AutoClickChem: Click Chemistry in Silico

Academic researchers and many in industry often lack the financial resources available to scientists working in “big pharma.” High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu

Histamine-driven responses are sustained via a bioactive metabolite

A histamine metabolite, imidazole acetic acid (IAA), recapitulates key histamine-driven biology, including recruitment of eosinophils, induction of itch, and induction of anaphylaxis. IAA may perpetuate anaphylactic and other allergic responses after the initial release and metabolism of histamine

Secondary findings from clinical genomic sequencing: prevalence, patient perspectives, family history assessment, and health-care costs from a multisite study

© 2018, American College of Medical Genetics and Genomics. Purpose: Clinical sequencing emerging in health care may result in secondary findings (SFs). Methods: Seventy-four of 6240 (1.2%) participants who underwent genome or exome sequencing through the Clinical Sequencing Exploratory Research (CSER) Consortium received one or more SFs from the original American College of Medical Genetics and Genomics (ACMG) recommended 56 gene–condition pair list; we assessed clinical and psychosocial actions. Results: The overall adjusted prevalence of SFs in the ACMG 56 genes across the CSER consortium was 1.7%. Initially 32% of the family histories were positive, and post disclosure, this increased to 48%. The average cost of follow-up medical actions per finding up to a 1-year period was $128 (observed, range:$0–$678) and$421 (recommended, range: $141–$1114). Case reports revealed variability in the frequency of and follow-up on medical recommendations patients received associated with each SF gene–condition pair. Participants did not report adverse psychosocial impact associated with receiving SFs; this was corroborated by 18 participant (or parent) interviews. All interviewed participants shared findings with relatives and reported that relatives did not pursue additional testing or care. Conclusion: Our results suggest that disclosure of SFs shows little to no adverse impact on participants and adds only modestly to near-term health-care costs; additional studies are needed to confirm these findings