Acpharis

In fragment-based drug design (FBDD), libraries of low molecular weight compounds are screened against a receptor. Due to their size, fragment hits typically bind with weak affinities by forming a handful of highly efficient interactions with the receptor. Such fragment hits must be expanded into more potent lead compounds in order to achieve higher binding affinities. Approaches for expanding fragments to leads include growing-the iterative expansion of the scaffold, and merging-the linking of two fragment hits. In both cases the design can be facilitated by information on the ligand binding preferences of the target protein. Here we describe a protocol for fragment expansion using E-FTMap, an automated web server that identifies important pharmacophore binding regions within a binding site of proteins using the receptor structure alone. E-FTMap distributes 119 small organic probes across a binding site, identifies energy minima in which similar probes bind, and clusters probes by their atom types to identify regions which preferably bind specific atom types. Unless a priori known, the binding site for this analysis can be identified by our FTMap server that uses only 16 probes to find binding hot spots that are generally preferable for ligand binding, whereas the subsequent use of E-FTMap provides atom-specific information. The utility of E-FTMap as a tool for guiding the expansion of fragments into higher affinity binders is demonstrated by its application to 17 proteins that have been targeted by FBDD. The E-FTMap webserver is publicly accessible at https://eftmap.bu.edu/.

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

The design of PROteolysis-TArgeting Chimeras (PROTACs) requires bringing an E3 ligase into proximity with a target protein to modulate the concentration of the latter through its ubiquitination and degradation. Here, we present a method for generating high-accuracy structural models of E3 ligase-PROTAC-target protein ternary complexes. The method is dependent on two computational innovations: adding a "silent" convolution term to an efficient protein-protein docking program to eliminate protein poses that do not have acceptable linker conformations and clustering models of multiple PROTACs that use the same E3 ligase and target the same protein. Results show that the largest consensus clusters always have high predictive accuracy and that the ensemble of models can be used to predict the dissociation rate and cooperativity of the ternary complex that relate to the degrading activity of the PROTAC. The method is demonstrated by applications to known PROTAC structures and a blind test involving PROTACs against BRAF mutant V600E. The results confirm that PROTACs function by stabilizing a favorable interaction between the E3 ligase and the target protein but do not necessarily exploit the most energetically favorable geometry for interaction between the proteins.

****** Release_2014.09.2 ******* (Changes relative to Release_2014.09.1) Acknowledgements: Sereina Riniker, Nadine Schneider, Paolo Tosco Bug Fixes: SMILES parser doing the wrong thing for odd dot-disconnected construct (github issue #378) O3A code generating incorrect results for multiconformer molecules (github issue #385) Suppliers probably not safe to read really large files (github issue #392) Torsion constraints not worrking properly for negative torsions (github issue #393) Core leak in reactions (github issue #396)