Combined Virtual and Experimental Screening for CK1 Inhibitors Identifies a Modulator of p53 and Reveals Important Aspects of in Silico Screening Performance

Senotherapeutic-like effect of Silybum marianum flower extract revealed on human skin cells

Cellular senescence causes irreversible growth arrest of cells. Prolonged accumulation of senescent cells in tissues leads to increased detrimental effects due to senescence associated secretory phenotype (SASP). Recent findings suggest that elimination of senescent cells has a beneficial effect on organismal aging and lifespan. In this study, using a validated replicative senescent human dermal fibroblasts (HDFs) model, we showed that elimination of senescent cells is possible through the activation of an apoptotic mechanism. We have shown in this replicative senescence model, that cell senescence is associated with DNA damage and cell cycle arrest (p21, p53 markers). We have shown that Silybum marianum flower extract (SMFE) is a safe and selective senolytic agent targeting only senescent cells. The elimination of the cells is induced through the activation of apoptotic pathway confirmed by annexin V/propidium iodide and caspase-3/PARP staining. Moreover, SMFE suppresses the expression of SASP factors such as IL-6 and MMP-1 in senescent HDFs. In a co-culture model of senescent and young fibroblasts, we demonstrated that senescent cells impaired the proliferative capacities of young cells. Interestingly, when the co-culture is treated with SMFE, the cell proliferation rate of young cells is increased due to the decrease of the senescent burden. Moreover, we demonstrated in vitro that senescent fibroblasts trigger senescent process in normal keratinocytes through a paracrine effect. Indeed, the conditioned medium of senescent HDFs treated with SMFE reduced the level of senescence-associated beta-galactosidase (SA-β-Gal), p16INK4A and SASP factors in keratinocytes compared with CM of senescent HDFs. These results indicate that SMFE can prevent premature aging due to senescence and even reprograms aged skin. Indeed, thanks to its senolytic and senomorphic properties SMFE is a candidate for anti-senescence strategies.

Recent Advances in the Development of Casein Kinase 1 Inhibitors

BACKGROUND

The casein kinase 1 (CK1) family is involved in regulating many cellular processes, including membrane trafficking, DNA damage repair, cytoskeleton dynamics, cytoskeleton maintenance and apoptosis. CK1 isoforms, especially CK1δ and CK1ε have emerged as important therapeutic targets for severe disorders such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), familial advanced sleep phase syndrome and cancer. Due to the importance of CK1 for the pathogenesis of disorders, there are great interests in the development of CK1 inhibitors.

METHODS

Using SciFinder® as a tool, the publications about the biology of CK1 and the recent developments of CK1 inhibitors were surveyed with an exclusion of those published as patents.

RESULTS

This review presents the current state of knowledge on the development of CK1 inhibitors, including both synthetic small molecular inhibitors that were divided into 7 categories according to structural features, and the natural compounds. An overview of the advancement of CK1 inhibitors was given, with the introduction of various existing CK1 inhibitors, their inhibitory activities, and the structure-activity relationships.

CONCLUSION

Through physicochemical characterization and biological investigations, it is possible to understand the structure-activity relationship of CK1 inhibitors, which will contribute to better design and discovery of potent and selective CK1 inhibitors as potential agents for severe disorders such as AD, ALS and cancer.

Predicting Potential Endocrine Disrupting Chemicals Binding to Estrogen Receptor α (ERα) Using a Pipeline Combining Structure-Based and Ligand-Based in Silico Methods

The estrogen receptors α (ERα) are transcription factors involved in several physiological processes belonging to the nuclear receptors (NRs) protein family. Besides the endogenous ligands, several other chemicals are able to bind to those receptors. Among them are endocrine disrupting chemicals (EDCs) that can trigger toxicological pathways. Many studies have focused on predicting EDCs based on their ability to bind NRs; mainly, estrogen receptors (ER), thyroid hormones receptors (TR), androgen receptors (AR), glucocorticoid receptors (GR), and peroxisome proliferator-activated receptors gamma (PPARγ). In this work, we suggest a pipeline designed for the prediction of ERα binding activity. The flagged compounds can be further explored using experimental techniques to assess their potential to be EDCs. The pipeline is a combination of structure based (docking and pharmacophore models) and ligand based (pharmacophore models) methods. The models have been constructed using the Environmental Protection Agency (EPA) data encompassing a large number of structurally diverse compounds. A validation step was then achieved using two external databases: the NR-DBIND (Nuclear Receptors DataBase Including Negative Data) and the EADB (Estrogenic Activity DataBase). Different combination protocols were explored. Results showed that the combination of models performed better than each model taken individually. The consensus protocol that reached values of 0.81 and 0.54 for sensitivity and specificity, respectively, was the best suited for our toxicological study. Insights and recommendations were drawn to alleviate the screening quality of other projects focusing on ERα binding predictions.

Achieving effective and selective CK1 inhibitors through structure modification

Casein kinase 1 (CK1) is an extensively expressed serine/threonine kinase family, with six highly conserved isoforms of human CK1. Due to its involvement in many biological processes, CK1 is a promising target for several pathological states, including circadian sleep disorder, neurodegenerative diseases, cancer and inflammation. However, due to the structural similarities between the six CK1 members, the design of CK1 inhibitors is intricate. So far, no effective CK1 inhibitors are reported to reach clinical trials; thus, approaches to obtaining both selective and effective CK1 inhibitors are in great demand. Here we analyze several CK1 inhibitors that provide successful experience for structure-based drug design and rational structure modification, which could provide references for further drug design.

Structure, regulation, and (patho-)physiological functions of the stress-induced protein kinase CK1 delta (CSNK1D)

Members of the highly conserved pleiotropic CK1 family of serine/threonine-specific kinases are tightly regulated in the cell and play crucial regulatory roles in multiple cellular processes from protozoa to human. Since their dysregulation as well as mutations within their coding regions contribute to the development of various different pathologies, including cancer and neurodegenerative diseases, they have become interesting new drug targets within the last decade. However, to develop optimized CK1 isoform-specific therapeutics in personalized therapy concepts, a detailed knowledge of the regulation and functions of the different CK1 isoforms, their various splice variants and orthologs is mandatory. In this review we will focus on the stress-induced CK1 isoform delta (CK1δ), thereby addressing its regulation, physiological functions, the consequences of its deregulation for the development and progression of diseases, and its potential as therapeutic drug target.

From bench to bedside, via desktop. Recent advances in the application of cutting-edge in silico tools in the research of drugs targeting bromodomain modules

The discipline of drug discovery has greatly benefited by computational tools and in silico algorithms aiming at rationalization of many related processes, from the stage of early hit identification to the preclinical phases of drug candidate validation. The various methodologies referred to as molecular modeling tools span a broad spectrum of applications, from straightforward approaches such as virtual screening of compound libraries to more advanced techniques involving the precise estimation of free energy upon binding of the candidate drug to its macromolecular target. To this end, we report an overview of specific studies where implementation of such sophisticated modeling algorithms has shown to be indispensable for addressing challenging systems and biological questions otherwise difficult to answer. We focus our attention on the emerging field of bromodomain inhibitors. Bromodomains are small modules involved in epigenetic signaling and currently comprise high-priority targets for developing both drug candidates and chemical probes for basic biomedical research. We attempt a critical presentation of selected cases utilizing cutting-edge in silico methodologies, with our main emphasis being on absolute or relative free energy simulations, on implementation of quantum-mechanics level calculations and on characterization of solvent thermodynamics. We discuss the advantages and strengths as well as the drawbacks and weaknesses of computational tools utilized in those works and we attempt to comment on specific issues related to their integration into the regular medicinal chemistry practice. Our conclusion is that while such methods indeed represent highly promising resources for further advancing the discipline, their application is not always trivial.

A facile consensus ranking approach enhances virtual screening robustness and identifies a cell-active DYRK1α inhibitor

BACKGROUND

Virtual screening is vital for contemporary drug discovery but striking performance fluctuations are commonly encountered, thus hampering error-free use. Results and Methodology: A conceptual framework is suggested for combining screening algorithms characterized by orthogonality (docking-scoring calculations, 3D shape similarity, 2D fingerprint similarity) into a simple, efficient and expansible python-based consensus ranking scheme. An original experimental dataset is created for comparing individual screening methods versus the novel approach. Its utilization leads to identification and phosphoproteomic evaluation of a cell-active DYRK1α inhibitor.

CONCLUSION

Consensus ranking considerably stabilizes screening performance at reasonable computational cost, whereas individual screens are heavily dependent on calculation settings. Results indicate that the novel approach, currently available as a free online tool, is highly suitable for prospective screening by nonexperts.