AIMC Topic: Membrane Proteins

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CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning.

Nucleic acids research Jul 5, 2022
Recent advances in protein structural modelling have enabled the accurate prediction of the holo 3D structures of almost any protein, however protein function is intrinsically linked to the interactions it makes. While a number of computational appro...
Software Protein Conformation Binding Sites Protein Interaction Mapping Membrane Proteins Ligands Deep Learning
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PST-PRNA: prediction of RNA-binding sites using protein surface topography and deep learning.

Bioinformatics (Oxford, England) Apr 12, 2022
MOTIVATION: Protein-RNA interactions play essential roles in many biological processes, including pre-mRNA processing, post-transcriptional gene regulation and RNA degradation. Accurate identification of binding sites on RNA-binding proteins (RBPs) i...
RNA Binding Sites RNA-Binding Proteins Membrane Proteins Protein Binding Computational Biology Deep Learning
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Predicting protein-membrane interfaces of peripheral membrane proteins using ensemble machine learning.

Briefings in bioinformatics Mar 10, 2022
Abnormal protein-membrane attachment is involved in deregulated cellular pathways and in disease. Therefore, the possibility to modulate protein-membrane interactions represents a new promising therapeutic strategy for peripheral membrane proteins th...
Machine Learning Algorithms Membrane Proteins Amino Acids
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Accurate flexible refinement for atomic-level protein structure using cryo-EM density maps and deep learning.

Briefings in bioinformatics Mar 10, 2022
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...
Protein Conformation Cryoelectron Microscopy Deep Learning Membrane Proteins Models, Molecular
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A deep learning-based approach to model anomalous diffusion of membrane proteins: the case of the nicotinic acetylcholine receptor.

Briefings in bioinformatics Jan 17, 2022
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...
Deep Learning Membrane Proteins Receptors, Nicotinic Diffusion Cell Membrane
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Computational Approaches for Investigating Disease-causing Mutations in Membrane Proteins: Database Development, Analysis and Prediction.

Current topics in medicinal chemistry Jan 1, 2022
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...
Protein Conformation, alpha-Helical Databases, Protein Mutation Humans Machine Learning Computational Biology Membrane Proteins Databases, Factual
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Precise estimation of residue relative solvent accessible area from Cα atom distance matrix using a deep learning method.

Bioinformatics (Oxford, England) Dec 22, 2021
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...
Deep Learning Solvents Membrane Proteins
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PolarProtPred: predicting apical and basolateral localization of transmembrane proteins using putative short linear motifs and deep learning.

Bioinformatics (Oxford, England) Dec 7, 2021
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...
Membrane Proteins Humans Epithelial Cells COVID-19 Cell Membrane Deep Learning
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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 Jan 1, 2021
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...
ROC Curve Humans WAP Four-Disulfide Core Domain Protein 2 Membrane Proteins Early Detection of Cancer L-Lactate Dehydrogenase Adult Ovarian Neoplasms Diagnosis, Differential Machine Learning Neutrophils Biomarkers, Tumor CA-125 Antigen Lymphocytes Middle Aged Leukocyte Count Female
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Anti-inflammatory and antibacterial activities of P. petiolosa (Christ) Ching ethyl acetate extract against S. aureus in mice.

Pakistan journal of pharmaceutical sciences Sep 1, 2020
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...
Solvents Membrane Proteins Bacterial Load Pneumonia, Staphylococcal Staphylococcus aureus Animals Anti-Bacterial Agents Anti-Inflammatory Agents Heme Oxygenase-1 Polypodiaceae Mice, Inbred BALB C Lung Tumor Necrosis Factor-alpha Acetates Disease Models, Animal Plant Leaves Plant Extracts Inflammation Mediators Nitric Oxide Synthase Type II
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