AIMC Topic: Amino Acid Sequence

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FALCON2: a web server for high-quality prediction of protein tertiary structures.

BMC bioinformatics Sep 15, 2021
BACKGROUND: Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a ...
Computers Proteins Amino Acid Sequence Protein Conformation Neural Networks, Computer Software
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Rosetta:MSF:NN: Boosting performance of multi-state computational protein design with a neural network.

PloS one Aug 26, 2021
Rational protein design aims at the targeted modification of existing proteins. To reach this goal, software suites like Rosetta propose sequences to introduce the desired properties. Challenging design problems necessitate the representation of a pr...
Amino Acid Sequence Neural Networks, Computer Proteins Thermodynamics Algorithms Databases, Protein Epistasis, Genetic Computational Biology Mutation
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On the Potential of Machine Learning to Examine the Relationship Between Sequence, Structure, Dynamics and Function of Intrinsically Disordered Proteins.

Journal of molecular biology Aug 12, 2021
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as having no ...
Protein Folding Humans Machine Learning Animals Amino Acid Sequence Intrinsically Disordered Proteins Protein Conformation
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HemoNet: Predicting hemolytic activity of peptides with integrated feature learning.

Journal of bioinformatics and computational biology Aug 5, 2021
Quantifying the hemolytic activity of peptides is a crucial step in the discovery of novel therapeutic peptides. Computational methods are attractive in this domain due to their ability to guide wet-lab experimental discovery or screening of peptides...
Peptides Amino Acid Sequence Hemolysis Antimicrobial Peptides Humans Machine Learning
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DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning.

Journal of bioinformatics and computational biology Jul 21, 2021
DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA replication, slicing, repair, and transcription. Some DBPs are indispensable for understanding many types of human cancers (i.e. lung, breast, and liver...
Amino Acid Sequence Position-Specific Scoring Matrices Support Vector Machine Databases, Protein DNA-Binding Proteins Humans Algorithms Computational Biology
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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity Jul 16, 2021
CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...
Phosphotransferases Protein Binding Binding Sites Support Vector Machine Small Molecule Libraries Humans Vitamin D Animals Databases, Pharmaceutical Machine Learning Metabolic Networks and Pathways Neural Networks, Computer Molecular Docking Simulation Molecular Dynamics Simulation Algorithms Models, Molecular 25-Hydroxyvitamin D3 1-alpha-Hydroxylase Drug Design Amino Acid Sequence Reproducibility of Results Structure-Activity Relationship Enzyme Inhibitors
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Accurate prediction of protein structures and interactions using a three-track neural network.

Science (New York, N.Y.) Jul 15, 2021
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...
Neural Networks, Computer Protein Folding Proteins Crystallography, X-Ray Sphingosine N-Acyltransferase Models, Molecular Computer Simulation Multiprotein Complexes Databases, Protein Protein Conformation Amino Acid Sequence Protein Subunits Deep Learning Receptors, G-Protein-Coupled Cryoelectron Microscopy ADAM Proteins Membrane Proteins
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Highly accurate protein structure prediction with AlphaFold.

Nature Jul 15, 2021
Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this r...
Protein Conformation Protein Folding Sequence Alignment Databases, Protein Models, Molecular Amino Acid Sequence Neural Networks, Computer Reproducibility of Results Deep Learning Computational Biology Proteins
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PyPEF-An Integrated Framework for Data-Driven Protein Engineering.

Journal of chemical information and modeling Jul 14, 2021
Data-driven strategies are gaining increased attention in protein engineering due to recent advances in access to large experimental databanks of proteins, next-generation sequencing (NGS), high-throughput screening (HTS) methods, and the development...
Directed Molecular Evolution Protein Engineering Artificial Intelligence Machine Learning Amino Acid Sequence
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SidechainNet: An all-atom protein structure dataset for machine learning.

Proteins Jul 12, 2021
Despite recent advancements in deep learning methods for protein structure prediction and representation, little focus has been directed at the simultaneous inclusion and prediction of protein backbone and sidechain structure information. We present ...
Neural Networks, Computer Machine Learning Amino Acid Sequence Datasets as Topic Protein Conformation Software Proteins Amino Acids
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