Kamaraj B

Purohit R.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

In-silico analysis of Betaine Aldehyde Dehydrogenase2 of Oryza sativa and significant mutations responsible for fragrance

Journal of Plant Interactions

Genome sequencing has overflowed the databases with huge amount of SNP data. Although the amount of detected single nucleotide polymorphisms (SNPs) is rising exponentially every day, we still lag behind in characterization techniques. Implementing computational platforms to determine the pathogenecity associated with the SNPs can provide a probable solution to this problem. To improve the prediction quality for SNP characterization methods, we implemented machine learning support vector classification method. Total 557 non-synonymous amino acid variants were collected from CENP family proteins, excluding CENPE. Multivariate simulation of associated changes in biological phenomena's for each SNPs was computed through available SNP analysis platforms. Support vector model was designed using training dataset and the raw classification data was subjected to the classification hyperplane. We observed multiple evidences of cancer associated genetic mutations in CENPI, CENPJ, CENPK, CENPL and CENPX protein. The former four proteins have showed positive hits in cosmic database for mutations in tumour samples, but CENPX has never been reported before for the cancer associated outcomes. Since CENPX has been recently classified and not much functional and pathological insight has been, the results obtained in this study will serve as a starting point for future investigation on cancer research in association to CENPX protein.

Interdisciplinary Sciences: Computational Life Sciences

Identifying novel oncogenes: A machine learning approach

Oculocutaneous albinism type III (OCA3), caused by mutations of TYRP1 gene, is an autosomal recessive disorder characterized by reduced biosynthesis of melanin pigment in the hair, skin, and eyes. The TYRP1 gene encodes a protein called tyrosinase-related protein-1 (Tyrp1). Tyrp1 is involved in maintaining the stability of tyrosinase protein and modulating its catalytic activity in eumelanin synthesis. Tyrp1 is also involved in maintenance of melanosome structure and affects melanocyte proliferation and cell death. In this work we implemented computational analysis to filter the most probable mutation that might be associated with OCA3. We found R326H and R356Q as most deleterious and disease associated by using PolyPhen 2.0, SIFT, PANTHER, I-mutant 3.0, PhD-SNP, SNP&GO, Pmut, and Mutpred tools. To understand the atomic arrangement in 3D space, the native and mutant (R326H and R356Q) structures were modelled. Finally the structural analyses of native and mutant Tyrp1 proteins were investigated using molecular dynamics simulation (MDS) approach. MDS results showed more flexibility in native Tyrp1 structure. Due to mutation in Tyrp1 protein, it became more rigid and might disturb the structural conformation and catalytic function of the structure and might also play a significant role in inducing OCA3. The results obtained from this study would facilitate wet-lab researches to develop a potent drug therapies against OCA3.

Fulltext

BioMed Research International

In SilicoScreening and Molecular Dynamics Simulation of Disease-Associated nsSNP in TYRP1 Gene and Its Structural Consequences in OCA3

Amino Acids

In silico investigation of molecular mechanism of laminopathy caused by a point mutation (R482W) in lamin A/C protein

Gene

Computational investigation of pathogenic nsSNPs in CEP63 protein

Journal of Biomolecular Structure and Dynamics

Studies on Adaptability of Binding Residues Flap Region of TMC-114 Resistance HIV-1 Protease Mutants

Remarkable advances have been made in the drug therapy of tuberculosis. However much remains to be learned about the molecular and structural basis of drug resistance in Mycobacterium tuberculosis. It is known that, activation of Isoniazid (INH) is mediated by Mycobacterium tuberculosis catalase-peroxidase (MtBKatG) and mutation at position 315 (serine to threonine) leads to resistance. We have conducted studies on the drug resistance through docking and binding analysis supported by time-scale (∼ 1000 ps) and unrestrained all-atom molecular dynamics simulations of wild and mutant MtBKatG. The study showed conformational changes of binding residues. Mutant (S315T) showed high docking score and INH binding affinity as compared to wild enzyme. In molecular dynamics simulation, mutant enzyme exhibited less structure fluctuation at INH binding residues and more degree of fluctuation at C-terminal domain compared to wild enzyme. Our computational studies and data endorse that MtBKatG mutation (S315T) decrease the flexibility of binding residues and made them rigid by altering the conformational changes, in turn it hampers the INH activity. We ascertain from this work that, this study on structural mechanism of resistance development in Mycobacterium tuberculosis would lead to new therapeutics based on the result obtained in this study.

Journal of Molecular Modeling

Relationship between mutation of serine residue at 315th position in M. tuberculosis catalase-peroxidase enzyme and Isoniazid susceptibility: An in silico analysis

To understand the origin of the apparent low sensitivity to mutations exhibited by Darunavir, the binding energetics of this inhibitor to the HIV-1 protease was studied. Our research indicates that the observed effectiveness of Darunavir against the wild type HIV-1 protease is due to an extremely high affinity towards the wild-type and a relatively mild effect to the I50V and I54M mutations is due to low affinity towards the inhibitor. Good affinity of Darunavir accounts for the additive effects of well accommodation at binding site, good ligand-receptor electrostatic and van der waals energy while, the low susceptibility to I50V and I54M can be rationalized in terms of flexibility in the binding site residues that do not permit drug accommodation to the binding site distortions created by the mutation. The major flap mutations I50V and I54M lower the binding affinity of Darunavir by altering the position of binding site residues in 3D space. It decreases the electrostatic and van der waals interaction energy and further reduction in total receptor-ligand interaction energy. The results summarized in this paper emphasize the importance of shape complementarity and protein flexibility analysis of binding residual interactions in drug design. These data together with an interaction energy and flexibility analysis have established rigorous guidelines for the design of new and more powerful inhibitors. The principles learned from the HIV-1 protease can be applied to other design problems.

Structural basis for the resilience of Darunavir (TMC114) resistance major flap mutations of HIV-1 protease

In-silico analysis of Betaine Aldehyde Dehydrogenase2 ofOryza sativaand significant mutations responsible for fragrance

Journal	Journal of Plant Interactions
Publisher	Informa UK Limited
ISSN	1742-9145
Open Access	0