The SAMPL9 host-guest blind challenge: an overview of binding free energy predictive accuracy.

We report the results of the SAMPL9 host-guest blind challenge for predicting binding free energies. The challenge focused on macrocycles from pillar[n]-arene and cyclodextrin host families, including WP6, and bCD and HbCD. A variety of methods were used by participants to submit binding free energy predictions. A machine learning approach based on molecular descriptors achieved the highest accuracy (RMSE of 2.04 kcal mol-1) among the ranked methods in the WP6 dataset. Interestingly, predictions for WP6 obtained via docking tended to outperform all methods (RMSE of 1.70 kcal mol-1), most of which are MD based and computationally more expensive. In general, methods applying force fields achieved better correlation with experiments for WP6 opposed to the machine learning and docking models. In the cyclodextrin-phenothiazine challenge, the ATM approach emerged as the top performing method with RMSE less than 1.86 kcal mol-1. Correlation metrics of ranked methods in this dataset were relatively poor compared to WP6. We also highlight several lessons learned to guide future work and help improve studies on the systems discussed. For example, WP6 may be present in other microstates other than its -12 state in the presence of certain guests. Machine learning approaches can be used to fine tune or help train force fields for certain chemistry (i.e. WP6-G4). Certain phenothiazines occupy distinct primary and secondary orientations, some of which were considered individually for accurate binding free energies. The accuracy of predictions from certain methods while starting from a single binding pose/orientation demonstrates the sensitivity of calculated binding free energies to the orientation, and in some cases the likely dominant orientation for the system. Computational and experimental results suggest that guest phenothiazine core traverses both the secondary and primary faces of the cyclodextrin hosts, a bulky cationic side chain will primarily occupy the primary face, and the phenothiazine core substituent resides at the larger secondary face.

Molecular Dynamics and Theratyping in Airway and Gut Organoids Reveal R352Q-CFTR Conductance Defect.

A significant challenge to making targeted cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies accessible to all individuals with cystic fibrosis (CF) are many mutations in the CFTR gene that can cause CF, most of which remain uncharacterized. Here, we characterized the structural and functional defects of the rare CFTR mutation R352Q, with a potential role contributing to intrapore chloride ion permeation, in patient-derived cell models of the airway and gut. CFTR function in differentiated nasal epithelial cultures and matched intestinal organoids was assessed using an ion transport assay and forskolin-induced swelling assay, respectively. CFTR potentiators (VX-770, GLPG1837, and VX-445) and correctors (VX-809, VX-445, with or without VX-661) were tested. Data from R352Q-CFTR were compared with data of 20 participants with mutations with known impact on CFTR function. R352Q-CFTR has residual CFTR function that was restored to functional CFTR activity by CFTR potentiators but not the corrector. Molecular dynamics simulations of R352Q-CFTR were carried out, which indicated the presence of a chloride conductance defect, with little evidence supporting a gating defect. The combination approach of in vitro patient-derived cell models and in silico molecular dynamics simulations to characterize rare CFTR mutations can improve the specificity and sensitivity of modulator response predictions and aid in their translational use for CF precision medicine.

An overview of the SAMPL8 host-guest binding challenge.

The SAMPL series of challenges aim to focus the community on specific modeling challenges, while testing and hopefully driving progress of computational methods to help guide pharmaceutical drug discovery. In this study, we report on the results of the SAMPL8 host-guest blind challenge for predicting absolute binding affinities. SAMPL8 focused on two host-guest datasets, one involving the cucurbituril CB8 (with a series of common drugs of abuse) and another involving two different Gibb deep-cavity cavitands. The latter dataset involved a previously featured deep cavity cavitand (TEMOA) as well as a new variant (TEETOA), both binding to a series of relatively rigid fragment-like guests. Challenge participants employed a reasonably wide variety of methods, though many of these were based on molecular simulations, and predictive accuracy was mixed. As in some previous SAMPL iterations (SAMPL6 and SAMPL7), we found that one approach to achieve greater accuracy was to apply empirical corrections to the binding free energy predictions, taking advantage of prior data on binding to these hosts. Another approach which performed well was a hybrid MD-based approach with reweighting to a force matched QM potential. In the cavitand challenge, an alchemical method using the AMOEBA-polarizable force field achieved the best success with RMSE less than 1 kcal/mol, while another alchemical approach (ATM/GAFF2-AM1BCC/TIP3P/HREM) had RMSE less than 1.75 kcal/mol. The work discussed here also highlights several important lessons; for example, retrospective studies of reference calculations demonstrate the sensitivity of predicted binding free energies to ethyl group sampling and/or guest starting pose, providing guidance to help improve future studies on these systems.

Free-Energy Simulations Resolve the Low-Affinity Na+-High-Affinity Asp Binding Paradox in GltPh.

Glutamate transporters clear up excess extracellular glutamate by cotransporting three Na+ and one H+ with the countertransport of one K+. The archaeal homologs are selective to aspartate and only cotransport three Na+. The crystal structures of GltPh from archaea have been used in computational studies to understand the transport mechanism. Although some progress has been made with regard to the ligand-binding sites, a consistent picture of transport still eludes us. A major concern is the discrepancy between the computed binding free energies, which predict high-affinity Na+-low-affinity aspartate binding, and the experimental results in which the opposite is observed. Here, we show that the binding of the first two Na+ ions involves an intermediate state near the Na1 site, where two Na+ ions coexist and couple to aspartate with similar strengths, boosting its affinity. Binding free energies for Na+ and aspartate obtained using this intermediate state are in good agreement with the experimental values. Thus, the paradox in binding affinities arises from the assumption that the ligands bind to the sites observed in the crystal structure following the order dictated by their binding free energies with no intermediate states. In fact, the presence of an intermediate state eliminates such a correlation between the binding free energies and the binding order. The intermediate state also facilitates transition of the first Na+ ion to its final binding site via a knock-on mechanism, which induces substantial conformational changes in the protein consistent with experimental observations.

A simple, parameter-free method for computing solvation free energies of ions.

Solvation free energies of ions are difficult to determine from molecular dynamics simulations due to the long-range Coulomb interactions. Various approximations and corrections are introduced to enable their calculation in small systems, which, however, raises issues of robustness. We show that solvation free energies of ions can be calculated using the spherical boundary conditions without introducing any corrections at the boundary via a buffer zone. The results are shown to converge for a droplet size of 21 Å and are independent of the parameters used for confining water or restraining the ion. The proposed method thus resolves the robustness issues in solvation free energy calculations of ions and can be used with confidence to determine force field parameters from such calculations. We apply the method to calculate the solvation free energies of the side chain analogs of charged amino acids. Tests using periodic boundary conditions show that similar results are also obtained in that case.

Tuning Potential Functions to Host-Guest Binding Data.

Software to more rapidly and accurately predict protein-ligand binding affinities is of high interest for early-stage drug discovery, and physics-based methods are among the most widely used technologies for this purpose. The accuracy of these methods depends critically on the accuracy of the potential functions that they use. Potential functions are typically trained against a combination of quantum chemical and experimental data. However, although binding affinities are among the most important quantities to predict, experimental binding affinities have not to date been integrated into the experimental data set used to train potential functions. In recent years, the use of host-guest complexes as simple and tractable models of binding thermodynamics has gained popularity due to their small size and simplicity, relative to protein-ligand systems. Host-guest complexes can also avoid ambiguities that arise in protein-ligand systems such as uncertain protonation states. Thus, experimental host-guest binding data are an appealing additional data type to integrate into the experimental data set used to optimize potential functions. Here, we report the extension of the Open Force Field Evaluator framework to enable the systematic calculation of host-guest binding free energies and their gradients with respect to force field parameters, coupled with the curation of 126 host-guest complexes with available experimental binding free energies. As an initial application of this novel infrastructure, we optimized generalized Born (GB) cavity radii for the OBC2 GB implicit solvent model against experimental data for 36 host-guest systems. This refitting led to a dramatic improvement in accuracy for both the training set and a separate test set with 90 additional host-guest systems. The optimized radii also showed encouraging transferability from host-guest systems to 59 protein-ligand systems. However, the new radii are significantly smaller than the baseline radii and lead to excessively favorable hydration free energies (HFEs). Thus, users of the OBC2 GB model currently may choose between GB cavity radii that yield more accurate binding affinities and GB cavity radii that yield more accurate HFEs. We suspect that achieving good accuracy on both will require more far-reaching adjustments to the GB model. We note that binding free-energy calculations using the OBC2 model in OpenMM gain about a 10× speedup relative to corresponding explicit solvent calculations, suggesting a future role for implicit solvent absolute binding free-energy (ABFE) calculations in virtual compound screening. This study proves the principle of using host-guest systems to train potential functions that are transferrable to protein-ligand systems and provides an infrastructure that enables a range of applications.

The temperature-dependence of host-guest binding thermodynamics: experimental and simulation studies.

The thermodynamic parameters of host-guest binding can be used to describe, understand, and predict molecular recognition events in aqueous systems. However, interpreting binding thermodynamics remains challenging, even for these relatively simple molecules, as they are determined by both direct and solvent-mediated host-guest interactions. In this contribution, we focus on the contributions of water to binding by studying binding thermodynamics, both experimentally and computationally, for a series of nearly rigid, electrically neutral host-guest systems and report the temperature-dependent thermodynamic binding contributions ΔGb(T), ΔHb(T), ΔSb(T), and ΔCp,b. Combining isothermal titration calorimetry (ITC) measurements with molecular dynamics (MD) simulations, we provide insight into the binding forces at play for the macrocyclic hosts cucurbit[n]uril (CBn, n = 7-8) and ß-cyclodextrin (ß-CD) with a range of guest molecules. We find consistently negative changes in heat capacity on binding (ΔCp,b) for all systems studied herein - as well as for literature host-guest systems - indicating increased enthalpic driving forces for binding at higher temperatures. We ascribe these trends to solvation effects, as the solvent properties of water deteriorate as temperature rises. Unlike the entropic and enthalpic contributions to binding, with their differing signs and magnitudes for the classical and non-classical hydrophobic effect, heat capacity changes appear to be a unifying and more general feature of host-guest complex formation in water. This work has implications for understanding protein-ligand interactions and other complex systems in aqueous environments.

Elucidation of the Role of a Conserved Methionine in Glutamate Transporters and Its Implication for Force Fields.

Glutamate transport through the excitatory amino acid transporters is coupled to the cotransport of three Na+ ions, the binding sites (Na1-Na3) of which are conserved from archaea to mammalians. Molecular dynamics (MD) simulations reproduce the Na1 and Na3 binding sites observed in the crystal structures but fail in the case of Na2. A distinguishing feature of the Na2 site is that an S atom from a conserved methionine residue is in the coordination shell of Na+. We perform MD simulations on the recent GltTk structure and show that the problem with the Na2 site arises from using an inadequate partial charge for S. When methionine is appropriately parametrized, both the position and the binding free energy of Na+ at the Na2 site can be reproduced in good agreement with the experimental data. Other properties of methionine, such as its dipole moment and the solvation energy of its side chain analog, also benefit from this reparametrization. Thus, the Na2 site in glutamate transporters provides a good opportunity for a proper parametrization of methionine in MD force fields.

Computational Investigation of the Effect of Lipid Membranes on Ion Permeation in Gramicidin A.

Membrane proteins are embedded in a lipid bilayer and interact with the lipid molecules in subtle ways. This can be studied experimentally by examining the effect of different lipid bilayers on the function of membrane proteins. Understanding the causes of the functional effects of lipids is difficult to dissect experimentally but more amenable to a computational approach. Here we perform molecular dynamics simulations and free energy calculations to study the effect of two lipid types (POPC and NODS) on the conductance of the gramicidin A (gA) channel. A larger energy barrier is found for the K⁺ potential of mean force in gA embedded in POPC compared to that in NODS, which is consistent with the enhanced experimental conductance of cations in gA embedded in NODS. Further analysis of the contributions to the potential energy of K⁺ reveals that gA and water molecules in gA make similar contributions in both bilayers but there are significant differences between the two bilayers when the lipid molecules and interfacial waters are considered. It is shown that the stronger dipole moments of the POPC head groups create a thicker layer of interfacial waters with better orientation, which ultimately is responsible for the larger energy barrier in the K⁺ PMF in POPC.

Computational Studies of Glutamate Transporters.

Glutamate is the major excitatory neurotransmitter in the human brain whose binding to receptors on neurons excites them while excess glutamate are removed from synapses via transporter proteins. Determination of the crystal structures of bacterial aspartate transporters has paved the way for computational investigation of their function and dynamics at the molecular level. Here, we review molecular dynamics and free energy calculation methods used in these computational studies and discuss the recent applications to glutamate transporters. The focus of the review is on the insights gained on the transport mechanism through computational methods, which otherwise is not directly accessible by experimental probes. Recent efforts to model the mammalian glutamate and other amino acid transporters, whose crystal structures have not been solved yet, are included in the review.

Li-ion adsorption and diffusion on two-dimensional silicon with defects: a first principles study.

Using first principles calculations we investigate the binding and diffusion of Li on silicene and evaluate the prospects for application to Li-ion batteries. We find that the defect formation energy for silicene is half that of graphene, showing that silicene is more likely to contain defects. The overall lithium adsorption energy on silicene with defects is greater than the bulk cohesive energy of lithium giving stability for use in storage. Our results predict high mobility for lithium atoms on the surface of silicene with energy barriers in the range of 0.28-0.30 eV. Further, we find that the diffusion barrier through silicene is significantly lower than the diffusion barrier through graphene, with a value of 0.05 eV for the double vacancy and 0.88 eV for the single vacancy. The low diffusion barriers, both on the surface and through the hollow site, suggest a suitable material for use in Li-ion batteries.