Key elements to unlocking deep learning for structural biology identified by the Australian research community
In an inspired demonstration of collaboration, the Australian Structural Biology Computing Community has come together to publish the Australian Structural Biology Deep-Learning Infrastructure Roadmap. Taking a holistic view, that includes the existing challenges, critical research bottlenecks, and looking forward to a potential national strategy, this new research infrastructure roadmap has been developed by the community, for the community.
Enabled by advances in deep learning methods for protein structure prediction and de novo protein design, computational structural biology has rapidly emerged as a powerful technology driving innovation in both fundamental and translational science. The technology underpins breakthroughs in drug design, diagnostics, personalised medicine, and synthetic biology, though a limitation has been that effective use requires concentrated interdisciplinary expertise and access to specialised hardware.
To understand these challenges, the Australian Structural Biology Computing (ASBC) Community was formed and has come together to lead a national, collaborative approach. This community-driven initiative, partnered with Australian BioCommons, brings together a diverse group of experts from leading institutions around the country. Authors of the roadmap represent Structural Biology Facility, Mark Wainwright Analytical Centre at the University of New South Wales, Pawsey Supercomputing Research Centre, University of Queensland, Walter and Eliza Hall Institute of Medical Research (WEHI), the National Computational Infrastructure, Sydney Informatics Hub and the School of Medical Sciences at the University of Sydney, School of Biomedical Sciences at the University of Melbourne, and the Monash Biomedicine Discovery Institute at Monash University.
The roadmap outlines key deliverables that will expedite the availability and accessibility of structural biology approaches to researchers nationwide:
A dedicated community space to foster collaboration and share best-practice recommendations for software deployments, benchmarking, validations and insights developed within the community.
Community training resources to on-board diverse stakeholders within the context of computational structural biology and strengthen the national impact of community expertise. For example, the Leveraging deep learning to design custom protein-binding proteins webinar series.
National computational infrastructure built on increased hardware investment and a user platform to facilitate efficient, high-throughput utilisation of national computing resources and drive translational outcomes enabled by curated and validated computational structural biology technologies.
Alignment, integration and engagement with global best-practice efforts for computational structural biology infrastructure and research.
A robust, sovereign capability in computational structural biology and protein design will position Australian universities, research institutes, and industry at the forefront of global innovation.
Read the Australian Structural Biology Deep-Learning Infrastructure Roadmap
Join the Australian Structural Biology Computing Community
Watch the Community’s webinar series Leveraging deep learning to design custom protein-binding proteins