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Bacterial Proteins

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Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila.

PloS one
Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several ma...

Discovering de novo peptide substrates for enzymes using machine learning.

Nature communications
The discovery of peptide substrates for enzymes with exclusive, selective activities is a central goal in chemical biology. In this paper, we develop a hybrid computational and biochemical method to rapidly optimize peptides for specific, orthogonal ...

CbpM and CbpG of Streptococcus Pneumoniae Elicit a High Protection in Mice Challenged with a Serotype 19F Pneumococcus.

Iranian journal of allergy, asthma, and immunology
Among many pneumococcal antigens, choline-binding proteins (CPBs) display a high immunogenicity in animal models. This study aims to determine the immunogenicity of CbpM, CbpG and CbpL proteins of Streptococcus pneumoniae in a mice model. The genes w...

Discrimination of contagious and environmental strains of Streptococcus uberis in dairy herds by means of mass spectrometry and machine-learning.

Scientific reports
Streptococcus uberis is one of the most common pathogens of clinical mastitis in the dairy industry. Knowledge of pathogen transmission route is essential for the selection of the most suitable intervention. Here we show that spectral profiles acquir...

Rapid Rule Out of Culture-Negative Bloodstream Infections by Use of a Novel Approach to Universal Detection of Bacteria and Fungi.

The journal of applied laboratory medicine
BACKGROUND: Currently it can take up to 5 days to rule out bloodstream infection. With the low yield of blood cultures (approximately 10%), a significant number of patients are potentially exposed to inappropriate therapy that can lead to adverse eve...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...

Large-scale protein function prediction using heterogeneous ensembles.

F1000Research
Heterogeneous ensembles are an effective approach in scenarios where the ideal data type and/or individual predictor are unclear for a given problem. These ensembles have shown promise for protein function prediction (PFP), but their ability to impro...

BlaPred: Predicting and classifying β-lactamase using a 3-tier prediction system via Chou's general PseAAC.

Journal of theoretical biology
Antibiotics of β-lactam class account for nearly half of the global antibiotic use. The β-lactamase enzyme is a major element of the bacterial arsenals to escape the lethal effect of β-lactam antibiotics. Different variants of β-lactamases have evolv...

Functional Annotation of Proteins Encoded by the Minimal Bacterial Genome Based on Secondary Structure Element Alignment.

Journal of proteome research
In synthetic biology, one of the key focuses is building a minimal artificial cell which can provide basic chassis for functional study. Recently, the J. Craig Venter Institute published the latest version of the minimal bacterial genome JCVI-syn3.0,...

Predicting lysine-malonylation sites of proteins using sequence and predicted structural features.

Journal of computational chemistry
Malonylation is a recently discovered post-translational modification (PTM) in which a malonyl group attaches to a lysine (K) amino acid residue of a protein. In this work, a novel machine learning model, SPRINT-Mal, is developed to predict malonylat...