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Protein Conformation

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Hallucinating symmetric protein assemblies.

Science (New York, N.Y.)
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-...

AI protein structure prediction-based modeling and mutagenesis of a protostome receptor and peptide ligands reveal key residues for their interaction.

The Journal of biological chemistry
The protostome leucokinin (LK) signaling system, including LK peptides and their G protein-coupled receptors, has been characterized in several species. Despite the progress, molecular mechanisms governing LK peptide-receptor interactions remain to b...

Improved Protein Real-Valued Distance Prediction Using Deep Residual Dense Network (DRDN).

The protein journal
Three-dimensional protein structure prediction is one of the major challenges in bioinformatics. According to recent research findings, real-valued distance prediction plays a vital role in determining the unique three-dimensional protein structure. ...

AlphaFold, Artificial Intelligence (AI), and Allostery.

The journal of physical chemistry. B
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises a...

I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.

Nature protocols
Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-d...

Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly.

Nature communications
Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps. However, building accurate models into intermediate-resolution EM maps remains challenging and labor-inten...

Automated Protein Secondary Structure Assignment from C Positions Using Neural Networks.

Biomolecules
The assignment of secondary structure elements in protein conformations is necessary to interpret a protein model that has been established by computational methods. The process essentially involves labeling the amino acid residues with H (Helix), E ...

Simultaneous prediction of antibody backbone and side-chain conformations with deep learning.

PloS one
Antibody engineering is becoming increasingly popular in medicine for the development of diagnostics and immunotherapies. Antibody function relies largely on the recognition and binding of antigenic epitopes via the loops in the complementarity deter...

Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold.

Science (New York, N.Y.)
INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of biomolecules between the nucleus and the cytosol, with vertebrate NPCs ~110 to 125 MDa in molecular m...

Using Big Data Analytics to "Back Engineer" Protein Conformational Selection Mechanisms.

Molecules (Basel, Switzerland)
In the living cells, proteins bind small molecules (or "ligands") through a "conformational selection" mechanism, where a subset of protein structures are capable of binding the small molecules well while most other protein structures are not capable...