Path Ensembles for Pin1-Catalyzed Cis-Trans Isomerization of a Substrate Calculated by Weighted Ensemble Simulations

Enhanced Sampling of Configuration and Path Space in a Generalized Ensemble by Shooting Point Exchange

The computer simulation of many molecular processes is complicated by long timescales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare events, which combines transition path sampling with enhanced exploration of configuration space. The method relies on exchange moves between configuration and trajectory space, carried out based on a generalized ensemble. This scheme substantially enhances the efficiency of the transition path sampling simulations, particularly for systems with multiple transition channels, and yields information on thermodynamics, kinetics and reaction coordinates of molecular processes without distorting their dynamics. The method is illustrated using the isomerization of proline in the KPTP tetrapeptide.

Bispidine as a promising scaffold for designing molecular machines

The development of artificial molecular machines is a challenging endeavor. Herein, we have synthesized a series of bispidine diamides D1-D6 that exhibit rotation reminiscent of a motor motion. Dynamic NMR, X-ray diffraction, quantum mechanical calculations, and molecular dynamics simulations provided insights into their rotational dynamics. All the diamides D1-D6 exhibited mutually independent rotation around the two bispidine arms. However, the rate of rotation and the presence or absence of directionality in amide bond rotation were found to depend on the solvent, temperature, and nature of substitution on the amide carbonyl. These engineered systems may aid in the development of biologically relevant synthetic molecular motors. Studies on homochiral and heterochiral bispidine-peptides revealed that the direction of rotation can be controlled by chirality and the nature of the amino acid.

Molecular Insights into the Intrinsic Dynamics and Their Roles During Catalysis in Pin1 Peptidyl-prolyl Isomerase

Proteins are intrinsically dynamic and change conformations over a wide range of time scales. While the conformational dynamics have been realized to be important for protein functions, e.g., in activity-stability trade-offs, how they play a role during enzyme catalysis has been of debate over decades. By studying Pin1 peptidyl-prolyl isomerase using extensive molecular dynamics simulations, here we discuss how the slow intrinsic dynamics of Pin1 observed in the NMR relaxation dispersion experiment occur and couple to isomerization reactions in molecular detail. In particular, we analyze the angular correlation functions of the backbone N-H bonds and find that slow conformational transitions occur at about the 3₁₀ helix in the apo state. These events at the helical region further affect the residues at about the ligand binding site. Unfolding of this helix leads to a tight hydrogen bond between the helical region and the ligand binding loop, thus forming a stable coiled structure. The helical and coiled structures are found to be characteristic of the Pin1-ligand complex with the ligand in the trans and cis states, respectively. These results indicate that the changes in the slow dynamics of Pin1 by the isomerization reaction occur via the shift in populations of the helical and coiled states, where the balance is dependent on the ligand isomerization states.

Multiscale aspects of molecular motions: From molecular vibrations, conformational changes of biomolecules to cellular dynamics

Molecular aspects of living systems are important because it is the most basic aspects of life as exemplified in biochemistry and structural biology. Since molecules move due to interactive forces between atoms, physics plays an important role to understand the dynamic phenomena of living systems. Here we review our multiscale approaches for computationally treating different levels of molecular motions: vibrational dynamics of molecules, conformational change of biomolecules, and cellular dynamics using statistical-mechanics-based models.