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Kinematic Vibrational Entropy Assessment and Analysis of SARS CoV-2 Main Protease.
Chen, Xiyu; Leyendecker, Sigrid; van den Bedem, Henry.
  • Chen X; Institute of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
  • Leyendecker S; Institute of Applied Dynamics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany.
  • van den Bedem H; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, 94720 San Francisco, California, United States.
J Chem Inf Model ; 62(11): 2869-2879, 2022 06 13.
Article in English | MEDLINE | ID: covidwho-1860271
ABSTRACT
The three-dimensional conformations of a protein influence its function and select for the ligands it can interact with. The total free energy change during protein-ligand complex formation includes enthalphic and entropic components, which together report on the binding affinity and conformational states of the complex. However, determining the entropic contribution is computationally burdensome. Here, we apply kinematic flexibility analysis (KFA) to efficiently estimate vibrational frequencies from static protein and protein-ligand structures. The vibrational frequencies, in turn, determine the vibrational entropies of the structures and their complexes. Our estimates of the vibrational entropy change caused by ligand binding compare favorably to values obtained from a dynamic Normal Mode Analysis (NMA). Higher correlation factors can be achieved by increasing the distance cutoff in the potential energy model. Furthermore, we apply our new method to analyze the entropy changes of the SARS CoV-2 main protease when binding with different ligand inhibitors, which is relevant for the design of potential drugs.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Severe Acute Respiratory Syndrome / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2022 Document Type: Article Affiliation country: Acs.jcim.2c00126

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Severe Acute Respiratory Syndrome / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2022 Document Type: Article Affiliation country: Acs.jcim.2c00126