Abstract
Artificial neural networks (ANNs) have been applied for the quantitative structure-activity relationships (QSAR) studies of antitumor activity of acridinone derivatives. Molecular modeling studies were performed with the use of HyperChem and Dragon computer programs and molecular geometry optimization using MM+ molecular mechanics and semi-empirical AM1 method, and several molecular descriptors of agents were obtained. A high correlation resulted between the ANN predicted antitumor activity and that one from biological experiments for the data used in the testing set of acridinones was obtained with correlation coefficient on the level of 0.9484. Moreover, the sensitivity analysis indicated that molecular parameters describing geometrical properties as well as lipophilicity of acridinone derivative molecule are important for acridinones antitumor activity.
Keywords: Acridinones, antitumor activity, artificial neural networks (ANNs), molecular descriptors, sensitivity analysis, acridinone derivative, lipophilicity, imidazoacridinones, triazoloacridinones
Medicinal Chemistry
Title:Application of Artificial Neural Networks for the Prediction of Antitumor Activity of a Series of Acridinone Derivatives
Volume: 8 Issue: 3
Author(s): Marcin Koba
Affiliation:
Keywords: Acridinones, antitumor activity, artificial neural networks (ANNs), molecular descriptors, sensitivity analysis, acridinone derivative, lipophilicity, imidazoacridinones, triazoloacridinones
Abstract: Artificial neural networks (ANNs) have been applied for the quantitative structure-activity relationships (QSAR) studies of antitumor activity of acridinone derivatives. Molecular modeling studies were performed with the use of HyperChem and Dragon computer programs and molecular geometry optimization using MM+ molecular mechanics and semi-empirical AM1 method, and several molecular descriptors of agents were obtained. A high correlation resulted between the ANN predicted antitumor activity and that one from biological experiments for the data used in the testing set of acridinones was obtained with correlation coefficient on the level of 0.9484. Moreover, the sensitivity analysis indicated that molecular parameters describing geometrical properties as well as lipophilicity of acridinone derivative molecule are important for acridinones antitumor activity.
Export Options
About this article
Cite this article as:
Koba Marcin, Application of Artificial Neural Networks for the Prediction of Antitumor Activity of a Series of Acridinone Derivatives, Medicinal Chemistry 2012; 8 (3) . https://dx.doi.org/10.2174/157340612800786651
DOI https://dx.doi.org/10.2174/157340612800786651 |
Print ISSN 1573-4064 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6638 |
- 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 Recent Patents of Gene Mutation Relative to JAK/STAT Pathway and Their Implication in Myeloproliferative Diseases
Recent Patents on DNA & Gene Sequences Therapeutic Perspectives for cN-II in Cancer.
Current Medicinal Chemistry Development of Liposomes and Pseudovirions with Fusion Activity for Efficient Gene Delivery
Current Gene Therapy Antimicrobial Activity of Phenolics and Glucosinolate Hydrolysis Products and their Synergy with Streptomycin against Pathogenic Bacteria
Medicinal Chemistry Which Dose of Folic Acid Should Pregnant Diabetic Women Receive?
Recent Patents on Endocrine, Metabolic & Immune Drug Discovery Resistance to Anti-VEGF Agents
Current Pharmaceutical Design Antioxidant Effects of Chalcones during the Inflammatory Response: An Overall Review
Current Medicinal Chemistry Global Cell Proteome Profiling, Phospho-signaling and Quantitative Proteomics for Identification of New Biomarkers in Acute Myeloid Leukemia Patients
Current Pharmaceutical Biotechnology Bladder Cancer Stem Cells
Current Stem Cell Research & Therapy Targeting Indoleamine 2,3-dioxygenase (IDO) to Counteract Tumour- Induced ImmuneDysfunction: From Biochemistry to Clinical Development
Endocrine, Metabolic & Immune Disorders - Drug Targets The Significance of Transferrin Receptors in Oncology: the Development of Functional Nano-based Drug Delivery Systems
Current Drug Delivery NAD(P) Biosynthesis Enzymes as Potential Targets for Selective Drug Design
Current Medicinal Chemistry Are the Antioxidant Properties of Carvedilol Important for the Protection of Cardiac Mitochondria?
Current Vascular Pharmacology Overview of Tumor-Associated Antigens (TAAs) as Potential Therapeutic Targets for Prostate Cancer Therapy
Current Cancer Therapy Reviews Overview of Ribonucleotide Reductase Inhibitors: An Appealing Target in Anti-Tumour Therapy
Current Medicinal Chemistry New Insights about the Potential Application of the Association of Vitamins C (Sodium Ascorbate) and K3 (Menadione) as Auxiliary Therapy in Cancer Treatment
Medicinal Chemistry Reviews - Online (Discontinued) Summary of Information on the Effects of Ionizing and Non-ionizing Radiation on Cytochrome P450 and Other Drug Metabolizing Enzymes and Transporters
Current Drug Metabolism Flavonoids in Cancer Prevention
Anti-Cancer Agents in Medicinal Chemistry New Perspective on the Dual Functions of Indirubins in Cancer Therapy and Neuroprotection
Anti-Cancer Agents in Medicinal Chemistry