David C. Teller

“Homology” in proteins and nucleic acids: A terminology muddle and a way out of it

“Homology” has the precise meaning in biology of “having a common evolutionary origin,” but it also carries the loose meaning of “possessing similarity or being matched.” Its rampant use in the loose sense is clogging the literature on protein and nucleic acid sequence comparisons with muddy writing and, in some cases, muddy thinking In its precise biological meaning, “homology” is a concept of quality. The word asserts a type of relationship between two or more things. Thus, amino acid or nucleotide sequences are either homologous or they are not. They cannot exhibit a particular “level of homology” or “percent homology.” Instead, two sequences possess a certain level of similarity. Similarity is thus a quantitative property. Homologous proteins or nucleic acid segments can range from highly similar to not recognizably similar (where similarity has disappeared through divergent evolution). If using “homology” loosely did not interfere with our thinking about evolutionary relationships, the way in which we use the term would be a rather unimportant semantic issue. The fact is, however, that loose usage in sequence comparison papers often makes it difficult to know the authors intent and can lead to confusion for the reader (and even for the author). There are three common situations in which hazards arise by using “homology” to mean similarity. The first case is the most obvious offense but perhaps the least troublesome. Here an author identifies sequence similarities (calling them homologies) but claims that the sequences being compared are not evolutionarily related. Some awkward moments occur in such a paper, since the author claims both homology (i.e., similarity) and nonhomology (i.e., lack of a common ancestor). Nonetheless, the author’s ideas are likely to be clear since arguments against common ancestry are presented explicitly. A second case is one in which an author points out similarities (again called homologies) but does not address the issue of evolutionary origins. The reader, seeing the term “homology,” may infer that the author is postulating coancestry when that is not the authors intent. The final case occurs most frequently and is the most subtle and therefore most troublesome. Here, similarities (called homologies) are used to support a hypothesis of evolutionary homology. In this case, the two meanings of homology seem to overlap, and it is almost inevitable that the thinking of author and reader alike will be intrusively distorted as follows. Similarity is relatively straightforward to document. In comparing sequences, a similarity can take the form of a numerical score (O/o amino acid or nucleotide positional identity, in the simplest approach) or of a probability associated with such a score. In comparisons of three-dimensional structures, a typical numerical description is root-mean-square positional deviation between compared atomic positions. A similarity, then, can become a fully documented, simple fact. On the other hand, a common evolutionary origin must usually remain a hypothesis, supported by a set of arguments that might include sequence or three-dimensional similarity. Not all similarity connotes homology but that can be easily overlooked if similarities are called homologies. Thus, in this third case, we can deceive ourselves into thinking we have proved something substantial (evolutionary homology) when, in actuality, we have merely established a simple fact (a similarity, mislabeled as homology). Homology among similar structures is a hypothesis that may be correct or mistaken, but a similarity itself is a fact, however it is interpreted. We believe that the concepts of evolutionary homology and sequence or three-dimensional similarity can be kept distinct only if they are referred to with different words. We therefore offer the following recommendations: *Sequence similarities (or other types of similarity) should simply be called similarities. They should be documented by appropriate statistical analysis. In writing about sequence similarities the following sorts of terms might be used: a level or degree of similarity; an alignment with optimized similarity; the % positional identity in an alignment; the probability associated with an alignment. *Homology should mean “possessing a common evolutionary origin” and in the vast majority of reports should have no other meaning. Evidence for evolutionary homology should be explicitly laid out, making it clear that the proposed relationship is based on the level of observed similarity, the statistical significance of the similarity, and possibly other lines of reasoning. One could argue that the meaning of the term “homology” is itself evolving. But if that evolution is toward vagueness and if it results in making our scientific discourse unclear, surely we should intervene. With a collective decision to mend our ways, proper usage would soon become fashionable and therefore easy. We believe that we and our scientific heirs would benefit significantly.

Crystal structure of a 30 kDa C-terminal fragment from the γ chain of human fibrinogen

Abstract Background: Blood coagulation occurs by a cascade of zymogen activation resulting from minor proteolysis. The final stage of coagulation involves thrombin generation and limited proteolysis of fibrinogen to give spontaneously polymerizing fibrin. The resulting fibrin network is covalently crosslinked by factor XIIIa to yield a stable blood clot. Fibrinogen is a 340 kDa glycoprotein composed of six polypeptide chains, ( α β γ ) 2 , held together by 29 disulfide bonds. The globular C terminus of the γ chain contains a fibrin-polymerization surface, the principal factor XIIIa crosslinking site, the platelet receptor recognition site, and a calcium-binding site. Structural information on this domain should thus prove helpful in understanding clot formation. Results: The X-ray crystallographic structure of the 30 kDa globular C terminus of the γ chain of human fibrinogen has been determined in one crystal form using multiple isomorphous replacement methods. The refined coordinates were used to solve the structure in two more crystal forms by molecular replacement; the crystal structures have been refined against diffraction data to either 2.5 A or 2.1 A resolution. Three domains were identified in the structure, including a C-terminal fibrin-polymerization domain (P), which contains a single calcium-binding site and a deep binding pocket that provides the polymerization surface. The overall structure has a pronounced dipole moment, and the C-terminal residues appear highly flexible. Conclusions: The polymerization domain in the γ chain is the most variable among a family of fibrinogen-related proteins and contains many acidic residues. These residues contribute to the molecular dipole moment in the structure, which may allow electrostatic steering to guide the alignment of fibrin monomers during the polymerization process. The flexibility of the C-terminal residues, which contain one of the factor XIIIa crosslinking sites and the platelet receptor recognition site, may be important in the function of this domain.

Prediction of peptide retention times in reversed-phases high-performance liquid chromatography during linear gradient elution

Abstract The retention behavior of 100 peptides was studied during high-performance liquid chromatography on a C18 column using aqueous trifluoroacetic acid as the mobile phase and acetonitrile as the mobile phase modifier in a linear gradient elution system. Retention times of the peptides were linearly related to the logarithm of the sum of Rekkers constants (R.F. Rekker, The Hydrophobic Fragmental Constant, Elsevier, Amsterdam, 1977, p. 301) for the constituent amino acid. Assuming this relationship, the best fit constants for this system were computed by non-linear multiple regression analysis. Using the new constants, it is possible to predict retention times for a wide variety of peptides at any slope of linear gradient, if the amino acid composition is known. It also enables accurate prediction of the retention time of peptides, whose amino acid composition in not known, after an analytical run with an alternate gradient.

The phylogeny of trypsin-related serine proteases and their zymogens. New methods for the investigation of distant evolutionary relationships

Abstract The sequence of all presently known trypsin-related serine proteases and their zymogens of animal and bacterial origin were optimally aligned on the basis of three different scoring schemes for amino acid comparisons. Sequence homology was found to extend into the activation peptides. The gaps resulting from the alignment of the sequences of the active enzymes formed the basis for a new procedure based on position and number of gaps, which allowed the correct topology of the evolutionary relationship of thrombin and the pancreatic enzymes trypsin, chymotrypsin and elastase to be determined. The procedure was applied in an analogous manner to changes in disulfide bridges as well as to a selected set of amino acid positions. Evolutionary distances between proteins were estimated by minimum, base differences as well as according to the stochastic model of evolution . These distances were used successfully to find the best topology of evolutionary relationships. The fact that the branch lengths in evolutionary trees were less affected by the number of sequences considered when evolutionary distances between contemporary sequences were measured in minimum base differences than when measured according to the stochastic model of evolution, suggested in our specific case, that minimum base differences yielded estimates of evolutionary distance closer to reality than the stochastic model of evolution. All these techniques combined yielded the following picture for the evolution of the four protease families. Prothrombin and the zymogens of the pancreatic serine proteases had a common ancestor with tryptic specificity. After the initial divergence, the gene for trypsinogen duplicated. Evidence was found that the duplicated gene underwent drastic changes for a short period of time to become eventually the common ancestor of chymotrypsin and elastase. The phylogenetic tree elaborated for these enzyme families and the methods introduced to determine its topology, should readily allow determination of the attachment site of branches leading to newly sequenced serine proteases, provided their amino acid sequence can be aligned fairly unambiguously. In addition, the consequences of the alignment of the different serine proteases for the relationship of zymogen to enzyme are discussed.

[8] The translational friction coefficient of proteins

Publisher Summary This chapter discusses the translational friction coefficient of proteins. It presents a semiempirical method for calculating the geometrical arrangement of subunits in oligomeric proteins. It also presents a method to calculate friction coefficients of proteins from atomic coordinates. In the chapter, the theory by which friction properties of objects can be calculated is discussed and the mechanics of such calculations are illustrated. The method for finding the principle axes of translation of a particle is provided in the chapter. Using the rigorous theory on protein atoms alone yields friction coefficients that are less than the observed values. Calculations based on the complete test sphere shell gives values greater than observed for proteins. Placing test spheres only on charged groups and computing the friction coefficients based on these test spheres and surface protein atoms yield values essentially in agreement with experimental values. Considering that a rigorous theory has been used and that charged groups are recognized to be hydrated, it appears legitimate to equate test spheres in this case with water of hydration. Thus, the frictional behavior of proteins is determined by several factors: overall dimensions, rugosity of the surface, and the hydration of charged groups on the surface.

Ligand channeling within a G-protein-coupled receptor: The entry and exit of retinals in native opsin

Deactivation of light-activated rhodopsin (metarhodopsin II) involves, after rhodopsin kinase and arrestin interactions, the hydrolysis of the covalent bond of all-trans-retinal to the apoprotein. Although the long-lived storage form metarhodopsin III is transiently formed, all-trans-retinal is eventually released from the active site. Here we address the question of whether the release results in a retinal that is freely diffusible in the lipid phase of the photoreceptor membrane. The release reaction is accompanied by an increase in intrinsic protein fluorescence (release signal), which arises from the relief of the fluorescence quenching imposed by the retinal in the active site. An analogous fluorescence decrease (uptake signal) was evoked by exogenous retinoids when they non-covalently bound to native opsin membranes. Uptake of 11-cis-retinal was faster than formation of the retinylidene linkage to the apoprotein. Endogenous all-trans-retinal released from the active site during metarhodopsin II decay did not generate the uptake signal. The data show that in addition to the retinylidene pocket (site I) there are two other retinoidbinding sites within opsin. Site II involved in the uptake signal is an entrance site, while the exit site (site III) is occupied when retinal remains bound after its release from site I. Support for a retinal channeling mechanism comes from the rhodopsin crystal structure, which unveiled two putative hydrophobic binding sites. This mechanism enables a unidirectional process for the release of photoisomerized chromophore and the uptake of newly synthesized 11-cis-retinal for the regeneration of rhodopsin.

Transglutaminase 1 Mutations in Autosomal Recessive Congenital Ichthyosis: Private and Recurrent Mutations in an Isolated Population

Autosomal recessive congenital ichthyosis (ARCI) is a rare, heterogenous keratinization disorder of the skin, classically divided into two clinical subtypes, lamellar ichthyosis (LI) and nonbullous congenital ichthyosiformis erythroderma (CIE). Recently, strong evidence for the involvement of the transglutaminase 1 gene (TGM1) in LI has evolved. We have studied ARCI in the isolated Finnish population, in which recessive disorders are often caused by single mutations enriched by a founder effect. Surprisingly, five different mutations of TGM1 (Arg141His, Arg142Cys, Gly217Ser, Val378Leu, and Arg395Leu) were found in Finnish ARCI patients. In addition to affected LI patients, we also identified TGM1 mutations in CIE patients. Moreover, haplotype analysis of the chromosomes carrying the most common mutation, a C-->T transition changing Arg142 to Cys, revealed that the same mutation has been introduced twice in the Finnish population. In addition to this Arg142Cys mutation, three other mutations, in Arg141 and Arg142, have been described elsewhere, in other populations. These findings suggest that this region of TGM1 is more susceptible to mutation. The corresponding amino acid sequence is conserved in other transglutaminases, but, for example, coagulation factor XIII (FXIII) mutations do not cluster in this region. Protein modeling of the Arg142Cys mutation suggested disruption or destabilization of the protein. In transfection studies, the closely related transglutaminase FXIII protein with the corresponding mutation was shown to be susceptible to degradation in COS cells, further supporting evidence of the destabilizing effect of the Arg142Cys mutation in TGM1.

Crystal structure of rhodopsin: a template for cone visual pigments and other G protein-coupled receptors

The crystal structure of rhodopsin has provided the first three-dimensional molecular model for a G-protein-coupled receptor (GPCR). Alignment of the molecular model from the crystallographic structure with the helical axes seen in cryo-electron microscopic (cryo-EM) studies provides an opportunity to investigate the properties of the molecule as a function of orientation and location within the membrane. In addition, the structure provides a starting point for modeling and rational experimental approaches of the cone pigments, the GPCRs in cone cells responsible for color vision. Homology models of the cone pigments provide a means of understanding the roles of amino acid sequence differences that shift the absorption maximum of the retinal chromophore in the environments of different opsins.

Identification of the calcium binding site and a novel ytterbium site in blood coagulation factor XIII by x-ray crystallography.

The presence or absence of calcium determines the activation, activity, oligomerization, and stability of blood coagulation factor XIII. To explore these observed effects, we have determined the x-ray crystal structure of recombinant factor XIII A2 in the presence of calcium, strontium, and ytterbium. The main calcium binding site within each monomer involves the main chain oxygen atom of Ala-457, and also the side chains from residues Asn-436, Asp-438, Glu-485, and Glu-490. Calcium and strontium bind in the same location, while ytterbium binds several angstroms removed. A novel ytterbium binding site is also found at the dimer two-fold axis, near residues Asp-270 and Glu-272, and this site may be related to the reported inhibition by lanthanide metals (Achyuthan, K. E., Mary, A., and Greenberg, C. S. (1989) Biochem. J. 257, 331–338). The overall structure of ion-bound factor XIII is very similar to the previously determined crystal structures of factor XIII zymogen, likely due to the constraints of this monoclinic crystal form. We have merged the three independent sets of water molecules in the structures to determine which water molecules are conserved and possibly structurally significant.

Estimation of primary sequence homology from amino acid composition of evolutionary related proteins.

Abstract The amino acid compositions of many of the known sequenced proteins were compared to determine if a relationship exists between the amino acid composition and the amount of sequence homology of these proteins. For this purpose, a function, the composition divergence, was defined. A computer program based on relatively simple assumptions has been successfully used to simulate the data distribution found in comparing composition divergence with the sequence dissimilarity. From this characterization of known proteins, it is possible to predict the sequence homology of unsequenced proteins, based on amino acid composition comparisons. The power and limitations of this technique are discussed.