An In Silico Intersection of Physics Chemistry & Biology

AtomForge utilizes a unique physics-based model to accurately represent the behaviours of atoms and molecules, which closely mimics the natural world and does not rely on training data.

HTuO aims to utilize the AtomForge software to revolutionize drug design and expedite drug discovery, particularly for hard-to-drug proteins.

Delivering on the Promises of In-Silico Drug Discovery

The introduction of conventional computer-aided drug discovery (CADD) tools revolutionized drug screening, improving hit rates from 0.1% to 1-30%. However, recent advancements in in-silico methods have plateaued, with modern technologies not consistently yielding favourable clinical outcomes.
AtomForge is a revolutionary tool for in-silico drug discovery, leveraging modern technology to meet the needs of industry leaders. It focuses on targeting previously “undruggable” proteins and advancing innovative therapeutic strategies like macrocyclic peptides and molecular glues.

Optimizing Interactions

Minimizing Clinical Failures

Non-specific drug interactions and off-target effects significantly contribute to toxicity, leading to failed clinical trials and substantial development costs. For instance, many clinical failures of small molecule GLP1R inhibitors are attributed to inadequate potency and high toxicity. By optimizing drug-target interactions for a more specific fit, the risk of toxicity issues, and associated expenses, can be minimized.

Core Applications

Accelerating the journey to IND enabling studies.

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Molecular Glues

AtomForge is particularly well-suited to support molecular glue development projects because of its dynamic charge model, which captures the intricate redistribution of charge at the protein-glue-protein interfaces. By leveraging AtomForge, researchers can improve hit detection and enhance lead optimization rates in this rapidly evolving field.

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Macrocyclic Peptides

Macrocyclic peptides combine the deliverability of small molecules with the specificity of protein-based therapies, presenting a promising therapeutic option. Traditional CADD methods have struggled with macrocyclic peptides, due to outdated physics models and rigid parameterization. AtomForge’s comprehensive parameterization allows our tools to provide valuable data for macrocyclic peptide based therapy projects.

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