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Updated: Mar 18, 2026

Engineering Antiviral Agents via Surface Plasmon Resonance
Published on: June 14, 2022
Mutation-driven adaptation of ACE2-RBD binding revealed by integrative molecular dynamics analysis
Linh Truong Hoai1, Baso Ilham1, Thanakorn Sompornpisut1
1The Center of Excellence in Computational Chemistry, Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Abstract:
Investigating the effects of residue-level variations in the receptor-binding domain (RBD) of the SARS-CoV-2 influence the molecular recognition and binding behavior toward the human ACE2 protein is essential for elucidating viral evolution and transmissibility. Earlier structural and computational analyses have provided valuable insights into the ACE2-RBD interaction mechanism. However, a systematic comparison integrating structural, dynamic, contact-based, and energetic characteristics across multiple variants remains limited. In this study, we performed an integrative molecular modeling study combining molecular dynamics simulations, dynamic cross-correlation and principal component analyses, interfacial contact mapping, hydrogen-bond characterization, and energetic decomposition to examine the structural dynamics and interfacial interactions of ACE2-RBD complexes in the wild type and five major variants (Alpha, Beta, Gamma, Delta, and Omicron). This multi-level approach reveals both conserved and adaptive interaction patterns. A persistent hydrogen-bond framework involving S19, Q24, and Y83 of ACE2 interacting with RBD positions A475, S477, and N487 is maintained across all variants, serving as an evolutionary anchor for receptor engagement. In contrast, Delta and Omicron exhibit distinct interfacial rearrangements through redistributed hydrophobic and electrostatic interactions that sustain binding despite multiple charge-altering mutations. Clustering and principal component analyses further distinguish early (Alpha-Gamma) from later (Delta-Omicron) variant lineages, reflecting progressive structural adaptation. Overall, this integrative analysis provides mechanistic insight into how mutations collectively modulate ACE2 recognition, offering a predictive framework for understanding variant evolution and guiding future therapeutic design.
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