Combinations of these strategies have also been developed [18], [19], [20], [21], [22]

Combinations of these strategies have also been developed [18], [19], [20], [21], [22]. S3: Energy histograms of docking 11,129 ZINC fragment-like compounds against 6 targets involved in protein-protein interactions. Color code is defined as druggable (green) and non-druggable (red).(1.03 MB TIF) pone.0010109.s004.tif (1007K) GUID:?39636594-6633-485E-873C-C169564637C0 Figure S4: Chemical structures of a ligand co-crystallized with PTP1B (1ph0), binders identified in experimental screening, and high-ranking fragment hits identified from virtual fragment screening (fragments bound to the Cinepazide maleate catalytic site are colored in green and to the non-catalytic site in magenta).(1.01 MB TIF) pone.0010109.s005.tif (990K) GUID:?DA438A59-43B9-4B6C-A2C5-7CA800A35B2F Figure S5: Chemical structures of a ligand co-crystallized with P38 MAPK (1kv2), binders identified in experimental screening, and high-ranking fragment hits identified from virtual fragment screening using two different crystal structures, 1kv2 and 1kv1 (fragments bound to ATP site colored in green, lipophilic pocket colored in cyan, and allosteric site in magenta).(1.06 MB TIF) pone.0010109.s006.tif (1.0M) GUID:?91B76BD0-54E1-4257-BA9F-B5D4CDEB2806 Figure S6: The correlation between the virtual fragment screening hit Cinepazide maleate rates and the NMR screening results, using different energy cut-offs for defining the fragment-like compounds as hits in the virtual screen.(0.78 MB TIF) pone.0010109.s007.tif (764K) GUID:?1569B3E3-3DD3-434D-B56D-1C24CC096AF4 Abstract The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock 11000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates PSTPIP1 measured experimentally in a previously published NMR-based screening method. Secondly, we show that the fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors. Introduction Since the completion of the human genome, there has been much interest in the druggability of new potential drug targets, and what fraction of the proteome is druggable. In this paper we are concerned with protein druggability in the sense defined by Hopkins and Groom [1], i.e., the ability of a protein to bind small, drug-like molecules with high affinity. For many classes of protein binding sites, such as the ATP binding sites in kinases, there is little ambiguity about whether the site is druggable; the challenge in developing inhibitors in such cases is achieving selectivity and other desired properties. However, not all biological targets are druggable since only certain binding sites are complementary to drug-like compounds in terms of physicochemical properties (i.e. size, shape, polar interactions and hydrophobicity) [1], [2]. An accurate method for predicting druggability would be particularly valuable for assessing emerging classes of binding sites such as protein-protein interactions (PPI) [3] and allosteric sites [4], which are generally Cinepazide maleate considered more challenging but are attracting increasing interest in both academia and industry as drug targets. For example, while some PPI sites have led to potent small molecule inhibitors, others Cinepazide maleate have.