WHEN?
Oct/24/2023“Efficiently Driving Protein-based NMR Fragment Screening and Lead Discovery”
Dr. Andrew “Dru” Namanja, Principal Research Scientist at AbbVie, will explore the potency ranking methods involving both qualitative single-point ligand concentration (Q Score) and quantitative binding affinity (KD), and how the combined utility can be used successfully to drive a Fragment-Based Drug Discovery (FBDD) campaign.
About the speaker
Dr. Andrew “Dru” Namanja
Principal Research Scientist – AbbVie
With over 20 years of experience in pharma and academia, Dru applies NMR methods to protein-ligand interactions to drive early-stage drug discovery research at AbbVie. His research interests include streamlining NMR workflows and applying AI/ML tools to advance FBDD. Dru holds a Biochemistry Ph.D. from the University of Notre Dame.
Abstract
Intro
Protein-based nuclear magnetic resonance (NMR) is an established gold-standard biophysical tool in early-stage drug discovery that provides atomic-resolution insights into protein-ligand interactions in solution. It ensures accurate confirmation of screening hits and drug leads by reducing the number of false positives and thereby saving resources and time in fast-paced setting with a high target attrition rate
Overview
The various applications of protein-based NMR in early-stage drug Discovery will be discussed, including classifying ligand mode-of-action (MoA), hit identification and confirmation from typical small molecule screening modalities such as DNA-encoded libraries (DEL), high-throughput screening (HTS), virtual library screening (VLS), and fragment-based screening (FBS).
Protein-based NMR also enables the tracking of structure-activity relationships (SAR) of weak binding fragments as they are elaborated to potent leads. This webinar will explore the potency ranking methods involving both qualitative single-point ligand concentration (Q Score) and quantitative binding affinity (KD), and how the combined utility can be used successfully to drive a Fragment-based Drug Discovery (FBDD) campaign. Furthermore, automated data analysis workflows will be discussed that employ spectral fingerprint analyses such as PCA (principal component analysis) and ECHOS (easy comparability of higher order structure) in conjunction with the standard chemical shift perturbation (CSP)-based method. This can significantly accelerate FBDD when using protein-detected NMR methods.
