This record includes training materials associated with the Australian BioCommons webinar ‘AIcrs: AI-Designed Anti-CRISPRs as Programmable CRISPR Inhibitors’. This webinar took place on 12 August 2025 and is part of the series “Leveraging deep learning to design custom protein-binding proteins”.

Series description

Deep learning methods are speeding up the process of designing proteins with desirable biophysical properties. This fast moving field leverages computational workflows that integrate deep learning models like RFdiffusion, ProteinMPNN, Bindcraft with protein structural prediction methods (Alphafold, Chai-1, Boltz-2) and traditional structural biology methods to improve protein design success rates.

This webinar series features case studies from leaders in the field and is designed to inspire and help you recognise potential applications of this new approach to the design of protein-binding-proteins. Join us to hear how software such as Bindcraft is being applied to different research questions and gain hints and tips on using them in your own work. This series is brought to you by the Community for Structural Biology Computing in Australia.

Speaker: Dr Cynita Taveneau, Monash University

Host: Dr Melissa Burke, Australian BioCommons

Talk title: AIcrs: AI-Designed Anti-CRISPRs as Programmable CRISPR Inhibitors

Training materials

Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.

Files and materials included in this record:

• Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.

• Taveneau_2025_slides (PDF): A PDF copy of the slides presented during the webinar.

Materials shared elsewhere:

A recording of this webinar is available on the Australian BIoCommons YouTube channel: https://youtu.be/GSoOfyJUYSA