Evidence map›Paper›PMID 41351698›Full record

ArticleJournal of molecular modeling2025

In silico evaluation of anticancer peptide as a novel therapeutic agent against AURKA for targeting oral carcinogenesis.

Deepak Saravanan, Monisha Mohan

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Article in Journal of molecular modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Deepak SaravananDepartment of Sciences and Humanities, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram Chennai, 600127, Tamil Nadu, India.
Monisha MohanSchool of Interdisciplinary Design and Innovation, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram Chennai, Tamil Nadu, India. monisha@iiitdm.ac.in.ORCID http://orcid.org/0009-0008-2550-2601

Funding

Science and Engineering Research Board, Government of India EEQ/2022/001047
6 · The paper itself

Abstract

contextOral squamous cell carcinoma (OSCC) is a malignant epithelial neoplasm that affects the head and neck region and contributes to around 84-97% of oral cancer. Aurora kinase A is a key regulator of cell cycle progression and mitotic spindle assembly, which plays a critical role in the development and progression of OSCC. Knockdown of AURKA suppresses cell proliferation, migration, and invasion, while inducing apoptosis and reactive oxygen species generation in oral squamous cell carcinoma. This highlights the functional significance of AURKA in tumor progression and supports its potential as a novel therapeutic target. This study focuses on the in silico evaluation of anticancer peptides (ACPs) as potential inhibitors of AURKA, aiming to identify novel peptide-based drugs for targeting oral cancer.

methodsUsing advanced computational techniques, including molecular docking, molecular dynamics simulation, and pharmacokinetics profiling, we have screened 116 ACPs to evaluate their binding affinity, structural stability, and effect of mutagenesis. Interestingly, it was observed that AIP19 peptide demonstrated high binding affinity of -1049.8 and exhibited strong binding affinity to the catalytic pocket of AURKA, forming key hydrophobic interactions with residues such as Leu139, Phe144, Val147, Leu210, and Trp277, along with hydrogen bonds involving Lys143, Pro214, and Glu260. These interactions highlight its potential as a promising peptide-based inhibitor. Using the in silico mutagenesis approach, several peptide variants of AIP19 were generated to study the impact of specific mutations on the binding affinity. The results indicated that AIP19 mutations, including F5W, V6Y, V9W and M11Y could potentially enhance the peptide's binding affinity for AURKA. Furthermore, the drug likeness properties, low toxicity, and better biocompatibility of peptides highlight their potential as cancer-targeted therapeutics with minimal adverse effect. The stability and binding affinity of the AURKA-peptide complexes were evaluated using molecular dynamic simulation and MM GB/PBSA analysis. This study highlights the effectiveness of in silico methodologies in accelerating the discovery and optimization of peptide-based drugs. The identified ACPs represent a promising step toward the development of safe and effective therapeutics against OSCC, offering a novel approach to combat tumor progression that leverages structure-based peptide engineering to enhance binding affinity. This study lays the groundwork for future experimental validation of AIP19, highlighting its promise as a targeted therapeutic strategy for OSCC.

Indexed as

Antineoplastic AgentsAurora Kinase AMouth NeoplasmsPeptidesProtein Kinase InhibitorsHumansMolecular Docking SimulationMolecular Dynamics SimulationAntineoplastic AgentsAURKA protein, humanAurora Kinase APeptidesProtein Kinase InhibitorsAnticancer peptidesAURKAMM GB/PBSA analysisMolecular dockingMolecular Dynamics SimulationMutagenesisPharmacokinetic studies

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.