A new collaboration aims to develop a first-in-class therapy targeting Delayed Cerebral Ischemia (DCI), a life-threatening complication of subarachnoid hemorrhage (SAH). DCI occurs in the aftermath of the initial intracranial bleeding and drastically reduces blood flow to many parts of the brain. The lack of oxygen and nutrient supply can lead to brain cell damage or death within minutes. DCI is a major cause of long-term neurological damage and disability after SAH and has limited treatment options.
Qanatpharma, Zuse Institute Berlin, Enamine, and Proteros biostructures are working together to use generative AI to accelerate drug discovery, with a Qanatpharma-identified protein that regulates cerebrovascular resistance and, hence, cerebral blood flow. The collaboration aims to deliver small molecule leads by combining advanced computational methods, medicinal chemistry, and structural biology. The program also aims to set a precedent for AI’s role in cerebrovascular drug discovery, with in vitro validation expected in late 2025.
Qanatpharma founder Steffen-Sebastian Bolz tells us more.
What makes DCI such a challenging target for drug development?
Historically, DCI has suffered from a lack of molecular targets and, hence, viable treatment options because the underlying molecular mechanism had not been identified. Until now, treatment modalities, predominantly calcium antagonists, fail to target the correct parts of the cerebrovascular tree and the underlying molecular mechanism, which renders these drugs largely clinically ineffective.
Qanatpharma has focused on the role of cerebral resistance arteries for the pathogenesis of DCI, which has led to a portfolio of novel disease-driving protein targets.
How are generative AI and computational approaches shaping drug discovery efforts?
Generative AI has allowed us to go beyond both physical and virtual chemical libraries to explore novel chemical spaces with far greater efficiency. For context, the theoretical drug-like chemical space is estimated to contain up to 1060 molecules – an astronomically large number that cannot be meaningfully explored through “brute force” methods. This is where generative AI becomes transformative. Machine learning and AI approaches reduce time and cost tremendously by focusing experimental efforts on the most promising molecules from computational drug discovery results. Basically, generative AI rewrites the rules of the drug development process by dramatically reducing costs and lowering entry barriers.
The shortening of new chemical entity development and validation processes enables the targeting of several mechanisms and principles in parallel at unprecedentedly low costs and speed. Research on SAH therapies – and its microvascular targets in particular – will greatly benefit from this acceleration.
How was the cerebrovascular protein target selected?
Qanatpharma has focused on myogenic responsiveness (aka the “Bayliss Effect”); the key mechanism for regulation of resistance, pressure, and flow in cerebral microcirculation for the last 25 years. The team has described an entirely new molecular pathway regulating this mechanism, and understands how different diseases interfere with healthy signalling and induce disease-causing molecular perturbations.
The first cerebrovascular protein target was chosen because it is well-characterized in a different disease context, and available drug therapies allowed us to obtain detailed preclinical data, which support the potential for therapeutic intervention.
How will you translate early-stage results such as docking or screening hits into viable clinical candidates?
The availability of accurate and high-quality proteins and structures, as well as quick turnarounds, are crucial for the success of docking, screening, and generative AI activities. Enamine’s synthesis capabilities enable rapid translation of virtual hits into real novel chemical matter. Proteros’ contribution includes early drug discovery expertise by delivering atomic resolution data of small molecule interactions with the target, along with measured binding and inhibition parameters through biochemical, cellular, and biophysical methods. Integration of this information informs the rational design of novel chemical structures for subsequent lead optimization and clinical programs.
What is your role in this consortium?
Qanatpharma provides detailed insights into the microvascular and molecular basis of DCI and will route its drug target portfolio candidates through the pipeline built and represented by the three partner institutions. Our detailed insight into the target proteins’ mode of action enables the development of assays precisely tailored to validate the AI-generated structures. The latter combines early generative molecular design and docking studies by the Zuse Institute Berlin, compound synthesis contributed by Enamine, and validation of hit compounds, with assessment of their therapeutic potential, performed by Proteros using their structural biology and drug discovery platform. At the end of the process, the biological effects of selected compounds will be tested in Qanatpharma’s in vitro isolated resistance artery and in vivo animal disease models.
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