Requirements for Efficient Proteolytic Cleavage of Prelamin A by ZMPSTE24

The proteolytic maturation of the nuclear protein lamin A by the zinc metalloprotease ZMPSTE24 is critical for human health. The lamin A precursor, prelamin A, undergoes a multi-step maturation process that includes CAAX processing (farnesylation, proteolysis and carboxylmethylation of the C-terminal CAAX motif), followed by ZMPSTE24-mediated cleavage of the last 15 amino acids, including the modified C-terminus. Failure to cleave the prelamin A "tail", due to mutations in either prelamin A or ZMPSTE24, results in a permanently prenylated form of prelamin A that underlies the premature aging disease Hutchinson-Gilford Progeria Syndrome (HGPS) and related progeroid disorders.Here we have investigated the features of the prelamin A substrate that are required for efficient cleavage by ZMPSTE24. We find that the C-terminal 41 amino acids of prelamin A contain sufficient context to allow cleavage of the tail by ZMPSTE24. We have identified several mutations in amino acids immediately surrounding the cleavage site (between Y646 and L647) that interfere with efficient cleavage of the prelamin A tail; these mutations include R644C, L648A and N650A, in addition to the previously reported L647R. Our data suggests that 9 of the 15 residues within the cleaved tail that lie immediately upstream of the CAAX motif are not critical for ZMPSTE24-mediated cleavage, as they can be replaced by the 9 amino acid HA epitope. However, duplication of the same 9 amino acids (to increase the distance between the prenyl group and the cleavage site) impairs the ability of ZMPSTE24 to cleave prelamin A.Our data reveals amino acid preferences flanking the ZMPSTE24 cleavage site of prelamin A and suggests that spacing from the farnesyl-cysteine to the cleavage site is important for optimal ZMPSTE24 cleavage. These studies begin to elucidate the substrate requirements of an enzyme activity critical to human health and longevity

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe