Host Guest Binding Affinities Research Articles

Supramolecular Annihilator with DPA Parallelly Arranged by Multiple Hydrogen-Bonding Interactions for Enhanced Triplet-Triplet Annihilation Upconversion.

The triplet annihilator is a critical component for triplet-triplet annihilation upconversion (TTA-UC); both the photophysical properties of the annihilator and the intermolecular orientation have pivotal effects on the overall efficiency of TTA-UC. Herein, we synthesized two supramolecular annihilators A-1 and A-2 by grafting 9,10-diphenylanthracene (DPA) fragments, which have been widely used as triplet annihilators for TTA-UC, on a macrocyclic host-pillar[5]arenes. In A-1, the orientation of the two DPA units was random, while, in A-2, the two DPA units were pushed to a parallel arrangement by intramolecular hydrogen-bonding interactions. The two compounds showed very similar photophysical properties and host-guest binding affinities toward electron-deficient guests, but showed totally different TTA-UC emissions. The UC quantum yield of A-2 could be optimized to 13.7% when an alkyl ammonia chain-attaching sensitizer S-2 was used, while, for A-1, only 5.1% was achieved. Destroying the hydrogen-bonding interactions by adding MeOH to A-2 significantly decreased the UC emissions, demonstrating that the parallel orientations of the two DPA units contributed greatly to the TTA-UC emissions. These results should be beneficial for annihilator designs and provide a new promising strategy for enhancing TTA-UC emissions.

Exploiting the Mechanical Bond Effect for Enhanced Molecular Recognition and Sensing.

The ubiquity of charged species in biological and industrial processes has resulted in ever-increasing interest in their selective recognition, detection, and environmental remediation. Building on the established coordination chemistry principles of the chelate and macrocyclic effects, and host preorganization, supramolecular chemists seek to construct specific 3D binding cavities reminiscent of biotic systems to enhance host-guest binding affinity and selectivity. Mechanically interlocked molecules (MIMs) present a wholly unique platform for synthetic host design, wherein topologies afforded by the mechanical bond enable the decoration of 3D cavities for non-covalent interactions with a range of target guest geometries. Notably, MIM host systems exhibit mechanical bond effect augmented affinities and selectivities for a variety of charged guest species, compared to non-interlocked acyclic and macrocycle host analogs. Furthermore, the modular nature of MIM synthesis facilitates incorporation of optical and electrochemical reporter groups, enabling fabrication of highly sensitive and specific molecular sensors. This review discusses the development of recognition and sensing MIMs, from the first reports in the late 20th century through to the present day, delineating how their topologically preorganized and dynamic host cavities enhance charged guest recognition and sensing, demonstrating the mechanical bond effect as a potent tool in future chemosensing materials.

How are N-methylcarbamates encapsulated by β-cyclodextrin: insight into the binding mechanism.

Guest molecules containing chromophore groups encapsulated by β-cyclodextrin (β-CD) generate circular dichroism (CD) signals, which enables a preliminary prediction of their binding modes. However, the accurate determination of the representative binding conformation (RC) remains a challenging task due to the complex conformational space of these host-guest systems. Here, we combine a molecular dynamics/quantum mechanics/continuum solvent model (MD/QM/CSM) with induced circular dichroism (ICD) data (N. L. Pacioni, A. B. Pierini and A. V. Veglia, Spectrochim. Acta A Mol. Biomol. Spectrosc., 2013, 103, 319-324.) to explore the binding mechanism of β-CD with four N-methylcarbamate molecules: promecarb (PC), bendiocarb (BC), carbaryl (CY) and carbofuran (CF). In aqueous solution, their stability decreases as: PC > BC > CY > CF. Comparing the ECD spectra computed from TD-DFT with the ICD data can help eliminate many common binding configurations and identify the RC. The host-guest binding affinities (BAs) estimated using a ONIOM2(B971:PM6)/SMD model reproduce the measured binding trend, reveal the competition between the non-covalent interaction and solvent effect and explain the large difference in their binding modes. We also examine the fluctuations in the computed BA using similar structures.

CASTING: A Potent Supramolecular Strategy to Cytosolically Deliver STING Agonist for Cancer Immunotherapy and SARS-CoV-2 Vaccination

CASTING: A Potent Supramolecular Strategy to Cytosolically Deliver STING Agonist for Cancer Immunotherapy and SARS-CoV-2 Vaccination

Application of the alchemical transfer and potential of mean force methods to the SAMPL8 host-guest blinded challenge.

We report the results of our participation in the SAMPL8 GDCC Blind Challenge for host-guest binding affinity predictions. Absolute binding affinity prediction is of central importance to the biophysics of molecular association and pharmaceutical discovery. The blinded SAMPL series have provided an important forum for assessing the reliability of binding free energy methods in an objective way. In this challenge, we employed two binding free energy methods, the newly developed alchemical transfer method (ATM) and the well-established potential of mean force (PMF) physical pathway method, using the same setup and force field model. The calculated binding free energies from the two methods are in excellent quantitative agreement. Importantly, the results from the two methods were also found to agree well with the experimental binding affinities released subsequently, with R values of 0.89 (ATM) and 0.83 (PMF). These results were ranked among the best of the SAMPL8 GDCC challenge and second only to those obtained with the more accurate AMOEBA force field. Interestingly, the two host molecules included in the challenge (TEMOA and TEETOA) displayed distinct binding mechanisms, with TEMOA undergoing a dehydration transition whereas guest binding to TEETOA resulted in the opening of the binding cavity that remains essentially dry during the process. The coupled reorganization and hydration equilibria observed in these systems is a useful prototype for the study of these phenomena often observed in the formation of protein-ligand complexes. Given that the two free energy methods employed here are based on entirely different thermodynamic pathways, the close agreement between the two and their general agreement with the experimental binding free energies are a testament to the high quality and precision achieved by theory and methods. The study provides further validation of the novel ATM binding free energy estimation protocol and paves the way to further extensions of the method to more complex systems.

Precise Assembly and Supramolecular Catalysis of Tetragonal- and Trigonal-Elongated Octahedral Coordination Containers

The construction of distorted or irregular coordination polyhedrons with specific shapes and functionalities is highly challenging. Here, we demonstrate a viable strategy for attaining a severely d...

Electron-rich Coordination Receptors Based on Tetrathiafulvalene Derivatives: Controlling the Host-Guest Binding.

The coordination-driven self-assembly methodology has emerged over the last few decades as an extraordinarily versatile synthetic tool for obtaining discrete macrocyclic or cage structures. Rational approaches using large libraries of ligands and metal complexes have allowed researchers to reach more and more sophisticated discrete structures such as interlocked, chiral, or heteroleptic cages, and some of them are designed for guest binding applications. Efforts have been notably produced in controlling host-guest affinity with, in particular, an evident interest in targeting substrate transportation and subsequent delivering. Recent accomplishments in this direction were described from functional cages which can be addressed with light, pH, or through a chemical exchange. The case of a redox-stimulation has been much less explored. In this case, the charge state of the redox-active cavity can be controlled through an applied electrical potential or introduction of an appropriate oxidizing/reducing chemical agent. Beyond possible applications in electrochemical sensing for environmental and medical sciences as well as for redox catalysis, controlling the cavity charge offers the possibility to modulate the host-guest binding affinity through electrostatic interactions, up to the point of disassembly of the host-guest complex, i.e., releasing of the guest molecule from the host cavity.This Account highlights the key studies that we carried out at Angers, related to discrete redox-active coordination-based architectures (i.e., metalla-rings, -cages, and -tweezers). These species are built upon metal-driven self-assembly between electron-rich ligands, based on the tetrathiafulvalene (TTF) moiety (as well as some of its S-rich derivatives), and various metal complexes. Given the high π-donating character of those ligands, the corresponding host structures exhibit a high electronic density on the cavity panels. This situation is favorable to bind complementary electron-poor guests, as it was illustrated with bis(pyrrolo)tetrathiafulvalene (BPTTF)-based cavities, which exhibit hosting properties for C60 or tetrafluorotetracyanoquinodimethane (TCNQ-F4). In addition to the pristine tetrathiafulvalene, which was successfully incorporated into palladium- or ruthenium-based architectures, the case of the so-called extended tetrathiafulvalene (exTTF) appears particularly fascinating. A series of related polycationic and neutral M4L2 ovoid containers, as well as a M6L3 cage, were synthesized, and their respective binding abilities for neutral and anionic guests were studied. Remarkably, such structures allow to control of the binding of the guest upon a redox-stimulation, through two distinctive processes: (i) cage disassembling or (ii) guest displacement. As an extension of this approach, metalla-assembled electron-rich tweezers were designed, which are able to trigger the guest release through an original process based on supramolecular dimerization activated through a redox stimulus. This ensemble of results illustrates the remarkable ability of electron-rich, coordination-based self-assembled cavities to bind various types of guests and, importantly, to trigger their release through a redox-stimulus.

SAMPL7 TrimerTrip host-guest binding affinities from extensive alchemical and end-point free energy calculations.

The prediction of host-guest binding affinities with computational modelling is still a challenging task. In the 7th statistical assessment of the modeling of proteins and ligands (SAMPL) challenge, a new host named TrimerTrip was synthesized and the thermodynamic parameters of 16 structurally diverse guests binding to the host were characterized. In the TrimerTrip-guest challenge, only structures of the host and the guests are provided, which indicates that the predictions of both the binding poses and the binding affinities are under assessment. In this work, starting from the binding poses obtained from our previous enhanced sampling simulations in the configurational space, we perform extensive alchemical and end-point free energy calculations to calculate the host-guest binding affinities retrospectively. The alchemical predictions with two widely accepted charge schemes (i.e. AM1-BCC and RESP) are in good agreement with the experimental reference, while the end-point estimates perform poorly in reproducing the experimental binding affinities. Aside from the absolute value of the binding affinity, the rank of binding free energies is also crucial in drug design. Surprisingly, the end-point MM/PBSA method seems very powerful in reproducing the experimental rank of binding affinities. Although the length of our simulations is long and the intermediate spacing is dense, the convergence behavior is not very good, which may arise from the flexibility of the host molecule. Enhanced sampling techniques in the configurational space may be required to obtain fully converged sampling. Further, as the length of sampling in alchemical free energy calculations already achieves several hundred ns, performing direct simulations of the binding/unbinding event in the physical space could be more useful and insightful. More details about the binding pathway and mechanism could be obtained in this way. The nonequilibrium method could also be a nice choice if one insists to use the alchemical method, as the intermediate sampling is avoided to some extent.

SAMPL6 host-guest binding affinities and binding poses from spherical-coordinates-biased simulations.

Host-guest binding is a challenging problem in computer simulation. The prediction of binding affinities between hosts and guests is an important part of the statistical assessment of the modeling of proteins and ligands (SAMPL) challenges. In this work, the volume-based variant of well-tempered metadynamics is employed to calculate the binding affinities of the host-guest systems in the SAMPL6 challenge. By biasing the spherical coordinates describing the relative position of the host and the guest, the initial-configuration-induced bias vanishes and all possible binding poses are explored. The agreement between the predictions and the experimental results and the observation of new binding poses indicate that the volume-based technique serves as a nice candidate for the calculation of binding free energies and the search of the binding poses.

Dynamic Supramolecular Hydrogels Spanning an Unprecedented Range of Host-Guest Affinity.

Cucurbit[7]uril (CB[7]) macrocycles exhibit a broad range of host-guest binding affinity. Attaching pendant CB[7] and complementary guests on 8-arm PEG macromers affords supramolecular hydrogels with cross-link affinity spanning more than 5 orders of magnitude (1.5 × 107 to 5.4 × 1012 M-1) without changing network topology. Cross-link affinity translates directly to bulk dynamic properties; hydrogels with high-affinity cross-linking behave like covalent gels with limited ability to relax or self-heal. Cross-link affinity furthermore dictates the release rate of encapsulated macromolecules, as well as cell infiltration and material clearance in vivo. This work thus informs a role for affinity in dictating supramolecular hydrogel properties by quantifying and isolating this feature over an unprecedented range.

Overview of the SAMPL6 host-guest binding affinity prediction challenge.

Accurately predicting the binding affinities of small organic molecules to biological macromolecules can greatly accelerate drug discovery by reducing the number of compounds that must be synthesized to realize desired potency and selectivity goals. Unfortunately, the process of assessing the accuracy of current computational approaches to affinity prediction against binding data to biological macromolecules is frustrated by several challenges, such as slow conformational dynamics, multiple titratable groups, and the lack of high-quality blinded datasets. Over the last several SAMPL blind challenge exercises, host-guest systems have emerged as a practical and effective way to circumvent these challenges in assessing the predictive performance of current-generation quantitative modeling tools, while still providing systems capable of possessing tight binding affinities. Here, we present an overview of the SAMPL6 host-guest binding affinity prediction challenge, which featured three supramolecular hosts: octa-acid (OA), the closely related tetra-endo-methyl-octa-acid (TEMOA), and cucurbit[8]uril (CB8), along with 21 small organic guest molecules. A total of 119 entries were received from ten participating groups employing a variety of methods that spanned from electronic structure and movable type calculations in implicit solvent to alchemical and potential of mean force strategies using empirical force fields with explicit solvent models. While empirical models tended to obtain better performance than first-principle methods, it was not possible to identify a single approach that consistently provided superior results across all host-guest systems and statistical metrics. Moreover, the accuracy of the methodologies generally displayed a substantial dependence on the system considered, emphasizing the need for host diversity in blind evaluations. Several entries exploited previous experimental measurements of similar host-guest systems in an effort to improve their physical-based predictions via some manner of rudimentary machine learning; while this strategy succeeded in reducing systematic errors, it did not correspond to an improvement in statistical correlation. Comparison to previous rounds of the host-guest binding free energy challenge highlights an overall improvement in the correlation obtained by the affinity predictions for OA and TEMOA systems, but a surprising lack of improvement regarding root mean square error over the past several challenge rounds. The data suggests that further refinement of force field parameters, as well as improved treatment of chemical effects (e.g., buffer salt conditions, protonation states), may be required to further enhance predictive accuracy.

A Linear Interaction Energy Model for Cavitand Host–Guest Binding Affinities

Host-guest systems provide excellent models to explore molecular recognition in solution along with relevant technological applications from drug carriers to chemosensors. Here, we present a linear interaction energy (LIE) model to predict the binding affinity in host-guests with remarkable efficiency and predictive power. Using four host families, including cucurbiturils, octa acids, and β-cyclodextrin, and a large set (49) of chemically diverse guests, we demonstrate that binding-affinity predictions with a root mean square error <1.5 kcal/mol from experiments can be obtained with a few nanoseconds of molecular dynamics. The parameters of the LIE model are shown to be transferable among host-guest families, and the quality of the predictionsis essentially force-field independent. Inclusion of the strain energy of the host in the bound state appears to be critically important to improve the quality of the predictions, particularly when the host and the guest have comparable sizes. Unsuccesful predictions for 28 additional highly charged and bulky guests to cucurbit[7]uril indicate future directions for improvement.

Pillar[5]arene-Diketopyrrolopyrrole Fluorescent Copolymer: A Promising Recognition and Adsorption Material for Adiponitrile by Selective Formation of a Conjugated Polypseudorotaxane.

Conjugated pillar[5]arene-diketopyrrolopyrrole copolymer (P1) is synthesized by the copolymerization of a difunctionalized pillar[5]arene and a diketopyrrolopyrrole-based monomer, which shows large extinction coefficients (1.1 × 104 m-1 cm-1 ) at 519 nm and strong emission at 587 nm. P1 exhibits very strong host-guest binding affinity towards adiponitrile but low binding affinity towards 1,4-dihalobutane and 1,4-bis(imidazol-1-yl)butane. Such an enhanced selectivity is first found in the polypseudorotaxane between pillararene and neutral guests in organic solution and is successfully used for the recognition and adsorption of adiponitrile by the formation of a P1-adiponitrile polypseudorotaxane.

On the fly estimation of host-guest binding free energies using the movable type method: participation in the SAMPL5 blind challenge.

We review our performance in the SAMPL5 challenge for predicting host-guest binding affinities using the movable type (MT) method. The challenge included three hosts, acyclic Cucurbit[2]uril and two octa-acids with and without methylation at the entrance to their binding cavities. Each host was associated with 6-10 guest molecules. The MT method extrapolates local energy landscapes around particular molecular states and estimates the free energy by Monte Carlo integration over these landscapes. Two blind submissions pairing MT with variants of the KECSA potential function yielded mean unsigned errors of 1.26 and 1.53kcal/mol for the non-methylated octa-acid, 2.83 and 3.06kcal/mol for the methylated octa-acid, and 2.77 and 3.36kcal/mol for Cucurbit[2]uril host. While our results are in reasonable agreement with experiment, we focused on particular cases in which our estimates gave incorrect results, particularly with regard to association between the octa-acids and an adamantane derivative. Working on the hypothesis that differential solvation effects play a role in effecting computed binding affinities for the parent octa-acid and the methylated octa-acid and that the ligands bind inside the pockets (rather than on the surface) we devised a new solvent accessible surface area term to better quantify solvation energy contributions in MT based studies. To further explore this issue a, molecular dynamics potential of mean force (PMF) study indicates that, as found by our docking calculations, the stable binding mode for this ligand is inside (rather than surface bound) the octa-acid cavity whether the entrance is methylated or not. The PMF studies also obtained the correct order for the methylation-induced change in binding affinities and associated the difference, to a large extent to differential solvation effects. Overall, the SAMPL5 challenge yielded in improvements our solvation modeling and also demonstrated the need for thorough validation of input data integrity prior to any computational analysis.

Prediction of SAMPL4 host–guest binding affinities using funnel metadynamics

Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110:6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host-guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300-400 ns per ligand, we show that the errors due to inadequate sampling are below 1 kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11 kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system.

Accurate Method To Quantify Binding in Supramolecular Chemistry

An approach for accurate and comparable measurement of host-guest binding affinities is introduced whereby differences in binding strength (ΔlogKass values) are measured between two host molecules toward a particular guest under identical solvent conditions. Measuring differences instead of absolute values enables obtaining highly accurate results, because many of the uncertainty sources (the solvation/association state of the guest in solution, deviations in solvent composition, etc.) cancel out. As a proof of concept, this method was applied to the measurement of the binding strength of 28 synthetic anion receptors toward acetate in acetonitrile containing 0.5% water. The receptors included differently substituted indolocarbazoles, ureas, thioureas, and some others. Possible deprotonation of more acidic receptors of each compound class by acetate was checked by measuring their acidities (ΔpKa values) relative to acetic acid in the same solvent. A self-consistent (consistency standard deviation 0.04 log units) binding affinity scale ranging for around 2.7 log units was constructed from the results. Absolute logKass values were found by anchoring the scale to the absolute logKass values of two receptor molecules, determined independently by direct measurements. This new approach is expected to find use in accurate quantification of a wide range of binding processes relevant to supramolecular chemistry.

Calculation of Host-Guest Binding Affinities Using a Quantum-Mechanical Energy Model.

The prediction of protein-ligand binding affinities is of central interest in computer-aided drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies suggesting that available force fields may be a key source of error motivate the present study, which reports the first mining minima (M2) binding affinity calculations based on a quantum mechanical energy model, rather than an empirical force field. We apply a semi-empirical quantum-mechanical energy function, PM6-DH+, coupled with the COSMO solvation model, to 29 host-guest systems with a wide range of measured binding affinities. After correction for a systematic error, which appears to derive from the treatment of polar solvation, the computed absolute binding affinities agree well with experimental measurements, with a mean error 1.6 kcal/mol and a correlation coefficient of 0.91. These calculations also delineate the contributions of various energy components, including solute energy, configurational entropy, and solvation free energy, to the binding free energies of these host-guest complexes. Comparison with our previous calculations, which used empirical force fields, point to significant differences in both the energetic and entropic components of the binding free energy. The present study demonstrates successful combination of a quantum mechanical Hamiltonian with the M2 affinity method.

SAMPL3: blinded prediction of host–guest binding affinities, hydration free energies, and trypsin inhibitors

This special issue of the Journal of Computer-Aided Molecular Design is the culmination of the 4th Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge and workshop. SAMPL3 had three datasets: blinded small-molecule hydration energies, provided by Peter Guthrie [1]; two novel host–guest systems, including eleven unpublished binding energies, provided by Adam Urbach and Lyle Issacs [2], and a monumental dataset including structural and affinity data for 500 fragments against Trypsin, provided by Tom Peat [3]. The SAMPL3 workshop saw over 40 attendees while the SAMPL3 challenge received 103 submissions from 23 participating groups using a variety of methods including: discrete and dynamic conformational sampling; implicit, semi-implicit and explicit water models; and myriad of force-fields and charge models. Gilson [2] and Geballe [1] have provided summaries of the host–guest challenge and solvation-energy challenge respectively. As with prior SAMPL challenges, many different approaches generated high-quality predictions yet no single technique distinguished itself significantly. Nevertheless, many important insights into the strengths and limitations of computational and experimental methods were developed through SAMPL. SAMPL3 was the first blinded challenge to include prediction of host–guest binding affinities. Host–guest binding affinities provided an outstanding blind challenge, as they are simple enough to encourage participants to recognize, explore and address assumptions and errors. Most participants had great difficulty modeling the aspartyl-protease-like formal charges found in the host molecules. This is concerning, for while ionization sites occur commonly in protein–ligand systems, rarely are they addressed at the level of detail participants found necessary for this host–guest system. More host–guest examples should be included in future SAMPL challenges as their streamlined nature highlights assumptions that can be too easily overlooked. SAMPL is one of several projects that provide blinded or prospective experimental challenges to the computational community [4–6]. These projects are intended to serve as both a guidepost for computational progress and a meeting ground for experimental and computational scientist. However, it has been a struggle to generate mutual interest between computational and experimental scientists. This year, SAMPL had a breakthrough in the form of Lyle Issacs (host–guest affinities) and Tom Peat (trypsin structures and affinities). Lyle and Tom are experimentalists who provided data to SAMPL3, attended the SAMPL workshop, and provided insights and challenges to the computational scientists. We hope they are the first of many experimentalists to join SAMPL and challenge theorists with their data. Unfortunately, no experimental collaborator has emerged to provide prospective hydration free energies, which have been part of each of the four SAMPL evaluations. Hydration energies are the most basic measure of the solvation of molecules in water. Aqueous solvation plays a critical role in most biophysical and biochemical phenomenon, and our ability to accurately predict biophysical processes is limited by our ability to accurately calculate solvation interactions. Hydration energies represent one of the simplest experiments that allow us to evaluate these predictions. As a consequence, comparison to hydration energies is a fundamental tool for evaluating force fields and electrostatic models (for example see [7]). A. G. Skillman (&) OpenEye Scientific Software, Santa Fe, NM, USA e-mail: skillman@eyesopen.com

Blind prediction of host–guest binding affinities: a new SAMPL3 challenge

The computational prediction of protein-ligand binding affinities is of central interest in early-stage drug-discovery, and there is a widely recognized need for improved methods. Low molecular weight receptors and their ligands--i.e., host-guest systems--represent valuable test-beds for such affinity prediction methods, because their small size makes for fast calculations and relatively facile numerical convergence. The SAMPL3 community exercise included the first ever blind prediction challenge for host-guest binding affinities, through the incorporation of 11 new host-guest complexes. Ten participating research groups addressed this challenge with a variety of approaches. Statistical assessment indicates that, although most methods performed well at predicting some general trends in binding affinity, overall accuracy was not high, as all the methods suffered from either poor correlation or high RMS errors or both. There was no clear advantage in using explicit versus implicit solvent models, any particular force field, or any particular approach to conformational sampling. In a few cases, predictions using very similar energy models but different sampling and/or free-energy methods resulted in significantly different results. The protonation states of one host and some guest molecules emerged as key uncertainties beyond the choice of computational approach. The present results have implications for methods development and future blind prediction exercises.

Thermodynamic integration to predict host-guest binding affinities

An alchemical free energy method with explicit solvent molecular dynamics simulations was applied as part of the blind prediction contest SAMPL3 to calculate binding free energies for seven guests to an acyclic cucurbit-[n]uril host. The predictions included determination of protonation states for both host and guests, docking pose generation, and binding free energy calculations using thermodynamic integration. We found a root mean square error (RMSE) of 3.6 kcal mol(-1) from the reference experimental results, with an R(2) correlation of 0.51. The agreement with experiment for the largest contributor to this error, guest 6, is improved by 1.7 kcal mol(-1) when a periodicity-induced free energy correction is applied. The corrections for the other ligands were significantly smaller, and altogether the RMSE was reduced by 0.4 kcal mol(-1). We link properties of the host-guest systems during simulation to errors in the computed free energies. Overall, we show that charged host-guest systems studied here, initialized in unconfirmed docking poses, present a challenge to accurate alchemical simulation methods.