Computer Simulation of Protein-Ligand Interactions

Abstract

The accurate modeling of protein-ligand interactions, like any prediction of macromolecular structure, requires an energy function of sufficient detail to account for all relevant interactions and a conformational search method that can reliably find the energetically favorable conformations of a heterogeneous system. Both of these prerequisites represent daunting challenges. Consequently, the routine docking of small molecules or peptides to proteins in their correct binding modes, and the reliable ranking of binding affinities remain unsolved problems. Nonetheless, computational techniques are continually evolving so as to broaden the range of feasible applications, and the accuracy of predictions and theoretical approaches can often be of great help in guiding and interpreting experiments. We discuss the energetics of protein-ligand systems and survey conformational searching techniques. We illustrate how molecular modeling of a protein-ligand complex sheds light on the observed resistance of a mutant dihydrofolate reductase to the antibiotic trimethoprim. In another example, we show that relaxation of side chains in different crystal structures of the same complex, benzamidine bound to trypsin, is needed to draw sensible conclusions from the calculations. The results of these relatively simple conformational searches underscore the importance of incorporating protein flexibility in simulations of protein-ligand interactions, even in the context of relatively rigid binding pockets.

Comparing and combining implicit ligand sampling with multiple steered molecular dynamics to study ligand migration processes in heme proteins

“…27,[33][34][35][36] Moreover, although standard molecular dynamics at the nanosecond time scale is not able to provide a complete picture of the ligand migration process, and very long simulations must be performed to allow the ligand to sample the tunnel/cavity system, [37][38][39][40][41] this difficulty can be overcome by the use of different strategies that enhance sampling at an affordable computational cost. Accordingly, several schemes have been developed to study the small ligand migration process in the last decade, as recently reviewed by Arroyo-Mañez et al 42 These methods are based on the use of different approaches: such as the use of guiding potentials, or simulation at different temperatures for the protein and the ligand, 43 use of a hierarchical optimization approach, 44 the use of grids, 45 or also previously computed MD trajectory, as further explained below.…”

Molecular Modeling of the Axial and Circumferential Elastic Moduli of Tubulin

“…In these extended simulations, no more than 5-10% difference was observed in total energy. Only one structure failed to stabilize (TBA8_CAEEL), regard- (32). The majority of the structural data for MT(microtubule)s has been acquired from highly purified preparations, thus our simulations most likely closely represent the material behavior of tubulin in isolated microtubules.…”

Dioxygen affinity in heme proteins investigated by computer simulation

“…Computational techniques for modeling biomolecules have emerged as an important tool to complement experimental information [14][15][16][17][18][19]. The in silico generated models and data are essential for analyzing structural and kinetic details that are difficult to capture experimentally.…”