Call for Papers (ACS Fall Meeting 2018)

Move Away from the Lamp Post & Find Druggable Targets

256th ACS National Meeting
Boston August 19-23, 2018
CINF Division

Dear colleagues, we are organizing a symposium focusing on methodologies and case studies that have explored under- or unstudied targets, with the goal of elucidating their function or role in the context of human disease. Several reports have highlighted the focus on current biomedical research on a relatively small set of protein targets. For example, Edwards et al (Nature, 2011) reported that 75% of research is focused on studying only 10% of the known mammalian proteins.

Clearly, there may be many unexplored opportunities among the set of under- and unstudied targets, the so called “dark targets”.  Our own report (Nature Rev Drug Discov 2018) suggests that as many as 38% of human proteins are significantly understudied, and that over 9000 human proteins are currently not associated with NIH funding.

At this critical juncture in human health research, we believe it is timely to discuss approaches to study the “dark genome”. We invite submissions that address all aspects of illuminating dark targets, with a particular focus on computational approaches that involve novel experimental methods. Topics of interest include, but are not limited to:

  • Target prioritization methods
  • Integrative approaches that combine data types, using well studied targets to shed light on unstudied targets
  • Case studies that have elucidated function or disease relevance for unstudied targets
  • Novel characterization of targets that go beyond traditional structure based approaches
  • Target-centric databases that highlight dark targets

The deadline for abstract submissions is March 20, 2018. All abstracts should be submitted via MAPS at https://acsnm256.abstractcentral.com/. If you have any questions feel free to contact  Tudor or myself

Rajarshi Guha             Tudor Oprea
NCATS, NIH                University of New Mexico
guhar@nih.gov            TOprea@salud.unm.edu

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