Abstract
Multivariate adaptive regression splines (MARSplines) 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 software. The structures of the compounds were firstly pre-optimized with the MM+ mechanics and semi-empirical AM1 method procedure included in the HyperChem and resulting geometrical structures were studied with the use of Dragon software, and several molecular descriptors of acridinones were calculated and used as predictor (independent) variables in the MARS model building. Principal component analysis (PCA) was used to select the training and test sets. The optimal MARS model uses 28 basis functions to describe acridinones' antitumor activity and characterized high correlation between predicted antitumor activity and that one from biological experiments for the data used in the training and testing sets of acridinones with correlation coefficients on the level of 0.9477 and 0.9660, respectively. Generally, results showed that MARS model provided powerful capacity of prediction of antitumor activity of acridinone derivatives. Moreover, a physicochemical explanation of the descriptors selected by MARSplines analysis is also given, and indicated that molecular parameters describing 3-D properties as well as lipophilicity of acridinone derivative molecule are important for acridinones antitumor activity.
Keywords: Acridinones, Antitumor activity, Multivariate Adaptive Regression Splines (MARSplines), Molecular descriptors, Prediction of activity, Quantitative structure-activity relationships (QSAR).
Medicinal Chemistry
Title:The Evaluation of Multivariate Adaptive Regression Splines for the Prediction of Antitumor Activity of Acridinone Derivatives
Volume: 9 Issue: 8
Author(s): Marcin Koba and Tomasz Bączek
Affiliation:
Keywords: Acridinones, Antitumor activity, Multivariate Adaptive Regression Splines (MARSplines), Molecular descriptors, Prediction of activity, Quantitative structure-activity relationships (QSAR).
Abstract: Multivariate adaptive regression splines (MARSplines) 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 software. The structures of the compounds were firstly pre-optimized with the MM+ mechanics and semi-empirical AM1 method procedure included in the HyperChem and resulting geometrical structures were studied with the use of Dragon software, and several molecular descriptors of acridinones were calculated and used as predictor (independent) variables in the MARS model building. Principal component analysis (PCA) was used to select the training and test sets. The optimal MARS model uses 28 basis functions to describe acridinones' antitumor activity and characterized high correlation between predicted antitumor activity and that one from biological experiments for the data used in the training and testing sets of acridinones with correlation coefficients on the level of 0.9477 and 0.9660, respectively. Generally, results showed that MARS model provided powerful capacity of prediction of antitumor activity of acridinone derivatives. Moreover, a physicochemical explanation of the descriptors selected by MARSplines analysis is also given, and indicated that molecular parameters describing 3-D 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 and Bączek Tomasz, The Evaluation of Multivariate Adaptive Regression Splines for the Prediction of Antitumor Activity of Acridinone Derivatives, Medicinal Chemistry 2013; 9 (8) . https://dx.doi.org/10.2174/1573406411309080005
DOI https://dx.doi.org/10.2174/1573406411309080005 |
Print ISSN 1573-4064 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6638 |
Call for Papers in Thematic Issues
Carbohydrates in Computational and Medicinal Chemistry
Carbohydrates are the most essential organic molecules and are involved in the maintenance of various physiological and metabolic processes in living organisms. Carbohydrate-based compounds have come to the attention of researchers because of their significant contributions to biological functions, such as cell development and cell proliferation, connections between several cells, ...read more
Recent Advances in the Medicinal Chemistry of Cancer
Scope of the Thematic Issue: Correlation between structure and function is one of the important aspects of the success of anti-cancer compounds associated with their structure-activity interactions, physiology, biochemical, molecular, and genetic processes. Overcoming these obstacles is key to obtaining further insights into developments in rational drug design, bioorganic chemistry, ...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
-
Chlorella vulgaris Induces Apoptosis of Human Non-Small Cell Lung Carcinoma (NSCLC) Cells
Medicinal Chemistry Synthesis, Anti-tumor Activity and Odd–even Effect of Simple Isatin Derivatives
Letters in Drug Design & Discovery Application of Metabolomics in Drug Discovery, Development and Theranostics
Current Metabolomics Development and Certification of Formononetin Reference Material for Quality Control of Functional Foods and Botanical Supplements
Current Analytical Chemistry Delivery of Curcumin and Medicinal Effects of the Copper(II)-Curcumin Complexes
Current Pharmaceutical Design Multifunctional Mesoporous Silica Nanoparticles for Combined Therapeutic, Diagnostic and Targeted Action in Cancer Treatment
Current Drug Targets The Pictet-Spengler Reaction Still on Stage
Current Pharmaceutical Design Identification, Prediction and Data Analysis of Noncoding RNAs: A Review
Medicinal Chemistry The Retrotransposition of L1 is Involved in the Reconsolidation of Contextual Fear Memory in Mice
CNS & Neurological Disorders - Drug Targets A Novel Platinum-based Compound with Preferential Cytotoxic Activity against a Panel of Cancer Cell Lines
Anti-Cancer Agents in Medicinal Chemistry Evaluation of the Biological Fate and the Transport Through Biological Barriers of Nanosilver in Mice
Current Pharmaceutical Design Capsaicin and Its Analogues: Structure-Activity Relationship Study
Current Medicinal Chemistry Realizing the Potential of Health-Promoting Rosehips from Dogroses (Rosa sect. Caninae)
Current Bioactive Compounds Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning
CNS & Neurological Disorders - Drug Targets Vitamin-D Receptor (VDR) Gene Polymorphisms (TaqI, FokI) in Turkish Patients with Hashimoto’s Thyroiditis: Relationship to the Levels of Vit-D and Cytokines
Endocrine, Metabolic & Immune Disorders - Drug Targets MicroRNAs as Biomarkers for Birth Defects
MicroRNA Interaction of Anthocyanins with Drug-metabolizing and Antioxidant Enzymes
Current Medicinal Chemistry Advanced Methods for the Analysis of Testosterone
Current Medicinal Chemistry Multilanthanide Systems for Medical Imaging Applications
Recent Patents on Nanomedicine Classifications and Clinical Assessment of Haemorrhoids: The Proctologist’s Corner
Reviews on Recent Clinical Trials