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Rational optimization of a human neutralizing antibody of SARS-CoV-2
- Source :
- Computers in Biology and Medicine
- Publication Year :
- 2021
-
Abstract
- SARS-CoV-2 has caused a worldwide epidemic of coronavirus disease 19 (COVID-19). Antibody drugs present an effective weapon for tens of millions of COVID-19 patients. Antibodies disrupting the interactions between the receptor-binding domain (RBD) of SARS-CoV-2 S protein and the angiotensin converting enzyme 2 (ACE2) effectively block SARS-CoV-2 cell entry into host cells. In order to rapidly develop more potent neutralizing antibodies, we utilized virtual scanning mutageneses and molecular dynamics simulations to optimize the antibody of P2B-2F6 isolated from single B cells of SARS-CoV-2 infected patients. Two potent P2B-2F6 mutants, namely H:V106R and H:V106R/H:P107Y, were found to possess higher binding affinities with the RBD domain of SARS-CoV-2 than others. Polar interactions are preferred near 106 and 107 paratope residues of the heavy chain. The mutations also increase the hydrogen-bonding network formed between the antibody and the RBD. Notably, the optimized antibodies possess potential neutralizing activity against the alarming SARS-CoV-2 variant of N501Y. This study provides insights into structure-based optimization of antibodies with higher affinity to the antigen. We hope that our proposed antibody mutants could contribute to the development of improved therapies against COVID-19.
- Subjects :
- 0301 basic medicine
Mutant
Health Informatics
medicine.disease_cause
Antibodies, Viral
Article
03 medical and health sciences
0302 clinical medicine
Antigen
Molecular dynamics simulation
medicine
Humans
Neutralizing antibody
Antibody
Coronavirus
biology
Chemistry
SARS-CoV-2
COVID-19
Entry into host
Virology
Antibodies, Neutralizing
Scanning mutageneses
Computer Science Applications
030104 developmental biology
Angiotensin-converting enzyme 2
Spike Glycoprotein, Coronavirus
biology.protein
Paratope
030217 neurology & neurosurgery
Protein Binding
Subjects
Details
- ISSN :
- 18790534
- Volume :
- 135
- Database :
- OpenAIRE
- Journal :
- Computers in biology and medicine
- Accession number :
- edsair.doi.dedup.....af65419caa962fcb7b62752c92c241fd