Development of Agonist-Based PROTACs Targeting Liver X Receptor

Liver X receptors (LXRs) belong to the nuclear hormone receptor superfamily and function as ligand-dependent transcription factors that regulate cholesterol homeostasis, lipid homeostasis, and immune responses. LXR antagonists are promising treatments for hypercholesterolemia and diabetes. However, effective LXR antagonists and inhibitors are yet to be developed. Thus, we aimed to develop LXR degraders (proteolysis targeting chimeras PROTACs against LXR) as a complementary strategy to provide a similar effect to LXR inhibition. In this study, we report the development of GW3965-PEG5-VH032 (3), a PROTAC capable of effectively degrading LXRβ protein. Compound 3 induced the ubiquitin-proteasome system-dependent degradation of the LXRβ protein, which requires VHL E3 ligase. We hope that PROTACs targeting LXR proteins will become novel therapeutic agents for LXR-related diseases.

Cholinergic System and Its Therapeutic Importance in Inflammation and Autoimmunity

Neurological and immunological signals constitute an extensive regulatory network in our body that maintains physiology and homeostasis. The cholinergic system plays a significant role in neuroimmune communication, transmitting information regarding the peripheral immune status to the central nervous system (CNS) and vice versa. The cholinergic system includes the neurotransmitter\ molecule, acetylcholine (ACh), cholinergic receptors (AChRs), choline acetyltransferase (ChAT) enzyme, and acetylcholinesterase (AChE) enzyme. These molecules are involved in regulating immune response and playing a crucial role in maintaining homeostasis. Most innate and adaptive immune cells respond to neuronal inputs by releasing or expressing these molecules on their surfaces. Dysregulation of this neuroimmune communication may lead to several inflammatory and autoimmune diseases. Several agonists, antagonists, and inhibitors have been developed to target the cholinergic system to control inflammation in different tissues. This review discusses how various molecules of the neuronal and non-neuronal cholinergic system (NNCS) interact with the immune cells. What are the agonists and antagonists that alter the cholinergic system, and how are these molecules modulate inflammation and immunity. Understanding the various functions of pharmacological molecules could help in designing better strategies to control inflammation and autoimmunity.

Biology and Clinical Applicability of Plasma Thymus and Activation-Regulated Chemokine (TARC) in Classical Hodgkin Lymphoma

Thymus and activation-regulated chemokine (TARC) is produced by different cell types and is highly expressed in the thymus. It plays an important role in T cell development, trafficking and activation of mature T cells after binding to its receptor C-C chemokine receptor type 4 (CCR4) and consecutive signal transducer and activator of transcription 6 (STAT6) activation. Importantly, TARC is also produced by malignant Hodgkin and Reed–Sternberg (HRS) cells of classical Hodgkin lymphoma (cHL). In cHL, HRS cells survive and proliferate due to the micro-environment consisting primarily of type 2 T helper (Th2) cells. TARC-mediated signaling initiates a positive feedback loop that is crucial for the interaction between HRS and T cells. The clinical applicability of TARC is diverse. It is useful as diagnostic biomarker in both children and adults with cHL and in other Th2-driven diseases. In adult cHL patients, TARC is also a biomarker for treatment response and prognosis. Finally, blocking TARC signaling and thus inhibiting pathological Th2 cell recruitment could be a therapeutic strategy in cHL. In this review, we summarize the biological functions of TARC and focus on its role in cHL pathogenesis and as a biomarker for cHL and other diseases. We conclude by giving an outlook on putative therapeutic applications of antagonists and inhibitors of TARC-mediated signaling.

Antagonistic Control of Genetic Circuit Performance for Rapid Analysis of Targeted Enzyme Activity in Living Cells

Genetic circuits have been developed for quantitative measurement of enzyme activity, metabolic engineering of strain development, and dynamic regulation of microbial cells. A genetic circuit consists of several bio-elements, including enzymes and regulatory cassettes, that can generate the desired output signal, which is then used as a precise criterion for enzyme screening and engineering. Antagonists and inhibitors are small molecules with inhibitory effects on regulators and enzymes, respectively. In this study, an antagonist and an inhibitor were applied to a genetic circuit for a dynamic detection range. We developed a genetic circuit relying on regulators and enzymes, allowing for straightforward control of its output signal without additional genetic modification. We used para-nitrophenol and alanine as an antagonist of DmpR and inhibitor of tyrosine phenol-lyase, respectively. We show that the antagonist resets the detection range of the genetic circuit similarly to a resistor in an electrical logic circuit. These biological resistors in genetic circuits can be used as a rapid and precise controller of variable outputs with minimal circuit configuration.

Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning

<p>A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic targets and disease stages involved in the SARS-CoV-2 induced COVID-19 pandemic, which include plasma kallikrein, HIV protease, NSP5, NSP12, JAK family and AT-1. The approach was highly accurate in determining the matched target for the different compound sets and suggests that the models could be used for virtual screening of target specific compound libraries. The curation-modeling process was successfully applied to a SARS-CoV-2 phenotypic screen and could be used for predictive bioactivity estimation and prioritization for clinical trial selection, virtual screening of drug libraries for repurposing of drug molecules, and analysis and direction of proprietary datasets.</p>

Novel Development of Predictive Feature Fingerprints to Identify Chemistry-Based Features for Effective Drug Design of SARS-CoV-2 Target Antagonists and Inhibitors Using Machine Learning

<p>A unique approach to bioactivity and chemical data curation coupled with Random forest analyses has led to a series of target-specific and cross-validated Predictive Feature Fingerprints (PFF) that have high predictability across multiple therapeutic targets and disease stages involved in the SARS-CoV-2 induced COVID-19 pandemic, which include plasma kallikrein, HIV protease, NSP5, NSP12, JAK family and AT-1. The approach was highly accurate in determining the matched target for the different compound sets and suggests that the models could be used for virtual screening of target specific compound libraries. The curation-modeling process was successfully applied to a SARS-CoV-2 phenotypic screen and could be used for predictive bioactivity estimation and prioritization for clinical trial selection, virtual screening of drug libraries for repurposing of drug molecules, and analysis and direction of proprietary datasets.</p>