Abstract
A process has been developed whereby libraries of compounds for lead optimization can be synthesized and screened with greater efficiency using computational tools. In this method, analogues of a lead chemical structure are considered in the form of a virtual library. Less than 1/3 of the library is selected as a training set by clustering the compounds and choosing the centroid of each cluster. This training set is then used to generate a model using PLS regression upon the experimental values from that assay using 1D/2D descriptors. The model is applied to the remaining compounds (the test set) for which assay values are predicted and a rank ordering established. An example of this was a set of 169 PDE4 inhibitors. A predictive model was achieved using a training set of 52 compounds. When applied to the remaining 117 compounds this model allowed a rank ordering of these compounds for synthesis and testing. Selecting the top 33 compounds of the test set gives 78% of the compounds with the desired activity (hits) by synthesizing only 50% of the library, including the training set. Selecting the top 59 of the test set gives 97% of the hits from only 67% of the library. This process succeeds by avoiding two principal weaknesses of 2D descriptors: lack of interpretation and lack of extrapolation. Two principal assumptions of QSAR are shown to be unnecessary; removing descriptor redundancy does not improve fit and a predictive r2 greater than 0.5 is not necessary if rank-ordering is desired.
Keywords: 1D/2D descriptors, QSAR, Scripting, dithiothreitol, binary fingerprints
Combinatorial Chemistry & High Throughput Screening
Title: Improving Synthetic Efficiency Using the Computational Prediction of Biological Activity
Volume: 9 Issue: 2
Author(s): K. C. Brogle, T. Gund and D. J. Kyle
Affiliation:
Keywords: 1D/2D descriptors, QSAR, Scripting, dithiothreitol, binary fingerprints
Abstract: A process has been developed whereby libraries of compounds for lead optimization can be synthesized and screened with greater efficiency using computational tools. In this method, analogues of a lead chemical structure are considered in the form of a virtual library. Less than 1/3 of the library is selected as a training set by clustering the compounds and choosing the centroid of each cluster. This training set is then used to generate a model using PLS regression upon the experimental values from that assay using 1D/2D descriptors. The model is applied to the remaining compounds (the test set) for which assay values are predicted and a rank ordering established. An example of this was a set of 169 PDE4 inhibitors. A predictive model was achieved using a training set of 52 compounds. When applied to the remaining 117 compounds this model allowed a rank ordering of these compounds for synthesis and testing. Selecting the top 33 compounds of the test set gives 78% of the compounds with the desired activity (hits) by synthesizing only 50% of the library, including the training set. Selecting the top 59 of the test set gives 97% of the hits from only 67% of the library. This process succeeds by avoiding two principal weaknesses of 2D descriptors: lack of interpretation and lack of extrapolation. Two principal assumptions of QSAR are shown to be unnecessary; removing descriptor redundancy does not improve fit and a predictive r2 greater than 0.5 is not necessary if rank-ordering is desired.
Export Options
About this article
Cite this article as:
Brogle C. K., Gund T. and Kyle J. D., Improving Synthetic Efficiency Using the Computational Prediction of Biological Activity, Combinatorial Chemistry & High Throughput Screening 2006; 9 (2) . https://dx.doi.org/10.2174/138620706775541846
DOI https://dx.doi.org/10.2174/138620706775541846 |
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
-
Synthesis of a Novel Series of 8-HETE Analogs and their Biological Evaluation Towards the PPAR Nuclear Receptors
Letters in Drug Design & Discovery In Silico Design of Protein Kinase Inhibitors: Successes and Failures
Anti-Cancer Agents in Medicinal Chemistry Primary Tumors of the Sacrum: Imaging Findings
Current Medical Imaging Recent Development of Heterocyclic Compounds with Indazole Moiety as Potential Antiparasitic Agents
Current Topics in Medicinal Chemistry Deacetylase Inhibitors Modulate the Myostatin/Follistatin Axis without Improving Cachexia in Tumor-Bearing Mice
Current Cancer Drug Targets 2-Mercaptobenzimidazole Schiff Bases: Design, Synthesis, Antimicrobial Studies and Anticancer Activity on HCT-116 Cell Line
Mini-Reviews in Medicinal Chemistry Glutamate Receptors in Microglia
CNS & Neurological Disorders - Drug Targets Managing Nutrition for Cancer Patients during COVID-19: Review
Current Nutrition & Food Science Synthesis of Daumone Derivatives and their Antiangiogenic Activities on Chorioallantoic Membrane
Medicinal Chemistry Strategies to Convert PACAP from a Hypophysiotropic Neurohormone Into a Neuroprotective Drug
Current Pharmaceutical Design Novel dibenzo[b,d]furan–1H-1,2,4-triazole derivatives: Synthesis and antitumor activity
Anti-Cancer Agents in Medicinal Chemistry subject Index To Volume 2
Current Medicinal Chemistry - Central Nervous System Agents Challenges in Breast Cancer Control in Malaysia
Current Women`s Health Reviews <i>In Silico</i> Screening of Some Anti-Cancer Drugs Against the Main Protease of COVID-19 Using Molecular Docking
Letters in Organic Chemistry Mental Disorders and Poor COVID-19 Prognosis: Reevaluating the Relationship through Ca<sup>2+</sup>/cAMP Signalling
Current Topics in Medicinal Chemistry Structural Investigation of Vinca Domain Tubulin Binders by Pharmacophore, Atom based QSAR, Docking and Molecular Dynamics Simulations
Combinatorial Chemistry & High Throughput Screening Synthesis, Anti-Methicillin-resistant S. aureus (MRSA) Evaluation, Quantitative Structure-Activity Relationship and Molecular Modeling Studies of Some Novel Bis-indoles as Prospective MRSA Pyruvate Kinase Inhibitors
Letters in Drug Design & Discovery The Activation of Procarcinogens by CYP1A1/1B1 and Related Chemo-Preventive Agents: A Review
Current Cancer Drug Targets Combination of Hydroxychloroquine, Melatonin and Mercaptopurine as a Possible Intervention for Prophylaxis and Treatment of Novel COVID-19 Infection
Coronaviruses Molecular Design and QSARs/QSPRs with Molecular Descriptors Family
Current Computer-Aided Drug Design