Pairwise contact energy statistical potentials can help to find probability of point mutations.

To adopt a particular fold, a protein requires several interactions between its amino acid residues. The energetic contribution of these residue-residue interactions can be approximated by extracting statistical potentials from known high resolution structures. Several methods based on statistical potentials extracted from unrelated proteins are found to make a better prediction of probability of point mutations. We postulate that the statistical potentials extracted from known structures of similar folds with varying sequence identity can be a powerful tool to examine probability of point mutation. By keeping this in mind, we have derived pairwise residue and atomic contact energy potentials for the different functional families that adopt the (α/ß)8 TIM-Barrel fold. We carried out computational point mutations at various conserved residue positions in yeast Triose phosphate isomerase enzyme for which experimental results are already reported. We have also performed molecular dynamics simulations on a subset of point mutants to make a comparative study. The difference in pairwise residue and atomic contact energy of wildtype and various point mutations reveals probability of mutations at a particular position. Interestingly, we found that our computational prediction agrees with the experimental studies of Silverman et al. (Proc Natl Acad Sci 2001;98:3092-3097) and perform better prediction than iMutant and Cologne University Protein Stability Analysis Tool. The present work thus suggests deriving pairwise contact energy potentials and molecular dynamics simulations of functionally important folds could help us to predict probability of point mutations which may ultimately reduce the time and cost of mutation experiments. Proteins 2016; 85:54-64. © 2016 Wiley Periodicals, Inc.

Search for identical octapeptides in unrelated proteins: Structural plasticity revisited.

Since proteins are dynamic in nature, they can alter their local structure in response to changes in their environment factors such as temperature, pH, phosphorylation, and binding of other small molecules. These conformational changes are extremely important for the correct folding and functioning of proteins. There are also a number of diseases associated with protein conformational change such as amyloid diseases. To stimulate research into the above factors which specify one conformation over another, different theoretical models have been proposed and tested against sequence similar distant structure protein fragments. In order to simplify the computational complexity of identifying conformational changes in proteins, various local sequence search algorithms were employed and the structural plasticity in unrelated proteins was examined by various research groups. In the present work, we revisit the mechanism of structural plasticity in unrelated proteins with increased number of structures in Protein Data Bank by comparing identical octapeptides in unrelated proteins with dictionary of protein secondary structure extracted from existing experimental data. Our goal is to bring out the influence of hydrophobic residues, hydrophilic residues, flanking residues, difference in secondary structural propensities of surrounding residues, difference in phi-psi angles and local and nonlocal interactions in identical octapeptides adopting different conformations. Also we have used surrounding hydrophobicity, environment dependent interaction energy, atomic mean force potential, structural unit contacts and difference profiles models to explore the factors which cause structural plasticity. The results discussed here may provide insights into protein folding, design and function.

Comparative Analysis of the Molecular Adjuvants and Their Binding Efficiency with CR1.

There are so many obstacles in developing a vaccine or vaccine technology for diseases like cancer and human immunodeficiency virus infection. While developing vaccines that target specific infection, molecular adjuvants are indispensable. These molecular adjuvants act as a vaccine delivery vehicle to the immune system to increase the effectiveness of the specific antigens. In the present work, a computational study has been done on molecular adjuvants like IgGFc, GMCSF and C3d to find out how efficiently they are binding to CR1. Sequence, structure and mutational analysis are performed on the molecular adjuvants to understand the features important for their binding with the receptor. Results obtained from our study indicate that the adjuvant IgGFc complexed with the receptor CR1 has the best binding efficiency, which can be used further to develop better vaccine technologies.

Analysis of secondary structural and physicochemical changes in protein-protein complexes.

Conformation switching in protein-protein complexes is considered important for the molecular recognition process. Overall analysis of 123 protein-protein complexes in a benchmark data-set showed that 6.8% of residues switched over their secondary structure conformation upon complex formation. Amino acid residue-wise preference for conformation change has been analyzed in binding and non-binding site residues separately. In this analysis, residues such as Ser, Leu, Glu, and Lys had higher frequency of secondary structural conformation change. The change of helix to coil and sheet to coil conformation and vice versa has been observed frequently, whereas the conformation change of helix to extended sheet occurred rarely in the studied complexes. Influence of conformation change toward the N and C terminal on either side of the binding site residues has been analyzed. Further, analysis on φ and ψ angle variation, conservation, stability, and solvent accessibility have been performed on binding site residues. Knowledge obtained from the present study could be effectively employed in the protein-protein modeling and docking studies.

Analysis of dihedral angle preferences for alanine and glycine residues in alpha and beta transmembrane regions.

For the past 50 years, the Ramachandran map has been used effectively to study the protein structure and folding. However, though extensive analysis has been done on dihedral angle preferences of residues in globular proteins, related studies and reports of membrane proteins are limited. It is of interest to explore the conformational preferences of residues in transmembrane regions of membrane proteins which are involved in several important and diverse biological processes. Hence, in the present work, a systematic comparative computational analysis has been made on dihedral angle preferences of alanine and glycine in alpha and beta transmembrane regions (the two major classes of transmembrane proteins) with the aid of the Ramachandran map. Further, the conformational preferences of residues in transmembrane regions were compared with the non-transmembrane regions. We have extracted cation-pi interacting residues present in transmembrane regions and explored the dihedral angle preferences. From our observations, we reveal the higher percentage of occurrences of glycine in alpha and beta transmembrane regions than other hydrophobic residues. Further, we noted a clear shift in ψ-angle preferences of glycine residues from negative bins in alpha transmembrane regions to positive bins in beta transmembrane regions. Also, cation-pi interacting residues in beta transmembrane regions avoid preferring ψ-angles in the range of -59° to -30°. In this article, we insist that the studies on preferences of dihedral angles in transmembrane regions, thorough understanding of structure and folding of transmembrane proteins, can lead to modeling of novel transmembrane regions towards designing membrane proteins.

Comparative analysis of the molecular adjuvants and their binding efficiency with CR1.

There are so many obstacles in developing a vaccine or vaccine technology for diseases like Cancer and Human Immunodeficiency Virus (HIV) infection. While developing vaccines that targets specific infection, molecular adjuvants are indispensable. These molecular adjuvants act as a vaccine delivery vehicle to the immune system to increase the effectiveness of the specific antigens. In the present work, a computational study has been done on molecular adjuvants like IgGFc, GMCSF and C3d to find out how efficiently they are binding to CR1. Sequence, structure and mutational analysis are performed on the molecular adjuvants to understand the features important for their binding with the receptor. Results obtained from our study indicate that the adjuvant IgGFc complexed with the receptor CR1 has the best binding efficiency, which can be used further to develop better vaccine technologies.