A computational study of competing conformational selection and induced fit in an abiotic system

Literature Information

Publication Date 2021-12-06
DOI 10.1039/D1CP05253E
Impact Factor 3.676
Authors

Remy F. Lalisse, Radoslav Z. Pavlović, Christopher M. Hadad, Jovica D. Badjić


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Abstract

Host–guest complexations can be described by two competing mechanisms, conformational selection (CS) and induced fit (IF). In this work, we used a combination of nudged elastic band (NEB), adaptive steered molecular dynamics (ASMD), and density functional theory (DFT, with a correction for dispersion) to study the dynamics of the pathways (IF/CS) by which two conformers of basket B(+) and B(−) interconvert and trap CX4 guests (X = Cl and Br). While the results from NEB/DFT studies disclosed host–guest noncovalent contacts reducing the basket's conformational dynamics, ASMD methodology suggested an associative mechanism for the guest complexation. With theory in excellent agreement with experiments, NEB and ASMD emerge as the methods of choice for studying dynamics of supramolecular systems.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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