Riaz Maira, Muhammad Azam, Ahmed Irfan, Muhammad Asim Raza Basra
{"title":"吡罗西康过渡金属配合物(Mn, Fe, Co, Ni和Zn)的综合DFT研究:对计算药物设计的影响","authors":"Riaz Maira, Muhammad Azam, Ahmed Irfan, Muhammad Asim Raza Basra","doi":"10.1007/s00894-025-06483-9","DOIUrl":null,"url":null,"abstract":"<p>Computational approaches are instrumental in understanding the structural and electronic characteristics of drug metal complexes, thereby facilitating the rational deign of more effective pharmaceutical agents prior to experimental validation. The present work was designed to evaluate the drug-likeness and therapeutic potential, bioavailability, pharmacokinetics, and toxicity characteristics of piroxicam transition metal (Mn, Fe, Co, Ni, and Zn). Additionally, the comprehensive structural, electronic, and solvent-dependent behavior were investigated through theoretical analysis, with particular emphasis geometry optimizations and stabilization effects explored in solvents such as water, ethanol, and DMSO. Among the studied systems, the Co and Ni-piroxicam complexes exhibited the highest stabilization energy. HOMO–LUMO energy gaps and molecular electrostatic potential (MEP) maps indicate enhanced charge transfer characteristics, helping to identify reactive electrophilic and nucleophilic sites. These findings underscore the significant influence of solvent polarity and metal ion size on the physicochemical properties and potential bioavailability of metal drug complexes. The ADMET assessment also proved the safety profile coupled with no predicted toxicity, offering meaningful insights for rational drug design.</p><p>ADMET analysis was carried out using the ADMETlab 3.0 online web server to predict, pharmacokinetic behavior, and various toxicity aspects. Furthermore, the geometry optimization and frequency analyses were performed using DFT at the B3LYP/6-31G(d,p) level for non-metal atoms and SDD basis set for transition metals. Solvent effects (water, ethanol, and DMSO) were modeled using the SMD continuum model as implemented in the Gaussian 16. Key descriptors such as HOMO–LUMO energies, their energy gaps, molecular electrostatic potential (ESP), and thermodynamics metrics were computed by Multiwf, Jmol, and SHERMO, respectively.</p><p>DFT studies of transition metal-piroxicam (Mn, Fe, Co, Ni, and Zn) focusing on solvent effects on different parameters. Solvent-induced changes in reactivity and stability are analyzed using solvation energy, global descriptors, molecular orbitals, and thermodynamic parameters. Complementary ADMET and toxicity evaluations via ADMETlab3.0 provide insights into pharmacokinetics, drug-likeness, and safety profiles, supporting their potential in drug formulation and development.</p>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 9","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comprehensive DFT study on piroxicam transition metal complexes (Mn, Fe, Co, Ni, and Zn): implications for computational drug design\",\"authors\":\"Riaz Maira, Muhammad Azam, Ahmed Irfan, Muhammad Asim Raza Basra\",\"doi\":\"10.1007/s00894-025-06483-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Computational approaches are instrumental in understanding the structural and electronic characteristics of drug metal complexes, thereby facilitating the rational deign of more effective pharmaceutical agents prior to experimental validation. The present work was designed to evaluate the drug-likeness and therapeutic potential, bioavailability, pharmacokinetics, and toxicity characteristics of piroxicam transition metal (Mn, Fe, Co, Ni, and Zn). Additionally, the comprehensive structural, electronic, and solvent-dependent behavior were investigated through theoretical analysis, with particular emphasis geometry optimizations and stabilization effects explored in solvents such as water, ethanol, and DMSO. Among the studied systems, the Co and Ni-piroxicam complexes exhibited the highest stabilization energy. HOMO–LUMO energy gaps and molecular electrostatic potential (MEP) maps indicate enhanced charge transfer characteristics, helping to identify reactive electrophilic and nucleophilic sites. These findings underscore the significant influence of solvent polarity and metal ion size on the physicochemical properties and potential bioavailability of metal drug complexes. The ADMET assessment also proved the safety profile coupled with no predicted toxicity, offering meaningful insights for rational drug design.</p><p>ADMET analysis was carried out using the ADMETlab 3.0 online web server to predict, pharmacokinetic behavior, and various toxicity aspects. Furthermore, the geometry optimization and frequency analyses were performed using DFT at the B3LYP/6-31G(d,p) level for non-metal atoms and SDD basis set for transition metals. Solvent effects (water, ethanol, and DMSO) were modeled using the SMD continuum model as implemented in the Gaussian 16. Key descriptors such as HOMO–LUMO energies, their energy gaps, molecular electrostatic potential (ESP), and thermodynamics metrics were computed by Multiwf, Jmol, and SHERMO, respectively.</p><p>DFT studies of transition metal-piroxicam (Mn, Fe, Co, Ni, and Zn) focusing on solvent effects on different parameters. Solvent-induced changes in reactivity and stability are analyzed using solvation energy, global descriptors, molecular orbitals, and thermodynamic parameters. Complementary ADMET and toxicity evaluations via ADMETlab3.0 provide insights into pharmacokinetics, drug-likeness, and safety profiles, supporting their potential in drug formulation and development.</p>\",\"PeriodicalId\":651,\"journal\":{\"name\":\"Journal of Molecular Modeling\",\"volume\":\"31 9\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Modeling\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00894-025-06483-9\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Modeling","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s00894-025-06483-9","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
A comprehensive DFT study on piroxicam transition metal complexes (Mn, Fe, Co, Ni, and Zn): implications for computational drug design
Computational approaches are instrumental in understanding the structural and electronic characteristics of drug metal complexes, thereby facilitating the rational deign of more effective pharmaceutical agents prior to experimental validation. The present work was designed to evaluate the drug-likeness and therapeutic potential, bioavailability, pharmacokinetics, and toxicity characteristics of piroxicam transition metal (Mn, Fe, Co, Ni, and Zn). Additionally, the comprehensive structural, electronic, and solvent-dependent behavior were investigated through theoretical analysis, with particular emphasis geometry optimizations and stabilization effects explored in solvents such as water, ethanol, and DMSO. Among the studied systems, the Co and Ni-piroxicam complexes exhibited the highest stabilization energy. HOMO–LUMO energy gaps and molecular electrostatic potential (MEP) maps indicate enhanced charge transfer characteristics, helping to identify reactive electrophilic and nucleophilic sites. These findings underscore the significant influence of solvent polarity and metal ion size on the physicochemical properties and potential bioavailability of metal drug complexes. The ADMET assessment also proved the safety profile coupled with no predicted toxicity, offering meaningful insights for rational drug design.
ADMET analysis was carried out using the ADMETlab 3.0 online web server to predict, pharmacokinetic behavior, and various toxicity aspects. Furthermore, the geometry optimization and frequency analyses were performed using DFT at the B3LYP/6-31G(d,p) level for non-metal atoms and SDD basis set for transition metals. Solvent effects (water, ethanol, and DMSO) were modeled using the SMD continuum model as implemented in the Gaussian 16. Key descriptors such as HOMO–LUMO energies, their energy gaps, molecular electrostatic potential (ESP), and thermodynamics metrics were computed by Multiwf, Jmol, and SHERMO, respectively.
DFT studies of transition metal-piroxicam (Mn, Fe, Co, Ni, and Zn) focusing on solvent effects on different parameters. Solvent-induced changes in reactivity and stability are analyzed using solvation energy, global descriptors, molecular orbitals, and thermodynamic parameters. Complementary ADMET and toxicity evaluations via ADMETlab3.0 provide insights into pharmacokinetics, drug-likeness, and safety profiles, supporting their potential in drug formulation and development.
期刊介绍:
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.