Benchmark Sets for Binding Hot Spot Identification in Fragment-Based Ligand Discovery.

Binding hot spots are regions of proteins that, due to their potentially high contribution to the binding free energy, have high propensity to bind small molecules. We present benchmark sets for testing computational methods for the identification of binding hot spots with emphasis on fragment-based ligand discovery. Each protein structure in the set binds a fragment, which is extended into larger ligands in other structures without substantial change in its binding mode.

Kinase Atlas: Druggability Analysis of Potential Allosteric Sites in Kinases.

The inhibition of kinases has been pursued by the pharmaceutical industry for over 20 years. While the locations of the sites that bind type II and III inhibitors at or near the adenosine 5'-triphosphate binding sites are well defined, the literature describes 10 different regions that were reported as regulatory hot spots in some kinases and thus are potential target sites for type IV inhibitors. Kinase Atlas is a systematic collection of binding hot spots located at the above ten sites in 4910 structures of 376 distinct kinases available in the Protein Data Bank.

The ClusPro web server for protein-protein docking.

The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank (PDB) format.

New additions to the ClusPro server motivated by CAPRI.

The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers.

ClusPro-DC: Dimer Classification by the Cluspro Server for Protein-Protein Docking.

ClusPro-DC (https://cluspro.bu.edu/) implements a straightforward approach to the discrimination between crystallographic and biological dimers by docking the two subunits to exhaustively sample the interaction energy landscape.

New Frontiers in Druggability.

A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here, we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins.

Detection of peptide-binding sites on protein surfaces: the first step toward the modeling and targeting of peptide-mediated interactions.

Peptide-mediated interactions, in which a short linear motif binds to a globular domain, play major roles in cellular regulation. An accurate structural model of this type of interaction is an excellent starting point for the characterization of the binding specificity of a given peptide-binding domain. A number of different protocols have recently been proposed for the accurate modeling of peptide-protein complex structures, given the structure of the protein receptor and the binding site on its surface.

Robust identification of binding hot spots using continuum electrostatics: application to hen egg-white lysozyme.

Binding hot spots, protein regions with high binding affinity, can be identified by using X-ray crystallography or NMR spectroscopy to screen libraries of small organic molecules that tend to cluster at such hot spots. FTMap, a direct computational analogue of the experimental screening approaches, uses 16 different probe molecules for global sampling of the surface of a target protein on a dense grid and evaluates the energy of interaction using an empirical energy function that includes a continuum electrostatic term. Energy evaluation is based on the fast Fourier transform correlation approach, which allows for the sampling of billions of probe positions.