Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors

Understanding the ideal wound healing mechanistic behavior using in silico modelling perspectives: A review

Complexity of the entire body precludes an accurate assessment of the specific contributions of tissues or cells during the healing process, which might be expensive and time consuming. Because of this, controlling the wound's size, depth, and dimensions may be challenging, and there is not yet an efficient and reliable chronic wound model representation. Furthermore, given the inherent challenges associated with conducting non-invasive in vivo investigations, it becomes peremptory to explore alternative methodologies for studying wound healing. In this context, biologically-realistic mathematical and computational models emerge as a valuable framework that can effectively address this need. Therefore, it might improve our approach to understanding the process at its core. This article will examines all facets of wound healing, including the kinds, pathways, and most current developments in wound treatment worldwide, particularly in silico modelling utilizing both mathematical and structure-based modelling techniques. It may be helpful to identify the crucial traits through the feedback loop of computer models and experimental investigations in order to build innovative therapies to cure wounds. Hence the effectiveness of personalised medicine and more targeted therapy in the healing of wounds may be enhanced by this interdisciplinary expertise.

Virtual screening and biological evaluation to identify pharmaceuticals potentially causing hypertension and hypokalemia by inhibiting steroid 11β-hydroxylase

Several drugs were found after their market approval to unexpectedly inhibit adrenal 11β-hydroxylase (CYP11B1)-dependent cortisol synthesis. Known side-effects of CYP11B1 inhibition include hypertension and hypokalemia, due to a feedback activation of adrenal steroidogenesis, leading to supraphysiological concentrations of 11-deoxycortisol and 11-deoxycorticosterone that can activate the mineralocorticoid receptor. This results in potassium excretion and sodium and water retention, ultimately causing hypertension. With the risk known but usually not addressed in preclinical evaluation, this study aimed to identify drugs and drug candidates inhibiting CYP11B1. Two conceptually different virtual screening methods were combined, a pharmacophore based and an induced fit docking approach. Cell-free and cell-based CYP11B1 activity measurements revealed several inhibitors with IC50 values in the nanomolar range. Inhibitors include retinoic acid metabolism blocking agents (RAMBAs), azole antifungals, α2-adrenoceptor ligands, and a farnesyltransferase inhibitor. The active compounds share a nitrogen atom embedded in an aromatic ring system. Structure activity analysis identified the free electron pair of the nitrogen atom as a prerequisite for the drug-enzyme interaction, with its pKa value as an indicator of inhibitory potency. Another important parameter is drug lipophilicity, exemplified by etomidate. Changing its ethyl ester moiety to a more hydrophilic carboxylic acid group dramatically decreased the inhibitory potential, most likely due to less efficient cellular uptake. The presented work successfully combined different in silico and in vitro methods to identify several previously unknown CYP11B1 inhibitors. This workflow facilitates the identification of compounds that inhibit CYP11B1 and therefore pose a risk for inducing hypertension and hypokalemia.

Applications of Virtual Screening in Bioprospecting: Facts, Shifts, and Perspectives to Explore the Chemo-Structural Diversity of Natural Products

Natural products are continually explored in the development of new bioactive compounds with industrial applications, attracting the attention of scientific research efforts due to their pharmacophore-like structures, pharmacokinetic properties, and unique chemical space. The systematic search for natural sources to obtain valuable molecules to develop products with commercial value and industrial purposes remains the most challenging task in bioprospecting. Virtual screening strategies have innovated the discovery of novel bioactive molecules assessing in silico large compound libraries, favoring the analysis of their chemical space, pharmacodynamics, and their pharmacokinetic properties, thus leading to the reduction of financial efforts, infrastructure, and time involved in the process of discovering new chemical entities. Herein, we discuss the computational approaches and methods developed to explore the chemo-structural diversity of natural products, focusing on the main paradigms involved in the discovery and screening of bioactive compounds from natural sources, placing particular emphasis on artificial intelligence, cheminformatics methods, and big data analyses.

Aldosterone synthase inhibitors for cardiovascular diseases: A comprehensive review of preclinical, clinical and in silico data

Aldosterone, the main mineralocorticoid hormone, plays a fundamental role in maintaining blood pressure (BP)and volume under hypovolemic conditions. However, in numerous diseases, where it is produced in excess, it plays a detrimental role and contributes to cardiovascular events and ultimately to death in a multitude of patients. The seminal observation that the fungicide-derivative fadrozole blunted steroidogenesis has led to develop several agents to inhibit aldosterone synthase (AS, CYP11B2), the mitochondrial NADH-dependent enzyme that is necessary for aldosterone biosynthesis. Aldosterone synthase inhibitors (ASI) have, thereafter, been conceived and investigated in phase I and phase II studies. We herein reviewed the ASIs available so far considering their chemical structure, the related aldosterone synthase binding and pharmacodynamic properties. We also examined the promising results obtained with ASIs that have already been tested in phase II human studies.

Identification of the fungicide epoxiconazole by virtual screening and biological assessment as inhibitor of human 11β-hydroxylase and aldosterone synthase

Humans are constantly exposed to a multitude of environmental chemicals that may disturb endocrine functions. It is crucial to identify such chemicals and uncover their mode-of-action to avoid adverse health effects. 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) catalyze the formation of cortisol and aldosterone, respectively, in the adrenal cortex. Disruption of their synthesis by exogenous chemicals can contribute to cardio-metabolic diseases, chronic kidney disease, osteoporosis, and immune-related disorders. This study applied in silico screening and in vitro evaluation for the discovery of xenobiotics inhibiting CYP11B1 and CYP11B2. Several databases comprising environmentally relevant pollutants, chemicals in body care products, food additives and drugs were virtually screened using CYP11B1 and CYP11B2 pharmacophore models. A first round of biological testing used hamster cells overexpressing human CYP11B1 or CYP11B2 to analyze 25 selected virtual hits. Three compounds inhibited CYP11B1 and CYP11B2 with IC50 values below 3 μM. The most potent inhibitor was epoxiconazole (IC50 value of 623 nM for CYP11B1 and 113 nM for CYP11B2, respectively); flurprimidol and ancymidol were moderate inhibitors. In a second round, these three compounds were tested in human adrenal H295R cells endogenously expressing CYP11B1 and CYP11B2, confirming the potent inhibition by epoxiconazole and the more moderate effects by flurprimidol and ancymidol. Thus, the in silico screening, prioritization of chemicals for initial biological tests and use of H295R cells to provide initial mechanistic information is a promising strategy to identify potential endocrine disruptors inhibiting corticosteroid synthesis. A critical assessment of human exposure levels and in vivo evaluation of potential corticosteroid disrupting effects by epoxiconazole is required.

Glucocorticoid Receptor Antagonist Administration Prevents Adrenal Gland Atrophy in an ACTH-Independent Cushing's Syndrome Rat Model

ACTH-independent Cushing's syndrome (CS) is mainly caused by cortisol-secreting adrenocortical tumours. It is well known that secondary adrenal insufficiency occurs after surgical resection of these tumours. In this regard, impaired adrenocortical function is likely induced by atrophy of the residual adrenal tissue as a result of chronic suppression by the low ACTH levels of the hypercortisolism state. Therefore, we considered the prevention of adrenal atrophy as a method for preventing postoperative adrenal insufficiency. On the basis of these findings, we hypothesized that the use of a glucocorticoid receptor (GR) antagonist before surgery in ACTH-independent CS would rapidly activate the hypothalamic-pituitary-adrenal (HPA) axis and residual adrenal function. We thus examined adrenal function in a dexamethasone- (DEX-) induced CS rat model with or without mifepristone (MIF). In this study, MIF-treated rats had elevated plasma ACTH levels and increased adrenal weights. In addition, we confirmed that there were fewer atrophic changes, as measured by the pathological findings and mRNA expression levels of corticosterone synthase CYP11B1 in the adrenal glands, in MIF-treated rats. These results indicate that MIF treatment prevents the suppression of the HPA axis and the atrophy of the residual adrenal tissue. Therefore, our study suggests that preoperative GR antagonist administration may improve residual adrenal function and prevent postoperative adrenal insufficiency in ACTH-independent CS.

Inhibitors of Aldosterone Synthase

The mineralocorticoid aldosterone is an important regulator of blood pressure and electrolyte balance. However, excess aldosterone can be deleterious as a driver of inflammation, vascular remodeling and tissue fibrosis associated with cardiometabolic diseases. Mineralocorticoid receptor antagonists (MRA) and renin-angiotensin-aldosterone system (RAAS) antagonists are current clinical therapies used to antagonize deleterious effects of aldosterone in patients. MRAs compete with aldosterone for binding at its cognate receptor thereby limiting its effect while RAS antagonists reduce aldosterone levels indirectly by blocking the stimulatory effect of angiotensin. Both MRAs and RAS antagonists can result in incomplete inhibition of the harmful effects of excess aldosterone. Aldosterone synthase (AS) inhibitors (ASI) attenuate the production of aldosterone directly and have been proposed as an alternative to MRAs and RAS blockers. Cortisol synthase (CS) is an enzyme closely related to AS and responsible for generating the important glucocorticoid cortisol, required for maintaining critical metabolic and immune responses. The importance of selectivity against CS is shown by early examples of ASIs that were only modestly selective and as such, attenuated cortisol responses when evaluated in patients. Recently, next-generation, highly selective ASIs have been described and are presently being evaluated in the clinic as an alternative to angiotensin and MR antagonists for cardiometabolic disease. Herein we provide a brief review of the challenges associated with discovery of selective ASIs and the transition from the early compounds that paved the way toward the next-generation of highly selective ASIs currently under development.

In Silico Workflow for the Discovery of Natural Products Activating the G Protein-Coupled Bile Acid Receptor 1

The G protein-coupled bile acid receptor (GPBAR1) has been recognized as a promising new target for the treatment of diverse diseases, including obesity, type 2 diabetes, fatty liver disease and atherosclerosis. The identification of novel and potent GPBAR1 agonists is highly relevant, as these diseases are on the rise and pharmacological unmet therapeutic needs are pervasive. Therefore, the aim of this study was to develop a proficient workflow for the in silico prediction of GPBAR1 activating compounds, primarily from natural sources. A protocol was set up, starting with a comprehensive collection of structural information of known ligands. This information was used to generate ligand-based pharmacophore models in LigandScout 4.08 Advanced. After theoretical validation, the two most promising models, namely BAMS22 and TTM8, were employed as queries for the virtual screening of natural product and synthetic small molecule databases. Virtual hits were progressed to shape matching experiments and physicochemical clustering. Out of 33 diverse virtual hits subjected to experimental testing using a reporter gene-based assay, two natural products, farnesiferol B (27) and microlobidene (28), were confirmed as GPBAR1 activators reaching more than 50% receptor activation at 20 μM with EC50s of 13.53 μM and 13.88 μM, respectively. This activity is comparable to that of the endogenous ligand lithocholic acid (1). Seven further virtual hits showed activity reaching at least 15% receptor activation either at 5 or 20 μM, including new scaffolds from natural and synthetic origin.