Biology subjects

Hung, L.-W.

Publications and source records attributed to Hung, L.-W..

4 recordsLinked to original sources

bioRxiv2026

SurfGraphPro: Integrating Protein Language Models with Geometric Deep Learning On Coarse Protein Surfaces for Binding Site Prediction

Accurate and fast prediction of protein binding sites remains essential for understanding molecular interactions and facilitating protein engineering. Here, we present SurfGraphPro, a geometric deep learning approach that bridges protein language models with surface-based structural representations for a rapid binding interface prediction. Our method operates on coarse-graphed triangulated protein surfaces, utilizing solvent-excluded surface meshes downsampled into amino acid residue centered patches. Unlike existing approaches that rely on extensive physicochemical feature engineering, we leverage evolutionary information directly from protein language model embeddings, eliminating the need for computationally expensive multiple sequence alignments and hand-crafted features. This integration achieves on average $\sim18-28 \times$ speedup for proteins of $\sim$100 to a few 1000s of amino acids over current state-of-the-art surface-based model while maintaining comparable accuracy on diverse binding interfaces, including challenging antibody-antigen complexes. To our knowledge, this represents the first approach to integrate protein language model embeddings with coarse geometric surface representations for binding site prediction, demonstrating that learned evolutionary features coupled with geometric transformers can replace traditional feature engineering without sacrificing performance.

bioinformatics↗

bioRxiv2026

Discovering Novel Therapeutic VHHs for Emerging Viruses: Perspectives from VEEV Selection Strategies

Evolution or emergence of a new viral variant is a significant public health concern. Alphaviruses, such as Venezuelan equine encephalitis virus (VEEV), are mosquito-borne viruses which are becoming more prevalent due to expansion of vector habitats. The increased prevalence of such viruses provides opportunities for novel variants to evolve. Key therapeutic molecules that could be developed against viral pathogens are recombinant antibodies or antibody fragments, such as the variable heavy domain of heavy chain antibodies (VHHs). These proteins can neutralize or sequester viral particles, preventing or reducing infection. However, due to the evolution of viruses, there is a need to isolate new antibodies and direct their binding to particular epitopes on the virus. In vitro selections offer a promising pathway for the selection of therapeutic antibodies, but as we demonstrate, the choice of a target for these selections is key to obtaining the desired viral binding characteristics. Here we report four novel "human" VHHs which bind to the VEEV E2 protein selected using different strategies that include both computational and biochemical design of suitable antigens and whole virus selections. These VHHs have distinct complementarity-determining regions (CDRs). Multiple VHHs bind to the VEEV viral particles in ELISAs, and we report the peptide epitope recognized by these VHHs. Though non-neutralizing, when immobilized, these VHHs bind to and sequester VEEV viral particles preventing infection, demonstrating the potential of these VHHs to perform viral "sponging". The selection strategies we report may have applications to further antibody developments against other viruses. Significance/ImportanceAlphaviruses, and in particular Venezuelan equine encephalitis virus (VEEV), are recognized for their ability to cause severe disease and for their potential to be used as a biothreat. Despite this, there are currently no antiviral therapies or FDA-approved vaccines available to treat or prevent VEEV infection. This study reports on a novel antibody selection pipeline to produce antibody fragments against VEEV. Antibodies produced via this method showed strong affinity and high specificity to the VEEV E2 glycoprotein in multiple conformations. Additionally, while not neutralizing, the antibody fragments described were shown to be effective as "viral sponges", having the ability to bind, sequester, and remove VEEV virions from solution, which represents a novel therapeutic approach.

immunology↗

bioRxiv2025

Epigenomic insights into extreme longevity in the world's oldest terrestrial animal, Jonathan

Giant tortoises exhibit exceptional longevity, often exceeding the human lifespan. To understand the genomic and epigenomic basis of their longevity, awe analyzed the DNA sequence and methylome of Jonathan, an Aldabra giant tortoise (Aldabrachelys gigantea), estimated to be 192 years old. Relative to other giant tortoises (Aldabrachelys gigantea and Chelonoidis abingdonii), we found Jonathan has gene variants in pathways associated with aging, including DNA repair and telomere regulation. Consistent with his advanced age, Jonathan has significant age-related changes in DNA methylation and methylation entropy, compared with a 5-year-old Aldabra individual. Notably, we found that low entropy regions in Jonathans methylome were enriched for genes involved in the electron transport chain. This suggests that high-fidelity transcription of these genes may be crucial for extreme longevity. With this data, we propose a model for aging, that links efficient mitochondrial energy production with nuclear maintenance of low methylation entropy.

genomics↗

bioRxiv2020

Outcomes of the 2019 EMDataResource model challenge: validation of cryo-EM models at near-atomic resolution

This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource (www.emdataresource.org). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers and users, and (3) compare the performance of current metrics used for evaluation of models. The focus was on near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution series (1.8 to 3.1 [A]) from the same specimen and imaging experiment. Tools developed in previous challenges were expanded for managing, visualizing and analyzing the 63 submitted coordinate models, and several novel metrics were introduced. The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual laboratory experiments and holdings of structure data archives such as the Protein Data Bank. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived from these benchmark maps by 13 participating teams, representing both widely used and novel modeling approaches. We also evaluate the pros and cons of the commonly used metrics to assess model quality and recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed density in the cryo-EM map.

biochemistry↗