AI Medical Compendium Topic:
Protein Binding

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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Machine Learning Algorithms Molecular Docking Simulation Protein Binding Protein Conformation Binding Sites Protein Multimerization Computational Biology Proteins Ligands
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High-order neural networks and kernel methods for peptide-MHC binding prediction.

Bioinformatics (Oxford, England) Jul 23, 2015
MOTIVATION: Effective computational methods for peptide-protein binding prediction can greatly help clinical peptide vaccine search and design. However, previous computational methods fail to capture key nonlinear high-order dependencies between diff...
Major Histocompatibility Complex Neural Networks, Computer Algorithms Epitopes Peptides Amino Acid Sequence Humans ROC Curve Molecular Sequence Data Protein Binding Support Vector Machine Databases, Protein Area Under Curve
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Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Journal of chemical information and modeling Jul 10, 2015
The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust est...
Machine Learning Algorithms Protein Conformation Protein Binding Support Vector Machine Protein Kinase Inhibitors Decision Trees Chromosomes Models, Molecular Cyclin-Dependent Kinases Bayes Theorem
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The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling Jun 19, 2015
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...
Ligands Cyclooxygenase 2 Inhibitors Datasets as Topic Catalytic Domain Structure-Activity Relationship Molecular Structure Quantum Theory Arachidonate 5-Lipoxygenase Cyclooxygenase 2 Lipoxygenase Inhibitors Substrate Specificity Humans Neural Networks, Computer Algorithms Molecular Docking Simulation Protein Binding
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Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

BMC bioinformatics Apr 17, 2015
BACKGROUND: Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when boun...
Ligands Binding Sites Drug Design Humans Drug Discovery Artificial Intelligence Protein Binding Software Proteins
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NIEluter: Predicting peptides eluted from HLA class I molecules.

Journal of immunological methods Apr 7, 2015
The immune system has evolved to make a diverse repertoire of peptides processed from self and foreign proteomes, which are displayed in antigen-binding grooves of major histocompatibility complex (MHC) proteins at cell surface for surveillance by T ...
Histocompatibility Antigens Class I Markov Chains Peptides Protein Binding Immunity, Cellular Support Vector Machine Humans Algorithms T-Lymphocytes
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BgN-Score and BsN-Score: bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes.

BMC bioinformatics Feb 23, 2015
BACKGROUND: Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scorin...
Ligands Humans Binding Sites Neural Networks, Computer Computational Biology Artificial Intelligence Models, Statistical Algorithms Proteins Protein Binding
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Machine learning in computational docking.

Artificial intelligence in medicine Feb 16, 2015
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...
Computational Biology Proteins Databases, Protein Data Interpretation, Statistical Quantum Theory Ligands Protein Conformation Humans Machine Learning Protein Binding
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PENG: a neural gas-based approach for pharmacophore elucidation. method design, validation, and virtual screening for novel ligands of LTA4H.

Journal of chemical information and modeling Feb 9, 2015
The pharmacophore concept is commonly employed in virtual screening for hit identification. A pharmacophore is generally defined as the three-dimensional arrangement of the structural and physicochemical features of a compound responsible for its aff...
Models, Molecular Benchmarking Ligands High-Throughput Screening Assays Prospective Studies Enzyme Inhibitors Humans Reproducibility of Results Neural Networks, Computer Crystallography, X-Ray Protein Binding Algorithms Thermodynamics Aminopeptidases Epoxide Hydrolases
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The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Nature communications Jan 27, 2015
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to...
Purine-Nucleoside Phosphorylase Thermodynamics Pyrrolidines Protein Multimerization Humans Machine Learning Algorithms Kinetics Time Factors Molecular Dynamics Simulation Protein Binding Ligands Cluster Analysis Pyrimidinones
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