Our latest blog post explores PoET, our generative protein language model, as a foundation model for protein ML. With only 200 million parameters, PoET is significantly faster than models like ESM2 and xTrimoPGLM. Despite its size, PoET shines in fine-tuning experiments. PoET delivers 15x greater data efficiency when learning from small mutagenesis datasets and also allows us to improve signal peptide prediction in larger scale fine-tuning. PoET embeddings also capture significant structural information, from sequence alone, giving improved secondary structure prediction accuracy. Read more: https://lnkd.in/gUrM-zzi
About us
OpenProtein.AI provides machine learning software and services to allow our customers to push beyond the boundaries of conventional protein engineering to build better products faster, cheaper, and more reliably. Our democratized web platform puts the power of cutting-edge ML tools directly in the hands of biologists.
- Website
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https://www.openprotein.ai/
External link for OpenProtein.AI
- Industry
- Biotechnology
- Company size
- 2-10 employees
- Headquarters
- Remote
- Type
- Privately Held
- Founded
- 2021
- Specialties
- Protein Engineering and Machine Learning
Locations
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Primary
Remote, US
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Remote, SG
Employees at OpenProtein.AI
Updates
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Engineering protein complexes or multimeric proteins is challenging, especially with current approaches that only work with one subunit at a time. The OpenProtein.AI platform addresses these limitations, allowing you to model critical interactions between subunits easily. Dive into a step-by-step example of how to design libraries for multimeric proteins in our latest walkthrough. We demonstrate how to use the OpenProtein.AI platform to chain together subunits and design variants from a larger, more relevant design space. The walkthrough covers structure prediction and optimizing variant libraries. To highlight the platform’s flexibility to work with multimeric proteins, we designed a library of variants that incorporate data from heavy and light chains of an antibody, identifying high affinity binding variants with mutations across both chains. Read it here: https://lnkd.in/gMeHK5xq
Designing libraries of multimeric proteins #
docs.openprotein.ai
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Exciting News from OpenProtein.AI! We're thrilled to introduce the latest platform enhancements, including the AlphaFold2 Web Interface for visualizing predicted structures of multimers and single-chain sequences with precision. Our Batch Predictions feature now allows you to analyze multiple sequences using your trained models, streamlining your workflow. Plus, our Python Documentation has a fresh look, offering improved organization and walkthroughs for enzymes, antibodies, and structural proteins. Sign up for early access now: https://lnkd.in/gMmKKCfQ
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OpenProtein.AI reposted this
Had an insightful conversation with Neeraj Rao discussing mutating proteins in-silico and learning about OpenProtein.AI .AI. Wish I had this tool during my lab work; it could have saved me lots of heartbreak. Looking forward to more insights at Future Labs Live Basel
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"This study underscores the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications. Modifying enzymes or proteins while retaining functionality has been a major challenge. Often, multiple mutations or modifications to the primary structure of the enzyme have significant and destructive consequences to the 3D structure and functionality of the resulting enzyme. New methods to leverage the known information and predict the structure and function of designer proteins are necessary for progressing efficiently in protein modification studies." At OpenProtein.AI, we make it easy to use evolutionary models that explore exponentially more sequence space than traditional mutagenesis approaches so you can identify novel variants with a greater chance of success faster. Contact us today to learn how you can harness the power of evolution to create better proteins!
Evolution-Informed Protein Design Aims to Improve Functionality of Enzymes
genengnews.com
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OpenProtein.AI will be exhibiting at Future Labs Live in two weeks! This is Europe's biggest lab innovation event, happening in Basel on June 26-27th. Stop by startup booth S240 to see a demo of OpenProtein.AI in action and see how you can easily incorporate machine learning into your protein engineering workflow. #FutureLabsLive #machinelearning #proteinengineering #labautomation
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OpenProtein.AI will be exhibiting at Future Labs Live! This is Europe's biggest lab innovation event, happening at the Congress Center Basel on June 25-27th. We'll be demoing the OpenProtein.AI web app and PoET, our generative protein language model for controllable sequence generation and zero-shot protein mutagenesis. Secure your free pass today and visit our booth in the startup zone. #FutureLabsLive #proteinengineering #machinelearning
Register for Future Labs Live Basel 2024 | 25-27 June
i.snoball.it
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OpenProtein.AI reposted this
PoET is our generative protein language model for controllable sequence generation, zero-shot protein mutagenesis & clinical variant effect prediction. In our latest blog post, we dive into PoET’s performance, which surpasses existing models in accuracy, speed, controllability, and generalizability. Bring the power of generative AI and ML to your protein engineering efforts today! No experimental data or coding experience needed. Find the link to our latest blog post in the comments below. Stay tuned for our upcoming post on PoET embeddings, also available on the OpenProtein.AI platform. #proteinengineering #machinelearning #openprotein #zeroshotengineering #MLforbiology #AIinMedicine #generativeAI
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PoET is our generative protein language model for controllable sequence generation, zero-shot protein mutagenesis & clinical variant effect prediction. In our latest blog post, we dive into PoET’s performance, which surpasses existing models in accuracy, speed, controllability, and generalizability. Bring the power of generative AI and ML to your protein engineering efforts today! No experimental data or coding experience needed. Find the link to our latest blog post in the comments below. Stay tuned for our upcoming post on PoET embeddings, also available on the OpenProtein.AI platform. #proteinengineering #machinelearning #openprotein #zeroshotengineering #MLforbiology #AIinMedicine #generativeAI
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Miss us at PEGS? Find out how Tamarack Bioscience, Inc. used OpenProtein.AI to engineer novel reverse transcriptase polymerase with more than 10 amino acid substitutions at once. In a collaboration between TamarackBio and OpenProtein.AI, scientists at Tamarack Bio were able to leverage OpenProtein.AI’s protein design tools to design 5 new polymerase variants for reverse transcription. These enzymes were critical COVID PCR testing and remain an important workhorse in diagnostics development and as laboratory reagents. By using machine-learning guided approaches to engineering proteins, the team was able to quickly design high activity, high diversity variants for screening. The designed variants had around 17 amino acid substitutions each and displayed high activity. This greatly reduced the time and resources used in screening for novel enzyme variants! Be sure to check out how you can apply the OpenProtein.AI platform to your protein engineering data by contacting us at contact@openprotein.ai. Or, sign up for early access now https://lnkd.in/gMmKKCfQ #PEGS #openproteinai #machinelearning #reversetranscription #pcr #polymerase #proteinengineering #enzymeengineering
Sign up for early access | OpenProtein.AI
openprotein.ai