In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies

Regulation of P-Glycoprotein during Oxidative Stress

P-glycoprotein (Pgp, ABCB1, MDR1) is an efflux transporter protein that removes molecules from the cells (outflow) into the extracellular space. Pgp plays an important role in pharmacokinetics, ensuring the absorption, distribution, and excretion of drugs and its substrates, as well as in the transport of endogenous molecules (steroid and thyroid hormones). It also contributes to tumor cell resistance to chemotherapy. In this review, we summarize the mechanisms of Pgp regulation during oxidative stress. The currently available data suggest that Pgp has a complex variety of regulatory mechanisms under oxidative stress, involving many transcription factors, the main ones being Nrf2 and Nf-kB. These factors often overlap, and some can be activated under certain conditions, such as the deposition of oxidation products, depending on the severity of oxidative stress. In most cases, the expression of Pgp increases due to increased transcription and translation, but under severe oxidative stress, it can also decrease due to the oxidation of amino acids in its molecule. At the same time, Pgp acts as a protector against oxidative stress, eliminating the causative factors and removing its by-products, as well as participating in signaling pathways.

The Alternating Access Mechanism in Mammalian Multidrug Resistance Transporters and Their Bacterial Homologs

Multidrug resistance (MDR) proteins belonging to the ATP-Binding Cassette (ABC) transporter group play a crucial role in the export of cytotoxic drugs across cell membranes. These proteins are particularly fascinating due to their ability to confer drug resistance, which subsequently leads to the failure of therapeutic interventions and hinders successful treatments. One key mechanism by which multidrug resistance (MDR) proteins carry out their transport function is through alternating access. This mechanism involves intricate conformational changes that enable the binding and transport of substrates across cellular membranes. In this extensive review, we provide an overview of ABC transporters, including their classifications and structural similarities. We focus specifically on well-known mammalian multidrug resistance proteins such as MRP1 and Pgp (MDR1), as well as bacterial counterparts such as Sav1866 and lipid flippase MsbA. By exploring the structural and functional features of these MDR proteins, we shed light on the roles of their nucleotide-binding domains (NBDs) and transmembrane domains (TMDs) in the transport process. Notably, while the structures of NBDs in prokaryotic ABC proteins, such as Sav1866, MsbA, and mammalian Pgp, are identical, MRP1 exhibits distinct characteristics in its NBDs. Our review also emphasizes the importance of two ATP molecules for the formation of an interface between the two binding sites of NBD domains across all these transporters. ATP hydrolysis occurs following substrate transport and is vital for recycling the transporters in subsequent cycles of substrate transportation. Specifically, among the studied transporters, only NBD2 in MRP1 possesses the ability to hydrolyze ATP, while both NBDs of Pgp, Sav1866, and MsbA are capable of carrying out this reaction. Furthermore, we highlight recent advancements in the study of MDR proteins and the alternating access mechanism. We discuss the experimental and computational approaches utilized to investigate the structure and dynamics of MDR proteins, providing valuable insights into their conformational changes and substrate transport. This review not only contributes to an enhanced understanding of multidrug resistance proteins but also holds immense potential for guiding future research and facilitating the development of effective strategies to overcome multidrug resistance, thus improving therapeutic interventions.

5-Arylidenerhodanines as P-gp Modulators: An Interesting Effect of the Carboxyl Group on ABCB1 Function in Multidrug-Resistant Cancer Cells

Multidrug resistance (MDR) is considered one of the major mechanisms responsible for the failure of numerous anticancer and antiviral chemotherapies. Various strategies to overcome the MDR phenomenon have been developed, and one of the most attractive research directions is focused on the inhibition of MDR transporters, membrane proteins that extrude cytotoxic drugs from living cells. Here, we report the results of our studies on a series newly synthesized of 5-arylidenerhodanines and their ability to inhibit the ABCB1 efflux pump in mouse T-lymphoma cancer cells. In the series, compounds possessing a triphenylamine moiety and the carboxyl group in their structure were of particular interest. These amphiphilic compounds showed over 17-fold stronger efflux pump inhibitory effects than verapamil. The cytotoxic and antiproliferative effects of target rhodanines on T-lymphoma cells were also investigated. A putative binding mode for 11, one of the most potent P-gp inhibitors tested here, was predicted by molecular docking studies and discussed with regard to the binding mode of verapamil.

Part-II- in silico drug design: application and success

In silico tools have indeed reframed the steps involved in traditional drug discovery and development process and the term in silico has become a familiar term in pharmaceutical sector like the terms in vitro and in vivo. The successful design of HIV protease inhibitors, Saquinavir, Indinavir and other important medicinal agents, initiated interest of researchers in structure based drug design approaches (SBDD). The interactions between biomolecules and a ligand, binding energy, free energy and stability of biomolecule-ligand complex can be envisioned and predicted by applying molecular docking studies. Protein-ligand, protein-protein, DNA-ligand interactions etc. aid in elucidating molecular level mechanisms of drug molecules. In the Ligand based drug design (LBDD) approaches, QSAR studies have tremendously contributed to the development of antimicrobial, anticancer, antimalarial agents. In the recent years, multiQSAR (mt-QSAR) approaches have been successfully employed for designing drugs against multifactorial diseases. Output of a research in several instances is rewarding when both SBDD and LBDD approaches are combined. Application of in silico studies for prediction of pharmacokinetics was once a real challenge but one can see unlimited number publications comprising tools, data bases which can accurately predict almost all the pharmacokinetic parameters. Absorption, distribution, metabolism, transporters, blood brain barrier permeability, hERG toxicity, P-gp affinity and several toxicological end points can be accurately predicted for a candidate molecule before its synthesis. In silico approaches are greatly encouraged a result of growing limitations and new legislations related to the animal use for research. The combined use of in vitro data and in silico tools will definitely decrease the use of animal testing in the future.In this chapter, in silico approaches and their applications are reviewed and discussed giving suitable examples.

Effect of the Force Field on Molecular Dynamics Simulations of the Multidrug Efflux Protein P-Glycoprotein

Molecular dynamics (MD) simulations have been used extensively to study P-glycoprotein (P-gp), a flexible multidrug transporter that is a key player in the development of multidrug resistance to chemotherapeutics. A substantial body of literature has grown from simulation studies that have employed various simulation conditions and parameters, including AMBER, CHARMM, OPLS, GROMOS, and coarse-grained force fields, drawing conclusions from simulations spanning hundreds of nanoseconds. Each force field is typically parametrized and validated on different data and observables, usually of small molecules and peptides; there have been few comparisons of force field performance on large protein-membrane systems. Here we compare the conformational ensembles of P-gp embedded in a POPC/cholesterol bilayer generated over 500 ns of replicate simulation with five force fields from popular biomolecular families: AMBER 99SB-ILDN, CHARMM 36, OPLS-AA/L, GROMOS 54A7, and MARTINI. We find considerable differences among the ensembles with little conformational overlap, although they correspond to similar extents to structural data obtained from electron paramagnetic resonance and cross-linking studies. Moreover, each trajectory was still sampling new conformations at a high rate after 500 ns of simulation, suggesting the need for more sampling. This work highlights the need to consider known limitations of the force field used (e.g., biases toward certain secondary structures) and the simulation itself (e.g., whether sufficient sampling has been achieved) when interpreting accumulated results of simulation studies of P-gp and other transport proteins.

What dominates the changeable pharmacokinetics of natural sesquiterpene lactones and diterpene lactones: a review focusing on absorption and metabolism

Sesquiterpene lactones (STLs) and diterpene lactones (DTLs) are two groups of common phytochemicals with similar structures. It's frequently reported that both exhibit changeable pharmacokinetics (PK) in vivo, especially the unstable absorption and extensive metabolism. However, the recognition of their PK characteristics is still scattered. In this review, representative STLs (atractylenolides, alantolactone, costunolide, artemisinin, etc.) and DTLs (ginkgolides, andrographolide, diosbulbins, triptolide, etc.) as typical cases are discussed in detail. We show how the differences of treatment regimens and subjects alter the PK of STLs and DTLs, with emphasis on the effects from absorption and metabolism. These compounds tend to be quite permeable in intestinal epithelium, but gastrointestinal pH and efflux transporters (represented by P-glycoprotein) have great impact and result in the unstable absorption. As the only characteristic functional moiety, the metabolic behavior of lactone ring is not dominant. The α, β-unsaturated lactone moiety has the strongest metabolic activity. While with the increase of low-activity saturated lactone moieties, the metabolism is led by other groups more easily. The phase I (oxidation, reduction and hydrolysis reaction) and II metabolism (conjugation reaction) are both extensive. CYP450s, mainly CYP3A4, are largely involved in biotransformation. However, only UGTs (UGT1A3, UGT1A4, UGT2B4 and UGT2B7) has been mentioned in studies about phase II metabolic enzymes. Our work offers a beneficial reference for promoting the safety evaluation and maximizing the utilization of STLs and DTLs.

Search for ABCB1 Modulators Among 2-Amine-5-Arylideneimidazolones as a New Perspective to Overcome Cancer Multidrug Resistance

Multidrug resistance (MDR) is a severe problem in the treatment of cancer with overexpression of glycoprotein P (Pgp, ABCB1) as a reason for chemotherapy failure. A series of 14 novel 5-arylideneimidazolone derivatives containing the morpholine moiety, with respect to two different topologies (groups A and B), were designed and obtained in a three- or four-step synthesis, involving the Dimroth rearrangement. The new compounds were tested for their inhibition of the ABCB1 efflux pump in both sensitive (parental (PAR)) and ABCB1-overexpressing (MDR) T-lymphoma cancer cells in a rhodamine 123 accumulation assay. Their cytotoxic and antiproliferative effects were investigated by a thiazolyl blue tetrazolium bromide (MTT) assay. For active compounds, an insight into the mechanisms of action using either the luminescent Pgp-Glo™ Assay in vitro or docking studies to human Pgp was performed. The safety profile in vitro was examined. Structure–activity relationship (SAR) analysis was discussed. The most active compounds, representing both 2-substituted- (11) and Dimroth-rearranged 3-substituted (18) imidazolone topologies, displayed 1.38–1.46 fold stronger efflux pump inhibiting effects than reference verapamil and were significantly safer than doxorubicin in cell-based toxicity assays in the HEK-293 cell line. Results of mechanistic studies indicate that active imidazolones are substrates with increasing Pgp ATPase activity, and their dye-efflux inhibition via competitive action on the Pgp verapamil binding site was predicted in silico.

Role of P-glycoprotein in the brain disposition of seletalisib: Evaluation of the potential for drug-drug interactions

Seletalisib is an orally bioavailable selective inhibitor of phosphoinositide 3-kinase delta (PI3Kδ) in clinical development for the treatment of immune-mediated inflammatory diseases. The present study investigated the role of P-gp in seletalisib disposition, especially brain distribution, and the associated risks of interactions. Seletalisib was found to be actively transported by rodent and human P-gp in vitro (transfected LLC-PK1 cells; K_m of ca. 20 µM), with minimal or no affinity for the other tested transporters. A distribution study in knockout rats (single oral dosing at 750 mg kg^-1) showed that P-gp restricts the brain disposition of seletalisib while having minimal effect on its intestinal absorption. Restricted brain penetration was also observed in cynomolgus monkeys (single oral dosing at 30 mg kg^-1) using brain microdialysis and cerebrospinal fluid sampling (K_p,uu of 0.09 and 0.24, respectively). These findings opened the question of potential pharmacokinetic interaction between seletalisib and P-gp inhibitors. In vitro, CsA inhibited the active transport of seletalisib with an IC₅₀ of 0.13 µM. In rats, co-administration of high doses of CsA (bolus iv followed by continuous infusion) increased the brain distribution of seletalisib (single oral dosing at 5 mg kg^-1). The observed data were found aligned with those predicted by in vitro-in vivo extrapolation. Based on the same extrapolation method combined with literature data, only very few P-gp inhibitors (i.e. CsA, quinine, quinidine) were predicted to increase the brain disposition of seletalisib in the clinical setting (maximal 3-fold changes).

Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery

With the continuous development in software, algorithms, and increase in computer speed, the field of computer-aided drug design has been witnessing reduction in the time and cost of the drug designing process. Structure based drug design (SBDD), which is based on the 3D structure of the enzyme, is helping in proposing novel inhibitors. Although a number of crystal structures are available in various repositories, there are various proteins whose experimental crystallization is difficult. In such cases, homology modeling, along with the combined application of MD and docking, helps in establishing a reliable 3D structure that can be used for SBDD. In this review, we have reported recent works, which have employed these three techniques for generating structures and further proposing novel inhibitors, for cytoplasmic proteins, membrane proteins, and metal containing proteins. Also, we have discussed these techniques in brief in terms of the theory involved and the various software employed. Hence, this review can give a brief idea about using these tools specifically for a particular problem.

Computational approaches in cancer multidrug resistance research: Identification of potential biomarkers, drug targets and drug-target interactions

Like physics in the 19th century, biology and molecular biology in particular, has been fertilized and enhanced like few other scientific fields, by the incorporation of mathematical methods. In the last decades, a whole new scientific field, bioinformatics, has developed with an output of over 30,000 papers a year (Pubmed search using the keyword "bioinformatics"). Huge databases of mass throughput data have been established, with ArrayExpress alone containing more than 2.7 million assays (October 2019). Computational methods have become indispensable tools in molecular biology, particularly in one of the most challenging areas of cancer research, multidrug resistance (MDR). However, confronted with a plethora of different algorithms, approaches, and methods, the average researcher faces key questions: Which methods do exist? Which methods can be used to tackle the aims of a given study? Or, more generally, how do I use computational biology/bioinformatics to bolster my research? The current review is aimed at providing guidance to existing methods with relevance to MDR research. In particular, we provide an overview on: a) the identification of potential biomarkers using expression data; b) the prediction of treatment response by machine learning methods; c) the employment of network approaches to identify gene/protein regulatory networks and potential key players; d) the identification of drug-target interactions; e) the use of bipartite networks to identify multidrug targets; f) the identification of cellular subpopulations with the MDR phenotype; and, finally, g) the use of molecular modeling methods to guide and enhance drug discovery. This review shall serve as a guide through some of the basic concepts useful in MDR research. It shall give the reader some ideas about the possibilities in MDR research by using computational tools, and, finally, it shall provide a short overview of relevant literature.

Discovery of a non-toxic [1,2,4]triazolo[1,5-a]pyrimidin-7-one (WS-10) that modulates ABCB1-mediated multidrug resistance (MDR)

Multidrug resistance (MDR) has been shown to reduce the effectiveness of chemotherapy. Strategies to overcoming MDR have been widely explored in the last decades, leading to a generation of numerous small molecules targeting ABC and MRP transporters. Among the ABC family, ABCB1 plays key roles in the development of drug resistance and is the most well studied. In this work, we report the discovery of non-toxic [1,2,4]triazolo[1,5-a]pyrimidin-7-one (WS-10) from our structurally diverse in-house compound collection that selectively modulates ABCB1-mediated multidrug resistance. WS-10 enhanced the intracellular accumulation of paclitaxel in SW620/Ad300 cells, but did not affect the expression of ABCB1 Protein and ABCB1 localization. The cellular thermal shift assay (CETSA) showed that WS-10 was able to bind to ABCB1, which could be responsible for the reversal effect of WS-10 toward paclitaxel and doxorubicin in SW620/Ad300 cells. Docking simulations were performed to show the possible binding modes of WS-10 within ABCB1 transporter. To conclude, WS-10 could be used as a template for designing new ABCB1 modulators to overcome ABCB1-mediated multidrug resistance.

Structural and functional aspects of P-glycoprotein and its inhibitors

P-glycoprotein (P-gp) is a member of ATP-binding cassette (ABC) superfamily which extrudes chemotherapeutic agents out of the cell. Suppression of this efflux activity has been the subject of numerous attempts to develop P-gp inhibitors. The aim of this review is to present up-to-date information on the structural and functional aspects of P-gp and its known inhibitors. The data presented also provide some information on drug discovery approaches for candidate P-gp inhibitors. Nucleotide-binding domains (NBDs) and drug-binding domains (DBDs) have been extensively studied to gain more information about P-gp inhibition and it looks that the ATPase activity of this pump has been the most attractive target for designing inhibitors. Hydrophobic and π-π (aromatic) interactions between P-gp binding domains and inhibitors are dominant intermolecular forces that have been reported in many studies using different methods. Many synthetic and natural products have been found to possess inhibitory or modulatory effects on drug transporter proteins. Log P value is an important factor in studying these inhibitors and has a crucial role on absorption, distribution, metabolism, and excretion (ADME) properties of candidate P-gp inhibitors.

Exploring movement and energy in human P-glycoprotein conformational rearrangement

Human P-glycoprotein (P-gp), a kind of ATP-Binding Cassette transporter, can export a diverse variety of anti-cancer drugs out of the tumor cell. Its overexpression is one of the main reasons for the multidrug resistance (MDR) of tumor cells. It has been confirmed that during the substrate transport process, P-gp experiences a large-scale structural rearrangement from the inward- to outward-facing states. However, the mechanism of how the nucleotide-binding domains (NBDs) control the transmembrane domains (TMDs) to open towards the periplasm in the outward-facing state has not yet been fully characterized. Herein, targeted molecular dynamics simulations were performed to explore the conformational rearrangement of human P-gp. The results show that the allosteric process proceeds in a coupled way, and first the transition is driven by the NBDs, and then transmitted to the cytoplasmic parts of TMDs, finally to the periplasmic parts. The trajectories show that besides the translational motions, the NBDs undergo a rotation movement, which mainly occurs in xy plane and ensures the formation of the correct ATP-binding pockets. The analyses on the interaction energies between the six structure segments (cICLs) from the TMDs and NBDs reveal that their subtle energy differences play an important role in causing the periplasmic parts of the transmembrane helices to separate from each other in the established directions and in appropriate amplitudes. This conclusion can explain the two experimental phenomena about human P-gp in some extent. These studies have provided a detailed exploration into human P-gp rearrangement process and given an energy insight into the TMD reorientation during P-gp transition.

The reliability of molecular dynamics simulations of the multidrug transporter P-glycoprotein in a membrane environment

Despite decades of research, the mechanism of action of the ABC multidrug transporter P-glycoprotein (P-gp) remains elusive. Due to experimental limitations, many researchers have turned to molecular dynamics simulation studies in order to investigate different aspects of P-gp function. However, such studies are challenging and caution is required when interpreting the results. P-gp is highly flexible and the time scale on which it can be simulated is limited. There is also uncertainty regarding the accuracy of the various crystal structures available, let alone the structure of the protein in a physiologically relevant environment. In this study, three alternative structural models of mouse P-gp (3G5U, 4KSB, 4M1M), all resolved to 3.8 Å, were used to initiate sets of simulations of P-gp in a membrane environment in order to determine: a) the sensitivity of the results to differences in the starting configuration; and b) the extent to which converged results could be expected on the times scales commonly simulated for this system. The simulations suggest that the arrangement of the nucleotide binding domains (NBDs) observed in the crystal structures is not stable in a membrane environment. In all simulations, the NBDs rapidly associated (within 10 ns) and changes within the transmembrane helices were observed. The secondary structure within the transmembrane domain was best preserved in the 4M1M model under the simulation conditions used. However, the extent to which replicate simulations diverged on a 100 to 200 ns timescale meant that it was not possible to draw definitive conclusions as to which structure overall was most stable, or to obtain converged and reliable results for any of the properties examined. The work brings into question the reliability of conclusions made in regard to the nature of specific interactions inferred from previous simulation studies on this system involving similar sampling times. It also highlights the need to demonstrate the statistical significance of any results obtained in simulations of large flexible proteins, especially where the initial structure is uncertain.

Targeting P-glycoprotein: Investigation of piperine analogs for overcoming drug resistance in cancer

P-glycoprotein (P-gp) is a drug transporter that effluxes chemotherapeutic drugs and is implicated in the development of resistance of cancer cells to chemotherapeutic drugs. To date, no drug has been approved to inhibit P-gp and restore chemotherapy efficacy. Moreover, majority of the reported inhibitors have high molecular weight and complex structures, making it difficult to understand the basic structural requirement for P-gp inhibition. In this study, two structurally simple, low molecular weight piperine analogs Pip1 and Pip2 were designed and found to better interact with P-gp than piperine in silico. A one step, acid-amine coupling reaction between piperic acid and 6,7-dimethoxytetrahydroisoquinoline or 2-(3,4-dimethoxyphenyl)ethylamine afforded Pip1 and Pip2, respectively. In vitro testing in drug resistant P-gp overexpressing KB (cervical) and SW480 (colon) cancer cells showed that both analogs, when co-administered with vincristine, colchicine or paclitaxel were able to reverse the resistance. Moreover, accumulation of P-gp substrate (rhodamine 123) in the resistant cells, a result of alteration of the P-gp efflux, was also observed. These investigations suggest that the natural product analog - Pip1 ((2E,4E)-5-(benzo[d][1,3]dioxol-5-yl)-1-(6,7-dimethoxy-3,4-dihydroisoquinolin-2(1 H)-yl)penta-2,4-dien-1-one) - is superior to piperine and could inhibit P-gp function. Further studies are required to explore the full potential of Pip1 in treating drug resistant cancer.

A significant mechanism of molecular recognition between bioflavonoids and P-glycoprotein leading to herb-drug interactions

Inhibition of P-glycoprotein (P-gp)'s function may conduct significant changes in the prescription drugs' pharmacokinetic profiles and escalate potential risks in taking place of drug/herb-drug interactions. Computational modeling was advanced to scrutinize some bioflavonoids which play roles in herb-drug interactions as P-gp inhibitors utilizing molecular docking and pharmacophore analyses. Twenty-five flavonoids were utilized as ligands for the modeling. The mouse P-gp (code: 4Q9H) was acquired from the PDB. The docking was operated utilizing AutoDock version 4.2.6 (Scripps Research Institute, La Jolla, CA) against the NBD2 of 4Q9H. The result illustrated the high correlation between the docking scores and observed activities of the flavonoids and the putative binding site of these flavonoids was proposed and compared with the site for ATP. To evaluate hotspot amino acid residues within the NBD2, Binding modes for the ligands were achieved using LigandScout to originate the NBD2-flavonoid pharmacophore models. The results asserted that these inhibitors competed with ATP for binding site in the NBD2 (as competitive inhibitors) including the hotspot residues which associated with electrostatic and van der Waals interactions with the flavonoids. In MD simulation of eight delegated complexes selected from the analyzed flavonoid subclasses, RMSD analysis of the trajectories indicated the residues were stable throughout the duration of simulations.

Insight into the molecular mechanism of P-glycoprotein mediated drug toxicity induced by bioflavonoids: an integrated computational approach

In this work, molecular docking, pharmacophore modeling and molecular dynamics (MD) simulation were rendered for the mouse P-glycoprotein (P-gp) (code: 4Q9H) and bioflavonoids; amorphigenin, chrysin, epigallocatechin, formononetin and rotenone including a positive control; verapamil to identify protein-ligand interaction features including binding affinities, interaction characteristics, hot-spot amino acid residues and complex stabilities. These flavonoids occupied the same binding site with high binding affinities and shared the same key residues for their binding interactions and the binding region of the flavonoids was revealed that overlapped the ATP binding region with hydrophobic and hydrophilic interactions suggesting a competitive inhibition mechanism of the compounds. Root mean square deviations (RMSDs) analysis of MD trajectories of the protein-ligand complexes and NBD2 residues, and ligands pointed out these residues were stable throughout the duration of MD simulations. Thus, the applied preliminary structure-based molecular modeling approach of interactions between NBD2 and flavonoids may be gainful to realize the intimate inhibition mechanism of P-gp at NBD2 level and on the basis of the obtained data, it can be concluded that these bioflavonoids have the potential to cause herb-drug interactions or be used as lead molecules for the inhibition of P-gp (as anti-multidrug resistance agents) via the NBD2 blocking mechanism in future.

Large-scale classification of P-glycoprotein inhibitors using SMILES-based descriptors

P-glycoprotein (Pgp) inhibition has been considered as an effective strategy towards combating multidrug-resistant cancers. Owing to the substrate promiscuity of Pgp, the classification of its interacting ligands is not an easy task and is an ongoing issue of debate. Chemical structures can be represented by the simplified molecular input line entry system (SMILES) in the form of linear string of symbols. In this study, the SMILES notations of 2254 Pgp inhibitors including 1341 active, and 913 inactive compounds were used for the construction of a SMILE-based classification model using CORrelation And Logic (CORAL) software. The model provided an acceptable predictive performance as observed from statistical parameters consisting of accuracy, sensitivity and specificity that afforded values greater than 70% and MCC value greater than 0.6 for training, calibration and validation sets. In addition, the CORAL method highlighted chemical features that may contribute to increased and decreased Pgp inhibitory activities. This study highlights the potential of CORAL software for rapid screening of prospective compounds from a large chemical space and provides information that could aid in the design and development of potential Pgp inhibitors.

Homology modelling of human P-glycoprotein

P-glycoprotein (P-gp) is an ATP-binding cassette transporter that exports a huge range of compounds out of cells and is thus one of the key proteins in conferring multi-drug resistance in cancer. Understanding how it achieves such a broad specificity and the series of conformational changes that allow export to occur form major, on-going, research objectives around the world. Much of our knowledge to date has been derived from mutagenesis and assay data. However, in recent years, there has also been great progress in structural biology and although the structure of human P-gp has not yet been solved, there are now a handful of related structures on which homology models can be built to aid in the interpretation of the vast amount of experimental data that currently exists. Many models for P-gp have been built with this aim, but the situation is complicated by the apparent flexibility of the system and by the fact that although many potential templates exist, there is large variation in the conformational state in which they have been crystallized. In this review, we summarize how homology modelling has been used in the past, how models are typically selected and finally illustrate how MD simulations can be used as a means to give more confidence about models that have been generated via this approach.

Structural and dynamic perspectives on the promiscuous transport activity of P-glycoprotein

The multidrug transporter P-glycoprotein (P-gp) is expressed in the blood-brain barrier endothelium where it effluxes a range of drug substrates, preventing their accumulation within the brain. P-gp has been studied extensively for 40 years because of its crucial role in the absorption, distribution, metabolism and elimination of a range of pharmaceutical compounds. Despite this, many aspects of the structure-function mechanism of P-gp are unresolved. Here we review the emerging role of molecular dynamics simulation techniques in our understanding of the membrane-embedded conformation of P-gp. We discuss its conformational plasticity in the presence and absence of ATP, and recent efforts to characterize the drug binding sites and uptake pathways.

Toward Understanding the Catalytic Mechanism of Human Paraoxonase 1: Site-Specific Mutagenesis at Position 192

Human paraoxonase 1 (h-PON1) is a serum enzyme that can hydrolyze a variety of substrates. The enzyme exhibits anti-inflammatory, anti-oxidative, anti-atherogenic, anti-diabetic, anti-microbial and organophosphate-hydrolyzing activities. Thus, h-PON1 is a strong candidate for the development of therapeutic intervention against a variety conditions in human. However, the crystal structure of h-PON1 is not solved and the molecular details of how the enzyme hydrolyzes different substrates are not clear yet. Understanding the catalytic mechanism(s) of h-PON1 is important in developing the enzyme for therapeutic use. Literature suggests that R/Q polymorphism at position 192 in h-PON1 dramatically modulates the substrate specificity of the enzyme. In order to understand the role of the amino acid residue at position 192 of h-PON1 in its various hydrolytic activities, site-specific mutagenesis at position 192 was done in this study. The mutant enzymes were produced using Escherichia coli expression system and their hydrolytic activities were compared against a panel of substrates. Molecular dynamics simulation studies were employed on selected recombinant h-PON1 (rh-PON1) mutants to understand the effect of amino acid substitutions at position 192 on the structural features of the active site of the enzyme. Our results suggest that, depending on the type of substrate, presence of a particular amino acid residue at position 192 differentially alters the micro-environment of the active site of the enzyme resulting in the engagement of different subsets of amino acid residues in the binding and the processing of substrates. The result advances our understanding of the catalytic mechanism of h-PON1.

Ligand-based modeling of diverse aryalkylamines yields new potent P-glycoprotein inhibitors

The P-glycoprotein (P-gp) efflux pump has an important role as a natural detoxification system in many types of normal and cancer cells. P-gp is implicated in multiple drug resistance (MDR) exhibited by several types of cancer against a multitude of anticancer chemotherapeutic agents, and therefore, it is clinically validated target for cancer therapy. Accordingly, in this study we combined exhaustive pharmacophore modeling and quantitative structure-activity relationship (QSAR) analysis to explore the structural requirements for potent P-gp inhibitors employing 130 known P-gp ligands. Genetic function algorithm (GFA) coupled with k nearest neighbor (kNN) or 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 new promising P-gp inhibitory leads retrieved from the National Cancer Institute (NCI) structural database. Several potent hits were captured. The most potent hit decreased the IC50 of doxorubicin from 0.906 to 0.190 μM on doxorubicin resistant MCF7 cell-line.