Specific epitopes form extensive hydrogen-bonding networks to ensure efficient antibody binding of SARS-CoV-2: Implications for advanced antibody design

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies.

Antibody drugs targeting SARS-CoV-2: Time for a rethink?

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) heavily burdens human health. Multiple neutralizing antibodies (nAbs) have been issued for emergency use or tested for treating infected patients in the clinic. However, SARS-CoV-2 variants of concern (VOC) carrying mutations reduce the effectiveness of nAbs by preventing neutralization. Uncoding the mutation profile and immune evasion mechanism of SARS-CoV-2 can improve the outcome of Ab-mediated therapies. In this review, we first outline the development status of anti-SARS-CoV-2 Ab drugs and provide an overview of SARS-CoV-2 variants and their prevalence. We next focus on the failure causes of anti-SARS-CoV-2 Ab drugs and rethink the design strategy for developing new Ab drugs against COVID-19. This review provides updated information for the development of therapeutic Ab drugs against SARS-CoV-2 variants.

Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

Biophysical Fitness Landscape of the SARS-CoV-2 Delta Variant Receptor Binding Domain

Among the five known SARS-CoV-2 variants of concern, Delta is the most virulent leading to severe symptoms and increased mortality among infected people. Our study seeks to examine how the biophysical parameters of the Delta variant correlate to the clinical observations. Receptor binding domain (RBD) is the first point of contact with the human host cells and is the immunodominant form of the spike protein. Delta variant RBD contains two novel mutations L452R and T478K. We examined the effect of single as well as the double mutations on RBD expression in human Expi293 cells, RBD stability using urea and thermal denaturation, and RBD binding to angiotensin converting enzyme 2 (ACE2) receptor and to neutralizing antibodies using isothermal titration calorimetry. Delta variant RBD showed significantly higher expression compared to the wild-type RBD, and the increased expression is due to L452R mutation. Despite their non-conservative nature, none of the mutations significantly affected RBD structure and stability. All mutants showed similar binding affinity to ACE2 and to Class 1 antibodies (CC12.1 and LY-CoV016) as that of the wild-type. Delta double mutant L452R/T478K showed no binding to Class 2 antibodies (P2B-2F6 and LY-CoV555) and a hundred-fold weaker binding to a Class 3 antibody (REGN10987), and the decreased antibody binding is determined by the L452R mutation. These results indicate that the immune escape from neutralizing antibodies, rather than increased receptor binding, is the main biophysical parameter that determined the fitness landscape of the Delta variant RBD.

Amomum tsao-ko essential oil, a Novel Anti-COVID-19 Omircon Spike Protein Natural Products: A Computational Study

Since the outbreak of COVID-19, this virus has been constantly mutating. The latest mutant Omicron has been identified as VOC by WHO. The main reason for its concern is the mutation of 46 amino acids in spike protein, which has brought the global epidemic prevention into another difficulty. Herbal aromatic plant Amomum tsao-ko was excavated from formula 1 and 2 for the treatment of COVID-19 in China, and its active components were extracted and identified. Molecular dynamics simulation and Fpocket were applied to find the key sites on RBD_Omicron, and molecular docking was also used to reveal the interaction between A. tsao-ko essential oil (AEO) and RBD_Omicron. The AEO components were analyzed and identified by GC/Q-TOF MS. There were 20 kinds of AEO with a relative area percentage of more than 1%, and they were related to the three active centres of RBD_Omicron. In this study, virtual screening was used to mine the essential oil components of medicinal plants, and it was found that the components could interact with the spike protein RBD in aerosol to block the interaction of RBD and hACE2, thus cutting off the transmission route and protecting the host. This study has certain guiding significance in the modernization of Traditional Chinese medicine and the prevention of COVID-19.

Unbinding of hACE2 and inhibitors from the receptor binding domain of SARS-CoV-2 spike protein

The first direful biomolecular event leading to COVID-19 disease is the SARS-CoV-2 virus surface spike (S) protein-mediated interaction with the human transmembrane protein, angiotensin-converting enzyme 2 (hACE2). Prevention of this interaction presents an attractive alternative to thwart SARS-CoV-2 replications. The development of monoclonal antibodies (mAbs) in the convalescent plasma treatment, nanobody, and designer peptides, which recognizes epitopes that overlap with hACE2 binding sites in the receptor-binding domain (RBD) of S protein (S/RBD) and thereby blocking the infection has been the center stage of therapeutic research. Here we report atomistic and reliable in silico structure-energetic features of the S/RBD interactions with hACE2 and its two inhibitors (convalescent mAb, B38, and an alpaca nanobody, Ty1). The discovered potential of mean forces exhibits free energy basin and barriers along the interaction pathways, providing sufficient molecular insights to design a B38 mutant and a Ty1-based peptide with higher binding capacity. While the mutated B38 forms a 60-fold deeper free energy minimum, the designer peptide (Ty1-based) constitutes 38 amino acids and is found to form a 100-fold deeper free energy minimum in the first binding basin than their wild-type variants in complex with S/RBD. Our strategy may help to design more efficacious biologics towards therapeutic intervention against the current raging pandemic.Communicated by Ramaswamy H. Sarma.

Intermolecular Interaction Analyses on SARS-CoV-2 Spike Protein Receptor Binding Domain and Human Angiotensin-Converting Enzyme 2 Receptor-Blocking Antibody/Peptide Using Fragment Molecular Orbital Calculation

The spike glycoprotein (S-protein) mediates SARS-CoV-2 entry via intermolecular interaction with human angiotensin-converting enzyme 2. The receptor binding domain (RBD) of the S-protein has been considered critical for this interaction and acts as the target of numerous neutralizing antibodies and antiviral peptides. This study used the fragment molecular orbital method to analyze the interactions between the RBD and antibodies/peptides and extracted crucial residues that can be used as epitopes. The interactions evaluated as interfragment interaction energy values between the RBD and 12 antibodies/peptides showed a fairly good correlation with the experimental activity pIC50 (R2 = 0.540). Nine residues (T415, K417, Y421, F456, A475, F486, N487, N501, and Y505) were confirmed as being crucial. Pair interaction energy decomposition analyses showed that hydrogen bonds, electrostatic interactions, and π-orbital interactions are important. Our results provide essential information for understanding SARS-CoV-2-antibody/peptide binding and may play roles in future antibody/antiviral drug design.