Unveiling the functional epitopes of cobra venom cytotoxin by immunoinformatics and epitope-omic analyses

Specific Amino Acid Residues in the Three Loops of Snake Cytotoxins Determine Their Membrane Activity and Provide a Rationale for a New Classification of These Toxins

Cytotoxins (CTs) are three-finger membrane-active toxins present mainly in cobra venom. Our analysis of the available CT amino acid sequences, literature data on their membrane activity, and conformational equilibria in aqueous solution and detergent micelles allowed us to identify specific amino acid residues which interfere with CT incorporation into membranes. They include Pro9, Ser28, and Asn/Asp45 within the N-terminal, central, and C-terminal loops, respectively. There is a hierarchy in the effect of these residues on membrane activity: Pro9 > Ser28 > Asn/Asp45. Taking into account all the possible combinations of special residues, we propose to divide CTs into eight groups. Group 1 includes toxins containing all of the above residues. Their representatives demonstrated the lowest membrane activity. Group 8 combines CTs that lack these residues. For the toxins from this group, the greatest membrane activity was observed. We predict that when solely membrane activity determines the cytotoxic effects, the activity of CTs from a group with a higher number should exceed that of CTs from a group with a lower number. This classification is supported by the available data on the cytotoxicity and membranotropic properties of CTs. We hypothesize that the special amino acid residues within the loops of the CT molecule may indicate their involvement in the interaction with non-lipid targets.

De novo designed proteins neutralize lethal snake venom toxins

Snakebite envenoming remains a devastating and neglected tropical disease, claiming over 100,000 lives annually and causing severe complications and long-lasting disabilities for many more1,2. Three-finger toxins (3FTx) are highly toxic components of elapid snake venoms that can cause diverse pathologies, including severe tissue damage3 and inhibition of nicotinic acetylcholine receptors (nAChRs) resulting in life-threatening neurotoxicity4. Currently, the only available treatments for snakebite consist of polyclonal antibodies derived from the plasma of immunized animals, which have high cost and limited efficacy against 3FTxs5,6,7. Here, we use deep learning methods to de novo design proteins to bind short- and long-chain α-neurotoxins and cytotoxins from the 3FTx family. With limited experimental screening, we obtain protein designs with remarkable thermal stability, high binding affinity, and near-atomic level agreement with the computational models. The designed proteins effectively neutralize all three 3FTx sub-families in vitro and protect mice from a lethal neurotoxin challenge. Such potent, stable, and readily manufacturable toxin-neutralizing proteins could provide the basis for safer, cost-effective, and widely accessible next-generation antivenom therapeutics. Beyond snakebite, our computational design methodology should help democratize therapeutic discovery, particularly in resource-limited settings, by substantially reducing costs and resource requirements for development of therapies to neglected tropical diseases.

Multi-epitopes vaccine design for surface glycoprotein against SARS-CoV-2 using immunoinformatic approach

Background

The recent COVID vaccinations have successfully reduced death and severity but did not stop the transmission of viruses by the emerging SARS-CoV-2 strain. There is a need for better and long-lasting dynamic vaccines for numerous prevailing strains and the evolving SARS-CoV-2 virus, necessitating the development of broad-spectrum strains being used to stop infection by reducing the spread rate and re-infection. The spike (S) glycoprotein is one of the proteins expressed commonly in the early phases of SARS-CoV-2 infection. It has been identified as the most immunogenic protein of SARS-CoV-2.

Methods

In this study, advanced bioinformatics techniques have been exploited to design the novel multi-epitope vaccine using conserved S protein portions from widespread strains of SARS-CoV-2 to predict B cell and T cell epitopes. These epitopes were selected based on toxicity, antigenicity score and immunogenicity. Epitope combinations were used to construct the maximum potent multi-epitope construct with potential immunogenic features. EAAAK, AAY, and GPGPG were used as linkers to construct epitopes.

Results

The developed vaccine has shown positive results. After the chimeric vaccine construct was cloned into the PET28a (+) vector for expression screening in Escherichia coli, the potential expression of the construct was identified.

Conclusion

The construct vaccine performed well in computer-based immune response simulation and covered a variety of allelic populations. These computational results are more helpful for further analysis of our contract vaccine, which can finally help control and prevent SARS-CoV-2 infections worldwide.