The COVID-19 caused by the SARS-CoV-2 virus was declared a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. At present, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein, and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations to identify possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br.

SummaryArguably, an important amount of scientific software development time is likely to be employed on user interfaces. In particular, science gateways have gained increasing interest from the e‐Science community. These gateways allow hiding the complexity of the underlying resources that give support to the management of scientific data and to the execution of scientific applications. Based on our previous experience with the development of science gateways for diverse application domains in the Brazilian national high‐performance computing network (SINAPAD), we have devised a rapid prototyping strategy to lower the barrier for scientific application developers to launch new science gateways. This strategy is based on two main tools. The first tool implements a gateway engine that can be configured by a small set of XML files. Such files completely define the desired functionality of a specific science gateway in the gateway engine. The gateway engine also offers other features not commonly found in related technologies, such as file sharing, data provenance tracking, and restricted anonymous access to underlying computational resources. The second tool implements both an editor and a packager for the aforementioned engine. This tool allows the developer to rapidly deploy and launch a new science gateway in ordinary Web application containers. In this paper, we present our results with the use of both tools in the SINAPAD network. We also discuss about the current limitations of both tools, as well as how we have been dealing with such limitations to provide a more comprehensive toolset to developers. Copyright © 2014 John Wiley & Sons, Ltd.

The COVID-19 caused by the SARS-CoV-2 virus was declared as a pandemic disease in March 2020 by the World Health Organization (WHO). Structure-Based Drug Design strategies based on docking methodologies have been widely used for both new drug development and drug repurposing to find effective treatments against this disease. In this work, we present the developments implemented in the DockThor-VS web server to provide a virtual screening (VS) platform with curated structures of potential therapeutic targets from SARS-CoV-2 incorporating genetic information regarding relevant non-synonymous variations. The web server facilitates repurposing VS experiments providing curated libraries of currently available drugs on the market. Currently, DockThor-VS provides ready-for-docking 3D structures for wild type and selected mutations for Nsp3 (papain-like, PLpro domain), Nsp5 (Mpro, 3CLpro), Nsp12 (RdRp), Nsp15 (NendoU), N protein and Spike. We performed VS experiments of FDA-approved drugs considering the therapeutic targets available at the web server to assess the impact of considering different structures and mutations in the identification of possible new treatments of SARS-CoV-2 infections. The DockThor-VS is freely available at www.dockthor.lncc.br.

Bioinformatics experiments are rapidly and constantly evolving due improvements in sequencing technologies. These experiments usually demand high performance computation and produce huge quantities of data. They also require different programs to be executed in a certain order, allowing the experiments to be modeled as workflows. However, users do not always have the infrastructure needed to perform these experiments. Our contribution is the integration of scientific workflow management systems and grid-enabled scientific gateways, providing the user with a transparent way to run these workflows in geographically distributed computing resources. The availability of the workflow through the gateway allows for a better usability of these experiments.

In this paper we present OSC, a scientific workflow specification language based on software architecture principles. In contrast with other approaches, OSC employs connectors as first-class constructs. In this way, we leverage reusability and compositionality in the workflow modeling process, specially in the configuration of mechanisms that manage non-functional attributes.Resumo. Este artigo apresenta OSC, uma linguagem de especificac ¸ão de workflows científicos baseada em princípios de arquitetura de software. Em contraposic ¸ão a outras abordagens, OSC emprega conectores como construc ¸ões de primeira classe. Desse modo, propicia-se uma maior capacidade de reuso e composicionalidade na modelagem de workflows, particularmente nas configurac ¸ões dos mecanismos que lidam com atributos não-funcionais.