Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows

We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.Fil: Goncearenco, Alexander. National Institutes of Health; Estados UnidosFil: Li, Minghui. Soochow University; China. National Institutes of Health; Estados UnidosFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Shoemaker, Benjamin A. National Institutes of Health; Estados UnidosFil: Panchenko, Anna R. National Institutes of Health; Estados Unido

Bio- and chemoinformatics approaches for metabolomics data analysis.

Metabolomics data analysis includes several repetitive tasks, including data sorting, calculation of exact masses or other physicochemical properties, or searching for identifiers in different databases. Several of these tasks can be automated using command line tools or short scripts in different scripting languages like Perl, Python, or R. This chapter presents simple solutions and short scripts written in R that can be used for the interaction with specific web services or for the calculation of physicochemical properties or molecular formulae

ImmunoNodes – graphical development of complex immunoinformatics workflows

Background: Immunoinformatics has become a crucial part in biomedical research. Yet many immunoinformatics tools have command line interfaces only and can be difficult to install. Web-based immunoinformatics tools, on the other hand, are difficult to integrate with other tools, which is typically required for the complex analysis and prediction pipelines required for advanced applications. Result We present ImmunoNodes, an immunoinformatics toolbox that is fully integrated into the visual workflow environment KNIME. By dragging and dropping tools and connecting them to indicate the data flow through the pipeline, it is possible to construct very complex workflows without the need for coding. Conclusion: ImmunoNodes allows users to build complex workflows with an easy to use and intuitive interface with a few clicks on any desktop computer