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Exploring the use of molecular dynamics in assessing protein variants for phenotypic alterations

Garg, A and Pal, D (2019) Exploring the use of molecular dynamics in assessing protein variants for phenotypic alterations. In: Human Mutation, 40 (9). pp. 1424-1435.

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Official URL: https://doi.org/10.1002/humu.23800


With the advent of rapid sequencing technologies, making sense of all the genomic variations that we see among us has been a major challenge. A plethora of algorithms and methods exist that try to address genome interpretation through genotype–phenotype linkage analysis or evaluating the loss of function/stability mutations in protein. Critical Assessment of Genome Interpretation (CAGI) offers an exceptional platform to blind-test all such algorithms and methods to assess their true ability. We take advantage of this opportunity to explore the use of molecular dynamics simulation as a tool to assess alteration of phenotype, loss of protein function, interaction, and stability. The results show that coarse-grained dynamics based protein flexibility analysis on 34 CHEK2 and 1719 CALM1 single mutants perform reasonably well for class-based predictions for phenotype alteration and two-thirds of the predicted scores return a correlation coefficient of 0.6 or more. When all-atom dynamics is used to predict altered stability due to mutations for Frataxin protein (8 cases), the predictions are comparable to the state-of-the-art methods. The competitive performance of our straightforward approach to phenotype interpretation contrasts with heavily trained machine learning approaches, and open new avenues to rationally improve genome interpretation.

Item Type: Journal Article
Publication: Human Mutation
Publisher: John Wiley and Sons Inc.
Additional Information: The copyright for this article belongs to the Authors.
Keywords: frataxin; mutant protein; protein variant; CALM2 protein, human; calmodulin; checkpoint kinase 2; CHEK2 protein, human; iron binding protein, algorithm; Article; correlation coefficient; gene mutation; genome; genotype phenotype correlation; linkage analysis; machine learning; molecular dynamics; phenotypic variation; priority journal; protein function; protein interaction; protein stability; chemistry; genetic association study; genetics; human; molecular dynamics; mutation; phenotype, Algorithms; Calmodulin; Checkpoint Kinase 2; Genetic Association Studies; Humans; Iron-Binding Proteins; Machine Learning; Molecular Dynamics Simulation; Mutation; Phenotype; Protein Stability
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 12 Oct 2022 12:03
Last Modified: 12 Oct 2022 12:03
URI: https://eprints.iisc.ac.in/id/eprint/77365

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