AIMC Topic: Protein Conformation

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Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Methods in enzymology Dec 8, 2022
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...
Models, Molecular Epitopes X-Ray Diffraction Deep Learning Proteins Proprotein Convertase 9 Antigen-Antibody Complex Scattering, Small Angle Protein Conformation Cryoelectron Microscopy Humans
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AlphaFill: enriching AlphaFold models with ligands and cofactors.

Nature methods Nov 24, 2022
Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein models in the AlphaFold protein structure database, however, all lack coordinates for small molecul...
Proteins Ions Protein Conformation Ligands Artificial Intelligence Zinc
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Single-sequence protein structure prediction using a language model and deep learning.

Nature biotechnology Oct 3, 2022
AlphaFold2 and related computational systems predict protein structure using deep learning and co-evolutionary relationships encoded in multiple sequence alignments (MSAs). Despite high prediction accuracy achieved by these systems, challenges remain...
Deep Learning Computational Biology Proteins Language Protein Conformation Sequence Alignment
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Fast and accurate Ab Initio Protein structure prediction using deep learning potentials.

PLoS computational biology Sep 16, 2022
Despite the immense progress recently witnessed in protein structure prediction, the modeling accuracy for proteins that lack sequence and/or structure homologs remains to be improved. We developed an open-source program, DeepFold, which integrates s...
Protein Folding Computational Biology Proteins Software Models, Molecular Databases, Protein Protein Conformation Algorithms Deep Learning
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Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.) Sep 15, 2022
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based pro...
Crystallography, X-Ray Protein Conformation Cryoelectron Microscopy Protein Engineering Proteins Amino Acid Sequence Deep Learning
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Hallucinating symmetric protein assemblies.

Science (New York, N.Y.) Sep 15, 2022
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-...
Protein Conformation Protein Engineering Cryoelectron Microscopy Models, Molecular Biocompatible Materials Protein Subunits Deep Learning
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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 Aug 30, 2022
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...
Ligands Receptors, Neuropeptide Protein Conformation Neuropeptides Mutagenesis Artificial Intelligence Amides Aplysia Animals
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Improved Protein Real-Valued Distance Prediction Using Deep Residual Dense Network (DRDN).

The protein journal Aug 25, 2022
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. ...
Computational Biology Protein Conformation Proteins Neural Networks, Computer Databases, Protein Algorithms
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AlphaFold, Artificial Intelligence (AI), and Allostery.

The journal of physical chemistry. B Aug 17, 2022
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...
Allosteric Regulation Protein Conformation Protein Folding Artificial Intelligence Molecular Dynamics Simulation Humans Intrinsically Disordered Proteins
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I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.

Nature protocols Aug 5, 2022
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...
Deep Learning Computational Biology Databases, Protein Models, Molecular Proteins Algorithms Protein Conformation Cryoelectron Microscopy
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