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Iosif I Vaisman

Publications and source records attributed to Iosif I Vaisman.

8 recordsLinked to original sources
PubMed2006

Computational mutagenesis studies of protein structure-function correlations.

Topological scores, measures of sequence-structure compatibility, are calculated for all 1,881 single point mutants of the human immunodeficiency virus (HIV)-1 protease using a four-body statistical potential function based on Delaunay tessellation of protein structure. Comparison of the mutant topological score data with experimental data from alanine scan studies specifically on the dimer interface residues supports previous findings that 1) L97 and F99 contribute greatly to the Gibbs energy of HIV-1 protease dimerization, 2) Q2 and T4 contribute the least toward the Gibbs energy, and 3) C-terminal residues are more sensitive to mutations than those at the N-terminus. For a more comprehensive treatment of the relationship between protease structure and function, mutant topological scores are compared with the activity levels for a set of 536 experimentally synthesized protease mutants, and a significant correlation is observed. Finally, this structure-function correlation is similarly identified by examining model systems consisting of 2,015 single point mutants of bacteriophage T4 lysozyme as well as 366 single point mutants of HIV-1 reverse transcriptase and is hypothesized to be a property generally applicable to all proteins.

Computational Biology↗
PubMed2006

Graph theoretic properties of networks formed by the Delaunay tessellation of protein structures.

The Delaunay tessellation of several sets of real and simplified model protein structures has been used to explore graph theoretic properties of residue contact networks. The system of contacts defined by residues joined by edges in the Delaunay simplices can be thought of as a graph or network and analyzed using techniques from elementary graph theory and the theory of complex networks. Such analysis indicates that protein contact networks have small world character, but technically are not small world networks. This approach also indicates that networks formed by native structures and by most misfolded decoys can be differentiated by their respective graph properties. The characteristic features of residue contact networks can be used for the detection of structural elements in proteins, such as the ubiquitous closed loops consisting of 22-32 consecutive residues, where terminal residues are Delaunay neighbors.

Binding Sites↗
PubMed2005

New method for protein secondary structure assignment based on a simple topological descriptor.

A simple, five-element descriptor, derived from the Delaunay tessellation of a protein structure in a single point per residue representation, can be assigned to each residue in the protein. The descriptor characterizes main-chain topology and connectivity in the neighborhood of the residue and does not explicitly depend on putative hydrogen bonds or any geometric parameter, including bond length, angles, and areas. Rules based on this descriptor can be used for accurate, robust, and computationally efficient secondary structure assignment that correlates well with the existing methods.

Algorithms↗
PubMed2005

Statistical geometry approach to the study of functional effects of human nonsynonymous SNPs.

The ability to predict the effect of nonsynonymous SNPs (nsSNPs) on protein function is important for the success of genetic disease association studies. Here we present a statistical geometry approach to nsSNP classification based on Delaunay tessellation, whereby the impact of nsSNPs on protein function is correlated with the change in the four-body statistical potential (DeltaQ) of the protein caused by the amino acid substitution. We observed that the DeltaQ of polymorphic proteins with disease-associated nsSNPs (daSNPs) was on average significantly lower than the DeltaQ of the proteins with neutral SNPs (ntSNPs). Clustering amino acid substitutions into conservative and nonconservative groups, and using a three-letter alphabet based on side-chain polarity showed significantly lower DeltaQ in nonconservative changes to daSNPs and when hydrophobic residues were substituted by charged or by polar residues. We also found that the daSNPs in the protein core caused much lower DeltaQ than surface daSNPs. This approach demonstrates a strong correlation between the computed DeltaQ and SNP classification. Integration of our approach with the existing models will help achieve a more precise recognition of nsSNPs that underlie polygenic diseases. All of the programs were written in Java and are available from the authors upon request.

Amino Acid Substitution↗
PubMed2004

A simple topological representation of protein structure: implications for new, fast, and robust structural classification.

A topological representation of proteins is developed that makes use of two metrics: the Euclidean metric for identifying natural nearest neighboring residues via the Delaunay tessellation in Cartesian space and the distance between residues in sequence space. Using this representation, we introduce a quantitative and computationally inexpensive method for the comparison of protein structural topology. The method ultimately results in a numerical score quantifying the distance between proteins in a heuristically defined topological space. The properties of this scoring scheme are investigated and correlated with the standard Calpha distance root-mean-square deviation measure of protein similarity calculated by rigid body structural alignment. The topological comparison method is shown to have a characteristic dependence on protein conformational differences and secondary structure. This distinctive behavior is also observed in the comparison of proteins within families of structural relatives. The ability of the comparison method to successfully classify proteins into classes, superfamilies, folds, and families that are consistent with standard classification methods, both automated and human-driven, is demonstrated. Furthermore, it is shown that the scoring method allows for a fine-grained classification on the family, protein, and species level that agrees very well with currently established phylogenetic hierarchies. This fine classification is achieved without requiring visual inspection of proteins, sequence analysis, or the use of structural superimposition methods. Implications of the method for a fast, automated, topological hierarchical classification of proteins are discussed.

Amino Acid Sequence↗
PubMed2003

Comprehensive mutagenesis of HIV-1 protease: a computational geometry approach.

A computational geometry technique based on Delaunay tessellation of protein structure, represented by C(alpha) atoms, is used to study effects of single residue mutations on sequence-structure compatibility in HIV-1 protease. Profiles of residue scores derived from the four-body statistical potential are constructed for all 1881 mutants of the HIV-1 protease monomer and compared with the profile of the wild-type protein. The profiles for an isolated monomer of HIV-1 protease and the identical monomer in a dimeric state with an inhibitor are analyzed to elucidate changes to structural stability. Protease residues shown to undergo the greatest impact are those forming the dimer interface and flap region, as well as those known to be involved in inhibitor binding.

Amino Acid Sequence↗
PubMed2003

A new topological method to measure protein structure similarity.

A method for the quantitative evaluation of structural similarity between protein pairs is developed that makes use of a Delaunay-based topological mapping. The result of the mapping is a three-dimensional array which is representative of the global structural topology and whose elements can be used to construe an integral scoring scheme. This scoring scheme was tested for its dependence on the protein length difference in a pairwise comparison, its ability to provide a reasonable means for structural similarity comparison within a family of structural neighbors of similar length, and its sensitivity to the differences in protein conformation. It is shown that such a topological evaluation of similarity is capable of providing insight into these points of interest. Protein structure comparison using the method is computationally efficient and the topological scores, although providing different information about protein similarity, correlate well with the distance root-mean-square deviation values calculated by rigid-body structural alignment.

Computational Biology↗