AIMC Topic: Proteins

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A Convolutional Neural Network System to Discriminate Drug-Target Interactions.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
Biological targets are most commonly proteins such as enzymes, ion channels, and receptors. They are anything within a living organism to bind with some other entities (like an endogenous ligand or a drug), resulting in change in their behaviors or f...
Neural Networks, Computer Algorithms Drug Development Proteins Pharmaceutical Preparations Drug Discovery Deep Learning Computational Biology
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Predicting mutant outcome by combining deep mutational scanning and machine learning.

Proteins Jul 31, 2021
Deep mutational scanning provides unprecedented wealth of quantitative data regarding the functional outcome of mutations in proteins. A single experiment may measure properties (eg, structural stability) of numerous protein variants. Leveraging the ...
Machine Learning Mutation Computational Biology Algorithms Models, Statistical High-Throughput Nucleotide Sequencing Protein Interaction Maps Proteins DNA Mutational Analysis
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MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

Biomolecules Jul 29, 2021
In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. Howeve...
Protein Conformation, alpha-Helical Proteins Drug Discovery Protein Conformation, beta-Strand Kinetics Deep Learning Drugs, Investigational Humans High-Throughput Screening Assays Datasets as Topic Protein Binding Molecular Docking Simulation Binding Sites Protein Interaction Domains and Motifs
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Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14.

Proteins Jul 27, 2021
Substantial progresses in protein structure prediction have been made by utilizing deep-learning and residue-residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by inc...
Humans Software Algorithms Deep Learning Sequence Alignment Protein Structure, Tertiary Sequence Analysis, Protein Proteins Models, Molecular
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Protein-Peptide Binding Site Detection Using 3D Convolutional Neural Networks.

Journal of chemical information and modeling Jul 22, 2021
Peptides and peptide-based molecules represent a promising therapeutic modality targeting intracellular protein-protein interactions, potentially combining the beneficial properties of biologics and small-molecule drugs. Protein-peptide complexes occ...
Protein Binding Proteins Binding Sites Neural Networks, Computer Peptides
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Accurate prediction of protein structures and interactions using a three-track neural network.

Science (New York, N.Y.) Jul 15, 2021
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...
Multiprotein Complexes Protein Subunits Sphingosine N-Acyltransferase Protein Conformation Cryoelectron Microscopy Membrane Proteins Protein Folding Neural Networks, Computer Proteins ADAM Proteins Computer Simulation Receptors, G-Protein-Coupled Databases, Protein Crystallography, X-Ray Deep Learning Models, Molecular Amino Acid Sequence
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Highly accurate protein structure prediction with AlphaFold.

Nature Jul 15, 2021
Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this r...
Models, Molecular Amino Acid Sequence Protein Conformation Computational Biology Proteins Databases, Protein Protein Folding Sequence Alignment Neural Networks, Computer Reproducibility of Results Deep Learning
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SidechainNet: An all-atom protein structure dataset for machine learning.

Proteins Jul 12, 2021
Despite recent advancements in deep learning methods for protein structure prediction and representation, little focus has been directed at the simultaneous inclusion and prediction of protein backbone and sidechain structure information. We present ...
Protein Conformation Amino Acids Amino Acid Sequence Datasets as Topic Neural Networks, Computer Machine Learning Software Proteins
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Structure-Based Molecular Generator Combined with Artificial Intelligence and Docking Simulations.

Journal of chemical information and modeling Jul 9, 2021
Recently, molecular generation models based on deep learning have attracted significant attention in drug discovery. However, most existing molecular generation models have serious limitations in the context of drug design wherein they do not suffici...
Artificial Intelligence Molecular Docking Simulation Drug Design Neural Networks, Computer Drug Discovery Proteins
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Prediction of Protein Solubility Based on Sequence Feature Fusion and DDcCNN.

Interdisciplinary sciences, computational life sciences Jul 8, 2021
BACKGROUND: Prediction of protein solubility is an indispensable prerequisite for pharmaceutical research and production. The general and specific objective of this work is to design a new model for predicting protein solubility by using protein sequ...
Amino Acid Sequence Solubility Neural Networks, Computer Proteins Protein Domains
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