AIMC Topic: Protein Conformation

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Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Bioinformatics (Oxford, England) Aug 14, 2015
MOTIVATION: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However...
Models, Statistical Evolution, Molecular Proteins Machine Learning Software Algorithms Protein Conformation Sequence Analysis, Protein Sequence Alignment
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LoopIng: a template-based tool for predicting the structure of protein loops.

Bioinformatics (Oxford, England) Aug 6, 2015
MOTIVATION: Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are n...
Machine Learning Proteins Software Protein Conformation Databases, Protein Models, Molecular
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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Protein Conformation Binding Sites Protein Multimerization Proteins Ligands Machine Learning Algorithms Molecular Docking Simulation Protein Binding Computational Biology
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Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Journal of chemical information and modeling Jul 10, 2015
The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust est...
Protein Kinase Inhibitors Chromosomes Cyclin-Dependent Kinases Bayes Theorem Protein Conformation Machine Learning Algorithms Protein Binding Support Vector Machine Decision Trees Models, Molecular
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Using support vector machines to improve elemental ion identification in macromolecular crystal structures.

Acta crystallographica. Section D, Biological crystallography Apr 25, 2015
In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific know...
Calcium Macromolecular Substances Manganese Crystallography, X-Ray Protein Conformation Models, Molecular Iron Nickel Metals Support Vector Machine Algorithms Zinc
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Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7).

Journal of chemical information and modeling Apr 8, 2015
Molecular docking, despite its undeniable usefulness in computer-aided drug design protocols and the increasing sophistication of tools used in the prediction of ligand-protein interaction energies, is still connected with a problem of effective resu...
Machine Learning Receptors, Serotonin Automation Protein Conformation Receptors, Adrenergic, beta-2 Algorithms Molecular Docking Simulation Ligands
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Machine learning in computational docking.

Artificial intelligence in medicine Feb 16, 2015
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...
Computational Biology Proteins Databases, Protein Humans Machine Learning Protein Conformation Data Interpretation, Statistical Protein Binding Quantum Theory Ligands
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Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation.

BMC systems biology Feb 6, 2015
BACKGROUND: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome...
Amino Acid Sequence Molecular Sequence Data Models, Molecular Computational Biology Protein Conformation Sequence Analysis, Protein Internet Support Vector Machine Nucleic Acid Conformation DNA-Binding Proteins
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PEGASUS: Prediction of MD-derived protein flexibility from sequence.

Protein science : a publication of the Protein Society Aug 1, 2025
Protein flexibility is essential to its biological function. However, experimental methods for its assessment, such as X-ray crystallography and nuclear magnetic resonance spectroscopy, are often limited by experimental variability and high cost, lea...
Protein Conformation Databases, Protein Molecular Dynamics Simulation Amino Acid Sequence Software Proteins
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Artificial intelligence and first-principle methods in protein redesign: A marriage of convenience?

Protein science : a publication of the Protein Society Aug 1, 2025
Since AlphaFold2's rise, many deep learning methods for protein design have emerged. Here, we validate widely used and recognized tools, compare them with first-principle methods, and explore their combinations, focusing on their effectiveness in pro...
Artificial Intelligence Deep Learning Protein Conformation Protein Engineering Protein Folding Proteins Databases, Protein Models, Molecular
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