Sàng lọc in silico các kháng thể cho thụ thể RBD của SARS-CoV-2 bằng HDOCK và PRODIGY

Kieu Nhat Ha1, Kieu Minh Nhan2, Bui Van Thang3, Le Thi Ngoc Tu4, Nguyen Quoc Thai4,
1 Master's student, Dong Thap University, Vietnam
2 Office of Facilities and Project Management, Dong Thap University, Cao Lanh 870000, Vietnam
3 Office of Academic Affairs, Dong Thap University, Cao Lanh 870000, Vietnam
4 Faculty of Natural Sciences Teacher Education, School of Education, Dong Thap University, Cao Lanh 870000, Vietnam

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Tóm tắt

The COVID-19 pandemic and the emergence of SARS-CoV-2 variants underscore the need for potent neutralizing monoclonal antibodies. This study screened 288 antibodies targeting the receptor-binding domain (RBD) of SARS-CoV-2 using the HDOCK platform for protein-protein docking, followed by binding affinity prediction with PRODIGY. Five antibody-RBD complexes (P4A2, C1A-B3, COVOX-150, CC12.1, and 3G10) were identified with high docking scores and binding affinities in the picomolar to nanomolar range (Kd: 8.20 x 10-15 to 1.20 x 10-13 M). Key RBD residues (Tyr473, Leu455, Asn487, Tyr501) were found to drive stable interactions through hydrogen bonds and nonbonded contacts. A strong correlation (R = -0.9, p < 0.001) between HDOCK docking scores, binding free energy (ΔG), and ln(Kd) validates the predictive consistency of this approach. These findings provide a computational framework for prioritizing antibody candidates for further experimental validation, supporting cost-effective antibody development for COVID-19 treatment in Vietnam.

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Tài liệu tham khảo

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