Protein Structure Prediction with NovaFold AI
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Conclusion
Knowledge of the tertiary structures of proteins is crucial to understanding protein function, but the traditional laboratory methods of determining these structures cannot keep up with demand. In response to this bottleneck, computer algorithms that can predict the structure of a protein based on its sequence have been developed and have become exponentially more accurate in recent years. The best algorithms today are almost as accurate as laboratory analyses like x-ray crystallography and NMR spectroscopy.
Since winning CASP14 in 2020, the AlphaFold 2 algorithm has captivated protein scientists with its unprecedented speed and its ability to accurately predict the structures of difficult molecules. But while this algorithm is free for public use, it requires expensive, specialized computing resources to install and run, as well as an operator who is comfortable running complex command-line scripts. Furthermore, the open source version of the AlphaFold 2 algorithm does not provide a utility for viewing the finished prediction, meaning that an additional application must be mastered for the analysis portion of the workflow.
DNASTAR has removed these obstacles by offering a way to use AlphaFold 2 from any Windows or Mac laptop. NovaFold AI uses the intuitive Protean 3D interface for effortless setup and prediction status monitoring, and for viewing and analyzing the predicted models. The prediction itself takes place “behind the scenes” in the secure Amazon (AWS) cloud, freeing up computing resources for other tasks.
“I have used NovaFold AI to generate models for a variety of chimeric proteins. The ability of NovaFold AI to predict the structure of complex proteins with multiple domains is impressive, in particular with those containing transmembrane domains and domains sourced from different proteins. The software is easy to use.”
Patricia Langan PhD
Senior Scientist
Miltenyi Biotec, USA
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