Orally Bioavailable Macrocyclic Peptide That Inhibits Binding of PCSK9 to the Low Density Lipoprotein Receptor.

BACKGROUND: Inhibition of PCSK9 (proprotein convertase subtilisin/kexin type 9)-low density lipoprotein receptor interaction with injectable monoclonal antibodies or small interfering RNA lowers plasma low density lipoprotein-cholesterol, but despite nearly 2 decades of effort, an oral inhibitor of PCSK9 is not available. Macrocyclic peptides represent a novel approach to target proteins traditionally considered intractable to small-molecule drug design. METHODS: Novel mRNA display screening technology was used to identify lead chemical matter, which was then optimized by applying structure-based drug design enabled by novel synthetic chemistry to identify macrocyclic peptide (MK-0616) with exquisite potency and selectivity for PCSK9. Following completion of nonclinical safety studies, MK-0616 was administered to healthy adult participants in a single rising-dose Phase 1 clinical trial designed to evaluate its safety, pharmacokinetics, and pharmacodynamics. In a multiple-dose trial in participants taking statins, MK-0616 was administered once daily for 14 days to characterize the safety, pharmacokinetics, and pharmacodynamics (change in low density lipoprotein cholesterol). RESULTS: MK-0616 displayed high affinity (Ki = 5pM) for PCSK9 in vitro and sufficient safety and oral bioavailability preclinically to enable advancement into the clinic. In Phase 1 clinical studies in healthy adults, single oral doses of MK-0616 were associated with >93% geometric mean reduction (95% CI, 84-103) of free, unbound plasma PCSK9; in participants on statin therapy, multiple-oral-dose regimens provided a maximum 61% geometric mean reduction (95% CI, 43-85) in low density lipoprotein cholesterol from baseline after 14 days of once-daily dosing of 20 mg MK-0616. CONCLUSIONS: This work validates the use of mRNA display technology for identification of novel oral therapeutic agents, exemplified by the identification of an oral PCSK9 inhibitor, which has the potential to be a highly effective cholesterol lowering therapy for patients in need.

Disruption of PAK3 Signaling in Social Interaction Induced cFos Positive Cells Impairs Social Recognition Memory.

P21-activated kinase 3 (PAK3) gene mutations are linked to several neurodevelopmental disorders, but the underlying mechanisms remain unclear. In this study, we used a tetracycline-inducible system to control the expression of a mutant PAK3 (mPAK3) protein in immediate early gene, namely cFos, positive cells to disrupt PAK signaling, specifically in cells activated by social interaction in transgenic mice. We show that the expression of mPAK3-GFP proteins was in cFos-expressing excitatory and inhibitory neurons in various brain regions, such as the cortex and hippocampus, commonly activated during learning and memory. Basal expression of mPAK3-GFP proteins in cFos-positive cells resulted in social recognition memory deficits in the three-chamber social interaction test, without affecting locomotor activity or other forms of memory. The social memory deficit was rescued by doxycycline to halt the mPAK3-GFP transgene expression. In addition, we show that the expression of mPAK3-GFP proteins in a subset of cFos-positive cells, induced by an antecedent short social interaction, termed social pairing, was sufficient to impair social recognition memory. These results indicate that normal PAK signaling in cFos-positive cells activated during social interaction is critical for social memory.

Novel Application of the Two-Period Microtracer Approach to Determine Absolute Oral Bioavailability and Fraction Absorbed of Ertugliflozin.

Ertugliflozin, a sodium glucose cotransporter-2 inhibitor, is approved in the United States for treatment of type 2 diabetes mellitus. A novel two-period study design with 14 C microtracer dosing in each period was used to determine absolute oral bioavailability (F) and fraction absorbed (Fa ) of ertugliflozin. Eight healthy adult men received 100-µg i.v. 14 C-ertugliflozin (400 nCi) dose 1 h after a 15-mg oral unlabeled ertugliflozin dose (period 1), followed by 100 µg 14 C-ertugliflozin orally along with 15 mg oral unlabeled ertugliflozin (period 2). Unlabeled ertugliflozin plasma concentrations were determined using high-performance liquid-chromatography tandem mass spectrometry (HPLC-MS/MS). 14 C-ertugliflozin plasma concentrations were determined using HPLC-accelerator mass spectrometry (AMS) and 14 C urine concentrations were determined using AMS. F ((area under the curve (AUC)p.o. /14 C-AUCi.v. )*(14 C-Dosei.v. /Dosep.o. )) and Fa ((14 C_Total_Urinep.o. /14 C_Total_Urinei.v. )* (14 C-Dosei.v. /14 C-Dosep.o. )) were estimated. Estimates of F and Fa were 105% and 111%, respectively. Oral absorption of ertugliflozin was complete under fasted conditions and F was ∼100%. Ertugliflozin was well tolerated.

Systematic Screening of Chemokines to Identify Candidates to Model and Create Ectopic Lymph Node Structures for Cancer Immunotherapy.

The induction of ectopic lymph node structures (ELNs) holds great promise to augment immunotherapy against multiple cancers including metastatic melanoma, in which ELN formation has been associated with a unique immune-related gene expression signature composed of distinct chemokines. To investigate the therapeutic potential of ELNs induction, preclinical models of ELNs are needed for interrogation of these chemokines. Computational models provide a non-invasive, cost-effective method to investigate leukocyte trafficking in the tumor microenvironment, but parameterizing such models is difficult due to differing assay conditions and contexts among the literature. To better achieve this, we systematically performed microchemotaxis assays on purified immune subsets including human pan-T cells, CD4+ T cells, CD8+ T cells, B cells, and NK cells, with 49 recombinant chemokines using a singular technique, and standardized conditions resulting in a dataset representing 238 assays. We then outline a groundwork computational model that can simulate cellular migration in the tumor microenvironment in response to a chemoattractant gradient created from stromal, lymphoid, or antigen presenting cell interactions. The resulting model can then be parameterized with standardized data, such as the dataset presented here, and demonstrates how a computational approach can help elucidate developing ELNs and their impact on tumor progression.