Unlocking Herbal Potentials: Novel Shikimate Kinase Inhibitors in the Fight Against Antibiotic Resistance
Nirgudkar, S.; Chai, Y.
Show abstract
Against a backdrop of stagnant antibiotic innovation, the escalating prevalence of antibiotic-resistant pathogens forecasts a challenging future [6]. Traditionally, antibiotics, predominantly derived from fungal sources, employ a limited set of mechanisms to inhibit bacterial growth [6, 16]. Shikimate Kinase has emerged as a promising antibacterial target due to its exclusivity to bacteria and the lethality of its inhibition [4, 13, 14, 15, 28, 29, 30]. Although synthetic inhibitors have been developed, the exploration of plant-derived alternatives remains untapped. Naturally derived plant-based compounds provide a more viable option because of the high cost of creating synthetic compounds. This study examines the Goldenrod plant, reputed in Native American Ethno-medicine for its antimicrobial properties [3, 12, 17]. Employing Liquid Chromatography - Mass Spectrometry (LC-MS) and Quantitative Structure Activity Relationship (QSAR) models, the study evaluates the plants compounds for their potential as antibacterial agents. Antibacterial activity against Bacillus Subtilis was assessed using the Kirby-Bauer Disk Diffusion assay, and genetic sequencing was performed on mutants that overcame the initial inhibition zone. By comparing the parent and mutant strains, the mode of inhibition by the plant antibiotic was determined by backtracking. The study identified Shikimate Kinase as the inhibitory target of the plant-derived compounds. Molecular docking revealed a binding affinity of -8.9 kcal/mol for the most effective compound, which is statistically significant compared to Shikimate Acid, the enzymes natural substrate. Through Pymol visualization, competitive inhibition was confirmed, with the compounds binding pocket exhibiting a druggability score of 0.84, approaching the threshold of clinical drugs. This research suggests new antibiotic classes targeting the Shikimate Kinase pathway, offering an alternative approach to tackling ESKAPE pathogens and enhancing health outcomes.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Identification of Natural Antiviral Drug Candidates Against Tilapia Lake Virus: Computational Drug Design Approaches 97%
- Virtual screening of antimicrobial plant extracts by machine-learning classification of chemical compounds in semantic space 96%
- Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation 96%
Similar papers in this journal
- Chemical composition, antimicrobial and antioxidant activities of essential oils from the receptacle of sunflower (Helianthus annuus L.) 96%
- Structure-Based Design of Small-Molecule Inhibitors of Human Interleukin-6 95%
- Macrocybin, a mushroom natural triglyceride, reduces tumor growth in vitro and in vivo through caveolin-mediated interference with the actin cytoskeleton 94%
Similar papers in this journal
- Structure-activity relationship of pyrrolidine pentamine derivatives as inhibitors of the aminoglycoside 6'-N-acetyltransferase type Ib 95%
- Capsaicin potently blocks Salmonella typhimurium invasion of Vero cells 95%
- Exploration of clinical breakpoint of Danofloxacin for Glaesserella parasuis in plasma and in PELF 93%
Similar papers in this journal
- PeruNPDB: The Peruvian Natural Products Database for in silico drug screening 96%
- A new strategy for identifying mechanisms of drug-drug interaction using transcriptome analysis: Compound Kushen injection as a proof of principle 96%
- In vitro screening of anti-viral and virucidal effects against SARS-CoV-2 by Hypericum perforatum and Echinacea. 95%
Similar papers in this journal
- Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-based Classifiers 96%
- Support Vector Machine based prediction models for drug repurposing and designing novel drugs for colorectal cancer 96%
- Chalcogen derivatives for the treatment of African trypanosomiasis: biological evaluation of thio and seleno- semicarbazones and their azole derivatives 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.