Minimotif Miner 4: a million peptide minimotifs and counting.

Nucleic Acids Res

Nevada Institute of Personalized Medicine and School of Life Sciences, University of Nevada, Las Vegas, 89154 4004 NV, USA.

Published: January 2018

AI Article Synopsis

  • Minimotif Miner (MnM) is a database that grew from ~300,000 to over 1,000,000 short peptide motifs, enabling better analysis of human genetic variations.
  • Updates include mapping minimotifs to human genetic variants from dbSNP, which helps generate hypotheses on how genetic variations can affect peptide functions.
  • The latest version identified a specific SNP in the ERCC2 gene linked to cancer, enhancing understanding of its role in disease through better mechanistic insights.

Article Abstract

Minimotif Miner (MnM) is a database and web system for analyzing short functional peptide motifs, termed minimotifs. We present an update to MnM growing the database from ∼300 000 to >1 000 000 minimotif consensus sequences and instances. This growth comes largely from updating data from existing databases and annotation of articles with high-throughput approaches analyzing different types of post-translational modifications. Another update is mapping human proteins and their minimotifs to know human variants from the dbSNP, build 150. Now MnM 4 can be used to generate mechanistic hypotheses about how human genetic variation affect minimotifs and outcomes. One example of the utility of the combined minimotif/SNP tool identifies a loss of function missense SNP in a ubiquitylation minimotif encoded in the excision repair cross-complementing 2 (ERCC2) nucleotide excision repair gene. This SNP reaches genome wide significance for many types of cancer and the variant identified with MnM 4 reveals a more detailed mechanistic hypothesis concerning the role of ERCC2 in cancer. Other updates to the web system include a new architecture with migration of the web system and database to Docker containers for better performance and management. Weblinks:minimotifminer.org and mnm.engr.uconn.edu.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753208PMC
http://dx.doi.org/10.1093/nar/gkx1085DOI Listing

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