AIMC Topic: Binding Sites

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Improving detection of protein-ligand binding sites with 3D segmentation.

Scientific reports Mar 19, 2020
In recent years machine learning (ML) took bio- and cheminformatics fields by storm, providing new solutions for a vast repertoire of problems related to protein sequence, structure, and interactions analysis. ML techniques, deep neural networks espe...
Protein Binding Proteins Ligands Binding Sites Software Drug Design Drug Discovery Neural Networks, Computer Machine Learning
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DeeplyTough: Learning Structural Comparison of Protein Binding Sites.

Journal of chemical information and modeling Mar 18, 2020
Protein pocket matching, or binding site comparison, is of importance in drug discovery. Identification of similar binding pockets can help guide efforts for hit-finding, understanding polypharmacology, and characterization of protein function. The d...
Protein Binding Proteins Binding Sites Neural Networks, Computer Algorithms
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Energy-based graph convolutional networks for scoring protein docking models.

Proteins Mar 16, 2020
Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative for su...
Protein Conformation, beta-Strand Thermodynamics Computer Graphics Protein Interaction Mapping Structural Homology, Protein Protein Conformation, alpha-Helical Protein Multimerization Protein Interaction Domains and Motifs Amino Acid Sequence Ligands Binding Sites Protein Binding Humans Proteins Software Benchmarking Molecular Docking Simulation Deep Learning Research Design Peptides
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Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Genes & genetic systems Mar 12, 2020
Unsupervised machine learning that can discover novel knowledge from big sequence data without prior knowledge or particular models is highly desirable for current genome study. We previously established a batch-learning self-organizing map (BLSOM) f...
Artificial Intelligence Protein Binding Humans Heterochromatin Genome, Human Binding Sites Centromere Chromosomes, Human Transcription Factors Oligonucleotides CpG Islands
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Druggability Assessment in TRAPP Using Machine Learning Approaches.

Journal of chemical information and modeling Mar 11, 2020
Accurate protein druggability predictions are important for the selection of drug targets in the early stages of drug discovery. Because of the flexible nature of proteins, the druggability of a binding pocket may vary due to conformational changes. ...
Protein Binding Proteins Protein Conformation Binding Sites Machine Learning
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ProNA2020 predicts protein-DNA, protein-RNA, and protein-protein binding proteins and residues from sequence.

Journal of molecular biology Mar 4, 2020
The intricate details of how proteins bind to proteins, DNA, and RNA are crucial for the understanding of almost all biological processes. Disease-causing sequence variants often affect binding residues. Here, we described a new, comprehensive system...
Protein Conformation Humans Nucleic Acid Conformation Neural Networks, Computer Binding Sites Machine Learning Eukaryota Sequence Analysis, Protein Protein Binding Proteins Prokaryotic Cells Computational Biology DNA RNA Software Animals
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Computational Identification and Analysis of Ubiquinone-Binding Proteins.

Cells Feb 24, 2020
Ubiquinone is an important cofactor that plays vital and diverse roles in many biological processes. Ubiquinone-binding proteins (UBPs) are receptor proteins that dock with ubiquinones. Analyzing and identifying UBPs via a computational approach will...
Computational Biology Membrane Proteins Carrier Proteins Amino Acid Sequence Humans Machine Learning Protein Binding Sequence Analysis, Protein Protein Interaction Domains and Motifs Position-Specific Scoring Matrices Ubiquinone Gene Ontology Binding Sites
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Deep neural networks for interpreting RNA-binding protein target preferences.

Genome research Jan 28, 2020
Deep learning has become a powerful paradigm to analyze the binding sites of regulatory factors including RNA-binding proteins (RBPs), owing to its strength to learn complex features from possibly multiple sources of raw data. However, the interpreta...
Binding Sites Deep Learning Humans Nucleotide Motifs Protein Binding Neural Networks, Computer RNA-Binding Proteins Algorithms
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Prediction of Protein-Protein Interaction Sites Using Convolutional Neural Network and Improved Data Sets.

International journal of molecular sciences Jan 11, 2020
Protein-protein interaction (PPI) sites play a key role in the formation of protein complexes, which is the basis of a variety of biological processes. Experimental methods to solve PPI sites are expensive and time-consuming, which has led to the dev...
Datasets as Topic Humans Binding Sites Animals Protein Interaction Mapping Neural Networks, Computer Protein Binding Reproducibility of Results
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Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4.

Journal of computer-aided molecular design Jan 8, 2020
Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secret...
Humans Neural Networks, Computer Molecular Docking Simulation Binding Sites Enzyme Inhibitors Drug Design Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases Protein Binding Macrocyclic Compounds Ligands
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