NDLI: Q-fit: A probabilistic method for docking molecular fragments by sampling low energy conformational space

Content Provider	Springer Nature Link
Author	Jackson, Richard M.
Copyright Year	2002
Abstract	A new method is presented that docks molecular fragments to a rigid protein receptor. It uses a probabilistic procedure based on statistical thermodynamic principles to place ligand atom triplets at the lowest energy sites. The probabilistic method ranks receptor binding modes so that the lowest energy ones are sampled first. This allows constraints to be introduced to limit the depth of the search leading to a computationally efficient method of sampling low energy conformational space. This is combined with energy minimization of the initial fragment placement to arrive at a low energy conformation for the molecular fragment. Two different search methods are tested involving (i) geometric hashing and (ii) pose clustering methods. Ten molecular fragments were docked that have commonly been used to test docking methods. The success rate was 8/10 and 10/10 for generating a close solution ranked first using the two different sampling procedures. In general, all five of the top ranked solutions reproduce the observed binding mode, which increases confidence in the predictions. A set of ten molecular fragments that have previously been identified as problematic were docked. Success was achieved in 3/10 and 4/10 using the two different methods. Again there is a high level of agreement between the two methods and again in the successful cases the top ranked solutions are correct whilst in the case of the failures none are. The geometric hashing and pose clustering methods are fast averaging ∼ 13 and ∼ 11 s per placement respectively using conservative parameters. The results are very encouraging and will facilitate the process of finding novel small molecule lead compounds by virtual screening of chemical databases.
Starting Page	43
Ending Page	57
Page Count	15
File Format	PDF
ISSN	0920654X
Journal	Journal of Computer-Aided Molecular Design
Volume Number	16
Issue Number	1
e-ISSN	15734951
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2002-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Computer Applications in Chemistry Physical Chemistry Animal Anatomy / Morphology / Histology
Content Type	Text
Resource Type	Article
Subject	Drug Discovery Physical and Theoretical Chemistry Computer Science Applications

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