Mycobacterial energy metabolism currently attracts strong attention as new target space for development of anti-tuberculosis drugs. The imidazopyridine Q203 targets the cytochrome bcc complex of the respiratory chain, a key component in energy metabolism. Q203 blocks growth of Mycobacterium tuberculosis at nanomolar concentrations, however, it fails to actually kill the bacteria, which may limit the clinical applicability of this candidate drug. In this report we show that inhibition of cytochrome bd, a parallel branch of the mycobacterial respiratory chain, by aurachin D invoked bactericidal activity of Q203. In biochemical assays using inverted membrane vesicles from Mycobacterium tuberculosis and Mycobacterium smegmatis we found that inhibition of respiratory chain activity by Q203 was incomplete, but could be enhanced by inactivation of cytochrome bd, either by genetic knock-out or by inhibition with aurachin D. These results indicate that simultaneously targeting the cytochrome bcc and the cytochrome bd branch of the mycobacterial respiratory chain may turn out as effective strategy for combating M. tuberculosis.

Candida auris, an evolving multidrug-resistant pathogenic yeast, is known for causing severe invasive infections associated with high mortality rates in hospitalized individuals. Distinct from other Candida species, C. auris can persist for longer periods on different surfaces and is resistant to all of the major classes of antifungal drugs. Therefore, there is an urgent need for new antimycotic drugs with improved efficacy and reduced toxicity. The development of new antifungals based on antimicrobial peptides from various sources is considered a promising alternative. In this study, we examined the in vitro anti-yeast activity of the human cathelicidin peptides LL-37 against clinical strains of C. auris alone and in combination with different antifungal drugs by broth microdilution assay. To understand the antifungal mechanism of action, cell envelopes, cell cycle arrest, and effect on oxidative stress enzymes were studied using standard protocols. The minimum inhibitory and fungicidal concentrations of cathelicidin LL-37 ranged from 25–100 and 50–200 µg/mL, respectively. A combination interaction in a 1:1 ratio (cathelicidin LL-37: antifungal drug) resulted in 70% synergy with fluconazole and 100% synergy with amphotericin B and caspofungin. Assessment of the C. auris membrane by using propidium iodide assay after exposure to cathelicidin LL-37 linked membrane permeabilization with inhibition of C. auris cell growth and viability. These results were backed up by scanning electron microscopy studies demonstrating that exposure with cathelicidin LL-37 caused C. auris cells to undergo extensive surface changes. Spectrophotometric analysis revealed that cathelicidin LL-37 caused oxidative stress in C. auris, as is evident from the significant increase in the activity of primary antioxidant enzymes. In addition, cathelicidin LL-37 inhibited the cell cycle and accumulated cells in the S phase. Therefore, these results specify the potential of cathelicidin LL-37 for developing a new and effective anti-Candida agent.

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.

Fungi are renowned as a fountainhead of bio-metabolites that could be employed for producing novel therapeutic agents, as well as enzymes with wide biotechnological and industrial applications. Stachybotrys chartarum (black mold) (Stachybotriaceae) is a toxigenic fungus that is commonly found in damp environments. This fungus has the capacity to produce various classes of bio-metabolites with unrivaled structural features, including cyclosporins, cochlioquinones, atranones, trichothecenes, dolabellanes, phenylspirodrimanes, xanthones, and isoindoline and chromene derivatives. Moreover, it is a source of various enzymes that could have variable biotechnological and industrial relevance. The current review highlights the formerly published data on S. chartarum, including its metabolites and their bioactivities, as well as industrial and biotechnological relevance dated from 1973 to the beginning of 2022. In this work, 215 metabolites have been listed and 138 references have been cited.