Abstract: This study uses an in silico screening docking model to evaluate the ACE2 inhibitory activity of natural compounds and drugs. The study collected 49 compounds and evaluated the ACE2 inhibitory effect in silico. The study results show that 11 out of the 49 compounds had stronger inhibitory activity on ACE2 than MLN-4760. Lipinski’s rule of five criteria and predictive pharmacokinetic-toxicity analysis show that eight compounds including quercetin, galangin, quisinostat, fluprofylline, spirofylline, RS 504393, TNP and GNF-5 had drug-likeness. These compounds could be potential drug for the Covid-19 treatment. Keywords SARS-CoV-2S, Covid-19, ACE2, molecular docking, in silico. References [[1] C. Wang, P.W. Horby, F.G. Hayden, G.F. Gao. A novel coronavirus outbreak of global health concern. The Lancet 395(10223) (2020) 470.[2] WHO. WHO Coronavirus Disease (COVID-19) Dashboard. WHO, 2020.[3] N. Chen, M. Zhou, X. Dong, J. Qu, F. Gong, Y. Han, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet 395(10223) (2020) 507.[4] J. Yang, Y. Zheng, X. Gou, K. Pu, Z. Chen, Q. Guo, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. International Journal of Infectious Diseases 94 (2020) 91.[5] R. Lu, X. Zhao, J. Li, P. Niu, B. Yang, H. Wu, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet 395(10224) (2020) 565.[6] R. Hilgenfeld. From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design. The FEBS journal 281(18) (2014) 4085.[7] D. Wrapp, N. Wang, K.S. Corbett, J.A. Goldsmith, C.L. Hsieh, O. Abiona, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science (New York, NY) 367(6483) (2020) 1260.[8] P.A. Rota, M.S. Oberste, S.S. Monroe, W.A. Nix, R. Campagnoli, J.P. Icenogle, et al. Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science (New York, NY) 300(5624) (2003) 1394.[9] M. Donoghue, F. Hsieh, E. Baronas, K. Godbout, M. Gosselin, N. Stagliano, et al. A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9. Circulation research 87(5) (2000) E1.[10] H. Zhang, Z. Kang, H. Gong, D. Xu, J. Wang, Z. Li, et al. The digestive system is a potential route of 2019-nCov infection: a bioinformatics analysis based on single-cell transcriptomes. bioRxiv (2020) 2020.01.30.927806.[11] Y. Zhao, Z. Zhao, Y. Wang, Y. Zhou, Y. Ma, W. Zuo. Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov. bioRxiv (2020) 2020.01.26.919985.[12] E.I. Bahbah, A. Negida, M.S. Nabet. Purposing Saikosaponins for the treatment of COVID-19. Med Hypotheses 140 (2020) 109782.[13] I.W. Cheung, S. Nakayama, M.N. Hsu, A.G. Samaranayaka, E.C. Li-Chan. Angiotensin-I converting enzyme inhibitory activity of hydrolysates from oat (Avena sativa) proteins by in silico and in vitro analyses. Journal of agricultural and food chemistry 57(19) (2009) 9234.[14] T. Joshi, T. Joshi, P. Sharma, S. Mathpal, H. Pundir, V. Bhatt, et al. In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking. European review for medical and pharmacological sciences 24(8) (2020) 4529.[15] S. Shahid, A. Kausar, M. Khalid, S. Tewari, T. Alghassab, T. Acar, et al. analysis of binding properties of angiotensin-converting enzyme 2 through in silico molecular docking, 2018.[16] K. Teralı, B. Baddal, H.O. Gülcan. Prioritizing potential ACE2 inhibitors in the COVID-19 pandemic: Insights from a molecular mechanics-assisted structure-based virtual screening experiment. J Mol Graph Model 100 (2020) 107697.[17] M. Muchtaridi, M. Fauzi, N.K. Khairul Ikram, A. Mohd Gazzali, H.A. Wahab. Natural Flavonoids as Potential Angiotensin-Converting Enzyme 2 Inhibitors for Anti-SARS-CoV-2. Molecules 25(17) (2020) 3980.[18] M.J. Huentelman, J. Zubcevic, J.A. Hernández Prada, X. Xiao, D.S. Dimitrov, M.K. Raizada, et al. Structure-based discovery of a novel angiotensin-converting enzyme 2 inhibitor. Hypertension (Dallas, Tex : 1979) 44(6) (2004) 903.[19] S. Choudhary, Y.S. Malik, S. Tomar. Identification of SARS-CoV-2 Cell Entry Inhibitors by Drug Repurposing Using in silico Structure-Based Virtual Screening Approach. Front Immunol 11((2020) 1664.[20] C.A. Lipinski. Lead-and drug-like compounds: the rule-of-five revolution. Drug Discovery Today: Technologies 1(4) (2004) 337.[21] B. Jayaram, T. Singh, G. Mukherjee, A. Mathur, S. Shekhar, V. Shekhar, Eds. Sanjeevini: a freely accessible web-server for target directed lead molecule discovery. Proceedings of the BMC bioinformatics; 2012. Springer (Year).[22] D.E. Pires, T.L. Blundell, D.B. Ascher. pkCSM: predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of medicinal chemistry 58(9) (2015) 4066.[23] P. Towler, B. Staker, S.G. Prasad, S. Menon, J. Tang, T. Parsons, et al. ACE2 X-ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis. The Journal of biological chemistry 279(17) (2004) 17996.[24] N.A. Dales, A.E. Gould, J.A. Brown, E.F. Calderwood, B. Guan, C.A. Minor, et al. Substrate-based design of the first class of angiotensin-converting enzyme-related carboxypeptidase (ACE2) inhibitors. Journal of the American Chemical Society 124(40) (2002) 11852.[25] P. Pandey, J.S. Rane, A. Chatterjee, A. Kumar, R. Khan, A. Prakash, et al. Targeting SARS-CoV-2 spike protein of COVID-19 with naturally occurring phytochemicals: an in silico study for drug development. Journal of Biomolecular Structure and Dynamics (2020) 1.[26] C.A. Lipinski. Lead- and drug-like compounds: the rule-of-five revolution. Drug discovery today Technologies 1(4) (2004) 337.[27] R.O. Barros, F.L. Junior, W.S. Pereira, N.M. Oliveira, R.M. Ramos. Interaction of drug candidates with various SARS-CoV-2 receptors: An in silico study to combat COVID-19. Journal of Proteome Research (2020).  

Abstract: With over 1 million incidence cases and more than 780,000 deaths in 2018, gastric cancer (GC) was ranked as the 5th most common cancer and the 3rd leading cause of cancer deaths worldwide. Though several biomarkers, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4), have been identified, their diagnostic accuracies were modest. Circulating tumor cells (CTCs), cells derived from tumors and present in body fluids, have recently emerged as promising biomarkers, diagnostically and prognostically, of cancers, including GC. In this review, we present the landscape of CTCs from migration, to the presence in circulation, biologic properties, and morphologic heterogeneities. We evaluated clinical implications of CTCs in GC patients, including diagnosis, prognosis, and therapeutic management, as well as their application in immunotherapy. On the one hand, major challenges in using CTCs in GC were analyzed, from the differences of cut-off values of CTC positivity, to techniques used for sampling, storage conditions, and CTC molecular markers, as well as the unavailability of relevant enrichment and detection techniques. On the other hand, we discussed future perspectives of using CTCs in GC management and research, including the use of circulating tumor microembolies; of CTC checkpoint blockade in immunotherapy; and of organoid models. Despite the fact that there are remaining challenges in techniques, CTCs have potential as novel biomarkers and/or a non-invasive method for diagnostics, prognostics, and treatment monitoring of GC, particularly in the era of precision medicine.

Abstract: One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Abstract: Multi-target drug development has become an attractive strategy in the discovery of drugs to treat of Alzheimer’s disease (AzD). In this study, for the first time, a rule-based machine learning (ML) approach with classification trees (CT) was applied for the rational design of novel dual-target acetylcholinesterase (AChE) and β-site amyloid-protein precursor cleaving enzyme 1 (BACE1) inhibitors. Updated data from 3524 compounds with AChE and BACE1 measurements were curated from the ChEMBL database. The best global accuracies of training/external validation for AChE and BACE1 were 0.85/0.80 and 0.83/0.81, respectively. The rules were then applied to screen dual inhibitors from the original databases. Based on the best rules obtained from each classification tree, a set of potential AChE and BACE1 inhibitors were identified, and active fragments were extracted using Murcko-type decomposition analysis. More than 250 novel inhibitors were designed in silico based on active fragments and predicted AChE and BACE1 inhibitory activity using consensus QSAR models and docking validations. The rule-based and ML approach applied in this study may be useful for the in silico design and screening of new AChE and BACE1 dual inhibitors against AzD.

Abstract: During the global COVID pandemic, the importance of professionals in the health care sector has been put in a new light, including pharmacists. In this context, the focus is also on how pharmacists are trained in different countries. Through an exchange of pharmacy teaching staff from a German to a Vietnamese university, the pharmacy education programs in both countries were compared. Aspects such as access to studies, structure of studies, and further training opportunities were considered. Differences and similarities emerged. In both countries, students first acquire basic knowledge and then delve deeper into pharmaceutical content in main studies. There is, expectedly, a great overlap in the content of the courses. Overall, the education at Vietnamese universities seems to be more practice-oriented due to a large number of placements. This also allows a specialization, which can be pursued in Germany with self-interest after graduation. There, the preparation for everyday work in the community pharmacy is separated from the university by a mandatory practical year. For the future, efforts are being made in both countries to strengthen the importance of clinical pharmacy in the curriculum. To this end, the Vietnamese are taking their inspiration from abroad in many cases, including Germany.

Abstract: Two series of 3‐[(1‐benzyl‐1 H ‐1,2,3‐triazol‐4‐yl)methyl]quinazolin‐4(3 H )‐ones and N ‐(1‐benzylpiperidin‐4‐yl)quinazolin‐4‐amines were designed initially as potential acetylcholine esterase inhibitors. Biological evaluation demonstrated that N ‐(1‐benzylpiperidin‐4‐yl)quinazolin‐4‐amines significantly inhibited AChE activity. Especially, two compounds of them were found to be the most potent with relative AChE inhibition percentages of 87 % in comparison to donepezil. The docking studies with AChE showed similar interactions between donepezil and four derivatives. N ‐(1‐Benzylpiperidin‐4‐yl)quinazolin‐4‐amines also exhibited significant DPPH scavenging effects. The two series of compound also exerted moderate to good cytotoxicity against three human cancer cell lines, including SW620 (human colon cancer), PC‐3 (prostate cancer), and NCI−H23 (lung cancer), with 3‐[(1‐benzyl‐1 H ‐1,2,3‐triazol‐4‐yl)methyl]quinazolin‐4(3 H )‐one being the most cytotoxic agent. 3‐[(1‐Benzyl‐1 H ‐1,2,3‐triazol‐4‐yl)methyl]quinazolin‐4(3 H )‐one significantly induced early apoptosis and arrested the SW620 cells at G2/M phase. From this study, two compounds of N ‐(1‐benzylpiperidin‐4‐yl)quinazolin‐4‐amines could serve as new leads for further design and AChE inhibitors, while 3‐[(1‐benzyl‐1 H ‐1,2,3‐triazol‐4‐yl)methyl]quinazolin‐4(3 H )‐one could serve as a new lead for the design and development of more potent anticancer agents.