Convolutional Neural Network-based Virtual Screening
- 1 March 2021
- journal article
- review article
- Published by Bentham Science Publishers Ltd. in Current Medicinal Chemistry
- Vol. 28 (10) , 2033-2047
Abstract
Virtual screening is an important means for lead compound discovery. The scoring function is the key to selecting hit compounds. Many scoring functions are currently available; however, there are no all-purpose scoring functions because different scoring functions tend to have conflicting results. Recently, neural networks, especially convolutional neural networks, have constantly been penetrating drug design and most CNN-based virtual screening methods are superior to traditional docking methods, such as Dock and AutoDock. CNNbased virtual screening is expected to improve the previous model of overreliance on computational chemical screening. Utilizing the powerful learning ability of neural networks provides us with a new method for evaluating compounds. We review the latest progress of CNN-based virtual screening and propose prospects.Keywords
Funding Information
- Xiamen University (SCAI1802)
- China Pharmaceutical University (CPU2018GY15)
- National Key R&D Program of China (2018YFC0-311001)
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