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J Chem Inf Model. 2013 Apr 22;53(4):836-51. doi: 10.1021/ci4000163. Epub 2013 Apr 11.

In silico fragment-based drug discovery: setup and validation of a fragment-to-lead computational protocol using S4MPLE.

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Université de Strasbourg, 1 rue B. Pascal, Strasbourg 67000, France.


This paper describes the use and validation of S4MPLE in Fragment-Based Drug Design (FBDD)--a strategy to build drug-like ligands starting from small compounds called fragments. S4MPLE is a conformational sampling tool based on a hybrid genetic algorithm that is able to simulate one (conformer enumeration) or more molecules (docking). The goal of the current paper is to show that due to the judicious design of genetic operators, S4MPLE may be used without any specific adaptation as an in silico FBDD tool. Such fragment-to-lead evolution involves either growing of one or linking of several fragment-like binder(s). The native ability to specifically "dock" a substructure that is covalently anchored to its target (here, some prepositioned fragment formally part of the binding site) enables it to act like dedicated de novo builders and differentiates it from most classical docking tools, which may only cope with non-covalent interactions. Besides, S4MPLE may address growing/linking scenarios involving protein site flexibility, and it might also suggest "growth" moves by bridging the ligand to the site via water-mediated interactions if H2O molecules are simply appended to the input files. Therefore, the only development overhead required to build a virtual fragment→ligand growing/linking strategy based on S4MPLE were two chemoinformatics programs meant to provide a minimalistic management of the linker library. The first creates a duplicate-free library by fragmenting a compound database, whereas the second builds new compounds, attaching chemically compatible linkers to the starting fragments. S4MPLE is subsequently used to probe the optimal placement of the linkers within the binding site, with initial restraints on atoms from initial fragments, followed by an optimization of all kept poses after restraint removal. Ranking is mainly based on two criteria: force-field potential energy and RMSD shifts of the original fragment moieties. This strategy was applied to several examples from the FBDD literature with good results over several monitored criteria: ability to generate the optimized ligand (or close analogs), good ranking of analogs among decoy compounds, and accurate predictions of expected binding modes of reference ligands. Simulations included "classical" covalent growing/linking, more challenging ones involving binding site conformational changes, and growth with optional recognition of putatively favorable water-mediated interactions.

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