Advances in all atom sampling methods for modeling protein-ligand binding affinities

Abstract

Conformational dynamics plays a fundamental role in the regulation of molecular recognition processes. Conformational heterogeneity and entropy variations upon binding, although not always evident from the analysis of structural data, can substantially affect affinity and specificity. Computer modeling is able to provide some of the most direct insights into these aspects of molecular recognition. We review recent physics-based computational studies that employ advanced conformational sampling algorithms and effective potentials to model the three main classes of degrees of freedom relevant to the binding process: ligand positioning relative to the receptor, ligand and receptor internal reorganization, and hydration. Collectively these studies show that all of these elements are important for proper modeling of protein-ligand interactions.

Figure 1

Illustrative example of the sampling enhancement achieved by parallel replica exchange sampling in λ space. The plot shows the value of λ assumed by a particular replica of the system as a function of time. In this example, (taken from the BEDAM trajectory data of reference [13] for catechol binding to L99A/M102Q T4-lysozyme) λ = 1 corresponds to full ligand-receptor interactions and λ = 0 to no ligand-receptor interactions. Above the plot, the structure frames corresponding to 0, 200, 400, and 600 ps simulation times are shown. The trajectory starts near λ = 1 with catechol forming a hydrogen bond (yellow line) with Gln102 of T4-lysozyme (first frame). Then the replica progressively assumes smaller values of λ and concurrently the ligand partially dissociates from the receptor (second and third frames). Subsequently the ligand reassociates with Gln102 in a different hydrogen bonding configuration when λ increases again (fourth frame).