AIMC Topic: Protein Domains

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Neural Networks in the Design of Molecules with Affinity to Selected Protein Domains.

International journal of molecular sciences Jan 16, 2023
Drug design with machine learning support can speed up new drug discoveries. While current databases of known compounds are smaller in magnitude (approximately 108), the number of small drug-like molecules is estimated to be between 1023 and 1060. Th...
Neural Networks, Computer Artificial Intelligence Drug Design Molecular Docking Simulation Bayes Theorem Protein Domains
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Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Science (New York, N.Y.) Dec 8, 2022
Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations ...
Protein Domains T-Lymphocytes, Cytotoxic Humans Peptide Library Signal Transduction Phenotype Receptors, Chimeric Antigen Machine Learning
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Learning Proteome Domain Folding Using LSTMs in an Empirical Kernel Space.

Journal of molecular biology Jun 15, 2022
The recognition of protein structural folds is the starting point for protein function inference and for many structural prediction tools. We previously introduced the idea of using empirical comparisons to create a data-augmented feature space calle...
Protein Folding Algorithms Neural Networks, Computer Proteome Protein Domains
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Protein sequence design with a learned potential.

Nature communications Feb 8, 2022
The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network mo...
Computer Simulation Deep Learning Amino Acid Sequence Crystallography, X-Ray Protein Engineering Models, Molecular Protein Domains Protein Folding
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Protein Design with Deep Learning.

International journal of molecular sciences Oct 29, 2021
Computational Protein Design (CPD) has produced impressive results for engineering new proteins, resulting in a wide variety of applications. In the past few years, various efforts have aimed at replacing or improving existing design methods using De...
Protein Engineering Computational Biology Proteins Protein Domains Deep Learning
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iMPT-FDNPL: Identification of Membrane Protein Types with Functional Domains and a Natural Language Processing Approach.

Computational and mathematical methods in medicine Oct 11, 2021
Membrane protein is an important kind of proteins. It plays essential roles in several cellular processes. Based on the intramolecular arrangements and positions in a cell, membrane proteins can be divided into several types. It is reported that the ...
Support Vector Machine Databases, Protein Protein Domains Computational Biology Humans Natural Language Processing Membrane Proteins Algorithms
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MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

Structure (London, England : 1993) Oct 5, 2021
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
Tetrahydrofolate Dehydrogenase Crystallography, X-Ray Trimethoprim Proteins Databases, Protein Protein Domains Ligands Models, Molecular Protein Binding Computational Biology Humans SARS-CoV-2 Drug Design Pandemics COVID-19 Machine Learning
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A deep-learning framework for multi-level peptide-protein interaction prediction.

Nature communications Sep 15, 2021
Peptide-protein interactions are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. Recently, a number of computational methods have been developed to predict peptide...
Protein Binding Computational Biology Models, Molecular Protein Domains Proteins Peptides Deep Learning Algorithms Reproducibility of Results Binding Sites
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Prediction of Protein Solubility Based on Sequence Feature Fusion and DDcCNN.

Interdisciplinary sciences, computational life sciences Jul 8, 2021
BACKGROUND: Prediction of protein solubility is an indispensable prerequisite for pharmaceutical research and production. The general and specific objective of this work is to design a new model for predicting protein solubility by using protein sequ...
Protein Domains Neural Networks, Computer Amino Acid Sequence Proteins Solubility
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TopDomain: Exhaustive Protein Domain Boundary Metaprediction Combining Multisource Information and Deep Learning.

Journal of chemical theory and computation Jun 23, 2021
Protein domains are independent, functional, and stable structural units of proteins. Accurate protein domain boundary prediction plays an important role in understanding protein structure and evolution, as well as for protein structure prediction. C...
Proteins Algorithms Deep Learning Protein Domains Protein Conformation Computational Biology
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