With the growth of protein structure data, the analysis of molecular interactions between ligands and their target molecules is gaining importance. PLIP, the protein–ligand interaction profiler, detects and visualises these interactions and provides data in formats suitable for further processing. PLIP has proven very successful in applications ranging from the characterisation of docking experiments to the assessment of novel ligand–protein complexes. Besides ligand–protein interactions, interactions with DNA and RNA play a vital role in many applications, such as drugs targeting DNA or RNA-binding proteins. To date, over 7% of all 3D structures in the Protein Data Bank include DNA or RNA. Therefore, we extended PLIP to encompass these important molecules. We demonstrate the power of this extension with examples of a cancer drug binding to a DNA target, and an RNA–protein complex central to a neurological disease. PLIP is available online at https://plip-tool.biotec.tu-dresden.de and as open source code. So far, the engine has served over a million queries and the source code has been downloaded several thousand times.
We identified a subset of Chronic Lymphocytic Leukemia (CLL) patients with high Signaling Lymphocytic Activation Molecule Family (SLAMF) receptor-related signaling that showed an indolent clinical course. Since SLAMF receptors play a role in NK cell biology, we reasoned that these receptors may impact NK cell-mediated CLL immunity. Indeed, our experiments showed significantly decreased degranulation capacity of primary NK cells from CLL patients expressing low levels of SLAMF1 and SLAMF7. Since the SLAMFlow signature was strongly associated with an unmutated CLL immunoglobulin heavy chain (IGHV) status in large datasets, we investigated the impact of SLAMF1 and SLAMF7 on the B cell receptor (BCR) signaling axis. Overexpression of SLAMF1 or SLAMF7 in IGHV mutated CLL cell models resulted in reduced proliferation and impaired responses to BCR ligation, whereas the knockout of both receptors showed opposing effects and increased sensitivity toward inhibition of components of the BCR pathway. Detailed molecular analyzes showed that SLAMF1 and SLAMF7 receptors mediate their BCR pathway antagonistic effects via recruitment of prohibitin-2 (PHB2) thereby impairing its role in signal transduction downstream the IGHV-mutant IgM-BCR. Together, our data indicate that SLAMF receptors are important modulators of the BCR signaling axis and may improve immune control in CLL by interference with NK cells.
Chagas disease, caused by the parasite Trypanosoma cruzi, affects millions of people in South America. The current treatments are limited, have severe side effects, and are only partially effective. Drug repositioning, defined as finding new indications for already approved drugs, has the potential to provide new therapeutic options for Chagas. In this work, we conducted a structure-based drug repositioning approach with over 130,000 3D protein structures to identify drugs that bind therapeutic Chagas targets and thus represent potential new Chagas treatments. The screening yielded over 500 molecules as hits, out of which 38 drugs were prioritized following a rigorous filtering process. About half of the latter were already known to have trypanocidal activity, while the others are novel to Chagas disease. Three of the new drug candidates—ciprofloxacin, naproxen, and folic acid—showed a growth inhibitory activity in the micromolar range when tested ex vivo on T. cruzi trypomastigotes, validating the prediction. We show that our drug repositioning approach is able to pinpoint relevant drug candidates at a fraction of the time and cost of a conventional screening. Furthermore, our results demonstrate the power and potential of structure-based drug repositioning in the context of neglected tropical diseases where the pharmaceutical industry has little financial interest in the development of new drugs.
Pan-assay interference compounds (PAINS) are promiscuous compound classes that produce false positive hits in high-throughput screenings. Yet, the mechanisms of PAINS activity are poorly understood. Although PAINS are often associated with protein reactivity, several recent studies have shown that they also mediate noncovalent interactions. Aiming at a deep understanding of PAINS promiscuity, we performed an analysis of the Protein Data Bank to characterize the binding modes of PAINS. We explored the binding mode conservation of 34 PAINS classes present in 871 ligands and among 517 protein targets. The two major findings of this work are the following: First, different PAINS classes exhibit different levels of binding mode conservation. Our novel classification of PAINS based on binding mode similarity enables a rational assessment of PAINS from a structural perspective. Second, PAINS classes with variable binding modes can bind with high affinity. The evaluation of noncovalent binding modes of PAINS-like compounds sheds light on the mechanisms of promiscuous binding. Our findings could facilitate the decisions on how to deal with PAINS and help scientists to understand why PAINS produce hits in their screenings.
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