Accepted Manuscript

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

Nandhitha Subramanian, Karmen Condic-Jurkic, Megan L. O'Mara

PII: S0197-0186(16)30088-2

DOI: 10.1016/j.neuint.2016.05.005

Reference: NCI 3869

To appear in: Neurochemistry International

Received Date: 18 November 2015

Revised Date: 28 April 2016

Accepted Date: 3 May 2016

Please cite this article as: Subramanian, N., Condic-Jurkic, K., O'Mara, M.L., Structural and dynamicperspectives on the promiscuous transport activity of P-glycoprotein, Neurochemistry International(2016), doi: 10.1016/j.neuint.2016.05.005.

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Structural and dynamic perspectives on the promiscuous

transport activity of P-glycoprotein

Nandhitha Subramanian1, Karmen Condic-Jurkic2, Megan L. O’Mara1,*

1Research School of Chemistry (RSC), The Australian National University, Canberra, ACT, 2601,

Australia

2School of Chemistry and Molecular Biosciences (SCMB), University of Queensland, Brisbane,

QLD, 4072, Australia

Corresponding author

* Correspondence to: Dr. Megan L. O’Mara

E-mail: megan.o'mara@anu.edu.au

Phone: +61 2 6125 3739

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Abstract

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.

Keywords

P-glycoprotein; ABC (ATP-binding cassette) transporter; molecular dynamics simulation; substrate

transport; multidrug transporter

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1. Introduction

The ABC (ATP-binding cassette) transporter P-glycoprotein (P-gp or ABCB1) is a

gatekeeper of the blood-brain barrier (BBB). P-gp is expressed in the luminal plasma membrane of

capillary endothelial cells, as illustrated in Figure 1, and is also expressed in the apical membranes

of barrier tissues across the body. P-gp transports more than 200 chemically diverse substrate

molecules, including therapeutic drugs, steroid hormones and signaling molecules. P-gp plays a

major role in the absorbance, distribution, metabolism and excretion (ADME) of these substrates,

both throughout the body and within the central nervous system. This key role of P-gp in central

nervous system ADME has been exploited extensively in drug development to minimize the off-

target effects. For example, previous studies have demonstrated reduced CNS effects in

antihistamines (Polli et al., 2003) and opioid (Mercer and Coop, 2011) that are P-gp substrates,

compared to structurally related non-substrates.

The expression and activity of P-gp is particularly important in the chemotherapeutic

intervention of primary and secondary brain tumors, where P-gp expressed in the BBB actively

effluxes cancer chemotherapeutics, preventing their uptake and accumulation in the brain (Schinkel,

1999). Other P-gp substrates include benzodiazapines, antiepileptics, antidepressants, ion channel

blockers, dopamine receptor agonists and antipsychotics drugs. As well as the staggering array of

substrates transported by P-gp, a complex spectrum of interactions exists, with competitive and

non-competitive substrate interactions identified, in addition to modulators and inhibitors of P-gp.

More recently, P-gp has been implicated in the efflux of the amyloidogenic Aβ peptide from the

neuronal endothelium into the bloodstream (Abuznait et al., 2011; Park et al., 2014).

Due to its key role in ADME, P-gp has been extensively studied and is the most

comprehensively characterized ABC transporter. While the general transport mechanism is known,

many atomic details of the transport process are still unresolved. These atomic details are crucial for

the understanding of substrate transport, or the development of specific inhibitors targeting P-gp or

other ABC transporters.

P-gp exhibits a typical ABC exporter architecture of two transmembrane domains (TMDs)

and two cytosolic nucleotide-binding domains (NBDs). Two molecules of ATP can bind between

the NBDs at their specific binding sites and the efflux of substrate through the TMD is coupled to

the binding and hydrolysis of ATP in the NBDs. Crystallographic data from P-gp and other ABC

exporters have revealed a spectrum of different conformations these proteins can adopt in varying

crystallization conditions, such as different detergents, presence and absence of nucleotides and

transport substrates, etc. The first structure of murine P-gp (PDBid: 3G5U) is a prototypical

conformation of ABC exporter representing the inward-open state (Aller et al., 2009). This state is

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suggested to be the initial state of the protein, in which the TMD substrate translocation pore

accessible from the cytosol in the absence of nucleotide, or when each ATP molecule interacts with

a single NBD, as observed in bacterial transporter TM287/288 (PDBid: 3QF4) (Hohl et al., 2012).

The representing conformation of the final, outward-open state of the P-gp transport cycle is linked

to the crystal structures of bacterial transporters Sav1866 (PDBid: 2HYD) (Dawson and Locher,

2006) or MsbA (PDBid: 3B60) (Ward et al., 2007). The outward-open conformation is

characterized by NBDs forming a sandwich dimer in presence of ATP analogues and opening of

TMD to the extracellular side to allow substrate release. The suggested transport mechanism for

ABC exporters, including P-gp, involves a series of conformational changes of protein between

these two extreme conformations, shown in Figure 2. The conformational diversity of ABC

exporters is captured in a number of crystal structures that correspond to the putative intermediary

states, including the occluded conformations (PDBid: 4AYT, 4PL0) presented in Figure 2

(Choudhury et al., 2014; Shintre et al., 2013). The conformational change in the TMDs during

transport is believed to be driven by NBD dimerization and ATP hydrolysis, allowing the efflux of

substrate. The protein returns to the initial state upon the release of hydrolysis products, ADP and Pi.

At present, the uncertainties of the currently proposed mechanism of P-gp transport include how

ATP binding and hydrolysis occurs, how it facilitates substrate transport, and the location of the

substrate binding sites (Jones and George, 2012). In addition, an increasing body of evidence

suggests that a key characteristic of ABC transporters is their ability to adopt a wide range of

conformations (Aller et al., 2009; Dawson and Locher, 2006; Hohl et al., 2012; Li et al., 2014;

Lugo and Sharom, 2005; van Wonderen et al., 2014; Wen et al., 2013). There is also an increasing

concern regarding the biological relevance of many of these crystal structure conformations.

Recently, it has been suggested that the choice of detergents used in the crystallization procedure

plays a very important role in conformational selection (Beck et al., 2013; Perez et al., 2015).

However, it is clear that ABC exporters possess an intrinsic flexibility, which may play an

important role in the transport mechanism and contribute to the promiscuity displayed by P-gp.

Molecular dynamics simulations allow investigation of P-gp embedded in the lipid bilayer, closely

mimicking the native environment. Here we will review recent insights into P-gp conformational

dynamics and substrate binding, derived from molecular dynamics simulation techniques.

2. Molecular dynamics as an investigative tool

Techniques such as molecular dynamics (MD) simulations are an attractive way to study the

motion of a single molecule in atomic detail in a time-dependent fashion. MD can be viewed as a

“computational microscope for molecular biology” (Dror et al., 2011). In MD simulations, a

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potential energy term, or force field, similar to those used in NMR and X-ray structure refinement,

is used to describe the potential energy of the system. Newton’s equations of motion are solved

classically for each atom in the simulation to propagate their motion in space and time. The protein

structural models derived from crystallographic and NMR data, or more recently from cryo-EM, are

usually used as starting points for these calculations, as they provide the information about atomic

positions required for further calculations. The MD trajectories generated contain vast amount of

information that can be used to evaluate various properties of interest, ranging from coupled domain

motions and signal transduction to the energetics and dynamic of ligand binding.

The rapid growth in computational power, combined with improvements in algorithms and

force fields, have enabled the simulation of increasingly larger systems at longer timescales.

However, the routinely available timescales (ns to µs) still present the bottleneck in biomolecular

simulations, as many biological processes occur at much longer timescales (µs to seconds).

Generating sufficient statistics to appropriately describe those processes remains challenging (van

Gunsteren et al., 2006) even for the most powerful computational facilities, such as purpose-built

hardware like Anton (Shaw et al., 2009) or high-end graphic processing units (GPUs) (Salomon-

Ferrer et al., 2013). Enhanced or biased sampling techniques such as umbrella sampling or replica

exchange present an alternative approach to sampling rare events such as transition states in the

transport cycle, or calculating the minimum energy pathway for substrate uptake and binding.

Enhanced sampling of these states can then be used as a starting point for non-biased simulations

examining the spontaneous atomic interactions occurring during these rare events.

3. Examining the physiological conformation of P-gp using MD simulations

The availability of a high-resolution structural model is crucial for understanding relevant

protein interactions using MD simulation techniques. There are currently >50 structures of murine

P-gp and homologous ABC exporters, solved in isolation or in complex with ATP analogues, cyclic

inhibitors or nanobodies. Collectively, these structures illustrate a wide spectrum of conformations,

shown in Figure 2 (cyan and purple) (Aller et al., 2009; Dawson and Locher, 2006; Hohl et al.,

2012; Shintre et al., 2013) that can be broadly grouped into either outward-facing or inward-facing

conformations described above. In particular, the inward-facing structures (Figure 2, PDBid: 3G5U,

3QF4, 4YAT) show a spectrum of conformations in which the NBDs may be partially contacting or

separated by distances of >30 Å. These dramatically different conformations may originate from the

intrinsic conformational flexibility of these transporters, also potentially reflected in the medium

resolution quality of the crystal structures (3 – 4 Å). However, the change in the environment

imposed by the crystallization conditions could also give rise to conformations that might not be

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accessible under physiological conditions. The physiological relevance of these structures has

particular implications for our understanding of the spectrum of conformations a protein can adopt

in its native state, and how protein dynamics modulates function. That is why it is important to

assess whether the diversity of crystallographic conformations are retained in a membrane

environment, and whether transitions between the crystallographic conformations are possible in

the native environment. MD simulation techniques present an appropriate tool to study protein

dynamics.

MD simulations that closely replicate the crystallographic milieu showed that the splayed

crystallographic conformation of murine P-gp, solved first in 2009 (Figure 2, PDBid: 3G5U), is

maintained in the presence of detergent, which bound to the TMDs and aggregated between the

widely separated NBDs (O'Mara and Mark, 2012). In contrast, MD simulations of membrane-

embedded P-gp demonstrated that the conformation of P-gp is acutely sensitive to the lipid

composition of the membrane. Here, simulations of P-gp embedded into pure DMPC (Ferreira et al.,

2012) or POPC membranes showed tilting and structural deformations of P-gp, attributed to a

mismatch between the hydrophobic belt of the protein and the thickness of the membrane (Ferreira

et al., 2012). Experimentally, the ATPase activity of reconstituted P-gp is known to be highly

dependent on both the phospholipid and cholesterol composition of the membrane (Modok et al.,

2004).

When P-gp is incorporated in an appropriate membrane environment, MD simulations have

consistently shown that its conformation diverges from that of the crystal structures.

Conformational changes commonly reported in MD studies involve the inwards pivot of the NBDs

pivot, allowing the formation a contact interface at their cytoplasmic base (Ferreira et al., 2012; Ma

and Biggin, 2013; O'Mara and Mark, 2012). Intriguingly, all MD studies of membrane-embedded

P-gp (PDBid: 3G5U) have documented relatively large backbone fluctuations, including kinking,

bending and/or unfolding of localized regions of the transmembrane helices (Ferreira et al., 2012;

Ma and Biggin, 2013; O'Mara and Mark, 2012; Wen et al., 2013) suggesting a high degree of

conformational plasticity that is alluded to by the diversity of ABC transporter crystallographic

structures observed. The helical flexibility has been attributed to the high proportion of glycine and

proline residues in transmembrane helices (O’Mara and Mark, 2014; Wen et al., 2013). This TMD

flexibility, combined with various orientations of NBDs, enables P-gp to undergo dynamic

transitions through a spectrum of closely related conformations. These MD conformations provide a

better estimate of the structural plasticity observed by distance measurements in biophysical and

biochemical studies than the corresponding distances in the widely splayed P-gp crystal structures

(O'Mara and Mark, 2012; van Wonderen et al., 2014; Wen et al., 2013). Subsequent re-

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crystallization (Ward et al., 2013) and re-refinement the original P-gp dataset (Li et al., 2014) have

indicated that residues within several of the TM helices from the original P-gp structure (PDBid:

3G5U) were incorrectly assigned, resulting in register shifts that affect their relative position and

orientation. While the assignment of residues in the more recent P-gp structures (PDBid: 4KSB,

4M1M) (Li et al., 2014; Ward et al., 2013) differ to that of the original (Aller et al., 2009), they also

differ to each other, leaving ambiguities regarding which structure best represents the correct

residue assignment (O’Mara and Mark, 2014; Subramanian et al., 2015). However, the major

obstacle in resolving this problem comes from the relatively low resolution of these crystal

structures (3.8 Å), which makes it difficult to assign the position of residues unambiguously.

Comparative simulations carried out using the original and more recent mouse P-gp crystal

structures, suggests underlying differences TMD stability associated with these register shifts.

However, the observed intrinsic flexibility in all systems makes it difficult to attribute the origin of

the observed structural changes without ambiguity (Condic-Jurkic et al., unpublished results). This

further demonstrates that the inherent flexibility of P-gp, which we postulate, may have broader

implications for other ABC exporters.

4. ATP binding and hydrolysis

P-gp requires ATP binding to drive the conformational changes that facilitate membrane

transport. Each NBD contains two ATP binding sites that become catalytically active upon

dimerization of NBDs. The accepted hypothesis assumes that ATP binding induces NBD

dimerization, which in turn triggers the further conformational changes through TMD that drive the

substrate across the membrane. The release of drug substrate and ADP is assumed to bring the

protein back to the initial conformation and close the transport cycle. However, details such as the

stoichiometry of the ATP molecules, binding site occupancy, the sequence of hydrolysis and

product release, and the conformational coupling mechanism between transport and ATP hydrolysis

remain unresolved.

Considering the observed flexibility of apo P-gp, we have investigated influence of ATP

binding on the conformation of membrane-embedded P-gp. Our simulations show that NBDs

pivoted inwards to form loose complexes, similar to the results obtained for the apo form. However,

the NBDs did not fully dimerize in the simulations timeframe. In half the simulations, a metastable

partial (asymmetric) dimerized conformation was observed (O’Mara and Mark, 2014). In this

conformation, one ATP site formed an occluded nucleotide-sandwich dimer primed to ATP

hydrolysis, while the other to partially open and available for ATP exchange (O’Mara and Mark,

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2014). In a separate study, Watanabe et al. observed an asymmetric closure of the NBDs in the

presence of ATP during 100 ns of MD simulations, with or without the transport substrate

verapamil in the TM pore (Watanabe et al., 2013). They did not observe partial or complete NBD

dimerization during their simulations, either with or without verapamil in the TM pore (Watanabe et

al., 2013), indicating that the structural rearrangements involved in ATP binding and substrate

transport are slow processes, which occur on timescales >100 ns. Furthermore, the spontaneous

asymmetric association of the NBDs in the presence of ATP observed in both studies may provide

an explanation for the residual ATPase activity of P-gp in the absence of drug substrates. Further

studies involving both ATP and drugs are required to address the question of transport mechanism

in P-gp.

5. Characterizing the P-gp drug binding sites

To date, the location of any high-affinity substrate binding site has not been conclusively

resolved. Extensive mutagenesis studies have been performed on P-gp, characterizing the relative

contribution of almost every residue in the protein on substrate binding and transport. Through a

cysteine, alanine or arginine mutagenesis approach, these studies identified clusters of residues

dispersed throughout the TMDs, NBDs and the connecting intracellular loops implicated in the

binding and/or transport of different P-gp substrates. Several studies found that the same residues

were implicated in binding and/or transport of non-competitive substrates (Loo et al., 2006a, b; Loo

and Clarke, 1997). For example, mutational analysis indicates that residues H61, L65, A947, F728

and Q946 are all implicated in the binding of the non-competitive substrates colchicine and

verapamil to human P-gp, while F770, M986 and A987 are implicated in the binding of rhodamine

and colchicine, which also bind to human P-gp in a non-competitive manner. Table 1 gives a

comprehensive list of the residues implicated experimentally in the binding and transport of

verapamil, colchicine, rhodamine and vinblastine. Overall, the spatial proximity of these residues

suggests that the binding locations for these substrates may not be truly distinct. When taken

together, these biochemical investigations suggest that P-gp contains a large, non-specific binding

pocket (Loo and Clarke, 2008; Pleban et al., 2005).

In contrast, pharmacological studies examining the competitive and non-competitive nature

of P-gp substrate have suggested that P-gp contains multiple substrate binding sites that are specific

for particular substrate classes. For example, three pharmacological binding sites have been

proposed based on competitive binding of different substrates at a common site: the H (Hoechst)

site (Shapiro et al., 1999; Shapiro and Ling, 1997); the R (Rhodamine) site (Shapiro and Ling,

1997); and the vinblastine site (Callaghan and Riordan, 1993; Pascaud et al., 1998; Safa, 2004).

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Equilibrium binding studies indicate that vinblastine binds in a non-competitive fashion in presence

of a number of other P-gp substrates, suggesting additional pharmacological binding sites (Martin et

al., 2000). As described by Subramanian et al., mapping the residues implicated in substrate binding

and transport to the crystal structures of mouse P-gp does not yield clear, well-defined binding

locations for any known P-gp substrate (Subramanian et al., 2015). Figure 3 summarizes the

biochemical and pharmacological studies carried out to understand the substrate binding to P-gp.

The 2009 murine P-gp structure has been used extensively to attempt to computationally

characterize the mechanism of substrate binding and the biochemical composition of the substrate

binding sites with varying levels of success. A range of molecular docking and pharmacophore

mapping studies (e.g., (Chufan et al., 2013; Ferreira et al., 2013; Jara et al., 2013; Klepsch et al.,

2014; Prajapati et al., 2013; Tarcsay and Keseru, 2011)) show varying degrees of correlation

between the predicted binding sites for canonical P-gp substrates and inhibitors. One key limitation

of these docking studies is their heavy reliance on the P-gp crystal structure, which disregards the

conformational flexibility observed in MD simulations and spectroscopic studies (Lugo and Sharom,

2005; van Wonderen et al., 2014; Wen et al., 2013). To address this, a range of MD simulation

techniques have been increasingly used in the efforts to identify the physical location of the P-gp

substrate binding sites and couple protein dynamics to substrate binding and transport. Ferreira et al.

carried out a series of short MD simulations (20-40 ns) in which substrates were placed in three

different locations within the TM pore. They found that in all cases there were substantial

hydrophobic and aromatic interactions with substrate molecules within the TM pore, but no specific

drug binding site or coordinating residues could be identified in the timescale of the simulations

(Ferreira et al., 2012). These results are consistent with other short (20 – 30 ns) MD studies of

substrate (Jagodinsky and Akgun, 2015) or inhibitor binding (Liu et al., 2013), which highlight the

flexibility of the ligands when bound to the P-gp TM pore, and their interaction with a range of

hydrophobic and aromatic amino acids. When considered together, these relatively short

simulations describe a pore that initially binds a wide variety of ligands in a non-specific, poorly

coordinated manner, dominated by hydrophobic interactions. Increases in the timescale of non-

biased simulations on murine P-gp (Ma and Biggin, 2013) and homology models of human P-gp

(Zhang et al., 2014) revealed spontaneous association of substrates with P-gp, and subsequent

dynamic rearrangements in the relative conformation of P-gp, hinting at the coupling mechanism

between substrate uptake and P-gp dynamics. To further investigate the spontaneous binding and

uptake of substrates, Subramanian et al. placed a number of substrate molecules in the aqueous

solution surrounding P-gp. They showed that P-gp substrates bound to electrostatic “hotspots” on

the surface of P-gp. These interactions persisted for the remainder of the simulations (Subramanian

et al., 2015). Here morphine interacted with the NBDs and cytosolic extensions of TM helices 6 and

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7. Nicardipine also interacted with NBD1 and with and the cytosolic extensions of TM helices 2, 3,

4, 10 and 11 and NBD1 (Subramanian et al., 2015). It should be noted that the adsorbed substrates

did not enter the TM pore within the timescale of these simulations, thus the hotspots do not

correspond to the binding residues listed above. Instead, the adsorption of drugs to the surface of P-

gp may present an initial mechanism of interaction with P-gp via the cytosol. Ferreira et al. also

examined the relative free energy of adsorption of a series of substrates to P-gp (Ferreira et al.,

2015a) and found that their adsorption locations corresponded to the electrostatic interaction

hotspots identified by Subramanian et al. (Subramanian et al., 2015). Substrate entry into the TM

pore was not observed (Ferreira et al., 2015a). Taken together, these simulations demonstrate that

timescales of 100 to 200 ns are not sufficient to identify the location of any high-affinity drug

binding sites, or to characterize the spectrum of conformational changes involved in substrate

transport by P-gp.

Enhanced sampling techniques provide a means to address the sampling limitations

identified in these spontaneous binding simulations. Notably, recent studies have used these

approaches to identify energetically favorable pathways for substrate uptake and binding in P-gp.

Many P-gp substrates are believed to partition into the cell membrane, before entering the P-gp TM

pore through one of two lipid accessible TMD portals. To investigate the feasibility of this

mechanism, Ferreira et al. calculated the relative difference in free energy for two substrates along a

pathway extending from the membrane, between the proposed portal helices and into the TM pore.

They found that both substrates experienced a continual downhill energy gradient, suggesting that

this portal is a viable substrate entry point into the pore (Ferreira et al., 2015b). Subramanian et al.

also used enhanced sampling techniques to examine the partitioning of P-gp substrates into a pure

POPC bilayer, or one enriched with 10% cholesterol that more closely mimics a neuronal

endothelial membrane. They found that the presence of 10% cholesterol facilitated partitioning and

diffusion of P-gp substrates across the membrane (Subramanian et al., 2016).

To identify the physical location of the minimum energy substrate binding sites,

Subramanian et al. estimated the free energy profile for the binding of two substrates, morphine and

nicardipine, to P-gp. They showed that both the minimum free energy binding sites and permeation

pathways of morphine and nicardipine were spatially distinct, but involved a set of overlapping

residues, many of which have been identified by mutagenesis studies as key residues implicated in

substrate binding and transport (Subramanian et al., 2015). These results suggest a physical basis

for the interactions of P-gp substrates, and the existence of preferred uptake pathways through P-gp.

However, they also indicate that that, in the case of morphine and nicardipine, the binding sites are

not physically distinct.

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Until recently, the large system size required for MD simulations of P-gp has been a critical

limitation in both non-biased simulations and the use of computationally intensive enhanced

sampling techniques. In recent years, advances in computational hardware and the reconfiguration

of GPUs for scientific programming has greatly enhanced the computational timescales achievable

and decreased the computational cost of such simulations, opening the door to further enhanced

sampling simulations that may help characterize the conformational changes and molecular

interactions governing P-gp function.

6. Conclusion

Molecular dynamics simulation techniques form the basis of the rapidly developing field of

computational structural biology, offering unprecedented insights into membrane protein dynamics

and structure-function relationships at atomic resolution. Here we show the conformational

ensembles generated by MD simulations can shed light on the structural heterogeneity and dynamic

transitions between conformational states that P-gp adopts. When considered together, these

simulations demonstrate that P-gp is a highly flexible protein that adopts a variety of conformations

in response to changes to its environment, such as membrane composition, the presence of

nucleotide, and crystallization conditions. Like all techniques used to study biomolecular systems,

MD simulations are limited to their spatial and temporal resolution. In the case of P-gp, MD

simulations are able to provide a clear link between its crystallographic conformation and the

conformation in a phospholipid membrane. MD simulations performed in the presence of substrates

can provide valuable information on the minimum energy uptake pathways and binding locations of

P-gp substrates, and begin to elucidate the conformational changes induced in P-gp on substrate or

inhibitor binding. Understanding the conformational dynamics and substrate binding sites of P-gp

can help provide a structural framework for our understanding of the biochemistry and physiology

of this key gatekeeper of the blood-brain barrier.

7. Acknowledgements

This work was supported by grants from the Australian Research Council (DP110100327),

the National Health and Medical Research Council (APP1049685) and the Merit Allocation

Scheme on the NCI National Facility at the ANU. MLO holds an ARC DECRA (DE120101550).

The author(s) declare no competing financial interests.

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8. Figure Captions

Figure 1 Schematic diagram of P-glycoprotein in the blood brain barrier. P-glycoprotein (blue

cartoon) is expressed at the luminal plasma membrane of the endothelial cells (pink), where it

effluxes substrates into the capillaries. Endothelial tight junctions (pink) are shown in thick lines.

The basement membrane (including pericytes) is shown in dark grey, while the contacting

astrocytes are in yellow.

Figure 2 Proposed P-glycoprotein (P-gp) transport cycle. a) Schematic representation of the

putative transport cycle and b) crystal structure conformations of different ABC exporters

representing the putative transport cycle intermediates. For both a) and b), clockwise from top left:

the inward-open conformation of P-gp is observed in the absence of ATP (top left, PDBid 3G5U

(Aller et al., 2009)) or semi-occluded with one ATP bound to the NBD (top right, PDBid 3QF4

(Hohl et al., 2012)). The binding of ATP at both ATP binding sites induces the formation of NBD

dimer and occludes the cytosolic entrance of the TM pore, capturing drug substrate in within the

transmembrane cavity in an occluded conformation (right, PDBid 4AYT (Shintre et al., 2013)). The

formation of an ATP sandwich dimer (bottom, PDBid 4PL0 (Choudhury et al., 2014)) facilitates the

hydrolysis of ATP and the extracellular entrance to the TM pore opens to allow the release of

substrate (center left, PDBid 2HYD (Dawson and Locher, 2006)). Dissociation of ADP+Pi from the

NBDs shifts the conformation from outward-open back to the inward-open conformation (top left,

PDBid 3G5U (Aller et al., 2009)) closing the transport cycle. Note that the adjectives inward and

outward refer to the exposure of TMD cavity to the cytosolic or extracellular side, respectively,

where open or occluded describe the position of NBDs.

Figure 3 Overview of the experimental studies and their implications for the nature of the substrate

interactions with P-glycoprotein. A range of pharmacological studies have suggested that P-

glycoprotein contains a number of pharmacologically distinct binding sites, while biochemical

studies suggest the transmembrane pore contains non-specific substrate binding pocket.

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9. Tables

Table 1. Residues within the transmembrane domains (TMDs) of human P-gp implicated in the

experimental binding and transport of substrates.

P-gp Substrates

Substrate Binding

Reference Substrate Transport

Reference

Ver

apam

il

L339 (Loo and Clarke, 2001)

S222 (Loo and Clarke, 2000)

V982 (Loo and Clarke, 1997)

L339, A342, I868, G984

(Loo and Clarke, 2001)

G939, F942, T945, Q946, A947

(Loo and Clarke, 1999)

A985 (Loo and Clarke, 1997)

I306 (Loo et al., 2003) Q132 (Parveen et al., 2011)

F728 (Loo et al., 2006b)

H61, G64, L65 (Loo et al., 2006a)

A302, L339, G872, F942, Q946

(Loo et al., 2009)

V982, S993 (Loo et al., 2009)

Rho

dam

ine

F728 (Loo et al., 2006b) Q773 (Parveen et al., 2011)

F336, F770, F983, M986, A987

(Loo et al., 2009) L339 (Loo et al., 2007)

Q990 (Loo et al., 2009) L65, I340, A841, L975, V982

(Loo and Clarke, 2002)

F343 (Loo et al., 2007)

Y953 (Donmez Cakil et al., 2014)

Vin

blas

tine

A947 (Loo and Clarke, 1999)

S222, G872 (Loo and Clarke, 2000)

I306 (Loo et al., 2003) L339, L975, V982 (Loo and Clarke, 1997)

F728 (Loo et al., 2006b) T945, Y950, Y953 (Loo and Clarke, 1999)

H61, G64 (Loo et al., 2006a) Q132 (Parveen et al., 2011)

L65, T199, I306 (Loo et al., 2007)

Col

chic

ine

Q946 (Loo and Clarke, 1999)

S222 (Loo and Clarke, 2000)

F728 (Loo et al., 2006b) L339, L975, V982 (Loo and Clarke, 1997)

H61, L65 (Loo et al., 2006a)

F770, M986, A987 (Loo et al., 2009)

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10. References

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Highlights

• P-gp effluxes >200 substrates from the blood-brain endothelium

• Highly flexible transporter that adopts a variety of conformations

• Molecular basis for structure-function is still unresolved

• Mechanism of substrate binding and interactions unresolved

• We review the role of MD simulations in our understanding of P-gp