by Davide Sabbadin, PhD.
Brief abstract: Supervised Molecular Dynamics (SuMD) is a computational technique for investigating unbiased receptor-ligand recognition pathways, in the nanosecond timescale, by combining molecular dynamics simulations and a tabu-like algorithm.
G protein-coupled receptors (GPCRs) are transmembrane proteins that play a crucial role in linking various extracellular inputs with diverse cellular responses. It has been estimated that GPCRs constitute the target of about half of all drugs in clinical use today. Thus, from structural and pharmacological perspectives, represent an ideal target to design molecules with potential therapeutic effect (1). Understanding the GPCR-ligand recognition process is crucial for the development of drug candidates with favorable pharmacodynamic profiles.
Recent technological innovation has allowed Molecular Dynamics (MD) simulations to reach timescales comparable with those on which most biomolecular events of interest take place, thus closing the gap between theoretical models and experiments (2,3). Although now possible, it remains expensive to use unbiased Molecular Dynamics to quantitatively characterise ligand-protein binding.
Supervised Molecular Dynamics (SuMD) addresses this shortcoming, enabling the complete ligand-protein recognition process to be elucidated, using unbiased all-atom Molecular Dynamics, in a reduced timescale. The general method is not sensitive to the ligand’s starting position, chemical structure and receptor binding affinity (4).
As shown in the figure below, SuMD uses a standard MD simulation in which the ligand-receptor docking pathway is supervised by a tabu-like algorithm. During the production of the MD trajectory the distances between the center of masses of the ligand atoms and the residues composing the orthosteric binding site of the GPCR (dcmL-R) are monitored over a fixed time window (Δtck, e.g. 200 ps). An arbitrary number of distance points (n: a, b, c, d, e) per each checkpoint trajectory are collected and a linear function f(x)=m·x is fitted on the distance points at the end of the checkpoint time.
The tabu-like algorithm is applied to increase the probability of ligand-receptor binding events occuring without introducing bias to the MD simulation. More precisely, if m<0, the ligand-receptor distance is likely to be shortened over the checkpoint time and so the MD simulation is restarted from the last produced set of coordinates. Otherwise, the simulation is restored from the original set of coordinates and random velocities drawn from the Boltzman distribution are reassigned. This has the effect of causing the restarted simulation to explore a different region of configuration space, while maintaining sampling from the correct NVT ensemble. The tabu-like supervision algorithm is repeatedly applied until ligand-receptor distance (dcmL-R) is less than 5 Å.
Supervised Molecular Dynamics (SuMD) can be fully integrated into
ACEMD and enable investigating the complete binding process, in a nanosecond time scale, and to reproduce with high accuracy the crystallographic pose of protein-ligand complexes. Moreover, using SuMD simulations, it is possible to easily determine and characterize all possible metastable sites on the binding pathway to the orthosteric pose.
Figure: High affinity antagonist ZM241385 (yellow spheres) recognition pathway, using Supervised Molecular Dynamics (SuMD), to the membrane embedded human A2A Adenosine Receptor. During classic Molecular Dynamics (MD) simulations, the receptor-ligand distance vector (dcmL-R) is monitored and supervised in real time by a tabu-like algorithm. This computational method allows investigating the multifaceted unbiased ligand binding process in a reduced time scale of orders of magnitude, while taking advantages of the all-atom MD simulations accuracy of a GPCR-ligand complex embedded into explicit lipid-water environment.
Video: ZM241385-human A2A Adenosine Receptor recognition mechanism using Supervised Molecular Dynamics (SuMD). Simulation time in nanoseconds is reported. Van der Waals spheres represent ZM241385 atoms. Ligand nitrogen atoms are depicted in blue, oxygen atoms in red while carbon atoms are colored in white. Receptor ribbon representation is viewed from the membrane side facing transmembrane domain 6 (TM6) and transmembrane domain 7 (TM7). Hydrogen atoms are not displayed. Ligand binding sites are highlighted by arrows.
(1) Jacobson, K. A.; Costanzi, S. New Insights for Drug Design from the X-Ray Crystallographic Structures of G-Protein-Coupled Receptors. Mol. Pharmacol. 2012, 82, 361–371.
(2) Dror, R. O.; Dirks, R. M.; Grossman, J. P.; Xu, H.; Shaw, D. E. Biomolecular Simulation: A Computational Microscope for Molecular Biology. Annu. Rev. Biophys. 2012, 41, 429–452.
(3) Buch, I.; Giorgino, T.; De Fabritiis, G. Complete Reconstruction of an Enzyme-Inhibitor Binding Process by Molecular Dynamics Simulations. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 10184–10189.
(4) Sabbadin, D.; Moro, S. Supervised Molecular Dynamics (SuMD) as a Helpful Tool to Depict GPCR-Ligand Recognition Pathway in a Nanosecond Time Scale. J. Chem. Inf. Model. 2014.