In Silico Development of Combinatorial Therapeutic Approaches Targeting Key Signaling Pathways in Metabolic Syndrome
Purpose Dysregulations of key signaling pathways in metabolic syndrome are multifactorial, eventually leading to cardiovascular events. Hyperglycemia in conjunction with dyslipidemia induces insulin resistance and provokes release of proinflammatory cytokines resulting in chronic inflammation, accelerated lipid peroxidation with further development of atherosclerotic alterations and diabetes. We have proposed a novel combinatorial approach using FDA approved compounds targeting IL-17a and DPP4 to ameliorate a significant portion of the clustered clinical risks in patients with metabolic syndrome. In our current research we have modeled the outcomes of metabolic syndrome treatment using two distinct drug classes.
Methods Targets were chosen based on the clustered clinical risks in metabolic syndrome: dyslipidemia, insulin resistance, impaired glucose control, and chronic inflammation. Drug development platform, BIOiSIM™, was used to narrow down two different drug classes with distinct modes of action and modalities. Pharmacokinetic and pharmacodynamic profiles of the most promising drugs were modeling showing predicted outcomes of combinatorial therapeutic interventions.
Results Preliminary studies demonstrated that the most promising drugs belong to DPP-4 inhibitors and IL-17A inhibitors. Evogliptin was chosen to be a candidate for regulating glucose control with long term collateral benefit of weight loss and improved lipid profiles. Secukinumab, an IL-17A sequestering agent used in treating psoriasis, was selected as a repurposed candidate to address the sequential inflammatory disorders that follow the first metabolic insult.
Conclusions Our analysis suggests this novel combinatorial therapeutic approach inducing DPP4 and Il-17a suppression has a high likelihood of ameliorating a significant portion of the clustered clinical risk in metabolic syndrome.
Introduction
Metabolic syndrome (MetS) is a group of clinical conditions manifested as abdominal obesity, hyperglycemia, hypertension, dyslipidemia, and chronic inflammation, concurrently leading to a marked increase in the risk of heart disease, diabetes, and stroke, or all three (1, 2). Currently, MetS is a growing health concern due to its increasing prevalence globally (3). Statistics on MetS occurrence frequency varies depending on the subgroup (social status, ethnicity, etc.) and diagnostic criteria. Currently, ~ 25% of the world population has MetS (4, 5), of which, higher incidence of MetS is observed in the United States. The rapid increase in obesity rates in the last decades, which promotes insulin resistance (6), has driven the prevalence of MetS. Numerous clinical studies confirm direct correlation between MetS progression and type 2 diabetes mellitus incidence (7) and faster development of atherosclerosis (8). Medical care of MetS patients, including therapeutic treatment, is essential, as these patients are predisposed to a variety of cardiovascular, cerebral, and hepato-renal complications as well as increased overall mortality (9–12).
During MetS, the development of substantiate adipose accumulation represents a risk factor of insulin resistance and cardiovascular disease (13). Brown and white adipose tissue regulate numerous metabolic pathways that, when altered, can lead to the carbohydrate and lipid metabolism impairment. Hypertrophy and hyperplasia of the adipocytes result in metabolic alterations and in the onset of a low grade chronic inflammatory state (14) due to the release of pro-inflammatory adipokines from adipose tissue that can trigger insulin resistance and diabetes mellitus leading to a sequentially increased cardiovascular risk (15). Clinical studies have identified in MetS patients an increased level of proinflammatory cytokines, such as IL-1, IL-17, and IL-18, as playing a key role in the development of atherosclerotic alterations in blood vessels caused by lipid imbalance (16, 17). Dyslipidemia in MetS is characterized by increased circulating triglyceride level, reduced HDL-C concentration and consequently increased level of low-density lipoprotein cholesterol. These alterations, in turn, are closely related to impaired glucose metabolism and chronic inflammation, leading to a feedback loop encompassing MetS (18). The above mentioned systemic inflammatory markers reflect the main risk factors for the development of macrovascular complications that lead to a significant increase in morbidity and mortality. Manifestation of clustered clinical conditions in MetS is one of the leading causes of liver steatosis, which is confirmed by recurrence of non-alcoholic fatty liver disease in patients with MetS after liver transplantation (19).
MetS as a whole should not be treated by a single therapeutic as there are several predisposing genetic risk factors that have been identified, yet the underlying signaling mechanisms in this complex phenotype are not fully elucidated. Therefore, very often therapeutic measures generally focus on specific sub-syndromes that present themselves in a symptomatic fashion, in particular, hyperglycemia, hypertension and lipid imbalance. In general, initial treatment focuses on lifestyle modifications, e.g. diet and exercise to drive weight loss, which is still the first-line recommendation for prevention and even treatment of MetS (20). It has been observed that lifestyle intervention resulting in a 7% weight loss has driven resolution of MetS in 15.6% of participants that were followed for a mean of 3.2 years. Unfortunately, only 50% of monitored patients generally achieve a weight loss of 7% (21, 22). Thus, long-term compliance with a balanced lifestyle and diet restrictions is difficult to achieve let alone maintain in the target population. There- fore, pharmaceutical interventions are directed at achieving goals of lowering the low-density lipoprotein cholesterol level, blood pressure, blood glucose and hemoglobin A1c levels. Treatment may also involve drug therapy with antihypertensives, insulin sensitizers, and/or cholesterol-lowering agents (23). These therapeutic interventions have palliative effects that do not impact the key disorders in metabolic pathways leading to MetS progression. Thus, there exists a major unmet medical need for novel therapeutic treatments for MetS, ultimately preventing the development of cardiometabolic-related morbidity and mortality.
Currently, there are two main approaches under investigation for alleviating MetS progression (24). One strategy is the ‘polypill’, a variably assembled single capsule contain- ing a combination of drugs targeting several risk factors. Although the polypill cannot be titrated for better risk factor control when used alone, its advantages include simplicity and cost reduction if generic drugs are used. A second pharmacological strategy to treat patients with several risk factors while reducing the problems associated with polypharmacy is to either develop single drugs that have multiple targets or to modulate targets that affect several risk factors (24). Therefore, despite therapeutic mitigation of the main symptoms, such as high blood pressure and an elevated LDL blood level, MetS continues to progress in the patient. Relief of symptoms without direct intervention against the clustered risks in MetS treatment leads to inevitable com- plications. To that end, several approaches can be used successfully, such as repurposing of FDA approved drugs for combination therapies to mitigate and potentially reverse the majority of the clustered risks in MetS in patients.
The repurposing of FDA-approved drugs for novel combinatorial therapies targeting key pathways involved in MetS progression is a path of least resistance in establishing a pipeline for effective therapeutics. Commonalities affecting redundant signaling mechanisms between the sequential polytherapy and aggregate polypill therapeutic approaches exist, promoting a strategy targeting these common pathways known to upregulate blood glucose, insulin resistance, lipid metabolism, and expression of pro-inflammatory cytokines. Focus on these multi-stage-related biological targets inherent to both primary pathological hypotheses of MetS development is a promising avenue for the rapid repurposing of existing therapeutics. One of the fastest and comprehensive approaches for development of combinatorial therapies is utilization of in silico methods for repurposing of the currently used drugs. The data-rich nature of well-studied FDA-approved drugs is particularly amenable to our hybrid AI/ML-integrated modeling platform, BIOiSIM™ (25). The platform enables high-throughput computational compound screening based on experimentally validated simulations of in vivo pharmacokinetic-pharmacodynamic (PK-PD) phenomena. Our research strategy entails the development of novel mod- els for PK-PD predictions from repurposed drugs leading to combination therapies. This novel combinatorial approach targets biochemical pathways responsible for the development of insulin resistance with consequent dyslipidemia and chronic inflammation, accounting for ~ 70% of the clustered clinical conditions manifesting in MetS. The key pathways include, but are not limited to, signaling cascades regulated by farnesoid X receptors (FXR), peroxisome proliferator- activated receptor (PPAR)-α, δ, and γ, fibroblast growth factor 21 (FGF21), dipeptidyl peptidase 4 (DPP-4), and soluble episode hydrolase (sEH) regulated pathways as well as IL- 17a-modulated inflamatory reactions. Pharmacological interventions towards all these pathways may provide health benefits for patients with MetS. But in the current clinical landscape, single therapy has been at best palliative, unfortunately not showing a large degree of promise in reversing any of the clustered clinical conditions of MetS. Therefore, we have hypothesized a novel combinatorial tactic that entails a repurposing strategy as a part of the therapeutic approach against major clinical risks in MetS. Our novel perspective is based on PK-PD predictions of two distinct modalities. By targeting a core tandem of pathophysiological pathways in the patient population we will be able to increase a likelihood of ameliorating a large percentage of the clustered clinical risks manifested in MetS and a potential to address unmet medical needs.
In the present study, we performed a brief analysis of literature sources to determine the most promising pathways involved in metabolic regulations. Then, we used computational modeling and simulations to generate PD and efficacy outcomes for novel combinatorial therapies made of repurposed drugs engaging the above-mentioned path- ways. All therapeutics used in the study are FDA-approved products belonging to FXR agonists, DPP4 inhibitors, and IL-17a inhibitors. These drugs should target critical path- ways responsible for insulin resistance and inflammation in the progressive development of MetS. Using abundant PK-PD data from publicly available sources (e.g. preclinical and clinical datasets), we have modeled drug exposure and potential dosing regimen of pharmaceutical compounds in target tissues known to be involved in key stages of the MetS progression. An understanding of compounds capable of assuming optimal target engagement and regulation of the biological target structures will help accelerate the development of a targeted anti-MetS combinatorial therapy. Overall, our investigation has identified FDA-approved therapeutics using the drug development platform for repurposing of drugs, leading to combination therapies and associated dos- ing regimens in the patient populations.
Materials and MethodsMeta-Analysis of Pathways Involved in MetS
A global systematic search of Medline and Web of Science was performed through October 2011 for experimental and clinical studies elucidating metabolic pathways involved into induction and development of MetS and relevant therapies confirming their role in metabolic disorders. Our core search consisted of such terms as metabolic syndrome, insulin resistance syndrome, and dyslipidemia, combined with specific terms for each pathway and therapeutic: soluble episode hydrolase, PPAR, PPAR agonist, fi oblast growth factor, IL-17a, IL-17a inhibitor, dipeptidyl peptidase 4, DPP4, DPP4 inhibitor, Farnesoid X receptor, FXR, FXR agonist. Relevant journals, bibliographies, reviews, and personal files were hand searched for additional articles and supplementary data. Experimental PK and PD observables for DPP4 inhibitors, FXR agonists, and IL-17a inhibitors were taken from the sources found and digitized for the modeling purposes. Briefl , in vivo drug plasma concentration vs time curves as well as plasma concentration datasets with related biomarker levels were manually digitized from source publications using “WebPlotDigitizer” version 4.2.34, and handed off for PK-PD-Efficacy modeling.