Dataset Information

Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors.

ABSTRACT: Since the onset of global pandemic, the most focused research currently in progress is the development of potential drug candidates and clinical trials of existing FDA approved drugs for other relevant diseases, in order to repurpose them for the COVID-19. At the same time, several high throughput screenings of drugs have been reported to inhibit the viral components during the early course of infection but with little proven efficacies. Here, we investigate the drug repurposing strategies to counteract the coronavirus infection which involves several potential targetable host proteins involved in viral replication and disease progression. We report the high throughput analysis of literature-derived repurposing drug candidates that can be used to target the genetic regulators known to interact with viral proteins based on experimental and interactome studies. In this work we have performed integrated molecular docking followed by molecular dynamics (MD) simulations and free energy calculations through an expedite in silico process where the number of screened candidates reduces sequentially at every step based on physicochemical interactions. We elucidate that in addition to the pre-clinical and FDA approved drugs that targets specific regulatory proteins, a range of chemical compounds (Nafamostat, Chloramphenicol, Ponatinib) binds to the other gene transcription and translation regulatory proteins with higher affinity and may harbour potential for therapeutic uses. There is a rapid growing interest in the development of combination therapy for COVID-19 to target multiple enzymes/pathways. Our in silico approach would be useful in generating leads for experimental screening for rapid drug repurposing against SARS-CoV-2 interacting host proteins.Communicated by Ramaswamy H. Sarma.

SUBMITTER: Kumawat A

PROVIDER: S-EPMC8220434 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 is a virus that belongs to the Coronaviridae family. This group of viruses commonly causes colds but possesses a tremendous pathogenic potential. In humans, an outbreak of SARS caused by the SARS-CoV virus was first reported in 2003, followed by 2012 when the Middle East respiratory syndrome coronavirus (MERS-CoV) led to an outbreak of Middle East respiratory syndrome (MERS). Moreover, COVID-19 represents a serious socioeconomic and global health problem that has already claimed more than four million lives. To date, there are only a handful of therapeutic options to combat this disease, and only a single direct-acting antiviral, the conditionally approved remdesivir. Since there is an urgent need for active drugs against SARS-CoV-2, the strategy of drug repurposing represents one of the fastest ways to achieve this goal. An in silico drug repurposing study using two methods was conducted. A structure-based virtual screening of the FDA-approved drug database on SARS-CoV-2 main protease was performed, and the 11 highest-scoring compounds with known 3CLpro activity were identified while the methodology was used to report further 11 potential and completely novel 3CLpro inhibitors. Then, inverse molecular docking was performed on the entire viral protein database as well as on the Coronaviridae family protein subset to examine the hit compounds in detail. Instead of target fishing, inverse docking fingerprints were generated for each hit compound as well as for the five most frequently reported and direct-acting repurposed drugs that served as controls. In this way, the target-hitting space was examined and compared and we can support the further biological evaluation of all 11 newly reported hits on SARS-CoV-2 3CLpro as well as recommend further in-depth studies on antihelminthic class member compounds. The authors acknowledge the general usefulness of this approach for a full-fledged inverse docking fingerprint screening in the future.

Project description:Breast cancer is a leading cause of cancer-related morbidity and mortality worldwide, with the highest incidence among women. Among the various subtypes of breast cancer, estrogen-receptor positive (ER+) is the most diagnosed. Estrogen upregulates cyclin D1, which in turn promotes the activity of CDK4/6 and facilitates cell cycle progression. To address this, the first-line treatment for ER+ breast cancer focuses on inhibiting estrogen production by targeting aromatase, the enzyme responsible for the rate-limiting step in estrogen synthesis. Thus, combining CDK4/6 inhibitors with aromatase inhibitors has emerged as a crucial treatment strategy for this type of breast cancer. This approach effectively suppresses estrogen biosynthesis and controls uncontrolled cell proliferation, significantly improving overall survival rates and delayed disease progression. This study aimed to identify compounds that are likely to inhibit CDK4/6 and aromatase simultaneously by using a structure-based drug design strategy. 12,432 approved and investigational drugs were prepared and docked into the active site of CDK6 using HTVS and XP docking modes of Glide resulting in 277 compounds with docking scores ≤ -7 kcal/mol. These compounds were docked into aromatase enzyme using XP mode to give seven drugs with docking scores≤ -6.001 kcal/mol. Furthermore, the shortlisted drugs were docked against CDK4 showing docking scores ranging from -3.254 to -8.254 kcal/mol. Moreover, MM-GBSA for the top seven drugs was calculated. Four drugs, namely ellagic acid, carazolol, dantron, and apomorphine, demonstrated good binding affinity to all three protein targets CDK4/6 and aromatase. Specifically, they exhibited favourable binding free energy with CDK6, with values of -51.92, -53.90, -50.22, and -60.97 kcal/mol, respectively. Among these drugs, apomorphine displayed the most favourable binding free energy with all three protein targets. To further evaluate the stability of the interaction, apomorphine was subjected to a 100 ns molecular dynamics simulation with CDK6. The results indicated the formation of a stable ligand-protein complex. While the results obtained from the MM-GBSA calculation of the binding free energies of the MD conformations of apomorphine showed less favourable binding free energy compared to that obtained post-docking. All these computational findings will provide better structural insight for the development of CDK4/6 and aromatase multi-target inhibitors.

Dataset Information

Integrated docking and enhanced sampling-based selection of repurposing drugs for SARS-CoV-2 by targeting host dependent factors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets