GoKawiilWe are giving a glimpse at a subset of the powerful and expansive capabilities of the Isomorphic Labs Drug Design Engine (IsoDDE), a unified computational drug-design system, progressing beyond AlphaFold 3 (AF3) in its predictive accuracy and introducing new capabilities which bridge the gap between structure prediction and real-world drug discovery.
We demonstrate that our IsoDDE more than doubles the accuracy of AlphaFold 3 on a challenging protein-ligand structure prediction generalisation benchmark, predicts small molecule binding-affinities with accuracies that exceed gold-standard physics-based methods at a fraction of the time and cost, and is able to accurately identify novel binding pockets on target proteins using only the amino acid sequence as input.
IsoDDE offers a scalable foundation for AI drug design, providing the predictive fidelity required to navigate novel biological systems with unprecedented accuracy.
Since our release of AlphaFold 3 in 2024 together with Google DeepMind, the field of AI drug discovery has moved at an extraordinary pace. Whilst AlphaFold 3 delivered a dramatic leap in performance from previous generations of structure prediction models, a key challenge remained: understanding biomolecular structures alone was not sufficient for unlocking real-world drug discovery programs in silico (on a computer).
Progress in rational drug design - vital for solving human disease - requires highly accurate predictive models, across an expansive range of biochemical properties and interactions, that are able to work in concert with one another. Crucially, with so much of biological and chemical space still unexplored, these models need the ability to generalise their predictive power beyond their training sets to novel, unseen systems.
As we continue to address these challenges, we are excited to introduce the Isomorphic Labs Drug Design Engine (IsoDDE), and to preview a subset of IsoDDE's capabilities below and in our technical report.
Read Our Technical Report
Structure Prediction of Truly Novel Systems
Accurately predicting the structure of biomolecules and how they interact remains a crucial capability for rational drug design. Many critical downstream tasks are unlocked by being able to accurately model the small nuances in a protein’s geometry - whether understanding the impact of disease-causing mutations, or predicting which molecules will bind to a target protein.
AlphaFold 3 transformed protein-ligand structure prediction at the time of its release and the freely available AlphaFold Protein Database accelerated science on a scale that was previously unimaginable. To date, it has been used by over 3 million researchers in more than 190 countries.
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