A computational journey in anticancer drug discovery: Exploring AKT1 inhibition by novel oxadiazoles using molecular docking, ADMET, density functional theory and molecular dynamic simulation

IF 2.6 4区 生物学 Q2 BIOLOGY
Gauri Alias Pooja Naik , Omkar Paradkar , Vishnu Sharma , Shubham Kumar , Pawan Gupta , Pankaj Wadhwa
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引用次数: 0

Abstract

AKT, also called (PKB) Protein Kinase B, is critical for cell proliferation, metabolism, and survival, with its dysfunction linked to various diseases, including cancer. The oxadiazole nucleus has demonstrated significant anticancer activity in literature surveys. The motivation for conducting this study stems from the fact that, despite numerous investigations into novel therapeutic targets and lead compounds, the inhibition of AKT1 presents limited treatment options due to various adverse drug reactions and specificity issues, given that AKT1 exists in three isoforms. So, this study aimed to identify top-hit molecules with 1,3,4 oxadiazole scaffold targeting the AKT1 enzyme by ligand-based virtual screening to produce a dataset library from PubChem database, structure-based virtual screening followed by ADMET profiling, DFT, and molecular dynamic simulation study as an innovative approach, as there is a dearth of AKT1 inhibitors that comprise oxadiazole in the market and clinical trials. The study employs a combination of advanced computational methods, including virtual screening, molecular docking, molecular dynamics simulations, density functional theory calculations, and ADMET predictions. This comprehensive approach offers a thorough investigation of prospective drug candidates. A comprehensive pharmacoinformatic analysis was conducted on a library of compounds containing oxadiazole rings. A total of 1000 compounds were analyzed through virtual screening utilizing molecular docking and subsequent validation, aiming to identify inhibitors that exhibit a strong affinity for binding for AKT1 (PDB ID: 3O96). Thus, 24 compounds demonstrating binding affinities analogous to the standard emerged as the most promising medicinal prospects and underwent ADMET profiling, and DFT studies followed by a molecular dynamic study on the best 2 compounds. Moreover, these compounds found by ADMET profiling showed suitable pharmacokinetic and pharmacodynamic profiles and were non-toxic using DFT analysis determining ideal structural characteristics. Especially showing comparable stability to the reference molecule over 200 ns in MD simulations, the best top 2 hit compounds having binding affinity −10.7 kcal/mol for PCOS_ 133 (CID-164189) and −11.6 kcal/mol for PCOS3_42 (CID-158973) emerged as potential AKT1 inhibitors for cancer therapy in comparison to −11.6 kcal/mol and −14.7 kcal/mol binding affinity of Miransertib reference drug and IQO cocrystallized ligand of AKT1 protein PDB code 3O96. LEU-210, LEU-264, ASP-292, and TRP-80 are the important amino acid residues required for AKT1 inhibition. These results provide important new perspectives for the rational design and optimization of oxadiazole-based AKT1/PKB inhibitors, therefore laying a strong basis for experimental validation including further in-vitro and in vivo studies and PKB inhibitor development.
抗癌药物发现的计算之旅:利用分子对接、ADMET、密度泛函理论和分子动态模拟探索新型噁二唑对 AKT1 的抑制作用。
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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