In Silico Development of Combinatorial Therapeutic Approaches Targeting Key Signaling Pathways in Metabolic Syndrome

Originally published in Pharmaceutical Research

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.


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 Methods

Meta-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.

Overview of the BIOiSIM™ Platform

BIOiSIM™ is an in silico AI-driven simulation platform that integrates machine learning with core semi-mechanistic models. The core functionality of our software platform used in the present study was largely described previously (26). The compartments are linked together using ordinary differential equations as a function of tissue-dependent fl dynamics, binding, partitioning and species-specific physiological characteristics (27). Among many, a key application of BIOiSIM™ is integrated modeling methods and prediction of PK-PD-Efficacy in the drug discovery and development pipeline. For this publication, BIOiSIM™ inputs include subject-specific parameters (organ volumes, blood flow rates, tissue composition, enzyme expression levels), relevant PK mechanisms (clearance, drug dissolution, permeability), among others. The platform is capable of utilizing AI/ML algorithms to either complete the missing parameters, e.g., if the drug properties are not provided, or provide predictive solutions to utilize existing in vivo and/or in vitro datasets. Model inputs include physiologically-specific parameters such as organ volumes, tissue composition, and blood flow rates, as well as mechanisms for clearance, drug solubility, and both intestinal and transdermal absorption. For this study, the implementation of the BIOiSIM™ model used was similar to commonly accepted physiologically-based pharmacokinetic (PBPK) models. Secondary inputs include drug-specific physicochemical properties and PK data such as in vitro microsomal clearances and fractions unbound in plasma. The platform utilizes a combination of Python and the Wolfram Language (28) to cross-validate PBPK simulations using a multicompartment model and PD and efficacy simulations via auxiliary models integrated into the centralized framework. The Python system makes use of auxiliary packages matplotlib (v2.0.2) and NumPy (v1.14.2); the Wolfram Language is a self-contained system (Mathematica v.12.3.1) (28). The software systems are hosted on Amazon Web Services (AWS) cloud, enabling high-throughput, parallelized PK or PD and Efficacy simulations, which are available on the VeriSIM Life customer portal, BIOiWare. The BIOiSIM™ platform was utilized to predict drug concentration following multiple administration with consequent target engagement in the model described below.

Learn more about VeriSIM Life’s BIOiSIM platform and unique Translational Index™️ technology.

Drug PD and Efficacy Modeling

Secukinumab pharmacokinetic and pharmacodynamic data (total serum IL-17A levels versus time) taken from the study of Bruin et al. (29) were digitized and analyzed. Free serum concentrations of IL-17A were computed implicitly via the Morrison equation from a solution to Eq. 1 (30). All concentrations were determined in μg/L and Secukinumab was assumed to bind two equivalents of IL-17A. Untreated free levels of IL-17A were below the limit of quantification in the report. A 52-week study in which Secukinumab was dosed subcutaneously (s.c.) at 150 mg weekly for the first 4 weeks and then once every 4 weeks for up to 52 weeks (extracted from Bruin et al., Fig. 5) was used, from which total IL-17A data were used to find best fit values of the untreated IL-17A concentration and its zero-order formation rate.

where [IL17]0 is the untreated serum concentration of IL- 17A, which was assumed to have been at steady-state prior to treatment.

where Kd = 45 nM [33].

Medications targeting DPP4 or FXR used in the study included Linagliptin, Evogliptin, Alogliptin, and Tropifexor, respectively. PK and target inhibition profiles of those drugs were collected from prior reports (31–34). PK and target engagement profiles were modeled within the BIOiSIM™ environment. Initially, each PK-PD pro- file was examined to determine if it was consistent with a direct response model. Observed DPP-4 inhibition was aligned with observed or imputed plasma concentrations and modeled as a direct response by use of Eq. 4.

DPP4 inhibitor pharmacokinetic profile, associated DPP-4 activity level and blood glucose concentration after chronic dosing were extracted from publicly available sources (33, 35–37). The percent inhibition of DPP-4 was computed from a best fit of Eq. 4.

Glucose challenge test analysis, study data reported in (35) were digitized and Glucose levels were modeled assuming a basal glucose level, a rate of systemic entry (k01) and a rate of elimination (k10) and an amplitude factor (A) by use of Eq. 5. From the study data, basal glucose levels were unchanged between daily 25 mg Alogliptin treatment and pretreatment levels. Pre-treatment and treated glucose profiles were fit globally with all parameters common to cohorts except glucose clearance (k10).

Triglyceride level analysis in response to DPP4 inhibition, study data reported in (38) were digitized and lipid levels were modeled, initially by use of Eq. 5, but it became apparent from fitting that the rate into plasma was equal to the rate of elimination (k_01 = k_10), which reduces the system to Eq. 7. DPP-4 inhibition had an influence on all three parameters describing glucose PK. Lipid had a similar PK model as the model of best fit.

Evogliptin repeat dose post-prandial plasma glucose response modeling: Glucose levels versus Evogliptin dose and time as reported in (33) were modeled by Eq. 7. Peak postprandial plasma glucose concentration was modeled by Eq.8.

Results and Discussion

Meta-Analysis of Key Pathways Dysregulated in MetS

Multifactorial targeting of key dysregulated metabolic pathways in high-risk MetS patients provides a strategic therapeutic avenue in abrogating the progress of MetS. For example, the STENO-2 study showed that simultaneously addressing glycemic control, renin blockade, and using lipid lowering and antiplatelet agents in diabetes patients, reduced death from cardiovascular disorder (39). There are a few main mechanisms that are shown to be involved in MetS induction and progression. To find the most effective targets for the pharmacological therapy, we performed a brief meta- analysis of those pathways focusing on the drug exposure and target engagement in avoidance of toxic adverse events. We then eliminated specific pathways based on their benefits for pharmacotherapies and identified optimal candidates for combinatorial therapeutic treatment. Brief description of those pathways’ roles in therapeutic regulation of MetS are given below and in the Table I.

Table I  Meta-analysis of Metabolic Pathways and Potential Target for Therapeutic Interventions

Soluble Episode Hydrolase (sEH) Pathway

sEH is the key enzyme hydrolyzing epoxyeicosatrienoic acids (EETs) to corresponding dihydroxyeicosatrienoic acids, resulting in loss of various protective functions of EETs (40). sEH inhibition has been found to be a prom- ising therapeutic approach for combating atherosclerosis, hypertension, diabetes, and non-alcoholic fatty acid disease, presumably as a result of increasing endogenous EET levels (41–46). Moreover, inhibition of sEH was revealed to have beneficial effects on cardiovascular disease, as well as fatty liver and kidney disease, mediated by suppression of inflam- matory signaling pathways (47, 48). Despite these promis- ing results, a number of clinical trials of experimental sEH inhibitors did not produce reliably efficacious results reduc- ing those conditions. Researchers agreed that more mecha- nistic studies are needed to enable extrapolation of animal results to humans, and a series of human genetic studies is needed to determine the correlation between sEH and human disease. The underlying mechanisms of sEH inhibition are not elucidated yet (49). Given the degree of uncertainty in these mechanisms, we consider the sEH enzyme to be a sub- optimal target.

PPAR Signaling Axis

PPARs are a part of superfamily of nuclear hormone recep- tors and presents a distinguished subfamily made of three isoforms of ligand-inducible transcription factors recog- nized as PPAR-ɑ, PPAR-β/δ and PPAR-γ. Their signaling axis is regulated by eicosanoids and fatty acids (50) and can be activated by numerous small molecule pharmaceutics. Therefore, PPAR agonist drugs are commonly recognized as effective pharmacological agents for the MetS therapy and prevention (51, 52). Within the recent years PPAR agonists have been widely investigated as they were acknowledged and even used for the treatment of non-alcoholic fatty liver disease (53), which is the hepatic manifestation of MetS. Fenofibrate, a PPAR-ɑ agonist administrated to mice led to a decreased glucokinase expression and reduced metabolic fl through this enzyme, that suggests glucose uptake by hepatocytes is suppressed due to activation PPAR-ɑ isoform. In addition, it provokes enhanced expression of pyruvate dehydrogenase kinase 4 (PDK4) with the following inhibition of the pyruvate transition to acetyl-CoA (54). The results of some studies demonstrated that stimulation of PPAR-ɑ activates anti-inflamatory pathways in murine models, despite the presence of reported controversial data (55). Unfortunately, clinical trial outcomes did not prove those beneficial effects in humans. The results of 22 randomized controlled trials with 11,402 patients in total were evaluated in a meta-analysis paper (56) demonstrating that PPAR-ɑ stimulation by administration of fibrate drug com- pounds helps reduce fasting plasma glucose (-5 mg/dL) and insulin levels (-0.56 IU/mL) as well as insulin resistance (HOMA-IR: -1.09), whereas HbA1C level remains unchanged. Furthermore, despite the glucose level reduction was statistically significant it cannot be considered clinically relevant due its small magnitude.

PPAR-β/δ (also called NR1C2) stimulating agents play a key role in the liver cell metabolism reducing activity of pro-inflammatory cascades and are now recognized as potential anti-inflamatory drug prototypes (57). Similar to PPAR-ɑ, those eff were also not noticed in clinical settings. PPAR-γ agonists belonging to the drug class of thiazolidinediones have been used for the therapy of diabetes since 1990s because of their significant glucose lowering capacity and reduced risk of cardiovascular events including lowered incidence of fatal and non-fatal stroke and myocardial infarction. Those effects were documented in clinical trials involved insulin resistant patients without diabetes (58). PPAR-γ agonists improve glucose balance and consequent metabolic disorders associated with MetS and may contribute to a weight gain.

In addition to the tiny benefits in hyperglycemia and up- regulated pro-inflammatory pathways, high likelihood of the body weight increase, which is a one of the main risk fac- tors of MetS, we consider all PPAR isoforms as suboptimal targets for a pharmacological correction of MetS.

FXR Pathway

FXR is one of the main regulators of the variety of the bile acid mediated metabolic pathways controlling a sensitive negative feedback mechanism linking FXR expression and tissue and plasma glucose levels (59). FXR activation leads to direct engagement of targeting cells as well as indirect influence involved in signaling fibroblast growth factor 19 (FGF19) modulation (60). FGF19 is a naturally occurring hormone secreted in response to physiological FXR stimulation in enterocytes (60). In addition, FXR was shown to be an important regulator of the carbohydrate metabolism reducing blood glucose level and lipid exchange affecting levels of cholesterol and triglycerides in pancreas, liver, and other tissue (61–63)). Activation of FXR has been shown to down-regulate inflammatory responses in hepatocytes (63), increase expression of endothelial nitric oxide synthase (eNOS) (64), and suppress endothelin-1 (ET-1) secretion (65). FXR agonists were reported to activate white adipose degradation resulting in decreased expression of pro- inflamatory cytokines leading to reduced insulin resistance and enhanced glucose tolerance (66). FXR activation was shown to reduce expression of genes involved in fatty acid synthesis, lipogenesis, and gluconeogenesis in hepatocytes. This leads to regression of insulin resistance and signs of liver steatosis in fa/fa rats (67). Besides the beneficial eff administration of FXR agonists was reported to cause adverse reactions due to enhanced PEPCK expression, high hepatic glucose production and plasma HDL-C level decrease that were shown to accelerate MetS development (68). While FXR activation improves hypertriglyceridemia, simultaneous decrease in HDL-C concentration is also observed (69). There is no data about its effect on glucose homeostasis in humans. In addition, increased PEPCK expression leads to hepatic glucose production de novo that reduces hypoglycemic efficacy of FXR agonists (70). More- over, clinical trials have demonstrated the presence of risk of adverse reactions related to local inflammatory symptoms such as pruritus (71). Due to uncertainty in any interruption of glucose homeostasis and upregulation of risk factors aggravating MetS progression, we consider FXR pathway targeting to be suboptimal.

Glucokinase Pathways

Glucokinase (GCK) is an enzyme facilitating phosphorylation of glucose to glucose-6-phosphate is found in the beta-cell and hepatocytes. It has a high degree of the insulin secretion control making it a highly sensitive glucose sensor adjusting hepatic glucose phosphorylation to the plasma glucose level. GCK-regulated glucose degrading processes were found to be involved in induction of hyperinsulinemia at the early disease stages but can be reduced to restore normal stimulus-secretion coupling (72). Both previous and current research demonstrates that GCK activation is associated with increased glucose accumulation in liver cells suggesting that GCK is a potential target for the management of hyperglycemia (73). At the same time, GCK activation does not reduce hypertriglyceridemia, nor affect HDL-C levels. It has no influence on pro-inflammatory cytokine level, and may provoke serious side effects such as hyperlipidemia. It is also worth noting that despite some GCK activating drugs like Berberine prescribed for type 2 diabetes treatment, their administration to patients manifesting in part clinical risks in MetS demonstrated reduction of insulin resistance and LDL cholesterol level specifically only in some sub-population carrying specific genotypes. Therefore, these findings require expanded clinical trials to confirm the low risk of adverse effects associated with lipid metabolism disorders that may aggravate MetS progression. Until then, GCK is generally rendered as suboptimal target (74).

Dipeptidyl Peptidase 4 Pathway

The gliptins drug class represents a valuable tool in the arsenal of oral antihyperglycemic agents available for the treatment of type II diabetes. They are characterized by a quite promising safety profile and mechanism of action because glucose metabolism was proved to greatly depend on the incretin pathway rendering the DPP4 inhibitors amenable to mono- and combinatorial therapeutic approaches. DPP4 is a type II transmembrane protein playing a core role in regulation of post-prandial glucose level via degradation of GLP-1 and GIP. DPP-4 is ubiquitously expressed in all body tissues and present in two isoforms: cell surface-associated enzyme or soluble peptidase. DPP-4 is easily available to its potential substrates presented with a variety of bioactive peptides circulating in general and local blood flow. in addition to GLP-1 and GIP, those peptides are modulated by the enzyme as well. DPP4 was also found to potentiate inflammation in diabetes patients that probably involves both catalytic and non-catalytic function of this enzyme. A majority of the publications confirm its role in glucose exchange and its potential as a target for Diabetes type 2 treatment. Long- Term DPP-4 inhibition improves metabolic parameter of homeostasis reflecting the ratio of insulin to glucose levels (75) as well as contribute to the recovery of oxidative status (76). It was found out that DPP4 activation results in upregulation of a series of pro-inflammatory cytokines including IL-1α, IL-1β, IL-4, IL-6, IL-10. Numerous clinical trials have demonstrated relative safety of the long-term therapy with major DPP4 inhibitors. Alogliptin was administered for two years to patients with severe T2D with a very low rate of adverse reactions (77), efficacy and safety of Linagliptin administration was clinically proved through 1-year long trials (78). Therefore, inhibition of DDP4 activity would provide reduction of inflammation, one of the main contributing factors in progression of metabolic syndrome (76). These results suggest unidentified, broad pleiotropic effects of DPP-4 inhibitors and indicate a potential role of vascular infl   modulators, which may allow for the reduction of the vascular complications of atherosclerosis related to metabolic syndrome (79). Taken together, we consider DPP-4 to be a promising target for a combinatorial approach for addressing MetS.

Pro-Inflammatory Pathways: IL-17 Cytokine Family

As alimentary based obesity became a global problem, it was noted that overeating lead to hypertrophy and hyperplasia of adipose cells, especially in abdomen, resulting in disbalance between cell volume and oxygen demand and their blood supply leading to relative hypoxia (80). Lack of oxygen activates the process of cell death leading to degradation with subsequent macrophage infiltration inducing overproduction of adipocytokines, in particular, the proinflamatory cytokines such as Interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) (81). Those cytokines are responsible for further progression of chronic inflammation, activation of immune cells and secretion of a secondary pro-inflamatory mediators, mainly, Interleukin-17a (IL-17a) (82). Generally, IL-17 cytokine family was found to be involved in immune responses to various infections and in pathological overlapping pathways of cardiovascular disorders and autoimmune diseases associated with enhanced inflammatory processes. Therefore, pharmacological modulation of the CD4 + T Helper cell-generated IL-17A cytokines may be considered as promising therapeutic approach in the treatment of above-mentioned pathologies. IL-17A plays an important role in the commonality that is manifested in the pathophysiology of clinical conditions in MetS. These similarities include an inflamatory presence associated with the development of modified autoantigens targeted by both arms of the immune system; the innate and adaptive immune system (82). Th1 in both scenarios plays an initiatory catalyst. The alteration of the vesicular blood fl w started by invasion of these inflammatory cells into the vessel wall is initially activated by adhesion molecules whose production is controlled by the secretion of pro-inflammatory cytokines and chemokines (82). Historic evidence establishing the correlation between cardiometabolic disease with psoriasis has existed for a long time (83). Severe psoriasis is associated with an increased risk of cardiovascular mortality (84), with a subsequent reduction in life expectancy in patients (85). Recently, cumulative research evidence demonstrated that IL-17A may represent one of the main links between cardio- metabolic disease manifestations and psoriatic inflammation (86, 87). Additionally, it has been established that psoriasis patients have an increased likelihood of high body mass index (88), and have higher chances of having metabolic syndrome (89) and type 2 diabetes (86). Bruin et al. (29) demonstrated that three weekly subcutaneous doses of IL-17a inhibitor Secukinumab followed by subcutaneous dosing every 4 weeks had contributed to the rapid onset of psoriatic lesion clearance confirmed by decreased hBD-2 in both serum and skin lesions. Since IL-17A mediated inflammation is implicated in a segment of the clustered risk in metabolic syndrome, specifically obe- sity, atherosclerosis, and low-grade chronic inflammation its down regulation poses a complex of benefit alleviating all those pathways. Recently, IL-17A upregulation in response to diet induced obesity induces PPAR-γ phosphorylation adipocytes in a CDK5-dependent manner, thereby modulating diabetogenic and obesity gene expression, this correlates with IL-17A signaling in the fat of individuals with morbid obesity. Here upregulation of IL-17A and its unexpected role in adipocyte biology, in which its direct- action correlates in pathogenic reprogramming of adipocytes, causes diet induced obesity and MetS. In the context of repurposing anti-IL 17 for MetS, it is important to note that IL-17A downregulation may play a critical role in neutrophil recruitment, angiogenesis, inflammation, and autoimmune disorders (90) including pulmonary, cardiac, and liver fibrosis via IL-17RA and MAPK signaling (91, 92). Recent studies suggested that IL‐17 administration may be used as an immunomodulatory intervention to prevent or treat MetS because IL‐17 induces neutrophil migration in the intestinal mucosa through the CXCL‐1 expression by epithelial cells. Hence, targeting the IL-17A signaling axis could be an effective treatment for the clustered clinical risks manifested in MetS (93). We performed a short analysis of the phase 3 JUNCTURE study to determine the reduction in free circulating levels of IL-17A after the use of IL-17a inhibitor Secukinumab (29) and used for the modeling purposes.

Modeling of DPP4 Inhibitors, FXR Agonist and Anti-IL-17a in the BIOiSIM™ Environment

Using the BIOiSIM™ environment, we evaluated DPP4 inhibitors, FXR agonist, and anti-IL-17 agents to determine successful approaches for potential combinatorial therapies that would abrogate a majority of the risks involved in MetS pathophysiology. FXR Tropifexor and DPP4 inhibitors were selected following one of the main drug discovery and repurposing principles of having more than one drug candidate for further development. Tropifexor was used for the comparative evaluation of the modeled results as a benchmark for PK properties and efficacy. Also, Tropifexor was suggested as an alternative to DDP4 inhibitors in case the pharmacologic profiles would not meet the requirements for the MetS amelioration. As observed in Fig. 1, Evogliptin, Linagliptin and Alogliptin produce DPP4 inhibition as a direct response to their instantaneous plasma concentrations.

Fig.1 DPP4 inhibition versus drug concentration for Evogliptin, Linagliptin and Alogliptin

A direct response model captures observed PK-DPP4 inhibition relationship of all three DPP4 inhibitors. Inter- estingly, Evogliptin (IC50 = 1.3 ng/ml, Hill = 1.2) and Linagliptin (IC50 = 1.2 ng/ml, Hill = 1.8) display nearly identi- cal DPP4 inhibition responses in contrast to Alogliptin which, in terms of total plasma concentration, is slightly more potent but also has a notably shallower Hill coefficient (IC50 = 0.38 ng/ml, Hill = 0.43). The shallower Hill coefficient suggests consistent DPP4 inhibition will be maintained over a wider range of Alogliptin concentrations in comparison to Evogliptin and especially Linagliptin.

Adipose tissue knockout mice given a fat enriched diet was noted to have significantly better glucose tolerance associated with improved insulin sensitivity in liver (94). Furthermore, the lack of adipose DPP4 lead to enhanced expression of anti-inflammatory cytokines and remodeling of adipose tissue, which was suggested as a main mechanism of increased hepatic insulin sensitivity (94). Chae et al. had demonstrated the direct effect of Evogliptin administration on tissue volume ratio in mice with modeled obese (36). Those mice were found to have reduced a whole-body fat volume due to increased energy expenses associated with significantly reduced blood glucose level after Evogliptin dosing in clinical regimens inducing more than 80% reduction of DPP4 level in plasma for 24 h (36). Moreover, AMP- activated protein kinase enhanced energy dissipation due to accelerated fatty acid oxidation in fat tissue confirmed that metabolic alterations in adipose cells can increase the total energy expenditure (36). Those studies demonstrated that adipose tissue volume reduction induced by DPP4 suppression is modulated by higher energy losses, adipose tissue remodeling improve hepatic insulin resistance involving changes in IGFBP3-modulated pathway. Taken together the favorable effects of Evogliptin at a clinical dosing regimen on whole body composition and especially favorable adipose tissue remodeling that has been established obese mice model (36, 94), we therefore speculate that Evogliptin can be a promising candidate among DPP4 inhibitors for combinatorial therapies.

Tropifexor-induced plasma levels of FGF19 are the result of a complex interplay that is difficult to model versus time and dose. As seen in panel B of Fig. 2, the interplay is not consistent with a direct response model. As well, mixed effects models or time dependent responses failed to capture the time response profiles. Alternatively, as seen in panel C, the AURC v dose produces a simple saturation response with a maxim response of 114,000 pg/ml*h with a Tropifexor half maximum response dose of 0.78 mg. We also modeled a drug exposure of Tropifexor generated from our BIOiSIM™ environment. However, due to the known safety-toxicology profile demonstrating pruritus for prolonged usage of FXR agonists (31), we did not select it as a potential candidate. Needless to say, Tropifexor has demonstrated positive out- comes in observed in both preclinical and clinical investigations (71).

Fig. 2 FGF19 plasma concentration responses versus Tropifexor dose and time. Time profiles of FGF19 plasma concentrations (Panel A), Alignment of FGF19 response v Tropifexor plasma concentrations (Panel B), FGF19 Area Under the Response Curve (AURC) vs Tropifexor dose (Panel C).

Type 2 diabetes (T2D) mellitus manifests itself as impaired blood glucose control underlying multiple metabolic abnormalities, including decreased level of insulin secretion and prolonged exposure to free fatty acids (95), insulin resistance, progressive loss of beta-cell function, impaired glucagon secretion, and dysregulation of incretin hormone signaling (96). Evogliptin blocks DPP-4 enzyme, prolonging the exposure and levels of the incretin hormones, glucagon-like peptide-1 (GLP-1) and glucose- dependent insulinotropic polypeptide (GIP) (36). These incretin hormones increase insulin secretion and decrease glucagon secretion, which also decreases hepatic glucose production and reduction in free fatty acid and lipid levels (97). Evogliptin is commonly prescribed at 5–10 mg daily for T2D, and our meta-analysis of the report by Gu et al. reveals DPP-4 is inhibited by 85 and 90% respectively for both doses at steady state with corresponding increase of GLP-1 level and blood glucose concentration reduction. Under this treatment regimen, projections of the simulated dose would lead to fasting glucose levels reduction by an average of 14% and triacylglycerides by an average of 17%. Long term administration of Evogliptin has shown global reductions in glucose levels and improved plasma lipid pro- fi (98). In addition, the agent is relatively well tolerated with few adverse eff  even after a 1-year long therapy. In addition to enhanced blood glucose regulation, report by Aramaki et al. (35) shows DPP4 inhibitors reduce postprandial triacylglycerol levels. A meta-analysis of the aforementioned articles indicates daily dosing of Evogliptin and other DPP4 inhibitors produces modest basal reductions in blood triacylglycerol levels and reduces the overall triacylglycerol exposure (99). Basic PD modeling indicates the rates of lipid absorption and clearance from blood are unaffected; rather, it seems the absorption from the gut is reduced or the liver captures more in the first pass. Our model predicts similar findings as mentioned previously on the efficacy and associated PD of glucose lowering activity in humans (Fig. 3). Postprandial blood glucose concentration gets lower in com- parison to placebo and corresponds to the degree of DDP4 inhibition model shown above on Fig. 1.

Fig. 3 Evogliptin reduction in post prandial plasma glucose levels at various doses.

MetS covers a group of clustered clinical conditions lead- ing to T2D and cardiovascular events in patients. These clinical conditions, if left unchecked, present several risks that could lead to high morbidity and mortality. Therefore, accelerating the development of therapeutic approaches is critical to patients. To date, relatively unsuccessful monotherapies or combinations therapies specifically using small molecules as a modality have been used in patients in hope of stopping and/or reversing a single clinical condition in the gamut of conditions encompass- ing MetS. We have investigated a novel approach using our BIOiSIM™ platform to accelerate the drug development pro- cess for a combination therapy using repurposed compounds consisting of two diff  ent modalities and mechanisms of action. Among the many FDA approved drug classes targeting different clinical conditions spanning the spectrum ranging from insulin resistance, dyslipidemia and inflammation under MetS, we have chosen a small molecule, Evogliptin (DPP-4 inhibitor) and Secukinumab (anti-IL-17a antibody) for a potential combinatorial approach targeting and possibly ameliorating a significant portion of MetS. This approach takes advantage of two distinct mechanisms of action cumulatively leading to immediate improvement resulting in initial decrease in insulin resistance and improved glucose control. This results in a long-term beneficial reduction in inflammation with consequent drop in lipid levels, which may in turn result in body weight reduction. As seen in Fig. 4 on the left panel, our modeling of free IL-17A levels suggests that during the loading phase of Secukinumab, circulating levels of free IL-17A are reduced by 98%. Further, during steady-state dosing of 150 mg Secukinumab every 4 weeks, circulating levels of IL-17A remain reduced to less than 5% of untreated. Based on our simulated outcomes, Secuki- numab is a potent IL-17A inhibitor and can be repurposed in targeting a significant portion of the infliven clustered risks of MetS. Our simulation demonstrates high potency and a unique tissue distribution for Evogliptin which combined with Secukinumab and downregulating their targets as shown in Figs. 4 and 5, can ameliorate a significant portion of the clustered clinical risk observed in MetS. We therefore anticipate that prolonged exposure to the combinations of DPP-4 inhibitors and anti-IL71a therapy could reduce markedly cardiovascular events and T2D in patients with MetS.

Fig. 4 Simulations of IL-17A inhibitor Secukinumab pharmacokinetics and its engagement with IL-17A target. Secukinumab is dosed 150 mg s.c. weekly for 4 weeks then once every 4 weeks. Simulations based on published reports.
Fig. 5 Simulation of Evogliptin pharmacokinetic profiles and its efficacy via engagement with specific target DPP4 if dosed 10 mg daily. Simulations based on published reports.


The silent pandemic of metabolic syndrome is indiscrimi- nate towards the global population and manifests in children to older persons. The prevalence of the metabolic syndrome is strongly associated with aging indicating higher risk of the key metabolic pathway dysregulations including insulin resistance, which is commonly rendered to be at the core of metabolic syndrome disorders. At the same time, the mechanistic link between insulin resistance and other major factors of the metabolic syndrome development remains elusive. Despite strong correlation between insulin resistance degree and hyperglycemia, atherogenic dyslipidemia as well as chronic inflammation is investigated and more or less clear, it is less tightly linked to elevated blood pressure and the prothrombotic state. Due to the complex origin of MetS disorder, much of the heterogeneity may be because of observation suggesting many clustered risk factors are regulated separately of insulin metabolism. Genetic factors involved in lipid exchange regulation as well as personal dietary intake, can worsen dyslipidemia induced by hyperglycemia raise a risk a cardiovascular event. They alone or in a tandem fashion with renal/adrenal organs affect blood pressure. Taken together, the clustered risk in MetS can manifest in sub-populations as a single disease or a combination of pathologies remaining an unmet medical need. Therapeutics currently available for MetS are varied in terms of their ability to improve the fi outcomes in patients. A common and an initial approach to improve and or reverse the deleterious nature of clinical risks in MetS, is changes in lifestyle diet with increased physical activity. Nevertheless, often these lifestyle modification are not enough to sway the balance towards normality in patients, hence, treatment may require a diff  ent therapeutic approach, a multi-drug therapy regimen. However, a multi-drug regimen or polypharmacy has been known to be a major problem for the treatment of patients with MetS due to suboptimal patient compliance, off-target effects, and potential drug-drug interactions. A potential solution to polypharmacy in MetS is by combining and or repurposing multiple drugs with diff ent modalities or to design drugs with multiple actions to combat key dysregulated pathways in MetS. We have taken a DPP4 inhibitor, a small molecule, and anti-IL-17a, a biologic with a completely distinct mechanism of action to address and combat outcomes of dysregulation of a wide range of key metabolic pathways involved in insulin resistance and inflammation. Specifically, the key dysregulated metabolic pathways in part, originate from impaired glucose control and disorders in lipid metabolism. This leads to elevated blood lipid level resulting in insulin resistance and chronic inflammation due to the release of proinflammatory cytokines. As MetS is a multifactorial-multidimensional disorder, the treatment measures cannot solely focus on the specific pathway because other metabolic changes would not be remedied, allowing progression of other problematic pathological states. Overall, our results suggest that simultaneously targeting lipid metabolic pathways, impaired glucose control, insulin resistance, and chronic inflammation with DPP-4 inhibitor Evogliptin and IL-17A inhibitor Secukinumab will likely provide a high likelihood of ameliorating a significant portion of the clustered clinical risk associated with MetS.

Acknowledgments and Disclosures The authors are all employees of VeriSIM Life and used a proprietary AI-driven platform to generate the outcomes for the manuscript.

All data generated or analyzed during this study are included in this published article.

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