Fragment-based drug discovery (FBDD) is a combinatorial approach in which individual fragments binding to regions of the target site ar selected from a fragment library, and then combined to form potential lead compounds. Since it is easier to find small molecules that complement a particular subsite within a binding site than larger molecules that are complementary to the entire site, FBDD usually yields higher hit rates than high throughput screening. Once initial fragment hits are identified, the goal of FBDD is to expand them into larger and stronger-binding lead compounds through medicinal chemistry. This step relies on the premise that the interactions between a fragment hi and the protein are sufficiently strong and specific that the fragment binding mode willbe robust and thus will be conserved as the fragment is grown. In spite of the high hit rate, for a variety of targets the standard fragment libraries do not yield stable binding hits that can serve as starting points for FBDD. The goal of this proposal is to develop and validate software that, given the 3D structure of a target protein, enables the selection of fragments that provid hits with sufficiently stable binding modes for expansion. The approach is based on th concept of binding hot spots, i.e., regions of the binding site that contribute most o the free energy of binding any ligand, determined by the protein mapping software developed by Acpharis. Recent studies show that for a given fragment, a high degree of overlap with the top hot spot leads to robust binding. Accordingly, the proposed protocol includes (1 preparing a large initial collection of fragments, e.g., by filtering for PAINS; (2) determinin the binding hot spots and pharmacophores of the target protein; (3) shape-based filtering for fragments that have the required overlap with the main hot spot; (4) further filtering to select fragments with pharmacophores that overlap well with the structure-based pharmacophores from mapping; (5) another filter based on docking and scoring of the fragments from the previous steps. The protocol will also explore some elements of fragment expansion by determining chemical handles, i.e., sites on the fragments where functional groups can be added, e.g., by searching for larger compounds that have the selected fragments as substructures, and testing whether such compounds extend into additional hot spots that contribute to the binding free energy. The protocol will be demonstrated by constructing fragment libraries for the discovery of novel compounds to disrupt the interaction between the immunoregulatory cytokine Interleukin 2 (IL-2) and the IL-2 receptor subunit IL-2R?, which is a well-studied example of protein-protein interacton targets. The library will be screened by (15N/1H) heteronuclear single quantum coherence (HSQC) NMR measurements, and the results of the experiments will be used to improve the library construction algorithm.
Fragment based drug discovery (FBDD) is a combinatorial approach in which individual fragments binding to regions of the target site are selected from a fragment library, and then combined to form potential lead compounds. The goal of this proposal is to develop and validate a protocol and software that, given a taget protein, enable selecting a library of fragments that provide hits with robust binding modes and thus increase the likelihood of successful FBDD.
| Padhorny, Dzmitry; Hall, David R; Mirzaei, Hanieh et al. (2018) Protein-ligand docking using FFT based sampling: D3R case study. J Comput Aided Mol Des 32:225-230 |
