Virtual screening and molecular dynamics simulation studies to predict the binding of Sisymbrium irio L. derived phytochemicals against Staphylococcus aureus dihydrofolate reductase (DHFR)

The discovery of antibiotics initiated the era of drug innovation and implementation for human and animal health. Very soon, antibiotic resistance started evolving due to over-prescription and heavy usage of drugs leading to deleterious side effects. However, using plant extracts or medicinal plants has emerged as a new approach to dealing with the current problem. One such medicinal plant Sisymbrium irio L. is widely used in Unani therapy as an antimicrobial, analgesic, antipyretic, antioxidant, anti-inflammatory, hepatoprotective, bronchoprotective etc. The phytochemicals extracted from the aerial part of the plant have been used as a natural compound library and screened against a well-known anti-bacterial drug target Dihydrofolate reductase (DHFR)  enzyme of Staphylococcus aureus. The top two phytochemicals with lower docking score along with the positive control were subjected to molecular dynamics (MD) simulation studies to examine the stabilities of the complexes over 100 ns, followed by binding free energy estimation. The Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and Radius of Gyration (Rg) yielded established results throughout the MD run. Moreover, the derived phytochemicals exhibited lower binding free energy values than the positive control that can be tested for its in vitro efficacy, followed by further optimization to attain a potent therapeutic against S. aureus. Taken together, the present study suggests two promising phytochemicals derived from the aerial part of the plant S. irio with stable MD simulation results, strong binding affinity and no side effects

Chemical Probes of Escherichia coli Uncovered through Chemical-Chemical Interaction Profiling with Compounds of Known Biological Activity

SummaryWhile cell-based screens have considerable power in identifying new chemical probes of biological systems and leads for new drugs, a major challenge to the utility of such compounds is in connecting phenotype with a cellular target. Here, we present a systematic study to elucidate the mechanism of action of uncharacterized inhibitors of the growth of Escherichia coli through careful analyses of interactions with compounds of known biological activity. We studied growth inhibition with a collection of 200 antibacterial compounds when systematically combined with a panel of 14 known antibiotics of diverse mechanism and chemical class. Our work revealed a high frequency of synergistic chemical-chemical interactions where the interaction profiles were unique to the various compound pairs. Thus, the work revealed that chemical-chemical interaction data provides a fingerprint of biological activity and testable hypotheses regarding the mechanism of action of the novel bioactive molecules. In the study reported here, we determined the mode of action of an inhibitor of folate biosynthesis and a DNA gyrase inhibitor. Moreover, we identified eight membrane-active compounds, found to be promiscuously synergistic with known bioactives

Multitargeting Compounds: A Promising Strategy to Overcome Multi-Drug Resistant Tuberculosis

Tuberculosis is still an urgent global health problem, mainly due to the spread of multi-drug resistant M. tuberculosis strains, which lead to the need of new more efficient drugs. A strategy to overcome the problem of the resistance insurgence could be the polypharmacology approach, to develop single molecules that act on different targets. Polypharmacology could have features that make it an approach more effective than the classical polypharmacy, in which different drugs with high affinity for one target are taken together. Firstly, for a compound that has multiple targets, the probability of development of resistance should be considerably reduced. Moreover, such compounds should have higher efficacy, and could show synergic effects. Lastly, the use of a single molecule should be conceivably associated with a lower risk of side effects, and problems of drug-drug interaction. Indeed, the multitargeting approach for the development of novel antitubercular drugs have gained great interest in recent years. This review article aims to provide an overview of the most recent and promising multitargeting antitubercular drug candidates

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism