Virtual Screening of Chinese Medicine Small Molecule Compounds Targeting SARS-CoV-2 3CL Protease (3CL pro)

Computer especially AI-assisted drug virtual screening and design in traditional Chinese medicine

BACKGROUND

Traditional Chinese medicine (TCM), as a significant part of the global pharmaceutical science, the abundant molecular compounds it contains is a valuable potential source of designing and screening new drugs. However, due to the un-estimated quantity of the natural molecular compounds and diversity of the related problems drug discovery such as precise screening of molecular compounds or the evaluation of efficacy, physicochemical properties and pharmacokinetics, it is arduous for researchers to design or screen applicable compounds through old methods. With the rapid development of computer technology recently, especially artificial intelligence (AI), its innovation in the field of virtual screening contributes to an increasing efficiency and accuracy in the process of discovering new drugs.

PURPOSE

This study systematically reviewed the application of computational approaches and artificial intelligence in drug virtual filtering and devising of TCM and presented the potential perspective of computer-aided TCM development.

STUDY DESIGN

We made a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Then screening the most typical articles for our research.

METHODS

The systematic review was performed by following the PRISMA guidelines. The databases PubMed, EMBASE, Web of Science, CNKI were used to search for publications that focused on computer-aided drug virtual screening and design in TCM.

RESULT

Totally, 42 corresponding articles were included in literature reviewing. Aforementioned studies were of great significance to the treatment and cost control of many challenging diseases such as COVID-19, diabetes, Alzheimer's Disease (AD), etc. Computational approaches and AI were widely used in virtual screening in the process of TCM advancing, which include structure-based virtual screening (SBVS) and ligand-based virtual screening (LBVS). Besides, computational technologies were also extensively applied in absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction of candidate drugs and new drug design in crucial course of drug discovery.

CONCLUSIONS

The applications of computer and AI play an important role in the drug virtual screening and design in the field of TCM, with huge application prospects.

Targeting the HIV-1 Tat and Human Tat Protein Complex through Natural Products: An In Silico Docking and Molecular Dynamics Simulation Approach

Background:

Tat protein is considered essential for substantial HIV-1 replication, and is also required to break HIV-1 latency, resulting in productive HIV replication. The multifaceted regulatory role of HIV Tat and the fact that it is expressed in the early stages of HIV infection justify its potential as an anti-HIV drug target.

Objective:

The present study was undertaken with the aim to target HIV-1 Tat protein with natural compounds which could help in identifying potential inhibitors against HIV-1 Tat.

Methods:

In this study, we compared the binding of Tat protein and Human P-TEFb Tat protein complex (TPC) with phyto-steroids and terpenes to evaluate their potential for HIV-1 treatment. The docking ability of plant products with HIV-1 Tat and TPC was studied with respect to dissociation constant, geometric shape complementary score, approximate interface area, and binding energy using Patch dock and YASARA. Molecular dynamics simulation was set up to investigate the interactions of the natural compounds with Tat protein and human tat protein complex (TPC).

Results:

The binding energy and dissociation constant of Diosgenin, Catharanthine and Ginkgolide A with Tat and TPC were comparable to antiretroviral drugs, Maraviroc and Emtricitabine. The natural products, Diosgenin, Ginkgolide A and Catharanthine, showed the highest binding energy and were stable with Tat protein and TPC in the entire MD simulation run.

Conclusion:

The natural products, Diosgenin, Ginkgolide A and Catharanthine, showed highest binding energy and were stable with Tat protein and TPC in the entire MD simulation run. The binding energy and dissociation constant of Diosgenin, Catharanthine and Ginkgolide A with Tat and TPC were comparable to antiretroviral drugs, Maraviroc and Emtricitabine.

Key Glycosyltransferase Genes of Panax notoginseng: Identification and Engineering Yeast Construction of Rare Ginsenosides

Panax notoginseng is one of the most famous valuable medical plants in China, and its broad application in clinical treatment has an inseparable relationship with the active molecules, ginsenosides. Ginsenosides are glycoside compounds that have varied structures for the diverse sugar chain. Although extensive work has been done, there are still unknown steps in the biosynthetic pathway of ginsenosides. Here, we screened candidate glycosyltransferase genes based on the previous genome and transcriptome data of P. notoginseng and cloned the full length of 27 UGT genes successfully. Among them, we found that PnUGT33 could catalyze different ginsenoside substrates to produce higher polarity rare ginsenosides by extending the sugar chain. We further analyzed the enzymatic kinetics and predicted the catalytic mechanism of PnUGT33 by simulating molecular docking. After that, we reconstructed the biosynthetic pathway of rare ginsenoside Rg₃ and gypenoside LXXV in yeast. By combining the Golden Gate method and overexpressing the UDPG biosynthetic genes, we further improved the yield of engineering yeast strain. Finally, the shake-flask culture yield of Rg₃ reached 51 mg/L and the fed-batch fermentation yield of gypenoside LXXV reached 94.5 mg/L, which was the first and highest record.