Abstract
Present work deals with generation of virtual samples as mathematical modeling of empirical data on the basis of empirical data. The generated samples were used for development of QSAR model. The method deals with extrapolation of sample vector in such a manner that there is conservation of the empirical data distribution. The data distribution has been judged with statistical parameters. The method was implemented with anticancer activity of Gossypol acetic acid against BCL2 target for colorectal cancer. Considering the virtual samples only for model development, model training showed a regression coefficient for leave one out cross validation as 0.996 with 66 virtual samples, and a regression coefficient with external test set data (51 samples) as 0.993. External test set data which were never used in the virtual sample generation showed predicted regression coefficient value of >0.61. On the basis of QSAR model, nine compounds were suggested as anti-BCL2 active compounds. The suggested compounds were further validated by docking study with Gossypol acetic acid and ‘Tetrahydroisoquinoline amide substituted phenyl pyrazole’ cocrystallized with chimeric BCL2-XL (PDBID: 2W3L) protein.
Keywords: BCL2, cancer, QSAR, SVR, virtual screening.
Combinatorial Chemistry & High Throughput Screening
Title:Development of Method for Three-Point Data Estimation and SVR-QSAR Model to Screen Anti Cancer Leads
Volume: 16 Issue: 6
Author(s): Om Prakash and Feroz Khan
Affiliation:
Keywords: BCL2, cancer, QSAR, SVR, virtual screening.
Abstract: Present work deals with generation of virtual samples as mathematical modeling of empirical data on the basis of empirical data. The generated samples were used for development of QSAR model. The method deals with extrapolation of sample vector in such a manner that there is conservation of the empirical data distribution. The data distribution has been judged with statistical parameters. The method was implemented with anticancer activity of Gossypol acetic acid against BCL2 target for colorectal cancer. Considering the virtual samples only for model development, model training showed a regression coefficient for leave one out cross validation as 0.996 with 66 virtual samples, and a regression coefficient with external test set data (51 samples) as 0.993. External test set data which were never used in the virtual sample generation showed predicted regression coefficient value of >0.61. On the basis of QSAR model, nine compounds were suggested as anti-BCL2 active compounds. The suggested compounds were further validated by docking study with Gossypol acetic acid and ‘Tetrahydroisoquinoline amide substituted phenyl pyrazole’ cocrystallized with chimeric BCL2-XL (PDBID: 2W3L) protein.
Export Options
About this article
Cite this article as:
Prakash Om and Khan Feroz, Development of Method for Three-Point Data Estimation and SVR-QSAR Model to Screen Anti Cancer Leads, Combinatorial Chemistry & High Throughput Screening 2013; 16 (6) . https://dx.doi.org/10.2174/1386207311316060002
DOI https://dx.doi.org/10.2174/1386207311316060002 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- 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
-
Recent Developments in CE-MS Based Metabolomics
Current Analytical Chemistry Autophagy and Ubiquitination as Two Major Players in Colorectal Cancer: A Review on Recent Patents
Recent Patents on Anti-Cancer Drug Discovery Targeting the Folate Receptor: Improving Efficacy in Inorganic Medicinal Chemistry
Current Medicinal Chemistry Synergistic Interactions between GW8510 and Gemcitabine in an In Vitro Model of Pancreatic Cancer
Anti-Cancer Agents in Medicinal Chemistry Encountering and Advancing Through Antiangiogenesis Therapy for Gliomas
Current Pharmaceutical Design PD-L1 Testing for Urothelial Carcinoma: Interchangeability, Reliability and Future Perspectives
Current Drug Targets Novel Agents in the Management of Lung Cancer
Current Medicinal Chemistry Potential Cardio-Protective Agents: A Resveratrol Review (2000-2019)
Current Pharmaceutical Design Protein Kinase Inhibitors in the Treatment of Pulmonary Fibrosis
Current Medicinal Chemistry Modular Protein Engineering in Emerging Cancer Therapies
Current Pharmaceutical Design Vascular Disrupting Agents (VDA) in Oncology: Advancing Towards New Therapeutic Paradigms in the Clinic
Current Drug Targets Development and Clinical Application of Peptide-Based Radiopharmaceuticals
Current Pharmaceutical Design Epidemiology, Clinical Presentation and Treatment of Uveal Melanoma
Clinical Cancer Drugs Cell Arrest and Apoptosis Induced by the Next Generation of Vanadium Based Drugs: Action Mechanism to Structure Relation and Future Perspectives
Anti-Cancer Agents in Medicinal Chemistry Synthesis of Silica Based Nanoparticles Against the Proliferation of Human Prostate Cancer
Anti-Cancer Agents in Medicinal Chemistry Recent Developments in Targeting Breast Cancer Stem Cells
Recent Patents on Regenerative Medicine Review of Theoretical Studies for Prediction of Neurodegenerative Inhibitors
Mini-Reviews in Medicinal Chemistry Targeted Drugs and Nanomedicine: Present and Future
Current Pharmaceutical Design Editorial (Thematic Issue: Antiangiogenic Agents in the Management of Solid Malignancies)
Current Angiogenesis (Discontinued) Personalized Peptide Vaccine for Treatment of Advanced Cancer
Current Medicinal Chemistry