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Bringing Structural Implications and Deep Learning-Based Drug Identification for KRAS Mutants by Aamir Mehmood; Aman Chandra Kaushik; Qiankun Wang; Cheng-Dong Li; Dong-Qing Wei is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Bringing Structural Implications and Deep Learning-Based Drug Identification for KRAS Mutants about?

Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten Rat Sarcoma (KRAS) harboring codons 13 and 61 mutations. The objective for this study is to search for clinically important codon 61 mutations and analyze how they affect the protein structural dynamics. Additionally, a deep-learning approach is used to carry out a similarity search for potential compounds that might have a comparatively better affinity. Public databases like The Cancer Genome Atlas and Genomic Data Commons were accessed for obtaining the data regarding mutations that are associated with colon cancer. Multiple analysis such as genomic alteration landscape, survival analysis, and systems biology-based kinetic simulations were carried out to predict dynamic changes for the selected mutations. Additionally, a molecular dynamics simulation of 100 ns for all the seven shortlisted codon 61 mutations have been conducted, which revealed noticeable deviations. Finally, the deep learning-based predicted compounds were docked with the KRAS 3D conformer, showing better affinity and good docking scores as compared to the already existing drugs. Taking together the outcomes of syst

Who reads Bringing Structural Implications and Deep Learning-Based Drug Identification for KRAS Mutants?

Author

Aamir Mehmood; Aman Chandra Kaushik; Qiankun Wang; Cheng-Dong Li; Dong-Qing Wei

Publisher

American Chemical Society (ACS)

Published

2021

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Physical Sciences)