R. Rajasekaran

Bio: R. Rajasekaran is an academic researcher from VIT University. The author has contributed to research in topic(s): Mutant & Single-nucleotide polymorphism. The author has an hindex of 15, co-authored 69 publication(s) receiving 758 citation(s). Previous affiliations of R. Rajasekaran include Department of Biotechnology.

Identification and in silico analysis of functional SNPs of the BRCA1 gene.

Abstract: Single-nucleotide polymorphisms (SNPs) play a major role in the understanding of the genetic basis of many complex human diseases. Also, the genetics of human phenotype variation could be understood by knowing the functions of these SNPs. It is still a major challenge to identify the functional SNPs in a disease-related gene. In this work, we have analyzed the genetic variation that can alter the expression and the function of the BRCA1 gene using computational methods. Of the total 477 SNPs, 65 were found to be nonsynonymous (ns) SNPs. Among the 14 SNPs in the untranslated region, 4 were found in the 5′ and 10 were found in the 3′ untranslated region (UTR). It was found that 16.9% of the nsSNPs were damaging, by both the SIFT and the PolyPhen servers. The UTR Resource tool suggested that 2 of 4 SNPs in the 5′ UTR and 3 of 10 SNPs in the 3′ UTR might change the protein expression levels. We identified major mutations from proline to serine at positions 1776 and 1812 of the native protein of the BRCA1 gene. From a comparison of the stabilizing residues of the native and mutant proteins, we propose that an nsSNP (rs1800751) could be an important candidate for the breast cancer caused by the BRCA1 gene.

A novel computational and structural analysis of nsSNPs in CFTR gene.

Abstract: Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.

Applications of computational algorithm tools to identify functional SNPs

Abstract: Single nucleotide polymorphisms (SNPs) are the most common type of genetic variations in humans Understanding the functions of SNPs can greatly help to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols To explore possible relationships between genetic mutation and phenotypic variation, different computational algorithm tools like Sorting Intolerant from Tolerant, Polymorphism Phenotyping, UTRscan, FASTSNP, and PupaSuite were used for prioritization of high-risk SNPs in coding region (exonic nonsynonymous SNPs) and noncoding regions (intronic and exonic 5' and 3'-untranslated region (UTR) SNPs) In this work, we have analyzed the SNPs that can alter the expression and function of transcriptional factor TP53 as a pipeline and for providing a guide to experimental work We identified the possible mutations and proposed modeled structure for the mutant proteins and compared them with the native protein These nsSNPs play a critical role in cancer association studies aiming to explain the disparity in cancer treatment responses as well as to improve the effectiveness of the cancer treatments Our results endorse the study with in vivo experimental protocols

Studies on flexibility and binding affinity of Asp25 of HIV-1 protease mutants.

Abstract: We have investigated and highlighted the behavior of binding residue, Asp25 by computational analysis, which play an important role in understanding docking process with drug molecule, Ritonavir (Norvir®) and the flexibility nature of the Human Immunodeficiency Virus-1 (HIV-1) protease enzyme. It is well known that Ritonavir is a potent and a selective HIV-1 protease inhibitor. Molecular dockings were performed in order to gain insights regarding the binding mode of this inhibitor. In our analysis, we observed Ritonavir had different rank orders of scores against different mutant of this enzyme. Asp25 of the enzyme was found to be the active site for all the mutants. The results clearly suggest that Ritonavir is not able to appropriately bind at the active site of each HIV-1 protease mutant due to RMSD difference of the amino acid (Asp) at the position 25 of all mutants. These findings support the concept that 3D space of active site is a qualitative assessment for binding affinity of inhibitor with an enzyme. The investigation on the flexibility nature of Asp25 by normal mode analysis, show that binding residue posses less flexibility due to its solvation potential. The overall analysis of our study brings clarity to the binding behavior with respect to the different mutants with Ritonavir on the basis RMSD and also on the flexible nature of HIV-1 protease enzyme with respect to Asp25 position.

Effect of deleterious nsSNP on the HER2 receptor based on stability and binding affinity with herceptin: a computational approach.

Abstract: In this study, we identified the most deleterious non-synonymous SNP of ERBB2 (HER2) receptors by its stability and investigated its binding affinity with herceptin. Out of 135 SNPs, 10 are nsSNPs in the coding region, in which one of the nsSNP (SNPid rs4252633) is commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen servers. With this effort, we modelled the mutant HER2 protein based on this deleterious nsSNP (rs4252633). The modeled mutant showed less stability than native HER 2 protein, based on both total energy of the mutant and stabilizing residues in the mutant protein. This is due to a deviation between the mutant and the native HER2, having an RMSD of about 2.81 A. Furthermore, we compared the binding efficiency of herceptin with native and mutant HER2 receptors. We found that herceptin has a high binding affinity with mutant HER2 receptor, with a binding energy of -24.40 kcal/mol, as compared to the native type, which has a binding energy of -15.26 kcal/mol due to six-hydrogen bonding and two salt bridges exist between herceptin and the mutant type, whereas the native type establishes four hydrogen bonds and two salt bridges with herceptin. This analysis portrays that mutant type has two additional hydrogen bonds with herceptin compared with the native type. Normal mode analysis also showed that the two amino acids, namely Asp596 and Glu598 of mutant HER2, forming additional hydrogen bonding with herceptin, had a slightly higher flexibility than the native type. Based on our investigations, we propose that SNPid rs4252633 could be the most deleterious nsSNP for HER2 receptor, and that herceptin could be the best drug for mutant compared to the native HER2 target.

Methods in Enzymology.

Abstract: I read this book the same weekend that the Packers took on the Rams, and the experience of the latter event, obviously, colored my judgment. Although I abhor anything that smacks of being a handbook (like, \"How to Earn a Merit Badge in Neurosurgery\") because too many volumes in biomedical science already evince a boyscout-like approach, I must confess that parts of this volume are fast, scholarly, and significant, with certain reservations. I like parts of this well-illustrated book because Dr. Sj6strand, without so stating, develops certain subjects on technique in relation to the acquisition of judgment and sophistication. And this is important! So, given that the author (like all of us) is somewhat deficient in some areas, and biased in others, the book is still valuable if the uninitiated reader swallows it in a general fashion, realizing full well that what will be required from the reader is a modulation to fit his vision, propreception, adaptation and response, and the kind of problem he is undertaking. A major deficiency of this book is revealed by comparison of its use of physics and of chemistry to provide understanding and background for the application of high resolution electron microscopy to problems in biology. Since the volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of The instrument and its ancillary tools are simply and well presented. The potential use of chemical or cytochemical information as it relates to biological fine structure , however, is quite deficient. I wonder when even sophisticated morphol-ogists will consider fixation a reaction and not a technique; only then will the fundamentals become self-evident and predictable and this sine qua flon will become less mystical. Staining reactions (the most inadequate chapter) ought to be something more than a technique to selectively enhance contrast of morphological elements; it ought to give the structural addresses of some of the chemical residents of cell components. Is it pertinent that auto-radiography gets singled out for more complete coverage than other significant aspects of cytochemistry by a high resolution microscopist, when it has a built-in minimal error of 1,000 A in standard practice? I don't mean to blind-side (in strict football terminology) Dr. Sj6strand's efforts for what is \"routinely used in our laboratory\"; what is done is usually well done. It's just that …

Patterns of Somatic Mutation in Human Cancer Genomes

Abstract: AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore PL02-05 All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Discrete molecular dynamics studies of the folding of a protein-like model

Abstract: Background: Many attempts have been made to resolve in time the folding of model proteins in computer simulations. Different computational approaches have emerged. Some of these approaches suffer from the insensitivity to the geometrical properties of the proteins (lattice models), while others are computationally heavy (traditional MD). Results: We use a recently-proposed approach of Zhou and Karplus to study the folding of the protein model based on the discrete time molecular dynamics algorithm. We show that this algorithm resolves with respect to time the folding --- unfolding transition. In addition, we demonstrate the ability to study the coreof the model protein. Conclusion: The algorithm along with the model of inter-residue interactions can serve as a tool to study the thermodynamics and kinetics of protein models.