Microcin C (McC), an inhibitor of the growth of enteric bacteria, consists of a heptapeptide with a modified AMP residue attached to the backbone of the C-terminal aspartate through an N-acyl phosphamidate bond. Here we identify maturation intermediates produced by cells lacking individual mcc McC biosynthesis genes. We show that the products of the mccD and mccE genes are required for attachment of a 3-aminopropyl group to the phosphate of McC and that this group increases the potency of inhibition of the McC target, aspartyl-tRNA synthetase.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655510PMC
http://dx.doi.org/10.1128/JB.00999-08DOI Listing

Publication Analysis

Top Keywords

mcc
5
maturation translation
4
translation inhibitor
4
inhibitor microcin
4
microcin microcin
4
microcin mcc
4
mcc inhibitor
4
inhibitor growth
4
growth enteric
4
enteric bacteria
4

Similar Publications

Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs.

Sci Rep

January 2025

Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.

We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.

View Article and Find Full Text PDF

Extraction of cellulose nanocrystals from date seeds using transition metal complex-assisted hydrochloric acid hydrolysis.

Int J Biol Macromol

January 2025

Chemical and Petroleum Engineering Department, College of Engineering, United Arab Emirates University, PO Box 15551, Al Ain, United Arab Emirates. Electronic address:

In this study, the role of a transition metal complex in improving hydrolysis efficiency during nanocellulose production was analysed. Cellulose nanocrystals (CNCs) were extracted from date seeds by incorporating a copper metal complex during HCl hydrolysis. In contrast to traditional HCl hydrolysis at moderate conditions, which yielded only microcrystalline cellulose (MCC), this approach resulted in the extraction of CNCs with a 10 % improved yield compared to MCC.

View Article and Find Full Text PDF

Substrate-specific responses to mixing conditions in high-solids enzymatic hydrolysis: Insights from microcrystalline cellulose and dilute-acid pretreated corncob.

Int J Biol Macromol

January 2025

Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest, Resources, College of Chemical Engineering, Nanjing Forestry University, Nanjing 210037, PR China. Electronic address:

This study investigates the mixing effects on the enzymatic hydrolysis of microcrystalline cellulose (MCC) and dilute-acid pretreated corncob substrates under high-solid conditions. Enzymatic hydrolysis experiments were conducted to assess cellulose conversion rates under varying mixing conditions (0, 50, 150, and 250 rpm) and solids loadings (5 %, 15 %, 25 %, and 35 %, w/v), and distinct physicochemical properties of the substrates were characterized. Additionally, the role of mixing conditions and solid loadings on cellulose hydrolysis kinetics and enzyme adsorption on both substrates and lignin were elucidated.

View Article and Find Full Text PDF

Given the complexities of continuous bioprocessing, it is critical to thoroughly investigate the process parameters unique to multi-column chromatography (MCC) and their potential impacts. However, existing studies have focused on either loading densities or residence time at steady states only, and their combined impact on critical quality attributes (CQAs) especially during transient phases were less known. In this study, we investigated the impact of critical process parameters during both steady-state and transient phases (start-up, close-down, and intermediate perturbation) through full factorial design.

View Article and Find Full Text PDF

Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM)-based hybrid model for health monitoring and health crisis forecasting. It consists of efficiently retrieving safe content from multiple social media sources.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!