In silico search for novel bacterial inhibitors targeting RNA polymerase switch region
Ali, Aliaa (2022-07-22)
In silico search for novel bacterial inhibitors targeting RNA polymerase switch region
Ali, Aliaa
(22.07.2022)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022080853230
https://urn.fi/URN:NBN:fi-fe2022080853230
Tiivistelmä
The arise of antibiotic-resistant bacterial strains in an alarming rate has increased the interest in the discovery of novel antibiotics. The rifamycins are a valuable class of antibiotics that target bacterial Ribonucleic Acid polymerase (RNAP) and are considered the first-line treatment for tuberculosis. Consequently, bacterial strains resistant to rifamycin constitute a public health threat. RNAP switch region is an attractive target for the development of new antibacterial agents as it lies away from the rifamycin binding region and thus the compounds that target the switch region would not show cross-resistance with rifamycins.
In this work, we developed a virtual screening pipeline to identify new bacterial RNAP inhibitors that target the enzyme switch region. The screening pipeline involved docking of the designated libraries using the Maestro Glide docking tool, and the compounds with the best docking scores were submitted for binding free energy calculations using the molecular mechanics-generalised born surface area (MM-GBSA)-based method. Moreover, a quantitative structure-activity relationship (QSAR) model was developed, and it was applied to predict the biological activity of the compounds with the most favourable calculated binding free energies. Based on the results of docking, MM-GBSA binding free energies and the activities predicted by the QSAR model, the most promising compounds were chosen to be evaluated by molecular dynamics (MD) simulations. The results of the MD simulation of each docked candidate compound in the RNAP binding site were compared with the MD simulations carried out with the apo protein and with a reference co-crystallized ligand in the RNAP binding site. The candidate compounds showing comparable binding to the RNAP site to the reference ligand were selected for further biological testing.
In this work, we developed a virtual screening pipeline to identify new bacterial RNAP inhibitors that target the enzyme switch region. The screening pipeline involved docking of the designated libraries using the Maestro Glide docking tool, and the compounds with the best docking scores were submitted for binding free energy calculations using the molecular mechanics-generalised born surface area (MM-GBSA)-based method. Moreover, a quantitative structure-activity relationship (QSAR) model was developed, and it was applied to predict the biological activity of the compounds with the most favourable calculated binding free energies. Based on the results of docking, MM-GBSA binding free energies and the activities predicted by the QSAR model, the most promising compounds were chosen to be evaluated by molecular dynamics (MD) simulations. The results of the MD simulation of each docked candidate compound in the RNAP binding site were compared with the MD simulations carried out with the apo protein and with a reference co-crystallized ligand in the RNAP binding site. The candidate compounds showing comparable binding to the RNAP site to the reference ligand were selected for further biological testing.