scholarly journals A new oligonucleotide array for the detection of multidrug and extensively drug-resistance tuberculosis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ching-Yu Chen ◽  
Jui-Yun Weng ◽  
Hsin-Hui Huang ◽  
Wen-Chun Yen ◽  
Yu-Han Tsai ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Oligonucleotide Array ◽  
Extensively Drug Resistance

Current insights into the chemistry and antitubercular potential of benzimidazole and imidazole derivatives

2020 ◽  
Vol 20 ◽  
Author(s):  
Deepa Parwani ◽  
Sushanta Bhattacharya ◽  
Akash Rathore ◽  
Chaitali Mallick ◽  
Vivek Asati ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Mycobacterium Tuberculosis ◽  
Multi Drug Resistance ◽  
Benzimidazole Derivatives ◽  
Duration Of Treatment ◽  
Structure Activity ◽  
Mdr Tb ◽  
Low Toxicity ◽  
Extensively Drug Resistance ◽  
Improved Characteristics

: Tuberculosis is a disease caused by Mycobacterium tuberculosis (Mtb), affecting millions of people worldwide. The emergence of drug resistance is a major problem in the successful treatment of tuberculosis. Due to the commencement of MDR-TB (multi-drug resistance) and XDR-TB (extensively drug resistance), there is a crucial need for the development of novel anti-tubercular agents with improved characteristics such as low toxicity, enhanced inhibitory activity and short duration of treatment. In this direction, various heterocyclic compounds have been synthesized and screened against Mycobacterium tuberculosis. Among them, benzimidazole and imidazole containing derivatives found to have potential anti-tubercular activity. The present review focuses on various imidazole and benzimidazole derivatives (from 2015-2019) with their structure activity relationships in the treatment of tuberculosis.

Recent Advancement in Predicting Subcellular Localization of Mycobacterial Protein with Machine Learning Methods

2020 ◽  
Vol 16 (5) ◽  
pp. 605-619 ◽  
Author(s):  
Shi-Hao Li ◽  
Zheng-Xing Guan ◽  
Dan Zhang ◽  
Zi-Mei Zhang ◽  
Jian Huang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Subcellular Localization ◽  
Protein Function ◽  
Sequence Data ◽  
Computational Prediction ◽  
Multidrug Resistant ◽  
Function Annotation ◽  
Benchmark Datasets ◽  
Mycobacterial Protein ◽  
Extensively Drug Resistance

Mycobacterium tuberculosis (MTB) can cause the terrible tuberculosis (TB), which is reported as one of the most dreadful epidemics. Although many biochemical molecular drugs have been developed to cope with this disease, the drug resistance—especially the multidrug-resistant (MDR) and extensively drug-resistance (XDR)—poses a huge threat to the treatment. However, traditional biochemical experimental method to tackle TB is time-consuming and costly. Benefited by the appearance of the enormous genomic and proteomic sequence data, TB can be treated via sequence-based biological computational approach-bioinformatics. Studies on predicting subcellular localization of mycobacterial protein (MBP) with high precision and efficiency may help figure out the biological function of these proteins and then provide useful insights for protein function annotation as well as drug design. In this review, we reported the progress that has been made in computational prediction of subcellular localization of MBP including the following aspects: 1) Construction of benchmark datasets. 2) Methods of feature extraction. 3) Techniques of feature selection. 4) Application of several published prediction algorithms. 5) The published results. 6) The further study on prediction of subcellular localization of MBP.

Extra-Pulmonary TB

2021 ◽  
pp. 91-116
Author(s):  
Sarita Rani ◽  
Ankur Kaul ◽  
Anil Kumar Mishra ◽  
Umesh Gupta
Keyword(s):  
Drug Resistance ◽  
Polymeric Micelles ◽  
New Drugs ◽  
Multi Drug Resistance ◽  
Liposomal Formulations ◽  
Extra Pulmonary ◽  
Stability Issues ◽  
Low Solubility ◽  
Line Drug ◽  
Extensively Drug Resistance

Tuberculosis is considered a fatal respiratory disease commonly seen in developing countries. This chapter includes the global scenario of TB patients and brief description of TB history, its pathogenesis, types, diagnosis tests, emergence of MDR (multi drug resistance) and XDR (extensively drug resistance). The traditional chemotherapy of TB includes first and second line drug therapy. These lines of therapies face many difficulties such as low solubility, low bioavailability, and stability issues. Therefore, some new drugs were introduced in the market that showed effective results to the patients. Nanoparticulate drug delivery gained much focus in recent years due to its advantages and ideal characteristics. Numerous nanoparticles, liposomal formulations, and polymeric micelles were reported by the researchers with significant and considerable results. Inhalable formulations were also prepared by scientists that showed effective and remarkable anti-tuberculosis action on TB patients. Many efforts are awaited to completely eradicate TB from the planet.

scholarly journals Novel Vaccine Candidates against Tuberculosis

2020 ◽  
Vol 27 (31) ◽  
pp. 5095-5118 ◽  
Author(s):  
Zhihao Li ◽  
Changping Zheng ◽  
Marco Terreni ◽  
Lisa Tanzi ◽  
Matthieu Sollogoub ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Clinical Trials ◽  
Recent Progress ◽  
Multi Drug Resistance ◽  
System Response ◽  
Bacillus Calmette Guerin ◽  
Vaccine Research ◽  
Vaccine Candidates ◽  
Immune System Response ◽  
Extensively Drug Resistance

Ranking above AIDS, Tuberculosis (TB) is the ninth leading cause of death affecting and killing many individuals every year. Drugs’ efficacy is limited by a series of problems such as Multi- Drug Resistance (MDR) and Extensively-Drug Resistance (XDR). Meanwhile, the only licensed vaccine BCG (Bacillus Calmette-Guérin) existing for over 90 years is not effective enough. Consequently, it is essential to develop novel vaccines for TB prevention and immunotherapy. This paper provides an overall review of the TB prevalence, immune system response against TB and recent progress of TB vaccine research and development. Several vaccines in clinical trials are described as well as LAM-based candidates.

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