Biomedical subjects

Petras J Kundrotas

Publications and source records attributed to Petras J Kundrotas.

7 recordsLinked to original sources

PubMed2006

Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives.

BACKGROUND: Predicting residues' contacts using primary amino acid sequence alone is an important task that can guide 3D structure modeling and can verify the quality of the predicted 3D structures. The correlated mutations (CM) method serves as the most promising approach and it has been used to predict amino acids pairs that are distant in the primary sequence but form contacts in the native 3D structure of homologous proteins. RESULTS: Here we report a new implementation of the CM method with an added set of selection rules (filters). The parameters of the algorithm were optimized against fifteen high resolution crystal structures with optimization criterion that maximized the confidentiality of the predictions. The optimization resulted in a true positive ratio (TPR) of 0.08 for the CM without filters and a TPR of 0.14 for the CM with filters. The protocol was further benchmarked against 65 high resolution structures that were not included in the optimization test. The benchmarking resulted in a TPR of 0.07 for the CM without filters and to a TPR of 0.09 for the CM with filters. CONCLUSION: Thus, the inclusion of selection rules resulted to an overall improvement of 30%. In addition, the pair-wise comparison of TPR for each protein without and with filters resulted in an average improvement of 1.7. The methodology was implemented into a web server http://www.ces.clemson.edu/compbio/recon that is freely available to the public. The purpose of this implementation is to provide the 3D structure predictors with a tool that can help with ranking alternative models by satisfying the largest number of predicted contacts, as well as it can provide a confidence score for contacts in cases where structure is known.

Algorithms↗

PubMed2006

PROTCOM: searchable database of protein complexes enhanced with domain-domain structures.

The database of protein complexes (PROTCOM) is a compilation of known 3D structures of protein-protein complexes enriched with artificially created domain-domain structures using the available entries in the Protein Data Bank. The domain-domain structures are generated by parsing single chain structures into loosely connected domains and are important features of the database. The database (http://www.ces.clemson.edu/compbio/protcom) could be used for benchmarking purposes of the docking and other algorithms for predicting 3D structures of protein-protein complexes. The database can be utilized as a template database in the homology or threading methods for modeling the 3D structures of unknown protein-protein complexes. PROTCOM provides the scientific community with an integrated set of tools for browsing, searching, visualizing and downloading a pool of protein complexes. The user is given the option to select a subset of entries using a combination of up to 10 different criteria. As on July 2006 the database contains 1770 entries, each of which consists of the known 3D structures and additional relevant information that can be displayed either in text-only or in visual mode.

Computer Graphics↗

PubMed2006

Predicting 3D structures of transient protein-protein complexes by homology.

The paper reports a homology based approach for predicting the 3D structures of full length hetero protein complexes. We have created a database of templates that includes structures of hetero protein-protein complexes as well as domain-domain structures (), which allowed us to expand the template pool up to 418 two-chain entries (at 40% sequence identity). Two protocols were tested-a protocol based on position specific Blast search (Protocol-I) and a protocol based on structural similarity of monomers (Protocol-II). All possible combinations of two monomers (350,284 pairs) in the ProtCom database were subjected to both protocols to predict if they form complexes. The predictions were benchmarked against the ProtCom database resulting to false-true positives ratios of approximately 5:1 and approximately 7:1 and recovery of 19% and 86%, respectively for protocols I and II. From 350,284 trials Protocol-I made only approximately 500 wrong predictions resulting to 0.5% error. In addition, though it was shown that artificially created domain-domain structures can in principle be good templates for modeling full length protein complexes, more sensitive methods are needed to detect homology relations. The quality of the models was assessed using two different criteria such as interfacial residues and overall RMSD. It was found that there is no correlation between these two measures. In many cases the interface residues were predicted correctly, but the overall RMSD was over 6 A and vice versa.

Algorithms↗

PubMed2006

Electrostatic properties of protein-protein complexes.

Statistical electrostatic analysis of 37 protein-protein complexes extracted from the previously developed database of protein complexes (ProtCom, http://www.ces.clemson.edu/compbio/protcom) is presented. It is shown that small interfaces have a higher content of charged and polar groups compared to large interfaces. In a vast majority of the cases the average pKa shifts for acidic residues induced by the complex formation are negative, indicating that complex formation stabilizes their ionizable states, whereas the histidines are predicted to destabilize the complex. The individual pKa shifts show the same tendency since 80% of the interfacial acidic groups were found to lower their pKas, whereas only 25% of histidines raise their pKa upon the complex formation. The interfacial groups have been divided into three sets according to the mechanism of their pKa shift, and statistical analysis of each set was performed. It was shown that the optimum pH values (pH of maximal stability) of the complex tend to be the same as the optimum pH values of the complex components. This finding can be used in the homology-based prediction of the 3D structures of protein complexes, especially when one needs to evaluate and rank putative models. It is more likely for a model to be correct if both components of the model complex and the entire complex have the same or at least similar values of the optimum pH.

Binding Sites↗

PubMed2004

Charge sequence coding in statistical modeling of unfolded proteins.

Unfolded proteins recently attracted attention due to accumulation of experimental evidences for their significant role in different life processes. Modeling of electrostatic interactions (EI) in unfolded state of proteins is becoming increasingly important as well. In this paper, we stress on the importance of how the sequence of charged residues of a given protein is incorporated into the models for calculation of EI in the unfolded state. On the basis of the distributions of distances between titratable sites of charged residues calculated for polypeptide chains of various compositions, it was found that the distance distribution for a pair of residues, located close to each other along the sequence of a protein, depends on what residues constitute the pair in question. It was concluded that the consideration of these residue-specific distributions is essential for a statistical model to be accurate from the physical point of view. It was suggested that use of distance intervals in the spherical model of unfolded proteins accounts better for the charge sequence than the set of single distance values. This was illustrated by comparison of the pK values of the titratable groups of the unfolded N-terminal SH3 domain of the Drosophila protein drk to the available experimental data.

Amino Acids↗

PubMed2002

Modeling of denatured state for calculation of the electrostatic contribution to protein stability.

Existing models of the denatured state of proteins consider only one possible spatial distribution of protein charges and therefore are applicable to a limited number of cases. In this article, a more general framework for the modeling of the denatured state is proposed. It is based on the assumption that the titratable groups of an unfolded protein can adopt a quasi-random distribution restricted by the protein sequence. The model was applied for the calculations of electrostatic interactions in two proteins, barnase and N-terminal domain of the ribosomal protein L9. The calculated free energy of denaturation, DeltaG(pH), reproduces the experimental data better than the commonly used null approximation (NA). It was shown that the seemingly good agreement with experimental data obtained by NA originates from the compensatory effect between the pairwise electrostatic interactions and the desolvation energy of the individual sites. It was also found that the ionization properties of denatured proteins are influenced by the protein sequence.

Bacterial Proteins↗

PubMedDate not supplied

Statistical studies of flexible nonhomogeneous polypeptide chains.

Unfolded proteins attract increasing attention nowadays because of the accumulation of experimental evidence that they play an important role in different biological processes. Therefore, studies of various statistical properties of flexible protein-like polypeptide chains are becoming increasingly important as well. This paper presents distributions (histograms) of distances between atoms of titratable residues for flexible polypeptide chains with various residue compositions and with the hard-spheres potential taken into consideration. The factors influencing the parameters of the obtained histograms have been identified and analyzed. It was found that the sensitivity of the distributions with respect to the internal structure of intermediate residues increases with the number of residues between the considered charged residues. It was shown that branching at C(beta) atoms of the side chains of the intermediate residues is among the most considerable factors influencing the shape of the distance distribution and the average distance between atoms in flexible chains. Despite the model simplicity, the results of the calculations can be applied for systems with other types of interactions presented, and this was demonstrated for the charge-charge interactions. In particular, it was shown that those interactions have a significant effect on distances between the unlike charges, while such an effect for the like charges is much less pronounced. The comparison of predictions made on the basis of the presented calculations to some experimental data is also given, and possible applications of the theoretical concept described in the paper are discussed.

Animals↗