Polo: an open-source graphical user interface for crystallization screening.

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• Automated analysis of crystallization images is crucial for efficient drug discovery and materials science.
• Manual review of high-throughput crystallization screening images is time-consuming and prone to error.

Purpose of the Study:

• To introduce Polo, a Python-based graphical user interface (GUI) for streamlined viewing and analysis of crystal growth images.
• To enhance the efficiency and accuracy of identifying positive crystallization conditions in high-throughput screening.

Main Methods:

• Development of a user-friendly GUI with one-click integration for the Machine Recognition of Crystallization Outcomes (MARCO) convolutional neural network.
• Implementation of tools for image viewing, scoring, comparison of crystallization conditions, and collaborative review.

Main Results:

• Polo significantly reduces the time and effort required for manual inspection of crystallization images.
• The software facilitates improved identification of optimal crystallization conditions through automated classification and comparative analysis.

Conclusions:

• Polo offers a powerful and accessible solution for researchers involved in crystal growth monitoring and analysis.
• The software is freely available for academic and commercial use, promoting wider adoption and collaboration in the field.