Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Monday Speaker Abstracts

Objectively and Automatically Building Multi-conformer Ligand Models in Electron Densities Gydo Van Zundert 1 , Daniel Keedy 2 , Pooja Suresh 2 , Amelie Heliou 3 , Kenneth Borrelli 1 , Tyler Day 1 , James Fraser 2 , Henry Van den Bedem 1 . 1 Schrodinger, New York, NY, USA, 2 UCSF, San Francisco, CA, USA, 3 Inria, Palaiseau, France, 4 SLAC National Accelerator Laboratory, Menlo Park, CA, USA. Structure-based drug design is often challenged by an inadequate understanding of the conformational dynamics of ligands and their receptors. X-ray-crystallography is generally the method of choice for resolving the structure of macromolecular molecules and investigating the binding pose of ligands. While the electron density represents a time-averaged representation of the underlying conformational ensemble, in the majority of cases the data are interpreted to represent a single conformation at unit occupancy. Temperature factors inadequately account for atom position ambiguity and thermal motion from their averaged positions. Multiple, alternative ligand conformations are under-represented, even in high resolution datasets. Moreover, the impact of alternative conformations for ligands remains underexplored. The presence of different binding poses for ligands would have important consequences for rational drug design and a fundamental understanding of the underlying binding mechanisms. Here, we show that evidence for alternative ligand poses is common in the PDB, including for pharmaceutically highly relevant targets. In addition, we introduce a fast, automated method for building multi-conformer ligand models in electron densities by hierarchically sampling and building the ligand’s degrees of freedom. We rely on powerful, state-of-the-art solvers to identify a minimal set of conformations to collectively explain the density and for determining the individual occupancies. This new tool provides an objective view on the ligand’s structural heterogeneity, while paving the way for a deep investigation of its impact on rational drug design.

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