Publication date: Jan 28, 2025
Nanobodies or variable antigen-binding domains (VH) derived from heavy chain-only antibodies (HcAb) occurring in the Camelidae family offer certain superior physicochemical characteristics like enhanced stability, solubility, and low immunogenicity compared to conventional antibodies. Their efficient antigen-binding capabilities make them a preferred choice for next-generation small biologics. In the present work, we design an anti-SARS-CoV-2 bi-paratopic nanobody drug conjugate by screening a nanobody database. SAbDab-nano database was screened based on the physicochemical properties and SARS-CoV-2 binding affinity of the documented nanobodies. Molecular docking, computational modeling, in silico site-directed mutagenesis, and MD simulations were performed to construct an effective nanobody bi-paratope. The construct’s physicochemical properties were assessed, and its structural integrity was validated through model energy refinement and quality assessment. The triple-mutant (N78Q K116N T123F) nanobody, based on the bioinformatics analysis, exhibited enhanced binding efficiency against its targets: SARS CoV-2 WT RB (- 353. 3), NRP1 (- 376. 5) and Omicron RBD (- 380. 8), compared to the WT nanobody (SARS CoV-2 WT RBD = - 337. 5, NRP1 = - 361. 5, Omicron RBD = - 359. 5). In silico evaluation also predicted that the construct would demonstrate efficient solubility, high thermostability (Tm 67. 4 ^0C), low molecular weight of 29. 36 KDa, and non-toxic, non-allergenic properties. Anti-SARS-CoV-2 neutralizing nanobody-based therapeutics, as demonstrated through this computational work, represents a promising alternative to traditional COVID-19 prophylaxis.
Concepts | Keywords |
---|---|
Antibodies | Nanobody |
Camelidae | Nanobody-drug conjugate |
Efficient | Neuropilin-1 |
Mutant | Omicron |
Pharmacoinformatics | SARS-CoV-2 |
Semantics
Type | Source | Name |
---|---|---|
disease | IDO | site |
disease | IDO | quality |
disease | MESH | COVID-19 |