title: Hot spot analysis for driving the development of hits into leads in fragment-based drug discovery.
abstract: Fragment-based drug design (FBDD) starts with finding fragment-sized compounds that are highly ligand efficient and can serve as a core moiety for developing high-affinity leads. Although the core-bound structure of a protein facilitates the construction of leads, effective design is far from straightforward. We show that protein mapping, a computational method developed to find binding hot spots and implemented as the FTMap server, provides information that complements the fragment screening results and can drive the evolution of core fragments into larger leads with a minimal loss or, in some cases, even a gain in ligand efficiency. The method places small molecular probes, the size of organic solvents, on a dense grid around the protein and identifies the hot spots as consensus clusters formed by clusters of several probes. The hot spots are ranked based on the number of probe clusters, which predicts the binding propensity of the subsites and hence their importance for drug design. Accordingly, with a single exception the main hot spot identified by FTMap binds the core compound found by fragment screening. The most useful information is provided by the neighboring secondary hot spots, indicating the regions where the core can be extended to increase its affinity. To quantify this information, we calculate the density of probes from mapping, which describes the binding propensity at each point, and show that the change in the correlation between a ligand position and the probe density upon extending or repositioning the core moiety predicts the expected change in ligand efficiency.
authors.affiliation: Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, Massachusetts 02215, USA.
authors.forename: David R
authors.initials: DR
authors.lastname: Hall
authors.forename: Chi Ho
authors.initials: CH
authors.lastname: Ngan
authors.forename: Brandon S
authors.initials: BS
authors.lastname: Zerbe
authors.forename: Dima
authors.initials: D
authors.lastname: Kozakov
authors.forename: Sandor
authors.initials: S
authors.lastname: Vajda
mesh_terms: D001665:Binding Sites; D001688:Biological Products / Q000737:chemistry* / Q000494:pharmacology; D017076:Computer-Aided Design; D018360:Crystallography, X-Ray; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D020128:Inhibitory Concentration 50; D008024:Ligands; D008958:Models, Molecular; D015335:Molecular Probes / Q000737:chemistry; D011485:Protein Binding; D011506:Proteins / Q000819:agonists / Q000037:antagonists & inhibitors / Q000737:chemistry*; D013329:Structure-Activity Relationship
chemical_list: D001688:Biological Products; D008024:Ligands; D015335:Molecular Probes; D011506:Proteins