Nuclera wants to use Google DeepMind to expedite the drug discovery process &Vertex AI’s AlphaFold2
The rapid protein access benchtop system from Nuclera, a biotechnology company based in the US and the UK, is being combined with AlphaFold2 (ref 1), a ground-breaking protein structure prediction tool from Google DeepMind, to serve the life science community. AlphaFold2 is hosted on Google Cloud’s Vertex AI machine learning platform.
Since proteins make about 95% of therapeutic targets, there is a growing need to generate various variants of active proteins to facilitate drug development. In particular, the discovery of compounds and biological leads requires accurate protein structure prediction.
The structural biology and drug development industries have been enthralled by AlphaFold2, a groundbreaking artificial intelligence tool that DeepMind published in 2021, since it represents a significant advancement in the accuracy of protein structure prediction (ref 2).
Combining the technologies of Google and Nuclera offers drug developers a new integrated approach to enhance protein construct creation and speed up the drug discovery process. Laser-guided protein design will soon be possible with the availability of high grade structures in a matter of minutes or hours. Furthermore, available will be dependable structures for proteins deemed “impossible” to describe experimentally.
Producing meaningful protein
Drug development relies heavily on the accessibility of proteins for lab-based research, which is notoriously expensive and difficult to acquire, placing time and budget constraints on research potential.
With its benchtop eProtein Discovery technology, Nuclera enables life science researchers to extract active proteins from DNA with the goal of improving human health. By combining digital microfluidics with cell-free protein synthesis on Smart Cartridges, Nuclera’s technology enables quick development on protein projects using an automated, high-throughput benchtop protein access system.
How Nuclera’s AlphaFold2 fits in: guided protein design
AlphaFold2 is an artificial intelligence (AI) model created by DeepMind that predicts the 3D structure of a protein based on its 1D amino acid sequence. It has been widely lauded as a breakthrough in biological research and a step forward in the production of vaccines and synthetic materials.
Nuclera’s cloud-based software will use AlphaFold2, which runs on Google Cloud’s Vertex AI, as a key component to enhance the quality and obtainability of proteins. With the use of Nuclera’s cloud software, users may now determine the best protein designs and conditions for protein scaling based on the results of expression and purification screens.
By providing an additional in silico filter during the experiment design phase, AlphaFold2’s integration with the eProtein Discovery Software improves the quality of constructs screened on the system and increases the likelihood of finding a truly optimal target protein on which to develop discovery programs. Moreover, AlphaFold2 will give users of eProtein Discovery profound insights into potential target protein designs, including any effects on folding, structural characteristics, and drug interactions.
Alphafold2 implementation on Vertex AI pipelines
Even though the AlphaFold2 algorithm has enormous potential, it’s vital to remember that it needs an operational model and serving infrastructure.
Predicting the structure of a protein requires a lot of computing power. Scaling up inference workflows can present difficulties, including as managing experiments, maximizing hardware resource consumption, and minimizing inference elapsed time.
In order to enable inference at scale, the Vertex AI solution for AlphaFold 2 prioritizes the following optimizations:
Parallelizing separate phases in the inference pipeline optimizes it.
utilizing the best hardware platform for each stage to maximize hardware usage and, consequently, expenses. The solution automatically provisioned and deprovisioned the computing resources needed for a step as part of this optimization.
presenting a strategy to experiment tracking that is both flexible and resilient, making it easier to execute and analyze hundreds of concurrent inference operations.
In order to create a scalable and resource-efficient AlphaFold pipeline, Nuclera will leverage the Vertex AI platform. Additionally, the company will leverage other Google Cloud services to expose the pipeline via an API and link it with its eProtein Discovery system.
What does the implementation setup entail?
The first goal that AlphaFold2 and Nuclera will accomplish is building a scalable API service that will allow users to access an AlphaFold2 instance running on Google Cloud. Secondly, a dashboard for analytics will be developed that will enable users to compare projected 3D structures for protein variations both statistically and graphically. Third, a feature called “protein of interest” (POI) recommendation will use intelligent selection algorithms to suggest to users potential synthetic protein variants (isoforms, truncations, mutations, orthologs, or fusions), while accounting for a number of constraints like conserved domains or computationally generated scores.
The relevance of eProtein Discovery/AlphaFold2’s application
With the aid of AlphaFold2’s 3D structural insights, Nuclera and its clients will be able to enhance the efficiency of their protein variant manufacturing procedure and learn more about the intricate relationships that exist between residues and the 3D folding protein structure.
The composite predictions provided by the AlphaFold2 module of the eProtein Discovery Software will help customers all over the world gain a better understanding of their proteins and make more informed decisions more quickly. This will ultimately save time needed to advance academic research and successfully find new drugs.
“AlphaFold2 integrated with Nuclera’s eProtein Discovery System is a really exciting demonstration of its practical use in drug discovery, enabling researchers to rapidly and efficiently design and produce proteins with the desired structure and function,” said Shweta Maniar, Global Director, Healthcare & Life Sciences Solutions, Google Cloud.
They are thrilled to be leading the way in the development of AI/ML-assisted drug discovery tools, which believe will accelerate the development of next-generation treatments. They are collaborating with Google Cloud and utilizing the amazing capabilities of AlphaFold2. Visit our GitHub repository to explore this solution in more detail and to test the universal and monomer pipelines that are included. The repository’s artifacts are made to allow for customization.
