The genomics revolution has resulted in a vast amount of knowledge about human physiology and how different diseases affect function. Additional technological advancements, such as transcriptomics and proteomics have pushed insights even further. However, translating these findings into new drugs has progressed less rapidly. One of the bottlenecks is the challenge of going from the identity of the most appropriate cellular target, to having a drug, usually a small molecule, that affect the biology of the target in a manner that corrects the disease phenotype. A type of strategy developed to address this challenge is high-throughput screening (HTS). HTS is used to identify small molecules that bind a target of interest, leading to desired change in target’s behavior (usually activity) and/or to cellular phenotype of interest. These methods commonly use robotic sample handling, small volumes, rapid data acquisition, and sophisticated software and compound library management systems, to conduct thousands, even millions of small scale experiments and identify the most promising hit compounds. Moreover, high-throughput methods to validated the hits in terms of their binding affinities, selectivity, in-cell target engagement, pharmacokinetic and pharmacodynamic properties, reactivity, and stability are also on the rise. This methods collection captures some of the work in this area, and it is certain to grow further as new advancements in HTS methods continue to be reported. It is a resource for anyone interested in drug discovery and development, as well as hit identification and validation
0 Views
•
Cited by 3
•
2019
•
0 Views
•
Cited by 10
•
2019
•
Shan Gao*1, Weiyang Chen*2, Nan Zhang1, Chi Xu3, Haiming Jing1,4, Wenjing Zhang1,4, Gaochao Han1,4, Matthew Flavel5, Markandeya Jois5, Yingxin Zeng1, Jing-Dong J. Han3, Bo Xian3, Guojun Li1,4
1Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control/Beijing Center of Preventive Medicine Research, China, 2College of Computer Science and Technology, Qilu University of Technology(Shandong Academy of Sciences), China, 3Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China, 4Beijing Key Laboratory of Environmental Toxicology, School of Public Health, Capital Medical University, China, 5School of Life Sciences, La Trobe University, Australia
0 Views
•
Cited by 3
•
2018
•
0 Views
•
Cited by 1
•
2018
•
0 Views
•
Cited by 17
•
2017
•
Con Sullivan1,2, Denise Jurcyzszak1, Michelle F. Goody3, Kristin A. Gabor4, Jacob R. Longfellow1, Paul J. Millard2,5, Carol H. Kim1,2
1Department of Molecular and Biomedical Sciences, University of Maine, 2Graduate School of Biomedical Sciences and Engineering, University of Maine, 3School of Biology and Ecology, University of Maine, 4Division of Intramural Research, Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences, NIH, 5Department of Chemical and Biological Engineering, University of Maine
Sequence to Structure to Drug: Molecular Modeling and Docking in Small Molecule Discovery
Asimul Islam*1,
Gourav Chaudhir1
1Jamia Millia Islamia