AIMC Topic: Amino Acid Sequence

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A protein folding robot driven by a self-taught agent.

Bio Systems Dec 29, 2020
This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to sol...
Systems Analysis Coronavirus Hemagglutinins, Viral Protein Conformation Viral Proteins Protein Folding Viral Fusion Proteins Machine Learning Algorithms Computer Simulation Models, Molecular Amino Acid Sequence Systems Biology Robotics Humans Neural Networks, Computer
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Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.

Scientific reports Dec 23, 2020
The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goal of this study was to use artificial intellige...
Immunogenicity, Vaccine Alleles Humans Amino Acid Sequence Haplotypes COVID-19 Vaccines Spike Glycoprotein, Coronavirus Proteomics COVID-19 HLA Antigens Algorithms Machine Learning Drug Evaluation, Preclinical Software SARS-CoV-2 Pandemics Proteome Epitopes, T-Lymphocyte Mutation
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Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts.

Journal of chemical information and modeling Dec 21, 2020
Predicting compound-protein affinity is beneficial for accelerating drug discovery. Doing so without the often-unavailable structure data is gaining interest. However, recent progress in structure-free affinity prediction, made by machine learning, f...
Deep Learning Proteins Amino Acid Sequence Neural Networks, Computer Machine Learning
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RAM-PGK: Prediction of Lysine Phosphoglycerylation Based on Residue Adjacency Matrix.

Genes Dec 20, 2020
BACKGROUND: Post-translational modification (PTM) is a biological process that is associated with the modification of proteome, which results in the alteration of normal cell biology and pathogenesis. There have been numerous PTM reports in recent ye...
Support Vector Machine Protein Processing, Post-Translational Amino Acid Sequence Glyceric Acids Software Datasets as Topic Algorithms Lysine ROC Curve
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Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell Dec 16, 2020
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...
Humans Serotonin Photons Amygdala Serotonin Plasma Membrane Transport Proteins Behavior, Animal Binding Sites Directed Molecular Evolution Mice, Inbred C57BL Kinetics Animals Amino Acid Sequence Machine Learning Protein Binding Wakefulness Linear Models Algorithms Mice Sleep HEK293 Cells Brain
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AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides.

Scientific reports Dec 8, 2020
Dietary antioxidants are an important preservative in food and have been suggested to help in disease prevention. With consumer demands for less synthetic and safer additives in food products, the food industry is searching for antioxidants that can ...
Deep Learning Antioxidants Food Preservatives Amino Acid Sequence Humans Software Peptides
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ENNAACT is a novel tool which employs neural networks for anticancer activity classification for therapeutic peptides.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Nov 27, 2020
The prevalence of cancer as a threat to human life, responsible for 9.6 million deaths worldwide in 2018, motivates the search for new anticancer agents. While many options are currently available for treatment, these are often expensive and impact t...
Peptides Antineoplastic Agents Deep Learning Humans Reproducibility of Results Structure-Activity Relationship Animals Amino Acid Sequence Neoplasms
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DeepPSP: A Global-Local Information-Based Deep Neural Network for the Prediction of Protein Phosphorylation Sites.

Journal of proteome research Nov 26, 2020
Identification of phosphorylation sites is an important step in the function study and drug design of proteins. In recent years, there have been increasing applications of the computational method in the identification of phosphorylation sites becaus...
Computational Biology Proteins Neural Networks, Computer Phosphorylation Amino Acid Sequence
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PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.

Computational and mathematical methods in medicine Nov 20, 2020
Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its...
Support Vector Machine Algorithms Humans Amyloidogenic Proteins Diabetes Mellitus, Type 2 Amino Acids Neural Networks, Computer Alzheimer Disease Computational Biology Amino Acid Sequence Machine Learning Mathematical Concepts
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Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning.

Cell systems Nov 18, 2020
Machine learning can infer how protein sequence maps to function without requiring a detailed understanding of the underlying physical or biological mechanisms. It is challenging to apply existing supervised learning frameworks to large-scale experim...
Machine Learning Proteins Amino Acid Sequence
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