AIMC Topic: Proteins

Clear Filters Showing 391 to 400 of 1967 articles

Label-free identification of protein aggregates using deep learning.

Nature communications Nov 28, 2023
Protein misfolding and aggregation play central roles in the pathogenesis of various neurodegenerative diseases (NDDs), including Huntington's disease, which is caused by a genetic mutation in exon 1 of the Huntingtin protein (Httex1). The fluorescen...
Proteins Protein Aggregates Deep Learning Humans Huntington Disease Protein Processing, Post-Translational Huntingtin Protein
View on PubMed DOI

Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction.

Science advances Nov 22, 2023
Chemical shift assignment is vital for nuclear magnetic resonance (NMR)-based studies of protein structures, dynamics, and interactions, providing crucial atomic-level insight. However, obtaining chemical shift assignments is labor intensive and requ...
Deep Learning Magnetic Resonance Spectroscopy Algorithms Magnetic Resonance Imaging Proteins
View on PubMed DOI

From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction.

Journal of chemical information and modeling Nov 20, 2023
Accurate in silico prediction of protein-ligand binding affinity is important in the early stages of drug discovery. Deep learning-based methods exist but have yet to overtake more conventional methods such as giga-docking largely due to their lack o...
Deep Learning Protein Binding Proteins Ligands Neural Networks, Computer
View on PubMed DOI

Ensemble Learning with Supervised Methods Based on Large-Scale Protein Language Models for Protein Mutation Effects Prediction.

International journal of molecular sciences Nov 18, 2023
Machine learning has been increasingly utilized in the field of protein engineering, and research directed at predicting the effects of protein mutations has attracted increasing attention. Among them, so far, the best results have been achieved by r...
Proteins Amino Acid Sequence Machine Learning Reproducibility of Results Linear Models
View on PubMed DOI

Evaluating the chaos game representation of proteins for applications in machine learning models: prediction of antibody affinity and specificity as a case study.

Journal of molecular modeling Nov 15, 2023
CONTEXT: Machine learning techniques are becoming increasingly important in the selection and optimization of therapeutic molecules, as well as for the selection of formulation components and the prediction of long-term stability. Compared to first-p...
Antibody Affinity Proteins Amino Acid Sequence Neural Networks, Computer Machine Learning
View on PubMed DOI

Functional annotation of enzyme-encoding genes using deep learning with transformer layers.

Nature communications Nov 14, 2023
Functional annotation of open reading frames in microbial genomes remains substantially incomplete. Enzymes constitute the most prevalent functional gene class in microbial genomes and can be described by their specific catalytic functions using the ...
Open Reading Frames Genome Escherichia coli K12 Molecular Sequence Annotation Deep Learning Escherichia coli Proteins
View on PubMed DOI

Predicting multiple conformations via sequence clustering and AlphaFold2.

Nature Nov 13, 2023
AlphaFold2 (ref. ) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological function often depends on multiple conformational substates, and disease-causing point mutations often ca...
Protein Conformation Protein Folding Bacterial Proteins Mutation Sequence Alignment Rhodobacter sphaeroides Machine Learning Cluster Analysis Proteins
View on PubMed DOI

Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations.

Journal of chemical information and modeling Nov 13, 2023
Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. H...
Artificial Intelligence Proteins Thermodynamics Protein Folding Molecular Dynamics Simulation
View on PubMed DOI

Role of environmental specificity in CASP results.

BMC bioinformatics Nov 11, 2023
BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Predict...
Protein Conformation Protein Folding Artificial Intelligence Proteins Models, Molecular Hydrophobic and Hydrophilic Interactions
View on PubMed DOI

Equivariant Flexible Modeling of the Protein-Ligand Binding Pose with Geometric Deep Learning.

Journal of chemical theory and computation Nov 8, 2023
Flexible modeling of the protein-ligand complex structure is a fundamental challenge for in silico drug development. Recent studies have improved commonly used docking tools by incorporating extra-deep learning-based steps. However, such strategies l...
Molecular Docking Simulation Deep Learning Ligands Protein Conformation Protein Binding Proteins
View on PubMed DOI
Popular Topics
Recent Journals