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SUMMARY:Merging Data Science and Physical Organic Chemistry in Multi-Object
 ive Optimization Tactics for Drug Design
LOCATION:Chemistry A101
TZID:America/Denver
DTSTART:20230501T160000
UID:2026-05-03-15-59-06@natsci.colostate.edu
DTSTAMP:20260503T155906
Description:Research Seminar -\nAbstract. Synthetic methods to access comp
 ound collections based on “privileged scaffolds” for a diverse array o
 f biologically relevant targets are highly desirable. Therefore\, the abil
 ity to interconvert between (often heterocyclic) scaffolds in a functional
 ized molecule is a topic of intense interest: such transformations have be
 en termed “skeletal editing.” Skeletal edits such as single-atom inser
 tion and deletion reactions can access similar structures with drastically
  altered molecular properties. We propose to develop computational tools t
 hat will enable medicinal chemists to use skeletal edits to (i) explore st
 ructural hypotheses (i.e.\, of a protein binding site) and (ii) target opt
 imized molecular properties. We will use data science approaches to evalua
 te substrates\, enumerate all possible skeletal edits\, and then prioritiz
 e the selection of transformations to explore structure and pharmacophore 
 space or optimize for desired physical properties while suppressing others
 . Our approach will assist in selecting compounds with similar reactivity 
 to target compounds with enhanced binding affinities during the drug disco
 very phase without resorting to a new synthetic route. Furthermore\, as la
 te-stage modification reactions continue to be developed\, we aim to assis
 t in method development for skeletal editing reactions for existing and ne
 w heterocyclic substrates based on the learned reactivity from physical-me
 aning molecular and atomistic properties from a pool of diverse\, aromatic
  heterocyclic substrates. 4:00 pm
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