Virtual Screening for the Development of New Effective Compounds Against Staphylococcus aureus

Modelling of AgrA inhibitors to combat anti-microbial resistance in Staphylococcus aureus

Staphylococcus aureus is a Gram-positive bacterium found on human skin that causes skin and soft tissue infections, as well as pneumonia, osteomyelitis, and endocarditis. The prevalence of antibiotic resistant strains has made the treatments less effective. An efficient alternate method for battling these contagious diseases is anti-virulence strategy. The AgrA protein, a key activator of Accessory Gene Regulator system in S. aureus, is vital to the virulence of the organism and, consequently, its pathogenesis. Using a Machine Learning algorithm, the Support Vector Machine (SVM), and a ligand-based pharmacophore modelling method, prediction models of AgrA inhibitors were developed. The metrics of the SVM model were inadequate, hence it was not used for virtual screening. For ligand-based pharmacophore modelling, 14 of 29 compounds were removed from the active set due to a lack of shared pharmacophore properties, and 504 compounds were designated as decoys. A 3D pharmacophore model was created using LigandScout 4.4.5, with a fit score of 57.48, including a positive ionizable group, one hydrogen bond donor, and three hydrogen bond acceptors. The model after further validation was used to virtually screen an external database which resulted in six hits. These compounds were docked with the AgrA domain crystal structure to determine the inhibitor activity. Further, each docked complex was subjected to a 100 ns molecular dynamics simulation. CID238 and CID20510252 demonstrated potent inhibitory binding interactions and hence can be used to develop AgrA inhibitors in future after proper validation.Communicated by Ramaswamy H. Sarma.

Anti-MRSA drug discovery by ligand-based virtual screening and biological evaluation

S. aureus resistant to methicillin (MRSA) is one of the most-concerned multidrug resistant bacteria, due to its role in life-threatening infections. There is an urgent need to develop new antibiotics against MRSA. In this study, we firstly compiled a data set of 2,3-diaminoquinoxalines by chemical synthesis and antibacterial screening against S. aureus, and then performed cheminformatics modeling and virtual screening. The compound with the Specs ID of AG-205/33156020 was discovered as a new antibacterial agent, and was further identified as a Gyrase B (GyrB) inhibitor. In light of the common features, we hypothesized that the 6c as the representative of 2,3-diaminoquinoxalines also inhibited GyrB and eventually proved it. Via molecular docking and molecular dynamics simulations, we identified binding modes of AG-205/33156020 and 6c to the ATPase domain of GyrB. Importantly, these GyrB inhibitors inhibited the MRSA strains and showed selectivity to HepG2 and HUVEC. Taken together, this research work provides an effective ligand-based computational workflow for scaffold hopping in anti-MRSA drug discovery, and discovers two new GyrB inhibitors that are worthy of further development.

A comprehensive application: Molecular docking and network pharmacology for the prediction of bioactive constituents and elucidation of mechanisms of action in component-based Chinese medicine

Traditional Chinese medicine (TCM) has been used for more than 2000 years in China. TCM has received wide attention recently due to its unique charm. At the same time, its main obstacles have attracted wide attention, including vagueness of drug composition and treatment mechanism. With the development of virtual screening technology, more and more Chinese medicine compounds have been studied to discover the potential active components and mechanisms of action. Molecular docking is a computer technology based on structural design. Network pharmacology establishes powerful and comprehensive databases to understand the relationship between TCM and disease network. In this review, emergent uses and applications of two techniques and further superiorities of the two techniques when embarked to boil down into a tidy system were illustrated. A combination of the two provides a theoretical basis and technical support for the construction of modern TCM based on the compatibility of components and accelerates the realization of two basic elements as well, including the clearness of the pharmacodynamic substances and explanation of the effect of TCM.

Bioguided Purification of Active Compounds from Leaves of Anadenanthera colubrina var. cebil (Griseb.) Altschul

Anadenanthera colubrina var cebil (Griseb.) Altschul is a medicinal plant found throughout the Brazilian semi-arid area. This work performed a bioguided purification of active substances present in ethyl acetate extract from A. colubrina leaves. The anti-Staphylococcus aureus and antioxidant actions were used as markers of bioactivity. The extract was subjected to flash chromatography resulting in five fractions (F1, F2, F3, F4, and F5). The fractions F2 and F4 presented the highest antimicrobial action, with a dose able to inhibit 50% of bacteria growth (IN50) of 19.53 μg/mL for S. aureus UFPEDA 02; whereas F4 showed higher inhibitory action towards DPPH radical (2,2-diphenyl-1-picryl-hydrazyl-hydrate) [dose able to inhibit 50% of the radical (IC50) = 133 ± 9 μg/mL]. F2 and F4 were then subjected to preparative high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR), resulting in the identification of p-hydroxybenzoic acid and hyperoside as the major compounds in F2 and F4, respectively. Hyperoside and p-hydroxybenzoic acid presented IN50 values of 250 μg/mL and 500 μg/mL against S. aureus UFPEDA 02, respectively. However, the hyperoside had an IN50 of 62.5 μg/mL against S. aureus UFPEDA 705, a clinical isolate with multidrug resistant phenotype. Among the purified compounds, the proanthocyanidins obtained from F2 exhibited the higher antioxidant potentials. Taken together, these results highlight the potential of A. colubrina leaves as an alternative source of biomolecules of interest for the pharmaceutical, food, and cosmetic industries.