A Streamlined, General Approach for Computing Ligand Binding Free Energies and Its Application to GPCR-Bound Cholesterol

Probing the energy landscape of the lipid interactions of the serotonin1A receptor

G protein-coupled receptors (GPCRs) are lipid-regulated transmembrane proteins that play a central role in cell signaling and pharmacology. Although the role of membrane lipids in GPCR function is well established, the underlying GPCR-lipid interactions have not been thermodynamically characterized due to the complexity of these interactions. In this work, we estimate the energetics and dynamics of lipid association from coarse-grain simulations of the serotonin1A receptor embedded in a complex membrane. We show that lipids bind to the receptor with varying energetics of 1-4 kT, and timescales of 1-10 μs. The most favorable energetics and longest residence times are observed for cholesterol, glycosphingolipid GM1, phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids. Multi-exponential fitting of the contact probability suggests distinct dynamic regimes, corresponding to ps, ns and μs timescales, that we correlate with the annular, intermediate and non-annular lipid sites. The timescales of lipid binding correspond to high barrier heights, despite their relatively weaker energetics. Our results highlight that GPCR-lipid interactions are driven by both thermodynamic interactions and the dynamical features of lipid binding.

The thermodynamics of self-assembled monolayer formation: a computational and experimental study of thiols on a flat gold surface

A methodology based on molecular dynamics simulations is presented to determine the chemical potential of thiol self-assembled monolayers on a gold surface. The thiol de-solvation and then the monolayer formation are described by thermodynamic integration with a gradual decoupling of one molecule from the environment, with the necessary corrections to account for standard state changes. The procedure is applied both to physisorbed undissociated thiol molecules and to chemisorbed dissociated thiyl radicals, considering in the latter case the possible chemical potential of the produced hydrogen. We considered monolayers formed by either 7-mercapto-4-methylcoumarin (MMC) or 3-mercapto-propanoic acid (MPA) on a flat gold surface: the free energy profiles with respect to the monolayer density are consistent with a transition from a very stable lying-down phase at low densities to a standing-up phase at higher densities, as expected. The maximum densities of thermodynamically stable monolayers are compared to experimental measures performed with reference-free grazing-incidence X-ray fluorescence (RF-GIXRF) on the same systems, finding a better agreement in the case of chemisorbed thiyl radicals.

Improved Highly Mobile Membrane Mimetic Model for Investigating Protein-Cholesterol Interactions

Cholesterol (CHL) plays an integral role in modulating the function and activity of various mammalian membrane proteins. Due to the slow dynamics of lipids, conventional computational studies of protein-CHL interactions rely on either long-time scale atomistic simulations or coarse-grained approximations to sample the process. A highly mobile membrane mimetic (HMMM) has been developed to enhance lipid diffusion and thus used to facilitate the investigation of lipid interactions with peripheral membrane proteins and, with customized in silico solvents to replace phospholipid tails, with integral membrane proteins. Here, we report an updated HMMM model that is able to include CHL, a nonphospholipid component of the membrane, henceforth called HMMM-CHL. To this end, we had to optimize the effect of the customized solvents on CHL behavior in the membrane. Furthermore, the new solvent is compatible with simulations using force-based switching protocols. In the HMMM-CHL, both improved CHL dynamics and accelerated lipid diffusion are integrated. To test the updated model, we have applied it to the characterization of protein-CHL interactions in two membrane protein systems, the human β2-adrenergic receptor (β2AR) and the mitochondrial voltage-dependent anion channel 1 (VDAC-1). Our HMMM-CHL simulations successfully identified CHL binding sites and captured detailed CHL interactions in excellent consistency with experimental data as well as other simulation results, indicating the utility of the improved model in applications where an enhanced sampling of protein-CHL interactions is desired.

Lambda-ABF: Simplified, Portable, Accurate, and Cost-Effective Alchemical Free-Energy Computation

We introduce the lambda-Adaptive Biasing Force (lambda-ABF) method for the computation of alchemical free-energy differences. We propose a software implementation and showcase it on biomolecular systems. The method arises from coupling multiple-walker adaptive biasing force with λ-dynamics. The sampling of the alchemical variable is continuous and converges toward a uniform distribution, making manual optimization of the λ schedule unnecessary. Contrary to most other approaches, alchemical free-energy estimates are obtained immediately without any postprocessing. Free diffusion of λ improves orthogonal relaxation compared to fixed-λ thermodynamic integration or free-energy perturbation. Furthermore, multiple walkers provide generic orthogonal space coverage with minimal user input and negligible computational overhead. We show that our high-performance implementations coupling the Colvars library with NAMD and Tinker-HP can address real-world cases including ligand-receptor binding with both fixed-charge and polarizable models, with a demonstrably richer sampling than fixed-λ methods. The implementation is fully open-source, publicly available, and readily usable by practitioners of current alchemical methods. Thanks to the portable Colvars library, lambda-ABF presents a unified user interface regardless of the back-end (NAMD, Tinker-HP, or any software to be interfaced in the future), sparing users the effort of learning multiple interfaces. Finally, the Colvars Dashboard extension of the visual molecular dynamics (VMD) software provides an interactive monitoring and diagnostic tool for lambda-ABF simulations.

The density-threshold affinity: Calculating lipid binding affinities from unbiased coarse-grained molecular dynamics simulations

Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the "density threshold affinity." The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between "bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows "bead-level" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields.

Structural basis of pH-dependent activation in a CLC transporter

CLCs are dimeric chloride channels and anion/proton exchangers that regulate processes such as muscle contraction and endo-lysosome acidification. Common gating controls their activity; its closure simultaneously silences both protomers, and its opening allows them to independently transport ions. Mutations affecting common gating in human CLCs cause dominant genetic disorders. The structural rearrangements underlying common gating are unknown. Here, using single-particle cryo-electron microscopy, we show that the prototypical Escherichia coli CLC-ec1 undergoes large-scale rearrangements in activating conditions. The slow, pH-dependent remodeling of the dimer interface leads to the concerted opening of the intracellular H+ pathways and is required for transport. The more frequent formation of short water wires in the open H+ pathway enables Cl- pore openings. Mutations at disease-causing sites favor CLC-ec1 activation and accelerate common gate opening in the human CLC-7 exchanger. We suggest that the pH activation mechanism of CLC-ec1 is related to the common gating of CLC-7.

Propofol directly binds and inhibits skeletal muscle ryanodine receptor 1 (RyR1)

As the primary Ca 2+ release channel in skeletal muscle sarcoplasmic reticulum (SR), mutations in the type 1 ryanodine receptor (RyR1) or its binding partners underlie a constellation of muscle disorders, including malignant hyperthermia (MH). In patients with MH mutations, exposure to triggering drugs such as the halogenated volatile anesthetics biases RyR1 to an open state, resulting in uncontrolled Ca 2+ release, sarcomere tension and heat production. Restoration of Ca 2+ into the SR also consumes ATP, generating a further untenable metabolic load. When anesthetizing patients with known MH mutations, the non-triggering intravenous general anesthetic propofol is commonly substituted for triggering anesthetics. Evidence of direct binding of anesthetic agents to RyR1 or its binding partners is scant, and the atomic-level interactions of propofol with RyR1 are entirely unknown. Here, we show that propofol decreases RyR1 opening in heavy SR vesicles and planar lipid bilayers, and that it inhibits activator-induced Ca 2+ release from SR in human skeletal muscle. In addition to confirming direct binding, photoaffinity labeling using m- azipropofol (AziP m ) revealed several putative propofol binding sites on RyR1. Prediction of binding affinity by molecular dynamics simulation suggests that propofol binds at least one of these sites at clinical concentrations. These findings invite the hypothesis that in addition to propofol not triggering MH, it may also be protective against MH by inhibiting induced Ca 2+ flux through RyR1.

Palmitoylation of the Glucagon-like Peptide-1 Receptor Modulates Cholesterol Interactions at the Receptor-Lipid Microenvironment

The G protein-coupled receptor (GPCR) superfamily of cell surface receptors has been shown to be functionally modulated by post-translational modifications. The glucagon-like peptide receptor-1 (GLP-1R), which is a drug target in diabetes and obesity, undergoes agonist-dependent palmitoyl tail conjugation. The palmitoylation in the C-terminal domain of GLP-1R has been suggested to modulate the receptor-lipid microenvironment. In this work, we have performed coarse-grain molecular dynamics simulations of palmitoylated and nonpalmitoylated GLP-1R to analyze the differential receptor-lipid interactions. Interestingly, the placement and dynamics of the C-terminal domain of GLP-1R are found to be directly dependent on the palmitoyl tail. We observe that both cholesterol and phospholipids interact with the receptor but display differential interactions in the presence and absence of the palmitoyl tail. We characterize important cholesterol-binding sites and validate sites that have been previously reported in experimentally resolved structures of the receptor. We show that the receptor acts like a conduit for cholesterol flip-flop by stabilizing cholesterol in the membrane core. Taken together, our work represents an important step in understanding the molecular effects of lipid modifications in GPCRs.

Standard Binding Free-Energy Calculations: How Far Are We from Automation?

Recent success stories suggest that in silico protein-ligand binding free-energy calculations are approaching chemical accuracy. However, their widespread application remains limited by the extensive human intervention required, posing challenges for the neophyte. As such, it is critical to develop automated workflows for estimating protein-ligand binding affinities with minimum personal involvement. Key human efforts include setting up and tuning enhanced-sampling or alchemical-transformation algorithms as a preamble to computational binding free-energy estimations. Additionally, preparing input files, bookkeeping, and postprocessing represent nontrivial tasks. In this Perspective, we discuss recent progress in automating standard binding free-energy calculations, featuring the development of adaptive or parameter-free algorithms, standardization of binding free-energy calculation workflows, and the implementation of user-friendly software. We also assess the current state of automated standard binding free-energy calculations and evaluate the limitations of existing methods. Last, we outline the requirements for future algorithms and workflows to facilitate automated free-energy calculations for diverse protein-ligand complexes.

Structural and thermodynamic framework for PIEZO1 modulation by small molecules

Mechanosensitive PIEZO channels constitute potential pharmacological targets for multiple clinical conditions, spurring the search for potent chemical PIEZO modulators. Among them is Yoda1, a widely used synthetic small molecule PIEZO1 activator discovered through cell-based high-throughput screening. Yoda1 is thought to bind to PIEZO1's mechanosensory arm domain, sandwiched between two transmembrane regions near the channel pore. However, how the binding of Yoda1 to this region promotes channel activation remains elusive. Here, we first demonstrate that cross-linking PIEZO1 repeats A and B with disulfide bridges reduces the effects of Yoda1 in a redox-dependent manner, suggesting that Yoda1 acts by perturbing the contact between these repeats. Using molecular dynamics-based absolute binding free energy simulations, we next show that Yoda1 preferentially occupies a deeper, amphipathic binding site with higher affinity in PIEZO1 open state. Using Yoda1's binding poses in open and closed states, relative binding free energy simulations were conducted in the membrane environment, recapitulating structure-activity relationships of known Yoda1 analogs. Through virtual screening of an 8 million-compound library using computed fragment maps of the Yoda1 binding site, we subsequently identified two chemical scaffolds with agonist activity toward PIEZO1. This study supports a pharmacological model in which Yoda1 activates PIEZO1 by wedging repeats A and B, providing a structural and thermodynamic framework for the rational design of PIEZO1 modulators. Beyond PIEZO channels, the three orthogonal computational approaches employed here represent a promising path toward drug discovery in highly heterogeneous membrane protein systems.

Alchemical Free Energy Calculations on Membrane-Associated Proteins

Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.

The energetics and ion coupling of cholesterol transport through Patched1

Patched1 (PTCH1) is a tumor suppressor protein of the mammalian Hedgehog (HH) signaling pathway, implicated in embryogenesis and tissue homeostasis. PTCH1 inhibits the G protein-coupled receptor Smoothened (SMO) via a debated mechanism involving modulating ciliary cholesterol accessibility. Using extensive molecular dynamics simulations and free energy calculations to evaluate cholesterol transport through PTCH1, we find an energetic barrier of ~15 to 20 kilojoule per mole for cholesterol export. In silico data are coupled to in vivo biochemical assays of PTCH1 mutants to probe coupling between cation binding sites, transmembrane motions, and PTCH1 activity. Using complementary simulations of Dispatched1, we find that transition between "inward-open" and solvent "occluded" states is accompanied by Na+-induced pinching of intracellular helical segments. Thus, our findings illuminate the energetics and ion coupling stoichiometries of PTCH1 transport mechanisms, whereby one to three Na+ or two to three K+ couple to cholesterol export, and provide the first molecular description of transitions between distinct transport states.

Binding site plasticity regulation of the FimH catch-bond mechanism

The bacterial fimbrial adhesin FimH is a remarkable and well-studied catch-bond protein found at the tip of E. coli type 1 pili, which allows pathogenic strains involved in urinary tract infections to bind high-mannose glycans exposed on human epithelia. The catch-bond behavior of FimH, where the strength of the interaction increases when a force is applied to separate the two partners, enables the bacteria to resist clearance when they are subjected to shear forces induced by urine flow. Two decades of experimental studies performed at the single-molecule level, as well as x-ray crystallography and modeling studies, have led to a consensus picture whereby force separates the binding domain from an inhibitor domain, effectively triggering an allosteric conformational change in the former. This force-induced allostery is thought to be responsible for an increased binding affinity at the core of the catch-bond mechanism. However, some important questions remain, the most challenging one being that the crystal structures corresponding to these two allosteric states show almost superimposable binding site geometries, which questions the molecular origin for the large difference in affinity. Using molecular dynamics with a combination of enhanced-sampling techniques, we demonstrate that the static picture provided by the crystal structures conceals a variety of binding site conformations that have a key impact on the apparent affinity. Crucially, the respective populations in each of these conformations are very different between the two allosteric states of the binding domain, which can then be related to experimental affinity measurements. We also evidence a previously unappreciated but important effect: in addition to the well-established role of the force as an allosteric regulator via domain separation, application of force tends to directly favor the high-affinity binding site conformations. We hypothesize that this additional "local" catch-bond effect could delay unbinding between the bacteria and the host cell before the "global" allosteric transition occurs, as well as stabilizing the complex even more once in the high-affinity allosteric state.

Comparison of Receptor-Ligand Restraint Schemes for Alchemical Absolute Binding Free Energy Calculations

Alchemical absolute binding free energy calculations are of increasing interest in drug discovery. These calculations require restraints between the receptor and ligand to restrict their relative positions and, optionally, orientations. Boresch restraints are commonly used, but they must be carefully selected in order to sufficiently restrain the ligand and to avoid inherent instabilities. Applying multiple distance restraints between anchor points in the receptor and ligand provides an alternative framework without inherent instabilities which may provide convergence benefits by more strongly restricting the relative movements of the receptor and ligand. However, there is no simple method to calculate the free energy of releasing these restraints due to the coupling of the internal and external degrees of freedom of the receptor and ligand. Here, a method to rigorously calculate free energies of binding with multiple distance restraints by imposing intramolecular restraints on the anchor points is proposed. Absolute binding free energies for the human macrophage migration inhibitory factor/MIF180, system obtained using a variety of Boresch restraints and rigorous and nonrigorous implementations of multiple distance restraints are compared. It is shown that several multiple distance restraint schemes produce estimates in good agreement with Boresch restraints. In contrast, calculations without orientational restraints produce erroneously favorable free energies of binding by up to approximately 4 kcal mol-1. These approaches offer new options for the deployment of alchemical absolute binding free energy calculations.

Allosteric Modulation of Membrane Proteins by Small Low-Affinity Ligands

Membrane proteins may respond to a variety of ligands under an applied external stimulus. These ligands include small low-affinity molecules that account for functional effects in the mM range. Understanding the modulation of protein function by low-affinity ligands requires characterizing their atomic-level interactions under dilution, challenging the current resolution of theoretical and experimental routines. Part of the problem derives from the fact that small low-affinity ligands may interact with multiple sites of a membrane protein in a highly degenerate manner to a degree that it is better conceived as a partition phenomenon, hard to track at the molecular interface of the protein. Looking for new developments in the field, we rely on the classic two-state Boltzmann model to devise a novel theoretical description of the allosteric modulation mechanism of membrane proteins in the presence of small low-affinity ligands and external stimuli. Free energy stability of the partition process and its energetic influence on the protein coupling with the external stimulus are quantified. The outcome is a simple formulation that allows the description of the equilibrium shifts of the protein in terms of the grand-canonical partition function of the ligand at dilute concentrations. The model's predictions of the spatial distribution and response probability shift across a variety of ligand concentrations, and thermodynamic conjugates can be directly compared to macroscopic measurements, making it especially useful to interpret experimental data at the atomic level. Illustration and discussion of the theory is shown in the context of general anesthetics and voltage-gated channels for which structural data are available.

The Energetics and Ion Coupling of Cholesterol Transport Through Patched1

Patched1 (PTCH1) is the principal tumour suppressor protein of the mammalian Hedgehog (HH) signalling pathway, implicated in embryogenesis and tissue homeostasis. PTCH1 inhibits the Class F G protein-coupled receptor Smoothened (SMO) via a debated mechanism involving modulating accessible cholesterol levels within ciliary membranes. Using extensive molecular dynamics (MD) simulations and free energy calculations to evaluate cholesterol transport through PTCH1, we find an energetic barrier of ~15-20 kJ mol -1 for cholesterol export. In simulations we identify cation binding sites within the PTCH1 transmembrane domain (TMD) which may provide the energetic impetus for cholesterol transport. In silico data are coupled to in vivo biochemical assays of PTCH1 mutants to probe coupling between transmembrane motions and PTCH1 activity. Using complementary simulations of Dispatched1 (DISP1) we find that transition between 'inward-open' and solvent 'occluded' states is accompanied by Na + induced pinching of intracellular helical segments. Thus, our findings illuminate the energetics and ion-coupling stoichiometries of PTCH1 transport mechanisms, whereby 1-3 Na + or 2-3 K + couple to cholesterol export, and provide the first molecular description of transitions between distinct transport states.

Regulation of membrane protein structure and function by their lipid nano-environment

Transmembrane proteins comprise ~30% of the mammalian proteome, mediating metabolism, signalling, transport and many other functions required for cellular life. The microenvironment of integral membrane proteins (IMPs) is intrinsically different from that of cytoplasmic proteins, with IMPs solvated by a compositionally and biophysically complex lipid matrix. These solvating lipids affect protein structure and function in a variety of ways, from stereospecific, high-affinity protein-lipid interactions to modulation by bulk membrane properties. Specific examples of functional modulation of IMPs by their solvating membranes have been reported for various transporters, channels and signal receptors; however, generalizable mechanistic principles governing IMP regulation by lipid environments are neither widely appreciated nor completely understood. Here, we review recent insights into the inter-relationships between complex lipidomes of mammalian membranes, the membrane physicochemical properties resulting from such lipid collectives, and the regulation of IMPs by either or both. The recent proliferation of high-resolution methods to study such lipid-protein interactions has led to generalizable insights, which we synthesize into a general framework termed the 'functional paralipidome' to understand the mutual regulation between membrane proteins and their surrounding lipid microenvironments.

Importance of molecular dynamics equilibrium protocol on protein-lipid interaction near channel pore

Multiscale molecular dynamics simulations using Martini coarse-grained (CG) and all-atom (AA) force fields are commonly used in membrane protein studies. In particular, reverse mapping an equilibrated CG model to an AA model offers an efficient way for preparing large membrane protein systems with complex protein shapes and lipid compositions. Here, we report that this hybrid CG-equilibrium-AA-production protocol may artificially increase lipid density and decrease hydration in ion channel pores walled with transmembrane gaps. To understand the origin of this conundrum, we conducted replicas of CG, AA, and CG reverse-mapped AA simulations of the pore domain of the mechanosensitive Piezo1 channel in a nonconducting conformation. Lipid/water density analysis and free energy calculations reveal that the lack of initial pore hydration allows excessive lipids to enter the upper pore lumen through gaps between pore helices during CG simulation. Due to the mismatch between CG and AA lipid kinetics, these pore lipids remain trapped in the subsequent AA simulations, despite unfavorable binding free energy. We tested several CG equilibrium protocols and found that a protocol restraining the whole lipid produces pore hydration consistent with AA results, thus eliminating this artifact for further studies of lipid gating and protein-lipid interactions.

Open-channel structure of a pentameric ligand-gated ion channel reveals a mechanism of leaflet-specific phospholipid modulation

Pentameric ligand-gated ion channels (pLGICs) mediate synaptic transmission and are sensitive to their lipid environment. The mechanism of phospholipid modulation of any pLGIC is not well understood. We demonstrate that the model pLGIC, ELIC (Erwinia ligand-gated ion channel), is positively modulated by the anionic phospholipid, phosphatidylglycerol, from the outer leaflet of the membrane. To explore the mechanism of phosphatidylglycerol modulation, we determine a structure of ELIC in an open-channel conformation. The structure shows a bound phospholipid in an outer leaflet site, and structural changes in the phospholipid binding site unique to the open-channel. In combination with streamlined alchemical free energy perturbation calculations and functional measurements in asymmetric liposomes, the data support a mechanism by which an anionic phospholipid stabilizes the activated, open-channel state of a pLGIC by specific, state-dependent binding to this site.

Concentration-Dependent Thermodynamic Analysis of the Partition Process of Small Ligands into Proteins

In the category of functional low-affinity interactions, small ligands may interact with multiple protein sites in a highly degenerate manner. Better conceived as a partition phenomenon at the molecular interface of proteins, such low-affinity interactions appear to be hidden to our current experimental resolution making their structural and functional characterization difficult in the low concentration regime of physiological processes. Characterization of the partition phenomenon under higher chemical forces could be a relevant strategy to tackle the problem provided the results can be scaled back to the low concentration range. Far from being trivial, such scaling demands a concentration-dependent understanding of self-interactions of the ligands, structural perturbations of the protein, among other molecular effects. Accordingly, we elaborate a novel and detailed concentration-dependent thermodynamic analysis of the partition process of small ligands aiming at characterizing the stability and structure of the dilute phenomenon from high concentrations. In analogy to an “aggregate” binding constant of a small molecule over multiple sites of a protein receptor, the model defines the stability of the process as a macroscopic equilibrium constant for the partition number of ligands that can be used to analyze biochemical and functional data of two-component systems driven by low-affinity interactions. Acquisition of such modeling-based structural information is expected to be highly welcome by revealing more traceable protein-binding spots for non-specific ligands.

Consistent Picture of Phosphate-Divalent Cation Binding from Models with Implicit and Explicit Electronic Polarization

The binding of divalent cations to the ubiquitous phosphate group is essential for a number of key biological processes, such as DNA compaction, RNA folding, or interactions of some proteins with membranes. Yet, probing their binding sites, modes, and associated binding free energy is a challenge for both experiments and simulations. In simulations, standard force fields strongly overestimate the interaction between phosphate groups and divalent cations. Here, we examine how different strategies to include electronic polarization effects in force fields─implicitly, through the use of scaled charges or pair-specific Lennard-Jones parameters, or explicitly, with the polarizable force fields Drude and AMOEBA─capture the interactions of a model phosphate compound, dimethyl phosphate, with calcium and magnesium divalent cations. We show that both implicit and explicit approaches, when carefully parameterized, are successful in capturing the overall binding free energy and that common trends emerge from the comparison of different simulation approaches. Overall, the binding is very moderate, slightly weaker for Ca²⁺ than Mg²⁺, and the solvent-shared ion pair is slightly more stable than the contact monodentate ion pair. The bidentate ion pair is higher in energy (or even fully unstable for Mg²⁺). Our results thus suggest practical ways to capture the divalent cations with biomolecular phosphate groups in complex biochemical systems. In particular, the computational efficiency of implicit models makes them ideally suited for large-scale simulations of biological assemblies, with improved accuracy compared to state-of-the-art fixed-charge force fields.

Symmetry-Adapted Restraints for Binding Free Energy Calculations

Binding free energy calculations rely critically on a precise definition of the bound state and well-designed ligand restraints to ensure that binding free energy calculations converge rapidly and yield estimates of well-defined thermodynamic quantities. The distance-to-bound-configuration (DBC) is a single variable that can precisely delineate the bound state of a ligand including translational, rotational and conformational degrees of freedom and has been successfully used to capture binding modes with complex geometries. DBC is defined as the root-mean-square deviation (RMSD) of ligand coordinates in the frame of reference of the binding site. In the special case where the ligand features symmetry-equivalent atoms, a standard RMSD arbitrarily distinguishes equivalent poses, mixing equivalent and nonequivalent degrees of freedom, and preventing the precise delineation of the bound state ensemble, which negates the benefits of defining a flat-bottom binding restraint. To remedy this, we introduce a symmetry-adapted DBC coordinate where the RMSD is minimized over permutations of equivalent ligand atoms. This coordinate is implemented in a portable software library, the Collective Variables Module. We tested the approach by computing the absolute binding free energy of benzene to the engineered site of a mutant lysozyme (L99A/M102H) using alchemical free energy perturbation. We found that the symmetry-adapted restraint leads to well-behaved convergence of both the decoupling free energy in the binding site and the restrained free energy in the gas phase, recovering the affinity computed using a classic center-of-mass restraint. Thus, symmetry-adapted DBC seamlessly generalizes the benefits of DBC restraints to the case of symmetric ligands. The underlying symmetric RMSD coordinate can also be used for analyzing or biasing simulations in other contexts than affinity predictions.

Human Learning for Molecular Simulations: The Collective Variables Dashboard in VMD

The Collective Variables Dashboard is a software tool for real-time, seamless exploration of molecular structures and trajectories in a customizable space of collective variables. The Dashboard arises from the integration of the Collective Variables Module (also known as Colvars) with the visualization software VMD, augmented with a fully discoverable graphical interface offering interactive workflows for the design and analysis of collective variables. Typical use cases include a priori design of collective variables for enhanced sampling and free energy simulations as well as analysis of any type of simulation or collection of structures in a collective variable space. A combination of those cases commonly occurs when preliminary simulations, biased or unbiased, reveal that an optimized set of collective variables is necessary to improve sampling in further simulations. Then the Dashboard provides an efficient way to intuitively explore the space of likely collective variables, validate them on existing data, and use the resulting collective variable definitions directly in further biased simulations using the Collective Variables Module. Visualization of biasing energies and forces is proposed to help analyze or plan biased simulations. We illustrate the use of the Dashboard on two applications: discovering coordinates to describe ligand unbinding from a protein binding site and designing volume-based variables to bias the hydration of a transmembrane pore.

PyLipID: A Python Package for Analysis of Protein-Lipid Interactions from Molecular Dynamics Simulations

Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these protein-lipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a Python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements while bound from full dissociation events. In addition to the characterization of protein-lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation data sets of multiple species of membrane proteins.

Druggable Lipid Binding Sites in Pentameric Ligand-Gated Ion Channels and Transient Receptor Potential Channels

Lipids modulate the function of many ion channels, possibly through direct lipid-protein interactions. The recent outpouring of ion channel structures by cryo-EM has revealed many lipid binding sites. Whether these sites mediate lipid modulation of ion channel function is not firmly established in most cases. However, it is intriguing that many of these lipid binding sites are also known sites for other allosteric modulators or drugs, supporting the notion that lipids act as endogenous allosteric modulators through these sites. Here, we review such lipid-drug binding sites, focusing on pentameric ligand-gated ion channels and transient receptor potential channels. Notable examples include sites for phospholipids and sterols that are shared by anesthetics and vanilloids. We discuss some implications of lipid binding at these sites including the possibility that lipids can alter drug potency or that understanding protein-lipid interactions can guide drug design. Structures are only the first step toward understanding the mechanism of lipid modulation at these sites. Looking forward, we identify knowledge gaps in the field and approaches to address them. These include defining the effects of lipids on channel function in reconstituted systems using asymmetric membranes and measuring lipid binding affinities at specific sites using native mass spectrometry, fluorescence binding assays, and computational approaches.

Building intuition for binding free energy calculations: Bound state definition, restraints, and symmetry

The theory behind computation of absolute binding free energies using explicit-solvent molecular simulations is well-established, yet somewhat complex, with counter-intuitive aspects. This leads to frequent frustration, common misconceptions, and sometimes erroneous numerical treatment. To improve this, we present the main practically relevant segments of the theory with constant reference to physical intuition. We pinpoint the role of the implicit or explicit definition of the bound state (or the binding site) to make a robust link between an experimental measurement and a computational result. We clarify the role of symmetry and discuss cases where symmetry number corrections have been misinterpreted. In particular, we argue that symmetry corrections as classically presented are a source of confusion and could be advantageously replaced by restraint free energy contributions. We establish that contrary to a common intuition, partial or missing sampling of some modes of symmetric bound states does not affect the calculated decoupling free energies. Finally, we review these questions and pitfalls in the context of a few common practical situations: binding to a symmetric receptor (equivalent binding sites), binding of a symmetric ligand (equivalent poses), and formation of a symmetric complex, in the case of homodimerization.

Spontaneous lipid binding to the nicotinic acetylcholine receptor in a native membrane

The nicotinic acetylcholine receptor (nAChR) and other pentameric ligand-gated ion channels are native to neuronal membranes with an unusual lipid composition. While it is well-established that these receptors can be significantly modulated by lipids, the underlying mechanisms have been primarily studied in model membranes with few lipid species. Here, we use coarse-grained molecular dynamics simulation to probe specific binding of lipids in a complex quasi-neuronal membrane. We ran a total of 50 μs of simulations of a single nAChR in a membrane composed of 36 species of lipids. Competition between multiple lipid species produces a complex distribution. We find that overall, cholesterol selects for concave inter-subunit sites and polyunsaturated fatty acids select for convex M4 sites, while monounsaturated and saturated lipids are unenriched in the nAChR boundary. We propose the "density-threshold affinity" as a metric calculated from continuous density distributions, which reduces to a standard affinity in two-state binding. We find that the density-threshold affinity for M4 weakens with chain rigidity, which suggests that flexible chains may help relax packing defects caused by the conical protein shape. For any site, PE headgroups have the strongest affinity of all phospholipid headgroups, but anionic lipids still yield moderately high affinities for the M4 sites as expected. We observe cooperative effects between anionic headgroups and saturated chains at the M4 site in the inner leaflet. We also analyze affinities for individual anionic headgroups. When combined, these insights may reconcile several apparently contradictory experiments on the role of anionic phospholipids in modulating nAChR.

Ketamine Metabolite (2R,6R)-Hydroxynorketamine Interacts with μ and κ Opioid Receptors

Ketamine is an anesthetic, analgesic, and antidepressant whose secondary metabolite (2R,6R)-hydroxynorketamine (HNK) has N-methyl-d-aspartate-receptor-independent antidepressant activity in a rodent model. In humans, naltrexone attenuates its antidepressant effect, consistent with opioid pathway involvement. No detailed biophysical description is available of opioid receptor binding of ketamine or its metabolites. Using molecular dynamics simulations with free energy perturbation, we characterize the binding site and affinities of ketamine and metabolites in μ and κ opioid receptors, finding a profound effect of the protonation state. G-protein recruitment assays show that HNK is an inverse agonist, attenuated by naltrexone, in these receptors with IC₅₀ values congruous with our simulations. Overall, our findings are consistent with opioid pathway involvement in ketamine function.

Activation of G-protein-coupled receptors is thermodynamically linked to lipid solvation

Preferential lipid solvation of the G-protein-coupled A_2A adenosine receptor (A_2AR) is evaluated from 35 μs of all-atom molecular dynamics simulation. A coarse-grained transition matrix algorithm is developed to overcome slow equilibration of the first solvation shell, obtaining estimates of the free energy of solvation by different lipids for the receptor in different activation states. Results indicate preference for solvation by unsaturated chains, which favors the active receptor. A model for lipid-dependent G-protein-coupled receptor activity is proposed in which the chemical potential of lipids in the bulk membrane modulates receptor activity. The entropies associated with moving saturated and unsaturated lipids from bulk to A_2AR's first solvation shell are evaluated. Overall, the acyl chains are more disordered (i.e., obtain a favorable entropic contribution) when partitioning to the receptor surface, and this effect is augmented for the saturated chains, which are relatively more ordered in bulk.

Cholesterol as a modulator of cannabinoid receptor CB2 signaling

Signaling through integral membrane G protein-coupled receptors (GPCRs) is influenced by lipid composition of cell membranes. By using novel high affinity ligands of human cannabinoid receptor CB₂, we demonstrate that cholesterol increases basal activation levels of the receptor and alters the pharmacological categorization of these ligands. Our results revealed that (2-(6-chloro-2-((2,2,3,3-tetramethylcyclopropane-1-carbonyl)imino)benzo[d]thiazol-3(2H)-yl)ethyl acetate ligand (MRI-2646) acts as a partial agonist of CB₂ in membranes devoid of cholesterol and as a neutral antagonist or a partial inverse agonist in cholesterol-containing membranes. The differential effects of a specific ligand on activation of CB₂ in different types of membranes may have implications for screening of drug candidates in a search of modulators of GPCR activity. MD simulation suggests that cholesterol exerts an allosteric effect on the intracellular regions of the receptor that interact with the G-protein complex thereby altering the recruitment of G protein.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Mechanistic insights into volatile anesthetic modulation of K2P channels

K2P potassium channels are known to be modulated by volatile anesthetic (VA) drugs and play important roles in clinically relevant effects that accompany general anesthesia. Here, we utilize a photoaffinity analog of the VA isoflurane to identify a VA-binding site in the TREK1 K2P channel. The functional importance of the identified site was validated by mutagenesis and biochemical modification. Molecular dynamics simulations of TREK1 in the presence of VA found multiple neighboring residues on TREK1 TM2, TM3, and TM4 that contribute to anesthetic binding. The identified VA-binding region contains residues that play roles in the mechanisms by which heat, mechanical stretch, and pharmacological modulators alter TREK1 channel activity and overlaps with positions found to modulate TASK K2P channel VA sensitivity. Our findings define molecular contacts that mediate VA binding to TREK1 channels and suggest a mechanistic basis to explain how K2P channels are modulated by VAs.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Distinct binding of cetirizine enantiomers to human serum albumin and the human histamine receptor H1

Cetirizine, a major metabolite of hydroxyzine, became a marketed second-generation H₁ antihistamine that is orally active and has a rapid onset of action, long duration of effects and a very good safety record at recommended doses. The approved drug is a racemic mixture of (S)-cetirizine and (R)-cetirizine, the latter being the levorotary enantiomer that also exists in the market as a third-generation, non-sedating and highly selective antihistamine. Both enantiomers bind tightly to the human histamine H₁ receptor (hH₁R) and behave as inverse agonists but the affinity and residence time of (R)-cetirizine are greater than those of (S)-cetirizine. In blood plasma, cetirizine exists in the zwitterionic form and more than 90% of the circulating drug is bound to human serum albumin (HSA), which acts as an inactive reservoir. Independent X-ray crystallographic work has solved the structure of the hH₁R:doxepin complex and has identified two drug-binding sites for cetirizine on equine serum albumin (ESA). Given this background, we decided to model a membrane-embedded hH₁R in complex with either (R)- or (S)-cetirizine and also the complexes of both ESA and HSA with these two enantiomeric drugs to analyze possible differences in binding modes between enantiomers and also among targets. The ensuing molecular dynamics simulations in explicit solvent and additional computational chemistry calculations provided structural and energetic information about all of these complexes that is normally beyond current experimental possibilities. Overall, we found very good agreement between our binding energy estimates and extant biochemical and pharmacological evidence. A much higher degree of solvent exposure in the cetirizine-binding site(s) of HSA and ESA relative to the more occluded orthosteric binding site in hH₁R is translated into larger positional fluctuations and considerably lower affinities for these two nonspecific targets. Whereas it is demonstrated that the two known pockets in ESA provide enough stability for cetirizine binding, only one such site does so in HSA due to a number of amino acid replacements. At the histamine-binding site in hH₁R, the distinct interactions established between the phenyl and chlorophenyl moieties of the two enantiomers with the amino acids lining up the pocket and between their free carboxylates and Lys179 in the second extracellular loop account for the improved pharmacological profile of (R)-cetirizine.

The energetics of protein-lipid interactions as viewed by molecular simulations

Membranes are formed from a bilayer containing diverse lipid species with which membrane proteins interact. Integral, membrane proteins are embedded in this bilayer, where they interact with lipids from their surroundings, whilst peripheral membrane proteins bind to lipids at the surface of membranes. Lipid interactions can influence the function of membrane proteins, either directly or allosterically. Both experimental (structural) and computational approaches can reveal lipid binding sites on membrane proteins. It is, therefore, important to understand the free energies of these interactions. This affords a more complete view of the engagement of a particular protein with the biological membrane surrounding it. Here, we describe many computational approaches currently in use for this purpose, including recent advances using both free energy and unbiased simulation methods. In particular, we focus on interactions of integral membrane proteins with cholesterol, and with anionic lipids such as phosphatidylinositol 4,5-bis-phosphate and cardiolipin. Peripheral membrane proteins are exemplified via interactions of PH domains with phosphoinositide-containing membranes. We summarise the current state of the field and provide an outlook on likely future directions of investigation.

Insights into Membrane Protein-Lipid Interactions from Free Energy Calculations

Integral membrane proteins are regulated by specific interactions with lipids from the surrounding bilayer. The structures of protein–lipid complexes can be determined through a combination of experimental and computational approaches, but the energetic basis of these interactions is difficult to resolve. Molecular dynamics simulations provide the primary computational technique to estimate the free energies of these interactions. We demonstrate that the energetics of protein–lipid interactions may be reliably and reproducibly calculated using three simulation-based approaches: potential of mean force calculations, alchemical free energy perturbation, and well-tempered metadynamics. We employ these techniques within the framework of a coarse-grained force field and apply them to both bacterial and mammalian membrane protein–lipid systems. We demonstrate good agreement between the different techniques, providing a robust framework for their automated implementation within a pipeline for annotation of newly determined membrane protein structures.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.