ArticleColloids and surfaces. B, Biointerfaces2023
Towards an optimal monoclonal antibody with higher binding affinity to the receptor-binding domain of SARS-CoV-2 spike proteins from different variants.
Article in Colloids and surfaces. B, Biointerfaces, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- Consensus-based computational mapping of NS1 antigenic determinants in dengue and Zika viruses to improve diagnostic specificity.BMC infectious diseases · 2026Article
- Computational methods in physical virology: a critical perspective across lengths and timescales.FEMS microbiology reviews · 2026Review
- Artificial intelligence in bioinformatics: a survey.Briefings in bioinformatics · 2025Review
- Fine-tuned protein language model identifies antigen-specific B cell receptors from immune repertoires.bioRxiv : the preprint server for biology · 2025Article
- The extract of dendrobium Coelonin inhibits PIH induced by AFR COPhotochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2025Article
- Biophysics of SARS-CoV-2 spike protein's receptor-binding domain interaction with ACE2 and neutralizing antibodies: from computation to functional insights.Biophysical reviews · 2025Review
- Unlocking the potential ofFrontiers in bioinformatics · 2025Review
- SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study.The journal of physical chemistry. B · 2024Article
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- Brown MacroalgaeMolecules (Basel, Switzerland) · 2022Article
- Effect of Delta and Omicron Mutations on the RBD-SD1 Domain of the Spike Protein in SARS-CoV-2 and the Omicron Mutations on RBD-ACE2 Interface Complex.International journal of molecular sciences · 2022Article
- Mutations of Omicron Variant at the Interface of the Receptor Domain Motif and Human Angiotensin-Converting Enzyme-2.International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A highly efficient and robust multiple scales in silico protocol, consisting of atomistic Molecular Dynamics (MD), coarse-grain (CG) MD, and constant-pH CG Monte Carlo (MC), has been developed and used to study the binding affinities of selected antigen-binding fragments of the monoclonal antibody (mAbs) CR3022 and several of its here optimized versions against 11 SARS-CoV-2 variants including the wild type. Totally 235,000 mAbs structures were initially generated using the RosettaAntibodyDesign software, resulting in top 10 scored CR3022-like-RBD complexes with critical mutations and compared to the native one, all having the potential to block virus-host cell interaction. Of these 10 finalists, two candidates were further identified in the CG simulations to be the best against all SARS-CoV-2 variants. Surprisingly, all 10 candidates and the native CR3022 exhibited a higher affinity for the Omicron variant despite its highest number of mutations. The multiscale protocol gives us a powerful rational tool to design efficient mAbs. The electrostatic interactions play a crucial role and appear to be controlling the affinity and complex building. Studied mAbs carrying a more negative total net charge show a higher affinity. Structural determinants could be identified in atomistic simulations and their roles are discussed in detail to further hint at a strategy for designing the best RBD binder. Although the SARS-CoV-2 was specifically targeted in this work, our approach is generally suitable for many diseases and viral and bacterial pathogens, leukemia, cancer, multiple sclerosis, rheumatoid, arthritis, lupus, and more.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.