Jehad Zuhair Tayyeb , Imren Bayıl , Taha Alqahtani , Gabriel Vinícius Rolim Silva , Guilherme Bastos Alves , Al-Anood M. Al-Dies , Abdelkrim Guendouzi , Jonas Ivan Nobre Oliveira , Magdi E.A. Zaki
{"title":"通过分子对接、动力学模拟和 DFT 计算鉴定针对磷脂酰肌醇 3-激酶 (PI3K) 的治疗化合物","authors":"Jehad Zuhair Tayyeb , Imren Bayıl , Taha Alqahtani , Gabriel Vinícius Rolim Silva , Guilherme Bastos Alves , Al-Anood M. Al-Dies , Abdelkrim Guendouzi , Jonas Ivan Nobre Oliveira , Magdi E.A. Zaki","doi":"10.1016/j.compbiolchem.2025.108433","DOIUrl":null,"url":null,"abstract":"<div><div>Cancer is one of the leading causes of death worldwide and characterized by uncontrolled cell proliferation. The phosphatidylinositol 3-kinase (PI3K) is an enzyme, which is essential for regulating cell growth and survival, is often dysregulated in tumors. Currently available PI3K inhibitors (like Duvelisib) have significant side effects, highlighting the need for safer therapeutics. Gallic acid, a natural phenolic compound with remarkable antineoplastic properties, showcases a promising scaffold for drug development. The aim of this study is to identify potential PI3K inhibitors from gallic acid derivatives using advanced computational techniques such as PASS prediction, molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Five derivatives 21, 37, 44, 68 and 75 were selected based on their predicted antineoplastic activity among 90 derivatives, as well as the control drug Duvelisib. Compound 68 proved to be the most promising candidate, exhibiting strong binding affinity to the PI3K receptor, forming multiple hydrogen bonds with key residues, and showing stable interactions over 500 ns MD simulation. ADMET analysis revealed that compound 68 had favorable pharmacokinetic properties. Compound 21 also showed strong binding affinity but exhibited limitations in its pharmacokinetic profile. This study aims to improve our understanding of ligand-protein dynamics in PI3K inhibition and highlight the potential of gallic acid derivatives in developing safer and more effective PI3K inhibitors for cancer therapy. Our results support further experimental validation of compound 68 and suggest that gallic acid derivatives could contribute to the development of safer therapies.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"118 ","pages":"Article 108433"},"PeriodicalIF":2.6000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Therapeutic Compounds Targeting Phosphatidylinositol 3-Kinase (PI3K) Through Molecular Docking, Dynamics Simulation, and DFT Calculations\",\"authors\":\"Jehad Zuhair Tayyeb , Imren Bayıl , Taha Alqahtani , Gabriel Vinícius Rolim Silva , Guilherme Bastos Alves , Al-Anood M. Al-Dies , Abdelkrim Guendouzi , Jonas Ivan Nobre Oliveira , Magdi E.A. Zaki\",\"doi\":\"10.1016/j.compbiolchem.2025.108433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cancer is one of the leading causes of death worldwide and characterized by uncontrolled cell proliferation. The phosphatidylinositol 3-kinase (PI3K) is an enzyme, which is essential for regulating cell growth and survival, is often dysregulated in tumors. Currently available PI3K inhibitors (like Duvelisib) have significant side effects, highlighting the need for safer therapeutics. Gallic acid, a natural phenolic compound with remarkable antineoplastic properties, showcases a promising scaffold for drug development. The aim of this study is to identify potential PI3K inhibitors from gallic acid derivatives using advanced computational techniques such as PASS prediction, molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Five derivatives 21, 37, 44, 68 and 75 were selected based on their predicted antineoplastic activity among 90 derivatives, as well as the control drug Duvelisib. Compound 68 proved to be the most promising candidate, exhibiting strong binding affinity to the PI3K receptor, forming multiple hydrogen bonds with key residues, and showing stable interactions over 500 ns MD simulation. ADMET analysis revealed that compound 68 had favorable pharmacokinetic properties. Compound 21 also showed strong binding affinity but exhibited limitations in its pharmacokinetic profile. This study aims to improve our understanding of ligand-protein dynamics in PI3K inhibition and highlight the potential of gallic acid derivatives in developing safer and more effective PI3K inhibitors for cancer therapy. Our results support further experimental validation of compound 68 and suggest that gallic acid derivatives could contribute to the development of safer therapies.</div></div>\",\"PeriodicalId\":10616,\"journal\":{\"name\":\"Computational Biology and Chemistry\",\"volume\":\"118 \",\"pages\":\"Article 108433\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Biology and Chemistry\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1476927125000933\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927125000933","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Identification of Therapeutic Compounds Targeting Phosphatidylinositol 3-Kinase (PI3K) Through Molecular Docking, Dynamics Simulation, and DFT Calculations
Cancer is one of the leading causes of death worldwide and characterized by uncontrolled cell proliferation. The phosphatidylinositol 3-kinase (PI3K) is an enzyme, which is essential for regulating cell growth and survival, is often dysregulated in tumors. Currently available PI3K inhibitors (like Duvelisib) have significant side effects, highlighting the need for safer therapeutics. Gallic acid, a natural phenolic compound with remarkable antineoplastic properties, showcases a promising scaffold for drug development. The aim of this study is to identify potential PI3K inhibitors from gallic acid derivatives using advanced computational techniques such as PASS prediction, molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Five derivatives 21, 37, 44, 68 and 75 were selected based on their predicted antineoplastic activity among 90 derivatives, as well as the control drug Duvelisib. Compound 68 proved to be the most promising candidate, exhibiting strong binding affinity to the PI3K receptor, forming multiple hydrogen bonds with key residues, and showing stable interactions over 500 ns MD simulation. ADMET analysis revealed that compound 68 had favorable pharmacokinetic properties. Compound 21 also showed strong binding affinity but exhibited limitations in its pharmacokinetic profile. This study aims to improve our understanding of ligand-protein dynamics in PI3K inhibition and highlight the potential of gallic acid derivatives in developing safer and more effective PI3K inhibitors for cancer therapy. Our results support further experimental validation of compound 68 and suggest that gallic acid derivatives could contribute to the development of safer therapies.
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.