Dachao Tang

As an important post-translational modification, lysine ubiquitination participates in numerous biological processes and is involved in human diseases, whereas the site specificity of ubiquitination is mainly decided by ubiquitin-protein ligases (E3s). Although numerous ubiquitination predictors have been developed, computational prediction of E3-specific ubiquitination sites is still a great challenge. Here, we carefully reviewed the existing tools for the prediction of general ubiquitination sites. Also, we developed a tool named GPS-Uber for the prediction of general and E3-specific ubiquitination sites. From the literature, we manually collected 1311 experimentally identified site-specific E3-substrate relations, which were classified into different clusters based on corresponding E3s at different levels. To predict general ubiquitination sites, we integrated 10 types of sequence and structure features, as well as three types of algorithms including penalized logistic regression, deep neural network and convolutional neural network. Compared with other existing tools, the general model in GPS-Uber exhibited a highly competitive accuracy, with an area under curve values of 0.7649. Then, transfer learning was adopted for each E3 cluster to construct E3-specific models, and in total 112 individual E3-specific predictors were implemented. Using GPS-Uber, we conducted a systematic prediction of human cancer-associated ubiquitination events, which could be helpful for further experimental consideration. GPS-Uber will be regularly updated, and its online service is free for academic research at http://gpsuber.biocuckoo.cn/.

Various post-translational modifications (PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently associated with human diseases. Here, we present a comprehensive database of PTMs associated with diseases (PTMD 2.0), including 342 624 PTM-disease associations (PDAs) in 15 105 proteins for 93 types of PTMs and 2083 diseases. Based on the distinct PTM states in diseases, we classified all PDAs into six categories: upregulation (U) or downregulation (D) of PTM levels, absence (A) or presence (P) of PTMs, and creation (C) or disruption (N) of PTM sites. We provided detailed annotations for each PDA and carefully annotated disease-associated proteins by integrating the knowledge from 101 additional resources that covered 13 aspects, including disease-associated information, variation and mutation, protein-protein interaction, protein functional annotation, DNA and RNA element, protein structure, chemical-target relationship, mRNA expression, protein expression/proteomics, subcellular localization, biological pathway annotation, functional domain annotation and physicochemical property. With a data volume of ∼8 GB, we anticipate that PTMD 2.0 will serve as a fundamental resource for further analysing the relationships between PTMs and diseases. The online service of PTMD 2.0 is freely available at https://ptmd.biocuckoo.cn/.

ABSTRACT In recent years, poly( N ‐isopropylacrylamide)‐based microgels have been emerged as a new thermoresponsive coating for cell/cell sheet harvesting, yet few work reports their effect on cell attachment, morphology, activity, and proliferation in details. In this work, poly( N ‐isopropylacrylamide‐ co ‐styrene) (pNIPAAmSt) microgel was selected as the model to study its density on NIH3T3 cell adhesion, morphology, activity, and detachment. Results showed that 0.5 wt % pNIPAAmSt microgel density leads to more cells adhesion, higher cell activity yet lower cell proliferation. Moreover, cell adhesion location can be well controlled either by manipulating the sub‐cellular scale distances between microgels or by fabricating large scale surface patterns of the microgels on higher microgel density. By temperature stimuli, similar ratio cells detached from the microgel density surface from 0.5 to 1.5 wt %. The results in this article are worthy for the application of thermoresponsive microgels in cell regulation. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137 , 48773.