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Combining Ramachandran plot and molecular dynamics simulation for structural-based variant classification: Using TP53 variants as model.

Abstract：

:The wide application of new DNA sequencing technologies is generating vast quantities of genetic variation data at unprecedented speed. Developing methodologies to decode the pathogenicity of the variants is imperatively demanding. We hypothesized that as deleterious variants may function through disturbing structural stability of their affected proteins, information from structural change caused by genetic variants can be used to identify the variants with deleterious effects. In order to measure the structural change for proteins with large size, we designed a method named RP-MDS composed of Ramachandran plot (RP) and Molecular Dynamics Simulation (MDS). Ramachandran plot captures the variant-caused secondary structural change, whereas MDS provides a quantitative measure for the variant-caused globular structural change. We tested the method using variants in TP53 DNA binding domain of 219 residues as the model. In total, RP-MDS identified 23 of 38 (60.5%) TP53 known Pathogenic variants and 17 of 42 (41%) TP53 VUS that caused significant changes of P53 structure. Our study demonstrates that RP-MDS method provides a powerful protein structure-based tool to screen deleterious genetic variants affecting large-size proteins.

journal_name

Comput Struct Biotechnol J

journal_title

Computational and structural biotechnology journal

authors

Tam B,Sinha S,Wang SM

doi

10.1016/j.csbj.2020.11.041

subject

Has Abstract

pub_date

2020-12-02 00:00:00

pages

4033-4039

issn

2001-0370

pii

S2001-0370(20)30508-0

journal_volume

18

pub_type

杂志文章

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