The conformational landscape of tartrate-based inhibitors of the TACE enzyme as revealed by Hamiltonian Replica Exchange simulation

Literature Information

Publication Date 2013-04-15
DOI 10.1039/C3CP00108C
Impact Factor 3.676
Authors

Carlo Guardiani, Piero Procacci


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Abstract

The inhibitors of the Tumor Necrosis Factor-α Converting Enzyme represent promising tools for the treatment of Rheumatoid Arthritis, Multiple Sclerosis and other autoimmune diseases. In this work, using Hamiltonian Replica Exchange Molecular Dynamics simulations and atomistic force field we perform an accurate structural characterization of a group of tartrate-based inhibitors. The simulations highlight a correlation between the conformational landscape in bulk solvent and inhibition potency. Since the structures in bulk solvent are much more compact than the crystallographic bound state, we formulate the hypothesis of a two-step docking mechanism: (i) formation of an intermediate between the compact, hydroxyl exposing conformations in solution and the catalytic zinc ion; (ii) structural rearrangement in the active site of TACE of the zinc-tethered drug in the final binding conformation.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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