AIMC Topic: Protein Binding

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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 Epitopes Amino Acid Sequence Molecular Sequence Data Neural Networks, Computer Algorithms Peptides ROC Curve Protein Binding Support Vector Machine Databases, Protein Area Under Curve Humans
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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 Binding Protein Conformation Protein Kinase Inhibitors Chromosomes Support Vector Machine Cyclin-Dependent Kinases Decision Trees Models, Molecular 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...
Humans Neural Networks, Computer Molecular Structure Quantum Theory Ligands Cyclooxygenase 2 Inhibitors Algorithms Molecular Docking Simulation Protein Binding Structure-Activity Relationship Cyclooxygenase 2 Lipoxygenase Inhibitors Substrate Specificity Datasets as Topic Catalytic Domain Arachidonate 5-Lipoxygenase
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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...
Drug Design Ligands Humans Drug Discovery Binding Sites 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 ...
Markov Chains Protein Binding Immunity, Cellular Support Vector Machine Histocompatibility Antigens Class I Algorithms T-Lymphocytes Peptides Humans
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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 Binding Sites Humans 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...
Humans Benchmarking Ligands High-Throughput Screening Assays Enzyme Inhibitors Crystallography, X-Ray Reproducibility of Results Neural Networks, Computer Thermodynamics Protein Binding Epoxide Hydrolases Aminopeptidases Algorithms Prospective Studies Models, Molecular
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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 Humans Thermodynamics Pyrrolidines Machine Learning Kinetics Algorithms Protein Multimerization Molecular Dynamics Simulation Time Factors Ligands Protein Binding Pyrimidinones Cluster Analysis
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A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach.

Journal of computer-aided molecular design Dec 20, 2014
The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast pr...
Trypsin Carbonic Anhydrases Models, Biological Ligands HIV Protease Humans Artificial Intelligence Computer-Aided Design Drug Design Protein Binding Proteins Databases, Protein
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