Free-energy based simulations like molecular dynamics (MD) are increasingly able to predict binding poses and binding affinities of small molecules to proteins. Unfortunately, due to the vast conformational spaces of ligand plus protein, MD often comes at a prohibitively high computational cost. Modelling Employing Limited Data (MELD) is an accelerator of MD simulations that uses external information to limit the search space. MELD offers speed-ups of orders of magnitudes compared to straight MD.  MELD is a Bayesian framework that allows for a broad range of types of focusing information, including that which is sparse, ambiguous, and uncertain. Importantly, MELD preserves the proper Boltzmann populations and free energies that enhanced-sampling MD methods can provide.<br/>We show that MELD accelerated MD (MELD x MD) gives good docking poses, and often affinities, of small-molecules, peptides, and proteins bound to proteins.  Also, MELD x MD is fast enough for testing in time-sensitive blind competitions such as CAPRI and D3R.

Predicting small molecule binding to proteins by integrating information into MD simulations

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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