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Modelling substrate specificity and enantioselectivity for lipases and esterases by substrate-imprinted docking

DOI: 10.1186/1472-6807-9-39

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Abstract:

Here we present a predictive and robust method to model substrate specificity and enantioselectivity of lipases and esterases that uses reaction intermediates and incorporates protein flexibility. Substrate-imprinted docking starts with covalent docking of reaction intermediates, followed by geometry optimisation of the resulting enzyme-substrate complex. After a second round of docking the same substrate into the geometry-optimised structures, productive poses are identified by geometric filter criteria and ranked by their docking scores. Substrate-imprinted docking was applied in order to model (i) enantioselectivity of Candida antarctica lipase B and a W104A mutant, (ii) enantioselectivity and substrate specificity of Candida rugosa lipase and Burkholderia cepacia lipase, and (iii) substrate specificity of an acetyl- and a butyrylcholine esterase toward the substrates acetyl- and butyrylcholine.The experimentally observed differences in selectivity and specificity of the enzymes were reproduced with an accuracy of 81%. The method was robust toward small differences in initial structures (different crystallisation conditions or a co-crystallised ligand), although large displacements of catalytic residues often resulted in substrate poses that did not pass the geometric filter criteria.The number of protein structures available to researchers has grown exponentially over the last two decades and more than 50 000 experimentally determined structure entries are now held in the Protein Data Bank [1]. Furthermore, comparative structure prediction allows to derive reliable structure models from sequence information [2]. In silico methods are being developed to predict affinity, activity, specificity, and selectivity of newly discovered proteins based on structure information [3]. In drug development, molecular docking is routinely used to identify new lead compounds by virtual screening of libraries of small compounds [4]. Recently, docking methods have also been succes

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