AIMC Topic: Proteins

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Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.

Proteins Aug 17, 2021
The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to se...
Computational Biology Proteins Sequence Analysis, Protein Metagenome Protein Structure, Tertiary Humans Software Deep Learning
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PYTHIA: Deep Learning Approach for Local Protein Conformation Prediction.

International journal of molecular sciences Aug 17, 2021
Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1...
Software Algorithms Proteins Databases, Protein Deep Learning Models, Molecular Sequence Analysis, Protein Protein Conformation Humans Neural Networks, Computer
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Assigning secondary structure in proteins using AI.

Journal of molecular modeling Aug 17, 2021
Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the 1980s, various methods bas...
Models, Molecular Protein Structure, Secondary Deep Learning Proteins Software
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An interpretable machine learning method for homo-trimeric protein interface residue-residue interaction prediction.

Biophysical chemistry Aug 13, 2021
Protein-protein interaction plays an important role in life activities. A more fine-grained analysis, such as residues and atoms level, will better benefit us to understand the mechanism for inter-protein interaction and drug design. The development ...
Computational Biology Proteins Machine Learning Algorithms
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Accurate Estimation of Solvent Accessible Surface Area for Coarse-Grained Biomolecular Structures with Deep Learning.

The journal of physical chemistry. B Aug 12, 2021
Coarse-grained (CG) models of biomolecules have been widely used in protein/ribonucleic acid (RNA) three-dimensional structure prediction, docking, drug design, and molecular simulations due to their superiority in computational efficiency. Most of t...
RNA Solvents Algorithms Deep Learning Proteins
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DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks.

Journal of chemical information and modeling Aug 10, 2021
A structure-based drug design pipeline involves the development of potential drug molecules or ligands that form stable complexes with a given receptor at its binding site. A prerequisite to this is finding druggable and functionally relevant binding...
Binding Sites Proteins Ligands Software Algorithms Neural Networks, Computer
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Deep learning to design nuclear-targeting abiotic miniproteins.

Nature chemistry Aug 9, 2021
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...
Deep Learning Proteins Datasets as Topic Cell Nucleus Protein Conformation Models, Molecular Molecular Weight Protein Transport Cytosol
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Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14.

Proteins Aug 7, 2021
In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed com...
Computational Biology Proteins Models, Molecular Software Deep Learning Protein Folding Sequence Alignment Sequence Analysis, Protein Protein Conformation Hydrogen Bonding
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Accurate Identification of Antioxidant Proteins Based on a Combination of Machine Learning Techniques and Hidden Markov Model Profiles.

Computational and mathematical methods in medicine Aug 7, 2021
Antioxidant proteins (AOPs) play important roles in the management and prevention of several human diseases due to their ability to neutralize excess free radicals. However, the identification of AOPs by using wet-lab experimental techniques is often...
Peroxiredoxins Evolution, Molecular Algorithms Computational Biology Proteins Humans Amino Acids Databases, Protein Antioxidants Machine Learning Markov Chains
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KenDTI: An Ensemble Model for Predicting Drug-Target Interaction by Integrating Multi-Source Information.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
The identification of drug-target interactions (DTIs) is an essential step in the process of drug discovery. As experimental validation suffers from high cost and low success rate, various computational models have been exploited to infer potential D...
Databases, Pharmaceutical Natural Language Processing Pharmaceutical Preparations Neural Networks, Computer Software Humans Drug Development Algorithms Computer Simulation Proteins Computational Biology Databases, Protein
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