A Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening

Virtual screening is receiving renewed attention in drug discovery, but progress is hampered by challenges on two fronts: handling the ever increasing sizes of libraries of drug-like compounds, and separating true positives from false positives. Here we developed a machine learning-enabled pipeline for large-scale virtual screening that promises breakthroughs on both fronts. By clustering compounds according to molecular properties and limited docking against a drug target, the full library was trimmed by 10-fold; the remaining compounds were then screened individually by docking; and finally a dense neural network was trained to classify the hits into true and false positives. As illustration, we screened for inhibitors against RPN11, the deubiquitinase subunit of the proteasome and a drug target for breast cancer.

Synthesis of Novel Halogenated Heterocyclic compounds and their uses as Target SARS-CoV-2 main Protease (Mpro) and Potential Anti-Covid-19

Since the first appearance of the coronavirus disease-2019 (COVID-19) in Wuhan, China, in December 2019, it has been spreading globally with devastating ramifications. The lack of anti-COVID-19 treatment to date warrants urgent research into potential therapeutic targets. Virtual drug screening techniques enable the identification of novel compounds that are capable of targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). The latter plays a fundamental role in mediating viral replication and transcription, rendering it an attractive drug target. In this study, twenty six novel halogenated, heterocyclic compounds, which can inhibit Mpro, were tested by molecular docking combined with molecular dynamics simulation. Three compounds showed the highest binding affinity to the protein active site and their binding modes coincide with that of Nelfinavir. The binding of the halogenated compounds to Mpro may inhibit the replication and transcription of SARS-CoV-2 and, ultimately, stop the virallife cycle. In times of dire need for anti-COVID-19 treatment, this study lays the groundwork for further experimental research to investigate the efficacy and potential medical uses of these compounds to treat COVID-19. Novel compounds including fused thiophene, pyrimidine and pyran derivatives were tested against human RNA N7-MTase (hRNMT) and selected viral N7-MTases such as SARS-CoV nsp14 and Vaccinia D1-D12 complex to evaluate their specificity and their molecular modeling was also studied in the aim of producing anti covid-19 target molecules.

Recombinant protein expression and purification experiments based on SARS-CoV-2 Mpro

Mpro is one of the most important drug targets of the novel Coronavirus. In this study, a series of potential compounds were obtained through virtual drug screening targeting Mpro. Using the key protease (Mpro) of SARS-COV-2 as the drug lead target for virtual drug screening has become a hot topic in current virus research. Mpro plays a key role in virus replication and transcription. Therefore, the key experimental strain of Escherichia coli containing Mpro is commonly used to inhibit drugs from Mpro. In this study, Mpro gene was located on peT-28A vector, and the size of the recombinant protein was about 36 kDa. The e. Coli expression strain BL21(DE3) containing Mpro was inoculated and cultured.