AIMC Topic: Carrier Proteins

Clear Filters Showing 21 to 30 of 32 articles

Linking of single-molecule experiments with molecular dynamics simulations by machine learning.

eLife May 3, 2018
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide data, such as donor-acceptor distances, whereas the latter give atomistic information, ...
Machine Learning Carrier Proteins Single Molecule Imaging Protein Folding Molecular Dynamics Simulation Fluorescence Resonance Energy Transfer Protein Conformation
View on PubMed DOI

Structure-function properties of hypolipidemic peptides.

Journal of food biochemistry Mar 8, 2018
This review addresses the structure-function properties of hypolipidemic peptides. The cholesterol-lowering peptide (lactostatin: IIAEK) operates via a new regulatory pathway in the calcium-channel-related mitogen-activated protein kinase (MAPK) sign...
Globulins Atherosclerosis Anti-Obesity Agents Oligopeptides Amino Acid Sequence Hypolipidemic Agents Structure-Activity Relationship Humans Hyperlipidemias Seed Storage Proteins Soybean Proteins Apolipoprotein A-I Carrier Proteins Antigens, Plant Membrane Glycoproteins
View on PubMed DOI

Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains.

Journal of theoretical biology Feb 22, 2018
The receptor-associated protein (RAP) is an inhibitor of endocytic receptors that belong to the lipoprotein receptor gene family. In this study, a computational approach was tried to find the evolutionarily related fold of the RAP proteins. Through t...
Databases, Protein Structure-Activity Relationship Models, Molecular Protein Conformation Support Vector Machine Computational Biology Carrier Proteins Evolution, Molecular
View on PubMed DOI

Development of a Support Vector Machine-Based System to Predict Whether a Compound Is a Substrate of a Given Drug Transporter Using Its Chemical Structure.

Journal of pharmaceutical sciences Jun 1, 2016
The aim of this study was to develop an in silico prediction system to assess which of 7 categories of drug transporters (organic anion transporting polypeptide [OATP] 1B1/1B3, multidrug resistance-associated protein [MRP] 2/3/4, organic anion transp...
Substrate Specificity Multidrug Resistance-Associated Proteins Algorithms Computer Simulation Support Vector Machine Pharmaceutical Preparations Biological Transport Carrier Proteins Molecular Weight Lipids Predictive Value of Tests
View on PubMed DOI

A Bayesian Optimization-Based Hybrid Deep Prediction Method for Zinc-Binding Protein Interaction Sites.

Journal of chemical information and modeling Jul 14, 2025
The binding of zinc ions to proteins plays a crucial role in normal physiological functions and life activities of organisms. To enhance the prediction accuracy of zinc-binding protein interaction sites, the paper proposes a novel hybrid deep predict...
Computational Biology Carrier Proteins Bayes Theorem Binding Sites Zinc Protein Binding
View on PubMed DOI

Deep-Learning Uncovers certain CCM Isoforms as Transcription Factors.

Frontiers in bioscience (Landmark edition) Feb 21, 2024
BACKGROUND: Cerebral Cavernous Malformations (CCMs) are brain vascular abnormalities associated with an increased risk of hemorrhagic strokes. Familial CCMs result from autosomal dominant inheritance involving three genes: (), (), and (). CCM1 and...
Protein Isoforms Humans Receptors, Progesterone Deep Learning Proto-Oncogene Proteins Hemangioma, Cavernous, Central Nervous System Transcription Factors Carrier Proteins
View on PubMed DOI

circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier.

Briefings in bioinformatics Jan 17, 2022
Circular RNAs (circRNAs) generally bind to RNA-binding proteins (RBPs) to play an important role in the regulation of autoimmune diseases. Thus, it is crucial to study the binding sites of RBPs on circRNAs. Although many methods, including traditiona...
Deep Learning Binding Sites Humans Computational Biology RNA, Circular Carrier Proteins
View on PubMed DOI

Improved protein contact prediction using dimensional hybrid residual networks and singularity enhanced loss function.

Briefings in bioinformatics Nov 5, 2021
Deep residual learning has shown great success in protein contact prediction. In this study, a new deep residual learning-based protein contact prediction model was developed. Comparing with previous models, a new type of residual block hybridizing 1...
Carrier Proteins Proteins Protein Interaction Mapping Software Reproducibility of Results Deep Learning Protein Binding Computational Biology
View on PubMed DOI

Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution.

Briefings in bioinformatics Nov 5, 2021
Major histocompatibility complex (MHC) possesses important research value in the treatment of complex human diseases. A plethora of computational tools has been developed to predict MHC class I binders. Here, we comprehensively reviewed 27 up-to-date...
Neural Networks, Computer Machine Learning Software ROC Curve Protein Binding Computational Biology Carrier Proteins Databases, Factual Reproducibility of Results Deep Learning Binding Sites Web Browser Epitopes Histocompatibility Antigens Class I Amino Acid Sequence
View on PubMed DOI

Identification of hormone binding proteins based on machine learning methods.

Mathematical biosciences and engineering : MBE Mar 22, 2019
The soluble carrier hormone binding protein (HBP) plays an important role in the growth of human and other animals. HBP can also selectively and non-covalently interact with hormone. Therefore, accurate identification of HBP is an important prerequis...
Analysis of Variance Databases, Protein Amino Acids Hormones Computational Biology Machine Learning Support Vector Machine Software Carrier Proteins Algorithms Humans Animals Computer Simulation Reproducibility of Results Peptides
View on PubMed DOI
Popular Topics
Recent Journals