Russell F. Doolittle

A simple method for displaying the hydropathic character of a protein

A computer program that progressively evaluates the hydrophilicity and hydrophobicity of a protein along its amino acid sequence has been devised. For this purpose, a hydropathy scale has been composed wherein the hydrophilic and hydrophobic properties of each of the 20 amino acid side-chains is taken into consideration. The scale is based on an amalgam of experimental observations derived from the literature. The program uses a moving-segment approach that continuously determines the average hydropathy within a segment of predetermined length as it advances through the sequence. The consecutive scores are plotted from the amino to the carboxy terminus. At the same time, a midpoint line is printed that corresponds to the grand average of the hydropathy of the amino acid compositions found in most of the sequenced proteins. In the case of soluble, globular proteins there is a remarkable correspondence between the interior portions of their sequence and the regions appearing on the hydrophobic side of the midpoint line, as well as the exterior portions and the regions on the hydrophilic side. The correlation was demonstrated by comparisons between the plotted values and known structures determined by crystallography. In the case of membrane-bound proteins, the portions of their sequences that are located within the lipid bilayer are also clearly delineated by large uninterrupted areas on the hydrophobic side of the midpoint line. As such, the membrane-spanning segments of these proteins can be identified by this procedure. Although the method is not unique and embodies principles that have long been appreciated, its simplicity and its graphic nature make it a very useful tool for the evaluation of protein structures.

Progressive sequence alignment as a prerequisitetto correct phylogenetic trees

SummaryA progressive alignment method is described that utilizes the Needleman and Wunsch pairwise alignment algorithm iteratively to achieve the multiple alignment of a set of protein sequences and to construct an evolutionary tree depicting their relationship. The sequences are assumed a priori to share a common ancestor, and the trees are constructed from difference matrices derived directly from the multiple alignment. The thrust of the method involves putting more trust in the comparison of recently diverged sequences than in those evolved in the distant past. In particular, this rule is followed: “once a gap, always a gap”. The method has been applied to three sets of protein sequences: 7 superoxide dismutases, 11 globins, and 9 tyrosine kinase-like sequences. Multiple alignments and phylogenetic trees for these sets of sequences were determined and compared with trees derived by conventional pairwise treatments. In several instances, the progressive method led to trees that appeared to be more in line with biological expectations than were trees obtained by more commonly used methods.

Determining Divergence Times of the Major Kingdoms of Living Organisms with a Protein Clock

Amino acid sequence data from 57 different enzymes were used to determine the divergence times of the major biological groupings. Deuterostomes and protostomes split about 670 million years ago and plants, animals, and fungi last shared a common ancestor about a billion years ago. With regard to these protein sequences, plants are slightly more similar to animals than are the fungi. In contrast, phylogenetic analysis of the same sequences indicates that fungi and animals shared a common ancestor more recently than either did with plants, the greater difference resulting from the fungal lineage changing faster than the animal and plant lines over the last 965 million years. The major protist lineages have been changing at a somewhat faster rate than other eukaryotes and split off about 1230 million years ago. If the rate of change has been approximately constant, then prokaryotes and eukaryotes last shared a common ancestor about 2 billion years ago, archaebacterial sequences being measurably more similar to eukaryotic ones than are eubacterial ones.

“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.

Aligning amino acid sequences: Comparison of commonly used methods

SummaryWe examined two extensive families of protein sequences using four different alignment schemes that employ various degrees of “weighting” in order to determine which approach is most sensitive in establishing relationships. All alignments used a similarity approach based on a general algorithm devised by Needleman and Wunsch. The approaches included a simple program, UM (unitary matrix), whereby only identities are scored; a scheme in which the genetic code is used as a basis for weighting (GC); another that employs a matrix based on structural similarity of amino acids taken together with the genetic basis of mutation (SG); and a fourth that uses the empirical log-odds matrix (LOM) developed by Dayhoff on the basis of observed amino acid replacements. The two sequence families examined were (a) nine different globins and (b) nine different tyrosine kinase-like proteins. It was assumed a priori that all members of a family share common ancestry. In cases where two sequences were more than 30% identical, alignments by all four methods were almost always the same. In cases where the percentage identity was less than 20%, however, there were often significant differences in the alignments. On the average, the Dayhoff LOM approach was the most effective in verifying distant relationships, as judged by an empirical “jumbling test.” This was not universally the case, however, and in some instances the simple UM was actually as good or better. Trees constructed on the basis of the various alignments differed with regard to their limb lengths, but had essentially the same branching orders. We suggest some reasons for the different effectivenesses of the four approaches in the two different sequence settings, and offer some rules of thumb for assessing the significance of sequence relationships.

Crystal structures of fragment D from human fibrinogen and its crosslinked counterpart from fibrin.

In blood coagulation, units of the protein fibrinogen pack together to form a fibrin clot, but a crystal structure for fibrinogen is needed to understand how this is achieved. The structure of a core fragment (fragment D) from human fibrinogen has now been determined to 2.9 Å resolution. The 86K three-chained structure consists of a coiled-coil region and two homologous globular entities oriented at approximately 130 degrees to each other. Additionally, the covalently bound dimer of fragment D, known as ‘double-D’, was isolated from human fibrin, crystallized in the presence of a Gly-Pro-Arg-Pro-amide peptide ligand, which simulates the donor polymerization site, and its structure solved by molecular replacement with the model of fragment D.

Convergent evolution: the need to be explicit

Convergence as a phenomenon in molecular evolution is an issue that confuses many discussions. Often the problem is that not enough care is taken to state exactly what kind of convergence one has in mind. Functional and mechanistic convergence are both common, and some structural convergence has probably occurred, but a convincing case for genuine sequence convergence has yet to be made.

Evolution by acquisition: the case for horizontal gene transfers

One of the most debated questions in the field of molecular evolution is the possible role of horizontal transfer in evolution. Of all the claims that have been made over the years, those reporting transfers between eukaryotes and prokaryotes are the most controversial. Here we present the cases for and against several such possible gene acquisitions.

The amino acid sequence of the α-chain of human fibrinogen

The amino acid sequence of the human fibrinogen α-chain reveals a structure that can be divided into three zones of unique amino acid composition. The middle of these contains the two primary α-chain cross-linking acceptor sites and consists of a remarkable series of internal duplications.

Antibody Active Sites and Immunoglobulin Molecules

In order to obtain detailed information about the relationship between structure and function in antibody molecules, a method called affinity labeling has been devised to attach chemical labels specifically to amino acid residues in the active sites of antibody molecules. With antibodies to three different haptens, highly specific labeling of the active sites has been achieved. Tyrosine residues on both heavy and light polypeptide chains have been labeled in a molar ratio close to 2:1, and labels on the two chains are equally specific to the active sites. Peptide fragmentation studies of the labeled chains of one antibody system have shown that: (i) within 25 amino acid residues of the labeled tyrosine on either chain, substantial chemical heterogeneity exists among different antibody molecules of the same specificity; and (ii) the labeled peptide fragments from both chains are very similar in physicochemical characteristics, including average size, heterogeneity, and unusual hydrophobicity. These experimental results have led us to the view that a particular region of the heavy chain and a particular region of the light chain are utilized to construct the active sites of the three different antibodies, differences in specificity arising from chemical perturbations in these two regions. Correlated structural studies of affinity-labeled antibodies and of the homogeneous light chains (Bence Jones proteins) and heavy chains produced in multiple myeloma may permit the identification of these special active-site regions. The view that active sites of different specificity are chemical perturbations of a particular region of the antibody molecule has a possible close analogue in enzyme systems, particularly among the esterases. The marked chemical similarities we have observed between the active site regions of heavy and light chains indicate to us that chemical homologies, but not identities, exist between the chains. This is reinforced by recently obtained amino acid sequence data which reveal homologies between the two chains near their carboxyl-terminals. These results indicate that the structural genes which code for the synthesis of heavy and light chains are related, presumably having arisen from some common ancestral gene during evolution. This conclusion strongly suggests that both heavy and light chains determine antibody specificity, and has important implications for the still-unknow mechanisms of antibody biosynthesis.