Identification of potential inhibitors, conformational dynamics, and mechanistic insights into mutant Kirsten rat sarcoma virus (G13D) driven cancers

Abstract

The mutations at the hotspot region of K‐Ras result in the progression of cancer types. Our study aimed to explore the small molecule inhibitors against the G13D mutant K‐Ras model with anti‐cancerous activity from food and drug administration (FDA)‐approved drug compounds. We implemented several computational strategies such as pharmacophore‐based virtual screening, molecular docking, absorption, distribution, metabolism and excretion features, and molecular simulation to ensure the identified hit compounds have potential efficacy against G13D K‐Ras. We found that the FDA‐approved compounds, namely, azelastine, dihydrocodeine, paroxetine, and tramadol, are potential candidates to inhibit the action of G13D mutant K‐Ras. All four compounds exhibited similar binding patterns of sotorasib, and a structural binding mechanism with significant hydrophobic contacts. The descriptor features from the QikProp of all four compounds are within allowable limits compared to sotorasib drug. Consequently, a molecular simulation result emphasized that the dihydrocodeine and tramadol exhibited less fluctuation, minimal basin, significant h‐bonds, and potent inhibition against G13D K‐Ras. As a result, the current research identifies prospective K‐Ras inhibitors that could be further improved with biochemical analysis for precision medicine against K‐Ras‐driven cancers.

Exploring the natural products chemical space to abrogate the F3L-dsRNA interface of monkeypox virus to enhance the immune responses using molecular screening and free energy calculations

“…This approach specifically targets proteins implicated in the advancement of an infection, allowing scientists to streamline the selection of promising drug candidates before investing resources and time in laborious experimental procedures. However, the molecular dynamic simulation analysis offering detailed insights into the behavior of drug-protein complexes at the molecular level ( Kumar et al, 2021a ; Kumar et al, 2021b ; Kumar and Doss, 2021 ; Tayubi et al, 2022 ; Abduljaleel et al, 2023 ). As part of the current investigation, virtual drug design tools were employed to screen the South African natural database against the F3 protein.…”

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease

“…Recently, whole exome sequencing techniques have been utilized to understand the mutational mechanisms in several diseases, including cancer (Kumar et al 2022 ). These advanced techniques also help to comprehend the structural mechanisms disrupted upon mutations using computer simulations and docking methods (Udhaya Kumar et al 2022 ) (Kumar and Priya Doss 2021 ) (Tayubi et al 2022 ).…”

Bitter-RF: A random forest machine model for recognizing bitter peptides

“…At present, computational methods have been carried out to study peptides (13,14). Models based on the quantitative structure of bitter taste relationship (QSBR), including multiple linear regression, the support vector machine (SVM), and artificial neural network (ANN), have been used to predict bitter peptides (2,(15)(16)(17)(18)(19)(20)(21).…”