AI Medical Compendium Topic:
Protein Binding

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Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques.

BMC bioinformatics Dec 31, 2018
BACKGROUND: Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within the proper range. Plasma prot...
Blood Proteins Pharmaceutical Preparations Peptides, Cyclic Small Molecule Libraries Computer Simulation Protein Binding Models, Theoretical Humans Machine Learning
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Gene ontology improves template selection in comparative protein docking.

Proteins Dec 27, 2018
Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and a...
Structural Homology, Protein Proteins Databases, Protein Models, Molecular Protein Interaction Maps Protein Conformation Binding Sites Humans Protein Binding Protein Interaction Mapping Gene Ontology Computational Biology Software Molecular Docking Simulation
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Toward Achieving Efficient and Accurate Ligand-Protein Unbinding with Deep Learning and Molecular Dynamics through RAVE.

Journal of chemical theory and computation Dec 24, 2018
In this work, we demonstrate how to leverage our recent iterative deep learning-all atom molecular dynamics (MD) technique "Reweighted autoencoded variational Bayes for enhanced sampling (RAVE)" (Ribeiro, Bravo, Wang, Tiwary, J. Chem. Phys. 2018, 149...
Proteins Molecular Dynamics Simulation Ligands Thermodynamics Deep Learning Protein Binding
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An SVM-based method for assessment of transcription factor-DNA complex models.

BMC bioinformatics Dec 21, 2018
BACKGROUND: Atomic details of protein-DNA complexes can provide insightful information for better understanding of the function and binding specificity of DNA binding proteins. In addition to experimental methods for solving protein-DNA complex struc...
Protein Binding Transcription Factors Algorithms Support Vector Machine DNA Models, Molecular
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SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.

PLoS computational biology Dec 11, 2018
LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational ...
Databases, Nucleic Acid RNA Processing, Post-Transcriptional Protein Binding Amino Acid Sequence Computational Biology RNA, Long Noncoding Base Sequence Humans RNA-Binding Proteins Databases, Protein Machine Learning Algorithms
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Discovering de novo peptide substrates for enzymes using machine learning.

Nature communications Dec 7, 2018
The discovery of peptide substrates for enzymes with exclusive, selective activities is a central goal in chemical biology. In this paper, we develop a hybrid computational and biochemical method to rapidly optimize peptides for specific, orthogonal ...
Bayes Theorem Bacterial Proteins Amino Acid Sequence Substrate Specificity Transferases (Other Substituted Phosphate Groups) Peptides Protein Binding Recombinant Proteins Machine Learning
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iSEE: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations.

Proteins Dec 3, 2018
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning-based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using...
Computational Biology Evolution, Molecular Proteins Machine Learning Protein Binding Tumor Suppressor Protein p53 Thermodynamics Binding, Competitive Proto-Oncogene Proteins c-mdm2 Models, Molecular Mutation Protein Domains
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Prediction of drug-target interaction by integrating diverse heterogeneous information source with multiple kernel learning and clustering methods.

Computational biology and chemistry Dec 2, 2018
BACKGROUND: Identification of potential drug-target interaction pairs is very important for pharmaceutical innovation and drug discovery. Numerous machine learning-based and network-based algorithms have been developed for predicting drug-target inte...
Protein Binding Computational Biology Cluster Analysis Machine Learning Algorithms Neoplasms Molecular Targeted Therapy Humans
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Learning protein binding affinity using privileged information.

BMC bioinformatics Nov 15, 2018
BACKGROUND: Determining protein-protein interactions and their binding affinity are important in understanding cellular biological processes, discovery and design of novel therapeutics, protein engineering, and mutagenesis studies. Due to the time an...
Support Vector Machine ROC Curve Machine Learning Proteins Ligands Protein Binding Amino Acid Sequence Algorithms Computational Biology Reproducibility of Results
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Application of molecular docking and PSO-SVR intelligent approaches in antimalarial activity prediction of enantiomeric cycloguanil analogues.

SAR and QSAR in environmental research Nov 1, 2018
A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the ...
Tetrahydrofolate Dehydrogenase Plasmodium falciparum Reproducibility of Results Folic Acid Antagonists Enzyme Inhibitors Triazines Molecular Structure Machine Learning Molecular Docking Simulation Quantitative Structure-Activity Relationship Substrate Specificity Antimalarials Algorithms Proguanil Protein Binding Stereoisomerism
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