Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

The ubiquitination mediated by ubiquitin activating enzyme (E1), ubiquitin conjugating enzyme (E2), and ubiquitin ligase (E3) cascade is crucial to protein degradation, transcription regulation, and cell signaling in eukaryotic cells. The high specificity of ubiquitination is regulated by the interaction between E3 ubiquitin ligases and their target substrates. Unfortunately, the landscape of human E3-substrate network has not been systematically uncovered. Therefore, there is an urgent need to develop a high-throughput and efficient strategy to identify the E3-substrate interaction. To address this challenge, we develop a computational model based on multiple types of heterogeneous biological evidence to investigate the human E3-substrate interactions. Furthermore, we provide UbiBrowser as an integrated bioinformatics platform to predict and present the proteome-wide human E3-substrate interaction network (http://ubibrowser.ncpsb.org).

Fire ants link their bodies to form aggregations; these can adopt a variety of structures, they can drip and spread, or withstand applied loads. Here, by using oscillatory rheology, we show that fire ant aggregations are viscoelastic. We find that, at the lowest ant densities probed and in the linear regime, the elastic and viscous moduli are essentially identical over the spanned frequency range, which highlights the absence of a dominant mode of structural relaxation. As ant density increases, the elastic modulus rises, which we interpret by alluding to ant crowding and subsequent jamming. When deformed beyond the linear regime, the aggregation flows, exhibiting shear-thinning behaviour with a stress load that is comparable to the maximum load the aggregation can withstand before individual ants are torn apart. Our findings illustrate the rich, collective mechanical behaviour that can arise in aggregations of active, interacting building blocks.

Toward an understanding of the protein interaction network of the human liverAn extensive interaction network of human liver-expressed proteins is described, composed of 3484 interactions among 2582 proteins. Proteins associated with liver disease tend to be central and highly connected in the network.

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