AIMC Topic: Carrier Proteins

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

eLife
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, ...

Structure-function properties of hypolipidemic peptides.

Journal of food biochemistry
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...

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
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...

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
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...

Deep-Learning Uncovers certain CCM Isoforms as Transcription Factors.

Frontiers in bioscience (Landmark edition)
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...

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

Briefings in bioinformatics
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...

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

Briefings in bioinformatics
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...

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

Briefings in bioinformatics
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...

Identification of hormone binding proteins based on machine learning methods.

Mathematical biosciences and engineering : MBE
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...

Estimating glucose requirements of an activated immune system in growing pigs.

Journal of animal science
Activated immune cells become obligate glucose utilizers, and a large i.v. lipopolysaccharide (LPS) dose causes insulin resistance and severe hypoglycemia. Therefore, study objectives were to quantify the amount of glucose needed to maintain euglycem...