Nature Search

Cas9 senses CRISPR RNA abundance to regulate CRISPR spacer acquisition

Cas9 in type II-C CRISPR–Cas systems functions independently of its RNA partners to regulate spacer acquisition, dynamically adjusting the process on the basis of crRNA abundance to maintain a sufficient CRISPR array size and immune memory.

Xufei Zhou
Rucheng Diao
Yan Zhang
ResearchOpen Access03 Sept 2025
Nature

P: 1-9
Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER

Protein structures are predicted by integrating deep learning potentials with iterative threading fragment assembly simulations.

Wei Zheng
Qiqige Wuyun
Yang Zhang
ResearchOpen Access23 May 2025
Nature Biotechnology

P: 1-13
Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data

The DeepMSA2 pipeline employs iterative alignment search against large genomic and metagenomic sequence databases to construct single- and multichain multiple-sequence alignment (MSA) for proteins. Use of these MSAs shows improvement for deep learning-based protein tertiary and quaternary structure predictions.

Wei Zheng
Qiqige Wuyun
Yang Zhang
ResearchOpen Access02 Jan 2024
Nature Methods

Volume: 21, P: 279-289
Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction

Here the authors developed an open-source program (DRfold) for RNA tertiary structure prediction from sequence. Through a unique combination of end-to-end learning and geometry restraint guided simulations, the method demonstrates advantage over peer methods.

Yang Li
Chengxin Zhang
Yang Zhang
ResearchOpen Access16 Sept 2023
Nature Communications

Volume: 14, P: 1-13
A graphic and command line protocol for quick and accurate comparisons of protein and nucleic acid structures with US-align

US-align is a versatile, open-source program for the structure comparisons of proteins, RNAs and DNAs in pairwise and multiple alignment forms. Applicable to both monomeric and multimeric structures, it allows comparison across different molecular types.

Chengxin Zhang
Lydia Freddolino
Yang Zhang
Protocols02 Jul 2025
Nature Protocols

P: 1-25
CR-I-TASSER: assemble protein structures from cryo-EM density maps using deep convolutional neural networks

CR-I-TASSER integrates deep neural-network learning with I-TASSER assembly simulations for automated cryo-EM structure determination.

Xi Zhang
Biao Zhang
Yang Zhang
Research07 Feb 2022
Nature Methods

Volume: 19, P: 195-204
Challenges in protein-folding simulations

A protein’s shape is crucial for fulfilling its function within a cell. This Review discusses how molecular dynamics simulations have given us insight into the processes that turn a linear chain of amino acids into a unique three-dimensional protein.

Lydia Freddolino
Christopher B. Harrison
Klaus Schulten
Reviews01 Oct 2010
Nature Physics

Volume: 6, P: 751-758

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Cas9 senses CRISPR RNA abundance to regulate CRISPR spacer acquisition

Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER

Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data

Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction

A graphic and command line protocol for quick and accurate comparisons of protein and nucleic acid structures with US-align

CR-I-TASSER: assemble protein structures from cryo-EM density maps using deep convolutional neural networks

Challenges in protein-folding simulations

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