Pre-Conference Workshop Day
Tuesday 12th December 2023
8:30 am Registration Opens & Welcome Coffee
09:00AMWorkshop A
Utilizing Machine Learning & Artificial Intelligence to Understand RNA Structure-Function & Interactions with Small Molecules
Synopsis
As drug discovery remains the focal point of the RNA-targeting drug discovery community, novel approaches are being developed to better identify and understand the features of targetable RNA and small molecules. As the field moves forward, artificial intelligence and machine learning are incorporated into drug discovery. However, questions surrounding their use still remain. Join this workshop to understand how AI is being used to carry out drug discovery, as well as the advantages and disadvantages od using AI and machine learning.
- Understanding the molecules and RNA structures found in cells and how it causes the mechanism of action
- Utilizing digital support to look for data and predicting structural confirmations
- Can these experiments be reproduced on a regular basis?
- Using AI models and computational tools to understand RNA-small molecule interactions and achieving proof-of-concept
- The advantages and disadvantages of using artificial intelligence and machine learning for drug discovery
- How is AI & machine learning changing how we carry out drug discovery in the space?
- What are the benefits of using AI and how has it transformed what is being done?
- Understanding the multi-dimensional chemical space using machine learning
- Where is the data coming from that informs the computers about the multi-dimensional space? How applicable is the data set to the problem that needs to be addressed?
- Using machine learning to select molecules from compound banks and determining which molecules have a functional effect
11:00 am Morning Networking Break
12:00PMWorkshop B
Evaluating How to Choose the Best Small Molecules to Achieve Desired On-Target Effects
Synopsis
With the increasing research in small molecule-RNA targeting over the last decade and advances in machine learning, there is a growing consensus around the distinct and predictive properties that distinguish RNA-targeting small molecules from those that target proteins. It is also clear that RNAtargeting small molecules can look very similar to typical small molecule
drugs.
Many of these studies have focused purely on RNA binding, however, and
this workshop will discuss both this background and the remaining questions
and challenges in choosing the best small molecules for on-target functional
effects, such as:
- Efficiently identifying biologically active agents
- Evaluating selectivity in biological systems
- Are there binding modes and/or mechanisms of action that are particularly well-suited for functional effects?
- What lessons from covalent protein inhibitors can be applied to RNA?
2:00 pm Lunch & Networking Break
03:00PMWorkshop C
Leveraging Lessons from Clinical Successes with RNA Splicing Modifiers & Modulators to Improve Small Molecule Drug Design
Synopsis
With Risdiplam being the first RNA-targeting small molecule drug in the clinic, the community is investigating the vast potentials of RNA splicing modulators. As the first-in-class splicing modulator for treatment of spinal muscular atrophy, Risdiplam carved the way to exploring future indications of the chemical space for splicing modulators.
- How to use RNA splicing to determine new small molecule scaffolds with reduced off-target splicing events
- Two candidates fell out of clinic due to these off-target events – what can we learn from their downfall?
- How to design screens to understand how often splicing events occur in nature?
- Splicing modulators for lead optimization and development at the candidate level