Biology subjects

Wahome, N.

Publications and source records attributed to Wahome, N..

4 recordsLinked to original sources

bioRxiv2026

Systematic exploration of predicted quaternary structures within pandemic-relevant viral proteomes

Mechanistic understanding of viral protein-protein interactions enables global health security and pandemic preparedness, yet experimental characterisation remains difficult, costly, and often restricted to specialised laboratories. Here, we describe an in silico campaign using AlphaFold2 and AlphaFold-Multimer to predict monomers and dimer structures within 2,812 viral proteomes from 23 viral families relevant to human health. We report high-confidence predicted structures of 5,279 hetero-, and 2,749 homo-dimers. Structural clustering of interfaces reduces the set fivefold to 1,598 consolidated by form and function, of which 471 (29.5%) lacked detectable similarity to experimentally determined interfaces in the PDB. These clusters yielded two notable findings: new data on vaccinology-relevant glycoproteins, and accurate prediction of the specificity and cleavage-site recognition of viral proteases, which are targets for anti-viral development. Viral monomers and high-confidence dimers are available for interactive browsing in the Pandemic Preparedness Portal of the AlphaFold Database (https://alphafold.ebi.ac.uk/), and the full dataset is available for bulk download.

bioinformatics↗

bioRxiv2024

Computational design of developable therapeutic antibodies: efficient traversal of binder landscapes and rescue of escape mutations

Developing therapeutic antibodies is a challenging endeavour, often requiring large-scale screening to produce initial binders, that still often require optimisation for developability. We present a computational pipeline for the discovery and design of therapeutic antibody candidates, which incorporates physics- and AI-based methods for the generation, assessment, and validation of developable candidate antibodies against diverse epitopes, via efficient few-shot experimental screens. We demonstrate that these orthogonal methods can lead to promising designs. We evaluated our approach by experimentally testing a small number of candidates against multiple SARS-CoV-2 variants in three different tasks: (i) traversing sequence landscapes of binders, we identify highly sequence dissimilar antibodies that retain binding to the Wuhan strain, (ii) rescuing binding from escape mutations, we show up to 54% of designs gain binding affinity to a new subvariant and (iii) improving developability characteristics of antibodies while retaining binding properties. These results together demonstrate an end-to-end antibody design pipeline with applicability across a wide range of antibody design tasks. We experimentally characterised binding against different antigen targets, developability profiles, and cryo-EM structures of designed antibodies. Our work demonstrates how combined AI and physics computational methods improve productivity and viability of antibody designs.

bioinformatics↗

bioRxiv2022

Structural and Computational Design of a SARS-CoV-2 Spike Antigen with Increased Receptor Binding Domain Exposure and Improved Immunogenicity

Emerging SARS-CoV-2 variants of concern challenge the efficacy of approved vaccines and emphasize the need for improved antigens. Using an evolutionary-based design approach starting from the widely used engineered Spike antigen, S-2P, we sought to increase antigen production levels and the exposure of highly conserved and neutralization sensitive receptor-binding domain (RBD) epitopes. Thirty-six prototypes were generated in silico, of which fifteen were produced and tested in biochemical assays. Design S2D14, which contains 20 mutations within the Spike S2 domain, showed a 6-fold increase in expression while preserving similar thermal stability and antigenicity as S-2P. Cryo-EM structures indicate that the dominant populations of S2D14 particles have RBDs in exposed states, and analysis of these structures revealed how modifications within the S2 domain balance trimer stability and RBD accessibility through formation and removal of hydrogen bonds and surface charge alterations. Importantly, vaccination of mice with adjuvanted S2D14 resulted in higher levels of neutralizing antibodies than adjuvanted S-2P against SARS-CoV-2 Wuhan strain and four variants of concern. These results can guide the design of next generation vaccines to combat current, and future coronaviruses and the approaches used may be broadly applicable to streamline the successful design of vaccine antigens.

immunology↗

bioRxiv2022

Paragraph - Antibody paratope prediction using Graph Neural Networks with minimal feature vectors

1SummaryThe development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce the cost of this process by improving our understanding of antibody-antigen binding. We present Paragraph, a structure-based paratope prediction tool that outperforms current state-of-the-art tools using simpler feature vectors and no antigen information. AvailabilitySource code is freely available at www.github.com/oxpig Contactdeane@stats.ox.ac.uk Supplementary informationSupplementary data are available at bioRxiv online.

bioinformatics↗