AI Medical Compendium Topic:
Protein Binding

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An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to ...
Reproducibility of Results Protein Binding Computational Biology Signal Transduction Humans Algorithms Phosphotyrosine Databases, Protein Workflow Supervised Machine Learning Protein Interaction Mapping Web Browser Protein Interaction Domains and Motifs src Homology Domains
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Continuous Hemodiafiltration with an AN69ST Hemofilter (AN69ST-CHDF) as FGF-23-Lowering Therapy.

Clinical laboratory Dec 1, 2016
BACKGROUND: Recent studies have shown that fibroblast growth factor-23 (FGF-23) is elevated not only in chronic kidney disease (CKD), but also in acute illnesses such as acute kidney injury, septic shock, and acute heart failure. FGF-23 would be not ...
Protein Binding Membranes, Artificial Aged Treatment Outcome Hemodiafiltration Equipment Design Humans Adsorption Male Acute Disease Biomarkers Fibroblast Growth Factor-23 Middle Aged Down-Regulation Female Fibroblast Growth Factors Time Factors Surface Properties Acrylic Resins Acrylonitrile
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Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase.

Molecular bioSystems Nov 15, 2016
N-Myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking substrate proteins to membrane locations, stabilization and protein-protei...
Trypanocidal Agents Acyltransferases Workflow Molecular Dynamics Simulation Enzyme Inhibitors Catalytic Domain Datasets as Topic Machine Learning Parasitic Sensitivity Tests Algorithms Quantitative Structure-Activity Relationship Molecular Docking Simulation Binding Sites Protein Binding
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Convolutional neural network architectures for predicting DNA-protein binding.

Bioinformatics (Oxford, England) Jun 15, 2016
MOTIVATION: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth...
Neural Networks, Computer Algorithms Protein Binding Proteins DNA
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Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Molecular bioSystems Mar 1, 2016
Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved i...
Machine Learning Reproducibility of Results ROC Curve Probability Protein Interaction Mapping Protein Binding Computational Biology Databases, Protein Sample Size
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Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or...
Support Vector Machine Glucose Molecular Dynamics Simulation Serum Albumin Binding Sites Humans Protein Binding Computational Biology
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A novel machine learning method for cytokine-receptor interaction prediction.

Combinatorial chemistry & high throughput screening Jan 1, 2016
Most essential functions are associated with various protein-protein interactions, particularly the cytokine-receptor interaction. Knowledge of the heterogeneous network of cytokine- receptor interactions provides insights into various human physiolo...
Receptors, Cytokine Protein Binding Databases, Protein High-Throughput Screening Assays Humans Machine Learning Cytokines
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A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Molecular bioSystems Dec 1, 2015
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize ...
Protein Interaction Mapping High-Throughput Screening Assays Molecular Conformation Binding Sites Gene Regulatory Networks Protein Binding Computational Biology Gene Expression Regulation, Neoplastic Machine Learning Antineoplastic Agents, Phytogenic Drug Discovery Receptors, CXCR4 Cell Line, Tumor Models, Molecular ROC Curve Humans Mouth Neoplasms
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Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.

EBioMedicine Nov 1, 2015
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes i...
Disease Resistance Mycobacterium Humans Female Disease Susceptibility Transcriptome Binding Sites Transcription Factors Protein Binding Young Adult Leukocyte Count Monocytes Tuberculosis Interferons Signal Transduction Adult Lymphocytes Male Gene Expression Profiling
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Predicting selective liver X receptor β agonists using multiple machine learning methods.

Molecular bioSystems May 1, 2015
Liver X receptor (LXR) α and β are cholesterol sensors; they respond to excess cholesterol and stimulate reverse cholesterol transport. Activating LXRs represents a promising therapeutic option for dyslipidemia. However, activating LXRα may cause unw...
Humans Machine Learning Algorithms Reproducibility of Results Drug Discovery Protein Binding Models, Theoretical Liver X Receptors Orphan Nuclear Receptors
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