Overcoming Mycobacterium tuberculosis through small molecule inhibitors to break down cell wall synthesis

Modulators targeting protein-protein interactions in Mycobacterium tuberculosis

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis (M. tuberculosis), mainly transmitted through droplets to infect the lungs, and seriously affecting patients' health and quality of life. Clinically, anti-TB drugs often entail side effects and lack efficacy against resistant strains. Thus, the exploration and development of novel targeted anti-TB medications are imperative. Currently, protein-protein interactions (PPIs) offer novel avenues for anti-TB drug development, and the study of targeted modulators of PPIs in M. tuberculosis has become a prominent research focus. Furthermore, a comprehensive PPI network has been constructed using computational methods and bioinformatics tools. This network allows for a more in-depth analysis of the structural biology of PPIs and furnishes essential insights for the development of targeted small-molecule modulators. Furthermore, this article provides a detailed overview of the research progress and regulatory mechanisms of PPI modulators in M. tuberculosis, the causative agent of TB. Additionally, it summarizes potential targets for anti-TB drugs and discusses the prospects of existing PPI modulators.

Targeting polyketide synthase 13 for the treatment of tuberculosis

Tuberculosis (TB) is one of the most threatening diseases for humans, however, the drug treatment strategy for TB has been stagnant and inadequate, which could not meet current treatment needs. TB is caused by Mycobacterial tuberculosis, which has a unique cell wall that plays a crucial role in its growth, virulence, and drug resistance. Polyketide synthase 13 (Pks13) is an essential enzyme that catalyzes the biosynthesis of the cell wall and its critical role is only found in Mycobacteria. Therefore, Pks13 is a promising target for developing novel anti-TB drugs. In this review, we first introduced the mechanism of targeting Pks13 for TB treatment. Subsequently, we focused on summarizing the recent advance of Pks13 inhibitors, including the challenges encountered during their discovery and the rational design strategies employed to overcome these obstacles, which could be helpful for the development of novel Pks13 inhibitors in the future.

Selection of Multi-Drug Targets against Drug-Resistant Mycobacterium tuberculosis XDR1219 Using the Hyperbolic Mapping of the Protein Interaction Network

Tuberculosis remains the leading cause of death from a single pathogen. On the other hand, antimicrobial resistance (AMR) makes it increasingly difficult to deal with this disease. We present the hyperbolic embedding of the Mycobacterium tuberculosis protein interaction network (mtbPIN) of resistant strain (MTB XDR1219) to determine the biological relevance of its latent geometry. In this hypermap, proteins with similar interacting partners occupy close positions. An analysis of the hypermap of available drug targets (DTs) and their direct and intermediate interactors was used to identify potentially useful drug combinations and drug targets. We identify rpsA and rpsL as close DTs targeted by different drugs (pyrazinamide and aminoglycosides, respectively) and propose that the combination of these drugs could have a synergistic effect. We also used the hypermap to explain the effects of drugs that affect multiple DTs, for example, forcing the bacteria to deal with multiple stresses like ethambutol, which affects the synthesis of both arabinogalactan and lipoarabinomannan. Our strategy uncovers novel potential DTs, such as dprE1 and dnaK proteins, which interact with two close DT pairs: arabinosyltransferases (embC and embB), Ser/Thr protein kinase (pknB) and RNA polymerase (rpoB), respectively. Our approach provides mechanistic explanations for existing drugs and suggests new DTs. This strategy can also be applied to the study of other resistant strains.

Metabolomics of infectious diseases in the era of personalized medicine

Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.

Recent Advances in Anti-Tuberculosis Drug Discovery Based on Hydrazide-Hydrazone and Thiadiazole Derivatives Targeting InhA

Tuberculosis is an extremely serious problem of global public health. Its incidence is worsened by the presence of multidrug-resistant (MDR) strains of Mycobacterium tuberculosis. More serious forms of drug resistance have been observed in recent years. Therefore, the discovery and/or synthesis of new potent and less toxic anti-tubercular compounds is very critical, especially having in mind the consequences and the delays in treatment caused by the COVID-19 pandemic. Enoyl-acyl carrier protein reductase (InhA) is an important enzyme involved in the biosynthesis of mycolic acid, a major component of the M. tuberculosis cell wall. At the same time, it is a key enzyme in the development of drug resistance, making it an important target for the discovery of new antimycobacterial agents. Many different chemical scaffolds, including hydrazide hydrazones and thiadiazoles, have been evaluated for their InhA inhibitory activity. The aim of this review is to evaluate recently described hydrazide-hydrazone- and thiadiazole-containing derivatives that inhibit InhA activity, resulting in antimycobacterial effects. In addition, a brief review of the mechanisms of action of currently available anti-tuberculosis drugs is provided, including recently approved agents and molecules in clinical trials.

Conformational Dynamics and Stability of Bilayers Formed by Mycolic Acids from the Mycobacterium tuberculosis Outer Membrane

Bilayers of mycolic acids (MAs) form the outer membrane of Mycobacterium tuberculosis that has high strength and extremely low permeability for external molecules (including antibiotics). For the first time, we were able to study them using the all-atom long-term molecular dynamic simulations (from 300 ns up to 1.2 μs) in order to investigate the conformational changes and most favorable structures of the mycobacterial membranes. The structure and properties of the membranes are crucially dependent on the initial packing of the α-mycolic acid (AMA) molecules, as well as on the presence of the secondary membrane components, keto- and methoxy mycolic acids (KMAs and MMAs). In the case of AMA-based membranes, the most labile conformation is W while other types of conformations (sU as well as sZ, eU, and eZ) are much more stable. In the multicomponent membranes, the presence of the KMA and MMA components (in the W conformation) additionally stabilizes both the W and eU conformations of AMA. The membrane in which AMA prevails in the eU conformation is much thicker and, at the same time, much denser. Such a packing of the MA molecules promotes the formation of a significantly stronger outer mycobacterial membrane that should be much more resistant to the threatening external factors.

Machine Learning Prediction of Mycobacterial Cell Wall Permeability of Drugs and Drug-like Compounds

The cell wall of Mycobacterium tuberculosis and related organisms has a very complex and unusual organization that makes it much less permeable to nutrients and antibiotics, leading to the low activity of many potential antimycobacterial drugs against whole-cell mycobacteria compared to their isolated molecular biotargets. The ability to predict and optimize the cell wall permeability could greatly enhance the development of novel antitubercular agents. Using an extensive structure-permeability dataset for organic compounds derived from published experimental big data (5371 compounds including 2671 penetrating and 2700 non-penetrating compounds), we have created a predictive classification model based on fragmental descriptors and an artificial neural network of a novel architecture that provides better accuracy (cross-validated balanced accuracy 0.768, sensitivity 0.768, specificity 0.769, area under ROC curve 0.911) and applicability domain compared with the previously published results.