Accelerating Lead Identification by High Throughput Virtual Screening: Prospective Case Studies from the Pharmaceutical Industry
| Autor: | Taraneh Mirzadegan, Navin Rao, Alec D. Lebsack, Kelly L. Damm-Ganamet, Nidhi Arora, John J. M. Wiener, James P. Edwards, Stéphane Bécart, Lori Westover, Marina I. Nelen, Heather M. McAllister |
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| Rok vydání: | 2019 |
| Předmět: |
Models
Molecular Time Factors Drug Industry Computer science Protein Conformation General Chemical Engineering Drug Evaluation Preclinical Computational biology Library and Information Sciences 01 natural sciences User-Computer Interface Lead (geology) 0103 physical sciences Agammaglobulinaemia Tyrosine Kinase Bruton's tyrosine kinase Humans Throughput (business) Protein Kinase Inhibitors Pharmaceutical industry Orphan receptor Virtual screening 010304 chemical physics biology Drug discovery business.industry General Chemistry HLA-DR Antigens Orphan Nuclear Receptors 0104 chemical sciences Computer Science Applications High-Throughput Screening Assays 010404 medicinal & biomolecular chemistry Identification (information) biology.protein business |
| Zdroj: | Journal of chemical information and modeling. 59(5) |
| ISSN: | 1549-960X |
| Popis: | At the onset of a drug discovery program, the goal is to identify novel compounds with appropriate chemical features that can be taken forward as lead series. Here, we describe three prospective case studies, Bruton Tyrosine Kinase (BTK), RAR-Related Orphan Receptor γ t (RORγt), and Human Leukocyte Antigen DR isotype (HLA-DR) to illustrate the positive impact of high throughput virtual screening (HTVS) on the successful identification of novel chemical series. Each case represents a project with a varying degree of difficulty due to the amount of structural and ligand information available internally or in the public domain to utilize in the virtual screens. We show that HTVS can be effectively employed to identify a diverse set of potent hits for each protein system even when the gold standard, high resolution structural data or ligand binding data for benchmarking, is not available. |
| Databáze: | OpenAIRE |
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