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Facilitating lead optimization with Receptor Image from Fragment Footprinting (RIFF)
Author(s) -
Dwyer Donard S.
Publication year - 2008
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.22.1_supplement.654.2
Subject(s) - pharmacophore , footprinting , fragment (logic) , drug discovery , ligand (biochemistry) , computational biology , chemistry , binding site , binding pocket , stereochemistry , dna , computer science , algorithm , biology , receptor , biochemistry , base sequence
Lead optimization in drug discovery programs is quite challenging especially when the structure of the drug target is not known. To overcome this limitation, we are developing a computational method called Receptor Image from Fragment Footprinting or RIFF. The goal is to devise a general method for creating realistic models of binding sites starting with only the structure of established ligands or active compounds from screening. The drug or fragment is soaked with a layer of solvent composed of individual amino acids, which is then dispersed (evaporates) from the ligand in molecular dynamics (MD) simulations as a function of time and temperature. The tightest‐binding amino acids from the MD simulations define potential binding modes and can be used to construct model binding sites. RIFF was applied to ligands that interact with HIV reverse transcriptase (HIV‐RT) to validate the method. RIFF correctly identified 6/7 amino acids in the binding site of HIV‐RT (composition matching) located in close proximity to their positions in the actual binding site determined by x‐ray crystallography (topology matching). This method will complement pharmacophore‐based approaches and may speed drug discovery.