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CoCoGraph AI Model Generates Molecules that Comply with Rules of Chemistry
Developing new molecular compounds is crucial to address pressing challenges, from drug discovery to sustainable materials. However, discovering viable new molecules is challenging due to the vastness of the search space.
In a new paper published in Nature Machine Intelligence titled, “A collaborative constrained graph diffusion model for the generation of realistic synthetic molecules,” researchers from Universitat Rovira i Virgili (URV) have developed an AI tool capable of generating molecules that are guaranteed to comply with the rules of chemistry. The model, named CoCoGraph, operates similarly to generative AI tools for text or images, such as ChatGPT or Dall-E.
“These models create new content that looks very much like the real thing. Our algorithm does the same, but with molecules,” said Roger Guimerà, PhD, ICREA research professor in the department of chemical engineering at URV and co-corresponding author of the study. He explains that the number of possible chemical molecules could be up to 10⁶⁰ variants, which is more than the number of water molecules in the ocean.
CoCoGraph uses a diffusion model, a technique common in image generation, which progressively “disorders” a real molecule and trains the system to learn how to reconstruct it.
Marta Sales-Pardo, PhD, professor in the department of chemical engineering at URV and co-corresponding author of the study, explains that the model begins with a real molecule, breaks the bonds, and then creates new bonds at random. The model then learns to reverse this process to reconstruct coherent structures.
Notably, CoCoGraph directly incorporates the basic rules of chemistry, such as maintaining the correct number of bonds, to guarantee that generated molecules are chemically valid. The system is also more efficient, uses fewer parameters, and requires less computing power to generate molecules more quickly.
The research team has compared the performance of CoCoGraph with other state-of-the-art models and analyzed 36 physicochemical properties, such as solubility and structural complexity. For two-thirds of these properties, the CoCoGraph generated molecules are chemically more realistic than those from other models.
Although the model cannot yet design molecules with a specific function, researchers have identified molecules with properties similar to the drug, paracetamol. They have also explored techniques to partially modify an existing molecule to create new variants with similar characteristics, which are useful for optimizing drugs or developing new materials.
The next step is to design molecules with specific properties, such as solubility and low toxicity. If successful, the technology could accelerate the discovery of new solutions across pharmacology and materials science in a chemical universe that is still practically unexplored.
The post CoCoGraph AI Model Generates Molecules that Comply with Rules of Chemistry appeared first on GEN – Genetic Engineering and Biotechnology News.
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STAT+: Sanofi asks to pull diabetes drug out of FDA voucher program after political appointee interfered with review
WASHINGTON — Sanofi has asked the Food and Drug Administration to pull its type 1 diabetes drug, teplizumab, out of Commissioner Marty Makary’s new speedy drug review program.
The move comes after acting Center for Drug Evaluation and Research Director Tracy Beth Høeg disagreed with a staff decision to approve the drug, according to sources familiar with the dispute who requested anonymity due to fear of reprisal. The agency has missed its goal date of April 21 to deliver a decision to Sanofi.
Such decisions are typically made by career scientists. It’s rare for a center director to become involved in scientific review of a single drug, and particularly a political appointee like Høeg. Makary recently told CNBC that he stands behind review teams, and that “disaster” occurs whenever political leaders overrule scientific staff.
WASHINGTON — Sanofi has asked the Food and Drug Administration to pull its type 1 diabetes drug, teplizumab, out of Commissioner Marty Makary’s new speedy drug review program.
The move comes after acting Center for Drug Evaluation and Research Director Tracy Beth Høeg disagreed with a staff decision to approve the drug, according to sources familiar with the dispute who requested anonymity due to fear of reprisal. The agency has missed its goal date of April 21 to deliver a decision to Sanofi.
Such decisions are typically made by career scientists. It’s rare for a center director to become involved in scientific review of a single drug, and particularly a political appointee like Høeg. Makary recently told CNBC that he stands behind review teams, and that “disaster” occurs whenever political leaders overrule scientific staff.
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Heavy-Chain BsAbs More Manufacturable than Light-Chains
Bispecific antibodies (BsAb) were first approved in 2014. Since then, a total of 19 have been approved globally, and approximately 250 BsAbs are being developed by some 180 companies, according to a report from Research and Markets. As this therapeutic class moves out of the lab and into clinical and commercial sectors, manufacturing may be its biggest challenge.
These dual-targeting compounds are considered difficult to produce, especially at scale. With low yields, potential chain mispairing, stability and aggregation issues, and analytical characterization challenges, biomanufacturers are eager to find expedient solutions. “There is still significant work to be done in bioprocess engineering to substantially improve the efficiency of bispecific antibody design and manufacturing,” Laura A. Palomares, PhD, senior researcher, Universidad Nacional Autónoma de Mexico (UNAM), tells GEN.
To that point, rather than relying upon transient expression systems or evaluating various antibody sequences, Palomares and her team are identifying manufacturable BsAbs by correlating their architectures to growth, productivity, downstream recovery, production of product-related variants, and in vitro binding to Zika virus and transferrin receptor (TfR). They found BsAb architecture is crucial in terms of those manufacturing criteria.
Structure governs performance
Specifically, as much as a 70% difference in productivity was found between symmetric heavy-chain scFv fusion BsAbs—which performed like the parental antibody—and BsAbs that were designed as light-chain scFv fusion, dual-variable domain immunoglobulin (DVD), or asymmetric antibodies. That’s according to a recent study by Palomares, doctoral student Juan Carlos Rivera-Castro, and senior researcher Octavio T. Ramirez, PhD.
Asymmetric BsAbs had the worst culture performance and productivity of the BsAb architectures tested. Asymmetry created imbalanced chain expression and formed homodimeric and half-antibody by-products, they reported, which dropped purity to approximately 68% after protein A purification. They found that binding to the LC-scFV diminished the binding to Zika virus, and that DVD increases it. Also, binding to TfR varied according to BsAb valency and configuration.
In contrast, “Bivalent heavy-chain scFV formats show[ed] stronger apparent binding than monovalent formats,” they report.
For the best manufacturability, the team says, “Avoid the modification of the light chain and preserve symmetric assembly.” This strategy resulted in higher cell viability, productivity, and final purity.
“The construction and head-to-head comparison of various formats, including the effect of the formats on antigen binding, can guide those planning the design and production of BsAbs,” Palomares says, by understanding the relative tradeoffs of various architectures as they design and clone BsAbs for specific functionalities.
“Format selection should prioritize manufacturability, with complex designs reserved for cases with particular functional requirements,” the scientists conclude.
Next steps, Palomares says, are to “determine the in vivo functionality of the constructed formats to neutralize Zika virus after traversing the blood-brain barrier. The results of those experiments will also be useful to scientists interested in BsAb design.”
The post Heavy-Chain BsAbs More Manufacturable than Light-Chains appeared first on GEN – Genetic Engineering and Biotechnology News.
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Amgen, Sanofi commit nearly $600M to North American expansions
Sanofi’s investment will support a Canadian site’s efforts to apply AI to drug production, while Amgen has unveiled the second expansion of its Puerto Rico plant in quick succession.
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