The role of protein dynamics on different time scales in enzyme catalysis remains an area of active debate. The connection between enzyme dynamics on the femtosecond time scale and transition state formation has been demonstrated in human purine nucleoside phosphorylase (PNP) through the study of a mass-altered enzyme. Isotopic substitution in human PNP (heavy PNP) decreased the rate of on-enzyme chemistry but did not alter either the transition state structure or steady-state kinetic parameters. Here we investigate the underlying atomic motions associated with altered barrier crossing probability for heavy PNP. Transition path sampling was employed to illuminate the molecular differences between barrier crossing in light and heavy enzymes. The mass effect is apparent in promoting vibrations that polarize the N-ribosidic bond, and that promote the stability of the purine leaving group. These motions facilitate barrier crossing.
Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.
The interactions of the 50S subunit of bacterial ribosome with antibiotic sparsomycin (SPS) and five analogs (AN) are investigated through the calculation of the standard (absolute) binding free energy and the characterization of conformational dynamics. The standard binding free energies of the complexes are computed using free energy perturbation molecular dynamics (FEP/MD) simulations with explicit solvent. Restraining potentials are applied and then released during the simulation to efficiently sample the changes in translational, orientational, and conformational freedom of the ligand and receptor upon binding. The biasing effects of the restraining potentials are rigorously removed. The loss of conformational freedom of the ligand upon binding is determined by introducing a potential of mean force (PMF) as a function of the root-mean-square deviation (rmsd) of the ligand relative to its conformation in the bound state. To reduce the size of the simulated system, the binding pocket of the ribosome is simulated in the framework of the generalized solvent boundary potential (GSBP). The number of solvent molecules in the buried binding site is treated via grand canonical Monte Carlo (GCMC) during the FEP/MD simulations. The correlation coefficient between the calculated and measured binding free energies is 0.96, and the experimentally observed ranking order for the binding affinities of the six ligands is reproduced. However, while the calculated affinities of the strong binders agree well with the experimental values, those for the weak binders are underestimated.
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