CMIC Seminar: Computational Drug Discovery and Event-Based Models for Atypical Alzheimer’s Disease

Speaker: Nick Firth
UCL Contact: Dominique Drai (Visitors from outside UCL please email in advance).
Date/Time: 02 Dec 15, 13:00 - 14:00
Venue: Roberts G06

Abstract

First part: Since the rise of the computer computational chemistry has been integrated into the drug discovery pipeline. Examples of its current application to discovery programmes include predicting properties of novel compounds or efficiently analysing the large quantities of data which is generated during drug development. MultiObjective Automated Replacement of Fragments (MOARF) has been designed to further support medicinal chemists by objective design of compounds predict to satisfy multiple criteria.

Second part: Typical Alzheimer’s disease is characterised symptomatically by an insidious onset and gradual decline of mental ability, in particular memory. However, atypical presentations of Alzheimer’s are not necessarily characterised by the same symptoms and follow a different neurodegenerative progression pathway. The event-based model has been developed and applied to various neurodegenerative diseases to elucidate the order of biomarker and symptomatic changes in these diseases and also to determine the stage of individual patients along the degenerative pathway. Applying the event-based model to atypical Alzheimer’s data, provided by the Dementia Research Council, will lead to a better understanding of these diseases and eventually a better diagnosis for the patients suffering with them.