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Amino Acid Sequence

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Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels.

Computers in biology and medicine
Glycosylation is a dynamic enzymatic process that attaches glycan to proteins or other organic molecules such as lipoproteins. Research has shown that such a process in ion channel proteins plays a fundamental role in modulating ion channel functions...

iT3SE-PX: Identification of Bacterial Type III Secreted Effectors Using PSSM Profiles and XGBoost Feature Selection.

Computational and mathematical methods in medicine
Identification of bacterial type III secreted effectors (T3SEs) has become a popular research topic in the field of bioinformatics due to its crucial role in understanding host-pathogen interaction and developing better therapeutic targets against th...

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

Bio Systems
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...

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.

Scientific reports
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...

Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts.

Journal of chemical information and modeling
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...

RAM-PGK: Prediction of Lysine Phosphoglycerylation Based on Residue Adjacency Matrix.

Genes
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...

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell
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...

AnOxPePred: using deep learning for the prediction of antioxidative properties of peptides.

Scientific reports
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 ...

ENNAACT is a novel tool which employs neural networks for anticancer activity classification for therapeutic peptides.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
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...