Skp2 E3 ligase is overexpressed in numerous human cancers and plays a critical role in cell cycle progression, senescence, metabolism, cancer progression and metastasis. In the present study, we identified a specific Skp2 inhibitor using high-throughput in silico screening of large and diverse chemical libraries. This Skp2 inhibitor selectively suppresses Skp2 E3 ligase activity, but not activity of other SCF complexes. It also phenocopies the effects observed upon genetic Skp2 deficiency, such as suppressing survival, Akt-mediated glycolysis as well as triggering p53-independent cellular senescence. Strikingly, we discovered a critical function of Skp2 in positively regulating cancer stem cell populations and self-renewal ability through genetic and pharmacological approaches. Notably, Skp2 inhibitor exhibits potent anti-tumor activities in multiple animal models and cooperates with chemotherapeutic agents to reduce cancer cell survival. Our study thus provides pharmacological evidence that Skp2 is a promising target for restricting cancer stem cell and cancer progression.

PI3K/Akt signaling is activated in cancers and governs tumor initiation and progression, but how Akt is activated under diverse stresses is poorly understood. Here we identify AMPK as an essential regulator for Akt activation by various stresses. Surprisingly, AMPK is also activated by growth factor EGF through Ca2+/Calmodulin-dependent kinase and is essential for EGF-mediated Akt activation and biological functions. AMPK phosphorylates Skp2 at S256 and promotes the integrity and E3 ligase activity of Skp2 SCF complex leading to K63-linked ubiquitination and activation of Akt and subsequent oncogenic processes. Importantly, AMPK-mediated Skp2 S256 phosphorylation promotes breast cancer progression in mouse tumor models, correlates with Akt and AMPK activation in breast cancer patients, and predicts poor survival outcomes. Finally, targeting AMPK-mediated Skp2 S256 phosphorylation sensitizes cells to anti-EGF receptor targeted therapy. Our study sheds light on how stress and EGF induce Akt activation and new mechanisms for AMPK-mediated oncogenesis and drug resistance.

Ubiquitination, the structured degradation and turnover of cellular proteins, is regulated by the ubiquitin-proteasome system. Most proteins that are critical for cellular regulations and functions are targets of the process. Ubiquitination is comprised of a sequence of three enzymatic steps, and aberrations in the pathway can lead to tumor development and progression as observed in many cancer types. Recent evidence indicates that targeting the ubiquitin-proteasome system is effective for certain cancer treatment, but many more potential targets might have been previously overlooked. In this review, we will discuss the current state of small molecules that target various elements of ubiquitination. Special attention will be given to novel inhibitors of E3 ubiquitin ligases, especially those in the SCF family.Ubiquitination, a step in the nonlysosomal degradation of proteins, is a crucial post-translational modification in eukaryotic organisms. Rapid and timely degradation of transcriptional regulators and other proteins by the ubiquitin-proteasome system (UPS) regulates a wide variety of cellular processes [1]. Ubiquitination involves covalent attachment of ubiquitin, a small 8-kDa protein, to a substrate and results in recognition and shuttling of the substrate to the 26S proteasome complex for degradation [2]. It is important to note that the ubiquitination process combined with the proteasome complex step is also referred to as the ubiquitin-proteasome system (UPS) or ubiquitin proteasome pathway (UPP).The ubiquitination process is tightly controlled by three families of enzymes: ubiquitin-activating enzymes (E1s), ubiquitin-conjugating enzymes (E2s), and finally ubiquitin-protein enzymes (E3s). There exists two E1 enzymes with ubiquitin-activating capability: UBA1 being the primary E1 and the recently discovered UBA6 with unclear functions and uncharacterized regulations [3,4]. In contrast to the small number of E1s, there are approximately 40 E2s [5,6] and 500-1000 human E3 ligases, providing both specificity and versatility [7]. The three steps of the ubiquitination process (Figure 1) have been reviewed previously [8,9]. Briefly, the activation step requires binding of both ATP and ubiquitin and links the α-carboxyl group of the C-terminal glycine residue of ubiquitin to a cysteine residue on E1, and a thioester linkage is formed between the u biquitin and E1.Then the E2 binds to both activated ubiquitin and the E1 enzyme and thus transfers the ubiquitin from E1 to the active site cysteine of the E2 via a trans(thio)esterification reaction. Finally, the E3 catalyzes the linking of ubiquitin to a lysine residue on the substrate. Repetitions of these sequential steps results in a long chains of ubiquitin (polyubiquitin) on the protein to be degraded, and the specific lysine residue on ubiquitin used for linking (e.g., K48, K63, etc.) results in different topologies [10]. Ubiquitination was originally described as a mechanism by which cells dispose of short-lived, damaged, or abnormal proteins, but more rece...

Glucuronidation is often recognized as one of the rate-determining factors that limit the bioavailability of flavonols. Hence, design and synthesis of more bioavailable flavonols would benefit from the establishment of predictive models of glucuronidation using kinetic parameters [e.g., K m , V max , intrinsic clearance (CL int ) ϭ V max /K m ] derived for flavonols. This article aims to construct position (3-OH)-specific comparative molecular field analysis (CoMFA) models to describe UDP-glucuronosyltransferase (UGT) 1A9-mediated glucuronidation of flavonols, which can be used to design poor UGT1A9 substrates. The kinetics of recombinant UGT1A9-mediated 3-O-glucuronidation of 30 flavonols was characterized, and kinetic parameters (K m , V max , CL int ) were obtained. The observed K m , V max , and CL int values of 3-O-glucuronidation ranged from 0.04 to 0.68 M, 0.04 to 12.95 nmol/mg/min, and 0.06 to 109.60 ml/mg/min, respectively. To model UGT1A9-mediated glucuronidation, 30 flavonols were split into the training (23 compounds) and test (7 compounds) sets. These flavonols were then aligned by mapping the flavonols to specific common feature pharmacophores, which were used to construct CoMFA models of V max and CL int , respectively. The derived CoMFA models possessed good internal and external consistency and showed statistical significance and substantive predictive abilities (V max model: q 2 ϭ 0.738, r 2 ϭ 0.976, r pred 2 ϭ 0.735; CL int model: q 2 ϭ 0.561, r 2 ϭ 0.938, r pred 2 ϭ 0.630). The contour maps derived from CoMFA modeling clearly indicate structural characteristics associated with rapid or slow 3-O-glucuronidation. In conclusion, the approach of coupling CoMFA analysis with a pharmacophore-based structural alignment is viable for constructing a predictive model for regiospecific glucuronidation rates of flavonols by UGT1A9.

Stabilization of protein–protein interactions (PPIs) holds great potential for therapeutic agents, as illustrated by the successful drugs rapamycin and lenalidomide. However, how such interface-binding molecules can be created in a rational, bottom-up manner is a largely unanswered question. We report here how a fragment-based approach can be used to identify chemical starting points for the development of small-molecule stabilizers that differentiate between two different PPI interfaces of the adapter protein 14-3-3. The fragments discriminately bind to the interface of 14-3-3 with the recognition motif of either the tumor suppressor protein p53 or the oncogenic transcription factor TAZ. This X-ray crystallography driven study shows that the rim of the interface of individual 14-3-3 complexes can be targeted in a differential manner with fragments that represent promising starting points for the development of specific 14-3-3 PPI stabilizers.

No abstract

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

The serine/threonine kinase Akt has proven to be a significant signaling target, involved in various biological functions. Because of its cardinal role in numerous cellular responses, Akt has been implicated in many human diseases, particularly cancer. It has been established that Akt is a viable and feasible target for anticancer therapeutics. Analysis of all Akt kinases reveals conserved homology for an N-terminal regulatory domain, which contains a pleckstrin-homology (PH) domain for cellular translocation, a kinase domain with serine/threonine specificity, and a C-terminal extension domain. These well defined regions have been targeted, and various approaches, including in silico methods, have been implemented to develop Akt inhibitors. In spite of unique techniques and a prolific body of knowledge surrounding Akt, no targeted Akt therapeutics have reached the market yet. Here we will highlight successes and challenges to date on the development of anticancer agents modulating the Akt pathway in recent patents as well as discuss the methods employed for this task. Special attention will be given to patents with focus on those discoveries using computer-aided drug design approaches.