AI Medical Compendium Topic:
Protein Binding

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Predicting protein-peptide binding sites with a deep convolutional neural network.

Journal of theoretical biology Apr 13, 2020
MOTIVATION: Interactions between proteins and peptides influence biological functions. Predicting such bio-molecular interactions can lead to faster disease prevention and help in drug discovery. Experimental methods for determining protein-peptide b...
Protein Binding Proteins Binding Sites Neural Networks, Computer Peptides
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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 Software Proteins Drug Design Neural Networks, Computer Binding Sites Ligands Machine Learning Drug Discovery
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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...
Neural Networks, Computer Algorithms Protein Binding Proteins Binding Sites
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Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Journal of computer-aided molecular design Mar 17, 2020
Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-meta...
Computational Biology Machine Learning Quantum Theory Proteins Drug Design Ligands Metals Databases, Protein Protein Binding
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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 Multimerization Protein Interaction Domains and Motifs Structural Homology, Protein Protein Conformation, alpha-Helical Molecular Docking Simulation Protein Conformation, beta-Strand Deep Learning Protein Binding Thermodynamics Proteins Computer Graphics Ligands Benchmarking Protein Interaction Mapping Binding Sites Amino Acid Sequence Software Research Design Peptides Humans
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Machine Learning to Identify Flexibility Signatures of Class A GPCR Inhibition.

Biomolecules Mar 14, 2020
We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our anal...
Protein Domains Ligands Machine Learning Protein Binding Humans Receptors, G-Protein-Coupled
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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...
Transcription Factors Oligonucleotides CpG Islands Genome, Human Binding Sites Centromere Humans Artificial Intelligence Protein Binding Chromosomes, Human Heterochromatin
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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. ...
Machine Learning Binding Sites Protein Binding Proteins Protein Conformation
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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...
Humans Neural Networks, Computer Machine Learning Sequence Analysis, Protein Prokaryotic Cells DNA RNA Protein Conformation Nucleic Acid Conformation Binding Sites Protein Binding Eukaryota Software Computational Biology Proteins Animals
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Combining Docking Pose Rank and Structure with Deep Learning Improves Protein-Ligand Binding Mode Prediction over a Baseline Docking Approach.

Journal of chemical information and modeling Mar 3, 2020
We present a simple, modular graph-based convolutional neural network that takes structural information from protein-ligand complexes as input to generate models for activity and binding mode prediction. Complex structures are generated by a standard...
Ligands Deep Learning Protein Binding Proteins Molecular Docking Simulation
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