ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Side-chain Packing Using SE(3)-Transformer.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- PackPPI: An integrated framework for protein-protein complex side-chain packing and ΔΔG prediction based on diffusion model.Protein science : a publication of the Protein Society · 2025Article
- Advances of deep Neural Networks (DNNs) in the development of peptide drugs.Future medicinal chemistry · 2025Review
- Article
- Amino-Acid Characteristics in Protein Native State Structures.Biomolecules · 2024Article
- Invariant point message passing for protein side chain packing.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Predicting protein side-chains is important for both protein structure prediction and protein design. Modeling approaches to predict side-chains such as SCWRL4 have become one of the most widely used tools of its type due to fast and highly accurate predictions. Motivated by the recent success of AlphaFold2 in CASP14, our group adapted a 3D equivariant neural network architecture to predict protein side-chain conformations, specifically within a protein-protein interface, a problem that has not been fully addressed by AlphaFold2.
Indexed as
Identifiers
34890135PMC8887833What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.