J Chem Inf Model - ALiBERO: evolving a team of complementary pocket conformations rather than a single leader.

Tópicos

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Resumo

Docking and virtual screening (VS) reach maximum potential when the receptor displays the structural changes needed for accurate ligand binding. Unfortunately, these conformational changes are often poorly represented in experimental structures or homology models, debilitating their docking performance. Recently, we have shown that receptors optimized with our LiBERO method (Ligand-guided Backbone Ensemble Receptor Optimization) were able to better discriminate active ligands from inactives in flexible-ligand VS docking experiments. The LiBERO method relies on the use of ligand information for selecting the best performing individual pockets from ensembles derived from normal-mode analysis or Monte Carlo. Here we present ALiBERO, a new computational tool that has expanded the pocket selection from single to multiple, allowing for automatic iteration of the sampling-selection procedure. The selection of pockets is performed by a dual method that uses exhaustive combinatorial search plus individual addition of pockets, selecting only those that maximize the discrimination of known actives compounds from decoys. The resulting optimized pockets showed increased VS performance when later used in much larger unrelated test sets consisting of biologically active and inactive ligands. In this paper we will describe the design and implementation of the algorithm, using as a reference the human estrogen receptor alpha.

Resumo Limpo

dock virtual screen vs reach maximum potenti receptor display structur chang need accur ligand bind unfortun conform chang often poor repres experiment structur homolog model debilit dock perform recent shown receptor optim libero method ligandguid backbon ensembl receptor optim abl better discrimin activ ligand inact flexibleligand vs dock experi libero method reli use ligand inform select best perform individu pocket ensembl deriv normalmod analysi mont carlo present alibero new comput tool expand pocket select singl multipl allow automat iter samplingselect procedur select pocket perform dual method use exhaust combinatori search plus individu addit pocket select maxim discrimin known activ compound decoy result optim pocket show increas vs perform later use much larger unrel test set consist biolog activ inact ligand paper will describ design implement algorithm use refer human estrogen receptor alpha

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