Computational Approaches and Resources in Single Amino Acid Substitutions Analysis Toward Clinical Research

Doss, C. George Priya; Chakraborty, Chiranjib; Narayan, Vaishnavi; Kumar, Dhirendra

doi:10.1016/b978-0-12-800168-4.00010-x

Cited by 23 publications

(8 citation statements)

References 456 publications

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“…Obtaining the biological significance of every nsSNP by wet laboratory technique remains impossible due to exponential increment in SNPs number. Instead, we can utilize in silico and statistical methods to understand the effect of a mutation on structure and function of biological protein (George Priya Doss et al, 2014a, 2014b. This approach could save time, money, and manpower and can be used to cure millions of patients by precise diagnosis and appropriate medicines.…”

Section: Discussionmentioning

confidence: 98%

Impact of I30T and I30M substitution in MPZ gene associated with Dejerine–Sottas syndrome type B (DSSB): A molecular modeling and dynamics

Agrahari

2015

Journal of Theoretical Biology

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Section: Discussionmentioning

confidence: 98%

Impact of I30T and I30M substitution in MPZ gene associated with Dejerine–Sottas syndrome type B (DSSB): A molecular modeling and dynamics

Agrahari

2015

Journal of Theoretical Biology

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“…The scoring algorithm evaluates and ranks the predicted ligand conformations in the target. The various scoring functions used by scoring algorithms include a force-field based function (computes binding energy considering non-covalent interactions, torsional forces, and entropy) and empirical free energy-based function [39,45,49].…”

Section: Molecular Docking Studiesmentioning

confidence: 99%

In-Silico Methods for Investigating the Effect of Single Nucleotide Polymorphisms on the Structure and Function of Proteins: A Review

Asiedu¹

2019

Preprint

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Single nucleotide polymorphisms (SNP) are associated with diseases and drug response variabilities in humans. Elucidating the damaging and disease-associated SNPs using wet-laboratory approaches can be challenging and resource-demanding due to the large number of SNPs in the human genome. Due to the growth in the field of computational biology and bioinformatics, algorithms have been developed to help screen and filter out the most deleterious SNPs that are worth considering for wet-laboratory studies. Here we review the existing in-silico based methods used to predict and characterize the effects of SNPs on protein structure and function. This cutting-edge approach will facilitate the search for novel therapeutics, help understand the etiology of diseases and fast-track the personalized medicine agenda.

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“…The nonsynonymous SNPs are further divided into missense mutations and nonsense mutations. The coding synonymous SNPs have a low effect over protein structure, while the nonsynonymous SNPs have a great impact on the protein structure and higher risk of diseases [ 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases

2021

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Peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PPARGC1A) regulates the expression of energy metabolism’s genes and mitochondrial biogenesis. The essential roles of PPARGC1A encouraged the researchers to assess the relation between metabolism-related diseases and its variants. To study Gly482Ser (+1564G/A) single-nucleotide polymorphism (SNP) after PPARGC1A modeling, we substitute Gly482 for Ser482. Stability prediction tools showed that this substitution decreases the stability of PPARGC1A or has a destabilizing effect on this protein. We then utilized molecular dynamics simulation of both the Gly482Ser variant and wild type of the PPARGC1A protein to analyze the structural changes and to reveal the conformational flexibility of the PPARGC1A protein. We observed loss flexibility in the RMSD plot of the Gly482Ser variant, which was further supported by a decrease in the SASA value in the Gly482Ser variant structure of PPARGC1A and an increase of H-bond with the increase of β-sheet and coil and decrease of turn in the DSSP plot of the Gly482Ser variant. Such alterations may significantly impact the structural conformation of the PPARGC1A protein, and it might also affect its function. It showed that the Gly482Ser variant affects the PPARGC1A structure and makes the backbone less flexible to move. In general, molecular dynamics simulation (MDS) showed more flexibility in the native PPARGC1A structure. Essential dynamics (ED) also revealed that the range of eigenvectors in the conformational space has lower extension of motion in the Gly482Ser variant compared with WT. The Gly482Ser variant also disrupts PPARGC1A interaction. Due to this single-nucleotide polymorphism in PPARGC1A, it became more rigid and might disarray the structural conformation and catalytic function of the protein and might also induce type 2 diabetes mellitus (T2DM), coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). The results obtained from this study will assist wet lab research in expanding potent treatment on T2DM.

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Computational Approaches and Resources in Single Amino Acid Substitutions Analysis Toward Clinical Research

Cited by 23 publications

References 456 publications

Impact of I30T and I30M substitution in MPZ gene associated with Dejerine–Sottas syndrome type B (DSSB): A molecular modeling and dynamics

Impact of I30T and I30M substitution in MPZ gene associated with Dejerine–Sottas syndrome type B (DSSB): A molecular modeling and dynamics

In-Silico Methods for Investigating the Effect of Single Nucleotide Polymorphisms on the Structure and Function of Proteins: A Review

Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases

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