Contact sites between mitochondria and endoplasmic reticulum (ER) are points in which the two organelles are in close proximity. Due to their structural and functional complexity, their exploitation as pharmacological targets has never been considered so far. Notwithstanding, the number of compounds described to target proteins residing at these interfaces either directly or indirectly is rising. Here we provide original insight into mitochondria–ER contact sites (MERCs), with a comprehensive overview of the current MERCs pharmacology. Importantly, we discuss the considerable potential of MERCs to become a druggable target for the development of novel therapeutic strategies.

Antibodies are indispensable tools for biomedicine and anticancer therapy. Nevertheless, their use is compromised by high production costs, limited stability, and difficulty of chemical modification. The design and preparation of synthetic polymer conjugates capable of replacing antibodies in biomedical applications such as ELISA, flow cytometry, immunocytochemistry, and immunoprecipitation is reported. The conjugates, named “iBodies”, consist of an HPMA copolymer decorated with low‐molecular‐weight compounds that function as targeting ligands, affinity anchors, and imaging probes. We prepared specific conjugates targeting several proteins with known ligands and used these iBodies for enzyme inhibition, protein isolation, immobilization, quantification, and live‐cell imaging. Our data indicate that this highly modular and versatile polymer system can be used to produce inexpensive and stable antibody substitutes directed toward virtually any protein of interest with a known ligand.

Glutamate carboxypeptidase II (GCPII), also known as prostate‐specific membrane antigen (PSMA) or folate hydrolase, is a metallopeptidase expressed predominantly in the human brain and prostate. GCPII expression is considerably increased in prostate carcinoma, and the enzyme also participates in glutamate excitotoxicity in the brain. Therefore, GCPII represents an important diagnostic marker of prostate cancer progression and a putative target for the treatment of both prostate cancer and neuronal disorders associated with glutamate excitotoxicity. For the development of novel therapeutics, mouse models are widely used. However, although mouse GCPII activity has been characterized, a detailed comparison of the enzymatic activity and tissue distribution of the mouse and human GCPII orthologs remains lacking. In this study, we prepared extracellular mouse GCPII and compared it with human GCPII. We found that mouse GCPII possesses lower catalytic efficiency but similar substrate specificity compared with the human protein. Using a panel of GCPII inhibitors, we discovered that inhibition constants are generally similar for mouse and human GCPII. Furthermore, we observed highest expression of GCPII protein in the mouse kidney, brain, and salivary glands. Importantly, we did not detect GCPII in the mouse prostate. Our data suggest that the differences in enzymatic activity and inhibition profile are rather small; therefore, mouse GCPII can approximate human GCPII in drug development and testing. On the other hand, significant differences in GCPII tissue expression must be taken into account when developing novel GCPII‐based anticancer and therapeutic methods, including targeted anticancer drug delivery systems, and when using mice as a model organism.

Recent proteomic, metabolomic, and transcriptomic studies have highlighted a connection between changes in mitochondria physiology and cellular pathophysiological mechanisms. Secondary assays to assess the function of these organelles appear fundamental to validate these -omics findings. Although mitochondrial membrane potential is widely recognized as an indicator of mitochondrial activity, high-content imaging-based approaches coupled to multiparametric to measure it have not been established yet. In this paper, we describe a methodology for the unbiased high-throughput quantification of mitochondrial membrane potential in vitro, which is suitable for 2D to 3D models. We successfully used our method to analyze mitochondrial membrane potential in monolayers of human fibroblasts, neural stem cells, spheroids, and isolated muscle fibers. Moreover, by combining automated image analysis and machine learning, we were able to discriminate melanoma cells from macrophages in co-culture and to analyze the subpopulations separately. Our data demonstrated that our method is a widely applicable strategy for large-scale profiling of mitochondrial activity.