AIMC Topic: Membrane Proteins

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Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning.

Briefings in bioinformatics
With the rapid progress of deep learning in cryo-electron microscopy and protein structure prediction, improving the accuracy of the protein structure model by using a density map and predicted contact/distance map through deep learning has become an...

A deep learning-based approach to model anomalous diffusion of membrane proteins: the case of the nicotinic acetylcholine receptor.

Briefings in bioinformatics
We present a concatenated deep-learning multiple neural network system for the analysis of single-molecule trajectories. We apply this machine learning-based analysis to characterize the translational diffusion of the nicotinic acetylcholine receptor...

Computational Approaches for Investigating Disease-causing Mutations in Membrane Proteins: Database Development, Analysis and Prediction.

Current topics in medicinal chemistry
Membrane proteins (MPs) play an essential role in a broad range of cellular functions, serving as transporters, enzymes, receptors, and communicators, and about ~60% of membrane proteins are primarily used as drug targets. These proteins adopt either...

Precise estimation of residue relative solvent accessible area from Cα atom distance matrix using a deep learning method.

Bioinformatics (Oxford, England)
MOTIVATION: The solvent accessible surface is an essential structural property measure related to the protein structure and protein function. Relative solvent accessible area (RSA) is a standard measure to describe the degree of residue exposure in t...

PolarProtPred: predicting apical and basolateral localization of transmembrane proteins using putative short linear motifs and deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Cell polarity refers to the asymmetric organization of cellular components in various cells. Epithelial cells are the best-known examples of polarized cells, featuring apical and basolateral membrane domains. Mounting evidence suggests th...

Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.

Cancer control : journal of the Moffitt Cancer Center
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classifie...

Anti-inflammatory and antibacterial activities of P. petiolosa (Christ) Ching ethyl acetate extract against S. aureus in mice.

Pakistan journal of pharmaceutical sciences
P. petiolosa as a typical Chinese herbal medicine has been generally utilized as Chinese native medicine formulation for treatment of chronic bronchitis, bronchial asthma and pneumoconiosis. The objective of this study was to evaluate the anti-inflam...

Identifying short disorder-to-order binding regions in disordered proteins with a deep convolutional neural network method.

Journal of bioinformatics and computational biology
Molecular recognition features (MoRFs) are key functional regions of intrinsically disordered proteins (IDPs), which play important roles in the molecular interaction network of cells and are implicated in many serious human diseases. Identifying MoR...

New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes.

Combinatorial chemistry & high throughput screening
BACKGROUND: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To date, many genes have been discovered to be related to rhinovirus infection. However, the pathogenic mechanism of rhinovirus is difficu...