Abstract
Ataxia telangiectasia-mutated and Rad3-related (ATR) protein kinase is an attractive anticancer target. In this study, comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were performed on a series of aminopyrazine ATR inhibitors. The models generated by CoMFA had a cross-validated coefficient (q2) of 0.752 and a regression coefficient (r2) of 0.947. The CoMSIA models had a q2 of 0.728 and an r2 of 0.936. The reasonable quantitative structure-activity relationship model showed robust predictive ability. The contour map provided guidelines for building novel virtual compounds based on compound NO.40. In addition, the 3D structure of ATR was modeled by homology modeling. Molecular dynamic simulations were employed to optimize the structure. The docking results offered insights into the interactions between the inhibitors and the active site for potent analysis. This study provides useful guidance for the discovery of more potent compounds.
Keywords: ATR inhibitor, 3D-QSAR, CoMFA, CoMSIA, docking, homology modeling, molecular design.
Current Computer-Aided Drug Design
Title:3D-QSAR Analysis on ATR Protein Kinase Inhibitors Using CoMFA and CoMSIA
Volume: 10 Issue: 4
Author(s): Xiurong Li, Mao Shu, Yuanqiang Wang, Rui Yu, Shuang Yao and Zhihua Lin
Affiliation:
Keywords: ATR inhibitor, 3D-QSAR, CoMFA, CoMSIA, docking, homology modeling, molecular design.
Abstract: Ataxia telangiectasia-mutated and Rad3-related (ATR) protein kinase is an attractive anticancer target. In this study, comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were performed on a series of aminopyrazine ATR inhibitors. The models generated by CoMFA had a cross-validated coefficient (q2) of 0.752 and a regression coefficient (r2) of 0.947. The CoMSIA models had a q2 of 0.728 and an r2 of 0.936. The reasonable quantitative structure-activity relationship model showed robust predictive ability. The contour map provided guidelines for building novel virtual compounds based on compound NO.40. In addition, the 3D structure of ATR was modeled by homology modeling. Molecular dynamic simulations were employed to optimize the structure. The docking results offered insights into the interactions between the inhibitors and the active site for potent analysis. This study provides useful guidance for the discovery of more potent compounds.
Export Options
About this article
Cite this article as:
Li Xiurong, Shu Mao, Wang Yuanqiang, Yu Rui, Yao Shuang and Lin Zhihua, 3D-QSAR Analysis on ATR Protein Kinase Inhibitors Using CoMFA and CoMSIA, Current Computer-Aided Drug Design 2014; 10 (4) . https://dx.doi.org/10.2174/1573409910666140701094853
DOI https://dx.doi.org/10.2174/1573409910666140701094853 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Targeting DNA Minor Groove by Hybrid Molecules as Anticancer Agents
Current Medicinal Chemistry Advancements in Non-steroidal Antiandrogens as Potential Therapeutic Agents for the Treatment of Prostate Cancer
Mini-Reviews in Medicinal Chemistry Recent Developments in PET Instrumentation
Current Pharmaceutical Biotechnology Cell Death: Tipping the Balance of Autoimmunity and Tissue Repair
Current Pharmaceutical Design 1,3,4-Oxadiazoles as Telomerase Inhibitor: Potential Anticancer Agents
Anti-Cancer Agents in Medicinal Chemistry Polynucleotide Kinase as a Potential Target for Enhancing Cytotoxicity by Ionizing Radiation and Topoisomerase I Inhibitors
Anti-Cancer Agents in Medicinal Chemistry Angiogenic and Vascular Modulation by Extracellular Matrix Cleavage Products
Current Pharmaceutical Design Inhibition of P-Glycoprotein Mediated Efflux of Paclitaxel by Coumarin Derivatives in Cancer Stem Cells: An In Silico Approach
Combinatorial Chemistry & High Throughput Screening Sensing, Transport and Other Potential Biomedical Applications of Pseudopeptides
Current Medicinal Chemistry Anti-Angiogenic Activity of Quercetin and its Derivatives
Letters in Drug Design & Discovery Transient Receptor Potential Channels and Dermatological Disorders
Current Topics in Medicinal Chemistry Imaging Methods in Gene Therapy of Cancer
Current Gene Therapy Mutation Mechanisms of Breast Cancer among the Female Population in China
Current Bioinformatics Editorial: (Pharmaco)Metabolomics in Drug Discovery and Individualisation of Treatment
Current Pharmaceutical Design Acknowledgements to Reviewers:
Anti-Cancer Agents in Medicinal Chemistry Optical Image-Guided Cancer Therapy
Current Pharmaceutical Biotechnology The Association of Sleep Disorders, Obesity and Sleep-Related Hypoxia with Cancer
Current Genomics Vitamin D Supplementation: A Promising Approach for the Prevention and Treatment of Strokes
Current Drug Targets Resveratrol and Cancer Treatment: Is Hormesis a Yet Unsolved Matter?
Current Pharmaceutical Design Cancer Gene Therapy with Tissue Inhibitors of Metalloproteinases (TIMPs)
Current Gene Therapy