2019
DOI: 10.1016/j.bpj.2019.06.030
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Structural Insights into Hearing Loss Genetics from Polarizable Protein Repacking

Abstract: Hearing loss is associated with $8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as ''variants of uncertain significance'' to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information is biophysical simulation, although input protein structures often contain defects because of limitations in experimental data and/or only distant… Show more

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Cited by 14 publications
(23 citation statements)
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“…Additional computational methods were used to predict the structural effects of the DNM on one of the most reported cleft candidate gene products. Starting from the predicted protein structures generated by AlphaFold2, we locally optimized the structure to relax its backbone torsions and performed sidechain optimization (i.e., sidechain repacking ) to find the most favorable position for each sidechain and improve MolProbity scores 69 . Both optimizations were done with the AMOEBA polarizable force field 70 , 71 .…”
Section: Methodsmentioning
confidence: 99%
“…Additional computational methods were used to predict the structural effects of the DNM on one of the most reported cleft candidate gene products. Starting from the predicted protein structures generated by AlphaFold2, we locally optimized the structure to relax its backbone torsions and performed sidechain optimization (i.e., sidechain repacking ) to find the most favorable position for each sidechain and improve MolProbity scores 69 . Both optimizations were done with the AMOEBA polarizable force field 70 , 71 .…”
Section: Methodsmentioning
confidence: 99%
“…MolProbity performed contact analysis between all atoms, Ramachandran plot, and rotamer distribution (side chain) [36]. A lower MolProbity value indicates a higher structural quality [37].…”
Section: Ipbcc08610 God Structurementioning
confidence: 99%
“…Initial optimization was performed with a root mean square (RMS) convergence criterion of 0.8 kcal/mol/Å. Many-body energy expansions were applied to the refined structures using the AMOEBA forcefield to optimize side-chain placement and improve MolProbity scores [81]. The optimized structures were locally optimized again with an RMS convergence criterion of 0.1 kcal/mol/Å to finalize backbone torsions with the optimized sidechain placement.…”
Section: Deep Learning Prediction Of Full-length Laminmentioning
confidence: 99%