Protein Flexibility in Structure-Based Drug Design: Method Development and Novel Mechanisms for Inhibiting HIV-1 Protease.

Abstract

Structure-based drug design (SBDD) has emerged as an important tool in drug discovery research. Traditionally, SBDD is based on a static crystal structure of the target protein. However, a protein in solution exists as an ensemble of energetically accessible conformations and is best described when all states are represented. Upon ligand binding, further conformational changes in the receptor can be induced. While ligand flexibility can be accurately reproduced, replicating the innumerable degrees of freedom of the protein is impractical due to limitations in computational power. Previously, Carlson et al. developed a robust method to generate receptor-based pharmacophore models based on an ensemble of protein conformations. The use of multiple protein structures (MPS) allows a range of conformational space that can be assumed by the protein to be sampled and hence, simulates the inherent flexibility of a binding site in a computationally feasible manner. Small molecule probes are used to map energetically favorable regions of each protein active site, and the MPS are then overlaid to identify the most important, chemically relevant features conserved across the conformations. Here, we have refined the MPS method by developing techniques to optimize different steps in the procedure. First, we outline tools to properly overlay flexible proteins based on the rigid regions of the structure by incorporating a Gaussian weight into a standard RMSD alignment. Atoms that barely move between the two conformations will have a greater weighting than those that have a large displacement. Using HIV-1 protease (HIV-1p) as a test case, we next examine the use of various sources of MPS: snapshots of an apo structure across a molecular dynamics simulation, a bound NMR ensemble, and a collection of bound crystal structures. Finally, we implement a simple ranking metric into the MPS method to quantify ligand overlap with a contour-based representation of the pharmacophore model. Overlapping in a region of the active site dense with pharmacophore spheres results in a higher ranking of a ligand pose. The refined MPS method and other computational techniques are then applied to study HIV-1p and investigate a novel inhibition mechanism by modulating its conformational behavior.