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J Comput Chem. 2013 May 30;34(14):1226-1240. doi: 10.1002/jcc.23245. Epub 2013 Feb 22.

Grid-based molecular footprint comparison method for docking and de novo design: application to HIVgp41.

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Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, New York 11794, USA.
Institute of Chemical Biology & Drug Discovery, Stony Brook University, Stony Brook, New York 11794, USA.
Laufer Center for Physical & Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA.
Contributed equally


Scoring functions are a critically important component of computer-aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multigrid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per-residue basis in a way that resembles a known reference. The grid-based FPS method is much faster than its Cartesian-space counterpart, which makes it computationally tractable for on-the-fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co-crystal structures, for crossdocking, and for database enrichment, and (iii) grid-based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method is available in the program DOCK6.

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