AIMC Topic: Proteins

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Lite-SeqCNN: A Light-Weight Deep CNN Architecture for Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
The short-and-long range interactions amongst amino-acids in a protein sequence are primarily responsible for the function performed by the protein. Recently convolutional neural network (CNN)s have produced promising results on sequential data inclu...
Amino Acids Amino Acid Sequence Proteins Databases, Factual Neural Networks, Computer
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GraphPLBR: Protein-Ligand Binding Residue Prediction With Deep Graph Convolution Network.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating dr...
Protein Binding Proteins Neural Networks, Computer Ligands Amino Acids
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Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
The recognition of protein-protein interaction sites (PPIs) is beneficial for the interpretation of protein functions and the development of new drugs. Traditional biological experiments to identify PPI sites are expensive and inefficient, leading to...
Proteins Neural Networks, Computer
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A Deep Neural Network-Based Co-Coding Method to Predict Drug-Protein Interactions by Analyzing the Feature Consistency Between Drugs and Proteins.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
Exploring drug-protein interactions (DPIs) through computational methods can effectively reduce the workload and the cost of DPI identification. Previous works try to predict DPIs by integrating and analyzing the unique features of drugs and proteins...
Proteins Neural Networks, Computer
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CPGL: Prediction of Compound-Protein Interaction by Integrating Graph Attention Network With Long Short-Term Memory Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2023
Recent advancements of artificial intelligence based on deep learning algorithms have made it possible to computationally predict compound-protein interaction (CPI) without conducting laboratory experiments. In this manuscript, we integrated a graph ...
Neural Networks, Computer Artificial Intelligence Humans Proteins Caenorhabditis elegans Animals Algorithms
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Using artificial neural networks to accelerate flowsheet optimization for downstream process development.

Biotechnology and bioengineering May 31, 2023
An optimal purification process for biopharmaceutical products is important to meet strict safety regulations, and for economic benefits. To find the global optimum, it is desirable to screen the overall design space. Advanced model-based approaches ...
Proteins Time Factors Drug Contamination Models, Theoretical Neural Networks, Computer Chromatography
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Mathematical and Machine Learning Approaches for Classification of Protein Secondary Structure Elements from Coordinates.

Biomolecules May 31, 2023
Determining Secondary Structure Elements (SSEs) for any protein is crucial as an intermediate step for experimental tertiary structure determination. SSEs are identified using popular tools such as DSSP and STRIDE. These tools use atomic information ...
Hydrogen Bonding Algorithms Machine Learning Proteins Protein Structure, Secondary
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An end-to-end deep learning method for protein side-chain packing and inverse folding.

Proceedings of the National Academy of Sciences of the United States of America May 30, 2023
Protein side-chain packing (PSCP), the task of determining amino acid side-chain conformations given only backbone atom positions, has important applications to protein structure prediction, refinement, and design. Many methods have been proposed to ...
Protein Folding Molecular Conformation Protein Conformation Amino Acids Proteins Deep Learning
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Identification of SH2 domain-containing proteins and motifs prediction by a deep learning method.

Computers in biology and medicine May 29, 2023
The Src Homology 2 (SH2) domain plays an important role in the signal transmission mechanism in organisms. It mediates the protein-protein interactions based on the combination between phosphotyrosine and motifs in SH2 domain. In this study, we desig...
Signal Transduction Deep Learning Proteins Phosphotyrosine Protein Binding Binding Sites src Homology Domains
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Residue-level error detection in cryoelectron microscopy models.

Structure (London, England : 1993) May 29, 2023
Building accurate protein models into moderate resolution (3-5 Å) cryoelectron microscopy (cryo-EM) maps is challenging and error prone. We have developed MEDIC (Model Error Detection in Cryo-EM), a robust statistical model that identifies local back...
Cryoelectron Microscopy Protein Conformation Proteins Models, Molecular Machine Learning
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