Pharmacophore modeling, homology modeling, and in silico screening reveal mammalian target of rapamycin inhibitory activities for sotalol, glyburide, metipranolol, sulfamethizole, glipizide, and pioglitazone

Novel bis-ureido-substituted sulfaguanidines and sulfisoxazoles as carbonic anhydrase and acetylcholinesterase inhibitors

To discover alternative substances to compounds used to treat many diseases, especially treating Alzheimer's disease (AD) and Parkinson's disease targeting carbonic anhydrase (hCA) and acetylcholinesterase (AChE) enzymes, is important. For this purpose, a series of novel bis-ureido-substituted sulfaguanidine (SG1-4) and sulfisoxazole (SO1-4) derivatives were synthesized, and their inhibitory capacities were screened against hCA isoenzymes (hCA I and II) and AChE. Possible binding mechanisms of inhibitors to the active site were elucidated by in silico studies, and the results were supported by in vitro results. Moreover, the percent radical scavenging capacities of the derivatives were also evaluated. The derivatives (SG1-4 and SO1-4) were more effective against hCAs compared to standard drug acetazolamide (KI values of 98.28-439.17 nM for hCA I and II, respectively) and exhibited the highest inhibition with the KIs in the ranges of 2.54 ± 0.50-41.02 ± 7.52 nM for hCA I, 11.20 ± 2.97-67.14 ± 13.58 nM for hCA II, and 257.60 ± 27.84-442.60 ± 52.13 nM for AChE. Also, compounds SG1 and SO1 also showed ABTS radical scavenging activity at the rate of 70% and 78%, respectively. These results will contribute to the literature for the rational design and synthesis of new potent and selective inhibitors targeting hCAs and AChE with multifunctional effects such as radical scavenging as well as inhibition. This study focused on the synthesis and inhibitory effects of bis-ureido-substituted sulfaguanidine (SG1-4) and sulfisoxazole (SO1-4) derivatives against human hCA I and II isoforms and AChE. In order to test synthesized derivatives' free radical scavenging potentials were the DPPH and ABTS assays. In silico studies elucidated possible binding mechanisms of inhibitors to the active site.

Sulfamethizole attenuates poloxamer 407-induced atherosclerotic neointima formation via inhibition of mTOR in C57BL/6 mice

Mammalian target of Rapamycin C1 (mTORC1) inhibition limits plaque progression in atherosclerosis. The present study evaluated the protective effect of sulfamethizole on poloxamer 407-induced atherosclerotic neointima formation in C57BL/6 mice via mTOR inhibition. Poloxamer 407 (P-407) (0.5 g/kg body weight) was administered intraperitoneally to male C57BL/6 mice every third day for 148 days to induce chronic hyperlipidemia. From Day 121 to 148, animals were additionally administered Sulfamethizole (5, 10, and 50 mg/kg, p.o.), Rapamycin (0.5 mg/kg, positive control), or vehicle (1 ml/kg). Plasma lipid levels were measured on Days 120 and 148. Upon sacrifice, histological studies were performed, and aortic tissue interleukin (IL)-6, tumor necrosis factor-α (TNF-α), and mTOR levels were evaluated. A molecular docking study was carried out to mimic the interaction of sulfamethizole with mTOR protein. Chronic P-407 administration significantly (p < 0.001) elevated plasma lipid levels, compared with those of the normal control group. Chronic hyperlipidemia resulted in increased tunica intima thickness, collagen deposition, and IL-6, TNF-α, and mTOR levels. Treatment with Sulfamethizole attenuated these parameters significantly in a dose-dependent manner. Molecular docking studies showed a significant interaction of Sulfamethizole with mTOR. In conclusion, this study suggests that sulfamethizole significantly limits poloxamer 407-induced atherosclerotic neointima formation in C57BL/6 mice via mTOR inhibition.

Novel regulators of airway epithelial barrier function during inflammation: potential targets for drug repurposing

INTRODUCTION

Endogenous inflammatory signaling molecules resulting from deregulated immune responses, can impair airway epithelial barrier function and predispose individuals with airway inflammatory diseases to exacerbations and lung infections. Targeting the specific endogenous factors disrupting the airway barrier therefore has the potential to prevent disease exacerbations without affecting the protective immune responses.

AREAS COVERED

Here, we review the endogenous factors and specific mechanisms disrupting airway epithelial barrier during inflammation and reflect on whether these factors can be specifically targeted by repurposed existing drugs. Literature search was conducted using PubMed, drug database of US FDA and European Medicines Agency until and including September 2021.

EXPERT OPINION

IL-4 and IL-13 signaling are the major pathways disrupting the airway epithelial barrier during airway inflammation. However, blocking IL-4/IL-13 signaling may adversely affect protective immune responses and increase susceptibility of host to infections. An alternate approach to modulate airway epithelial barrier function involves targeting specific downstream component of IL-4/IL-13 signaling or different inflammatory mediators responsible for regulation of airway epithelial barrier. Airway epithelium-targeted therapy using inhibitors of HDAC, HSP90, MIF, mTOR, IL-17A and VEGF may be a potential strategy to prevent airway epithelial barrier dysfunction in airway inflammatory diseases.

Glibenclamide ameliorates the expression of neurotrophic factors in sevoflurane anaesthesia-induced oxidative stress and cognitive impairment in hippocampal neurons of old rats

Introduction

Several antidiabetic medications have been proposed as prospective treatments for cognitive impairments in type 2 diabetes patients, glibenclamide (GBC) among them. Our research aimed to evaluate the impact of GBC on hippocampal learning memory and inflammation due to enhanced neurotrophic signals induced by inhalation of sevoflurane.

Material and Methods

Rats (Sprague Dawley, both sexes) were assigned to four groups: a control (vehicle, p.o.), GBC (10 mg/kg b.w.; p.o.), low-dose sevoflurane and low-dose sevoflurane + GBC (10 mg/kg b.w.; p.o.) for 23 days. Terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) staining was performed to analyse the count of apoptotic cells and ELISA was conducted to assess the protein signals. A Western blot, a Y-maze test, and a Morris maze test were performed, and the results analysed. Blood and tissues were collected, and isolation of RNA was performed with qRT-PCR.

Results

The Morris maze test results revealed an improvement in the length of the escape latency on days 1 (P < 0.05), 2 (P < 0.01), 3, and 4 in the low-dose Sevo group. Time spent in the quadrant and crossing axis and the percentage of spontaneous alterations showed a substantial decrease in the low-dose Sevo group which received GBC at 10 mg/kg b.w. Significant increases were shown in IL-6 and TNF-α levels in the low-dose Sevo group, whereas a decrease was evident in the GBC group.

Conclusion

Our results indicate that glibenclamide may be a novel drug to prevent sevoflurane inhalation-induced impaired learning and reduce brain-derived neurotrophic factor release, which may be a vital target for the development of potential therapies for cognitive deficits and neurodegeneration.

Novel inhibitors with sulfamethazine backbone: synthesis and biological study of multi-target cholinesterases and α-glucosidase inhibitors

The underlying cause of many metabolic diseases is abnormal changes in enzyme activity in metabolism. Inhibition of metabolic enzymes such as cholinesterases (ChEs; acetylcholinesterase, AChE and butyrylcholinesterase, BChE) and α-glucosidase (α-GLY) is one of the accepted approaches in the treatment of Alzheimer's disease (AD) and diabetes mellitus (DM). Here we reported an investigation of a new series of novel ureido-substituted derivatives with sulfamethazine backbone (2a-f) for the inhibition of AChE, BChE, and α-GLY. All the derivatives demonstrated activity in nanomolar levels as AChE, BChE, and α-GLY inhibitors with K_I values in the range of 56.07-204.95 nM, 38.05-147.04 nM, and 12.80-79.22 nM, respectively. Among the many strong N-(4,6-dimethylpyrimidin-2-yl)-4-(3-substitutedphenylureido) benzenesulfonamide derivatives (2a-f) detected against ChEs, compound 2c, the 4-fluorophenylureido derivative, demonstrated the most potent inhibition profile towards AChE and BChE. A comprehensive ligand/receptor interaction prediction was performed in silico for the three metabolic enzymes providing molecular docking investigation using Glide XP, MM-GBSA, and ADME-Tox modules. The present research reinforces the rationale behind utilizing inhibitors with sulfamethazine backbone as innovative anticholinergic and antidiabetic agents with a new mechanism of action, submitting propositions for the rational design and synthesis of novel strong inhibitors targeting ChEs and α-GLY.Communicated by Ramaswamy H. Sarma.

Marine-Derived Natural Products as ATP-Competitive mTOR Kinase Inhibitors for Cancer Therapeutics

The mammalian target of rapamycin (mTOR) is a serine/threonine kinase portraying a quintessential role in cellular proliferation and survival. Aberrations in the mTOR signaling pathway have been reported in numerous cancers including thyroid, lung, gastric and ovarian cancer, thus making it a therapeutic target. To attain this objective, an in silico investigation was designed, employing a pharmacophore modeling approach. A structure-based pharmacophore (SBP) model exploiting the key features of a selective mTOR inhibitor, Torkinib directed at the ATP-binding pocket was generated. A Marine Natural Products (MNP) library was screened using SBP model as a query. The retrieved compounds after consequent drug-likeness filtration were subjected to molecular docking with mTOR, thus revealing four MNPs with better scores than Torkinib. Successive refinement via molecular dynamics simulations demonstrated that the hits formed crucial interactions with key residues of the pocket. Furthermore, the four identified hits exhibited good binding free energy scores through MM-PBSA calculations and the subsequent in silico toxicity assessments displayed three hits deemed essentially non-carcinogenic and non-mutagenic. The hits presented in this investigation could act as potent ATP-competitive mTOR inhibitors, representing a platform for the future discovery of drugs from marine natural origin.

Design and Synthesis of New Sulfonamides-Based Flt3 Inhibitors

Background:

Flt3 is an oncogenic kinase involved in different leukemias. It is most prominently associated with acute myeloid leukemia (AML). Flt3-specific inhibitors have shown promising results in interfering with AML.

Methods:

The crystallographic structures of two inhibitors complexed within Flt3, namely, quizartinib and F6M, were used to guide the synthesis of new sulfonamide-based Flt3 inhibitors.

Results:

One of the prepared compounds showed low micromolar anti-Flt3 bioactivity, and interestingly, low micromolar bioactivity against the related oncogenic kinase VEGFR2.

Conclusion:

Sulfonamides were successfully used as privileged scaffolds for the synthesis of novel Flt3 inhibitors of micromolar potencies.

Triple-negative breast cancer suppressive activities, antioxidants and pharmacophore model of new acylated rhamnopyranoses from Premna odorata

Phytochemical investigation of Premna odorata Blanco “Lamiaceae” young stems afforded four new acylated rhamnopyranoses 1–4, along with fourteen known compounds 5–19.

Metabolomic Profiling and Cytotoxic Tetrahydrofurofuran Lignans Investigations from Premna odorata Blanco

Metabolomic profiling of different Premna odorata Blanco (Lamiaceae) organs, bark, wood, young stems, flowers, and fruits dereplicated 20, 20, 10, 20, and 20 compounds, respectively, using LC-HRESIMS. The identified metabolites (1-34) belonged to different chemical classes, including iridoids, flavones, phenyl ethanoids, and lignans. A phytochemical investigation of P. odorata bark afforded one new tetrahydrofurofuran lignan, 4β-hydroxyasarinin 35, along with fourteen known compounds. The structure of the new compound was confirmed using extensive 1D and 2D NMR, and HRESIMS analyses. A cytotoxic investigation of compounds 35-38 against the HL-60, HT-29, and MCF-7 cancer cell lines, using the MTT assay showed that compound 35 had cytotoxic effects against HL-60 and MCF-7 with IC50 values of 2.7 and 4.2 µg/mL, respectively. A pharmacophore map of compounds 35 showed two hydrogen bond acceptor (HBA) aligning the phenoxy oxygen atoms of benzodioxole moieties, two aromatic ring features vectored on the two phenyl rings, one hydrogen bond donor (HBD) feature aligning the central hydroxyl group and thirteen exclusion spheres which limit the boundaries of sterically inaccessible regions of the target's active site.

Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening Approaches

Background:

Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation.

Results:

Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery. Similarity, searches and virtual screening are used to identify molecules with an increased probability to interact with drug targets of interest, while the other computational approaches are applied for the design and evaluation of molecules with enhanced activity and improved safety profile.

Conclusion:

In this review are described the main in silico techniques used in rational drug design of antineoplastic agents and presented optimal combinations of computational methods for design of more efficient antineoplastic drugs.

Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis

BACKGROUND

PI3Kδ is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3Kδ inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3Kδ binding.

METHODS

Seventeen PI3Kδ crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon combination with other physicochemical descriptors).

RESULTS

The best QSAR model (r2 = 0.71, r2 LOO = 0.70, r2 press against external testing list of 15 compounds = 0.80) included a single crystallographic pharmacophore of optimal explanatory qualities. The resulting pharmacophore and QSAR model were used to screen the National Cancer Institute (NCI) database for new PI3Kδ inhibitors. Two hits showed low micromolar IC50 values.

CONCLUSION

Crystallography-based pharmacophores were successfully combined with QSAR analysis for the identification of novel PI3Kδ inhibitors.

Mechanism involved in insulin resistance via accumulation of β-amyloid and neurofibrillary tangles: link between type 2 diabetes and Alzheimer's disease

The pathophysiological link between type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) has been suggested in several reports. Few findings suggest that T2DM has strong link in the development process of AD, and the complete mechanism is yet to be revealed. Formation of amyloid plaques (APs) and neurofibrillary tangles (NFTs) are two central hallmarks in the AD. APs are the dense composites of β-amyloid protein (Aβ) which accumulates around the nerve cells. Moreover, NFTs are the twisted fibers containing hyperphosphorylated tau proteins present in certain residues of Aβ that build up inside the brain cells. Certain factors contribute to the aetiogenesis of AD by regulating insulin signaling pathway in the brain and accelerating the formation of neurotoxic Aβ and NFTs via various mechanisms, including GSK3β, JNK, CamKII, CDK5, CK1, MARK4, PLK2, Syk, DYRK1A, PPP, and P70S6K. Progression to AD could be influenced by insulin signaling pathway that is affected due to T2DM. Interestingly, NFTs and APs lead to the impairment of several crucial cascades, such as synaptogenesis, neurotrophy, and apoptosis, which are regulated by insulin, cholesterol, and glucose metabolism. The investigation of the molecular cascades through insulin functions in brain contributes to probe and perceive progressions of diabetes to AD. This review elaborates the molecular insights that would help to further understand the potential mechanisms linking T2DM and AD.

New views and possibilities of antidiabetic drugs in treating and/or preventing mild cognitive impairment and Alzheimer's Disease

Mounting evidence suggests that diabetes mellitus (DM) is associated with mild cognitive impairment (MCI), vascular dementia and Alzheimer's disease (AD). Biological, clinical and epidemiological data support a close link between DM and AD. Increasingly, studies have found that several antidiabetic agents can promote neurogenesis, and clinically ameliorate cognitive and memory impairments in different clinical settings. Data has shown that these antidiabetic drugs positively affect mitochondrial and synaptic function, neuroinflammation, and brain metabolism. Evidence to date strongly suggests that these antidiabetic drugs could be developed as disease-modifying therapies for MCI and AD in patients with and without diabetes.

Combining Stochastic Deformation/Relaxation and Intermolecular Contacts Analysis for Extracting Pharmacophores from Ligand-Receptor Complexes

We previously combined molecular dynamics (classical or simulated annealing) with ligand-receptor contacts analysis as a means to extract valid pharmacophore model(s) from single ligand-receptor complexes. However, molecular dynamics methods are computationally expensive and time-consuming. Here we describe a novel method for extracting valid pharmacophore model(s) from a single crystallographic structure within a reasonable time scale. The new method is based on ligand-receptor contacts analysis following energy relaxation of a predetermined set of randomly deformed complexes generated from the targeted crystallographic structure. Ligand-receptor contacts maintained across many deformed/relaxed structures are assumed to be critical and used to guide pharmacophore development. This methodology was implemented to develop valid pharmacophore models for PI3K-γ, RENIN, and JAK1. The resulting pharmacophore models were validated by receiver operating characteristic (ROC) analysis against inhibitors extracted from the CHEMBL database. Additionally, we implemented pharmacophores extracted from PI3K-γ to search for new inhibitors from the National Cancer Institute list of compounds. The process culminated in new PI3K-γ/mTOR inhibitory leads of low micromolar IC₅₀s.

Insulin signaling: An opportunistic target to minify the risk of Alzheimer's disease

Alzheimer's disease (AD) is progressive neurodegenerative disorder characterized by accumulation of senile plaques, neurofibrillary tangles (NFT) and neurodegeneration. The diabetes mellitus (DM) is one of the risk factors for AD pathogenesis by impairment in insulin signaling and glucose metabolism in central as well as peripheral system. Insulin resistance, impaired glucose and lipid metabolism are leading to the Aβ (Aβ) aggregation, Tau phosphorylation, mitochondrial dysfunction, oxidative stress, protein misfolding, memory impairment and also mark over Aβ transport through central to peripheral and vice versa. Several pathways, like enzymatic degradation of Aβ, forkhead box protein O1 (FOXO) signaling, insulin signaling shared common pathological mechanism for both AD and DM. Recent evidence showed that hyperinsulinemia and hyperglycemia affect the onset and progression of AD differently. Some researchers have suggested that hyperglycemia influences vascular tone, while hyperinsulinemia may underlie mitochondrial deficit. The objective of this review is to determine whether existing evidence supports the concept that impairment in insulin signaling and glucose metabolism play an important role in pathogenesis of AD. In the first part of this review, we tried to explain the interconnecting link between AD and DM, whereas the second part includes more information on insulin resistance and its involvement in AD pathogenesis. In the final part of this review, we have focused more toward the AD treatment by targeting insulin signaling like anti-diabetic, antioxidant, nutraceuticals and dietary supplements. To date, more researches should be done in this field in order to explore the pathways in insulin signaling, which might ameliorate the treatment options and reduce the risk of AD due to DM.

Simulated annealing molecular dynamics and ligand-receptor contacts analysis for pharmacophore modeling

AIM

Ligand-based pharmacophore modeling requires long list of inhibitors, while pharmacophores based on single ligand-receptor crystallographic structure can be too restricted or promiscuous.

METHODOLOGY

This prompted us to combine simulated annealing molecular dynamics (SAMD) with ligand-receptor contacts analysis as means to construct pharmacophore model(s) from single ligand-receptor complex. Ligand-receptor contacts that survive numerous heating-cooling SAMD cycles are considered critical and are used to guide pharmacophore development.

RESULTS

This methodology was implemented to develop pharmacophores for acetylcholinesterase and protein kinase C-θ. The resulting models were validated by receiver-operating characteristic analysis and in vitro bioassay. Assay identified four new protein kinase C-θ inhibitors among captured hits, two of which exhibited nanomolar potencies.

CONCLUSION

The results illustrate the ability of the new method to extract valid pharmacophores from single ligand-protein complex.

The Molecular Mechanism of Glucagon-Like Peptide-1 Therapy in Alzheimer's Disease, Based on a Mechanistic Target of Rapamycin Pathway

The mechanistic target of rapamycin (mTOR) is an important molecule that connects aging, lifespan, energy balance, glucose and lipid metabolism, and neurodegeneration. Rapamycin exerts effects in numerous biological activities via its target protein, playing a key role in energy balance, regulation of autophagy, extension of lifespan, immunosuppression, and protection against neurodegeneration. There are many similar pathophysiological processes and molecular pathways between Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM), and pharmacologic agents used to treat T2DM, including glucagon-like peptide-1 (GLP-1) analogs, seem to be beneficial for AD. mTOR mediates the effects of GLP-1 analogs in the treatment of T2DM; hence, I hypothesize that mTOR is a key molecule for mediating the protective effects of GLP-1 for AD.

Potential effects of current drug therapies on cognitive impairment in patients with type 2 diabetes

Type 2 diabetes mellitus is a complex metabolic disease that can cause serious damage to various organs. Among the best-known complications, an important role is played by cognitive impairment. Impairment of cognitive functioning has been reported both in type 1 and 2 diabetes mellitus. While this comorbidity has long been known, no major advances have been achieved in clinical research; it is clear that appropriate control of blood glucose levels represents the best current (although unsatisfactory) approach in the prevention of cognitive impairment. We have focused our attention on the possible effect on the brain of antidiabetic drugs, despite their effects on blood glucose levels, giving a brief rationale on the mechanisms (e.g. GLP-1, BDNF, ghrelin) that might be involved. Indeed, GLP-1 agonists are currently clinically studied in other neurodegenerative diseases (i.e. Parkinson's and Alzheimer's disease); furthermore, also other antidiabetic drugs have proven efficacy in preclinical studies. Overall, promising results are already available and finding new intervention strategies represents a current need in this field of research.

The impact of dementia on antidiabetic drug use in Medicare beneficiaries with diabetes: findings post-Medicare part D

AIM

The objectives of the study were to measure the utilization rates of antidiabetic drugs in diabetic patients with dementia and to assess the impact of dementia on antidiabetic drug use.

MATERIALS & METHODS

This study was a pooled cross-sectional study of the Medicare Current Beneficiaries Survey from 2006 to 2010.

RESULTS & CONCLUSION

Lower utilizations of biguanides, DPP-4 inhibitors and thiazolidinediones were observed in dementia patients. The likelihood of using antidiabetic drugs was about 30% (odds ratio: 0.69; 95% CI: 0.56-0.84) lower in dementia patients and 40% (odds ratio: 0.61; 95% CI: 0.44-0.84) lower in patients with Alzheimer's disease. Healthcare providers should be aware of underuse of antidiabetic drugs in patients with dementia.

ATP Sensitive Potassium Channels in the Skeletal Muscle Function: Involvement of the KCNJ11(Kir6.2) Gene in the Determination of Mechanical Warner Bratzer Shear Force

The ATP-sensitive K⁺-channels (KATP) are distributed in the tissues coupling metabolism with K⁺ ions efflux. KATP subunits are encoded by KCNJ8 (Kir6.1), KCNJ11 (Kir6.2), ABCC8 (SUR1), and ABCC9 (SUR2) genes, alternative RNA splicing give rise to SUR variants that confer distinct physiological properties on the channel. An high expression/activity of the sarco-KATP channel is observed in various rat fast-twitch muscles, characterized by elevated muscle strength, while a low expression/activity is observed in the slow-twitch muscles characterized by reduced strength and frailty. Down-regulation of the KATP subunits of fast-twitch fibers is found in conditions characterized by weakness and frailty. KCNJ11 gene knockout mice have reduced glycogen, lean phenotype, lower body fat, and weakness. KATP channel is also a sensor of muscle atrophy. The KCNJ11 gene is located on BTA15, close to a QTL for meat tenderness, it has also a role in glycogen storage, a key mechanism of the postmortem transformation of muscle into meat. The role of KCNJ11 gene in muscle function may underlie an effect of KCNJ11 genotypes on meat tenderness, as recently reported. The fiber phenotype and genotype are important in livestock production science. Quantitative traits including meat production and quality are influenced both by environment and genes. Molecular markers can play an important role in the genetic improvement of animals through breeding strategies. Many factors influence the muscle Warner-Bratzler shear force including breed, age, feeding, the biochemical, and functional parameters. The role of KCNJ11gene and related genes on muscle tenderness will be discussed in the present review.

Discovering new mTOR inhibitors for cancer treatment through virtual screening methods and in vitro assays

Mammalian target of rapamycin (mTOR) is an attractive target for new anticancer drug development. We recently developed in silico models to distinguish mTOR inhibitors and non-inhibitors. In this study, we developed an integrated strategy for identifying new mTOR inhibitors using cascaded in silico screening models. With this strategy, fifteen new mTOR kinase inhibitors including four compounds with IC₅₀ values below 10 μM were discovered. In particular, compound 17 exhibited potent anticancer activities against four tumor cell lines, including MCF-7, HeLa, MGC-803, and C6, with IC₅₀ values of 1.90, 2.74, 3.50 and 11.05 μM. Furthermore, cellular studies and western blot analyses revealed that 17 induces cell death via apoptosis by targeting both mTORC1 and mTORC2 within cells and arrests the cell cycle of HeLa at the G₁/G₀-phase. Finally, multi-nanosecond explicit solvent simulations and MM/GBSA analyses were carried out to study the inhibitory mechanisms of 13, 17, and 40 for mTOR. The potent compounds presented here are worthy of further investigation.

Potency and pharmacokinetics of broad spectrum and isoform-specific p110γ and δ inhibitors in cancers

Emerging data on cancer suggesting that target-based therapy is promising strategy in cancer treatment. PI3K-AKT pathway is extensively studied in many cancers; several inhibitors target this pathway in different levels. Recent finding on this pathway uncovered the therapeutic applications of PI3K-specific inhibitors; PI3K, AKT, and mTORC broad spectrum inhibitors. Noticeably, class I PI3K isoforms, p110γ and p110δ catalytic subunits have rational therapeutic application than other isoforms. Therefore, three classes of inhibitors: isoform-specific, dual-specific and broad spectrum were selected for molecular docking and dynamics. First, p110δ structure was modelled; active site was analyzed. Then, molecular docking of each class of inhibitors were studied; the docked complexes were further used in 1.2 ns molecular dynamics simulation to report the potency of each class of inhibitor. Remarkably, both the studies retained the similar kind of protein ligand interactions. GDC-0941, XL-147 (broad spectrum); TG100-115 (dual-specific); and AS-252424, PIK-294 (isoform-specific) were found to be potential inhibitors of p110γ and p110δ, respectively. In addition to that pharmacokinetic properties are within recommended ranges. Finally, molecular phylogeny revealed that p110γ and p110δ are evolutionarily divergent; they probably need separate strategies for drug development.

Molecular and biochemical trajectories from diabetes to Alzheimer’s disease: A critical appraisal

Diabetes mellitus (DM), a metabolic disorder is a major orchestra influencing brain and behavioral responses via direct or indirect mechanisms. Many lines of evidence suggest that diabetic patients apparently face severe brain complications, but the story is far from being fully understood. Type 2 diabetes, an ever increasing epidemic and its chronic brain complications are implicated in the development of Alzheimer’s disease (AD). Evidences from clinical and experimental studies suggest that insulin draws a clear trajectory from the peripheral system to the central nervous system. This review is a spot light on striking pathological, biochemical, molecular and behavioral commonalities of AD and DM. Incidence of cognitive decline in diabetic patients and diabetic symptoms in AD patients has brought the concept of brain diabetes to attention. Brain diabetes reflects insulin resistant brain state with oxidative stress, cognitive impairment, activation of various inflammatory cascade and mitochondrial vulnerability as a shared footprint of AD and DM. It has become extremely important for the investigators to understand the patho-physiology of brain complications in diabetes and put intensive pursuits for therapeutic interventions. Although, decades of research have yielded a range of molecules with potential beneficial effects, but they are yet to meet the expectations.

Olive Oil-derived Oleocanthal as Potent Inhibitor of Mammalian Target of Rapamycin: Biological Evaluation and Molecular Modeling Studies

The established anticancer and neuroprotective properties of oleocanthal combined with the reported role of mammalian target of rapamycin (mTOR) in cancer and Alzheimer's disease development encouraged us to examine the possibility that oleocanthal inhibits mTOR. To validate this hypothesis, we docked oleocanthal into the adenosine triphosphate binding pocket of a close mTOR protein homologue, namely, PI3K-γ. Apparently, oleocanthal shared nine out of ten critical binding interactions with a potent dual PIK3-γ/mTOR natural inhibitor. Subsequent experimental validation indicated that oleocanthal indeed inhibited the enzymatic activity of mTOR with an IC50 value of 708 nM. Oleocanthal inhibits the growth of several breast cancer cell lines at low micromolar concentration in a dose-dependent manner. Oleocanthal treatment caused a marked downregulation of phosphorylated mTOR in metastatic breast cancer cell line (MDA-MB-231). These results strongly indicate that mTOR inhibition is at least one of the factors of the reported anticancer and neuroprotective properties of oleocanthal.

Determination and validation of mTOR kinase-domain 3D structure by homology modeling

The AKT/mammalian target of rapamycin (mTOR) pathway is considered as one of the commonly activated and deregulated signaling pathways in human cancer. mTOR is associated with other proteins in two molecular complexes: mTOR complex 1/Raptor and the mTOR complex 2/Rictor. Using the crystal structure of the related lipid kinase PI3Kγ, we built a model of the catalytic region of mTOR. The modeling of the three-dimensional (3D) structure of the mTOR was performed by homology modeling program SWISS-MODEL. The quality and validation of the obtained model were performed using PROCHECK and PROVE softwares. The overall stereochemical property of the protein was assessed by the Ramachandran plot. The model validation was also done by docking of known inhibitors. In this paper, we describe and validate a 3D model for the mTOR catalytic site.

Design and Evaluation of 3-(Benzylthio)benzamide Derivatives as Potent and Selective SIRT2 Inhibitors

Inhibitors of sirtuin-2 (SIRT2) deacetylase have been shown to be protective in various models of Huntington's disease (HD) by decreasing polyglutamine aggregation, a hallmark of HD pathology. The present study was directed at optimizing the potency of SIRT2 inhibitors containing the 3-(benzylsulfonamido)benzamide scaffold and improving their metabolic stability. Molecular modeling and docking studies revealed an unfavorable role of the sulfonamide moiety for SIRT2 binding. This prompted us to replace the sulfonamide with thioether, sulfoxide, or sulfone groups. The thioether analogues were the most potent SIRT2 inhibitors with a two- to three-fold increase in potency relative to their corresponding sulfonamide analogues. The newly synthesized compounds also demonstrated higher SIRT2 selectivity over SIRT1 and SIRT3. Two thioether-derived compounds (17 and 18) increased α-tubulin acetylation in a dose-dependent manner in at least one neuronal cell line, and 18 was found to inhibit polyglutamine aggregation in PC12 cells.

Pharmacophore approaches in protein kinase inhibitors design

Protein kinases constitute a superfamily of therapeutic targets for a number of human and animal diseases that include more than 500 members accordingly to sequencing data of the human genome. The well characterized nature of protein kinases makes them excellent targets for drug development. Pharmacophore approaches have become one of the major tools in the area of drug discovery. Application of pharmacophore modeling approaches allows reducing of expensive overall cost associated with drug development project. Pharmacophore models are important functional groups of atoms in the proper spatial position for interaction with target protein. Various ligand-based and structure-based methods have been developed for pharmacophore model generation. Despite the successes in pharmacophore models generation these approaches have not reached their full capacity in application for drug discovery. In the following review, we summarize the published data on pharmacophore models for inhibitors of tyrosine protein kinases (EGFR, HER2, VEGFR, JAK2, JAK3, Syk, ZAP-70, Tie2) and inhibitors of serine/threonine kinases (Clk, Dyrk, Chk1, IKK2, CDK1, CDK2, PLK, JNK3, GSK3, mTOR, p38 MAPK, PKB). Here, we have described the achievements of pharmacophore modeling for protein kinase inhibitors, which provide key points for further application of generated pharmacophore hypotheses in virtual screening, de novo design and lead optimization.

Predicting mTOR inhibitors with a classifier using recursive partitioning and Naïve Bayesian approaches

Background

Mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. Thus, there is a great deal of interest in developing clinical drugs based on mTOR. In this paper, in silico models based on multi-scaffolds were developed to predict mTOR inhibitors or non-inhibitors.

Methods

First 1,264 diverse compounds were collected and categorized as mTOR inhibitors and non-inhibitors. Two methods, recursive partitioning (RP) and naïve Bayesian (NB), were used to build combinatorial classification models of mTOR inhibitors versus non-inhibitors using physicochemical descriptors, fingerprints, and atom center fragments (ACFs).

Results

A total of 253 models were constructed and the overall predictive accuracies of the best models were more than 90% for both the training set of 964 and the external test set of 300 diverse compounds. The scaffold hopping abilities of the best models were successfully evaluated through predicting 37 new recently published mTOR inhibitors. Compared with the best RP and Bayesian models, the classifier based on ACFs and Bayesian shows comparable or slightly better in performance and scaffold hopping abilities. A web server was developed based on the ACFs and Bayesian method (http://rcdd.sysu.edu.cn/mtor/). This web server can be used to predict whether a compound is an mTOR inhibitor or non-inhibitor online.

Conclusion

In silico models were constructed to predict mTOR inhibitors using recursive partitioning and naïve Bayesian methods, and a web server (mTOR Predictor) was also developed based on the best model results. Compound prediction or virtual screening can be carried out through our web server. Moreover, the favorable and unfavorable fragments for mTOR inhibitors obtained from Bayesian classifiers will be helpful for lead optimization or the design of new mTOR inhibitors.

Elaborate ligand-based modeling coupled with multiple linear regression and k nearest neighbor QSAR analyses unveiled new nanomolar mTOR inhibitors

The mammalian target of rapamycin (mTOR) has an important role in cell growth, proliferation, and survival. mTOR is frequently hyperactivated in cancer, and therefore, it is a clinically validated target for cancer therapy. In this study, we combined exhaustive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent mTOR inhibitors employing 210 known mTOR ligands. Genetic function algorithm (GFA) coupled with k nearest neighbor (kNN) and multiple linear regression (MLR) analyses were employed to build self-consistent and predictive QSAR models based on optimal combinations of pharmacophores and physicochemical descriptors. Successful pharmacophores were complemented with exclusion spheres to optimize their receiver operating characteristic curve (ROC) profiles. Optimal QSAR models and their associated pharmacophore hypotheses were validated by identification and experimental evaluation of several new promising mTOR inhibitory leads retrieved from the National Cancer Institute (NCI) structural database. The most potent hit illustrated an IC50 value of 48 nM.