In-Silico Identification and Characterization of KRAS G12C Inhibitors: Molecular Docking and ADMET Analysis

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.

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Publication Details

Journal
Current Indian Science
Published
2025-06-13
DOI
https://doi.org/10.2174/012210299x372076250528015126
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

In-Silico Identification and Characterization of KRAS G12C Inhibitors: Molecular Docking and ADMET Analysis

Shubham Bhosale, Palde Omkar Dinkar
Current Indian Science
Computational Drug Discovery Methods
article

In-Silico Identification and Characterization of KRAS G12C Inhibitors: Molecular Docking and ADMET Analysis

Shubham Bhosale, Palde Omkar Dinkar
article en

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.

Current Indian ScienceVol. 03
Hindu College of Pharmacy (IN)
Good health and well-being
Openalex Percentile: Top 85%
Computational Drug Discovery Methods
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