Homogeneous, bioluminescent proteasome assays

Identification of Novel Trypanosoma cruzi Proteasome Inhibitors Using a Luminescence-Based High-Throughput Screening Assay

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi, is a potentially life-threatening condition that has become a global issue. Current treatment is limited to two medicines that require prolonged dosing and are associated with multiple side effects, which often lead to treatment discontinuation and failure. One way to address these shortcomings is through target-based drug discovery on validated T. cruzi protein targets. One such target is the proteasome, which plays a crucial role in protein degradation and turnover through chymotrypsin-, trypsin-, and caspase-like catalytic activities. In order to initiate a proteasome drug discovery program, we isolated proteasomes from T. cruzi epimastigotes and characterized their activity using a commercially available glow-like luminescence-based assay. We developed a high-throughput biochemical assay for the chymotrypsin-like activity of the T. cruzi proteasome, which was found to be sensitive, specific, and robust but prone to luminescence technology interference. To mitigate this, we also developed a counterscreen assay that identifies potential interferers at the levels of both the luciferase enzyme reporter and the mechanism responsible for a glow-like response. Interestingly, we also found that the peptide substrate for chymotrypsin-like proteasome activity was not specific and was likely partially turned over by other catalytic sites of the protein. Finally, we utilized these biochemical tools to screen 18,098 compounds, exploring diverse drug-like chemical space, which allowed us to identify 39 hits that were active in the primary screening assay and inactive in the counterscreen assay.

A comparison of in vitro cytotoxicity assays in medical device regulatory studies

Medical device biocompatibility testing is used to evaluate the risk of adverse effects on tissues from exposure to leachates/extracts. A battery of tests is typically recommended in accordance with regulatory standards to determine if the device is biocompatible. In vitro cytotoxicity, a key element of the standards, is a required endpoint for all types of medical devices. Each validated cytotoxicity method has different methodology and acceptance criteria that could influence the selection of a specific test. In addition, some guidances are more specific than others as to the recommended test methods. For example, the International Organization for Standardization (ISO¹) cites preference for quantitative methods (e.g., tetrazolium (MTT/XTT), neutral red (NR), or colony formation assays (CFA)) over qualitative methods (e.g., elution, agar overlay/diffusion, or direct), while a recent ISO standard for contact lens/lens care solutions specifically requires a qualitative direct test. Qualitative methods are described in United States Pharmacopeia (USP) while quantitative CFAs are listed in Japan guidance. The aim of this review is to compare the methodologies such as test article preparation, test conditions, and criteria for six cytotoxicity methods recommended in regulatory standards in order to inform decisions on which method(s) to select during the medical device safety evaluation.

Prediction of bioluminescent proteins by using sequence-derived features and lineage-specific scheme

Background

Bioluminescent proteins (BLPs) widely exist in many living organisms. As BLPs are featured by the capability of emitting lights, they can be served as biomarkers and easily detected in biomedical research, such as gene expression analysis and signal transduction pathways. Therefore, accurate identification of BLPs is important for disease diagnosis and biomedical engineering. In this paper, we propose a novel accurate sequence-based method named PredBLP (Prediction of BioLuminescent Proteins) to predict BLPs.

Results

We collect a series of sequence-derived features, which have been proved to be involved in the structure and function of BLPs. These features include amino acid composition, dipeptide composition, sequence motifs and physicochemical properties. We further prove that the combination of four types of features outperforms any other combinations or individual features. To remove potential irrelevant or redundant features, we also introduce Fisher Markov Selector together with Sequential Backward Selection strategy to select the optimal feature subsets. Additionally, we design a lineage-specific scheme, which is proved to be more effective than traditional universal approaches.

Conclusion

Experiment on benchmark datasets proves the robustness of PredBLP. We demonstrate that lineage-specific models significantly outperform universal ones. We also test the generalization capability of PredBLP based on independent testing datasets as well as newly deposited BLPs in UniProt. PredBLP is proved to be able to exceed many state-of-art methods. A web server named PredBLP, which implements the proposed method, is free available for academic use.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1709-6) contains supplementary material, which is available to authorized users.