Proteins and peptides are fascinating biological molecules with diverse functions, ranging from diagnostics to therapeutics and vaccines. At Protèic Bioscience, a leading biotech company, their mission is to leverage the power of AI to design proteins and peptides with the ideal structure and properties. In this blog post, we'll dive into Protèic’s innovative approach, their current workflow, and how the integration of Scispot is revolutionizing their protein design process.

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Unleashing the Potential of Protein Design

Protèic Bioscience’s design platform enables them to navigate through millions of possible protein sequences and narrow down the selection to a curated list of promising candidates. This computational work helps identify sequences that have the potential to perform exceptionally well in the lab. Once the top contenders are identified, they are tested experimentally, and the best-performing proteins are incorporated into actual products through collaborations with partners.

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The Complexity of Protein Design Workflows

Protèic's workflow involves several intricate steps to achieve optimal protein design. It begins with defining the target and setting specific design parameters. The platform filters and assesses designs based on predetermined criteria, iterating if necessary. Once satisfied with the results, AI comes into play. Protèic utilizes physics-informed neural networks to generate more diverse peptides, enhancing the design pool. These peptides then undergo experimental testing, potentially leading to further iterations. Finally, a comprehensive design report is generated, capturing crucial information for product development.

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Overcoming Manual Processes with Scispot’s Computational Protein Design Tools

Protèic Bioscience's journey has been marked by manual steps, such as setting filtration criteria, assessing designs, and generating design reports. These processes required significant effort and meticulous tracking. With the introduction of Scispot, Protèic Bioscience gains newfound efficiency and automation. The integration of the JupyterHub API within Scispot streamlines crucial aspects of their workflow. Filtration of designs, tracking design origins, and managing iteration stages become automated, freeing up time for scientists to focus on the science itself. The burden of writing reports is lightened with Scispot, and Protèic can now fully harness the power of AI to propel their computational protein design advancements.

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Looking Ahead to the Future of AI Protein Design

Protèic Bioscience is thrilled about their recent onboarding with Scispot. They eagerly anticipate the automation and streamlining of design processes, making protein design an even more enjoyable and efficient endeavor. By leveraging Scispot's capabilities, Protèic aims to shift their focus from manual tasks to scientific exploration, pushing the boundaries of protein and peptide design. The integration of computational tools and Scispot marks a significant milestone in Protèic's journey, one that promises exciting developments and groundbreaking innovations in the field of biotechnology.

Protèic Bioscience's use of AI to design proteins and peptides showcases the transformative power of technology in the biotech industry. By streamlining their workflow and integrating Scispot, Protèic maximizes efficiency, reduces manual efforts, and enhances their ability to generate groundbreaking protein designs. As Protèic Biosciences continues to push the boundaries of protein engineering, their collaboration with Scispot serves as a testament to the transformative potential of AI in revolutionizing scientific research and development.

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