AIMC Topic: Proteins

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Explainable deep drug-target representations for binding affinity prediction.

BMC bioinformatics Jun 17, 2022
BACKGROUND: Several computational advances have been achieved in the drug discovery field, promoting the identification of novel drug-target interactions and new leads. However, most of these methodologies have been overlooking the importance of prov...
Neural Networks, Computer Proteins Binding Sites Reproducibility of Results Plant Extracts
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Predicting Protein-Ligand Docking Structure with Graph Neural Network.

Journal of chemical information and modeling Jun 14, 2022
Modern day drug discovery is extremely expensive and time consuming. Although computational approaches help accelerate and decrease the cost of drug discovery, existing computational software packages for docking-based drug discovery suffer from both...
Ligands Neural Networks, Computer Molecular Docking Simulation Protein Binding Proteins
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Screening membraneless organelle participants with machine-learning models that integrate multimodal features.

Proceedings of the National Academy of Sciences of the United States of America Jun 10, 2022
Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to th...
Biomolecular Condensates Internet Use Proteome Proteins Phosphorylation Organelles Humans Machine Learning
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Sfcnn: a novel scoring function based on 3D convolutional neural network for accurate and stable protein-ligand affinity prediction.

BMC bioinformatics Jun 8, 2022
BACKGROUND: Computer-aided drug design provides an effective method of identifying lead compounds. However, success rates are significantly bottlenecked by the lack of accurate and reliable scoring functions needed to evaluate binding affinities of p...
Neural Networks, Computer Proteins Ligands Machine Learning Protein Binding
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Sequence-assignment validation in cryo-EM models with checkMySequence.

Acta crystallographica. Section D, Structural biology Jun 7, 2022
The availability of new artificial intelligence-based protein-structure-prediction tools has radically changed the way that cryo-EM maps are interpreted, but it has not eliminated the challenges of map interpretation faced by a microscopist. Models w...
Humans Artificial Intelligence Models, Molecular SARS-CoV-2 RNA, Viral Proteins COVID-19 Cryoelectron Microscopy
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OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets.

BMC bioinformatics Jun 7, 2022
BACKGROUND: Due to their diverse bioactivity, natural product (NP)s have been developed as commercial products in the pharmaceutical, food and cosmetic sectors as natural compound (NC)s and in the form of extracts. Following administration, NCs typic...
Machine Learning Diabetes Mellitus, Type 2 Humans Deep Learning Proteins Pharmaceutical Preparations
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Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images.

Analytical and bioanalytical chemistry Jun 4, 2022
Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited cryst...
Image Processing, Computer-Assisted Proteins Machine Learning Algorithms Crystallization Neural Networks, Computer
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Sparse group selection and analysis of function-related residue for protein-state recognition.

Journal of computational chemistry Jun 3, 2022
Machine learning methods have helped to advance wide range of scientific and technological field in recent years, including computational chemistry. As the chemical systems could become complex with high dimension, feature selection could be critical...
Algorithms Machine Learning Proteins
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EPGAT: Gene Essentiality Prediction With Graph Attention Networks.

IEEE/ACM transactions on computational biology and bioinformatics Jun 3, 2022
Identifying essential genes and proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and the correla...
Neural Networks, Computer Humans Machine Learning Proteins Genes, Essential Algorithms Protein Interaction Maps
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Neural Network and Random Forest Models in Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Jun 3, 2022
Over the past decade, the demand for automated protein function prediction has increased due to the volume of newly sequenced proteins. In this paper, we address the function prediction task by developing an ensemble system automatically assigning Ge...
Software Proteins Neural Networks, Computer Databases, Protein Sequence Alignment
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