Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
Volume 32, Issue 15, Pages 3226-3232Publisher
WILEY
DOI: 10.1002/jcc.21905
Keywords
protein-ligand docking; global optimization; AutoDock; conformational space annealing; scoring function
Categories
Funding
- Center for In Silico Protein Science (Creative Research Initiatives of MEST/KOSEF) [2009-0063610]
- MEST/KOSEF [305-20100007]
- Center for Marine Natural Products and Drug Discovery (CMDD)
- Ministry of Land, Transport, and Maritime Affairs
- Korea Institute of Marine Science & Technology Promotion (KIMST) [20046003] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- Ministry of Education, Science & Technology (MoST), Republic of Korea [CG009102] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2008-0061987] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Ask authors/readers for more resources
Protein-ligand docking techniques are one of the essential tools for structure-based drug design. Two major components of a successful docking program are an efficient search method and an accurate scoring function. In this work, a new docking method called LigDockCSA is developed by using a powerful global optimization technique, conformational space annealing (CSA), and a scoring function that combines the AutoDock energy and the piecewise linear potential (PLP) torsion energy. It is shown that the CSA search method can find lower energy binding poses than the Lamarckian genetic algorithm of AutoDock. However, lower-energy solutions CSA produced with the AutoDock energy were often less native-like. The loophole in the AutoDock energy was fixed by adding a torsional energy term, and the CSA search on the refined energy function is shown to improve the docking performance. The performance of LigDockCSA was tested on the Astex diverse set which consists of 85 protein-ligand complexes. LigDockCSA finds the best scoring poses within 2 angstrom root-mean-square deviation (RMSD) from the native structures for 84.7% of the test cases, compared to 81.7% for AutoDock and 80.5% for GOLD. The results improve further to 89.4% by incorporating the conformational entropy. (C) 2011 Wiley Periodicals, Inc. J Comput Chem 32: 3226-3232, 2011
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available