Analysis of computational models for an accurate study of electronic excitations in GFP

Literature Information

Publication Date 2014-12-03
DOI 10.1039/C4CP04524F
Impact Factor 3.676
Authors

Tobias Schwabe, Maarten T. P. Beerepoot, Jacob Kongsted


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Abstract

Using the chromophore of the green fluorescent protein (GFP), the performance of a hybrid RI-CC2/polarizable embedding (PE) model is tested against a quantum chemical cluster approach. Moreover, the effect of the rest of the protein environment is studied by systematically increasing the size of the cluster and analyzing the convergence of the excitation energies. It is found that the influence of the environment of the chromophore can accurately be described using a polarizable embedding model with only a minor error compared to a full quantum chemical description. It is also shown that the treatment of only a small region around the chromophore is only by coincidence a good approximation. Therefore, such cluster approaches should be used with care. Based on our results, we suggest that polarizable embedding models, including a large part of the environment to describe its effect on biochromophores on top of an accurate way of describing the central subsystem, are both accurate and computationally favourable in many cases.

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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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