The Molecular Mechanism Underlying Ligand Binding to the

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The Molecular Mechanism Underlying Ligand Binding to the Membrane-Embedded Site of a G-Protein-Coupled Receptor Xiao-Jing Yuan, Stefano Raniolo, Vittorio Limongelli, and Yechun Xu J. Chem. Theory Comput., Just Accepted Manuscript • DOI: 10.1021/acs.jctc.8b00046 • Publication Date (Web): 16 Apr 2018 Downloaded from http://pubs.acs.org on April 21, 2018

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Journal of Chemical Theory and Computation

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The Molecular Mechanism Underlying Ligand

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Binding to the Membrane-Embedded Site of a G-

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Protein-Coupled Receptor

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Xiaojing Yuan†‡, Stefano Raniolo§, Vittorio Limongelli§¶, and Yechun Xu†*

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†CAS Key Laboratory of Receptor Research, Drug Discovery and Design Center, Shanghai

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Institute of Materia Medica, Chinese Academy of Sciences (CAS), Shanghai 201203, China

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‡University of Chinese Academy of Sciences, Beijing 100049, China

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§Faculty of Biomedical Sciences, Institute of Computational Science - Center for Computational

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Medicine in Cardiology, Università della Svizzera Italiana (USI), CH-6900 Lugano, Switzerland

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¶Department of Pharmacy, University of Naples “Federico II”, I-80131 Naples, Italy

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*Corresponding Author, E-mail: [email protected]

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ABSTRACT The crystal structure of P2Y1 receptor (P2Y1R), a class A GPCR, revealed a

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special extra-helical site for its antagonist, BPTU, which locates in between the membrane and

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the protein. However, due to the limitation of crystallization experiments, the membrane was

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mimicked by use of detergents and the information related to the binding of BPTU to the

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receptor in the membrane environment is rather limited. In the present work, we conducted a

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total of ~7.5 µs all-atom simulations in explicit solvent using conventional molecular dynamics

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and multiple enhanced sampling methods, with models of BPTU and a POPC bilayer, both in the

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absence and presence of P2Y1R. Our simulations revealed that BPTU prefers partitioning into

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the interface of polar/lipophilic region of the lipid bilayer before associating with the receptor.

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Then, it interacts with the second extracellular loop of the receptor and reaches the binding site

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through the lipid-receptor interface. In addition, by use of funnel-metadynamics simulations

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which efficiently enhance the sampling of bound and unbound states, we provide a statistically

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accurate description of the underlying binding free energy landscape. The calculated absolute

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ligand-receptor binding affinity is in excellent agreement with the experimental data (∆Gb0_theo =

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-11.5 kcal mol−1, ∆Gb0_exp= -11.7 kcal mol−1). Our study broadens the view of the current

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experimental/theoretical models and our understanding of the protein-ligand recognition

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mechanism in the lipid environment. The strategy used in this work is potentially applicable to

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investigate ligands association/dissociation with other membrane-embedded sites, allowing

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identification of compounds targeting membrane receptors of pharmacological interest.

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INTRODUCTION

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G protein-coupled receptors (GPCRs) constitute the largest and the most important membrane

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protein family, and ~40% of marketed drugs act by binding to GPCRs.1 Despite the structural

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and functional diversity of GPCRs, the ligand binding pockets on the transmembrane region have

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mostly been found inside the helical bundle.2 However, in 2015, the first extra-helical binding

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site was reported for an antagonist of the P2Y1 receptor (P2Y1R), BPTU (Figure 1).3 Soon after


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the discovery of the site in this class A GPCR, such allosteric binding sites outside the helical

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bundles have also been found in class B GPCRs such as the glucagon-like peptide-1 receptor

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(GLP-1R) and the glucagon receptor (GCGR).4-6 The possible universal existence of such a

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binding site among multiple GPCRs makes it intriguing and necessary to study the binding

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mechanism of ligands with these sites. Since they are located in-between receptors and the

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membrane, it is likely that the membrane plays a crucial role in protein-ligand recognition

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processes. However, incompatible with the importance, in crystallization experiments the

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membrane was usually mimicked by various detergents (such as monoolein) which have no ionic

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headgroups, unlike the major component of the natural membranes, phospholipids such as POPC

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lipids (Figure 1). This raises the question if the ligands such as BPTU can still find their ways to

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bind to the extra-helical sites with the same poses as they were in the experimentally determined

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structures, when the lipids of the natural environment are used.

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Moreover, in comparison with the common solvent-exposed sites to which the binding of

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ligands is governed by the desolvation as well as interactions with receptors,7-10 when the

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pockets locate inside the membrane, the ligand binding event could be significantly influenced

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by the lipids and becomes more complicated. Unfortunately, such an important pharmaceutical

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process is poorly understood in the present time. Several models have been proposed to explain

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the membrane related phenomena in drug binding. For instance, a “microkinetic” model suggests

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that the membrane acts as a repository to accumulate drugs around the membrane-embedded

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receptors, while a “reduction in dimensionality” effect presumes that drugs move from 3D

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diffusion in the solvent to 2D diffusion within the plane of the membrane so as to increase the

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drug-receptor collision rate, and the rebinding effect may increase the in vivo duration of the

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drug effect.11-14 In the context of the microkinetic model, the concentration of hydrophobic


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ligands in the membrane solvated layer may be driven up due to their affinity to the membrane,

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with the increase of ligand occupancy in the target compartment. In this way, the experimentally

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measured affinity may be more potent than the “actual” affinity to the receptor. This membrane

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accumulation effect thus could muddy the structure-affinity relationship (SAR) analysis in drug

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design.15 However, these theoretical models are difficult to validate directly with general

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experimental methods. Although the membrane association effect may be mimicked by use of

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the immobilized artificial membrane (IAM) method,16 the experiment was conducted without

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receptors and the direct connection between the membrane effect and the receptor could not be

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established. Apart from the accumulation effect of the membrane, attentions should also be paid

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on more advanced questions as to how the membrane could affect drug’s diffusion and what kind

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of pathway the drug utilizes to associate with its pocket on the receptor.

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Figure 1. Crystal structure of the P2Y1R-BPTU complex, and chemical structures of BPTU,

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monoolein and POPC. The protein is represented by yellow cartoon and transparent molecular

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surface, and BPTU is shown in blue sticks. The grey ovals indicate the upper and lower

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boundary of the membrane.


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Due to the difficulty in measuring ligand binding interactions with membrane proteins by use

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of experimental methods, molecular dynamics (MD) simulations serve as an alternative

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approach. Previously, long-timescale conventional molecular dynamics (CMD) simulations and

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enhanced-sampling techniques have been used to study the binding of ligands to the orthosteric

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pockets of GPCRs,7-8, 17-20 in which the ligands all progressed from the water phase into the

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extracellular crevice within the helical bundles and the lipids did not play fundamental roles in

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the binding process. To date, only few researches have investigated the association of ligands,

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including cholesterol, with GPCRs via the membrane environment.21-26 However, the binding

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sites in these simulations are mostly intra-helical, the intermediate states along the binding path

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could be different from those of the extra-helical sites, and the significant role of the lipids has

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not been clearly characterized yet. A comprehensive interpretation of a ligand binding

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mechanism needs a detailed description of the interplay among water, lipids, the ligand and its

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receptor, and an accurate characterization of the underlying free energy landscape. Noteworthy,

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the access of a ligand to its binding site occurs in the timescale which is usually beyond the

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capability of CMD, more sophisticated techniques are thereby required. Metadynamics is able to

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enhance sampling and reconstruct the free energy surface (FES) afterwards, thus it has been

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widely used in ligand binding studies.8, 18, 27-28 With this method, a history-dependent bias

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potential that acts on a selected number of degrees of freedom, called collective variables (CVs),

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is introduced to discourage the system from revisiting the sampled configurations. The well-

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tempered metadynamics (WT-MetaD) is an evolution of standard metadynamics in which the

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height of the bias potential introduced is decreased with the amount of bias already deposited.

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Consequently, the resulting FES could be limited to the low free energy regions which are

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physically meaningful.29 However, an accurate estimation of the binding affinity needs several


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recrossing events between the bound and unbound states, which remains challenging to WT-

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MetaD simulations due to the large amount of unbound conformations to be sampled. A recently

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developed metadynamics-based approach, called funnel metadynamics (FM), has proven to be

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successful in describing ligand/protein and ligand/DNA binding interactions. FM places a

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funnel-shaped restraining potential on the system so as to enclose the bound states in the cone

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region and restrain the sampling of the solvated states in a cylinder. As such, a number of back-

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and-forth events between the bound and unbound states within an affordable computational time

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become available, which results in a description of a statistically accurate FES and a calculation

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of the accurate binding affinity.30-32

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P2Y1R, a class A GPCR, is activated by ADP to induce platelet activation and is thus a

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promising target for design of novel antithrombotic drugs. BPTU, 1-(2-(2-(tert-butyl)

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phenoxy)pyridin-3-yl)-3-(4-(trifluoromethoxy)phenyl)urea, is a novel antagonist of P2Y1R and

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was once developed for the treatment of thrombosis.33 Due to the unique binding site of BPTU

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and the importance of P2Y1R as a drug target, this system has been recently studied with various

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computational methods. In 2016, a CMD study was done in order to interpret how BPTU acts as

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an antagonist of the receptor.34 Meanwhile, based on the BPTU-P2Y1R structure, Xu et al. used

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the 2D structural similarity search, pharmacophore based screening, and molecular docking to

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identify new antagonists of P2Y1R from Traditional Chinese Medicine (TCM).35 Later,

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Antonella et al. performed molecular docking together with CMD studies on P2Y1R and several

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antagonists, including BPTU, to demystify the P2Y1R-ligand recognition.36 Nevertheless, in

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these studies BPTU are always positioned in the binding site, the comprehensive binding process

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of BPTU from a fully solvated state to its final pose in the crystal structure of the complex has

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not been investigated yet. To clearly reveal the molecular mechanisms underlying the BPTU-


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P2Y1R recognition, fundamental questions such as how BPTU interacts with water/lipids

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molecules before approaching the receptor, how BPTU initially associates with the receptor, how

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BPTU could pave its way to the binding site in the complicated water-lipid environment, how

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BPTU interacts with key residues to lie itself into the pocket with a favorable binding pose, and

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what the exact role of lipids are in the recognition process, must be addressed.

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By combining CMD and multiple enhanced-sampling approaches including umbrella

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sampling, well-tempered metadynamics and funnel-metadynamics simulations, we explored the

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molecular mechanism underlying the binding of this allosteric antagonist to the extra-helical site

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of P2Y1R. Remarkably, We compared the performance of BPTU in the POPC bilayer with or

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without the receptor, and explicitly discussed the role of lipids in the binding pathway. With

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these valuable trajectories, we successfully captured the whole association event and

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characterized the underlying free energy landscape. The current study broadens our

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understanding of the pharmaceutically relevant ligand/receptor recognition process, especially in

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the case of binding between ligands and the lipid-exposed sites of membrane proteins, which

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remains challenging to most experimental techniques.

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METHODS

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Simulations of BPTU trafficking inside the POPC bilayer in the absence of the receptor

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CMD Simulations. The simulation system was built via CHARMM-GUI server by randomly

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placing one BPTU in aqueous solution with a distance of ~30 Å from the ligand to the center of

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the bilayer.37 The simulation box, with a size of ~49 Å × 49 Å × 94 Å, contains 72 POPC

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molecules, 3,875 TIP3P water molecules, and NaCl at a concentration of 0.15 M, resulting in a

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total of 21,292 atoms approximately. The lipids, water molecules and ions were modeled using


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the CHARMM36 force field.38 The parameter of BPTU was assigned with the CHARMM

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General Force Field (CGenFF) by analogy through the ParamChem service (https://cgenff.

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paramchem.org).39 The system was first minimized and equilibrated using GROMACS40 v5.1.2

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in a NPT ensemble at 310 K and 1 bar using the Berendsen coupling, and the harmonic-position

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restraints were applied to the heavy atoms of BPTU and POPC. These restraints were tapered off

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gradually over the equilibration process. Periodic boundary conditions were applied to the

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simulation systems. Bonds containing hydrogen atoms were restrained with the LINCS algorithm

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to allow an integration time step of 2 fs.41 Electrostatic interactions were calculated using the

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particle-mesh Ewald (PME) summation algorithm.42 In the production runs, the Parrinello-

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Rahman coupling and the Nose-Hoover coupling were used to maintain a constant pressure of 1

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bar and a constant temperature of 310 K. Finally, two 500-ns production runs, starting with

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different initial velocities assigned on each atom of the simulation systems, were resulted.

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Potential of Mean Force Simulations. The free energy profile of transferring BPTU from the

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center of the POPC bilayer to the water phase was calculated using the umbrella restraint

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potential of mean force method. Since pulling from membrane center outward has been shown to

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increase convergence of final free energy profile,43 one BPTU molecule was placed at the center

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of the bilayer at the beginning. The size of the box and the following energy minimization and

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equilibration steps are the same as in the CMD simulations, except that the system was

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equilibrated for 5 ns in the NPT ensemble. BPTU was then pulled from z = 0 Å (at the center of

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the bilayer) out to 39 Å (in the bulk water phase) with a pulling rate of 1 Å/ns and a force

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constant of 1000 kJ/mol/nm2. Snapshots were then extracted from the pulling simulation with

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BPTU positioned at z = 0 Å, 1 Å, 2 Å, ..., 39 Å from the bilayer center. Following the

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10ns/window equilibration, 80ns/window production runs were performed with an umbrella


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potential using a force constant of 1000 kJ/mol/nm2 applied to the centroid of the BPTU

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molecule using the pull geometry cylinder method. The free energy profile was then constructed

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using the weighted histogram analysis (WHAM) method implemented in Gromacs 5.1.2 with a

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tolerance of 1 × 10−8.44 The resulted profile was symmetrized and statistical errors were

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estimated using the bootstrap analysis (Figure S2). As shown in Figure S1, a window of 80ns is

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long enough for simulations to converge.

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H-Bonds Analysis. The average numbers of H-bonds between BPTU and water/lipids were

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calculated for each window of the umbrella sampling using hbond implemented in Gromacs

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5.1.2, and the default criteria (distance

The Molecular Mechanism Underlying Ligand Binding to the

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