Exploring the role of receptor flexibility in structure-based drug discovery

Abstract

The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads.

Understanding the challenges of protein flexibility in drug design

“…It does not allow for larger conformational changes, such as large side-chain rotations or backbone motions [34], [35]. Another drawback of soft docking is its tendency to increase the rate of false positives [25], [36]. Nowadays, soft docking is used only rarely on its own, but sometimes as a first docking step within more complex methods (see Section II-D) [37], [38].…”

“…Unfortunately, MD is strongly limited by the available computational power. Additionally, MD is known for often being unable to cross high-energy barriers, and exploring only local minima of the rugged energy landscape [36], [81]. Therefore, performing a reasonable exploration of the protein's conformational space can be computationally extremely high.…”

“…Therefore, performing a reasonable exploration of the protein's conformational space can be computationally extremely high. A solution is to introduce artificial biases into MD simulations by applying enhanced-sampling techniques (e.g., temperature-accelerated replica exchange, umbrella sampling, metadynamics) [90] or using accelerated MD [36], [81]. Other methods have been suggested, combining MD with essential dynamics [91] or with molecular mechanics and quantum mechanics [92].…”

“…Instead, building a compact ensemble of representative protein conformations, as in ensemble docking, can be a useful preprocessing step. As this is done only once, this can involve more sophisticated and computationally-expensive approaches to sample large-scale conformational changes [36], [140]- [144]. Additionally, selective docking can be used for local refinement of the binding mode for each ligand in the dataset.…”

Structural and Dynamic Insights of the Interaction between Tritrpticin and Micelles: An NMR Study

“…The most accepted theory is that with conformational selection, the dominant bonding process occurs in conjunction with structural adjustment (induced fit) to optimize the interaction (63)(64)(65)(66)(67).…”