Screening of Antibacterial Compounds With Novel Structure From The FDA Approved Drugs Using Machine Learning Methods

Background: Due to the lack of new antibiotics in recent years, bacterial resistance has increasingly become a serious problem globally. The aim of this study is to construct an antibacterial compound predictor using machine learning methods to screen potential antibacterial drugs.Methods: Active and inactive antibacterial compounds were acquired from the ChEMBL and PubChem database, which were used to construct benchmark datasets. The antibacterial compound predictor is constructed using the support vector machine (SVM), random forest (RF), and multi-layer perception (MLP) methods. We predicted the antibacterial activity of the Food and Drug Administration (FDA) approved drugs in the DrugBank database and screened novel antibacterial drugs through structural similarity analysis.Results: In the initial screen process, the results suggested that the benchmark dataset based on FP2 molecular fingerprints, along with the SVM, RF, and MLP methods showed excellent prediction performance (mean AUC > 0.9 for all models). Using the combination of these three models, a total of 957 potential antibacterial drugs were predicted. Most of the predicted drugs showed low structural similarities compared with the FDA approved antibacterial drugs. We finally screened 9 predicted antibacterial drugs with novel structures including 2 anti-tumor drugs (cyclophosphamide and ifosfamide), 2 ophthalmic drugs (apraclonidine and echothiophate) and 5 anesthetics (desflurane, enflurane, isoflurane, methoxyflurane, and sevoflurane).Conclusions: This study provides a new insight for predicting antibacterial compounds with novel structures by using FDA approved drugs. The predicted compounds with novel structures are worthy of further experimental verification in the future.

THE RELATIONSHIP OF THE ANTIBACTERIAL ACTIVITY OF A PLANT SPECIES WITH CHEMICAL COMPOUNDS OF DIFFERENT GROUPS: A STATISTICAL APPROACH

The article deals with the question of the statistical attraction of chemical compounds that have an antibacterial effect and belong to various groups (terpenoids, phenols, flavonoids, quinones, alkaloids, lactones, coumarins, iridoids, xanthones) to the same types of plants. To assess the occurrence of species containing an antibacterial compound of a certain group in a set of species containing an antibacterial compound of another group (in comparison with the species of the flora of the Russian Federation outside this set), the student’s mathematical and statistical criterion was used. It is shown that in 12 combinations of groups ("terpenoids-phenols", "terpenoids-flavonoids", "terpenoids-quinones", "terpenoids-coumarins", "phenols-flavonoids". "Phenols-quinones", "phenols-coumarins", "flavonoids-coumarins", "flavonoids-iridoids", "flavonoids-xanthones", "lactones-coumarins") the occurrence of species containing an antibacterial compound related to one element of the combination is significantly increased in the set of species containing an antibacterial compound related to another element. It is noted that these statistical relationships are created by species belonging to 19 families of the flora of the Russian Federation (Iridaceae, Ranunculaceae, Chenopodyaceae, Ericaceae, Pyrolaceae, Salicaceae, Brassicaceae, Moraceae, Crassulaceae, Rosaceae, Fabaceae, Apiaceae, Valerianaceae,Viburnaceae,Rubiacae,Gentianaceae, Scrophulariaceae, Lamiaceae, Asteracaeae).

In Vitro Antibacterial Effect of the Methanolic Extract of the Korean Soybean Fermented Product Doenjang against Staphylococcus aureus

Ultra-high performance liquid chromatography/mass spectrometry showed soyasaponin I and the isoflavones daidzein, genistein, and glycitein to be the main components of the methanolic extract of the Korean soybean fermented product doenjang, which is known to be a rich source of naturally occurring bioactive substances, at average contents of 515.40, 236.30, 131.23, and 29.00 ng/mg, respectively. The antimicrobial activity of the methanolic extract of doenjang against nine Staphylococcusaureus strains was determined in vitro by the broth microdilution method to investigate its potential to serve as an alternative antibacterial compound. The results suggest that the extract is an effective antistaphylococcal agent at concentrations of 2048–4096 µg/mL. Moreover, the tested extract also showed the ability to inhibit the growth of both methicillin-sensitive and methicillin-resistant animal and clinical S. aureus isolates. The growth kinetics of the chosen strains of S. aureus at the minimum inhibitory concentration of the methanolic extract of doenjang support the idea that the tested extract acts as an antibacterial compound. To the best of our knowledge, this is the first report on the antistaphylococcal action of the methanolic extract of doenjang thus, additional studies including in vivo testing are necessary to confirm this hypothesis.

Fermentation and Extraction of Antibacterial Metabolite Using Streptomyces spp. Isolated from Taplejung, Nepal

Realizing an increasing need for a novel antibiotic, this study was carried out to screen antibacterial metabolites producing actinomycetes from 15 soil samples collected from Taplejung. Antibacterial metabolites producing actinomycetes were confirmed by primary screening and secondary screening. Macroscopic, microscopic, and biochemical characteristics were used for presumptive identification of probable actinomycetes genera. The potential isolate was cultured in starch casein broth for production of possible antibacterial compound. The antibacterial compound was extracted from fermented broth using organic solvents like ethyl acetate, n-butanol, chloroform, dichloromethane, and methanol. Among 24 isolates, only one (T18) showed antibacterial activity against both Gram-positive (Staphylococcus aureus and Bacillus subtilis) and Gram-negative (Escherichia coli, Salmonella Typhi and Pseudomonas aeruginosa) test-bacteria. The isolate was considered as Streptomyces spp based on microscopy and various biochemical, and physiological characteristics. Extracted antibacterial metabolite showed antibacterial activity with a MIC value of 1.2 mg/mL against E. coli (ATCC 25922). The chromatogram in Thin Layer Chromatography showed only one spot exhibited by extract with Rf value 0.87 suggested that the isolate produced a compound that was completely different from the spot with Rf value 0.94 produced by gentamicin (standard). This study revealed the distribution of the potent antibacterial metabolite producing actinomycetes in the soils of Taplejung.

ANTIBACTERIAL EFFECT OF EUGENIA POLYANTHA WIGHT WITH CORYNEBACTERIUM DIPHTHERIAE NON-TOXIGENIC

Introduction: Corynebacterium diphtheriae is a bacteria that causes diphtheria. In recent years, the bacterium is resistant to antibiotics. Eugenia polyantha wight might be a suitable antibiotic alternative as it has antibacterial effect against Staphylococcus aureus. The content of the antibacterial compound in Eugenia polyantha wight at specific concentrations is expected to be able to kill the Corynebacterium diphtheriae. Purpose: This study aimed to examine the antibacterial effect of Eugenia polyantha wight to Corynebacterium diphtheriae non-toxic. Method: Bay leaf extract (Eugenia polyantha wight) made with maceration method. This research is an experimental study conducted in vitro using a microdilution test on 96 well plates then count value with the streaking method to find out MBC. Results: bactericidal power was quite effective at the concentration of 40%, while at the concentration of 80%-100% has very strong bactericidal power that could destroy the growth of bacteria 99.9%. The higher the concentration of bay leaves extract, the higher the bactericidal power of bacteria Conclusion: Eugenia polyantha wight has an antibacterial effect against Corynebacterium diphtheriae non-toxic.