ArticleNature2022
A backbone-centred energy function of neural networks for protein design.
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Article in Nature, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39citing papers in PubMed
8.4field-weighted citation impact, top 1% of its field
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Who cites it
39 citing papers in PubMed, 101 citations in OpenAlex.
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
- Benchmarking Generative AI Protein Models Reveals Differences Between Structural and Sequence-based Approaches.Genomics, proteomics & bioinformatics · 2026Article
- Crystal structure of the histone heterodimer containing histone variant H2A.W.Biochemistry and biophysics reports · 2026Article
- Protein design and RNA design: Perspectives.Quantitative biology (Beijing, China) · 2026Article
- Generalist biological artificial intelligence in modeling the language of life.Nature biotechnology · 2026Review
- Scaffold-Lab: Critical evaluation and ranking of protein backbone generation methods in a unified framework.PLoS computational biology · 2026Article
- Review
- Computational design of superstable proteins through maximized hydrogen bonding.Nature chemistry · 2026Article
- Packing of apolar amino acids is not a strong stabilizing force in transmembrane helix dimerization.Biophysical journal · 2025Article
- Evolution-guided design of mini-protein for high-contrastActa pharmaceutica Sinica. B · 2025Article
- Delaying pyroptosis with an AI-screened gasdermin D pore blocker mitigates inflammatory response.Nature immunology · 2025Article
- A Programmed DNA Dynamic Assembly-Guided Molecular Amplifier for Authentic Information Decryption.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.Interdisciplinary sciences, computational life sciences · 2025Article
- Advances of deep Neural Networks (DNNs) in the development of peptide drugs.Future medicinal chemistry · 2025Review
- SCUBA-D: a freshly trained diffusion model generates high-quality protein structures.Nature methods · 2024Article
- De novo protein design with a denoising diffusion network independent of pretrained structure prediction models.Nature methods · 2024Article
- Opportunities and challenges in design and optimization of protein function.Nature reviews. Molecular cell biology · 2024Review
- An all-atom protein generative model.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Improving the enzymatic activity and stability of N-carbamoyl hydrolase using deep learning approach.Microbial cell factories · 2024Article
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Authors and funding
10 authors at 1 institution in 1 country.
Bin Huang *MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.ORCID http://orcid.org/0000-0002-6884-9778
Yang Xu *MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.ORCID http://orcid.org/0000-0003-3335-3278
Xiuhong Hu *MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.ORCID http://orcid.org/0000-0001-7110-274X
Yongrui LiuMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Shanhui LiaoMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Jiahai ZhangMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Chengdong HuangMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Jingjun HongMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Quan ChenMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China. chenquan@ustc.edu.cn.ORCID http://orcid.org/0000-0002-3301-3065
Haiyan LiuMOE Key Laboratory for Membraneless Organelles and Cellular Dynamics, Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China. hyliu@ustc.edu.cn.ORCID http://orcid.org/0000-0002-5926-820X
University of Science and Technology of China · CN
Funding
No grant is acknowledged in the PubMed record.
Abstract
A protein backbone structure is designable if a substantial number of amino acid sequences exist that autonomously fold into it
Indexed as
Neural Networks, ComputerProteinsAmino Acid SequenceModels, MolecularProtein ConformationProteins
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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.