A comparative computational approach on the most deleterious missense variant in Connexin 43 protein and its potent inhibitor analysis

Intercellular communication between the cell plays an essential role in cell growth and cell formation, including migration, metabolism, and cell differentiation. Cell function and tissue homeostasis are maintained through gap junction intercellular communication (GJIC), thus regulating connexin hemichannels. Mis regulation of such connexin, especially connexin (Cx) 43, affects a comprehensive process, including cell differentiation, inflammation, and cell death. Mis regulation may be due to the missense variant in Cx43. Thus, we screened the complete set of mutations from public mutational databases and obtained 219 missense variants, which were then classified based on their pathogenicity, functional impact, stability, conservation, and physiochemical properties. Variant L214P was scrutinized to have the most deleterious, which was then modelled using the I-TASSER server and performed molecular docking analysis to screen potent inhibitors. The compound Kanamycin, Ginsenoside, and Astragaloside IV have better interactions with Cx43 mutant with a maximum of 5 hydrogen bonds. Ginsenoside is a compound that follows a Lipinski rule of five. Thus, the result obtained from this study suggests that Ginsenoside would be a better potent inhibitor for native and mutant Cx43.

Discovery of novel α2A adrenergic receptor agonists coupling to Gαi/o proteins by virtual screening / 中国药理学与毒理学杂志

Most α2-AR agonists derived from dexme-detomidine have few structure differences between them and have no selectivity for α2A/2B-AR or Gi/Gs,that can lead to the side effect of drugs.To get novel and potent α2A-AR agonists,we built the homology model for human α 2A-AR and α2B-AR to find α2A-AR agonists with higher selectivity.Compound P300-2342 and its 3 analogs sig-nificantly decreased the locomotor activity of mice(P＜0.05).Furthermore,P300-2342 and its 3 analogs inhibited the binding of[3H]rauwolscine to α 2A-AR and α 2B-AR respectively.In α2A-AR-HEK293 cells,P300-2342 decre-ased forskolinstimulatedcAMPpruductionwithoutincreas-ing cAMP pruduction,that indicated the P300-2342 acti-vating α2A-AR coupling with Gαi/o pathway without Gαs coupling.P300-2342 had no agonistic and antagonistic activities on α 2B-AR.Similar results were shown in 3 analogs of P300-2342.The docking results showed that P300-2342 formed the π-hydrogen bonds with Y394,V114 of α2A-AR,and with V93 of α2B-AR.3 analogs of P300-2342 formed several π-hydrogen bonds with V114,Y196,F390 of α 2A-AR and with V93 of α 2B-AR.We believe that these molecules can serve as leads for fur-ther optimization of α2A-AR agonists with potentially few side effects.

The Discovery of Putative Small Molecules via Ligand-based Pharmacophore Modelling Targeting Human Tau Protein for an Effective Treatment of Parkinson’s Disease

@#Introduction: The human tau protein is a key protein involved in various neurodegenerative disease (NDs) including Parkinson’s disease (PD). The protein has high tendency to aggregate into oligomers, subsequently generating insoluble mass in the brain. Symptoms of PD include tremor, bradykinesia, rigidity, and postural instability. Currently drugs for PD treatment are only symptom-targeted while effective therapeutic treatment remains a challenge. The objective of this study is to identify novel promising anti-PD drugs using computational techniques. Method: ligand-based (LB) receptor modelling was conducted using LigandScout, validated and subjected to Glide XP docking, virtual screening, ADMET, and molecular dynamics predictions. Results: The adopted LB modelling generated pharmacophoric features of 5 hydrogen bond donors, 1 aromatic rings, and 7 hydrogen bond acceptors. The validation result indicated GH score of 0.73 and EF of 36.30 as validation protocols, probing it to be an ideal model. Using 3D query of the modelling a total of 192 compounds were retrieved from interbioscreen database containing 70,436 natural compounds. Interestingly, ligands 1, 2, 3, 4 and 5 orderly indicated higher binding affinities to the receptor with Glide XP docking of -7.451, -7.368, -7.101, -6.878, and -6.789 compared to a clinical drug Anle138b with -4.552 kcal/mol respectively. Furthermore, molecular dynamics and pkCSM pharmacokinetics demonstrated ligands 1, 2, & 4 having better stability and low toxicity profiles compared to the reference. Conclusion: In summary, the study pave way for discovery of small molecules that could be recommended as adjuvant /single candidate as ant-PD candidates upon further translational study.

Virtual screening of potential ATR kinase inhibitors based on machine learning and molecular docking / 中国药科大学学报

@#Screening potential active compounds from molecular libraries is a common method for drug discovery.However, with the continuous exploration of chemical space, there are already compound libraries with more than billions of molecules, so molecular docking is no longer enough to quickly screen specific target inhibitors from the ultra-large compound libraries.This study proposes a method for screening potential active compounds, which involves filtering and selecting compounds from a candidate compound library containing over 5.5 billion molecules through a series of steps, including calculating physical and chemical property similarities, constructing machine learning prediction models, and molecular docking.In the end, 51 compounds with potential ataxia telangiectasia-mutated and rad3-related (ATR) inhibitory activity were obtained.This method is effective for rapidly screening novel potential active compounds from large compound libraries.

Discovery of new Schistosoma mansoni aspartyl protease inhibitors by structure-based virtual screening

BACKGROUND Schistosomiasis is a neglected tropical disease caused by trematodes of the genus Schistosoma, with a limited treatment, mainly based on the use of praziquantel (PZQ). Currently, several aspartic proteases genes have already been identified within the genome of Schistosoma species. At least one enzyme encoded from this gene family (SmAP), named SmCD1, has been validated for the development of schistosomicidal drugs, since it has a key role in haemoglobin digestion by worms. OBJECTIVE In this work, we integrated a structure-based virtual screening campaign, enzymatic assays and adult worms ex vivo experiments aiming to discover the first classes of SmCD1 inhibitors. METHODS Initially, the 3D-structures of SmCD1, SmCD2 and SmCD3 were generated using homology modelling approach. Using these models, we prioritised 50 compounds from 20,000 compounds from ChemBridge database for further testing in adult worm aqueous extract (AWAE) and recombinant SmCD1 using enzymatic assays. FINDINGS Seven compounds were confirmed as hits and among them, two compounds representing new chemical scaffolds, named 5 and 19, had IC50 values against SmCD1 close to 100 μM while presenting binding efficiency indexes comparable to or even higher than pepstatin, a classical tight-binding peptide inhibitor of aspartyl proteases. Upon activity comparison against mammalian enzymes, compound 50 was selective and the most potent against the AWAE aspartic protease activity (IC50 = 77.7 μM). Combination of computational and experimental results indicate that compound 50 is a selective inhibitor of SmCD2. Compounds 5, 19 and 50 tested at low concentrations (10 uM) were neither cytotoxic against WSS-1 cells (48 h) nor could kill adult worms ex-vivo, although compounds 5 and 50 presented a slight decrease on female worms motility on late incubations times (48 or 72 h). MAIN CONCLUSION Overall, the inhibitors identified in this work represent promising hits for further hit-to-lead optimisation.

Cryptosporidiosis, a public health challenge: A combined 3D shape-based virtual screening, docking study, and molecular dynamics simulation approach to identify inhibitors with novel scaffolds for the treatment of cryptosporidiosis

Cryptosporidiosis is a neglected tropical disease caused by the protozoan parasite Cryptosporidium parvum. Limited therapeutic options, limitation in in vitro parasite culture, and lack of a reliable animal model of parasite for replication of in vivo life cycle and drug testing demand alternative methods for drug development. The in silico methods of drug discovery prove a crucial process in such conditions.Recent research reported a limited number of small molecules for drug development. Purine nucleotide biosynthesis in Cryptosporidium species is dependent on the IMPDH (CpIMPDH) enzyme, so distortion of parasite IMPDH has been pursued as a compelling strategy for curbing Cryptosporidium infection due to its different kinetics from the host enzyme. Our study's primary aim was to discover novel ligand molecules with noticeable activity against Cryptosporidium parvum IMPDH. For this purpose, we selected 18 previously discovered ligands to understand the interaction feature between ligand and receptor, and their shape and electronic features are employed as a template for shape-based virtual screening of the ZINC database (drug-like subset) search approach via Schrodinger-2019 (Maestro 11.9). The obtained hits were subsequently subjected to structure-based screening, quantum polarized ligand docking (QPLD), and molecular dynamics simulations to fetch potential small molecules with the highest binding affinity for CpIMPDH protein. Further ligand binding energy and pharmacokinetic analysis were also taken into consideration as filtering criteria for selecting the most promising drug-like compounds. On this experimentation analysis, three top-ranked (ZINC24855054, ZINC58171263, and ZINC08000072) molecules were found to have appropriate pharmacokinetic properties along with surpassing in silico inhibitory potential towards the CpIMPDH compared to known inhibitors. The molecular docking and molecular dynamics simulation analysis results satisfactorily confirmed the inhibitory action. Therefore, these new scaffolds deduced by the presented computational methodology could recommend lead molecules for designing promising anti-cryptosporidial drugs targeting CpIMPDH protein.

Discovery of a small-molecule inhibitor of carbamoyl phosphate synthase 1 and its anti-colorectal cancer mechanism / 药学学报

The carbamoyl phosphate synthase 1 (CPS1) enzyme is involved in the first phase of the urea cycle, providing a prerequisite molecule for pyrimidine synthesis, as well as promoting tumor cell proliferation and growth. Studies have found that CPS1 is highly expressed in a variety of tumors, including colorectal cancer, lung cancer, etc. and its overexpression is related to the poor prognosis of tumors. Thus, small molecules targeted to inhibit the function of CPS1 in tumors may provide therapeutic benefits for cancer patients who overexpress CPS1. In this study, the function of CPS1 was investigated in vitro, and we found that overexpression of CPS1 can enhance the migration ability of colorectal cancer cells HCT15. Here, based upon the existing crystal structure, combined with high-throughput virtual screening, we obtained 8 candidate small molecule compounds. In vitro activity evaluation, we found that compound 3 has good anti-HCT15, HCT116 cell proliferation activity (HCT15, IC50, 7.69 ± 1.10 μmol‧L-1, HCT116, IC50, 13.53 ± 0.46 μmol‧L-1). Subsequently, molecular docking and molecular dynamics (MD) simulation analysis showed that, compound 3 could target and inhibit the activity of CPS1. In vitro studies showed that compound 3 could inhibit the migration of HCT15 cells, as well as induced cell cycle arrest and apoptosis. Taken together, this study found that compound 3 is a potential small molecule inhibitor that targets CPS1, which provides the experimental basis and theoretical basis for the development of targeted intervention small molecule therapeutic drugs. Based upon the chemical structure of compound 3, we will shed new light on further optimizing its activity and therapeutic potential, which may provide a therapeutic benefit to the patients with CPS1-related tumors.

Study on Q-markers of Da Chaihu decoction based on specific chromatogram and network pharmacology / 药学学报

Da Chaihu decoction is a classic prescription for the treatment of cholecystitis that is widely used in clinical practice, and has a definite curative effect. However, due to its diverse components and complex functions, the traditional indexes fail to capture its overall efficacy. Therefore, this study analyzed and predicted the quality markers (Q-markers) of Da Chaihu decoction based on specific chromatogram and network pharmacology to provide a reference for the comprehensive control of the quality. The study obtained 35 potential practical components of Da Chaihu decoction through virtual screening. The specific chromatogram of 15 batches of Da Chaihu decoction was established by HPLC-DAD with neohesperidin as a reference. Compared with the chromatographic peaks and the reference substance, the chemical components were assigned to predict the nine components of albiflorin, paeoniflorin, naringin, hesperidin, neohesperidin, baicalin, wogonoside, saikosaponin b2, saikosaponin b1 as Q-markers of Da Chaihu decoction. Finally, the network of the "components-key targets-signal pathways-biological processes" was constructed by network pharmacology to explore the mechanism of Da Chaihu decoction in treating cholecystitis to clarify the accuracy of Q-markers. The results indicated that potential Q-markers could act on multiple targets to regulate inflammatory and metabolism, and then combine to treat cholecystitis. Q-markers could combine with the pharmacologic action of Da Chaihu decoction, which could elucidate the overall efficacy of Da Chaihu decoction. This study explored the Q-markers of Da Chaihu decoction combined with the specific chromatogram and network pharmacology, which provided a basis for the quality control and evaluation of Da Chaihu decoction.

Acoplamiento molecular sobre la proteína dUTPasa de Trypanosoma cruzi para el descubrimiento de inhibidores en el tratamiento de la enfermedad de Chagas

Introducción: la enfermedad de Chagas es endémica de las zonas tropicales de América Latina y presenta una importante prevalencia, sin embargo, existen pocos tratamientos disponibles en el mercado por lo que la búsqueda de moléculas con potencial farmacológico que actúen en el parásito Trypanosoma cruzi, causante de la enfermedad, es necesaria considerando las graves complicaciones. Objetivo: evaluar las potenciales proteínas blanco, disponibles en la base de datos de PDB considerando como parámetro inicial, la similitud con proteínas humanas e identificar potenciales inhibidores del blanco elegido por medio de acoplamiento molecular. Metodología: se realizó una evaluación de las proteínas del parásito por medio de alineamiento de secuencias y posteriormente un cribado virtual por acoplamiento molecular con bases de datos y recursos informáticos disponibles en el Centro de Cómputo Avanzado de la Universidad de Texas (TACC), y se evaluaron los mejores resultados en función de afinidad, farmacocinética y toxicidad. Resultados: el blanco molecular elegido fue la dUTPasa. Posterior al cribado virtual se seleccionaron 12 moléculas que presentan potencial inhibidor de estas, la 4-{3-[3-(trifluorometil)fenil]isoxazol-5-il}pirimidin-2-amina es una de las moléculas con mejor perfil para convertirse en candidato en el tratamiento de la enfermedad de Chagas.

SUMMARY Introduction: Chagas disease is endemic to the tropical areas of Latin America and has an important prevalence, however, there are few treatments available in the market, so the search for molecules with pharmacological potential that can act in the same way as the disease, it is necessary considering the serious complications. Aim: to evaluate the possible target proteins available in the PDB database, considering the similarity with human proteins as an initial parameter and identify potential inhibitors of the chosen target using molecular docking. Methodology: an evaluation of the parasite proteins was carried out by means of sequence alignment and subsequently a virtual molecular coupling screening was performed with databases and computer resources available at Centro de Cómputo Avanzado de Universidad de Texas (TACC), and the best results were evaluated based on affinity, pharmacokinetics, and toxicity. Results: the molecular target chosen was the dUTPase. After virtual screening, 12 moles showing inhibitory potential were selected of these, 4- {3-[3- (trifluoromethyl) phenyl] isoxazole-5-yl} pyrimidine-2-amine is one of the molecules with the best profile to become a candidate in the treatment of Chagas disease.

Introdução: a doença de Chagas é endêmica das áreas tropicais da América Latina e possui importante prevalência, porém, poucos são os tratamentos disponíveis no mercado, por isso a busca por moléculas com potencial farmacológico que possam atuar da mesma forma que a doença, é necessário considerando as complicações graves. Objetivo: avaliar as possíveis proteínas-alvo disponíveis na base de dados do PDB, considerando a similaridade com proteínas humanas como parâmetro inicial e identificação de potenciais inibidores do alvo escolhido por meio de acoplamento molecular. Metodologia: uma avaliação das proteínas do parasita foi realizada por meio de alinhamento de sequências e posteriormente foi realizada uma triagem de acoplamento molecular virtual com bancos de dados e recursos computacionais disponíveis no Centro de Cómputo Avanzado de Universidad de Texas (TACC), e os melhores resultados foram avaliados com base na afinidade, farmacocinética e toxicidade. Resultados: o alvo molecular escolhido foi a dUTPase. Após a triagem virtual, 12 moles mostrando potencial inibitório foram selecionados destes, 4- {3- [3- (trifluorometil) fenil] isoxazol-5-il} pirimidina-2-amina é uma das moléculas com o melhor perfil para se tornar um candidato no tratamento da doença de Chagas.

In Silico Screening of DNA Gyrase B Potent Flavonoids for the Treatment of Clostridium difficile Infection from PhytoHub Database

Abstract Clostridium difficile infection (CDI) is the most common hospital acquired diarrheal disease with its increasing incidence and mortality rate globally. DNA Gyrase B (GyrB) is a key component of DNA replication process across all bacterial genera; thus, this offers a potential target for the treatment of CDI. In the present study, several virtual screening approaches were employed to identify a novel C. difficile GyrB inhibitor. The 139 known metabolites were screened out from the 480 flavonoids in PhytoHub database. Molinspiration and PROTOX II servers were used to calculate the ADME properties and oral toxicity of the metabolites, whereas mutagenicity, tumorigenicity, irritant, and reproductive effect were predicted using DataWarrior program. The binding mode and the binding efficiency of the screened flavonoids against the GyrB were studied using FlexX docking program. From virtual screening of 139 metabolites, we found 25 flavonoids with no mutagenicity, tumorigenicity, irritant, and reproductive effect. Docking study suggested that flavonoids 1030 ((-)-epicatechin 3'-O-sulfate), 1032 ((-)-epicatechin 4'-O-sulfate), 1049 (3'-O-methyl-(-)-epicatechin 4-O-sulfate), 1051 (3'-O-methyl-(-)-epicatechin 7-O-sulfate), 1055 (4'-O-methyl-(-)-epicatechin 7-O-sulfate) and 1317 (quercetin sulfate) have significantly higher binding affinity than the known GyrB inhibitor novobiocin. The results from molecular dynamics simulation and free energy calculations based on solvated interaction energy suggested that (-)-epicatechin 3'-O-sulfate could be a potential drug candidate in the management of CDI.

Corilagin inhibits SARS-CoV-2 replication by targeting viral RNA-dependent RNA polymerase

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has become one major threat to human population health. The RNA-dependent RNA polymerase (RdRp) presents an ideal target of antivirals, whereas nucleoside analogs inhibitor is hindered by the proofreading activity of coronavirus. Herein, we report that corilagin (RAI-S-37) as a non-nucleoside inhibitor of SARS-CoV-2 RdRp, binds directly to RdRp, effectively inhibits the polymerase activity in both cell-free and cell-based assays, fully resists the proofreading activity and potently inhibits SARS-CoV-2 infection with a low 50% effective concentration (EC

Preliminary screening of therapeutic drugs for phenylalanine hydroxylase deficiency / 中国基层医药

Objective:To screen new drugs for treatment of phenylalanine hydroxylase deficiency.Methods:From October 2019 to October 2020, virtual drug screening was performed in Center of Genetic Medicine, Nanjing Maternity and Child Health Care Hospital, Women's Hospital of Nanjing Medical University computer according to the characteristics of the binding ability of phenylalanine hydroxylase to drug spatial structure. Ten candidate drugs were screened from the FDA drug library (including 2 697 kinds of active pharmaceutical ingredients). A eukaryotic expression system was used to determine the effects of drugs on the activity of phenylalanine hydroxylase at the molecular level. Drug-sensitive mutants were screened.Results:Among the 10 candidate drugs, neoplasm hydrochloride, fluocinonide acetate and risperidone increased 23% [ t = 18.21, P < 0.001, vs. non-drug-treated phenylalanine hydroxylase group (i.e., only solvent and no drug added to the reaction system)], 21% ( t = 3.44, P < 0.05, vs. non-drug-treated phenylalanine hydroxylase group), 31% ( t = 19.57, P < 0.001, vs. non-drug-treated phenylalanine hydroxylase group) of the activity of phenylalanine hydroxylase. The remaining drugs exhibited weak even inhibitory effects on the activity of phenylalanine hydroxylase. 25% of p.D101N mutant could be activated by risperidone ( t = 15.86, P < 0.001, vs. non-drug-treated p.D101N mutant group). Conclusion:Neoplasm hydrochloride, fluocinonide acetate and risperidone can be used as potential therapeutic drugs for phenylalanine hydroxylase deficiency, and p.D101N mutant can be used as the drug-sensitive mutation site.

Progress on the application of artificial intelligence technology in ligand-based and receptor structure-based drug screening / 药学学报

Artificial intelligence technology is being widely applied in drug screening. This paper introduces the characteristics of artificial intelligence, and summarizes the application and progress of artificial intelligence technology especially deep learning in drug screening, from ligand-based and receptor structure-based aspects. This paper also introduces how to apply artificial intelligence to drug design from these two aspects. Finally, we discuss the main limitations, challenges, and prospects of artificial intelligence technology in the field of drug screening.

Construction of pharmacophore model and its application in identification of effective components of Chinese medicine / 中国中药杂志

The effective material basis of Chinese medicine is the key and difficult point in the quality control and modernization research of Chinese medicine. With the increasing application of pharmacophore-based virtual screening in computer-aided drug design, it is possible to employ this technology in the modernization of Chinese medicine. Based on the systematic research method of the pharmacophore model, the present study systematically reviewed the pharmacophore-based technologies and strategies in the identification of active components in Chinese medicine.

Drug repurposing against coronavirus disease 2019 (COVID-19):A review / 药物分析学报

Since December 2019,severe acute respiratory syndrome coronavirus 2 has been found to be the culprit in the coronavirus disease 2019 (COVID-19),causing a global pandemic.Despite the existence of many vaccine programs,the number of confirmed cases and fatalities due to COVID-19 is still increasing.Furthermore,a number of variants have been reported.Because of the absence of approved anti-coronavirus drugs,the treatment and management of COVID-19 has become a global challenge.Under these circumstances,drug repurposing is an effective method to identify candidate drugs with a shorter cycle of clinical trials.Here,we summarize the current status of the application of drug repurposing in COVID-19,including drug repurposing based on virtual computer screening,network pharmacology,and bioactivity,which may be a beneficial COVID-19 treatment.

Metabolomic study and in silico approach of DLBS1442 as progesterone receptor agonist

Endometriosis prevalence has been known to be quite high among women of reproductive age and with pelvic painand/or infertility. The reason is that the estrogen level in the eutopic endometrium of women with endometriosis ishigher than in normal endometrium which may possibly be caused by the lack of interaction between progesteroneand progesterone receptor (PR). Dexa Laboratories of Biomolecular Sciences (DLBS) has developed DLBS1442,a bioactive fraction from Phaleria macrocarpa (Scheff) Boerl fruit, which has been found to be potential to treatsymptoms of primary dysmenorrhea and alleviate endometriosis. Therefore, the identification of DLBS1442 activecompounds which act as a PR agonist was necessary. Identification was performed using metabolomics study whichresulted in 14 compounds. Crystal structure of the PR with asoprisnil as the reference was obtained from PDB (4A2J).Virtual screening validation process was performed using Protein-Ligand ANT System (PLANTS) and Pythonbased Protein-Ligand Interaction Fingerprinting (PyPLIF). According to the virtual screening protocol validation,the highest Enrichment Factor (EF) 1% value was obtained with hydrogen interaction with GLN725 and ARG766residue. Virtual screening of the DLBS1442 metabolomics study showed that only glyceryl pentacosanoate exhibited alower Chem Piecewise Linear Potential (ChemPLP) than the cutoff. This compound might have a role as a PR agonistwhich supported the previous findings of DLBS1442 to alleviate endometriosis. However, this finding requires furtherin vitro and/or in vivo study to ensure the agonist activity of glyceryl pentacosanoate as a DLBS1442 active compound.

Network pharmacology study on anti-stroke of Xiaoshuan Tongluo formula based on systematic compound-target interaction prediction models / 药学学报

Xiaoshuan Tongluo formula is effective in treating mental retardation and speech astringency caused by cerebral thrombosis, but its mechanism remains unclear. In this investigation, by collecting the chemical constituents from Xiaoshuan Tongluo formula and the targets related to stroke, we obtained 1 251 constituents from the formula and 10 drug targets related with stroke. We established 18 prediction models of compound-target interaction for 10 stroke-related targets, using molecular docking method and machine learning methods includes Naive Bayesian and recursive partitioning based on the input of molecular fingerprints and molecular descriptors. Using these models, we predicted the active chemical constituents from Xiaoshuan Tongluo formula and their drug targets, 153 potential active constituents were discovered, 22 among them could interact with at least two drug targets related with stroke. On this basis, the chemical constituent-target network was constructed using network construction software, and then the important metabolic pathways of the targets were identified by using Gene-Ontology (GO) enrichment analysis, such as blood coagulation, positive regulation of angiogenesis, positive regulation of ion transport and so on. On this basis, a target-pathway network was constructed. In conclusion, using machine learning, molecular docking, virtual screening, data mining and network construction, this study explored and partially revealed the active chemical constituents and chemical constituent-target-pathway network action mechanism of Xiaoshuan Tongluo formula against stroke, which will provide important information for its further study.

In Silico Screening of Potential Spike Glycoprotein Inhibitors of SARS-CoV-2 with Drug Repurposing Strategy / 中国结合医学杂志

OBJECTIVE@#To select potential molecules that can target viral spike proteins, which may potentially interrupt the interaction between the human angiotension-converting enzyme 2 (ACE2) receptor and viral spike protein by virtual screening.@*METHODS@#The three-dimensional (3D)-coordinate file of the receptor-binding domain (RBD)-ACE2 complex for searching a suitable docking pocket was firstly downloaded and prepared. Secondly, approximately 15,000 molecular candidates were prepared, including US Food and Drug Administration (FDA)-approved drugs from DrugBank and natural compounds from Traditional Chinese Medicine Systems Pharmacology (TCMSP), for the docking process. Then, virtual screening was performed and the binding energy in Autodock Vina was calculated. Finally, the top 20 molecules with high binding energy and their Chinese medicine (CM) herb sources were listed in this paper.@*RESULTS@#It was found that digitoxin, a cardiac glycoside in DrugBank and bisindigotin in TCMSP had the highest docking scores. Interestingly, two of the CM herbs containing the natural compounds that had relatively high binding scores, Forsythiae fructus and Isatidis radix, are components of Lianhua Qingwen (), a CM formula reportedly exerting activity against severe acute respiratory syndrome (SARS)-Cov-2. Moreover, raltegravir, an HIV integrase inhibitor, was found to have a relatively high binding score.@*CONCLUSIONS@#A class of compounds, which are from FDA-approved drugs and CM natural compounds, that had high binding energy with RBD of the viral spike protein. Our work provides potential candidates for other researchers to identify inhibitors to prevent SARS-CoV-2 infection, and highlights the importance of CM and integrative application of CM and Western medicine on treating COVID-19.

Design of drug-like hepsin inhibitors against prostate cancer and kidney stones

Hepsin, a transmembrane serine protease abundant in renal endothelial cells, is a promising therapeutic target against several cancers, particularly prostate cancer. It is involved in the release and polymerization of uromodulin in the urine, which plays a role in kidney stone formation. In this work, we design new potential hepsin inhibitors for high activity, improved specificity towards hepsin, and promising ADMET properties. The ligands were developed through a novel hierarchical pipeline. This pipeline explicitly accounts for off-target binding to the related serine proteases matriptase and HGFA (human hepatocyte growth factor activator). We completed the pipeline incorporating ADMET properties of the candidate inhibitors into custom multi-objective optimization functions. The ligands designed show excellent prospects for targeting hepsin the blood stream and the urine and thus enable key experimental studies. The computational pipeline proposed is remarkably cost-efficient and can be easily adapted for designing inhibitors against new drug targets.