The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

Chemoinformatics of Natural Products

Используемые программы Adobe AcrobatVol. 2 of Chemoinformatics of Natural Products introduces the reader to the currently available tools for toxicity prediction, drug property prediction, an enumeration of compounds, scaffolds and functional groups in nature, computational methods for lead identification, metabolite biosynthesis, etc. Selected case studies and hands-on tutorial exercises have been included.Том 2 "Хемоинформатики натуральных продуктов" знакомит читателя с доступными в настоящее время инструментами прогнозирования токсичности, свойств лекарственных средств, перечнем соединений, каркасов и функциональных групп в природе, вычислительными методами идентификации свинца, биосинтеза метаболитов и т.д. Были включены отдельные тематические исследования и практические обучающие упражнения

A primer on natural product-based virtual screening

Databases play an important role in various computational techniques, including virtual screening (VS) and molecular modeling in general. These collections of molecules can contain a large amount of information, making them suitable for several drug discovery applications. For example, vendor, bioactivity data or target type can be found when searching a database. The introduction of these data resources and their characteristics is used for the design of an experiment. The description of the construction of a database can also be a good advisor for the creation of a new one. There are free available databases and commercial virtual libraries of molecules. Furthermore, a computational chemist can find databases for a general purpose or a specific subset such as natural products (NPs). In this chapter, NP database resources are presented, along with some guidelines when preparing an NP database for drug discovery purposes. © 2019 Walter de Gruyter GmbH, Berlin/Boston 2019

1-Aryl-1,2,3,4-tetrahydroisoquinolines as potential antimalarials : synthesis, in vitro antiplasmodial activity and in silico pharmacokinetics evaluation

In the present study, twenty-one 1-aryl-6-hydroxy-1,2,3,4-tetrahydroisoquinoline (THIQ) analogues were synthesized by base-catalyzed Pictet-Spengler reaction, and tested in vitro against P. falciparum using the [H-3] hypoxanthine incorporation assay. Two compounds were found to be inactive while seventeen compounds displayed moderate antiplasmodial activity and two compounds were found to be highly active (IC50 > 0.2 mu g ml(-1)). The two highly active compounds, 1-(4-chlorophenyl)-6-hydroxyl-1,2,3,4tetrahydroisoquinoline and 6-hydroxyspiro[1,2,3,4-tetrahydroisoquinoline-1:1'-cyclohexane], also displayed low cytotoxicity, against rat skeletal myoblast cells, with CC50 values of 257.6 and 174.2 mu M respectively. These results justify further investigation of simple 1-aryl-1,2,3,4-tetrahydroisoquinolines as potential anti-malarial agent

Pharmacophore modeling and in silico toxicity assessment of potential anticancer agents from African medicinal plants

Fidele Ntie-Kang,1,2,* Conrad Veranso Simoben,1,2,* Berin Karaman,1 Valery Fuh Ngwa,3 Philip Neville Judson,4 Wolfgang Sippl,1 Luc Meva’a Mbaze5 1Department of Pharmaceutical Chemistry, Martin-Luther University of Halle-Wittenberg, Halle (Saale), Germany; 2Department of Chemistry, University of Buea, Buea, Cameroon; 3Interuniversity Institute For Biostatistics and Statistical Bioinformatics (I-BioStat), University of Hasselt, Hasselt, Belgium; 4Chemical Bioactivity Information Centre, Harrogate, UK; 5Department of Chemistry, Faculty of Science, University of Douala, Douala, Cameroon *These authors contributed equally to this work Abstract: Molecular modeling has been employed in the search for lead compounds of chemotherapy to fight cancer. In this study, pharmacophore models have been generated and validated for use in virtual screening protocols for eight known anticancer drug targets, including tyrosine kinase, protein kinase B β, cyclin-dependent kinase, protein farnesyltransferase, human protein kinase, glycogen synthase kinase, and indoleamine 2,3-dioxygenase 1. Pharmacophore models were validated through receiver operating characteristic and Güner–Henry scoring methods, indicating that several of the models generated could be useful for the identification of potential anticancer agents from natural product databases. The validated pharmacophore models were used as three-dimensional search queries for virtual screening of the newly developed AfroCancer database (~400 compounds from African medicinal plants), along with the Naturally Occurring Plant-based Anticancer Compound-Activity-Target dataset (comprising ~1,500 published naturally occurring plant-based compounds from around the world). Additionally, an in silico assessment of toxicity of the two datasets was carried out by the use of 88 toxicity end points predicted by the Lhasa’s expert knowledge-based system (Derek), showing that only an insignificant proportion of the promising anticancer agents would be likely showing high toxicity profiles. A diversity study of the two datasets, carried out using the analysis of principal components from the most important physicochemical properties often used to access drug-likeness of compound datasets, showed that the two datasets do not occupy the same chemical space. Keywords: anticancer, natural products, medicinal plants, pharmacophore, toxicity, virtual screenin