Combined ligand- and structure-based studies on inhibitors of P-glycoprotein

Der aktive Effluxtransporter P-Glykoprotein (P-gp) ist verantwortlich für Multidrug Resistenz (MDR) in Tumoren und beeinflusst außerdem die ADME Eigenschaften von Arzneistoffkandidaten. P-gp zeigt eine sehr breite Substratspezifität und transportiert daher eine hohe Anzahl von strukturell und funktionell diversen Substanzen aus Tumorzellen hinaus und über physiologische Barrieren hinweg. Obwohl in den letzten zwei Jahrzehnten einige Inhibitoren von P-gp identifiziert wurden, scheiterten alle von ihnen in klinischen Studien, entweder wegen schwerwiegenden Nebenwirkungen, oder wegen fehlender Wirksamkeit. Dies betont die Notwendigkeit von verlässlichen in silico Modellen für die Vorhersage von P-gp Substraten und Inhibitoren bereits in frühen Phasen der Wirkstoffentwicklung. In dieser Arbeit wurden daher unterschiedliche in silico Methoden verwendet um Einblicke in die dreidimensionalen strukturellen Voraussetzungen der Liganden, ihren Bindungsmodus und ihre Stereoselektivität gegenüber P-gp zu erhalten. Verschiedene 2D- und 3D-QSAR Modelle wurden mit einfachen physicochemischen sowie komplexen 3D-Deskriptoren (GRIND) für unterschiedliche chemische Grundkörper erstellt, um globale strukturelle Merkmale von P-gp Inhibitoren zu untersuchen. Um die vielversprechendsten P-gp Liganden mit dem besten Wirksamkeits/Lipophilie- oder Größenverhältnis zu identifizieren, verwendeten wir zum bisher ersten Mal ligandeneffizienz- und lipophilieeffizienzbasierte Ansätze. Interessanterweise überschritt keine der vielversprechendsten Substanzen den LipE Grenzwert von 5. Dies könnte mit dem einzigartigen Zugangsweg der Substanzen zusammenhängen, der anders als bei anderen Transportern oder Ionenkanälen direkt aus der Zellmembran erfolgt. Unsere Dockingstudien bieten einen ersten Nachweis über unterschiedliche Bindungsareale für zwei diastereomere Substanzserien und zeigen eine stereoselektive Ligandenerkennung von P-gp. Zusätzlich war es uns möglich zu zeigen, dass sich ein Benzophenon-Dimer so platzieren lässt, dass diese beiden Areale verbunden werden, was die Hypothese von mehreren, teilweise überlappenden, Bindunsarealen von P-gp verstärkt. Die in dieser Dissertation beschriebene Arbeit wird den Weg für die Entwicklung von zukünftlichen neuen und vielversprechenderen Inhibitoren von P-gp bereiten, die bessere ADME Eigenschaften und verringerte Toxizität besitzen.The drug efflux pump P-glycoprotein (P-gp) has been shown to cause multidrug resistance (MDR) in tumors as well as to influence ADME properties of drug candidates. P-gp is highly promiscuous in its ligand recognition profiles and thus transports numerous structurally and functionally diverse compounds out of tumor cells and accross physiological barriers. Several inhibitors of P-gp mediated drug efflux have been identified in the past two decades, but all of them failed in clinical trials due to severe side effects and lack of efficacy. This further emphasizes the necessity of reliable in-silico tools for prediction of P-gp substrates and inhibitors during the early phases of drug discovery. Therefore, in this thesis, various in silico tools have been utilized to get insights into 3D structural requirements of ligands, their binding modes, as well as their stereoselectivity towards P-gp. Different 2D- and 3D-QSAR models using simple physicochemical and GRID independent molecular descriptors have been constructed across different chemical scaffolds to investigate global structural attributes of P-gp inhibitors. In order to identify most promising P-gp ligands with best potency/lipophilicity or size ratio, we, for the first time, also used ligand efficiency and lipophilic efficiency based approaches. Interestingly, none of the P-gp inhibitors/substrates cross the LipE threshold of 5 for highly promising compounds. This might be linked to the unique entry pathway directly from the membrane bilayer, which is rather unique for transporters and ion channels. Our docking studies provide the first evidence for different binding areas of two diastereomeric compound series and provides evidence for stereoselective ligand recognition of by P-gp. In addition we could show that a benzophenone dimer is well docked in a pose bridging these two distinct binding sites, which further strengthens the hypothesis of multiple, partly overlapping binding sites at P-gp. The work described in this thesis will pave the way for the design of new and more promising inhibitors of P-gp in the future with better ADME properties and reduced toxicity

Structure, Function, and Modulation of γ-Aminobutyric Acid Transporter 1 (GAT1) in Neurological Disorders: A Pharmacoinformatic Prospective

γ-Aminobutyric acid (GABA) Transporters (GATs) belong to sodium and chloride dependent-transporter family and are widely expressed throughout the brain. Notably, GAT1 is accountable for sustaining 75% of the synaptic GABA concentration and entails its transport to the GABAA receptors to initiate the receptor-mediated inhibition of post-synaptic neurons. Imbalance in ion homeostasis has been associated with several neurological disorders related to the GABAergic system. However, inhibition of the GABA uptake by these transporters has been accepted as an effective approach to enhance GABAergic inhibitory neurotransmission in the treatment of seizures in epileptic and other neurological disorders. Here, we reviewed computational methodologies including molecular modeling, docking, and molecular dynamic simulations studies to underscore the structure and function of GAT1 in the GABAergic system. Additionally, various SAR and QSAR methodologies have been reviewed to probe the 3D structural features of inhibitors required to modulate GATs activity. Overall, present review provides an overview of crucial role of GAT1 in GABAergic system and its modulation to evade neurological disorders

GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors

Background The γ-aminobutyric acid (GABA) transporter GAT1 is involved in GABA transport across the biological membrane in and out of the synaptic cleft. The efficiency of this Na+ coupled GABA transport is regulated by an electrochemical gradient, which is directed inward under normal conditions. However, in certain pathophysiological situations, including strong depolarization or an imbalance in ion homeostasis, the GABA influx into the cytoplasm is increased by re-uptake transport mechanism. This mechanism may lead to extra removal of extracellular GABA which results in numerous neurological disorders such as epilepsy. Thus, small molecule inhibitors of GABA re-uptake may enhance GABA activity at the synaptic clefts. Methods In the present study, various GRID-independent molecular descriptor (GRIND) models have been developed to shed light on the 3D structural features of human GAT1 (hGAT1) inhibitors using nipecotic acid and N-diarylalkenyl piperidine analogs. Further, a binding hypothesis has been developed for the selected GAT1 antagonists by molecular docking inside the binding cavity of hGAT1 homology model. Results Our results indicate that two hydrogen bond acceptors, one hydrogen bond donor and one hydrophobic region at certain distances from each other play an important role in achieving high inhibitory potency against hGAT1. Our docking results elucidate the importance of the COOH group in hGAT1 antagonists by considering substitution of the COOH group with an isoxazol ring in compound 37, which subsequently leads to a three order of magnitude decrease in biological activity of 37 (IC50 = 38 µM) as compared to compound 1 (IC50 = 0.040 µM). Discussion Our docking results are strengthened by the structure activity relationship of the data series as well as by GRIND models, thus providing a significant structural basis for understanding the binding of antagonists, which may be useful for guiding the design of hGAT1 inhibitors

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG

Combined Pharmacophore and Grid-Independent Molecular Descriptors (GRIND) Analysis to Probe 3D Features of Inositol 1,4,5-Trisphosphate Receptor (IP3R) Inhibitors in Cancer

Inositol 1, 4, 5-trisphosphate receptor (IP3R)-mediated Ca2+ signaling plays a pivotal role in different cellular processes, including cell proliferation and cell death. Remodeling Ca2+ signals by targeting the downstream effectors is considered an important hallmark in cancer progression. Despite recent structural analyses, no binding hypothesis for antagonists within the IP3-binding core (IBC) has been proposed yet. Therefore, to elucidate the 3D structural features of IP3R modulators, we used combined pharmacoinformatic approaches, including ligand-based pharmacophore models and grid-independent molecular descriptor (GRIND)-based models. Our pharmacophore model illuminates the existence of two hydrogen-bond acceptors (2.62 Å and 4.79 Å) and two hydrogen-bond donors (5.56 Å and 7.68 Å), respectively, from a hydrophobic group within the chemical scaffold, which may enhance the liability (IC50) of a compound for IP3R inhibition. Moreover, our GRIND model (PLS: Q2 = 0.70 and R2 = 0.72) further strengthens the identified pharmacophore features of IP3R modulators by probing the presence of complementary hydrogen-bond donor and hydrogen-bond acceptor hotspots at a distance of 7.6–8.0 Å and 6.8–7.2 Å, respectively, from a hydrophobic hotspot at the virtual receptor site (VRS). The identified 3D structural features of IP3R modulators were used to screen (virtual screening) 735,735 compounds from the ChemBridge database, 265,242 compounds from the National Cancer Institute (NCI) database, and 885 natural compounds from the ZINC database. After the application of filters, four compounds from ChemBridge, one compound from ZINC, and three compounds from NCI were shortlisted as potential hits (antagonists) against IP3R. The identified hits could further assist in the design and optimization of lead structures for the targeting and remodeling of Ca2+ signals in cancer

Molecular Dynamic Simulations to Probe Stereoselectivity of Tiagabine Binding with Human GAT1

The human gamma aminobutyric acid transporter subtype 1 (hGAT1) located in the nerve terminals is known to catalyze the neuronal function by the electrogenic reuptake of γ-aminobutyric acid (GABA) with the co-transport of Na+ and Cl− ions. In the past, there has been a major research drive focused on the dysfunction of hGAT1 in several neurological disorders. Thus, hGAT1 of the GABAergic system has been well established as an attractive target for such diseased conditions. Till date, there are various reports about stereo selectivity of –COOH group of tiagabine, a Food and Drug Administration (FDA)-approved hGAT1-selective antiepileptic drug. However, the effect of the stereochemistry of the protonated –NH group of tiagabine has never been scrutinized. Therefore, in this study, tiagabine has been used to explore the binding hypothesis of different enantiomers of tiagabine. In addition, the impact of axial and equatorial configuration of the–COOH group attached at the meta position of the piperidine ring of tiagabine enantiomers was also investigated. Further, the stability of the finally selected four hGAT1–tiagabine enantiomers namely entries 3, 4, 6, and 9 was evaluated through 100 ns molecular dynamics (MD) simulations for the selection of the best probable tiagabine enantiomer. The results indicate that the protonated –NH group in the R-conformation and the –COOH group of Tiagabine in the equatorial configuration of entry 4 provide maximum strength in terms of interaction within the hGAT1 binding pocket to prevent the change in hGAT1 conformational state, i.e., from open-to-out to open-to-in as compared to other selected tiagabine enantiomers 3, 6, and 9

A 2D-QSAR and Grid-Independent Molecular Descriptor (GRIND) Analysis of Quinoline-Type Inhibitors of Akt2: Exploration of the Binding Mode in the Pleckstrin Homology (PH) Domain.

Protein kinase B-β (PKBβ/Akt2) is a serine/threonine-specific protein kinase that has emerged as one of the most important regulators of cell growth, differentiation, and division. Upregulation of Akt2 in various human carcinomas, including ovarian, breast, and pancreatic, is a well-known tumorigenesis phenomenon. Early on, the concept of the simultaneous administration of anticancer drugs with inhibitors of Akt2 was advocated to overcome cell proliferation in the chemotherapeutic treatment of cancer. However, clinical studies have not lived up to the high expectations, and several phase II and phase III clinical studies have been terminated prematurely because of severe side effects related to the non-selective isomeric inhibition of Akt2. The notion that the sequence identity of pleckstrin homology (PH) domains within Akt-isoforms is less than 30% might indicate the possibility of the development of selective antagonists against the Akt2 PH domain. Therefore, in this study, various in silico tools were utilized to explore the hypothesis that quinoline-type inhibitors bind in the Akt2 PH domain. A Grid-Independent Molecular Descriptor (GRIND) analysis indicated that two hydrogen bond acceptors, two hydrogen bond donors and one hydrophobic feature at a certain distance from each other were important for the selective inhibition of Akt2. Our docking results delineated the importance of Lys30 as an anchor point for mapping the distances of important amino acid residues in the binding pocket, including Lys14, Glu17, Arg25, Asn53, Asn54 and Arg86. The binding regions identified complement the GRIND-based pharmacophoric features

Exploring the Chemical Space of Cytochrome P450 Inhibitors Using Integrated Physicochemical Parameters, Drug Efficiency Metrics and Decision Tree Models

The cytochrome P450s (CYPs) play a central role in the metabolism of various endogenous and exogenous compounds including drugs. CYPs are vulnerable to inhibition and induction which can lead to adverse drug reactions. Therefore, insights into the underlying mechanism of CYP450 inhibition and the estimation of overall CYP inhibitor properties might serve as valuable tools during the early phases of drug discovery. Herein, we present a large data set of inhibitors against five major metabolic CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) for the evaluation of important physicochemical properties and ligand efficiency metrics to define property trends across various activity levels (active, efficient and inactive). Decision tree models for CYP inhibition were developed with an accuracy >90% for both the training set and 10-folds cross validation. Overall, molecular weight (MW), hydrogen bond acceptors/donors (HBA/HBD) and lipophilicity (clogP/logPo/w) represent important physicochemical descriptors for CYP450 inhibitors. However, highly efficient CYP inhibitors show mean MW, HBA, HBD and logP values between 294.18–482.40,5.0–8.2,1–7.29 and 1.68–2.57, respectively. Our results might help in optimization of toxicological profiles associated with new chemical entities (NCEs), through a better understanding of inhibitor properties leading to CYP-mediated interactions