In-Silico Identification and Characterization of KRAS G12C Inhibitors: Molecular Docking and ADMET Analysis
Year: 2025
Type: article
Abstract: Aims: This study aims to identify and evaluate novel KRAS G12C inhibitors using in-silico methods, focusing on molecular docking and ADMET profiling to optimize binding affinity, pharmacokinetics, and safety profiles. Background: The KRAS G12C mutation is a key driver of oncogenesis in aggressive cancers, including non-small cell lung cancer. Although inhibitors such as sotorasib have been developed, challenges like hepatotoxicity and resistance limit their clinical use. Objectives: This study seeks to design and assess potential KRAS G12C inhibitors with superior binding interactions and pharmacokinetic properties compared to existing drugs. Materials and Methods: Molecular docking simulations were conducted to evaluate the binding affinities of inhibitors, followed by ADMET profiling to assess pharmacokinetics, drug-likeness, and toxicity. Results: Novel compounds, such as CID_137278727, demonstrated higher binding affinities (-10.8 kcal/mol) and favourable ADMET profiles compared to sotorasib (-8.1 kcal/mol). Key interactions with residues GLU62, TYR96, and CYS12 were identified, though hepatotoxicity remains a concern. Conclusion: In-silico approaches have identified promising KRAS G12C inhibitors with enhanced efficacy and pharmacokinetics, highlighting the potential of computational methods in advancing targeted therapies for KRAS-driven cancers.
Source: Current Indian Science
Authors: Palde Omkar Dinkar, Sachin Bhosale
Institution: SMBT College of Pharmacy
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411256158