Abstract
Fragment-based drug discovery using NMR and x-ray crystallographic methods has proven utility but also non-trivial time, materials, and labor costs. Current computational fragment-based approaches circumvent these issues but suffer from limited representations of protein flexibility and solvation effects, leading to difficulties with rigorous ranking of fragment affinities. To overcome these limitations we describe an explicit solvent all-atom molecular dynamics methodology (SILCS: Site Identification by Ligand Competitive Saturation) that uses small aliphatic and aromatic molecules plus water molecules to map the affinity pattern of a protein for hydrophobic groups, aromatic groups, hydrogen bond donors, and hydrogen bond acceptors. By simultaneously incorporating ligands representative of all these functionalities, the method is an in silico free energy-based competition assay that generates three-dimensional probability maps of fragment binding (FragMaps) indicating favorable fragment∶protein interactions. Applied to the two-fold symmetric oncoprotein BCL-6, the SILCS method yields two-fold symmetric FragMaps that recapitulate the crystallographic binding modes of the SMRT and BCOR peptides. These FragMaps account both for important sequence and structure differences in the C-terminal halves of the two peptides and also the high mobility of the BCL-6 His116 sidechain in the peptide-binding groove. Such SILCS FragMaps can be used to qualitatively inform the design of small-molecule inhibitors or as scoring grids for high-throughput in silico docking that incorporate both an atomic-level description of solvation and protein flexibility.
Highlights
Fragment-based drug discovery relies on a simple premise: identify small-molecule fragments that bind to a target region of the protein and evolve or link them to create a larger highaffinity molecule
The resulting 3D free energy-based probability distributions (FragMaps) suggest the optimal placement of aliphatic hydrophobic, aromatic, hydrogen-bond donor, and hydrogen-bond acceptor functionalities in a binding pocket
SILCS FragMaps computed for the BCL-6 oncoprotein do an excellent job of reproducing the binding interactions of the non-homologous SMRT and BCOR peptides with the BCL-6 protein and include biologically relevant conformational changes in the binding pocket
Summary
Fragment-based drug discovery relies on a simple premise: identify small-molecule fragments that bind to a target region of the protein and evolve or link them to create a larger highaffinity molecule. These two methods benefit from the fact that they yield structural information about fragment binding poses, which is useful for confirming that two fragments bind to two adjacent sites and can be productively linked Despite their utility, there are significant time, labor, and materials costs associated with experimental fragment-based drug discovery approaches. In computational approaches the protein is assumed to be rigid and fragments sample the surface of the rigid protein using an energy function that models the solvent environment as a continuum [8,9,10,11,12] As a result, these methods are limited in their ability to accurately account for protein conformational heterogeneity and solvation effects, contributions that are essential to compute free energies of binding [13]. All-atom explicit-solvent molecular dynamics (MD) simulations of proteins give an atomic-level-of-detail description of the motions
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