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Updated: Jul 30, 2025

Engineering Antiviral Agents via Surface Plasmon Resonance
Published on: June 14, 2022
Towards a free energy-based elastic network model and its application to the SARS-COV2 binding to ACE2
1Department of Computer Science, Penn State Harrisburg, Middletown, PA 17057, United States of America.
Abstract:
Classical normal mode analysis (cNMA) is a standard method for studying the equilibrium vibrations of macromolecules. A major limitation of cNMA is that it requires a cumbersome step of energy minimization that also alters the input structure significantly. Variants of normal mode analysis (NMA) exist that perform NMA directly on PDB structures without energy minimization, while maintaining most of the accuracy of cNMA. Spring-based NMA (sbNMA) is such a model. sbNMA uses an all-atom force field as cNMA does, which includes bonded terms such as bond stretching, bond angle bending, torsional, improper, and non-bonded terms such as van der Waals interactions. Electrostatics was not included in sbNMA because it introduced negative spring constants. In this work, we present a way to incorporate most of the electrostatic contributions in normal mode computations, which marks another significant step toward a free-energy-based elastic network model (ENM) for NMA. The vast majority of ENMs are entropy models. One significance of having a free energy-based model for NMA is that it allows one to study the contributions of both entropy and enthalpy. As an application, we apply this model to study the binding stability between SARS-COV2 and angiotensin converting enzyme 2 (or ACE2). Our results show that the stability at the binding interface is contributed nearly equally by hydrophobic interactions and hydrogen bonds.
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