Free energy methods for pharmaceutical drug discovery
Samuel C. Gill, Nathan M. Lim, Patrick B. Grinaway, Ariën S. Rustenburg, Josh Fass, Gregory A. Ross, John D. Chodera and David L. Mobley
Accurately predicting protein-ligand binding affinities and binding modes is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. [More…]
Plans are starting to shape up for the SAMPL6 blind prediction challenge, coming later this year! (Our overall SAMPL initiative is still unfunded and we need your input, but we are able to proceed with SAMPL6).
SAMPL6 will focus on host-guest binding on some familiar systems, as well as logD prediction with known (provided) pKa values for a series of small organic compounds. [More…]
For some time, we’ve been involved with running the SAMPL series of blind challenges focused on driving progress in modeling of physical properties and binding (see also the D3R page and our SAMPL NIH proposal) and recently, we’ve sought support from the NIH for this work. However, this is an unconventional type of proposal for the NIH, since the focus is on driving progress of other people’s methods. [More…]
Interested in developing and applying new methods relating to free energy calculations? I have a postdoc position which just opened up in this area, working with OpenMM to advance binding free energy techniques and apply/validate them on problems relating to drug discovery. This is an NIH-funded project (1R01GM108889-01) and interfaces closely with other work going on in the group and elsewhere. [More…]
