User guide for the discovery of potential drugs via protein structure prediction and ligand docking simulation
- Authors
- Shaker, Bilal; Yu, Myung-Sang; Lee, Jingyu; Lee, Yongmin; Jung, Chanjin; Na, Dokyun
- Issue Date
- Mar-2020
- Publisher
- MICROBIOLOGICAL SOCIETY KOREA
- Keywords
- drug discovery; docking; ADMET; protein structure prediction
- Citation
- JOURNAL OF MICROBIOLOGY, v.58, no.3, pp 235 - 244
- Pages
- 10
- Journal Title
- JOURNAL OF MICROBIOLOGY
- Volume
- 58
- Number
- 3
- Start Page
- 235
- End Page
- 244
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/38158
- DOI
- 10.1007/s12275-020-9563-z
- ISSN
- 1225-8873
1976-3794
- Abstract
- Due to accumulating protein structure information and advances in computational methodologies, it has now become possible to predict protein-compound interactions. In biology, the classic strategy for drug discovery has been to manually screen multiple compounds (small scale) to identify potential drug compounds. Recent strategies have utilized computational drug discovery methods that involve predicting target protein structures, identifying active sites, and finding potential inhibitor compounds at large scale. In this protocol article, we introduce an in silico drug discovery protocol. Since multi-drug resistance of pathogenic bacteria remains a challenging problem to address, UDP-N-acetylmuramate-L-alanine ligase (murC) of Acinetobacter baumannii was used as an example, which causes nosocomial infection in hospital setups and is responsible for high mortality worldwide. This protocol should help microbiologists to expand their knowledge and research scope.
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