Dataset Information

Non-apoptotic roles of apoptotic proteases: new tricks for an old dog.

ABSTRACT: This Open Question article highlights current advances in the study of non-apoptotic roles of apoptotic proteins. Apoptosis is a highly regulated and energy-requiring process in which cells actively kill themselves. Apoptosis helps remove extra cells to sculpt organs during embryo development and culls damaged cells throughout the body. Apoptosis relies on evolutionarily conserved proteins that include a family of proteases called caspases. Caspases activity has long been considered a hallmark of apoptosis. Yet an emerging body of literature indicates that caspase activity is required for a number of non-lethal processes that range from sculpting cells, removing protein aggregates, changing cell identity during differentiation or de-differentiation, and rebuilding tissues. Failure in each of these processes is associated with human disease. This article is not meant to be an exhaustive review but an introduction to the subject for an educated public, with caspases as a gateway example. I propose that it is time to explore non-apoptotic roles of caspases and other apoptotic proteins, in order to better understand their non-apoptosis function and to leverage new knowledge into new therapies.

SUBMITTER: Su TT

PROVIDER: S-EPMC7479936 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Non-apoptotic roles of apoptotic proteases: new tricks for an old dog.

Su Tin Tin TT

Open biology 20200819 8

This Open Question article highlights current advances in the study of non-apoptotic roles of apoptotic proteins. Apoptosis is a highly regulated and energy-requiring process in which cells actively kill themselves. Apoptosis helps remove extra cells to sculpt organs during embryo development and culls damaged cells throughout the body. Apoptosis relies on evolutionarily conserved proteins that include a family of proteases called caspases. Caspases activity has long been considered a hallmark o ...[more]

PMID: 32810419

Similar Datasets

Project description:High throughput screening (HTS) is an important component of lead discovery, with virtual screening playing an increasingly important role. Both methods typically suffer from lack of sensitivity and specificity against their true biological targets. With ever-increasing screening libraries and virtual compound collections, it is now feasible to conduct follow-up experimental testing on only a small fraction of hits. In this context, advances in virtual screening that achieve enrichment of true actives among top-ranked compounds ("early recognition") and, hence, reduce the number of hits to test, are highly desirable. The standard ligand-based virtual screening method for large compound libraries uses a molecular similarity search method that ranks the likelihood of a compound to be active against a drug target by its highest Tanimoto similarity to known active compounds. This approach assumes that the distributions of Tanimoto similarity values to all active compounds are identical (i.e., same mean and standard deviation)-an assumption shown to be invalid (Baldi and Nasr, 2010). Here, we introduce two methods that improve early recognition of actives by exploiting similarity information of all molecules. The first method ranks a compound by its highest z-score instead of its highest Tanimoto similarity, and the second by an aggregated score calculated from its Tanimoto similarity values to all known actives and inactives (or a large number of structurally diverse molecules when information on inactives is unavailable). Our evaluations, which use datasets of over 20 HTS campaigns downloaded from PubChem, indicate that compared to the conventional approach, both methods achieve a ~10% higher Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) score-a metric of early recognition. Given the increasing use of virtual screening in early lead discovery, these methods provide straightforward means to enhance early recognition.

Dataset Information

Non-apoptotic roles of apoptotic proteases: new tricks for an old dog.

Publications

Non-apoptotic roles of apoptotic proteases: new tricks for an old dog.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets