{"title":"Computational design and structural insights into quinazoline-based lead molecules for targeting PARP10 in cancer therapy","authors":"Revathi Gnanavelou , Manikandan Jayaraman , Jeyakanthan Jeyaraman , Konda Reddy Girija","doi":"10.1016/j.jmgm.2025.109005","DOIUrl":null,"url":null,"abstract":"<div><div>Quinazoline scaffolds, a class of nitrogen-containing heterocyclic compounds, are considered a “privileged structure\" in drug development due to their broad physiological activities and significant therapeutic potential. Many anti-breast cancer therapies are designed using this pharmacophore. Structural modifications such as halogen substitution and aromatic amino group insertion have been explored to improve the anticancer efficacy of quinazoline derivatives. Breast cancer continues to be the primary cause of cancer-related mortality among women, approximately 670,000 deaths globally in 2022, emphasizing the need for novel therapies. To combat multidrug resistance in breast cancer, new drug candidates targeting the Poly (ADP-ribose) polymerase (PARP) enzyme are being developed to improve chemotherapeutic efficacy and reduce toxicity. In this study, computational screening of 365 quinazoline derivatives was conducted to identify potential PARP inhibitors. Docking based screening identified three quinazoline scaffolds (RFAP77, RISA30, and RISAC) as top hits, demonstrating docking scores ranging from −8.41 to −9.31 kcal/mol and MM-GBSA binding free energy scores between −52.08 and −55.99 kcal/mol, compared to the reference approved inhibitor. ADMET analysis revealed favorable predicted drug-likeness profiles for the identified scaffolds. The structural stability of the docked PARP-ligand complexes was further investigated using molecular dynamics simulations (MDS). The computational simulations revealed significant conformational changes upon ligand binding, as evidenced by RMSD, RMSF, and hydrogen bond analyses. Essential dynamics analysis, including PCA-based FEL mapping, demonstrated energy minima profiles for all top docked PARP complexes. These computational findings highlight the potential of these scaffolds as promising candidates for further development as PARP inhibitors.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"137 ","pages":"Article 109005"},"PeriodicalIF":2.7000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of molecular graphics & modelling","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1093326325000658","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Quinazoline scaffolds, a class of nitrogen-containing heterocyclic compounds, are considered a “privileged structure" in drug development due to their broad physiological activities and significant therapeutic potential. Many anti-breast cancer therapies are designed using this pharmacophore. Structural modifications such as halogen substitution and aromatic amino group insertion have been explored to improve the anticancer efficacy of quinazoline derivatives. Breast cancer continues to be the primary cause of cancer-related mortality among women, approximately 670,000 deaths globally in 2022, emphasizing the need for novel therapies. To combat multidrug resistance in breast cancer, new drug candidates targeting the Poly (ADP-ribose) polymerase (PARP) enzyme are being developed to improve chemotherapeutic efficacy and reduce toxicity. In this study, computational screening of 365 quinazoline derivatives was conducted to identify potential PARP inhibitors. Docking based screening identified three quinazoline scaffolds (RFAP77, RISA30, and RISAC) as top hits, demonstrating docking scores ranging from −8.41 to −9.31 kcal/mol and MM-GBSA binding free energy scores between −52.08 and −55.99 kcal/mol, compared to the reference approved inhibitor. ADMET analysis revealed favorable predicted drug-likeness profiles for the identified scaffolds. The structural stability of the docked PARP-ligand complexes was further investigated using molecular dynamics simulations (MDS). The computational simulations revealed significant conformational changes upon ligand binding, as evidenced by RMSD, RMSF, and hydrogen bond analyses. Essential dynamics analysis, including PCA-based FEL mapping, demonstrated energy minima profiles for all top docked PARP complexes. These computational findings highlight the potential of these scaffolds as promising candidates for further development as PARP inhibitors.
期刊介绍:
The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.
As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.