Biology subjects

Woo, H.

Publications and source records attributed to Woo, H..

8 recordsLinked to original sources

bioRxiv2025

Precision at Every Scale: Efficiency in AI-Driven De Novo Antibody Design

The precise de novo design of antibodies remains a therapeutic challenge. The AI platform, GaluxDesign, was evaluated in a high-efficiency Precision-Scale Workflow by synthesizing and testing only 50 full-length IgG candidates per epitope across eight distinct epitopes from six therapeutic targets. This campaign yielded a 10.5% binder rate (estimated EC50 < 100 nM), identifying target-specific binders for seven of eight epitopes, with multiple candidates exhibiting sub-nanomolar to single-digit nanomolar dissociation constants (Kd). We further assessed the same workflow on nine shared benchmark targets selected for external comparison, where GaluxDesign identified target-specific binders for eight of nine targets, demonstrating strong target-level performance relative to previously reported de novo antibody design approaches. Together, these results establish a high-efficiency, precision-scale workflow for generating novel, high-affinity therapeutic antibodies.

bioengineering↗

bioRxiv2025

Precise, Specific, and Sensitive De Novo Antibody Design Across Multiple Cases

The precision design of antibodies, which naturally recognize diverse molecules through six variable loops, remains a critical challenge in therapeutic molecule discovery. In this study, we demonstrate that precise, sensitive, and specific antibody design can be achieved without prior antibody information across eight distinct target proteins. For each target, binders were identified from a yeast display scFv library of approximately 106 sequences, constructed by combining 102 designed light chain sequences with 104 designed heavy chain sequences. Binders with varying binding strengths were identified for all eight targets, including a case where no experimentally resolved target protein structure was available, demonstrating the highest level of precision compared to previous de novo antibody design reports. To further validate the designed antibodies, they were characterized in the IgG format for five distinct targets. The antibodies exhibited favorable developability properties, positioning them as promising hit or lead candidates. Notably, for one target in particular, the IgG-formatted antibodies exhibited affinity, activity, and developability, comparable to a commercial antibody, highlighting the sensitivity of the design method. Furthermore, binders capable of distinguishing closely related protein subtypes or mutants were identified, demonstrating that the method can achieve high molecular specificity. Cryo-EM analysis experimentally validated the designs accuracy by confirming that the key binding interactions were precisely as designed. These findings underscore the effectiveness of precision molecular design based on atomic-accuracy structure prediction. This study establishes computational antibody design as a viable approach for generating therapeutic molecules with tailored properties, with promising potential for achieving the efficacy and safety required for successful therapeutics.

bioengineering↗

bioRxiv2024

Accurate antibody loop structure prediction enables zero-shot design of target-specific antibodies

Protein loops, characterized by their versatile structures with varying sizes and shapes, can recognize a wide range of targets with high specificity and affinity. The variable loops of the antibody complementarity-determining region (CDR) are particularly crucial for immune responses and therapeutic applications due to their effective target recognition capabilities. Accurate structure prediction of these antibody loops is essential for the efficient in silico design of target-binding antibodies for therapeutic or industrial use. However, predicting antibody loop structures is challenging due to the lack of evolutionary information from related proteins. Thus, a successful ab initio structure prediction method, which operates without structural templates or related sequences, is crucial for the effective design of antibody loop-mediated interactions. This study demonstrates that highly accurate antibody loop structure prediction enables the effective zero-shot design of target-binding antibody loops. The performance of loop design has been shown to depend on the accuracy of ab initio loop structure prediction, as tested with two versions of our design model. The high affinity, diversity, novelty, and specificity of the antibody loops designed with these new methods were validated experimentally on four target proteins.

bioengineering↗

bioRxiv2023

Enhanced Omicron subvariant cross-neutralization efficacy of a monovalent SARS-CoV-2 BA.4/5 mRNA vaccine encoding a noncleaved, nonfusogenic spike antigen

The rapid emergence of diverse SARS-CoV-2 variants, notably the Omicron variant, poses challenges to vaccine development. Here, we present a noncleaved, nonfusogenic spike (S) protein eliciting robust B- and T-cell immune responses against Omicron BA.5. The antigen incorporates the R685S and R815A mutations, effectively preventing the shedding of the S1 subunit and eliminating fusogenic activity of the resulting S antigen, termed S(SA). Through reverse genetic analysis, we found that the noncleaved form S protein with the R685S mutation enhances ACE2-dependent viral entry in vitro compared to the wild-type S protein, without increasing the virulence of the mutant virus in mice. The mRNA vaccine encoding the Omicron BA.4/5 S(SA) antigen conferred protective immunity in mice following two doses of 1 g {Psi}-UTP- or UTP-incorporated mRNA vaccines. Despite a roughly 6-fold reduction in neutralizing potency, both mRNA vaccines exhibited broad neutralizing efficacy against Omicron subvariants, including the XBB lineage variants XBB.1.5 and XBB.1.16.

immunology↗

bioRxiv2022

Cryo-EM structure of human somatostatin receptor 2 complex with its agonist somatostatin delineates the ligand binding specificity

Somatostatin is a peptide hormone regulating endocrine systems through binding to G-protein-coupled somatostatin receptors. somatostatin receptor 2 (SSTR2) is one of the human somatostatin receptors and highly implicated in cancers and neurological disorders. Here, we report the high resolution cryo-EM structure of full-length human SSTR2 bound to the agonist somatostatin (SST-14) complex with inhibitory G (Gi) proteins. Our structure shows that seven transmembrane helices form a deep pocket for ligand binding and that the highly conserved Trp-Lys motif of SST-14 positions at the bottom of the pocket. Furthermore, our sequence analysis combined with AlphaFold modeled structures of other SSTR isoforms provide how SSTR family proteins specifically interact with their cognate ligands. This work provides the first glimpse into the molecular recognition of somatostatin receptor and crucial resource to develop therapeutics targeting somatostatin receptors.

biophysics↗

bioRxiv2021

Dynamic Interactions of Fully Glycosylated SARS-CoV-2 Spike Protein with Various Antibodies

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a public health crisis, and the vaccines that can induce highly potent neutralizing antibodies are essential for ending the pandemic. The spike (S) protein on the viral envelope mediates human angiotensin-converting enzyme 2 (ACE2) binding and thus is the target of a variety of neutralizing antibodies. In this work, we built various S trimer-antibody complex structures on the basis of the fully glycosylated S protein models described in our previous work, and performed all-atom molecular dynamics simulations to get insight into the structural dynamics and interactions between S protein and antibodies. Investigation of the residues critical for S-antibody binding allows us to predict the potential influence of mutations in SARS-CoV-2 variants. Comparison of the glycan conformations between S-only and S-antibody systems reveals the roles of glycans in S-antibody binding. In addition, we explored the antibody binding modes, and the influences of antibody on the motion of S protein receptor binding domains. Overall, our analyses provide a better understanding of S-antibody interactions, and the simulation-based S-antibody interaction maps could be used to predict the influences of S mutation on S-antibody interactions, which will be useful for the development of vaccine and antibody-based therapy.

biophysics↗

bioRxiv2020

Structure, Dynamics, Receptor Binding, and Antibody Binding of Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediates host cell entry by binding to angiotensin-converting enzyme 2 (ACE2), and is considered the major target for drug and vaccine development. We previously built fully-glycosylated full-length SARS-CoV-2 S protein models in a viral membrane including both open and closed conformations of receptor binding domain (RBD) and different templates for the stalk region. In this work, multiple s-long all-atom molecular dynamics simulations were performed to provide deeper insight into the structure and dynamics of S protein, and glycan functions. Our simulations reveal that the highly flexible stalk is composed of two independent joints and most probable S protein orientations are competent for ACE2 binding. We identify multiple glycans stabilizing the open and/or closed states of RBD, and demonstrate that the exposure of antibody epitopes can be captured by detailed antibody-glycan clash analysis instead of a commonly-used accessible surface area analysis that tends to overestimate the impact of glycan shielding and neglect possible detailed interactions between glycan and antibody. Overall, our observations offer structural and dynamic insight into SARS-CoV-2 S protein and potentialize for guiding the design of effective antiviral therapeutics.

biophysics↗

bioRxiv2020

Modeling and Simulation of a Fully-glycosylated Full-length SARS-CoV-2 Spike Protein in a Viral Membrane

This technical study describes all-atom modeling and simulation of a fully-glycosylated full-length SARS-CoV-2 spike (S) protein in a viral membrane. First, starting from PDB:6VSB and 6VXX, full-length S protein structures were modeled using template-based modeling, de-novo protein structure prediction, and loop modeling techniques in GALAXY modeling suite. Then, using the recently-determined most occupied glycoforms, 22 N-glycans and 1 O-glycan of each monomer were modeled using Glycan Reader & Modeler in CHARMM-GUI. These fully-glycosylated full-length S protein model structures were assessed and further refined against the low-resolution data in their respective experimental maps using ISOLDE. We then used CHARMM-GUI Membrane Builder to place the S proteins in a viral membrane and performed all-atom molecular dynamics simulations. All structures are available in CHARMM-GUI COVID-19 Archive (http://www.charmm-gui.org/docs/archive/covid19), so researchers can use these models to carry out innovative and novel modeling and simulation research for the prevention and treatment of COVID-19.

biophysics↗