Biology subjects

Kim, R. S.

Publications and source records attributed to Kim, R. S..

7 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↗

bioRxiv2026

BFVD v3-UniProt-complete, improved viral protein structure predictions

The Big Fantastic Virus Database (BFVD) v3 is the most comprehensive resource for ColabFold-AlphaFold2-predicted viral protein structures. It holds 5,776,417 structures of nearly all viral sequences in UniProt 2025_03, a 16.4-fold increase compared to the representative-only catalogs of BFVD v1 and v2. Structure prediction quality has also improved, with high-confidence predictions accounting for 75.3% of BFVD v3 entries. This is due to Logan's enormous sequence assembly, now mined for the entire BFVD v3 instead of only for shallow alignments, alongside continued prediction quality improvements. BFVD v3 covers 72.7% of ICTV's virus species, 1.54-fold more than BFVD v2. With this version, the fraction of fully covered viral reference proteomes increases from 1.5% to 72.6%. BFVD v3 thus brings us closer to a structural catalog of the known virosphere and is freely available at bfvd.steineggerlab.workers.dev and bfvd.foldseek.com.

bioinformatics↗

bioRxiv2026

Foldseek-Interface reveals a protein interface universe far from complete

Protein-protein interactions mediate a vast range of cellular functions, requiring diverse modes of binding. While recent years have seen major efforts to chart and classify the protein structure universe, we lack comparable methods to assess and cluster that diversity in interface structure at interactome scale. Here, we present Foldseek-Interface, a method that converts 3D interface structures into searchable sequences to enable fast alignment and clustering of protein interaction interfaces. It matches the accuracy of state-of-the-art tools while running up to 230 times faster. Applying it to all biological assemblies in the PDB, we cluster 3.1 million dimers into 77{,}167 interface clusters and use this resource to characterise interface diversity, evolution, and pathogen mimicry. Application of Foldseek-Interface to resources of predicted protein complex structures rapidly revealed putatively novel interface types worth further experimental interrogation. Foldseek-Interface and the interface cluster resource are freely available as webservers for search https://search.foldseek.com/interface and exploration https://interface.foldseek.com.

bioinformatics↗

bioRxiv2025

Protein Structure Informed Bacteriophage Genome Annotation with Phold

Bacteriophage (phage) genome annotation is essential for understanding their functional potential and suitability for use as therapeutic agents. Here we introduce Phold, an annotation framework utilising protein structural information that combines the ProstT5 protein language model and structural alignment tool Foldseek. Phold assigns annotations using a database of over 1.36 million predicted phage protein structures with high quality functional labels. Benchmarking reveals that Phold outperforms existing sequence-based homology approaches in functional annotation sensitivity whilst maintaining speed, consistency and scalability. Applying Phold to diverse cultured and metagenomic phage genomes shows it consistently annotates over 50% of genes on an average phage and 40% on an average archaeal virus. Comparisons of phage protein structures to other protein structures across the tree of life reveals that phage proteins commonly have structural homology to proteins shared across the tree of life, particularly those that have nucleic acid metabolism and enzymatic functions. Phold is available as free and open-source software at https://github.com/gbouras13/phold.

bioinformatics↗

bioRxiv2025

Structural motif search across the protein-universe with Folddisco

Detecting similar protein structural motifs, functionally crucial short 3D patterns, in large structure collections is computationally prohibitive. Therefore, we developed Folddisco, which overcomes this through an index of position-independent geometric features, including side-chain orientation, combined with a rarity-based scoring system. Folddiscos compact 1.45-terabyte index of 53 million AFDB50 structures enables querying this database within seconds. It is 20-fold faster in querying and 4-fold more storage-efficient than existing methods. Folddisco is more accurate and storage-efficient than state-of-the-art methods, while being an order of magnitude faster. Folddisco is free software available at folddisco.foldseek.com and a webserver at search.foldseek.com/folddisco.

bioinformatics↗

bioRxiv2024

BFVD - a large repository of predicted viral protein structures

The AlphaFold Protein Structure Database (AFDB) is the largest repository of accurately predicted structures with taxonomic labels. Despite providing predictions for over 214 million UniProt entries, the AFDB does not cover viral sequences, severely limiting their study. To bridge this gap, we created the Big Fantastic Virus Database (BFVD), a repository of 351,242 protein structures predicted by applying ColabFold to the viral sequence representatives of the UniRef30 clusters. BFVD holds a unique repertoire of protein structures as over 63% of its entries show no or low structural similarity to existing repositories. We demonstrate how BFVD substantially enhances the fraction of annotated bacteriophage proteins compared to sequence-based annotation using Bakta. In that, BFVD is on par with the AFDB, while holding nearly three orders of magnitude fewer structures. BFVD is an important virus-specific expansion to protein structure repositories, offering new opportunities to advance viral research. BFVD is freely available at https://bfvd.steineggerlab.workers.dev/

bioinformatics↗

bioRxiv2021

Cytolytic memory CD4+ T cell clonotypes are expanded during Plasmodium falciparum infection

Plasmodium falciparum (Pf) malaria causes high rates of morbidity and mortality and lacks a sufficiently effective vaccine. Clinical immunity develops in residents of malaria endemic regions which confers reduced clinical symptoms during infection and protection against severe disease. We hypothesized that understanding the immune mechanisms of clinical immunity could inform vaccine design to improve efficacy. We compared the peripheral blood cellular and humoral immune responses during a mild episode of Pf malaria infection. Participants were classified as either clinically susceptible or clinically protected, based on the number of recurrent clinical infections over an 18-month longitudinal study in a malaria endemic region in Malawi. Susceptible participants had three or more recurrent clinical episodes while clinically immune individuals had one or none. Protected participants exhibited higher plasma immunoglobulin G (IgG) breadth and titers against Pf antigens, and greater antibody (Ab)-dependent Pf opsonization compared to susceptible participants. Using high dimensional mass cytometry (CyTOF), spectral flow cytometry and single-cell transcriptomic analyses, we identified expanded memory CD4+ T cell clones sharing identical T cell receptor clonotypes in the blood of protected participants during malaria infection. These cells express a strong cytolytic T helper 1 effector program with transcripts encoding granzymes (A, B, H, M), granulysin, NKG7 and the Zeb2 master transcriptional regulator of terminally differentiated effector T cells. Memory CD4+ T cells expressing Zeb2+ were CD39hiTIGIThi and expressed multiple chemotactic and checkpoint inhibitory receptors, although the cellular levels of several of these receptors were reduced in protected compared to susceptible individuals. We propose that clonally expanded Zeb2+ cytolytic memory CD4+ Th1 cells could represent essential contributors to clinical immunity against Pf malaria. One Sentence SummaryA population of cytolytic memory CD4+ T cells is clonally expanded in patients with Plasmodium falciparum malaria and has reduced chemotactic and inhibitory receptor expression in patients with naturally acquired clinical malaria immunity.

immunology↗