New drug restores vision by regenerating retinal nerves

The nice thing about being an academic is that I can investigate anything I find to be interesting, regardless of the field. One would have to have a fairly limited imagination to focus on only one thing your entire life. Discoveries in one area usually impact other areas, so a new analytical method can be used in many fields. Once you invent a new method or a technique, even the most limited researchers can and do use it in many important fields. It is the invention of the new effective technique that mattered.

Success in research demands passion. It's crucial to find a subject that genuinely interests you and dedicate yourself to it. While there may be long periods where the efforts don't seem to yield desired or meaningful outcomes, perseverance is key. When success does come, it's a deeply rewarding experience. Hold onto that feeling.

In the study, published in Scientific Reports, the researchers built on their earlier discovery of the peptide called AC253. This compound was tested in mice with AD. It was found to block the attachment of beta-amyloid to a brain cell receptor called the amylin receptor, and thus inhibit its toxic effects, as shown by an improvement in spatial memory. However, it is difficult to administer this compound because it doesn’t cross the blood-brain barrier in large amounts, and is quickly broken down in the blood. The dosage must therefore be massively increased, pushing up the amounts required for efficacy and increasing the difficulty of administration, besides enhancing the chances of an immune reaction. One way out is to convert the formulation into a pill rather than an injectable form. The complex structure of AC253 makes this difficult as well. Instead, the team devised an ingenious solution. They cleaved the compound into smaller amylin peptides, or chains of 12-14 amino acids, and tested each for its anti-amyloid activity in old mice which showed signs of AD. In this way, they found two short peptides that had the same effects as the larger compound. In particular, the researchers identified a segment that was common to both peptides, namely, SQELHRLQTY.

Data-driven models, such as Quantitative Structure Activity Relationships (QSAR), are incredibly attractive because they offer rapid methods for predicting molecular properties, including those that are difficult to access through fundamental chemical and physical theory. For new molecules, in related regions of chemical space to the training data, they can often be very accurate. The challenge is that they typically do not generalize across large diverse chemical and biological spaces. Therefore real care is needed when applying them to novel chemistry or biology. Some attempts to build more widely applicable QSAR models have been made in recent years, but most models in use today are still built for specific chemistries and properties owing to the scale and complexity of chemical space. When I started this work, especially for solubility predictions, the datasets were modest by today’s standards, often hundreds to a few thousand molecules. One of the first things that teaches you is to explore the data carefully, assess its quality and quantity, and only then move forward with modeling. The aim is to capture genuine relationships between numerical molecular descriptions and important target endpoints, but those relationships may be only locally generalizable. I also think the phrase “simple descriptors” is interesting. Some are simple, such as atom counts or bond counts, but others rely on detailed parameterization, group contributions, and graph-theoretical techniques. We still see these descriptors used today, sometimes alongside embeddings from graph neural networks or language models. The main lesson for me is that there is no single workflow. Each dataset, model, and end-use case needs careful thought.

COTI-2 is a computer-designed small molecule that was discovered by our artificial intelligence drug discovery platform called CHEMSAS. The molecule has undergone extensive preclinical evaluation at multiple centres in Canada, Europe and the USA. It has been well tolerated in preclinical testing and very effective against human tumours with p53 mutations and/or mutations in the PI3K/AKT pathway. We have positive results from more than 10 different human tumour xenograft models using COTI-2 alone or in combination with conventional therapy. COTI-2 is now in late preclinical development being prepared for a Phase 1 study and should be ready for clinical development by the end of this year.