Discovery of potential natural dihydroorotate dehydrogenase inhibitors and their synergism with brequinar via integrated molecular docking, dynamic simulations and in vitro approach

Abstract

The critical function of dihydroorotate dehydrogenase (DHODH) in pyrimidine synthesis attracted a great interest throughout beyond decades. Inhibitors of human DHODH (hDHODH) have validated efficacy for remedy of many immunological diseases. Brequinar and leflunomide are examples of such compounds. However, most of such immunosuppressive medications suffer from a lot of side effects and accompanied by adverse metabolic disturbances and toxicities. So that, immunomodulation utilizing natural products received the attention of many researchers. In this study, computer-aided molecular docking, molecular dynamic (MD) simulations and biochemical testing were utilized to find new pharmacologically active chemical entities from natural sources to combat immunosuppressive diseases. More specifically, Glide docking was used for a structure-based virtual screening of in-house 3D database of compounds retrieved from some traditionally known immunomodulatory plants surveyed from literature. The top five scored plants were found to be Zingiber officinale, Curcuma longa, Glycyrrhiza glabra, Allium sativum and Olea europaea. In vitro hDHODH inhibitory assays illustrated the ability of Allium sativum and silymarin standard hits; specifically, silibinin, to significantly inhibit the hDHODH enzyme. Molecular docking and MD simulations revealed a strong binding of the discovered hits within the active site. Following that, the most promising hits were tested separately with brequinar in a fixed-ratio combination setting to assess their combined effects on hDHODH catalytic inhibition. The binary combination of silibinin and brequinar revealed that in this combination, brequinar could be utilized at a dose 9.33-fold less when compared to its single-use to produce 99% inhibition for hDHODH enzyme. These findings confirmed that this binary mixture is an excellent combination providing better therapeutic effects and lower side effects.

Attenuation of quorum sensing regulated virulence functions and biofilm of pathogenic bacteria by medicinal plant Artemisia annua and its phytoconstituent 1, 8‐cineole

“…In this section, stability study of protein-ligand complexes of LasI, LasR, CviR, PilY1, PilT, and RhlR with 1,8-cineole obtained by molecular docking study was carried out by means of 100 ns MD simulations. Mobility of 1,8-cineole with respect to active site residues of target proteins was numerically calculated by RMSD measurements (Khairy et al, 2022). As shown in Figure 10, RMSD values were measured for compound 1,8-cineole with LasI below 0.7 nm and mean 0.43 nm, with LasR below 0.5 nm and mean 0.32 nm, with CviR below 0.5 nm and mean 0.35 nm, with PilT below 0.8 nm and mean 0.64 nm, with PilY1 below 1.4 nm and mean 0.75 nm, with RhlR below 0.7 nm and mean 0.39 nm.…”

Phytochemical Composition, In Vitro Antimicrobial, Antioxidant, and Enzyme Inhibition Activities, and In Silico Molecular Docking and Dynamics Simulations of Centaurea lycaonica: A Computational and Experimental Approach

“…MD simulation was performed for 150 ns in this study to demonstrate the stability of the apigenin and myristoleic acid complexes with α-glucosidase and α-amylase obtained from the molecular docking study . Fitting of apigenin to the backbone atoms of α-glucosidase and α-amylase, conformational changes of the ligand at the active site were analyzed by RMSD calculations . As shown in Figure A, the α-glucosidase active site of apigenin remained stable below 0.45 nm and had a mean value of 0.39 ± 0.39 nm.…”

“…33 Fitting of apigenin to the backbone atoms of α-glucosidase and α-amylase, conformational changes of the ligand at the active site were analyzed by RMSD calculations. 34 As shown in Figure 7A, the α-glucosidase active site of apigenin remained stable below 0.45 nm and had a mean value of 0.39 ± 0.39 nm. As given in Figure 7B in the other MD simulation, apigenin and α-amylase were stable around 0.2 nm for the first 60 ns, fluctuating up to 0.8 nm between 60 and 75 nm, after which there were shifts but below 0.4 nm, and remained stable on average around 0.2 nm.…”

Forecasting of potential anti-inflammatory targets of some immunomodulatory plants and their constituents using in vitro, molecular docking and network pharmacology-based analysis

“…Depending on our previous study of the chemical makeup of 32 selected immunomodulatory plants, 2154 phytochemical constituents were obtained for compilation of an in-house database as illustrated in Table S3 . These plants were selected according to their traditionally known action to treat immune related disorders or based on prior in vivo, in vitro or clinical trials from literature review as mentioned in Khairy et al 73 and summarized briefly in Table 6 . Different resources including Dictionary of natural products ( http://dnp.chemnetbase.com/faces/chemical/ChemicalSearch.xhtml;jsessionid=0A16BF52515E734B15A96DCBAE7788B9 ), National Centre for Biotechnology Information's PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ), ChEMBL ( https://www.ebi.ac.uk/chembl/ ) and Chemdraw software (CambridgeSoft Corporation, Cambridge, USA) were used to provide 2D structures of these compounds in (.sdf) format.…”