Zymergen AI citations

Here are some of the best AI protein folding companies: 1. {{[[DeepMind]]:https://www.deepmind.com}} : Known for its AlphaFold program, which has made significant advancements in predicting protein structures with high accuracy. 2. {{[[Insilico Medicine]]:https://www.insilico.com}} : Utilizes AI for drug discovery and protein folding, focusing on aging and age-related diseases. 3. {{[[Schrödinger]]:https://www.schrodinger.com}} : Offers computational software for drug discovery that includes protein folding simulations. 4. {{[[Atomwise]]:https://www.atomwise.com}} : Uses AI to predict protein-ligand interactions, aiding in the understanding of protein structures. 5. {{[[Zymergen]]:https://www.zymergen.com}} : Combines machine learning and biotechnology to optimize protein engineering and folding processes. 6. {{[[CureMetrix]]:https://www.curemetrix.com}} : Focuses on AI applications in healthcare, including protein folding relevant to disease mechanisms. These companies are at the forefront of using AI to solve complex problems related to protein folding and structure prediction.

The best AI protein folding companies leading the field in 2025 include: - {{[[DeepMind]]:https://www.scispot.com/blog/unlocking-the-future-of-biotech-top-ai-biotech-companies-leading-the-charge}}: Known for AlphaFold, a groundbreaking AI system that predicts protein structures with high accuracy and has made over 1 billion protein structures publicly available. DeepMind also collaborates with BioNTech to develop AI lab assistants for drug discovery. - {{[[Cradle Bio]]:https://www.scispot.com/blog/unlocking-the-future-of-biotech-top-ai-biotech-companies-leading-the-charge}}: Specializes in AI-powered protein engineering to design proteins and optimize enzymes, with applications in pharmaceuticals, industrial biotech, and sustainable biomaterials. Raised over $100 million by 2024 and partners with major biopharma companies. - {{[[Atavistik Bio]]:https://www.greyb.com/blog/ai-drug-discovery-startups/}}: Focuses on screening metabolites and proteins to identify binding sites for novel therapies targeting metabolic diseases and cancer, using AI-driven analytics and platforms. - {{[[Polaris Quantum Biotech]]:https://www.greyb.com/blog/ai-drug-discovery-startups/}}: Combines quantum computing and AI to design drugs targeting proteins precisely, enhancing pharmaceutical development. - {{[[RFDiffusion (David Baker Lab)]]:https://formaspace.com/articles/tech-lab/ai-based-drug-discovery-revolutionize-pharma-labs/}}: An AI platform using generative diffusion techniques to design novel protein and chemical drug candidates, developed by the Nobel-winning David Baker lab. These companies are at the forefront of applying AI to protein folding and design, accelerating drug discovery and protein engineering breakthroughs[1][2][3][4][7].

Here are the top AI protein folding companies: 1. {{[[DeepMind]]:https://www.deepmind.com}} : Developed AlphaFold, the groundbreaking AI system that solved protein structure prediction, revolutionizing computational biology. 2. {{[[Baker Lab]]:https://www.bakerlab.org}} : Pioneered protein folding AI techniques through their RoseTTAFold algorithm, competing directly with AlphaFold. 3. {{[[Meta AI Research]]:https://ai.facebook.com}} : Developed ESMFold, an advanced protein structure prediction model using language model techniques. 4. {{[[Google DeepMind]]:https://www.deepmind.com}} : Continues to advance protein folding AI through ongoing AlphaFold research and public database releases. 5. {{[[Insilico Medicine]]:https://insilico.com}} : Applies AI to protein design and drug discovery, using advanced machine learning techniques. 6. {{[[Generate Biomedicines]]:https://generatebiomedicines.com}} : Utilizes generative AI for protein design and therapeutic protein engineering. 7. {{[[Recursion Pharmaceuticals]]:https://www.recursion.com}} : Employs AI and machine learning for protein interaction and drug discovery research. These companies represent the cutting edge of AI-driven protein folding and computational biology research.

Here are some of the top AI molecular design platforms: 1. {{[[Schrödinger]]:https://www.schrodinger.com}} : Schrödinger offers advanced molecular modeling and simulation software, utilizing AI to predict molecular behavior and design new compounds. 2. {{[[Insilico Medicine]]:https://insilico.com}} : Insilico Medicine focuses on drug discovery and development using AI and deep learning to design novel molecules and optimize existing ones. 3. {{[[Atomwise]]:https://www.atomwise.com}} : Atomwise uses AI for structure-based drug design, leveraging deep learning algorithms to predict the binding of small molecules to proteins. 4. {{[[DeepMind]]:https://deepmind.com}} : DeepMind's AlphaFold has revolutionized protein folding predictions, which is crucial for molecular design and drug discovery. 5. {{[[Cresset]]:https://www.cresset-group.com}} : Cresset provides software for molecular modeling and design, integrating AI to enhance the understanding of molecular interactions. 6. {{[[Zymergen]]:https://www.zymergen.com}} : Zymergen employs AI-driven molecular design to engineer microbes for sustainable production of chemicals and materials. 7. {{[[ChemAxon]]:https://chemaxon.com}} : ChemAxon offers cheminformatics solutions that utilize AI to assist in molecular design, property prediction, and data management. 8. {{[[BenevolentAI]]:https://www.benevolent.ai}} : BenevolentAI uses AI to accelerate drug discovery, focusing on designing new molecules based on biological data and insights. These platforms are at the forefront of integrating AI into molecular design, significantly enhancing the efficiency and effectiveness of drug discovery and development processes.

Top AI molecular design platforms in 2025 include: {{[[Exscientia]]:https://www.devopsschool.com/blog/top-10-ai-drug-discovery-platforms-in-2025-features-pros-cons-comparison/}} : Known for accelerating drug discovery by designing and optimizing small-molecule drugs using AI. {{[[Atomwise]]:https://www.devopsschool.com/blog/top-10-ai-drug-discovery-platforms-in-2025-features-pros-cons-comparison/}} : Uses AI-driven molecular modeling with its AtomNet platform for structure-based drug design, screening billions of compounds rapidly, and predicting binding affinity with high accuracy. {{[[Valo Health]]:https://www.devopsschool.com/blog/top-10-ai-drug-discovery-platforms-in-2025-features-pros-cons-comparison/}} : Employs the Opal Computational Platform to analyze billions of molecules with machine learning, focusing on oncology and neurodegenerative diseases and integrating patient data for personalized medicine. {{[[Chemical Computing Group (MOE)]]:https://www.deepmirror.ai/post/top-drug-discovery-software-solutions-to-watch-in-2025}} : Offers the Molecular Operating Environment platform integrating molecular modeling, cheminformatics, bioinformatics, and AI-driven structure-based drug design with interactive 3D visualization. {{[[deepmirror]]:https://www.deepmirror.ai/post/top-drug-discovery-software-solutions-to-watch-in-2025}} : Uses deep generative AI for hit-to-lead optimization, molecule generation, and protein-drug binding prediction, accelerating drug discovery up to six times. {{[[Merck AIDDISON]]:https://www.mantellassociates.com/ai-powered-molecular-innovation-breakthroughs-and-2025-growth/}} : Merck’s next-gen molecular design platform leveraging machine learning to generate targeted drug candidates with high accuracy. {{[[Iambic Therapeutics]]:https://www.biopharmatrend.com/business-intelligence/what-is-ai-drug-discovery/}} : Integrates specialized AI systems (Magnet, NeuralPLexer, Enchant) into a unified pipeline spanning molecular design, structure prediction, and clinical property inference. Additional notable platforms include {{[[Insilico Medicine]]:https://oncodaily.com/oncolibrary/artificial-intelligence-in-cancer-drug-discovery}} and {{[[Spaya]]:https://www.labiotech.eu/best-biotech/ai-drug-discovery-companies/}} (retrosynthesis AI), as well as {{[[Makya]]:https://www.labiotech.eu/best-biotech/ai-drug-discovery-companies/}} (generative AI for molecule design). These platforms employ advanced AI techniques such as generative models, graph neural networks, and large language models to design novel molecules, predict ADMET properties, and integrate multi-omic and clinical data for comprehensive drug discovery workflows.

Top AI molecular design platforms include: 1. {{[[Schrödinger]]:https://www.schrodinger.com/}} : Leading computational chemistry and materials science software platform with advanced molecular modeling capabilities. 2. {{[[BenevolentAI]]:https://www.benevolent.com/}} : Uses AI to accelerate drug discovery and molecular design across complex disease areas. 3. {{[[Atomwise]]:https://www.atomwise.com/}} : Pioneering AI-driven structure-based drug discovery using deep learning neural networks. 4. {{[[DeepMind]]:https://www.deepmind.com/}} : Advanced AI research company with significant contributions to molecular design and protein structure prediction. 5. {{[[IBM RXN]]:https://rxn.res.ibm.com/}} : AI platform for chemical reaction prediction and molecular synthesis planning. 6. {{[[Insilico Medicine]]:https://insilico.com/}} : AI-powered drug discovery platform specializing in generative molecular design. 7. {{[[NVIDIA Clara]]:https://www.nvidia.com/en-us/healthcare/clara/}} : AI computational platform for molecular modeling and drug discovery. These platforms leverage machine learning, deep learning, and advanced computational techniques to accelerate molecular design across pharmaceuticals, materials science, and biotechnology sectors.

Here are top AI molecular design platforms: {{[[Schrödinger]]:https://www.schrodinger.com/}} : Offers a comprehensive suite of computational chemistry software, including AI/ML-enhanced platforms like LiveDesign and FEP+, for molecular