants (or Evolutionary Parsimony) methods
  • Interactive tree manipulation
  • Looking for hybridization or recombination events
  • Bootstrapping and other measures of support
  • Compatibility analysis
  • Consensus trees, subtrees, supertrees, distances between trees
  • Tree-based alignment
  • Gene duplication and genomic analysis
  • Biogeographic analysis and host-parasite comparison
  • Comparative method analysis
  • Simulation of trees or data
  • Examination of shapes of trees
  • Clocks, dating and stratigraphy
  • Model Selection
  • Description or prediction of data from trees
  • Tree plotting/drawing
  • Sequence management/job submission
  • Teaching about phylogenies
  • Web or e-mail servers that can analyze data for you
  • PHYLIP
  • PAUP*
  • MEGA
  • Phylo_win
  • ARB
  • DAMBE
  • PAL
  • Bionumerics
  • Mesquite
  • PaupUp
  • BIRCH
  • Bosque
  • EMBOSS
  • phangorn
  • Bio++
  • ETE
  • DendroPy
  • SeaView
  • Crux
  • PHYLIP
  • PAUP*
  • Hennig86
  • MEGA
  • RA
  • NONA
  • CAFCA
  • PHYLIP
  • Phylo_win
  • sog
  • gmaes
  • LVB
  • GeneTree
  • ARB
  • DAMBE
  • MALIGN
  • POY
  • Gambit
  • TNT
  • GelCompar II
  • Bionumerics
  • Network
  • TCS
  • GAPars
  • CRANN
  • Mesquite
  • PAST
  • FootPrinter
  • BPAnalysis
  • Simplot
  • Parsimov
  • NimbleTree
  • PaupUp
  • Notung
  • BIRCH
  • IDEA
  • PSODA
  • PRAP
  • SeqState
  • Bosque
  • PhyloNet
  • EMBOSS
  • phangorn
  • Murka
  • Freqpars
  • SeaView
  • PAUPRat
  • PHYLIP
  • PAUP*
  • MEGA
  • MacT
  • ODEN
  • TREECON
  • DISPAN
  • RESTSITE
  • NTSYSpc
  • METREE
  • GDA
  • SeqPup
  • PHYLTEST
  • Lintre
  • Phylo_win
  • POPTREE2
  • Gambit
  • gmaes
  • DENDRON
  • BIONJ
  • TFPGA
  • MVSP
  • ARB
  • Darwin
  • T-REX
  • sendbs
  • nneighbor
  • DAMBE
  • weighbor
  • DNASIS
  • MINSPNET
  • PAL
  • Arlequin
  • PEBBLE
  • HY-PHY
  • Vanilla
  • GelCompar II
  • Bionumerics
  • qclust
  • TCS
  • Populations
  • Winboot
  • SYN-TAX
  • PTP
  • SplitsTree
  • FastME
  • APE
  • MacVector
  • QuickTree
  • Simplot
  • ProfDist
  • START2
  • STC
  • NimbleTree
  • CBCAnalyzer
  • PaupUp
  • Geneious
  • BIRCH
  • SEMPHY
  • FASTML
  • Rate4Site
  • SWORDS
  • IDEA
  • FAMD
  • Bosque
  • GAME
  • Bioinformatics_Toolbox
  • TreeFit
  • EMBOSS
  • phangorn
  • PC-ORD
  • Bio++
  • UGENE
  • NINJA
  • SeaView
  • Statio
  • TIMER
  • Crux
  • Ancestor
  • ANC-GENE
  • Bn-Bs
  • PHYLIP
  • PAUP*
  • RAPDistance
  • MULTICOMP
  • Microsat
  • DIPLOMO
  • OSA
  • DISPAN
  • RESTSITE
  • NTSYSpc
  • TREE-PUZZLE
  • GCUA
  • DERANGE2
  • POPGENE
  • TFPGA
  • REAP
  • MVSP
  • RSTCALC
  • Genetix
  • DISTANCE
  • Darwin
  • sendbs
  • Arlequin
  • DAMBE
  • DnaSP
  • PAML
  • puzzleboot
  • PAL
  • Vanilla
  • GelCompar II
  • Bionumerics
  • qclust
  • Populations
  • Winboot
  • FSTAT
  • SYN-TAX
  • Phylo_win
  • Phyltools
  • MSA
  • APE
  • YCDMA
  • NSA
  • T-REX
  • LDDist
  • DIVAGE
  • Genepop
  • START2
  • Swaap
  • Swaap PH
  • SPAGeDi
  • CBCAnalyzer
  • PaupUp
  • SEMPHY
  • SWORDS
  • rRNA phylogeny
  • FAMD
  • GAME
  • Bioinformatics_Toolbox
  • GenoDive
  • analysis
  • TreeFit
  • EMBOSS
  • Murka
  • Bio++
  • UGENE
  • POPTREE2
  • DISTREE
  • SeaView
  • Crux
  • Bn-Bs
  • HON-new
  • PHYLIP
  • PAUP*
  • fastDNAml
  • MOLPHY
  • PAML
  • Spectrum
  • SplitsTree
  • TREE-PUZZLE
  • SeqPup
  • Phylo_win
  • PASSML
  • ARB
  • Darwin
  • Modeltest
  • DAMBE
  • PAL
  • dnarates
  • HY-PHY
  • Vanilla
  • DT-ModSel
  • Bionumerics
  • fastDNAmlRev
  • RevDNArates
  • rate-evolution
  • CONSEL
  • EDIBLE
  • PLATO
  • Mesquite
  • PTP
  • Treefinder
  • MetaPIGA
  • RAxML
  • PHYML
  • r8s-bootstrap
  • MrMTgui
  • MrModeltest
  • BootPHYML
  • PARBOOT
  • p4
  • Porn*
  • SIMMAP
  • Spectronet
  • Rhino
  • TipDate
  • ProtTest
  • ModelGenerator
  • Simplot
  • MrAIC
  • Modelfit
  • IQPNNI
  • PARAT
  • ALIFRITZ
  • PhyNav
  • DPRML
  • MultiPhyl
  • NimbleTree
  • PaupUp
  • SSA
  • CoMET
  • BIRCH
  • Mac5
  • Kakusan4
  • GARLI
  • PHYSIG
  • SEMPHY
  • FASTML
  • Rate4Site
  • aLRT
  • McRate
  • EREM
  • PROCOV
  • DART
  • PhyloCoCo
  • PRAP
  • SeqState
  • Leaphy
  • NHML
  • SLR
  • rRNA phylogeny
  • Bosque
  • Concaterpillar
  • PHYLLAB
  • NEPAL
  • EMBOSS
  • CodeAxe
  • phangorn
  • Bio++
  • FastTree
  • nhPhyML
  • PhyML-Multi
  • Segminator
  • raxmlGUI
  • MixtureTree
  • SeaView
  • GZ-Gamma
  • PAUPRat
  • Crux
  • PAML
  • BAMBE
  • PAL
  • Vanilla
  • MrBayes
  • Mesquite
  • PHASE
  • BEAST
  • MrBayes tree scanners
  • p4
  • SIMMAP
  • IMa2
  • BAli-Phy
  • BayesPhylogenies
  • MrBayesPlugin
  • PhyloBayes
  • PHASE
  • Cadence
  • Multidivtime
  • BEST
  • AMBIORE
  • PHYLLAB
  • bms_runner
  • tracer
  • burntrees
  • Bio++
  • Crux
  • ANC-GENE
  • TREE-PUZZLE
  • SplitsTree
  • PHYLTEST
  • GEOMETRY
  • PICA
  • Darwin
  • PhyloQuart
  • Willson quartets programs
  • Gambit
  • IQPNNI
  • STC
  • Quartet Suite
  • LEVEL2
  • Bosque
  • MacClade
  • PHYLIP
  • PDAP
  • TreeTool
  • ARB
  • WINCLADA
  • TreeEdit
  • TreeExplorer
  • TreeThief
  • RadCon
  • Mavric
  • T-REX
  • EDIBLE
  • Mesquite
  • Treefinder
  • TreeView
  • TreeJuxtaposer
  • TreeMe
  • ArboDraw
  • Notung
  • TreeDyn
  • TreeMaker
  • MESA
  • BIRCH
  • SimpleClade
  • Dendroscope
  • Forest
  • Phylocom
  • TreeToy
  • Bioinformatics_Toolbox
  • Phyutility
  • EMBOSS
  • PhyloWidget
  • Phybase
  • ETE
  • TreeGraph 2
  • Crux
  • RecPars
  • TOPALi
  • partimatrix
  • Network
  • TCS
  • T-REX
  • PLATO
  • PPH
  • Spectronet
  • IMa2
  • Simplot
  • START2
  • Likewind
  • DualBrothers
  • cBrother
  • EEEP
  • HGT
  • PhyloNet
  • EvolSimulator
  • Concaterpillar
  • PhyML-Multi
  • RDP3
  • PHYLIP
  • PAUP*
  • Random Cladistics
  • AutoDecay
  • TreeRot
  • DNA Stacks
  • OSA
  • DISPAN
  • PHYLTEST
  • Lintre
  • sog
  • POPTREE2
  • MEGA
  • PARBOOT
  • PICA
  • ModelTest
  • TAXEQ3
  • BAMBE
  • DAMBE
  • puzzleboot
  • CodonBootstrap
  • Gambit
  • PAL
  • MrBayes
  • CONSEL
  • Populations
  • LVB
  • EDIBLE
  • Winboot
  • Mesquite
  • Phylo_win
  • PAST
  • Treefinder
  • RAxML
  • Phyltools
  • PHASE
  • PHYML
  • BEAST
  • r8s-bootstrap
  • MrBayes tree scanners
  • T-REX
  • MrMTgui
  • MrModeltest
  • BootPHYML
  • Porn*
  • ProtTest
  • ModelGenerator
  • Simplot
  • Permute!
  • ELW
  • MultiPhyl
  • GHOSTS
  • PaupUp
  • Geneious
  • BIRCH
  • BayesPhylogenies
  • scaleboot
  • aLRT
  • PhyloBayes
  • SWORDS
  • CTree
  • PRAP
  • FAMD
  • PhyloNet
  • PHYLLAB
  • Phyutility
  • EMBOSS
  • FastTree
  • Bionumerics
  • tracer
  • burntrees
  • Bio++
  • raxmlGUI
  • MixtureTree
  • COMPROB
  • PHYLIP
  • PICA
  • partimatrix
  • PPH
  • Spectronet
  • BIRCH
  • EMBOSS
  • Murka
  • Phybase
  • TIGER
  • COMPONENT
  • TREEMAP
  • NTSYSpc
  • PHYLIP
  • PAUP*
  • REDCON
  • TAXEQ3
  • MEGA
  • RadCon
  • Mesquite
  • PAST
  • Treefinder
  • Robinson and Foulds distance
  • Clann
  • PhyNav
  • SuperTree
  • Supertree scripts
  • PaupUp
  • Supertree
  • BIRCH
  • HeuristicMRF2
  • TopD/fMts
  • Quartet Suite
  • Rainbow
  • PhySIC_IST
  • EEEP
  • PhyloSort
  • FAMD
  • Phyutility
  • EMBOSS
  • phangorn
  • Murka
  • RAxML
  • Phybase
  • iGTP
  • raxmlGUI
  • Crux
  • TreeAlign
  • ClustalW
  • MALIGN
  • GeneDoc
  • DAMBE
  • POY
  • ALIGN
  • DNASIS
  • FootPrinter
  • ALIFRITZ
  • T-Coffee
  • ArboDraw
  • BAli-Phy
  • Geneious
  • BIRCH
  • MAFFT
  • LOBSTER
  • DART
  • MUSCLE
  • Bosque
  • EMBOSS
  • SeaView
  • SuiteMSA
  • DERANGE2
  • FORESTER
  • BPAnalysis
  • Notung
  • TopD/fMts
  • DTscore
  • DART
  • gtp
  • EvolSimulator
  • DTdraw
  • Mgenome
  • Tree Tracker
  • bms_runner
  • MANTiS
  • ETE
  • MANTiS
  • iGTP
  • COMPONENT
  • TREEMAP
  • DIVA
  • TreeFitter
  • GEODIS
  • Tarzan
  • ParaFit
  • Phylocom
  • AxParafit
  • GenGIS
  • S-DIVA
  • Lagrange
  • CoRe-PA
  • Jane
  • PHYLIP
  • CAIC
  • COMPARE
  • PDAP
  • ANCML
  • RIND
  • MacroCAIC
  • Phylogenetic Independence
  • MacClade
  • Mesquite
  • APE
  • Jevtrace
  • SIMMAP
  • PHYLOGR
  • TreeSAAP
  • Permute!
  • Parsimov
  • DIVERGE
  • IDC
  • OUCH
  • BIRCH
  • BayesTraits
  • PHYSIG
  • Cactus-Pie
    • Phylocom
    • pcca
    • EMBOSS
    • bms_runner
    • SLOUCH
    • Phybase
    • COMPONENT
    • Seq-Gen
    • Treevolve and PTreevolve
    • PSeq-Gen
    • COMPARE
    • ROSE
    • PAML
    • ProSeq
    • PAL
    • Vanilla
    • MacClade
    • EDIBLE
    • Mesquite
    • Treefinder
    • Network
    • Phylogen
    • MESA
    • SGRunner
    • apTreeshape
    • Simprot
    • EREM
    • indel-Seq-Gen
    • DAWG
    • EvolveAGene3
    • EvolSimulator
    • Bio::Phylo
    • Recodon
    • NetRecodon
    • SuiteMSA
    • Crux
    • MacroCAIC
    • Genie
    • PAL
    • Vanilla
    • RadCon
    • BRANCHLENGTH
    • APE
    • Tracer
    • SymmeTREE
    • TreeScan
    • MESA
    • apTreeshape
    • TreeStat
    • CTree
    • Phyutility
    • laser
    • PhyRe
    • Bio::Phylo
    • PHYLIP
    • QDate
    • Modeltest
    • PAML
    • RRTree
    • PEBBLE
    • TreeEdit
    • HY-PHY
    • MEGA
    • PAL
    • rate-evolution
    • BRANCHLENGTH
    • r8s
    • PAST
    • Treefinder
    • Network
    • APE
    • BEAST
    • MrMTgui
    • MrModeltest
    • SymmeTREE
    • Porn*
    • TipDate
    • Rhino
    • GHOSTS
    • Cadence
    • Multidivtime
    • CodonRates
    • BIRCH
    • Brownie
    • PATHd8
    • McRate
    • PhyloBayes
    • Cactus-Pie
    • GRate
    • NHML
    • TreeFit
    • PHYLTEST
    • Murka
    • TIMER
    • Modeltest
    • MrMTgui
    • MrModeltest
    • Porn*
    • ModelGenerator
    • ProtTest
    • MrAIC
    • Modelfit
    • DT-ModSel
    • BayesTraits
    • Kakusan4
    • MAPPS
    • DART
    • Concaterpillar
    • Statio
    • jMODELTEST
    • PHYLIP
    • PAUP*
    • TreeTool
    • TreeView
    • NJplot
    • DendroMaker
    • Tree Draw Deck
    • Phylodendron
    • ARB
    • unrooted
    • DAMBE
    • TREECON
    • Mavric
    • TreeExplorer
    • TreeThief
    • Bionumerics
    • FORESTER
    • MacClade
    • MEGA
    • Mesquite
    • Phylogenetic Tree Drawing
    • APE
    • T-REX
    • TreeJuxtaposer
    • Spectronet
    • TreeSetViz
    • TreeGraph 2
    • ArboDraw
    • PaupUp
    • Notung
    • TreeDyn
    • DigTree
    • Geneious
    • BIRCH
    • Paloverde
    • MrEnt
    • FigTree
    • HyperTree
    • GeoPhyloBuilder
    • Dendroscope
    • CTree
    • TreeToy
    • TreeSnatcher Plus
    • DTdraw
    • PHYLLAB
    • Bioinformatics_Toolbox
    • EMBOSS
    • PhyloWidget
    • GenGIS
    • Bio++
    • Bio::Phylo
    • S-DIVA
    • UGENE
    • ETE
    • POPTREE2
    • Segminator
    • MixtureTree
    • SeaView
    • Archaeopteryx
    • SuiteMSA
    • Random Cladistics
    • GDE
    • MUST 2000
    • DNA Stacks
    • SeqPup
    • PARBOOT
    • ARB
    • DAMBE
    • BioEdit
    • Singapore PHYLIP web interface
    • Bionumerics
    • W2H
    • Phyledit
    • GeneStudio Pro
    • Simplot
    • DPRML
    • NimbleTree
    • Geneious
    • BIRCH
    • TOPALi
    • MBEToolbox
    • PISE
    • Bosque
    • Bioinformatics_Toolbox
    • EMBOSS
    • PyCogent
    • PHYDIT
    • Segminator
    • SeaView
    • SuiteMSA

    T able of contents by computer systems
    on which they work

    • Unix (source code in C or executables). I have included programs that are available as C source code because most Unix workstations have a C compiler. (Programs in other compiled languages such as FORTRAN and Pascal, and in interpreted languages such as Java, Perl, Python, or R are also included), as are Java executables. For many of these the programs can also be compiled or run on Windows or Mac OS X systems if they have the appropriate compilers or interpreters loaded.
      • PHYLIP
      • PAUP*
      • Phylo_win
      • ODEN
      • SeqPup
      • Lintre
      • Microsat
      • OSA
      • TREE-PUZZLE
      • fastDNAml
      • MOLPHY
      • PAML
      • SplitsTree
      • PHYLTEST
      • TreeAlign
      • ClustalW
      • MALIGN
      • GeneDoc
      • COMPARE
      • Seq-Gen
      • TreeTool
      • GDE
      • sog
      • Phylodendron
      • Treevolve and PTreevolve
      • PSeq-Gen
      • POPTREE2
      • gmaes
      • GCUA
      • DERANGE2
      • LVB
      • BIONJ
      • ANCML
      • QDate
      • PASSML
      • TOPALi
      • RecPars
      • PARBOOT
      • ARB
      • DISTANCE
      • Darwin
      • sendbs
      • partimatrix
      • BAMBE
      • nneighbor
      • unrooted
      • ROSE
      • weighbor
      • PhyloQuart
      • puzzleboot
      • Willson quartets programs
      • POY
      • RIND
      • RRTree
      • Mavric
      • dnarates
      • Arlequin
      • HY-PHY
      • Genie
      • Vanilla
      • qclust
      • fastDNAmlRev
      • RevDNArates
      • BRANCHLENGTH
      • TCS
      • CONSEL
      • FORESTER
      • Populations
      • T-REX
      • MrBayes
      • W2H
      • GAPars
      • EDIBLE
      • r8s
      • Mesquite
      • Treefinder
      • PPH
      • PLATO
      • MetaPIGA
      • FastME
      • MSA
      • Phylogenetic Tree Drawing
      • APE
      • PHASE
      • PHYML
      • BEAST
      • TreeView
      • r8s-bootstrap
      • MrBayes tree scanners
      • Robinson and Foulds distance
      • Clann
      • Jevtrace
      • MrMTgui
      • MrModeltest
      • BootPHYML
      • SymmeTREE
      • TreeJuxtaposer
      • LDDist
      • p4
      • Porn*
      • TNT
      • Phylogen
      • Rhino
      • TipDate
      • Phylap
      • Dnatree
      • QuickTree
      • IMa2
      • FootPrinter
      • BPAnalysis
      • ProtTest
      • GEODIS
      • TreeScan
      • TreeSetViz
      • ModelGenerator
      • PHYLOGR
      • ProfDist
      • MrAIC
      • Modelfit
      • IQPNNI
      • PARAT
      • ALIFRITZ
      • PhyNav
      • STC
      • TreeSAAP
      • Likewind
      • ELW
      • TreeGraph 2
      • Supertree scripts
      • Parsimov
      • Bosque
      • DIVERGE
      • T-Coffee
      • CBCAnalyzer
      • GHOSTS
      • Tarzan
      • DT-ModSel
      • DualBrothers
      • apTreeshape
      • Multidivtime
      • Mgenome
      • ParaFit
      • IDC
      • TreeMaker
      • CodonRates
      • BAli-Phy
      • Supertree
      • OUCH
      • TreeDyn
      • DigTree
      • Geneious
      • BIRCH
      • Brownie
      • Mac5
      • BayesPhylogenies
      • BayesTraits
      • Paloverde
      • HeuristicMRF2
      • CRANN
      • Kakusan4
      • PATHd8
      • MAFFT
      • GARLI
      • TreeStat
      • FigTree
      • PHYSIG
      • scaleboot
      • cBrother
      • RAxML
      • MrBayesPlugin
      • LOBSTER
      • SEMPHY
      • FASTML
      • Rate4Site
      • TopD/fMts
      • Quartet Suite
      • Rainbow
      • McRate
      • HyperTree
      • PhyloBayes
      • Cactus-Pie
      • SWORDS
      • Dendroscope
      • Forest
      • Phylocom
      • PhySIC_IST
      • Simprot
      • BEST
      • pcca
      • EREM
      • indel-Seq-Gen
      • MBEToolbox
      • DTscore
      • PROCOV
      • DART
      • EEEP
      • DAWG
      • LEVEL2
      • PSODA
      • PhyloSort
      • PISE
      • MUSCLE
      • AMBIORE
      • CTree
      • PRAP
      • HGT
      • NHML
      • SLR
      • rRNA phylogeny
      • AxParafit
      • EvolveAGene3
      • gtp
      • TreeToy
      • TreeSnatcher Plus
      • EvolSimulator
      • Concaterpillar
      • GAME
      • DTdraw
      • NEPAL
      • PHYLLAB
      • Bioinformatics_Toolbox
      • Tree Tracker
      • analysis
      • CodeAxe
      • Phyutility
      • EMBOSS
      • phangorn
      • FastTree
      • PhyloWidget
      • laser
      • bms_runner
      • tracer
      • burntrees
      • SLOUCH
      • Murka
      • MANTiS
      • Freqpars
      • GenGIS
      • CONSERVE
      • Bio++
      • UGENE
      • DISTREE
      • Phybase
      • ETE
      • PyCogent
      • DendroPy
      • CAIC
      • NINJA
      • MUST
      • nhPhyML
      • PhyML-Multi
      • Segminator
      • iGTP
      • Bio::Phylo
      • Recodon
      • NetRecodon
      • Lagrange
      • CoRe-PA
      • MixtureTree
      • TIGER
      • SeaView
      • Jane
      • GZ-Gamma
      • PAUPRat
      • Archaeopteryx
      • SuiteMSA
      • Crux
      • Ancestor
      • ANC-GENE
      • Bn-Bs
      • HON-new

      (I am just starting to list interpreter code here. Until recently it was listed under Unix, Windows and/or Mac OS X). Until I finish transferring interpreter code here this list will be incomplete, and you will find many programs written in interpreted languages there).

      • PAL
      • Mesquite
      • BIRCH
      • PRAP
      • SeqState
      • TCS
      • IDEA
      • PhyloNet
      • Notung
      • Vanilla
      • NINJA
      • qclust
      • PEBBLE
      • SplitsTree
      • SeqPup
      • DPRML
      • MultiPhyl
      • Treefinder
      • PhyloCoCo
      • ProtTest
      • CoMET
      • Segminator
      • jMODELTEST
      • as Windows executables (not counting executing in a "DOS box"). Programs available as source code which is Windows-specific are listed here. Java executables are also included. (Note that compilers available on Windows systems, particularly the free Cygwin and MinGW compilers, can also be used to compile many of the programs listed above under Unix generic source code). Programs run in interpreted environments such as Perl, Python, R or MATLAB can also be run under Windows if the proper environment is installed. These programs are listed above under Unix.
        • PHYLIP
        • PAUP*
        • TREECON
        • GDA
        • SeqPup
        • MOLPHY
        • GeneDoc
        • COMPONENT
        • TREEMAP
        • COMPARE
        • RAPDistance
        • TreeView
        • Phylodendron
        • POPGENE
        • TFPGA
        • GeneTree
        • MVSP
        • RSTCALC
        • Genetix
        • NJplot
        • unrooted
        • Arlequin
        • DAMBE
        • DnaSP
        • PAML
        • DNASIS
        • MINSPNET
        • BioEdit
        • ProSeq
        • WINCLADA
        • NONA
        • Phylogenetic Independence
        • HY-PHY
        • TreeExplorer
        • Genie
        • MEGA
        • TNT
        • GelCompar II
        • Bionumerics
        • FORESTER
        • Populations
        • T-REX
        • MrBayes
        • EDIBLE
        • Winboot
        • r8s
        • Mesquite
        • Phyledit
        • SYN-TAX
        • PTP
        • DIVA
        • TreeFitter
        • Phylo_win
        • PAST
        • GeneStudio Pro
        • Treefinder
        • PPH
        • MetaPIGA
        • Phyltools
        • MSA
        • Mgenome
        • APE
        • PHASE
        • PHYML
        • YCDMA
        • NSA
        • BEAST
        • Clann
        • Jevtrace
        • MrMTgui
        • MrModeltest
        • SymmeTREE
        • TreeJuxtaposer
        • Network
        • Spectronet
        • Phylogen
        • Phylap
        • Dnatree
        • IMa2
        • ProtTest
        • GEODIS
        • TreeSetViz
        • TreeMe
        • ModelGenerator
        • Simplot
        • PHYLOGR
        • ProfDist
        • START2
        • IQPNNI
        • STC
        • TreeSAAP
        • Swaap
        • Swaap PH
        • TreeGraph 2
        • DIVERGE
        • MESA
        • NimbleTree
        • ArboDraw
        • SPAGeDi
        • CBCAnalyzer
        • DualBrothers
        • PaupUp
        • SSA
        • Multidivtime
        • ParaFit
        • IDC
        • TreeMaker
        • CodonRates
        • BAli-Phy
        • TreeDyn
        • DigTree
        • Geneious
        • Brownie
        • Mac5
        • BayesPhylogenies
        • BayesTraits
        • MrEnt
        • SimpleClade
        • CRANN
        • PATHd8
        • MAFFT
        • GARLI
        • TreeStat
        • FigTree
        • MrBayesPlugin
        • LOBSTER
        • SEMPHY
        • FASTML
        • Rate4Site
        • Quartet Suite
        • Rainbow
        • aLRT
        • McRate
        • HyperTree
        • SWORDS
        • GeoPhyloBuilder
        • Dendroscope
        • Phylocom
        • TOPALi
        • Simprot
        • BEST
        • pcca
        • EREM
        • MBEToolbox
        • DTscore
        • EEEP
        • LEVEL2
        • PSODA
        • PhyloSort
        • RAxML
        • MUSCLE
        • CTree
        • PRAP
        • Leaphy
        • GRate
        • SLR
        • rRNA phylogeny
        • FAMD
        • AxParafit
        • DTscore
        • PROCOV
        • DART
        • EEEP
        • CONSERVE
        • DAWG
        • EvolveAGene3
        • Bosque
        • TreeToy
        • TreeSnatcher Plus
        • GAME
        • TreeFit
        • FastTree
        • PhyloWidget
        • tracer
        • Murka
        • MANTiS
        • PC-ORD
        • GenGIS
        • Bio++
        • S-DIVA
        • UGENE
        • Phybase
        • ETE
        • Cactus-Pie
        • PHYDIT
        • POPTREE2
        • RDP3
        • PhyRe
        • Segminator
        • iGTP
        • Recodon
        • NetRecodon
        • CoRe-PA
        • TIGER
        • SeaView
        • Jane
        • TIMER
        • HON-new
        • PHYLIP
        • PAUP*
        • MEGA
        • Hennig86
        • MEGA
        • RA
        • NONA
        • TREECON
        • Microsat
        • DISPAN
        • RESTSITE
        • NTSYSpc
        • METREE
        • PHYLTEST
        • RAPDistance
        • DIPLOMO
        • TREE-PUZZLE
        • ClustalW
        • MALIGN
        • GeneDoc
        • Random Cladistics
        • POPTREE2
        • GEOMETRY
        • PDAP
        • PICA
        • REDCON
        • TAXEQ3
        • BIONJ
        • ANCML
        • REAP
        • MVSP
        • Lintre
        • T-REX
        • sendbs
        • weighbor
        • POY
        • TreeDis
        • Network
        • Gambit
        • CONSEL
        • LVB
        • FSTAT
        • SYN-TAX
        • FastME
        • MSA
        • QDate
        • Robinson and Foulds distance
        • DIVAGE
        • BPAnalysis
        • TreeScan
        • Genepop
        • Kakusan4
        • DISTREE
        • GZ-Gamma
        • PAUPRat
        • Statio
        • Ancestor
        • ANC-GENE
        • Bn-Bs
        • PHYLIP
        • PAUP*
        • MacT
        • SeqPup
        • Microsat
        • TREE-PUZZLE
        • fastDNAml
        • MacClade
        • Spectrum
        • AutoDecay
        • CAFCA
        • ClustalW
        • TREEMAP
        • CAIC
        • COMPARE
        • Seq-Gen
        • CONSERVE
        • TreeView
        • NJplot
        • DendroMaker
        • MUST
        • DNA Stacks
        • Phylogenetic Investigator
        • Tree Draw Deck
        • Phylodendron
        • TreeRot
        • Treevolve and PTreevolve
        • PSeq-Gen
        • BIONJ
        • GCUA
        • GeneTree
        • QDate
        • LVB
        • T-REX
        • unrooted
        • COMPONENT Lite
        • weighbor
        • Modeltest
        • PAML
        • Willson quartets programs
        • ALIGN
        • CodonBootstrap
        • DNASIS
        • PLATO
        • MacroCAIC
        • RadCon
        • TreeEdit
        • Arlequin
        • HY-PHY
        • TreeThief
        • Genie
        • MrBayes
        • FORESTER
        • r8s
        • GDA
        • Mesquite
        • SYN-TAX
        • DIVA
        • TreeFitter
        • Phylo_win
        • Treefinder
        • PPH
        • MetaPIGA
        • MSA
        • PHYML
        • BEAST
        • Robinson and Foulds distance
        • Clann
        • Jevtrace
        • MrModeltest
        • BootPHYML
        • SymmeTREE
        • TreeJuxtaposer
        • MacVector
        • SIMMAP
        • TNT
        • Phylogen
        • Rhino
        • TipDate
        • Phylap
        • Dnatree
        • ProtTest
        • GEODIS
        • TreeScan
        • TreeSetViz
        • ModelGenerator
        • PHYLOGR
        • ProfDist
        • IQPNNI
        • TreeSAAP
        • Permute!
        • MESA
        • SGRunner
        • DualBrothers
        • Cadence
        • ParaFit
        • TreeMaker
        • BAli-Phy
        • Supertree
        • TreeDyn
        • Geneious
        • Brownie
        • Mac5
        • BayesPhylogenies
        • BayesTraits
        • Paloverde
        • CRANN
        • MAPPS
        • PATHd8
        • MAFFT
        • GARLI
        • TreeStat
        • FigTree
        • MrBayesPlugin
        • SEMPHY
        • Quartet Suite
        • Rainbow
        • HyperTree
        • Kakusan4
        • SWORDS
        • Dendroscope
        • Phylocom
        • PhySIC_IST
        • TOPALi
        • BEST
        • pcca
        • indel-Seq-Gen
        • PhyloCoCo
        • LEVEL2
        • PSODA
        • PhyloSort
        • RAxML
        • MUSCLE
        • CTree
        • PRAP
        • SLR
        • AxParafit
        • EvolveAGene3
        • TreeToy
        • TreeSnatcher Plus
        • GAME
        • GenoDive
        • PhyloWidget
        • tracer
        • MANTiS
        • GenGIS
        • Bio++
        • UGENE
        • Phybase
        • ETE
        • PyCogent
        • DendroPy
        • NEPAL
        • Bosque
        • TreeGraph 2
        • Segminator
        • iGTP
        • Bio::Phylo
        • Recodon
        • Lagrange
        • NetRecodon
        • CoRe-PA
        • TIGER
        • SeaView
        • Jane
        • PAUPRat
        • SuiteMSA

        A nalyzing particular types of data

        Here you will find lists of programs that analyze types of data other than molecular sequence data. We will gradually expand this list of data types.

        • RSTCALC
        • POPTREE2
        • Microsat
        • Populations
        • MSA
        • YCDMA
        • Network
        • IMa2
        • Arlequin
        • tfpga
        • RAPDistance
        • GelCompar II
        • Bionumerics
        • Winboot
        • REAP
        • RESTSITE
        • MVSP
        • DENDRON
        • Phyltools
        • Network
        • BIRCH
        • FAMD
        • EMBOSS
        • PHYLIP
        • MacClade
        • Mesquite
        • ANCML
        • COMPARE
        • PDAP
        • Phylogenetic Independence
        • APE
        • CAIC
        • TreeScan
        • PHYLOGR
        • IDC
        • CoMET
        • OUCH
        • Brownie
        • BayesTraits
        • TNT
        • PHYSIG
        • Cactus-Pie
        • Phylocom
        • pcca
        • EMBOSS
        • Permute
        • SIMMAP
        • SLOUCH
        • PC-ORD
        • PHYLIP
        • DAMBE
        • Freqpars
        • DISPAN
        • GDA
        • POPGENE
        • YCDMA
        • FSTAT
        • Arlequin
        • DnaSP
        • APE
        • DIVAGE
        • POPTREE2
        • Genepop
        • SPAGeDi
        • GenoDive
        • TreeFit
        • EMBOSS

        (under construction: more coming soon)

        Here are the packages that have most recently been added to these listings: (the most recent ones first). Entries are retained in this list for 6 months. Note also below the "waiting list" area listing programs that are to be added. You can use the submission form here to submit new entries.

        • (List is currently empty because I have been unable to do much updating owing to other pressures so no new packages have been added in the last year).

        Here are the packages whose entries have most recently been changed: The date on which each change was entered is shown. Entries are retained in this list for 6 months. (Note that changes may be as small as updated version numbers or a modified web address). The most recent changes are first.

        O ther lists of phylogeny software

        • There is one phylogeny software list even more complete and up-to-date than this one: a more recent version of this list. If you are reading this on the web pages at our server evolution.gs.washington.edu , you are reading the most up-to-date version. But if you are reading a version stored anywhere else, you might want to look here instead.
        • Sergios-Orestis Kolokotronis has posted an extensive table of phylogeny programs at his site at the American Museum of Natural History, and near it are others under headings such as "molecular evolution" and "alignment".
        • Wikipedia has a good list of sequence alignment software (including both tree-based and non-tree-based alignment methods) here at http://en.wikipedia.org/wiki/List_of_sequence_alignment_software
        • David Robertson of the Bioinformatics Education and Research at the University of Manchester, England, maintains a very informative web site at listing programs and their web sites that test for the presence of recombination or hybridization events in DNA sequence data. It lists some programs that are covered here, and others that are outside the scope of these web pages. That site is located at http://bioinf.man.ac.uk/robertson/recombination/programs.shtml .
        • Mike Robeson at the University of Colorado maintains a page with multiple programs listed as Bioinformatics software for Mac OS X.
        • The Bioinformatics Organization, a nonprofit group in Hudson, Massachusetts, has posted the bioinformatics.org web pages. These offer a free membership and host open source software projects in bioinformatics. They also have a Molecular Linux listing of Linux programs to carry out bioinformatics tasks, which can be sorted by keywords.
        • On Wikipedia there is a List of phylogenetic tree visualization software at http://en.wikipedia.org/wiki/List_of_phylogenetic_tree_visualization_software
        • The University of California Museum of Paleontology page of Phylogenetics Software Resources at http://www.ucmp.berkeley.edu/subway/phylo/phylosoft.html . A few programs are listed, but there is a very nice list of software lists there.
        • Andrea Ramge, of Biomax Informatics AG, Martinsried, Germany has created the bioinformatik.de index of resources. It includes a list of software located at http://www.bioinformatik.de/cgi-bin/browse/Catalog/Software . The phylogeny programs listings there are located within the categories for different operating systems. The phylogeny software is under "Phylogenetic Analysis" within each operating system.
        • Richard Christen at the Université de Nice, France, has a list of Tree and Tree-software for visualisation and manipulations dealing with phylogenetic trees at http://bioinfo.unice.fr/biodiv/Tree_editors.html
        • Silvio Nihei at the University of São Paulo in Brazil has produced a list: Programas para Filogenia in Portugese. It concentrates on a small number of programs that mostly use parsimony methods.

        N ew programs waiting to be added

        This is a "waiting list" showing links to the web pages of many new phylogeny programs, which I have not yet had time to add to the main listing. They will be listed there, with a single web link and no detailed explanation. I hope that this list will gradually shrink as the new programs are put into the main listing. You can use the submission form here to submit new entries.

        These are waiting to be added:

        • ADAPTSITE, intended to estimate positive and negative selection at a single amino acid site.
        • PhyRe infers adequacy of taxon sampling for phylogenetic studies.
        • phylobase is an R package that contains a class of functions for comparative methods, incorporating one or more trees and trait data.
        • PhyML-mixtures, a PhyML version for mixture of amino acid models (EX2, EX3, EHO, UL2, and UL3).
        • PhyD*, Fast NJ-like algorithms to deal with incomplete distance matrices.
        • SDM a fast distance-based approach for tree and supertree building in phylogenomics.
        • SSIMUL does speciation signal extraction from multigene families.
        • Clearcut carries out Relaxed Neighbor Joining (RNJ), a faster NJ-like distance method.
        • MP-EST (also described here) uses trees from different loci to infer a species tree by a pseudo-maximum-likelihood method.
        • TreeRogue, an R script for getting trees from published figures of them.
        • Serial NetEvolve simulation program evolves serially-sampled sequences with or without recombination.
        • Rococo reconstructs ancestral gene clusters for a multigene family on a given tree.
        • (27 May 2012) Adding one entry from the Waiting List each week, have caught up with submissions submitted through the web form, and am populating a new column in the cross-referenced table, one for multiplatform interpreted code such as Java, Perl, Python, R, and MatLab. The Java programs are entered in that column. After this I will put the others in it, then go back to the main Phylogeny Programs front web page and put in a software category for these interpreters. If you have a new program, or an old one that I don't list, don't wait for me to find it by myself -- I still don't have time to, so use the web submission form.
        • (19 March 2012) Well, I should have known that another quarter of teaching lay ahead. Now that is done and I should make gradual progress over the next two quarters.
        • (23 December 2011) Once again I got stalled by heavy teaching. Now resuming again and hope to gradually catch up. One puzzle is how to handle R packages. There are a great many of them, and most are not listed here yet. It simply is too much work for me to track them all down, figure out their features, and make an entry for each one. So I will put in only those whose authors use our submission form to help create the entry.
        • (20 August 2011) I have resumed adding new submissions that people sent in using our software submission forms -- there are about 10 waiting, some having waited for over 6 months. Apologies for that, I was busy teaching and desperately trying to write up old results. I hope to gradually add all 10 over the next month or so, one at a time.
        • (17 December 2010) I have started (on this 107th anniversary of the Wright Brothers' famous first flight) this News section of the page. The current status is that I have completed (over the past 2-3 years) a complete pass through the listings, updating them. However of course some may have become outdated since then. Ahead is adding new entries, of which I expect there to be 30-40. I am caught up on entries that were submitted by the web submission form.
        • (19 December 2010) I have finished adding the ones that were already in our Waiting List. Now to take some of the approximately 40 leads that I have accumulated and put entries for the relevant ones into the Waiting List.
        • (19 June 2014) Things have been stalled for some years but now I am gradually (and slowly) resuming adding and correcting entries. Please keep using the software submission form, and please be patient. I was stalled owing to needing to write grants, and owing to not getting them so I now have no programming assistance. Progress to being current will be slow. If you are impatient, how about volunteering to help? We could set up some web site accessible to a team.

        M ysteries you can help us solve

        • 3item extracts 3-item statements from "areagrams", whatever that means, but can only be accessed by joining their Yahoo group. So I don't really know what it does.
        • Dependency v2.1 uses Multiple Interdependency to detect functional interactions between amino acids in proteins. Does not seem to actually use a phylogeny.
        • Codep Maximizes co-evolutionary interdependencies to discover interacting proteins. Also does not seem to actually use a phylogeny.
        • PhyloGrapher shows clustering relationships between genes in a genome based on a distance matrix. But is it a phylogeny program?
        • Phylosopher commercial package for functional genomics said to include some phylogeny functions. Does it?
        • Phylogenator server displaying aligned sequences -- does it actually use or construct phylogenies?
        • MultiLocus calculates multiple-locus measures of population differentiation from population genetic data. But unless someone can show me that it can calculate a measure of distance between two populations within a data set, it does not seem appropriate for this list.
        • CIPRES-KEPLER Java-based framework for organizing workflow and submitting jobs. I am not sure whether any specifically phylogeny-based pieces have yet been supplied with this.

        Notices added in compliance with University of Washington requirements for web sites hosted at the University: Privacy Terms


        Unit 1 – Fundamental Biology Skills and Knowledge

        • Matter
        • Water Is Essential
        • Cohesion and Adhesion
        • Density of Water
        • The Universal Solvent
        • pH and Living Organisms
        • Carbon
        • Important Biological Functional Groups
        • Root Words, Prefixes and Suffixes

        Unit 2 – Cells: Structure and Function

        • Prokaryotic and Eukaryotic Cells—Similarities and Differences
        • Eukaryotic Organelles—A Detailed Look
        • Cytoskeleton
        • Cellular Membranes—Phospholipid Bilayer
        • Cellular Membranes—Membrane Proteins
        • Passive Transport
        • Active Transport
        • Exocytosis and Endocytosis
        • Cellular Communication
        • Neurons and Cell Signaling
        • Relationship of Surface Area to Volume

        Unit 3 – The Cell Cycle

        • Cell Cycle Phases
        • Chromosomes
        • Mitotic Phase
        • The Five Stages of Mitosis
        • Prokaryotes and Cell Division Evolution
        • Cell Cycle Control Systems
        • The Loss of Cell Cycle Control
        • Gene Expression and Cell Types

        Unit 4 – Meiosis: Heredity and Variation

        • Heredity
        • Haploid and Diploid Cells
        • Human Life Cycle
        • Meiosis
        • Phases of Meiosis
        • Mitosis vs. Meiosis—Similarities and Differences
        • Genetic Variation and Contribution to Evolution

        Unit 5 – Mendelian and Molecular Genetics

        • Inheritance
        • Mendelian Genetics
        • DNA Structure
        • DNA Replication
        • Mutations
        • DNA Repair Mechanisms
        • Gene to Protein
        • Transcription
        • Translation

        Unit 6 – Evidence of Evolution

        • The Geologic Timeline
        • Absolute Radiometric Dating
        • Relative Dating
        • Fossil Record
        • Anatomical Structures and Molecular Evidence
        • Case Study—Deciphering Whale Evolution
        • Life History
        • Comparing Classical and Modern Classification
        • Direct Observations of Evolution

        Unit 7 – Evolution: Natural Selection

        • Conditions for Natural Selection
        • Genetic Variation
        • Sources of Genetic Variation
        • Overproduction of Offspring
        • Struggle for Existence and Differential Survival and Reproduction
        • Sexual Selection
        • Artificial Selection

        Unit 8 – Evolution: Populations

        • Microevolution in Populations
        • Hardy-Weinberg Equilibrium Conditions
        • Hardy-Weinberg Equation
        • Adaptive Evolution or Chance?
        • Genetic Drift
        • Changes in Allele Frequencies within a Generation
        • Analyzing the Evolution of Multigene Traits
        • Speciation
        • Ecological Definition of a Species
        • Case Study—Spotted Owls and Barred Owls

        Unit 9 – Interdependence in Ecosystems

        • Components of an Ecosystem
        • Climate
        • Abiotic Factors in Local Ecosystems
        • Ecological Hierarchy
        • Interactions Between Species
        • Predation and Herbivory
        • Symbiosis
        • Competition
        • Facilitation
        • Ecosystem Stability and Disturbance
        • Case Study—Fire in Western United States Pine Forests
        • Population Dynamics
        • Counting Populations to Determine Ecosystem Health

        Unit 10 – Ecology: Energy Flow and Nutrient Cycling

        • Elemental Components of Living Things
        • Matter Moves in Cycles
        • The Nitrogen Cycle
        • The Carbon Cycle
        • Photosynthesis: The Light Reactions
        • Photosynthesis: The Calvin Cycle
        • Respiration
        • Energy Transfer between Trophic Levels
        • Bioaccumulation and Biomagnification of Toxins
        • Case Study—Orcas in Puget Sound and PCBs

        Unit 11 – Biochemistry

        • Types of Macromolecules
        • Monomers and Polymers
        • Carbohydrates
        • Lipids
        • Protein Structure
        • Protein Function
        • Enzyme Structure and Function
        • Measuring and Predicting Enzyme Activity
        • Case Study—Pepsin and Lipase in the Digestive System

        Unit 12 – Energy and Metabolism

        • Free Energy in Living Systems
        • Endergonic and Exergonic Reactions
        • Free Energy Utilization and Availability
        • The First Law of Thermodynamics in Living Systems
        • The Second Law of Thermodynamics
        • The Role of ATP in Cells
        • Introduction to Cellular Respiration
        • Electron Carriers
        • Glycolysis
        • The Krebs Cycle
        • Chemiosmosis, Electron Transport and Oxidative Phosphorylation
        • Fermentation

        Unit 13 – Organismal Regulation

        • Homeostasis
        • Negative Feedback
        • Temperature Control and Evolution
        • Positive Feedback Loop
        • Neurons and Homeostasis
        • Integration of Body Systems with the Nervous System and Endocrine System
        • Osmoregulation
        • Osmoregulation in Animals
        • Osmoregulation in Plants A

        Unit 14 – Gene Regulation and Cell Communication

        • Gene Regulation Overview
        • Gene Regulation in Protein Synthesis
        • Evidence of Evolution through Gene Regulation Mechanisms
        • Discovering Prokaryotic Gene Regulation
        • The Iac Operon
        • Repressible Operons
        • Eukaryotic Gene Regulation Introduction
        • Gene Regulation through Histone Modification
        • Gene Regulation through Transcription Factors
        • Gene Regulation through RNA Modification
        • Regulation of Gene Expression through Phosphorylation of Proteins
        • Summary of Regulation Pathways
        • Summary of Eukaryotic Gene Expression
        • Cell Communication in Multicellular Eukaryotes
        • G-protein Coupled Receptors
        • Receptor Tyrosine Kinases
        • Case Study—Quorum Sensing in Bacteria

        Unit 15 – The Immune Response

        • Immune Responses of Plants
        • Immune Responses in Animals
        • Nonspecific Immune Responses
        • Specific Immune Response in Vertebrates
        • Specific Immune Response in Prokaryotes
        • Biotechnology and Immunity
        • Allergies and Immune System Malfunction
        • Autoimmune Disease
        • Case Study—Type 1 Diabetes

        Can we predict temperature-sensitive changes in enzyme function from sequence alone?

        A great deal of effort is necessary to accomplish the type of research described above associating functional changes in enzymes with their underlying structural modifications. Typically, the workflow involves measurement of enzyme kinetics across a range of temperatures from purified enzyme or tissue homogenates, sequencing of cDNA of each ortholog to identify differences in amino acid sequence, site-directed mutagenesis and expression of recombinant protein, and further kinetics assays to confirm that candidate amino acid substitutions indeed are responsible for the differences in function that have been ascribed to them. The process can be time consuming, technically challenging and expensive. Thus, a valuable addition to research on enzyme adaptation to temperature would be an in silico approach that would allow us to predict whether amino acid substitutions between enzyme orthologs of two species adapted to different temperatures lead to the expected direction and magnitude of change in a functionally important attribute like ligand binding affinity. Such a predictive capacity might allow in silico screening for adaptive change across the proteome.

        In the past 10 years, a number of algorithms have been developed that may have the potential to allow these types of predictions. These algorithms are designed to assess how specified amino acid substitutions will affect global protein stability, specifically by estimating the Gibbs free energy change as the protein transitions from the unfolded to the folded state (ΔGf) – a process that should be energetically favorable (because the folded state is more stable than the unfolded state under physiological conditions), leading to a negative ΔGf value. These calculations are based on a set of rules determining thermodynamic changes expected as a specified amino acid sequence folds, and can use sequence data alone or incorporate information on the three-dimensional structure of the protein. When a protein with a particular amino acid at position X is compared with the same protein with a new amino acid at that position, two ΔGf values can be estimated, one for the ‘wild-type’ and one for the ‘mutant’ protein, and the difference, ΔΔG, will indicate whether the amino acid substitution is predicted to stabilize or destabilize the folded protein. When the mutant is stabilized relative to the wild-type, the mutant ΔGf will have a negative value of greater magnitude than the ΔGf of the wild-type, resulting in a positive ΔΔG value.

        The studies described above focusing on temperature adaptation in A4-LDHs and cMDHs provide an excellent opportunity to test the usefulness of these protein stability prediction (PSP) algorithms in assessing enzyme adaptation to small differences in habitat temperature. Thus, we can compare six independent examples of one-amino-acid changes associated with small but physiologically significant changes in enzyme function (ligand affinity): in A4-LDH the substitutions (in the cold→warm direction) are N8D (Sphyraena), E233M and Q317V (notothenioids) and T219A (Chromis) in cMDH the substitutions are V114N (Mytilus) and G291S (Lottia).


        Structure, Function, and Evolution of Coronavirus Spike Proteins

        The coronavirus spike protein is a multifunctional molecular machine that mediates coronavirus entry into host cells. It first binds to a receptor on the host cell surface through its S1 subunit and then fuses viral and host membranes through its S2 subunit. Two domains in S1 from different coronaviruses recognize a variety of host receptors, leading to viral attachment. The spike protein exists in two structurally distinct conformations, prefusion and postfusion. The transition from prefusion to postfusion conformation of the spike protein must be triggered, leading to membrane fusion. This article reviews current knowledge about the structures and functions of coronavirus spike proteins, illustrating how the two S1 domains recognize different receptors and how the spike proteins are regulated to undergo conformational transitions. I further discuss the evolution of these two critical functions of coronavirus spike proteins, receptor recognition and membrane fusion, in the context of the corresponding functions from other viruses and host cells.


        Delivery of Nitric Oxide and the Enzymatic Activities of Hemoglobin and Myoglobin

        Nitric oxide (NO) is a gas that acts also as a neurotransmitter in the nervous system and as a second messenger in various signaling systems. Red blood cells make up the body’s largest intravascular reservoir of NO, and Hgb is indispensable to its formation, storage and release. In the vascular system NO is an important potent local vasodilator synthesized by the endothelium of arterioles. It binds to its receptor on smooth muscle cells surrounding arterioles and brings about relaxation allowing greater blood flow. This facilitates the transfer of O2 from Hgb to the tissues. Nitric oxide has a very short half-life (1–5 seconds) because it is destroyed rapidly. However, its lifespan can be greatly increased minutes to hours by binding it to Hgb and/or small sulfur-containing compounds in the blood such as glutathione. It is also a free radical and thus potentially toxic to cells.

        Nitric oxide binds to the iron in the heme of Hgb with much greater affinity than O2 (approximately 10,000X greater!). Nitric oxide can form a stable bond to the heme-iron only when Hgb is in the deoxy-T state because in the oxy-R state NO could be rapidly oxidized to NO3 - . The interaction between Hgb and NO is, then, controlled by the transition of Hgb from the oxy-R state to the deoxy-T state. When in the tissues, as O2 is released it leaves the heme-iron available to bind NO. A strategically placed Cys faces the surface of Hgb where it can easily transfer a bound NO to glutathione for delivery to the smooth muscle. Returning to the lungs O2 begins to bind to Hgb and CO2 and H + leave causing it to convert to the oxy-R state. This shift now places the crucial Cys close to the heme-iron. At this point the NO on the heme-iron is transferred to the Cys. This leaves the heme-iron vacant to accept an O2. Upon return to the tissues O2 is released and Hgb converts back to the deoxy-T state. The Cys with its bound NO is back on the surface and NO is released to certain membrane proteins of the RBC where it is then transferred to glutathione for transfer to the smooth muscle cells. Thus, we see that the binding, transport and release of NO is dependent on the ability of Hgb to transition between the R- and T-states. A transition only made possible by the specifically designed subunit structure of Hgb.

        In addition to its ability to transport O2 from the lungs to the tissues and H + and CO2 from the tissues to the lungs, Hgb has two often overlooked enzymatic activities: nitric oxide dioxygenase and nitrite reductase. These two activities are, however, dependent upon whether the molecule is in the R- or T-state. Thus, these activities depend on the ability of Hgb to change its conformation. Under normal conditions when O2 is plentiful, oxygenated Hgb, in the R state, acts as a nitric oxide dioxygenase by adding its bound O2 to the NO to generate a non-toxic nitrate ion (NO3 - ). In the process, however, methemoglobin is generated, but as stated above methemoglobin reductase acts to regenerate the +2 oxidation state.

        Under hypoxic (low O2) conditions Hgb, along with Mb, plays a protective role in suppressing the production of superoxide radicals by the mitochondria. Tissues subjected to hypoxic conditions suffer from greater tissue damage when O2 levels are restored. Under these conditions, mitochondria generate more superoxide radicals than normal. Hemoglobin exhibits the nitrite reductase activity only when in the deoxy-T state. The reductase activity synthesizes NO from ever-present nitrite ions (NO2-). The new NO increases O2 delivery by causing relaxation of the smooth muscle cells of arterioles and increasing blood flow and it also acts to suppress the production of radicals by the electron transport chain in the mitochondria thus reducing tissue damage when O2 delivery is resumed.


        Denaturing

        What happens when you drop an egg into a hot frying pan? No - apart from spit fat at you!? It changes colour - this is an example of proteins denaturing. All through this hub it has been made clear that a proteins&apos shape (determined by its&apos primary structure, in turn determined by DNA sequences) is vital to its function - but this shape can be distorted.

        Heating a protein increases the kinetic energy in the molecule (scientific term for movement energy). This can literally shake the delicate structure of the protein to pieces - remember, the bonds holding this structure in place are not covalent bonds, each one is quite weak. If so much heat is applied that the whole tertiary structure unravels, the protein is said to have been denatured. This is a one-way ticket: once an enzyme has been denatured, you cannot reform the original complex structure - even if you cool it again.

        Heat is not the only thing that destroys proteins. Enzymes are perfectly suited to specific pH conditions. Enzymes working in the stomach can only work in acidic pH - if you put them in neutral, or in alkaline pH, they will denature. Enzymes in the intestine are optimised for alkaline conditions - place them in acidic or neutral conditions and they will denature.


        Watch the video: Σπιτική Μπάρα Πρωτεΐνης ΜΟΝΟ η μπάρα (May 2022).