Efficient Management of High-Throughput Screening Libraries with SAVANAH

Organizing a crystallization laboratory

Managing chemical stocks and samples in any laboratory is an arduous task; in a crystallization laboratory this is particularly burdensome, given the need for many stocks to facilitate optimization of crystal hits obtained from screening experiments. Although inventory management is widespread in retail and other arenas, most small academic laboratories do not adopt formal stock management systems. Without an overarching system for handling stocks and samples, problems such as stock duplication, inappropriate stock storage and insufficient labelling are rife. Two applications have been developed in the Collaborative Crystallization Centre, the first of which manages the hundreds of stocks used for crystallization, and a second which manages protein (and other) samples stored in the 193 K freezer. Both applications are built around a simple database, with a Python front end that allows samples or stocks to be scanned in or out. Information from a decade of crystallization stock usage allows a good estimation of what chemicals are used (and in what quantities) in a crystallization laboratory.

Using Docker Compose for the Simple Deployment of an Integrated Drug Target Screening Platform

Docker virtualization allows for software tools to be executed in an isolated and controlled environment referred to as a container. In Docker containers, dependencies are provided exactly as intended by the developer and, consequently, they simplify the distribution of scientific software and foster reproducible research. The Docker paradigm is that each container encapsulates one particular software tool. However, to analyze complex biomedical data sets, it is often necessary to combine several software tools into elaborate workflows. To address this challenge, several Docker containers need to be instantiated and properly integrated, which complicates the software deployment process unnecessarily. Here, we demonstrate how an extension to Docker, Docker compose, can be used to mitigate these problems by providing a unified setup routine that deploys several tools in an integrated fashion. We demonstrate the power of this approach by example of a Docker compose setup for a drug target screening platform consisting of five integrated web applications and shared infrastructure, deployable in just two lines of codes.