The full activation mechanism of the adenosine A1 receptor revealed by GaMD and Su-GaMD simulations.

The full activation process of G protein-coupled receptor (GPCR) plays an important role in cellular signal transduction. However, it remains challenging to simulate the whole process in which the GPCR is recognized and activated by a ligand and then couples to the G protein on a reasonable simulation timescale. Here, we developed a molecular dynamics (MD) approach named supervised (Su) Gaussian accelerated MD (GaMD) by incorporating a tabu-like supervision algorithm into a standard GaMD simulation. By using this Su-GaMD method, from the active and inactive structure of adenosine A1 receptor (A1R), we successfully revealed the full activation mechanism of A1R, including adenosine (Ado)-A1R recognition, preactivation of A1R, and A1R-G protein recognition, in hundreds of nanoseconds of simulations. The binding of Ado to the extracellular side of A1R initiates conformational changes and the preactivation of A1R. In turn, the binding of Gi2 to the intracellular side of A1R causes a decrease in the volume of the extracellular orthosteric site and stabilizes the binding of Ado to A1R. Su-GaMD could be a useful tool to reconstruct or even predict ligand-protein and protein-protein recognition pathways on a short timescale. The intermediate states revealed in this study could provide more detailed complementary structural characterizations to facilitate the drug design of A1R in the future.

Modified Protein-Water Interactions in CHARMM36m for Thermodynamics and Kinetics of Proteins in Dilute and Crowded Solutions.

Proper balance between protein-protein and protein-water interactions is vital for atomistic molecular dynamics (MD) simulations of globular proteins as well as intrinsically disordered proteins (IDPs). The overestimation of protein-protein interactions tends to make IDPs more compact than those in experiments. Likewise, multiple proteins in crowded solutions are aggregated with each other too strongly. To optimize the balance, Lennard-Jones (LJ) interactions between protein and water are often increased about 10% (with a scaling parameter, λ = 1.1) from the existing force fields. Here, we explore the optimal scaling parameter of protein-water LJ interactions for CHARMM36m in conjunction with the modified TIP3P water model, by performing enhanced sampling MD simulations of several peptides in dilute solutions and conventional MD simulations of globular proteins in dilute and crowded solutions. In our simulations, 10% increase of protein-water LJ interaction for the CHARMM36m cannot maintain stability of a small helical peptide, (AAQAA)3 in a dilute solution and only a small modification of protein-water LJ interaction up to the 3% increase (λ = 1.03) is allowed. The modified protein-water interactions are applicable to other peptides and globular proteins in dilute solutions without changing thermodynamic properties from the original CHARMM36m. However, it has a great impact on the diffusive properties of proteins in crowded solutions, avoiding the formation of too sticky protein-protein interactions.

Replica sub-permutation method for molecular dynamics and monte carlo simulations.

We propose an improvement of the replica-exchange and replica-permutation methods, which we call the replica sub-permutation method (RSPM). Instead of considering all permutations, this method uses a new algorithm referred to as sub-permutation to perform parameter transition. The RSPM succeeds in reducing the number of combinations between replicas and parameters without the loss of sampling efficiency. For comparison, we applied the replica sub-permutation, replica-permutation, and replica-exchange methods to a ß-hairpin mini protein, chignolin, in explicit water. We calculated the transition ratio and number of tunneling events in the parameter space, the number of folding-unfolding events, the autocorrelation function, and the autocorrelation time as measures of sampling efficiency. The results indicate that among the three methods, the proposed RSPM is the most efficient in both parameter and conformational spaces. © 2019 Wiley Periodicals, Inc.

Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

BACKGROUND: In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. RESULTS: The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. CONCLUSIONS: Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

[Development of Membrane Permeability Coefficient by Means of Novel Molecular Dynamics Methods].

The membrane permeability, and its evaluation, is crucial factor in the process of uptake of compounds from outside to inside the cell and in the inhibition of the activity of disease-causing target proteins. Although molecular dynamics (MD) simulations have been shown to be able to reproduce the conformational changes of compounds occurring during membrane permeation, it is still challenging to extract the membrane permeability at an affordable computational workload solely by conventional MD. Indeed, the time scale accessible by MD is far below the one characterizing the actual permeation process. Phenomena occurring in living organisms escaping the reach of standard MD are generally referred to as biological rare events, and the membrane permeation process is one of them. To overcome this time-scale problem, several enhanced sampling methods have been proposed over the years to improve conformational sampling. In this review, a hybrid sampling method that combines the parallel cascade selection MD (PaCS-MD) and the outlier flooding method (OFLOOD), introduced and developed by our group, is proposed as a tool to study the membrane permeation from structural sampling (rare-event sampling). The obtained trajectories are used to estimate the free energy profiles for the membrane permeation and to compute the membrane permeation coefficients. Moreover, we present an example of application of the free energy reaction network method as a versatile way for incorporating explicitly into reaction coordinates the degrees of freedom related to internal motion.

Binding of human serum albumin with uranyl ion at various pH: an all atom molecular dynamics study.

Uranium is routinely handled in various stages of nuclear fuel cycle and its association with human serum albumin (HSA) has been reported in literature, however, their binding characteristics still remains obscure. The present study aims to understand interaction of uranium with HSA by employing all atom molecular dynamics simulation of the HSA-metal ion complex. His67, His247 and Asp249 residues constitute the major binding site of HSA, which capture the uranyl ion (UO22+). A total of six sets of initial coordinates are used for Zn2+-HSA and UO22+-HSA system at pH = 4, 7.4 and 9, respectively. Enhance sampling method, namely, well-tempered meta-dynamics (WT-MtD) is employed to study the binding and un-binding processes of UO22+ and Zn2+ ions. Potential of mean force (PMF) profiles are generated for all the six sets of complexes from the converged WT-MtD run. Various basins and barriers are observed along the (un)binding pathways. Hydrogen bond dynamics and short-range Coulomb interactions are evaluated from the equilibrium run at each basins and barriers for both the ions at all pH values. The binding of UO22+ ion with HSA is the result of the dynamical balance between UO22+-HSA and UO22+-water short range Coulomb interactions. Zn2+ ion interact more strongly than UO22+ at all pH through short range Coulomb interactions. PMF values further concludes that UO22+ cannot associate to the Zn2+ bound HSA protein but can be captured by free HSA at all pH values i.e. endosomal, alkaline and physiological pH.Communicated by Ramaswamy H. Sarma.

Binding free energy of protein/ligand complexes calculated using dissociation Parallel Cascade Selection Molecular Dynamics and Markov state model.

We recently proposed a computational procedure to simulate the dissociation of protein/ligand complexes using the dissociation Parallel Cascade Selection Molecular Dynamics simulation (dPaCS-MD) method and to analyze the generated trajectories using the Markov state model (MSM). This procedure, called dPaCS-MD/MSM, enables calculation of the dissociation free energy profile and the standard binding free energy. To examine whether this method can reproduce experimentally determined binding free energies for a variety of systems, we used it to investigate the dissociation of three protein/ligand complexes: trypsin/benzamine, FKBP/FK506, and adenosine A2 A receptor/T4E. First, dPaCS-MD generated multiple dissociation pathways within a reasonable computational time for all the complexes, although the complexes differed significantly in the size of the molecules and in intermolecular interactions. Subsequent MSM analyses produced free energy profiles for the dissociations, which provided insights into how each ligand dissociates from the protein. The standard binding free energies obtained by dPaCS-MD/MSM are in good agreement with experimental values for all the complexes. We conclude that dPaCS-MD/MSM can accurately calculate the binding free energies of these complexes.