Mycobacterium tuberculosis is a leading cause of infectious disease in the world today. This outlook is aggravated by a growing number of M. tuberculosis infections in individuals who are immunocompromised as a result of HIV infections. Thus, new and more potent anti-TB agents are necessary. Therefore, dUTpase was selected as a target enzyme to combat M. tuberculosis. In this work, molecular modeling methods involving docking and QM/MM calculations were carried out to investigate the binding orientation and predict binding affinities of some potential dUTpase inhibitors. Our results suggest that the best potential inhibitor investigated, among the compounds studied in this work, is the compound dUPNPP. Regarding the reaction mechanism, we concluded that the decisive stage for the reaction is the stage 1. Furthermore, it was also observed that the compounds with a -1 electrostatic charge presented lower activation energy in relation to the compounds with a -2 charge.

Download full-text PDF

Source
http://dx.doi.org/10.1080/07391102.2011.10508617DOI Listing

Publication Analysis

Top Keywords

molecular modeling
8
mycobacterium tuberculosis
8
modeling mycobacterium
4
tuberculosis
4
tuberculosis dutpase
4
dutpase docking
4
docking catalytic
4
catalytic mechanism
4
mechanism studies
4
studies mycobacterium
4

Similar Publications

An updated systematic review with meta-analysis and meta-regression of the factors associated with human visceral leishmaniasis in the Americas.

Infect Dis Poverty

January 2025

Universidade Federal de São João del Rei (UFSJ), Campus Centro-Oeste Dona Lindu, Avenida Sebastião Gonçalves Coelho 400, Chanadour, Divinópolis, MG, Brazil.

Background: Human visceral leishmaniasis (VL) is a systemic disease with high case-fatality rates and a widespread distribution. Continuous evaluation of the risk factors for VL is essential to ensure the effective implementation of prevention and control measures. The present study reviews the factors associated with VL in the Americas.

View Article and Find Full Text PDF

A large set of antimalarial molecules (N ~ 15k) was employed from ChEMBL to build a robust random forest (RF) model for the prediction of antiplasmodial activity. Rather than depending on high throughput screening (HTS) data, molecules tested at multiple doses against blood stages of Plasmodium falciparum were used for model development. The open-access and code-free KNIME platform was used to develop a workflow to train the model on 80% of data (N ~ 12k).

View Article and Find Full Text PDF

Background: HER2-targeted therapies have revolutionized the treatment of HER2-positive breast cancer patients, leading to significant improvements in tumor response rates and survival. However, resistance and incomplete response remain considerable challenges. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition is a novel therapeutic strategy for the management of dyslipidemia by enhancing the clearance of low-density lipoprotein cholesterol receptors, however recent evidence also shows links between PCSK9 and cancer cells.

View Article and Find Full Text PDF

Acute myeloid leukemia (AML) is caused by altered maturation and differentiation of myeloid blasts, as well as transcriptional/epigenetic alterations, all leading to excessive proliferation of malignant blood cells in the bone marrow. Tumor heterogeneity due to the acquisition of new somatic alterations leads to a high rate of resistance to current therapies or reduces the efficacy of hematopoietic stem cell transplantation (HSCT), thus increasing the risk of relapse and mortality. Single-cell RNA sequencing (scRNA-seq) will enable the classification of AML and guide treatment approaches by profiling patients with different facets of the same disease, stratifying risk, and identifying new potential therapeutic targets at the time of diagnosis or after treatment.

View Article and Find Full Text PDF

Background: Growing evidence shows that dysregulated metabolic intrauterine environments can affect offspring's neurodevelopment and behaviour. However, the results of individual cohort studies have been inconsistent. We aimed to investigate the association between maternal diabetes before pregnancy and gestational diabetes mellitus (GDM) with neurodevelopmental, cognitive and behavioural outcomes in children.

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!