Estimation of the frequency of amino acid substitutions causing instability of the spatial structure in an overall mutation spectrum of alpha- and beta-subunits of human hemoglobin

The influence of single amino acid substitutions on the stability of alpha- and beta-chains of human hemoglobin was investigated by the computer method. The method was based on characteristics of protein tertiary structure and physico-chemical properties of amino acids. Frequencies of unstable mutations in the total mutational spectra of alpha- and beta-subunits of human hemoglobin were analysed: instability was produced by 26% of mutations in the alpha-subunit and by 32% in the beta-subunit. These results support the idea that certain limitations exist for stability changes produced by amino acid substitutions.     

Identification of domains and domain interface residues in multidomain proteins from graph spectral method

We present a novel method for the identification of structural domains and domain interface residues in proteins by graph spectral method. This method converts the three-dimensional structure of the protein into a graph by using atomic coordinates from the PDB file. Domain definitions are obtained by constructing either a protein backbone graph or a protein side-chain graph. The graph is constructed based on the interactions between amino acid residues in the three-dimensional structure of the proteins. The spectral parameters of such a graph contain information regarding the domains and subdomains in the protein structure. This is based on the fact that the interactions among amino acids are higher within a domain than across domains. This is evident in the spectra of the protein backbone and the side-chain graphs, thus differentiating the structural domains from one another. Further, residues that occur at the interface of two domains can also be easily identified from the spectra. This method is simple, elegant, and robust. Moreover, a single numeric computation yields both the domain definitions and the interface residues.     

Determination of the autocorrelation orders of proteins

A statistical analysis of the autocorrelation characteristics of active polypeptides has been carried out by means of the correlogram method. It is shown that the amino acid sequences of the analysed proteins, considered as a whole, are autocorrelated and that the correlograms characterize each protein reflecting its three-dimensional structure.     

Analysis of the factors and implications of an empirical method for estimating the stability of mutant human haemoglobins

An empirical method for estimating the effects of single amino acid substitutions on structural stability of proteins with known spatial structure is developed. Twenty physical and chemical properties of amino acids and characteristics of protein tertiary structure were analysed to determine those most involved in producing instability. We employed data on 330 mutant variants of the alpha- and beta-subunits of human haemoglobin in choice of the parameters of the method developed which yielded a 81% of prediction accuracy of stability estimates for human mutant haemoglobins.     

Simulation of alpha-helix and beta-hairpin formation in water-soluble proteins by the code physics method

One of the possible ways for complete and final solution of the problem of determination of three-dimensional structure of proteins on amino acid sequence is simulation of protein three-dimensional structure formation. The use of the code physics method developed by the author has been suggested to fulfill this task. The simulation of alpha-helix and beta-hairpin formation in water-soluble proteins as a start of realization of the plan is described here. The results of the simulation were compared with the experimental data for 14 proteins of no more than 50 amino acids and therefore with little number of alpha-helices and beta-strands (to meet limits of simulation process) and with secondary structure predictions by the best to data methods of protein secondary structure prediction, PSIpred, PORTER and PROFsec. Secondary structure of the proteins, obtained as a result of the simulation of alpha-helix and beta-hairpin formation using the code physics method, corresponded completely to experimental data while the secondary structure predicted by the PSIpred, PORTER and PROFsec methods differed from these data significantly.     

Prediction of the location of structural domains in globular proteins

The location of structural domains in proteins is predicted from the amino acid sequence, based on the analysis of a computed contact map for the protein, the average distance map (ADM). Interactions between residues i and j in a protein are subdivided into several ranges, according to the separation |i-j| in the amino acid sequence. Within each range, average spatial distances between every pair of amino acid residues are computed from a data base of known protein structures. Infrequently occurring pairs are omitted as being statistically insignificant. The average distances are used to construct a predicted ADM. The ADM is analyzed for the occurrence of regions with high densities of contacts (compact regions). Locations of rapid changes of density between various parts of the map are determined by the use of scanning plots of contact densities. These locations serve to pinpoint the distribution of compact regions. This distribution, in turn, is used to predict boundaries of domains in the protein. The technique provides an objective method for the location of domains both on a contact map derived from a known three-dimensional protein structure, the real distance map (RDM), and on an ADM. While most other published methods for the identification of domains locate them in the known three-dimensional structure of a protein, the technique presented here also permits the prediction of domains in proteins of unknown spatial structure, as the construction of the ADM for a given protein requires knowledge of only its amino acid sequence.     

Solution structure of the single-stranded DNA binding protein of the filamentous Pseudomonas phage Pf3: similarity to other proteins binding to single-stranded nucleic acids.

The three-dimensional structure of the homodimeric single-stranded DNA binding protein encoded by the filamentous Pseudomonas bacteriophage Pf3 has been determined using heteronuclear multidimensional NMR techniques and restrained molecular dynamics. NMR experiments and structure calculations have been performed on a mutant protein (Phe36 --> His) that was successfully designed to reduce the tendency of the protein to aggregate. The protein monomer is composed of a five-stranded antiparallel beta-sheet from which two beta-hairpins and a large loop protrude. The structure is compared with the single-stranded DNA binding protein encoded by the filamentous Escherichia coli phage Ff, a protein with a similar biological function and DNA binding properties, yet quite different amino acid sequence, and with the major cold shock protein of Escherichia coli, a single-stranded DNA binding protein with an entirely different sequence, biological function and binding characteristics. The amino acid sequence of the latter is highly homologous to the nucleic acid binding domain (i.e. the cold shock domain) of proteins belonging to the Y-box family. Despite their differences in amino acid sequence and function, the folds of the three proteins are remarkably similar, suggesting that this is a preferred folding pattern shared by many single-stranded DNA binding proteins.     

Protein plasticity to the extreme: changing the topology of a 4-alpha-helical bundle with a single amino acid substitution.

BACKGROUND: Conventional wisdom has it that two proteins sharing 98.4% sequence identity have nearly identical three-dimensional structures. Here we provide a counter-example to this statement by showing that a single amino acid substitution can change the topology of a homodimeric 4-alpha-helical bundle protein. RESULTS: We have determined the high-resolution crystal structure of a 4-alpha-helical protein with a single alanine to proline mutation in the turn region, and show that this single amino acid substitution leads to a complete reorganisation of the whole molecule. The protein is converted from the canonical left-handed all-antiparallel form, to a right-handed mixed parallel and antiparallel bundle, which to the best of our knowledge and belief represents a novel topological motif for this class of proteins. CONCLUSIONS: The results suggest a possible new mechanism for the creation and evolution of topological motifs, show the importance of loop regions in determining the allowable folding pathways, and illustrate the malleability of protein structures.     

Protein synthesis rhythm.

The three-dimensional structure of a protein molecule appears to depend on the amino acid sequence of the protein in an as yet incompletely described manner. If the amino acid sequence is replaced by a numerical sequence of values representing a physical or chemical property of amino acids, the resulting numerical sequence is amenable to autocorrelation analysis. Further, if certain geometrical parameters are calculated from the three-dimensional structure of a protein to form a configurational series, pairs of property series and configurational series can be analyzed by cross-correlation techniques. The data base for the analysis was the three-dimensional structures of ten proteins as determined by X-ray crystallography. Such analysis yields the result that the hydrophobicity of an amino acid residue in a protein influences the orientation angle of the amino acid side chain. This result is consistent with the widely current “oil-drop” model of protein structure. Hydrophobicity also appears to influence the backbone dihedral angle φ, but not ψ Such a directional effect cannot be explained by a current model of information transfer in protein helices. The magnitude of the cross correlations does not appear to be satisfactory for construction of a transfer function model for the prediction of general features of protein structure from amino acid sequences.     

Computer modeling studies of the structure of a repressor

Due to advances in molecular biology the DNA sequences of structural genes coding for proteins are often known before a protein is characterized or even isolated. The function of a protein whose amino acid sequence has been deduced from a DNA sequence may not even be known. This has created greater interest in the development of methods to predict the tertiary structures of proteins. The a priori prediction of a protein's structure from its amino acid sequence is not yet possible. However, since proteins with similar amino acid sequences are observed to have similar three-dimensional structures, it is possible to use an analogy with a protein of known structure to draw some conclusions about the structure and properties of an uncharacterized protein. The process of predicting the tertiary structure of a protein relies very much upon computer modeling and analysis of the structure. The prediction of the structure of the bacteriophage 434 cro repressor is used as an example illustrating current procedures.     

An Integrated Sequence-Structure Database incorporating matching mRNA sequence, amino acid sequence and protein three-dimensional structure data.

We have constructed a non-homologous database, termed the Integrated Sequence-Structure Database (ISSD) which comprises the coding sequences of genes, amino acid sequences of the corresponding proteins, their secondary structure and straight phi,psi angles assignments, and polypeptide backbone coordinates. Each protein entry in the database holds the alignment of nucleotide sequence, amino acid sequence and the PDB three-dimensional structure data. The nucleotide and amino acid sequences for each entry are selected on the basis of exact matches of the source organism and cell environment. The current version 1.0 of ISSD is available on the WWW at http://www.protein.bio.msu.su/issd/ and includes 107 non-homologous mammalian proteins, of which 80 are human proteins. The database has been used by us for the analysis of synonymous codon usage patterns in mRNA sequences showing their correlation with the three-dimensional structure features in the encoded proteins. Possible ISSD applications include optimisation of protein expression, improvement of the protein structure prediction accuracy, and analysis of evolutionary aspects of the nucleotide sequence-protein structure relationship.     

Development of a protein–ligand-binding site prediction method based on interaction energy and sequence conservation

We present a new method for predicting protein–ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction.     

A structural bioinformatics approach to the analysis of nonsynonymous single nucleotide polymorphisms (nsSNPs) and their relation to disease

The prediction of the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on function depends critically on exploiting all information available on the three-dimensional structures of proteins. We describe software and databases for the analysis of nsSNPs that allow a user to move from SNP to sequence to structure to function. In both structure prediction and the analysis of the effects of nsSNPs, we exploit information about protein evolution, in particular, that derived from investigations on the relation of sequence to structure gained from the study of amino acid substitutions in divergent evolution. The techniques developed in our laboratory have allowed fast and automated sequence-structure homology recognition to identify templates and to perform comparative modeling; as well as simple, robust, and generally applicable algorithms to assess the likely impact of amino acid substitutions on structure and interactions. We describe our strategy for approaching the relationship between SNPs and disease, and the results of benchmarking our approach -- human proteins of known structure and recognized mutation.     

Prediction of protein domain boundaries based on statistics of appearance of amino acid residues

We have created a database of two-domain proteins with homology less than 25% (452 proteins). Based on one half of this set of proteins statistics of appearance of amino acid residues on the domain boundaries of multiple domain proteins has been obtained. Small and hydrophilic amino acids (proline, glycine, asparagine, glutamic acid, arginine and others) appear on the domain boundaries more often than in the whole protein. Opposite, hydrophobic amino acid residues (tryptophane, methionine, phenylalanine and others) appear on the domain boundaries more rarely. The obtained scales of the appearance of amino acid residues on the boundary regions from the statistics have been used for calculation of domain boundaries in the proteins of the second half of the database. The probability scale obtained by averaging the appearance of amino acid residues on the domain boundary region including 8 residues (+/-4 residues from the real domain boundary) gives the best result: for 57% of proteins the predicted boundary was closer than 40 residues to the boundary assigned from three-dimensional structures, for 41% it was closer than 20 residues from the real boundary. The probability scale was used to predict domain boundaries for proteins with unknown three-dimensional structure (international competition CASP6).     

Distinguishing structural and functional restraints in evolution in order to identify interaction sites

Structural genomics projects are producing many three-dimensional structures of proteins that have been identified only from their gene sequences. It is therefore important to develop computational methods that will predict sites involved in productive intermolecular interactions that might give clues about functions. Techniques based on evolutionary conservation of amino acids have the advantage over physiochemical methods in that they are more general. However, the majority of techniques neither use all available structural and sequence information, nor are able to distinguish between evolutionary restraints that arise from the need to maintain structure and those that arise from function. Three methods to identify evolutionary restraints on protein sequence and structure are described here. The first identifies those residues that have a higher degree of conservation than expected: this is achieved by comparing for each amino acid position the sequence conservation observed in the homologous family of proteins with the degree of conservation predicted on the basis of amino acid type and local environment. The second uses information theory to identify those positions where environment-specific substitution tables make poor predictions of the overall amino acid substitution pattern. The third method identifies those residues that have highly conserved positions when three-dimensional structures of proteins in a homologous family are superposed. The scores derived from these methods are mapped onto the protein three-dimensional structures and contoured, allowing identification clusters of residues with strong evolutionary restraints that are sites of interaction in proteins involved in a variety of functions. Our method differs from other published techniques by making use of structural information to identify restraints that arise from the structure of the protein and differentiating these restraints from others that derive from intermolecular interactions that mediate functions in the whole organism.     

Simulation of formation of α-helices and β-hairpins in water-soluble proteins by the code-based physics method

One of the possible ways for a complete and final decision of the problem of the determination of three-dimensional structure of proteins from their amino acid sequence is simulation of protein three-dimensional structure formation. For the performance of this task it is suggested to use the code-based physics method developed by the author. In this article a simulation of the α-helix and β-hairpin formation in water-soluble proteins as a start of the realization of this plan is described. Results of the simulation are compared from experimental data for 14 proteins of no more than 50 amino acids and, therefore, with a small number of α-helices and β-strands (to meet limits of simulation process) and secondary structure predictions by the best current methods of protein secondary structure prediction, PSIpred, PORTER and PROFsec. The secondary structure of proteins, obtained as a result of the simulation of α-helix and β-hairpin formation by the code-based physics method, agrees completely with the experiment, while the secondary structure predicted by the PSIpred, PORTER, and PROFsec methods contains significant differences from the experimental data.     

Analysis of Protein Three-Dimension Structure Using Amino Acids Depths

The issue of amino acid depth in proteins gives important insights to our understanding of protein’s three-dimensional structure. There has already been much research done in mathematical and statistical sciences regarding the general definitions, properties and algorithms describing the particle depth of spatially extended systems. We constructed a method of calculating the amino acids depths and applied it to a set of 527 protein structures. We propose the introduction of amino acid depth tendency factors for three-dimensional structures of proteins. The depth tendency factors relate not only to the hydrophobicity indices but also to the electrostatic charge. We found a relationship between the protein size and the number of residues using the distance between the deepest residue and surface residues. We made a prediction regarding the number of residues on the surface of a protein, the deepest amino acid, and the average depth, all of which are fitted well to a linear functional relationship with the length of the protein. Finally, we have predicted the depths of multiple peptides in protein’s three-dimension structure. Electronic supplementary material The online version of this article () contains supplementary material, which is available to authorized users.     

Evolutionary information hidden in a single protein structure

The knowledge of conserved sequences in proteins is valuable in identifying functionally or structurally important residues. Generating the conservation profile of a sequence requires aligning families of homologous sequences and having knowledge of their evolutionary relationships. Here, we report that the conservation profile at the residue level can be quantitatively derived from a single protein structure with only backbone information. We found that the reciprocal packing density profiles of protein structures closely resemble their sequence conservation profiles. For a set of 554 nonhomologous enzymes, 74% (408/554) of the proteins have a correlation coefficient > 0.5 between these two profiles. Our results indicate that the three-dimensional structure, instead of being a mere scaffold for positioning amino acid residues, exerts such strong evolutionary constraints on the residues of the protein that its profile of sequence conservation essentially reflects that of its structural characteristics.