2026-04-17T01:02:50Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1821062025-12-05T14:17:44Zcom_2072_1057col_2072_478902col_2072_478917

00925njm 22002777a 4500 dc Martí Ballesté, Dídac author Martin Martinez, Eduard author Torras Costa, Joan author Bertran Cànovas, Òscar author Turon, Pau author Alemán Llanso, Carlos author 2022-01-04T14:28:52Z 2022-01-04T14:28:52Z 2021-10-07 2022-01-03T07:23:58Z Engineered immunoglobulin-G molecules (IgGs) are of wide interest for the development of detection elements in protein-based biosensors with clinical applications. The strategy usually employed for the de novo design of such engineered IgGs consists on merging fragments of the three-dimensional structure of a native IgG, which is immobilized on the biosensor surface, and of an antibody with an exquisite target specificity and affinity. In this work conventional and accelerated classical molecular dynamics (cMD and aMD, respectively) simulations have been used to propose two IgG-like antibodies for COVID-19 detection. More specifically, the crystal structure of the IgG1 B12 antibody, which inactivates the human immunodeficiency virus-1, has been merged with the structure of the antibody CR3022 Fab tightly bounded to SARS-CoV-2 receptor-binding domain (RBD) and the structure of the 5309 antibody Fab fragment complexed with SARS-CoV-2 RBD. The two constructed antibodies, named IgG1-CR3022 and IgG1-S309, respectively, have been immobilized on a stable gold surface through a linker. Analyses of the influence of both the merging strategy and the substrate on the stability of the two constructs indicate that the IgG1-S309 antibody better preserves the neutralizing structure than the IgG1-CR3022 one. Overall, results indicate that the IgG1-S309 is appropriated for the generation of antibody based sensors for COVID-19 diagnosis. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. SARS-CoV-2 Immunoglobulines Simulació per ordinador SARS-CoV-2 Immunoglobulins Computer simulation In silico antibody engineering for SARS-CoV-2 detection