Project description:During almost all 2020, coronavirus disease 2019 (COVID-19) pandemic has constituted the major risk for the worldwide health and economy, propelling unprecedented efforts to discover drugs for its prevention and cure. At the end of the year, these efforts have culminated with the approval of vaccines by the American Food and Drug Administration (FDA) and the European Medicines Agency (EMA) giving new hope for the future. On the other hand, clinical data underscore the urgent need for effective drugs to treat COVID-19 patients. In this work, we embarked on a virtual screening campaign against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mpro chymotrypsin-like cysteine protease employing our in-house database of peptide and non-peptide ligands characterized by different types of warheads acting as Michael acceptors. To this end, we employed the AutoDock4 docking software customized to predict the formation of a covalent adduct with the target protein. In vitro verification of the inhibition properties of the most promising candidates allowed us to identify two new lead inhibitors that will deserve further optimization. From the computational point of view, this work demonstrates the predictive power of AutoDock4 and suggests its application for the in silico screening of large chemical libraries of potential covalent binders against the SARS-CoV-2 Mpro enzyme.
Project description:Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (MPro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure-based techniques against MPro itself.
Project description:The global emergency caused by COVID-19 makes the discovery of drugs capable of inhibiting SARS-CoV-2 a priority, to reduce the mortality and morbidity of this disease. Repurposing approved drugs can provide therapeutic alternatives that promise rapid and ample coverage because they have a documented safety record, as well as infrastructure for large-scale production. The main protease of SARS-CoV-2 (Mpro) is an excellent therapeutic target because it is critical for viral replication; however, Mpro has a highly flexible active site that must be considered when performing computer-assisted drug discovery. In this work, potential inhibitors of the main protease (Mpro) of SARS-Cov-2 were identified through a docking-assisted virtual screening procedure. A total of 4384 drugs, all approved for human use, were screened against three conformers of Mpro. The ligands were further studied through molecular dynamics simulations and binding free energy analysis. A total of nine currently approved molecules are proposed as potential inhibitors of SARS-CoV-2. These molecules can be further tested to speed the development of therapeutics against COVID-19.
Project description:SARS-CoV-2 causes the current global pandemic coronavirus disease 2019. Widely-available effective drugs could be a critical factor in halting the pandemic. The main protease (3CLpro) plays a vital role in viral replication; therefore, it is of great interest to find inhibitors for this enzyme. We applied the combination of virtual screening based on molecular docking derived from the crystal structure of the peptidomimetic inhibitors (N3, 13b, and 11a), and experimental verification revealed FDA-approved drugs that could inhibit the 3CLpro of SARS-CoV-2. Three drugs were selected using the binding energy criteria and subsequently performed the 3CLpro inhibition by enzyme-based assay. In addition, six common drugs were also chosen to study the 3CLpro inhibition. Among these compounds, lapatinib showed high efficiency of 3CLpro inhibition (IC50 value of 35 ± 1 μM and Ki of 23 ± 1 μM). The binding behavior of lapatinib against 3CLpro was elucidated by molecular dynamics simulations. This drug could well bind with 3CLpro residues in the five subsites S1', S1, S2, S3, and S4. Moreover, lapatinib's key chemical pharmacophore features toward SAR-CoV-2 3CLpro shared important HBD and HBA with potent peptidomimetic inhibitors. The rational design of lapatinib was subsequently carried out using the obtained results. Our discovery provides an effective repurposed drug and its newly designed analogs to inhibit SARS-CoV-2 3CLpro.
Project description:The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 2,000,000 deaths worldwide. Currently, vaccine development and drug repurposing have been the main strategies to find a COVID-19 treatment. However, the development of new drugs could be the solution if the main strategies fail. Here, a virtual screening of pentapeptides was applied in order to identify peptides with high affinity to SARS-CoV-2 main protease (Mpro). Over 70,000 peptides were screened employing a genetic algorithm that uses a docking score as the fitness function. The algorithm was coupled with a RESTful API to persist data and avoid redundancy. The docking exhaustiveness was adapted to the number of peptides in each virtual screening step, where the higher the number of peptides, the lower the docking exhaustiveness. Two potential peptides were selected (HHYWH and HYWWT), which have higher affinity to Mpro than to human proteases. Albeit preliminary, the data presented here provide some basis for the rational design of peptide-based drugs to treat COVID-19.
Project description:Background: Conserved domains within SARS-CoV-2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS-CoV-2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three compounds were selected as coronavirus NSP5 inhibitors after passing absorption, distribution, metabolism, excretion and toxicity study; root and mean square deviation; and radius of gyration calculations. Conclusion: ZINC000049899562, ZINC000169336666 and ZINC000095542577 are potential NSP5 protease inhibitors that warrant further experimental studies.
Project description:Global health is under heavy threat by a worldwide pandemic caused by a new type of coronavirus (COVID-19) since its rapid spread in China in 2019 [1]. Currently, there are no approved specific drugs and effective treatment for COVID-19 infection, but several available drugs are known to facilitate tentative treatment. Since drug design, development and testing procedures are time-consuming [2], [1], [2], [3], virtual screening studies with the aid of available drug databases take the initiative at this point and save the time. Besides, drug repurposing strategies promises to identify new agents for the novel diseases in a time-critical fashion. In this study, we used structure based virtual screening method on FDA approved drugs and compounds in clinical trials. As a result of this study we choose three most prominent compounds for further studies. Here we show that these three compounds (dobutamine and its two derivatives) can be considered as promising inhibitors for SARS-CoV-2 main protease and results also demonstrate the possible interactions of dobutamine and its derivatives with SARS-CoV-2 main protease (6W63) [6]. Our efforts in this work directly address current urgency of a new drug discovery against COVID-19.
Project description:Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), threatens global public health. The world needs rapid development of new antivirals and vaccines to control the current pandemic and to control the spread of the variants. Among the proteins synthesized by the SARS-CoV-2 genome, main protease (Mpro also known as 3CLpro) is a primary drug target, due to its essential role in maturation of the viral polyproteins. In this study, we provide crystallographic evidence, along with some binding assay data, that three clinically approved anti hepatitis C virus drugs and two other drug-like compounds covalently bind to the Mpro Cys145 catalytic residue in the active site. Also, molecular docking studies can provide additional insight for the design of new antiviral inhibitors for SARS-CoV-2 using these drugs as lead compounds. One might consider derivatives of these lead compounds with higher affinity to the Mpro as potential COVID-19 therapeutics for further testing and possibly clinical trials.
Project description:The development of SARS-CoV-2 main protease (Mpro) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate Mpro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of Mpro. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using Mpro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of Mpro with low nanomolar Ki values. Furthermore, these compounds demonstrate efficacy against mutant forms of Mpro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.