Significant Enhancement of Docking Sensitivity Using Implicit Ligand Sampling

Abstract

The efficient and accurate quantification of protein-ligand interactions using computational methods is still a challenging task. Two factors strongly contribute to the failure of docking methods to predict free energies of binding accurately: the insufficient incorporation of protein flexibility coupled to ligand binding and the neglected dynamics of the protein-ligand complex in current scoring schemes. We have developed a new methodology, named the ‘ligand-model’ concept, to sample protein conformations that are relevant for binding structurally diverse sets of ligands. In the ligand-model concept, molecular-dynamics (MD) simulations are performed with a virtual ligand, represented by a collection of functional groups that binds to the protein and dynamically changes its shape and properties during the simulation. The ligand model essentially represents a large ensemble of different chemical species binding to the same target protein. Representative protein structures were obtained from the MD simulation, and docking was performed into this ensemble of protein conformation. Similar binding poses were clustered, and the averaged score was utilized to re-rank the poses. We demonstrate that the ligand-model approach yields significant improvements in predicting native-like binding poses and quantifying binding affinities compared to static docking and ensemble docking simulations into protein structures generated from an apo MD simulation.

Utilizing Experimental Data for Reducing Ensemble Size in Flexible-Protein Docking

“…21 However, the same trend was not observed for AChE, where increased binding pose prediction quality 21 didn’t translate into improved enrichment. Importantly, no significant reduction in enrichment performance was observed for any of the five protein systems.…”

“…For additional details on Limoc and its default settings we refer to our recent publication on this method. 21 …”

“…21 In this method, MD simulations are performed with a dynamically changing set of restrained functional groups in the binding site of the protein, essentially representing a large hypothetical ensemble of different chemical species binding to the same target protein. Starting from an apo structure, the ligand-model approach is used to derive an EPS used for docking.…”

Understanding the challenges of protein flexibility in drug design

“…For example, ensembles derived from NMA or Monte Carlo can be filtered using ligand information to select representative protein conformations [75]. Using a dynamic virtual ligand (represented by a collection of functional groups), an MD simulation of the binding event can generate promising protein conformations [94], [95]. Another method generates an ensemble of protein conformations by docking flexible ligands to a flexible receptor, using known active compounds [96].…”

Studies on the binding modes of Lassa nucleoprotein complexed with m7GpppG and dTTP by molecular dynamic simulations and free energy calculations

“…However, the mechanism of induced fit is put forward that ligand binding induces a conformational change of protein to adapt each other when the ligand binds to a low-energy conformation of the unbound protein (Csermely, Palotai, & Nussinov, 2010). Therefore, if the ligand-free protein structure is used as the receptor, the rigid docking cannot sufficiently incorporate the protein flexibility induced by ligand; while if the ligand-bound protein conformations taken from the MD trajectory are used as the receptors, other ligands may be unable to bind to the ensemble of conformations because the MD trajectory of the ligand-bound form of the protein is biased towards the specific ligand used in the simulation (Xu & Lill, 2011). In order to get the plausible binding mode of m7GpppG to NP, conformations sampled every 1 ns from the MD trajectories (1.5-10.5 ns) of the dTTP complex, the crystal structure of native NP, and the dTTP complex are used as receptors to which m7GpppG are docked (the C domain of NP was truncated in all these receptors), 12 docking experiments are done totally.…”