Quinones are secondary metabolites of higher plants associated with many biological activities, including antiviral effects and cytotoxicity. In this study, the anti-herpetic and anti-dengue evaluation of 27 terpenyl-1,4-naphthoquinone (NQ), 1,4-anthraquinone (AQ) and heterocycle-fused quinone (HetQ) derivatives was done in vitro against Human Herpesvirus (HHV) type 1 and 2, and Dengue virus serotype 2 (DENV-2). The cytotoxicity on HeLa and Jurkat tumor cell lines was also tested. Using plaque forming unit assays, cell viability assays and molecular docking, we found that NQ 4 was the best antiviral compound, while AQ 11 was the most active and selective molecule on the tested tumor cells. NQ 4 showed a fair antiviral activity against Herpesviruses (EC₅₀: <0.4 µg/mL, <1.28 µM) and DENV-2 (1.6 µg/mL, 5.1 µM) on pre-infective stages. Additionally, NQ 4 disrupted the viral attachment of HHV-1 to Vero cells (EC₅₀: 0.12 µg/mL, 0.38 µM) with a very high selectivity index (SI = 1728). The in silico analysis predicted that this quinone could bind to the prefusion form of the E glycoprotein of DENV-2. These findings demonstrate that NQ 4 is a potent and highly selective antiviral compound, while suggesting its ability to prevent Herpes and Dengue infections. Additionally, AQ 11 can be considered of interest as a leader for the design of new anticancer agents.

Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.

Summary: myChEMBL is a completely open platform, which combines public domain bioactivity data with open source database and cheminformatics technologies. myChEMBL consists of a Linux (Ubuntu) Virtual Machine featuring a PostgreSQL schema with the latest version of the ChEMBL database, as well as the latest RDKit cheminformatics libraries. In addition, a self-contained web interface is available, which can be modified and improved according to user specifications. Availability and implementation: The VM is available at: ftp://ftp.ebi.ac.uk/pub/databases/chembl/VM/myChEMBL/current. The web interface and web services code is available at: https://github.com/rochoa85/myChEMBL. Contact:jpo@ebi.ac.uk