AI Medical Compendium Topic:
Databases, Protein

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Improved prediction of drug-target interactions based on ensemble learning with fuzzy local ternary pattern.

Frontiers in bioscience (Landmark edition)
: The prediction of interacting drug-target pairs plays an essential role in the field of drug repurposing, and drug discovery. Although biotechnology and chemical technology have made extraordinary progress, the process of dose-response experiments ...

DeepBL: a deep learning-based approach for in silico discovery of beta-lactamases.

Briefings in bioinformatics
Beta-lactamases (BLs) are enzymes localized in the periplasmic space of bacterial pathogens, where they confer resistance to beta-lactam antibiotics. Experimental identification of BLs is costly yet crucial to understand beta-lactam resistance mechan...

Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method.

Briefings in bioinformatics
As a newly discovered protein posttranslational modification, histone lysine crotonylation (Kcr) involved in cellular regulation and human diseases. Various proteomics technologies have been developed to detect Kcr sites. However, experimental approa...

The breakthrough in protein structure prediction.

The Biochemical journal
Proteins are the essential agents of all living systems. Even though they are synthesized as linear chains of amino acids, they must assume specific three-dimensional structures in order to manifest their biological activity. These structures are ful...

State-of-the-art web services for de novo protein structure prediction.

Briefings in bioinformatics
Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent...

MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm.

Briefings in bioinformatics
Deep learning is an important branch of artificial intelligence that has been successfully applied into medicine and two-dimensional ligand design. The three-dimensional (3D) ligand generation in the 3D pocket of protein target is an interesting and ...

AntiCP 2.0: an updated model for predicting anticancer peptides.

Briefings in bioinformatics
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides...

Using deep neural networks and biological subwords to detect protein S-sulfenylation sites.

Briefings in bioinformatics
Protein S-sulfenylation is one kind of crucial post-translational modifications (PTMs) in which the hydroxyl group covalently binds to the thiol of cysteine. Some recent studies have shown that this modification plays an important role in signaling t...

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.

Briefings in bioinformatics
Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational met...