Abstract
Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.
Keywords: QSAR-quantitative structure activity relationships, combi-QSAR-combinatorial QSAR, kNN - k nearest neighbors, SA -simulating annealing, PLS - partial least squares
Current Pharmaceutical Design
Title: Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening
Volume: 13 Issue: 34
Author(s): Alexander Tropsha and Alexander Golbraikh
Affiliation:
Keywords: QSAR-quantitative structure activity relationships, combi-QSAR-combinatorial QSAR, kNN - k nearest neighbors, SA -simulating annealing, PLS - partial least squares
Abstract: Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.
Export Options
About this article
Cite this article as:
Tropsha Alexander and Golbraikh Alexander, Predictive QSAR Modeling Workflow, Model Applicability Domains, and Virtual Screening, Current Pharmaceutical Design 2007; 13 (34) . https://dx.doi.org/10.2174/138161207782794257
DOI https://dx.doi.org/10.2174/138161207782794257 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
Call for Papers in Thematic Issues
"Tuberculosis Prevention, Diagnosis and Drug Discovery"
The Nobel Prize-winning discoveries of Mycobacterium tuberculosis and streptomycin have enabled an appropriate diagnosis and an effective treatment of tuberculosis (TB). Since then, many newer diagnosis methods and drugs have been saving millions of lives. Despite advances in the past, TB is still a leading cause of infectious disease mortality ...read more
Current Pharmaceutical challenges in the treatment and diagnosis of neurological dysfunctions
Neurological dysfunctions (MND, ALS, MS, PD, AD, HD, ALS, Autism, OCD etc..) present significant challenges in both diagnosis and treatment, often necessitating innovative approaches and therapeutic interventions. This thematic issue aims to explore the current pharmaceutical landscape surrounding neurological disorders, shedding light on the challenges faced by researchers, clinicians, and ...read more
Emerging and re-emerging diseases
Faced with a possible endemic situation of COVID-19, the world has experienced two important phenomena, the emergence of new infectious diseases and/or the resurgence of previously eradicated infectious diseases. Furthermore, the geographic distribution of such diseases has also undergone changes. This context, in turn, may have a strong relationship with ...read more
Melanoma and Non-Melanoma Skin Cancer Treatment: Standard of Care and Recent Advances
In this thematic issue, we aim to provide a standard of care of the diagnosis and treatment of melanoma and non-melanoma skin cancer. The editor will invite authors from different countries who will write review articles of melanoma and non-melanoma skin cancers. The Diagnosis, Staging, Surgical Treatment, Non-Surgical Treatment all ...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
- Announcements
Related Articles
-
The Osteopontin Tissue Level as a Breast Cancer Biomarker in Females After Mastectomy Measured by the Capillary Gel Electrophoresis Technique
Combinatorial Chemistry & High Throughput Screening T Cell Receptor Bias in Humans
Current Immunology Reviews (Discontinued) Nanomedicine to Overcome Cancer Multidrug Resistance
Current Drug Metabolism Chemoresistance of Cancer Cells: Oncogenic Mutation of the p53 Tumor Suppressor Gene
Current Signal Transduction Therapy Salinomycin: A Novel Anti-Cancer Agent with Known Anti-Coccidial Activities
Current Medicinal Chemistry Endocrine and Antineoplastic Actions of Growth Hormone-Releasing Hormone Antagonists
Current Medicinal Chemistry Targeted Drug Delivery to Macrophages in Parasitic Infections
Current Drug Delivery Targeting CSC-Related miRNAs for Cancer Therapy by Natural Agents
Current Drug Targets MicroRNA-34 Family, Mechanisms of Action in Cancer: A Review
Current Cancer Drug Targets Stem Cell Differentiation Stage Factors from Zebrafish Embryo: A Novel Strategy to Modulate the Fate of Normal and Pathological Human (Stem) Cells
Current Pharmaceutical Biotechnology Chemodiversity in Freshwater and Terrestrial Cyanobacteria – A Source for Drug Discovery
Current Drug Targets Thiosemicarbazone-Pt(II) Complex Causes a Growth Inhibitory Effect on Human Mesenchymal Stem Cells
Medicinal Chemistry Pyrazole Derivatives as Antitumor, Anti-Inflammatory and Antibacterial Agents
Mini-Reviews in Medicinal Chemistry The Evolution of Schizophrenia: A Model for Selection by Infection, with a Focus on NAD
Current Pharmaceutical Design Metformin Treatment Sensitizes Human Laryngeal Cancer Cell Line Hep- 2 to 5-Fluorouracil
Clinical Cancer Drugs 3-Nitro-Tyrosine as an Internal Quencher of Autofluorescence Enhances the Compatibility of Fluorescence Based Screening of OBOC Combinatorial Libraries
Combinatorial Chemistry & High Throughput Screening Variances in the Level of COX-2 and iNOS in Different Grades of Endometrial Cancer
Current Pharmaceutical Biotechnology MicroRNAs: Potential Diagnostic and Therapeutic Targets for Breast Cancer
Epigenetic Diagnosis & Therapy (Discontinued) The Function of LncRNA FTX in Several Common Cancers
Current Pharmaceutical Design Molecular Mechanisms of Pancreatic Cancer Dissemination: The Role of the Chemokine System
Current Pharmaceutical Design