AIMC Topic: Proteins

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Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.

PloS one Sep 2, 2021
Finding optimal parameters for force fields used in molecular simulation is a challenging and time-consuming task, partly due to the difficulty of tuning multiple parameters at once. Automatic differentiation presents a general solution: run a simula...
Crystallization Protein Structure, Tertiary Protein Conformation, beta-Strand Nuclear Energy Temperature Protein Conformation, alpha-Helical Deep Learning Proteins Molecular Dynamics Simulation
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Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses.

Journal of chemical information and modeling Sep 1, 2021
Machine learning scoring functions for protein-ligand binding affinity have been found to consistently outperform classical scoring functions when trained and tested on crystal structures of bound protein-ligand complexes. However, it is less clear h...
Protein Binding Proteins Ligands Machine Learning Molecular Docking Simulation
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DEEP picker is a deep neural network for accurate deconvolution of complex two-dimensional NMR spectra.

Nature communications Sep 1, 2021
The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Her...
Neural Networks, Computer Deep Learning Magnetic Resonance Imaging Automation Algorithms Metabolomics Nuclear Magnetic Resonance, Biomolecular Proteins Magnetic Resonance Spectroscopy
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Improved protein relative solvent accessibility prediction using deep multi-view feature learning framework.

Analytical biochemistry Aug 31, 2021
The accurate prediction of the relative solvent accessibility of a protein is critical to understanding its 3D structure and biological function. In this study, a novel deep multi-view feature learning (DMVFL) framework that integrates three differen...
Solvents Protein Structure, Secondary Databases, Protein Internet Computational Biology Proteins Feedback Deep Learning Neural Networks, Computer
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From computer-aided drug discovery to computer-driven drug discovery.

Drug discovery today. Technologies Aug 30, 2021
Computational chemistry and structure-based design have traditionally been viewed as a subset of tools that could aid acceleration of the drug discovery process, but were not commonly regarded as a driving force in small molecule drug discovery. In t...
Drug Discovery Proteins Computers Artificial Intelligence Computer-Aided Design Machine Learning Drug Design
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Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.

PloS one Aug 26, 2021
Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to introduce the desired properties. Challenging design problems necessitate the representation of a pr...
Computational Biology Proteins Neural Networks, Computer Algorithms Amino Acid Sequence Databases, Protein Thermodynamics Mutation Epistasis, Genetic
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SecProCT: In Silico Prediction of Human Secretory Proteins Based on Capsule Network and Transformer.

International journal of molecular sciences Aug 22, 2021
Identifying secretory proteins from blood, saliva or other body fluids has become an effective method of diagnosing diseases. Existing secretory protein prediction methods are mainly based on conventional machine learning algorithms and are highly de...
Bodily Secretions Deep Learning Proteins Computer Simulation Biomarkers, Tumor Humans
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DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning.

Molecular & cellular proteomics : MCP Aug 21, 2021
A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular medicine, and targeted treatment. Antibody-based proteomics using immunohistochemistry (IHC) has pr...
Testis Proteins Workflow Immunohistochemistry Bayes Theorem Deep Learning Image Processing, Computer-Assisted Humans Male
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Protein inter-residue contact and distance prediction by coupling complementary coevolution features with deep residual networks in CASP14.

Proteins Aug 19, 2021
This article reports and analyzes the results of protein contact and distance prediction by our methods in the 14th Critical Assessment of techniques for protein Structure Prediction (CASP14). A new deep learning-based contact/distance predictor was ...
Software Deep Learning Computational Biology Sequence Analysis, Protein Protein Conformation Proteins Sequence Alignment Models, Molecular
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Informed training set design enables efficient machine learning-assisted directed protein evolution.

Cell systems Aug 19, 2021
Directed evolution of proteins often involves a greedy optimization in which the mutation in the highest-fitness variant identified in each round of single-site mutagenesis is fixed. The efficiency of such a single-step greedy walk depends on the ord...
Machine Learning Proteins Mutation Mutagenesis
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