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Possu Huang Lab

@PossuHuangLab

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Our lab uses experimental and computational methods to design de novo proteins | @Stanford

Stanford, CA
Joined October 2022
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@PossuHuangLab
Possu Huang Lab
7 months
1/ In two back-to-back papers, we present our de novo TRACeR platform for targeting MHC-I and MHC-II antigens. TRACeR for MHC-I: TRACeR for MHC-II: @HaotianDu4 @ljjchem @SgourakisLab @StanfordBiosci @UPennAllergyImm @CHOP_Research
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@PossuHuangLab
Possu Huang Lab
5 months
RT @CryoKhan: Full-atom MPNN (FAMPNN) - a sequence design method that explicitly models both sequence identity and sidechain conformation.….
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@PossuHuangLab
Possu Huang Lab
5 months
RT @BiologyAIDaily: Sidechain conditioning and modeling for full-atom protein sequence design with FAMPNN. 1. This paper introduces FAMPNN….
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@PossuHuangLab
Possu Huang Lab
5 months
RT @KevinKaichuang: All-atom fixed backbone protein sequence design with FAMPNN. @richardwshuai @talaldotpdb @PossuHuangLab @BrianHie https….
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@PossuHuangLab
Possu Huang Lab
5 months
RT @BrianHie: In new work led by @talaldotpdb and @richardwshuai, we make exciting progress toward functional molecular design by augmentin….
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@PossuHuangLab
Possu Huang Lab
5 months
RT @talaldotpdb: Excited to share our joint work with @richardwshuai, Full-Atom MPNN (FAMPNN), a protein sequence design method that explic….
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@PossuHuangLab
Possu Huang Lab
6 months
RT @KevinKaichuang: A framework for evaluating how well generative models of protein structure match the distribution of natural structures….
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@PossuHuangLab
Possu Huang Lab
6 months
RT @MoAlQuraishi: I'm organizing a Keystone symposium, along with @kellogg_liz and @PossuHuangLab, on machine learning and macromolecules.….
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@PossuHuangLab
Possu Huang Lab
6 months
Preprint: Code: Dataset:
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@PossuHuangLab
Possu Huang Lab
6 months
Our supplement has many additional figures of the rasterized protein structure space, stratified by designable and not designable and spatially organized by ESM3 and ProtDomainSegmentor embeddings. Also includes Foldseek token distributions and more designability analysis.
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@PossuHuangLab
Possu Huang Lab
6 months
One consequence of unbiased sampling of protein structure space is a higher likelihood of finding TERtiary Motifs (TERMs) which involve complex loops, with implications for functional protein design (see Figure 5 legend for group labels).
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@PossuHuangLab
Possu Huang Lab
6 months
Inspired by the FPD metric in EvoDiff for protein sequence distributions, we compute Fréchet distance using protein structure embeddings, subsetted to designable and non-designable samples (FPD-D and FPD-ND).
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@PossuHuangLab
Possu Huang Lab
6 months
New preprint from our group! We propose SHAPES, a set of metrics to quantify the distributional coverage of generative models of protein structures with embeddings at different structural hierarchies and quantify undersampling / extrapolation behaviors.
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@PossuHuangLab
Possu Huang Lab
6 months
RT @biorxiv_bioeng: Assessing Generative Model Coverage of Protein Structures with SHAPES #biorxiv_bioeng.
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@PossuHuangLab
Possu Huang Lab
6 months
RT @BiologyAIDaily: Assessing Generative Model Coverage of Protein Structures with SHAPES. 1. This paper introduces SHAPES, a comprehensive….
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@PossuHuangLab
Possu Huang Lab
6 months
RT @StanfordCancer: TRACeR platforms more accurately recognize a wide variety of surface proteins expressed by cancer cells, which makes th….
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@PossuHuangLab
Possu Huang Lab
7 months
RT @NatureBiotech: A method for designing high-affinity, specific binders to peptide–MHC complexes may improve the next generation of antig….
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@PossuHuangLab
Possu Huang Lab
7 months
RT @HaotianDu4: Thanks @MEBirnbaum and lab for the great perspective on TRACeR papers!.
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@PossuHuangLab
Possu Huang Lab
7 months
RT @Steph_Gaglione: Our piece celebrating the @PossuHuangLab's clever approach to designing high-affinity, specific binders to peptide–MHC….
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@PossuHuangLab
Possu Huang Lab
7 months
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@PossuHuangLab
Possu Huang Lab
7 months
RT @StanfordOTL: New immunotherapy platform could increase potential to target cancer cells.@PossuHuangLab.🔬Read ab….
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