An Effective MM/GBSA Protocol for Absolute Binding Free Energy Calculations: A Case Study on SARS-CoV-2 Spike Protein and the Human ACE2 Receptor

The binding free energy calculation of protein–ligand complexes is necessary for research into virus–host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the molecular mechanics generalized Born surface area (MM/GBSA) framework allows for efficient calculations without significant loss of accuracy. Here, GBNSR6, a new flavor of the generalized Born model, is employed in the MM/GBSA framework for measuring the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor. A computational protocol is developed based on the widely studied Ras–Raf complex, which has similar binding free energy to SARS-CoV-2/ACE2. Two options for representing the dielectric boundary of the complexes are evaluated: one based on the standard Bondi radii and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein–ligand binding. Predictions based on the two radii sets provide upper and lower bounds on the experimental references: −14.7(ΔGbindBondi)<−10.6(ΔGbindExp.)<−4.1(ΔGbindOPT1) kcal/mol. The consensus estimates of the two bounds show quantitative agreement with the experiment values. This work also presents a novel truncation method and computational strategies for efficient entropy calculations with normal mode analysis. Interestingly, it is observed that a significant decrease in the number of snapshots does not affect the accuracy of entropy calculation, while it does lower computation time appreciably. The proposed MM/GBSA protocol can be used to study the binding mechanism of new variants of SARS-CoV-2, as well as other relevant structures.     

Solvation Free Energy Calculations: The Combination between the Implicitly Polarized Fixed-charge Model and the Reference Potential Strategy

The IPolQ-Mod charges, which are the average of two charge sets fitted in vacuum state and condensed phase, take account of polarization effect implicitly in the solvation free energy calculation. However, the performance of the IPolQ-Mod charges sensitively depends on the QM levels used to generate the electrostatic potential from which the charges are fitted. In addition, the forces on atoms are not accurate theoretically in the molecular dynamics (MD) simulation as the solvent only feels the electrostatic potential of a half-polarized density of the solute according to the derivation of the IPolQ-Mod charges. To study these issues in detail, the IPolQ-Mod charges are combined with the reference potential (RP) strategy to predict the solvation free energies in the present study. It is found that the thermodynamic perturbation (TP) corrections utilizing total energy difference and interaction energy difference are almost the same and free of bias. The solvation free energies estimated by the RP method match very well with those obtained by applying IPolQ-Mod charges into MD simulation directly. By means of the RP strategy, the performances of the IPolQ-Mod charges with the change of the strength of the exact HF exchange in several DFT functionals are determined effectively. Although the “optimal” strengths are found in B3LYP and LC-ωPBE, the improvements over the default strength are not too much. In addition to the IPolQ-Mod charges, other charge models like bond charge correction (BCC) charges could also be combined with the RP strategy to study the thermodynamic properties like solvation free energy. © 2019 Wiley Periodicals, Inc.     

Docking,Binding Free Energy Calculations and In Vitro Characterization of Pyrazine Linked 2-Aminobenzamides as Novel Class I Histone Deacetylase (HDAC) Inhibitors

Class I histone deacetylases, HDAC1, HDAC2, and HDAC3, represent potential targets for cancer treatment. However, the development of isoform-selective drugs for these enzymes remains challenging due to their high sequence and structural similarity. In the current study, we applied a computational approach to predict the selectivity profile of developed inhibitors. Molecular docking followed by MD simulation and calculation of binding free energy was performed for a dataset of 2-aminobenzamides comprising 30 previously developed inhibitors. For each HDAC isoform, a significant correlation was found between the binding free energy values and in vitro inhibitory activities. The predictive accuracy and reliability of the best preforming models were assessed on an external test set of newly designed and synthesized inhibitors. The developed binding free-energy models are cost-effective methods and help to reduce the time required to prioritize compounds for further studies.     

Binding Free Energy (BFE) Calculations and Quantitative Structure–Activity Relationship (QSAR) Analysis of Schistosoma mansoni Histone Deacetylase 8 (smHDAC8) Inhibitors

Histone-modifying proteins have been identified as promising targets to treat several diseases including cancer and parasitic ailments. In silico methods have been incorporated within a variety of drug discovery programs to facilitate the identification and development of novel lead compounds. In this study, we explore the binding modes of a series of benzhydroxamates derivatives developed as histone deacetylase inhibitors of Schistosoma mansoni histone deacetylase (smHDAC) using molecular docking and binding free energy (BFE) calculations. The developed docking protocol was able to correctly reproduce the experimentally established binding modes of resolved smHDAC8–inhibitor complexes. However, as has been reported in former studies, the obtained docking scores weakly correlate with the experimentally determined activity of the studied inhibitors. Thus, the obtained docking poses were refined and rescored using the Amber software. From the computed protein–inhibitor BFE, different quantitative structure–activity relationship (QSAR) models could be developed and validated using several cross-validation techniques. Some of the generated QSAR models with good correlation could explain up to ~73% variance in activity within the studied training set molecules. The best performing models were subsequently tested on an external test set of newly designed and synthesized analogs. In vitro testing showed a good correlation between the predicted and experimentally observed IC₅₀ values. Thus, the generated models can be considered as interesting tools for the identification of novel smHDAC8 inhibitors.     

In Silico Study towards Repositioning of FDA-Approved Drug Candidates for Anticoronaviral Therapy: Molecular Docking,Molecular Dynamics and Binding Free Energy Calculations

The SARS-CoV-2 targets were evaluated for a set of FDA-approved drugs using a combination of drug repositioning and rigorous computational modeling methodologies such as molecular docking and molecular dynamics (MD) simulations followed by binding free energy calculations. Six FDA-approved drugs including, Ouabain, Digitoxin, Digoxin, Proscillaridin, Salinomycin and Niclosamide with promising anti-SARS-CoV-2 activity were screened in silico against four SARS-CoV-2 proteins—papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), SARS-CoV-2 main protease (Mpro), and adaptor-associated kinase 1 (AAK1)—in an attempt to define their promising targets. The applied computational techniques suggest that all the tested drugs exhibited excellent binding patterns with higher scores and stable complexes compared to the native protein cocrystallized inhibitors. Ouabain was suggested to act as a dual inhibitor for both PLpro and Mpro enzymes, while Digitoxin bonded perfectly to RdRp. In addition, Salinomycin targeted PLpro. Particularly, Niclosamide was found to target AAK1 with greater affinity compared to the reference drug. Our study provides comprehensive molecular-level insights for identifying or designing novel anti-COVID-19 drugs.     

Binding Energies of the π‐Stacked Anisole Dimer: New Molecular Beam—Laser Spectroscopy Experiments and CCSD(T) Calculations

Among noncovalent interactions, π–π stacking is a very important binding motif governed mainly by London dispersion. Despite its importance, for instance, for the structure of bio‐macromolecules, the direct experimental measurement of binding energies in π–π stacked complexes has been elusive for a long time. Only recently, an experimental value for the binding energy of the anisole dimer was presented, determined by velocity mapping ion imaging in a two‐photon resonant ionisation molecular beam experiment. However, in that paper, a discrepancy was already noted between the obtained experimental value and a theoretical estimate. Here, we present an accurate recalculation of the binding energy based on the combination of the CCSD(T)/CBS interaction energy and a DFT‐D3 vibrational analysis. This proves unambiguously that the previously reported experimental value is too high and a new series of measurements with a different, more sensitive apparatus was performed. The new experimental value of 1800±100 cm^?1 (5.15±0.29 kcal mol^?1) is close to the present theoretical prediction of 5.04±0.40 kcal mol^?1. Additional calculations of the properties of the cationic and excited states involved in the photodissociation of the dimer were used to identify and rationalise the difficulties encountered in the experimental work.     

Converging free energy estimates: MM-PB(GB)SA studies on the protein-protein complex Ras-Raf

Estimating protein-protein interaction energies is a very challenging task for current simulation protocols. Here, absolute binding free energies are reported for the complex H-Ras/C-Raf1 using the MM-PB(GB)SA approach, testing the internal consistency and model dependence of the results. Averaging gas-phase energies (MM), solvation free energies as determined by Generalized Born models (GB/SA), and entropic contributions calculated by normal mode analysis for snapshots obtained from 10 ns explicit-solvent molecular dynamics in general results in an overestimation of the binding affinity when a solvent-accessible surface area-dependent model is used to estimate the nonpolar solvation contribution. Applying the sum of a cavity solvation free energy and explicitly modeled solute-solvent van der Waals interaction energies instead provides less negative estimates for the nonpolar solvation contribution. When the polar contribution to the solvation free energy is determined by solving the Poisson-Boltzmann equation (PB) instead, the calculated binding affinity strongly depends on the atomic radii set chosen. For three GB models investigated, different absolute deviations from PB energies were found for the unbound proteins and the complex. As an alternative to normal-mode calculations, quasiharmonic analyses have been performed to estimate entropic contributions due to changes of solute flexibility upon binding. However, such entropy estimates do not converge after 10 ns of simulation time, indicating that sampling issues may limit the applicability of this approach. Finally, binding free energies estimated from snapshots of the unbound proteins extracted from the complex trajectory result in an underestimate of binding affinity. This points to the need to exercise caution in applying the computationally cheaper "one-trajectory-alternative" to systems where there may be significant changes in flexibility and structure due to binding. The best estimate for the binding free energy of Ras-Raf obtained in this study of -8.3 kcal mol(-1) is in good agreement with the experimental result of -9.6 kcal mol(-1), however, further probing the transferability of the applied protocol that led to this result is necessary.     

Ultra-Large-Scale Screening of Natural Compounds and Free Energy Calculations Revealed Potential Inhibitors for the Receptor-Binding Domain (RBD) of SARS-CoV-2

The emergence of immune-evading variants of SARS-CoV-2 further aggravated the ongoing pandemic. Despite the deployments of various vaccines, the acquired mutations are capable of escaping both natural and vaccine-induced immune responses. Therefore, further investigation is needed to design a decisive pharmacological treatment that could efficiently block the entry of this virus into cells. Hence, the current study used structure-based methods to target the RBD of the recombinant variant (Deltacron) of SARS-CoV-2, which was used as a model variant. From the virtual drug screenings of various databases, a total of four hits were identified as potential lead molecules. Key residues were blocked by these molecules with favorable structural dynamic features. The binding free energies further validated the potentials of these molecules. The TBE for MNP was calculated to be −32.86 ± 0.10 kcal/mol, for SANC00222 the TBE was −23.41 ± 0.15 kcal/mol, for Liriodenine the TBE was −34.29 ± 0.07 kcal/mol, while for Carviolin the TBE was calculated to be −27.67 ± 0.12 kcal/mol. Moreover, each complex demonstrated distinct internal motion and a free energy profile, indicating a different strategy for the interaction with and inhibition of the RBD. In conclusion, the current study demands further in vivo and in vitro validation for the possible usage of these compounds as potential drugs against SARS-CoV-2 and its variants.     

Solvent models for protein–ligand binding: Comparison of implicit solvent poisson and surface generalized born models with explicit solvent simulations

Solvent effects play a crucial role in mediating the interactions between proteins and their ligands. Implicit solvent models offer some advantages for modeling these interactions, but they have not been parameterized on such complex problems, and therefore, it is not clear how reliable they are. We have studied the binding of an octapeptide ligand to the murine MHC class I protein using both explicit solvent and implicit solvent models. The solvation free energy calculations are more than 10³ faster using the Surface Generalized Born implicit solvent model compared to FEP simulations with explicit solvent. For some of the electrostatic calculations needed to estimate the binding free energy, there is near quantitative agreement between the explicit and implicit solvent model results; overall, the qualitative trends in the binding predicted by the explicit solvent FEP simulations are reproduced by the implicit solvent model. With an appropriate choice of reference system based on the binding of the discharged ligand, electrostatic interactions are found to enhance the binding affinity because the favorable Coulomb interaction energy between the ligand and protein more than compensates for the unfavorable free energy cost of partially desolvating the ligand upon binding. Some of the effects of protein flexibility and thermal motions on charging the peptide in the solvated complex are also considered. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 591–607, 2001     

Supramolecular Arrangement and DFT analysis of Zinc(II) Schiff Bases: An Insight towards the Influence of Compartmental Ligands on Binding Interaction with Protein

We report, for the first time, a detailed crystallographic study of the supramolecular arrangement for a set of zinc(II) Schiff base complexes containing the ligand 2,6-bis((E)-((2-(dimethylamino)ethyl)imino)methyl)-4-R-phenol], where R=methyl/tert-butyl/chloro. The supramolecular study acts as a pre-screening tool for selecting the compartmental ligand R of the Schiff base for effective binding with a targeted protein, bovine serum albumin (BSA). The most stable hexagonal arrangement of the complex [Zn − Me] (R=Me) stabilises the ligand with the highest FMO energy gap (ΔE=4.22 eV) and lowest number of conformations during binding with BSA. In contrast, formation of unstable 3D columnar vertebra for [Zn − Cl] (R=Cl) tend to activate the system with lowest FMO gap (3.75 eV) with highest spontaneity factor in molecular docking. Molecular docking analyses reported in terms of 2D LigPlot+ identified site A, a cleft of domains IB, IIIA and IIIB, as the most probable protein binding site of BSA. Arg144, Glu424, Ser428, Ile455 and Lys114 form the most probable interactions irrespective of the type of compartmental ligands R of the Schiff base whereas Arg185, Glu519, His145, Ile522 act as the differentiating residues with ΔG=−7.3 kcal mol⁻¹.     

Hot spot computational identification: Application to the complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10

The definition and comprehension of the hot spots in an interface is a subject of primary interest for a variety of fields, including structure‐based drug design. Therefore, to achieve an alanine mutagenesis computational approach that is at the same time accurate and predictive, capable of reproducing the experimental mutagenesis values is a major challenge in the computational biochemistry field. Antibody/protein antigen complexes provide one of the greatest models to study protein–protein recognition process because they have three fundamentally features: specificity, high complementary association and a small epitope restricted to the diminutive complementary determining regions (CDR) region, while the remainder of the antibody is largely invariant. Thus, we apply a computational mutational methodological approach to the study of the antigen–antibody complex formed between the hen egg white lysozyme (HEL) and the antibody HyHEL‐10. A critical evaluation that focuses essentially on the limitations and advantages between different computational methods for hot spot determination, as well as between experimental and computational methodological approaches, is presented. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Competition between (18, 18) and (18, 16) Configurations in Ni2(CO)5: An Isomerization Energy Decomposition Analysis

The potential energy landscape of the neutral Ni$_2$(CO)$_5$ complex was re-examined. A new $C_{\rm{2v}}$ structure with double bridging carbonyls is found to compete with the previously proposed triply carbonyl-bridged $D_{\rm{3h}}$ isomer for the global minimum of Ni$_2$(CO)$_5$. Despite that the tri-bridged isomer possesses the more favored (18, 18) configuration, where both metal centers satisfy the 18-electron rule, the neutral Ni$_2$(CO)$_5$ complex prefers the di-bridged geometry with (18, 16) configuration. The isomerization energy decomposition analysis reveals that the structural preference is a consequence of the maximization of electrostatic and orbital interactions.     

Comparative study of kinetics isomerization of substituted polyacetylene (Cl,F and I): Ab initio and DFT calculations

Ab initio and DFT methods were used to investigate the interconversions of substituted polyacetylene conformers C₁₀H₆X₆ (X=F, Cl and I) in the vapour phase. The rates of this geometrical isomerization have been calculated and the Arrhenius parameters evaluated. In the case of unsubstituted polyacetylene as the reference, the B3LYP Arrhenius parameters obtained are A₁=2.99 × 10¹⁷ s^–1 and E_a=17.30 kcal mol^–1. The values of the equilibrium constant for the reaction have also been determined at various temperatures between 300 and 500 K and the value of the energies change calculated. The results also suggest that the straightforward kinetics characterizing the majority of substituted polyacetylene isomerizations above 300 K. The isomerization energies are positive and the barrier heights ΔE_barrier are expected to be sensitive for the magnitude of halogens effects. According to geometries features the Cis → Trans isomerization in the gas phase occurs by a rotational mechanism.