We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.


Identifying Novel Drug Targets for Neurodegeneration

Identifying Novel Drug Targets for Neurodegeneration content piece image
Listen with
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: 4 minutes

Neurodegenerative diseases are caused by the progressive degeneration of the structure and functioning of nerve cells. The proportion of the global population aged 60 years and over is growing faster than ever – by 2050, it will have increased to 2.1 billion compared to 901 million in 2015. Considering that aging is a primary risk factor for most neurodegenerative diseases, treatments are urgently needed.

Researchers from the Alzheimer’s Research UK Oxford Drug Discovery Institute
are working to accelerate the discovery of therapeutics for Alzheimer’s disease and other neurodegenerative diseases. During this year’s ELRIG Drug Discovery Meeting, Prof. Paul Brennan from the University of Oxford discussed recent progress to develop drug compounds against novel targets in neuroinflammatory and sub-cellular organelle dysfunction pathways.

Technology Networks
had the pleasure of speaking with Brennan to delve deeper into the topics highlighted in his talk.

Laura Lansdowne (LL): The Alzheimer’s Research UK Oxford Drug Discovery Institute (ODDI) focuses on two target areas. Can you tell us more about your work in these areas?

Paul Brennan (PB):
At the ODDI, our work on neurodegenerative disease is currently focused on Alzheimer’s disease (AD) – the most common form of dementia and the leading cause of death for women in the UK, and Parkinson’s disease (PD) – traditionally viewed as a degenerative movement disorder, but commonly showing dementia in late stages.

Due to recently discovered genetic links between AD and neuroinflammation, we have four projects to develop drugs that treat this important cellular system in the brain. One of the biggest challenges in doing drug discovery in neuroinflammation is that no one knows yet exactly when and how the neuroimmune system goes awry in AD or when best to treat the neuroimmune component of AD, but we are confident that there is so much interest around the world in neuroinflammation that we will have the answers we need by the time we are ready to test our drugs in patients.

Although neuroinflammation is probably important in most other forms of neurodegeneration, the genetic causes of PD point to problems in the endo-lysosomal system in the cells that die first and kick-off PD. The endo-lysosomal system is critical for cells to clear out cellular waste and debris and when it’s not working correctly, the cells die under the burden of their own waste. We are working on four targets that we believe will tune up the endo-lysosomal system, keep it functioning properly, and keep neurons alive longer thereby preventing PD from developing.

LL: At the start of your
talk during ELRIG drug discovery 2021, you highlighted three key elements (novel, validated, tractable) when considering targets for neurodegeneration, could you elaborate on these?

It’s of utmost importance when working on complex neurodegenerative diseases that take most of a lifetime to develop that we pick drug targets that are validated – they have strong biological links and rationale for treating disease. I mentioned drug safety in my talk only briefly, but this is equally important in target selection. We have to pick targets that will treat or cure disease if we modulate them but won’t cause other sides effects – the cure can’t be worse than the disease.

The targets also have to be possible to develop drugs for – tractable; at the end of the day, we have to go into a lab, make proteins, run assays, discover and optimize molecules and there are technical challenges at every step. Fortunately, the space of tractable targets is expanding all the time as new drug modalities are developed. When I started my career in drug discovery in 1995, the only realistic way to treat diseases of the central nervous system was with classical small molecules. That has changed dramatically in the past 26 years, with new drug modalities like antibodies, peptides, oligonucleotides, gene and cell therapies moving from the realm of science fiction into non-fiction and these new types of drug molecules are either approved or in clinical trials right now.

Compared to the pharma and biotech sector, academic drug discovery research has much less funding. At the ODDI, it’s important to us that we don’t duplicate research done elsewhere as that could just be a waste of the charity’s precious research funding. That’s why we pick targets that we think are novel with no one else in the world working on them, or at least not in the same way we are. Novel targets are also very attractive to the pharma and biotech companies who collaborate with us and fund our research.

LL: You visually depicted how these three elements influence each other, from your slide it seemed that there is a fine balance is needed, could you elaborate?

 The best projects will be validated, tractable and novel. Occasionally we deemphasize one of the three if the other two are so strong. For example, with our sibling institute, the University College London Drug Discovery Institute, we are developing activators for an important genetically implicated target for AD called phospholipase C-gamma 2 (PLCG2). Traditionally, enzyme activators are very tough to discover, and this project would not be in tractable space, but in this case, we believe we have a novel strategy to address this challenging but validated target.

LL: Can you tell us more about NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) and its role in AD – what approaches did you exploit to investigate this further?

NLRP3 is a protein important in the inflammasome – a huge intercellular protein machine that produces other inflammatory proteins instigating widespread neuroinflammation and damage to nearby neurons. By developing inhibitors of NLRP3, we will be able to keep neuroinflammation in check and prevent the death of neurons whose loss leads to AD. Many drug discovery groups around the world are working on NLRP3 inhibitors but almost all of them are focused on inflammatory cells and diseases outside the brain. The inhibitors they are pursuing are not suitable for neuroinflammation because they don’t get into the brain very well. The inhibitors we are designing and making have much better brain activity and will be suitable for treating neuroinflammation.

Can you tell us more about the automated target assessment tool “Target DB” developed by your colleague
Stephane De Cesco? How has this tool helped to define the factors that make a good target?

compiles target information from the many excellent databases that gather data on human genes and proteins and summarizes the key attributes in an easy-to-read and search format. Additionally, for target tractability, if there is little known about a particular protein of interest, it will search for better known, very similar proteins and assess their tractability by inference. TargetDB also uses a machine-learned method to give every target a “druggability” score based on its similarity to known drug targets. A user of TargetDB either inputs a single gene or a list of genes and is presented with a summary of the target and a druggability ranking versus other targets. This helps us to prioritize the best targets for further research.

Paul Brennan was speaking with Laura Elizabeth Lansdowne, Managing Editor for Technology Networks.