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

Screening Power of End-Point Free-Energy Calculations in Cucurbituril Host-Guest Systems

End-point free-energy methods as an indispensable component in virtual screening are commonly recognized as a tool with a certain level of screening power in pharmaceutical research. While a huge number of records could be found for end-point applications in protein-ligand, protein-protein, and protein-DNA complexes from academic and industrial reports, up to now, there is no large-scale benchmark in host-guest complexes supporting the screening power of end-point free-energy techniques. A good benchmark requires a data set of sufficient coverage of pharmaceutically relevant chemical space, a long-time sampling length supporting the trajectory approximation of the ensemble average, and a sufficient sample size of receptor-acceptor pairs to stabilize the performance statistics. In this work, selecting a popular family of macrocyclic hosts named cucurbiturils, we construct a large data set containing 154 host-guest pairs, perform extensive end-point sampling of several hundred nanosecond lengths for each system, and extract the free-energy estimates with a variety of end-point free-energy techniques, including the advanced three-trajectory dielectric-constant-variable regime proposed in our recent work. The best-performing end-point protocol employs GAFF2 for solute descriptions, the three-trajectory end-point sampling regime, and the MM/GBSA Hamiltonian in free-energy extraction, achieving a high ranking metrics of Kendall τ > 0.6, a Pearlman predictive index of ∼0.8, and a high scoring power of Pearson r > 0.8. The current project as the first large-scale systematic benchmark of end-point methods in host-guest complexes in academic publications provides solid evidence of the applicability of end-point techniques and direct guidance of computational setups in practical host-guest systems.

Host Dynamics under General-Purpose Force Fields

Macrocyclic hosts as prototypical receptors to gaseous and drug-like guests are crucial components in pharmaceutical research. The external guests are often coordinated at the center of these macromolecular containers. The formation of host-guest coordination is accompanied by the broken of host-water and host-ion interactions and sometimes also involves some conformational rearrangements of the host. A balanced description of various components of interacting terms is indispensable. However, up to now, the modeling community still lacks a general yet detailed understanding of commonly employed general-purpose force fields and the host dynamics produced by these popular selections. To fill this critical gap, in this paper, we profile the energetics and dynamics of four types of popular macrocycles, including cucurbiturils, pillararenes, cyclodextrins, and octa acids. The presented investigations of force field definitions, refitting, and evaluations are unprecedently detailed. Based on the valuable observations and insightful explanations, we finally summarize some general guidelines on force field parametrization and selection in host-guest modeling.

A General Picture of Cucurbit[8]uril Host–Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamic feature of host–guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has an intermediate portal size and cavity volume. It can exploit almost all host–guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of seven commonly abused and structurally diverse drugs to the CB8 host was performed, and a general dynamic binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted with generalized force-matching to improve the intra-molecular conformational preference, and thus the description of inter-molecular host–guest interactions. The interaction pattern and binding thermodynamics show a significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host–guest binding.

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host–Guest Binding: III. Force-Field Comparison, Three-Trajectory Realization and Further Dielectric Augmentation

Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations.

Obstructing Salmonella typhi's virulence in eukaryotic cells through design of its SipB protein antagonists

Objective

Typhoid fever, a disease caused by Salmonella typhi, is a leading cause of morbidity and mortality, particularly in developing nations. The evolution of resistance mechanisms to existing antibiotics has necessitated a search for newer drug candidates. This study used computer aided drug design techniques to design novel antibiotics that function by antagonizing SipB, an effector protein of the bacterium that is responsible for its pathogenicity and virulence in eukaryotic host cells.

Methods

A data set of 32 bioactive molecules with established antibacterial activity against S. typhi was retrieved from the PubChem data base; optimized through a DFT approach in Spartan 14 software; and further subjected to QSAR modeling in BIOVIA-Accelrys Material Studio. The validated model (R² = 0.80, R² _Adj = 0.78, Q² _LOO = 0.74, R² _pred = 0.54, lack of fit = 0.07) revealed the dominant influence of MATS6c and E3p descriptors on the observed antibacterial activity of the compounds. Information from the model was used to optimize the structures of selected lead compounds in the data set, thus leading to the design of a highly potent set of novel analogues denoted D-1, D-2 and D-3.

Results

The predicted MIC values of D-1, D-2 and D-3 were 1.03, 0.73 and 0.30 μg/mL, respectively. Furthermore, molecular docking studies on these novel ligands against the active sites of SipB revealed binding energy values of -8.0, -7.7 and -7.7 kcal/mol for D-1, D-2 and D-3, respectively. These values were better than the -7.0 kcal/mol recorded for ciprofloxacin, the reference antibiotic used herein for quality assurance. In addition, drug-likeness and ADMET evaluation of the designed compounds revealed that they are orally bioavailable and exhibit excellent pharmacokinetic and toxicological profiles.

Conclusion

The current findings may provide a roadmap for the discovery of more potent antibiotics against S. typhi.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: II. regression and dielectric constant

End-point free energy calculations as a powerful tool have been widely applied in protein-ligand and protein-protein interactions. It is often recognized that these end-point techniques serve as an option of intermediate accuracy and computational cost compared with more rigorous statistical mechanic models (e.g., alchemical transformation) and coarser molecular docking. However, it is observed that this intermediate level of accuracy does not hold in relatively simple and prototypical host-guest systems. Specifically, in our previous work investigating a set of carboxylated-pillar[6]arene host-guest complexes, end-point methods provide free energy estimates deviating significantly from the experimental reference, and the rank of binding affinities is also incorrectly computed. These observations suggest the unsuitability and inapplicability of standard end-point free energy techniques in host-guest systems, and alteration and development are required to make them practically usable. In this work, we consider two ways to improve the performance of end-point techniques. The first one is the PBSA_E regression that varies the weights of different free energy terms in the end-point calculation procedure, while the second one is considering the interior dielectric constant as an additional variable in the end-point equation. By detailed investigation of the calculation procedure and the simulation outcome, we prove that these two treatments (i.e., regression and dielectric constant) are manipulating the end-point equation in a somehow similar way, i.e., weakening the electrostatic contribution and strengthening the non-polar terms, although there are still many detailed differences between these two methods. With the trained end-point scheme, the RMSE of the computed affinities is improved from the standard ~ 12 kcal/mol to ~ 2.4 kcal/mol, which is comparable to another altered end-point method (ELIE) trained with system-specific data. By tuning PBSA_E weighting factors with the host-specific data, it is possible to further decrease the prediction error to ~ 2.1 kcal/mol. These observations along with the extremely efficient optimized-structure computation procedure suggest the regression (i.e., PBSA_E as well as its GBSA_E extension) as a practically applicable solution that brings end-point methods back into the library of usable tools for host-guest binding. However, the dielectric-constant-variable scheme cannot effectively minimize the experiment-calculation discrepancy for absolute binding affinities, but is able to improve the calculation of affinity ranks. This phenomenon is somehow different from the protein-ligand case and suggests the difference between host-guest and biomacromolecular (protein-ligand and protein-protein) systems. Therefore, the spectrum of tools usable for protein-ligand complexes could be unsuitable for host-guest binding, and numerical validations are necessary to screen out really workable solutions in these 'prototypical' situations.

Seeding the multi-dimensional nonequilibrium pulling for Hamiltonian variation: indirect nonequilibrium free energy simulations at QM levels

The combination of free energy simulations in the alchemical and configurational spaces provides a feasible route to access the thermodynamic profiles under a computationally demanding target Hamiltonian. Normally, due to the significant differences between the computational cost of ab initio quantum mechanics (QM) calculations and those of semi-empirical quantum mechanics (SQM) and molecular mechanics (MM), this indirect method could be used to obtain the QM thermodynamics by combining the SQM or MM results and the SQM-to-QM or MM-to-QM corrections. In our previous work, a multi-dimensional nonequilibrium pulling framework for Hamiltonian variations was introduced based on bidirectional pulling and bidirectional reweighting. The method performs nonequilibrium free energy simulations in the configurational space to obtain the thermodynamic profile along the conformational change pathway under a selected computationally efficient Hamiltonian, and uses the nonequilibrium alchemical method to correct or perturb the thermodynamic profile to that under the target Hamiltonian. The BAR-based method is designed to achieve the best generality and transferability and thus leads to modest (∼20 fold) speedup. In this work, we explore the possibility of further accelerating the nonequilibrium free energy simulation by employing unidirectional pulling and using the selection criterion to obtain the initial configurations used to initiate nonequilibrium trajectories following the idea of adaptive steered molecular dynamics (ASMD). A single initial condition is used to seed the whole multi-dimensional nonequilibrium free energy simulation and the sampling is performed fully in the nonequilibrium ensemble. Introducing very short ps-length equilibrium sampling to grab more initial seeds could also be helpful. The ASMD scheme estimates the free energy difference with the unidirectional exponential average (EXP), but it does not follow exactly the requirements of the EXP estimator. Another deficiency of the seeding simulation is the inherently sequential or serial pulling due to the inter-segment dependency, which triggers some problems in the parallelizability of the simulation. Numerical tests are performed to grasp some insights and guidelines for using this selection-criterion-based ASMD scheme. The presented selection-criterion-based multi-dimensional ASMD scheme follows the same perturbation network of the BAR-based method, and thus could be used in various Hamiltonian-variation cases.

Correction Schemes for Absolute Binding Free Energies Involving Lipid Bilayers

Absolute binding free-energy (ABFE) calculations are playing an increasing role in drug design, especially as they can be performed on a range of disparate compounds and direct comparisons between them can be made. It is, however, especially important to ensure that they are as accurate as possible, as unlike relative binding free-energy (RBFE) calculations, one does not benefit as much from a cancellation of errors during the calculations. In most modern implementations of ABFE calculations, a particle mesh Ewald scheme is typically used to treat the electrostatic contribution to the free energy. A central requirement of such schemes is that the box preserves neutrality throughout the calculation. There are many ways to deal with this problem that have been discussed over the years ranging from a neutralizing plasma with a post hoc correction term through to a simple co-alchemical ion within the same box. The post hoc correction approach is the most widespread. However, the vast majority of these studies have been applied to a soluble protein in a homogeneous solvent (water or salt solution). In this work, we explore which of the more common approaches would be the most suitable for a simulation box with a lipid bilayer within it. We further develop the idea of the so-called Rocklin correction for lipid-bilayer systems and show how such a correction could work. However, we also show that it will be difficult to make this generalizable in a practical way and thus we conclude that the use of a “co-alchemical ion” is the most useful approach for simulations involving lipid membrane systems.

A General Picture of Cucurbit[8]uril Host-Guest Binding

Describing, understanding, and designing complex interaction networks within macromolecular systems remain challenging in modern chemical research. Host-guest systems, despite their relative simplicity in both the structural feature and interaction patterns, still pose problems in theoretical modeling. The barrel-shaped supramolecular container cucurbit[8]uril (CB8) shows promising functionalities in various areas, e.g., catalysis and molecular recognition. It can stably coordinate a series of structurally diverse guests with high affinities. In this work, we examine the binding of seven commonly abused drugs to the CB8 host, aiming at providing a general picture of CB8-guest binding. Extensive sampling of the configurational space of these host-guest systems is performed, and the binding pathway and interaction patterns of CB8-guest complexes are investigated. A thorough comparison of widely used fixed-charge models for drug-like molecules is presented. Iterative refitting of the atomic charges suggests significant conformation dependence of charge generation. The initial model generated at the original conformation could be inaccurate for new conformations explored during conformational search, and the newly fitted charge set improves the prediction-experiment correlation significantly. Our investigations of the configurational space of CB8-drug complexes suggest that the host-guest interactions are more complex than expected. Despite the structural simplicities of these molecules, the conformational fluctuations of the host and the guest molecules and orientations of functional groups lead to the existence of an ensemble of binding modes. The insights of the binding thermodynamics, performance of fixed-charge models, and binding patterns of the CB8-guest systems are useful for studying and elucidating the binding mechanism of other host-guest complexes.

DFT-D4 Insight into the Inclusion of Amphetamine and Methamphetamine in Cucurbit[7]uril: Energetic, Structural and Biosensing Properties

The host-guest interactions of cucurbit[7]uril (CB[7]) as host and amphetamine (AMP), methamphetamine (MET) and their enantiomeric forms (S-form and R-form) as guests were computationally investigated using density functional theory calculations with the recent D4 atomic-charge dependent dispersion corrections. The analysis of energetic, structural and electronic properties with the aid of frontier molecular orbital analysis, charge decomposition analysis (CDA), extended charge decomposition analysis (ECDA) and independent gradient model (IGM) approach allowed to characterize the host-guest interactions in the studied systems. Energetic results indicate the formation of stable non-covalent complexes where R-AMP@CB[7] and S-AMP@CB[7] are more stable thermodynamically than R-MET@CB[7] and S-MET@CB[7] in gas phase while the reverse is true in water solvent. Based on structural analysis, a recognition mechanism is proposed, which suggests that the synergistic effect of van der Waals forces, ion-dipole interactions, intermolecular charge transfer interactions and intermolecular hydrogen bonding is responsible for the stabilization of the complexes. The geometries of the complexes obtained theoretically are in good agreement with the X-ray experimental structures and indicate that the phenyl ring of amphetamine and methamphetamine is deeply buried into the cavity of CB[7] through hydrophobic interactions while the ammonium group remains outside the cavity to establish hydrogen bonds with the portal oxygen atoms of CB[7].

Conformational Fluctuations in GTP-Bound K-Ras: A Metadynamics Perspective with Harmonic Linear Discriminant Analysis

Biomacromolecules often undergo significant conformational rearrangements during function. In proteins, these motions typically consist in nontrivial, concerted rearrangement of multiple flexible regions. Mechanistic, thermodynamics, and kinetic predictions can be obtained via molecular dynamics simulations, provided that the simulation time is at least comparable to the relevant time scale of the process of interest. Because of the substantial computational cost, however, plain MD simulations often have difficulty in obtaining sufficient statistics for converged estimates, requiring the use of more-advanced techniques. Central in many enhanced sampling methods is the definition of a small set of relevant degrees of freedom (collective variables) that are able to describe the transitions between different metastable states of the system. The harmonic linear discriminant analysis (HLDA) has been shown to be useful for constructing low-dimensional collective variables in various complex systems. Here, we apply HLDA to study the free-energy landscape of a monomeric protein around its native state. More precisely, we study the K-Ras protein bound to GTP, focusing on two flexible loops and on the region associated with oncogenic mutations. We perform microsecond-long biased simulations on the wild type and on G12C, G12D, G12 V mutants, describe the resulting free-energy landscapes, and compare our predictions with previous experimental and computational studies. The fast interconversion between open and closed macroscopic states and their similar thermodynamic stabilities are observed. The mutation-induced effects include the alternations of the relative stabilities of different conformational states and the introduction of many microscopic metastable states. Together, our results demonstrate the applicability of the HLDA-based protocol for the conformational sampling of multiple flexible regions in folded proteins.

Recent Developments in Free Energy Calculations for Drug Discovery

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry.

Binding thermodynamics and interaction patterns of human purine nucleoside phosphorylase-inhibitor complexes from extensive free energy calculations

Human purine nucleoside phosphorylase (hPNP) plays a significant role in the catabolism of deoxyguanosine. The trimeric protein is an important target in the treatment of T-cell cancers and autoimmune disorders. Experimental studies on the inhibition of the hPNP observe that the first ligand bound to one of three subunits effectively inhibits the protein, while the binding of more ligands to the subsequent sites shows negative cooperativities. In this work, we performed extensive end-point and alchemical free energy calculations to determine the binding thermodynamics of the trimeric protein-ligand system. 13 Immucillin inhibitors with experimental results are under calculation. Two widely accepted charge schemes for small molecules including AM1-BCC and RESP are adopted for ligands. The results of RESP are in better agreement with the experimental reference. Further investigations of the interaction networks in the protein-ligand complexes reveal that several residues play significant roles in stabilizing the complex structure. The most commonly observed ones include PHE200, GLU201, MET219, and ASN243. The conformations of the protein in different protein-ligand complexes are observed to be similar. We expect these insights to aid the development of potent drugs targeting hPNP.

Testing automatic methods to predict free binding energy of host-guest complexes in SAMPL7 challenge

The design of new host–guest complexes represents a fundamental challenge in supramolecular chemistry. At the same time, it opens new opportunities in material sciences or biotechnological applications. A computational tool capable of automatically predicting the binding free energy of any host–guest complex would be a great aid in the design of new host systems, or to identify new guest molecules for a given host. We aim to build such a platform and have used the SAMPL7 challenge to test several methods and design a specific computational pipeline. Predictions will be based on machine learning (when previous knowledge is available) or a physics-based method (otherwise). The formerly delivered predictions with an RMSE of 1.67 kcal/mol but will require further work to identify when a specific system is outside of the scope of the model. The latter is combines the semiempirical GFN2B functional, with docking, molecular mechanics, and molecular dynamics. Correct predictions (RMSE of 1.45 kcal/mol) are contingent on the identification of the correct binding mode, which can be very challenging for host–guest systems with a large number of degrees of freedom. Participation in the blind SAMPL7 challenge provided fundamental direction to the project. More advanced versions of the pipeline will be tested against future SAMPL challenges.

Binding Thermodynamics and Interaction Patterns of Inhibitor-Major Urinary Protein-I Binding from Extensive Free-Energy Calculations: Benchmarking AMBER Force Fields

Mouse major urinary protein (MUP) plays a key role in the pheromone communication system. The one-end-closed β-barrel of MUP-I forms a small, deep, and hydrophobic central cavity, which could accommodate structurally diverse ligands. Previous computational studies employed old protein force fields and short simulation times to determine the binding thermodynamics or investigated only a small number of structurally similar ligands, which resulted in sampled regions far from the experimental structure, nonconverged sampling outcomes, and limited understanding of the possible interaction patterns that the cavity could produce. In this work, extensive end-point and alchemical free-energy calculations with advanced protein force fields were performed to determine the binding thermodynamics of a series of MUP-inhibitor systems and investigate the inter- and intramolecular interaction patterns. Three series of inhibitors with a total of 14 ligands were simulated. We independently simulated the MUP-inhibitor complexes under two advanced AMBER force fields. Our benchmark test showed that the advanced AMBER force fields including AMBER19SB and AMBER14SB provided better descriptions of the system, and the backbone root-mean-square deviation (RMSD) was significantly lowered compared with previous computational studies with old protein force fields. Surprisingly, although the latest AMBER force field AMBER19SB provided better descriptions of various observables, it neither improved the binding thermodynamics nor lowered the backbone RMSD compared with the previously proposed and widely used AMBER14SB. The older but widely used AMBER14SB actually achieved better performance in the prediction of binding affinities from the alchemical and end-point free-energy calculations. We further analyzed the protein-ligand interaction networks to identify important residues stabilizing the bound structure. Six residues including PHE38, LEU40, PHE90, ALA103, LEU105, and TYR120 were found to contribute the most significant part of protein-ligand interactions, and 10 residues were found to provide favorable interactions stabilizing the bound state. The two AMBER force fields gave extremely similar interaction networks, and the secondary structures also showed similar behavior. Thus, the intra- and intermolecular interaction networks described with the two AMBER force fields are similar. Therefore, AMBER14SB could still be the default option in free-energy calculations to achieve highly accurate binding thermodynamics and interaction patterns.