Targeting mechanism for SARS-CoV-2 in silico: interaction and key groups of TMPRSS2 toward four potential drugs.

The global dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seriously endangered human health. The number of confirmed cases is still increasing; however, treatment options are limited. Transmembrane protease serine 2 (TMPRSS2), as a key protease that primes the binding of SARS-CoV-2 spike protein and angiotensin-converting enzyme 2 (ACE2), has become an attractive target and received widespread attention. Thus, four potential drugs (bromhexine, camostat, gabexate, and nafamostat) were used to explore the mechanism of binding with TMPRSS2 in this work. A 65 ns molecular dynamics simulation was performed three times for each drug-TMPRSS2 system for reliable energy calculation and conformational analysis, of which the simulations of nafamostat-TMPRSS2 systems were further extended to 150 ns three times due to the discovery of two binding modes. Through the results of calculating binding free energy by nine methods, the binding affinity of camostat, gabexate, and nafamostat to TMPRSS2 showed great advantages compared with bromhexine, where the nafamostat was surprisingly found to present two reasonable binding conformations (forward and reverse directions). Two negatively charged amino acids (Asp435 and Glu299) can clamp the two positively charged groups (guanidinium group and amidinium group) in either forward or reverse fashion, and the forward one is more stable than the reverse. In addition, compared with gabexate, the dimethylamino group in camostat forms more van der Waals interactions with surrounding hot-spots His296 and Val280, resulting in a stronger affinity to TMPRSS2. For bromhexine, multiple binding sites are displayed in the binding pocket due to its small molecular structure, and van der Waals interactions play the dominant role in the binding process. In particular, six typical hot-spots were identified in the last three serine protease inhibitor systems, i.e., Asp435, Ser436, Gln438, Trp461, Ser463, and Gly464. The guanidinium groups of the drugs have powerful interactions with adjacent residues due to the formation of more hydrogen bonds, suggesting that this may be the critical site for drug design against TMPRSS2. This work provides valuable molecular insight into these four drug-TMPRSS2 binding mechanisms and is helpful for designing and screening drugs targeting TMPRSS2.

Inhibition mechanism and hot-spot prediction of nine potential drugs for SARS-CoV-2 Mpro by large-scale molecular dynamic simulations combined with accurate binding free energy calculations.

Coronavirus disease 2019 (COVID-19), which is caused by a new coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading around the world. However, a universally effective treatment regimen has not been developed to date. The main protease (Mpro), a key enzyme of SARS-CoV-2, plays a crucial role in the replication and transcription of this virus in cells and has become the ideal target for rational antiviral drug design. In this study, we performed molecular dynamics simulations three times for these complexes of Mpro (monomeric and dimeric) and nine potential drugs that have a certain effect on the treatment of COVID-19 to explore their binding mechanism. In addition, a total of 12 methods for calculating binding free energy were employed to determine the optimal drug. Ritonavir, Arbidol, and Chloroquine consistently showed an outstanding binding ability to monomeric Mpro under various methods. Ritonavir, Arbidol, and Saquinavir presented the best performance when binding to a dimer, which was independent of the protonated state of Hie41 (protonated at Nε) and Hid41 (protonated at Nδ), and these findings suggest that Chloroquine may not effectively inhibit the activity of dimeric Mproin vivo. Furthermore, three common hot-spot residues of Met165, Hie41, and Gln189 of monomeric Mpro systems dominated the binding of Ritonavir, Arbidol, and Chloroquine. In dimeric Mpro, Gln189, Met165, and Met49 contributed significantly to binding with Ritonavir, Arbidol, and Saquinavir; therefore, Gln189 and Met165 might serve as the focus in the discovery and development of anti-COVID-19 drugs. In addition, the van der Waals interaction played a significant role in the binding process, and the benzene ring of the drugs showed an apparent inhibitory effect on the normal function of Mpro. The binding cavity had great flexibility to accommodate these different drugs. The results would be notably helpful for enabling a detailed understanding of the binding mechanisms for these important drug-Mpro interactions and provide valuable guidance for the design of potent inhibitors.

Computational analysis of binding free energies, hotspots and the binding mechanism of Bcl-xL/Bcl-2 binding to Bad/Bax.

The anti-apoptotic proteins B-cell lymphoma-extra large (Bcl-xL) and B-cell lymphoma/leukemia-2 (Bcl-2) are members of the Bcl-2 protein family, and they play important roles in regulating apoptosis and cell cycle retardation. However, the binding mechanisms of Bcl-xL/Bcl-2 with their associated agonists, including Bcl-2-associated death promoter (Bad) and Bcl-2-associated X protein (Bax), are not well understood. In the present study, the recently developed interaction entropy approach was employed for the calculation of entropic contribution, and the computational alanine scanning method was used to identify the hot spot in the protein-protein interactions between Bcl-xL/Bcl-2 and Bad/Bax. The calculated binding free energies and their ranks for the four systems were in good agreement with the experimental results. Computational analysis shows that there are more hot-spot residues in the Bcl-xL/Bad complex than that in the Bcl-xL/Bax complex, leading to a stronger binding affinity in the former. It is interesting to find that the reason for the stronger binding affinity of Bcl-2 to Bad than to Bax is different for the Bcl-xL system. Although there are more hot-spot residues in the Bcl-2/Bax system than in the Bcl-2/Bad complex, there are also more negatively contributing residues in the Bcl-2/Bax. Our study identified Arg104, Tyr105, Leu116, and Leu134 to be the common key residues in the Bcl-xL complexes, and Arg107, Tyr108, Phe112, Gln118, Leu137, Arg146, and Tyr202 are common key residues in the Bcl-2 complexes. These results would provide valuable information for the design of potent inhibitors of Bcl-xL/Bcl-2.

Alanine scanning combined with interaction entropy studying the differences of binding mechanism on HIV-1 and HIV-2 proteases with inhibitor.

Quantitative characterization of binding affinity in protein-ligand and residue-ligand is critical for understanding binding mechanisms of protein-ligand and predicting hot-spot residues. In this paper, binding free energies between two HIV (HIV-1 and HIV-2) proteases and four inhibitors are calculated by molecular mechanics/generalized Born surface area (MM/GBSA) combined with the newly developed interaction entropy (IE) approach. The internal dielectric constant is set on the basis of different types of amino acids. The entropy change in protein-ligand binding is computed by IE method which is superior to the traditional normal mode (Nmode) method in the analysis of the ranking of binding free energy, statistical stability and enthalpy-entropy compensation. Importantly, IE method combined with alanine scanning is applied to calculate residue-specific binding free energy. And the calculated total binding free energy using the current method is in excellent with the experimental observed. Our research indicates that HIV-1 and HIV-2 proteases share the common hot-spot residues with ILE50/50' and ILE84/ILE84' which provide the major favorable contribution to the binding of protein and inhibitor in all systems. The predicted hot-spot residues are more in HIV-1 complex than HIV-2 complex and some hot-spot residues contributing to HIV-1 don't play a significant role in HIV-2. To some extent, this explains the reason of decrease in potency inhibitors against HIV-2 compared to HIV-1 protease. The study is expected to understand quantitatively the binding mechanism of HIV-inhibitor and provide important theoretical guidance for the design of equipotent HIV-1/HIV-2 protease inhibitors.Communicated by Ramaswamy H. Sarma.

An accurate free energy estimator: based on MM/PBSA combined with interaction entropy for protein-ligand binding affinity.

The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method is constantly used to calculate the binding free energy of protein-ligand complexes, and has been shown to effectively balance computational cost against accuracy. The relative binding affinities obtained by the MM/PBSA approach are acceptable, while it usually overestimates the absolute binding free energy. This paper proposes four free energy estimators based on the MM/PBSA for enthalpy change combined with interaction entropy (IE) for entropy change using different weights for individual energy terms. The ΔGPBSA_IE method is determined to be an optimal estimator based on its performance in terms of the correlation between experimental and theoretical values and error estimations. This approach is optimized using high-quality experimental values from a training set containing 84 protein-ligand systems, and the coefficients for the sum of electrostatic energy and polar solvation free energy, van der Waals (vdW) energy, non-polar solvation energy and entropy change are obtained by multivariate linear fitting to the corresponding experimental values. A comparison between the traditional MM/PBSA method and this method shows that the correlation coefficient is improved from 0.46 to 0.72 and the slope of the regression line increases from 0.10 to 1.00. More importantly, the mean absolute error (MAE) is significantly reduced from 22.52 to 1.59 kcal mol-1. Furthermore, the numerical stability of this method is validated on a test set with a similar correlation coefficient, slope and MAE to those of the training set. Based on the above advantages, the ΔGPBSA_IE method can be a powerful tool for a reliable and accurate estimation of binding free energy and plays a significant role in a detailed energetic investigation of protein-ligand interaction.

Entropic effect and residue specific entropic contribution to the cooperativity in streptavidin-biotin binding.

Molecular dynamics (MD) simulations were performed employing the polarized protein-specific charge (PPC) to explore the origin of the cooperativity in streptavidin-biotin systems (wild type, two single mutations and one double-mutation). The results of the experiment found that the existence of cooperativity is mainly the result of the entropic effect. In this study, the entropic contribution to the binding free energy was calculated using the recently developed interaction entropy (IE) method, and computational results are in excellent agreement with the experimental observations and are further verified by the calculation of the thermodynamic integration. Comparison of different force fields in terms of predicted binding strength ordering, cooperativity of energy and the stability of hydrogen bonding suggests that the PPC force field combined IE method is a suitable choice. In addition, the IE method enables us to obtain the residue-specific entropic contributions to the streptavidin-biotin binding affinity and identify ten hot-spot residues providing the dominant contribution to the cooperative binding. Importantly, the overall cooperativity obtained from the ten residues also comes mainly from the entropic effect in our study. The calculation of the potential of mean force shows that the unbinding of streptavidin-biotin is a multi-step process, and each step corresponds to the formation and rupture of the hydrogen bond network. And S45A mutation may increase the rigidity of the linker region, making the flap region relatively difficult to open. The present study provides significant molecular insight into the binding cooperativity of the streptavidin-biotin complex.

Improving the performance of the MM/PBSA and MM/GBSA methods in recognizing the native structure of the Bcl-2 family using the interaction entropy method.

In the research and development of new drugs, theoretical and computational studies play an increasingly important role in discriminating native and decoy structures by their binding free energies. Predicting the binding free energy using the molecular mechanics/Poisson-Boltzmann (Generalized Born) surface area (MM/PB(GB)SA) methods to identify the native structure as the lowest-energy conformation is more theoretically rigorous than most scoring functions, but the main challenge of this method is the calculation of the entropic contribution. In this study, we add the entropic contribution to the MM/PBSA and two MM/GBSA (GBHCT and GBOBC1) models using the interaction entropy (IE) method. We then systemically evaluate the performance of these methods in recognizing the native structures by predicting the binding affinities of 176 protein-ligand and protein-protein systems of the Bcl-2 family. By calculating a series of statistical metrics, sensitivity, specificity, accuracy, Matthews correlation coefficient, the G-mean, and the receiver operating characteristic (ROC) curve, we find that the ability to discern the native structure from a decoy ensemble is improved significantly by the modification of the binding free energy using the IE method in both protein-ligand and protein-protein systems. Furthermore, the maximum area under the ROC curve (AUC) was 0.97, which was obtained by the GBHCT model combined with the IE method, indicating that this method has the best performance. The largest improvement occurs in the PB method, with a change in the AUC of 0.32. The modification of the energy is more obvious for protein-protein interactions than for protein-ligand interactions. This study indicates the effectiveness of the IE method in successfully recognizing the native structure, which is critical in rational drug design.

Drug-resistance mechanisms of three mutations in anaplastic lymphoma kinase against two inhibitors based on MM/PBSA combined with interaction entropy.

As a promising drug target in the treatment of lung cancer, anaplastic lymphoma kinase (ALK) and its mutations have been studied widely through the development of multiple generations of inhibitors. Experiments have found that compared with the wild-type, the L1198F and C1156Y/L1198F mutations resulted in resistance to 5P8 inhibitors, and the C1156Y mutation resulted in resistance to VGH inhibitors. In this study, the newly developed interaction entropy (IE) method combined with the polarized protein-specific charge (PPC) force field was utilized to explore the origin of the resistance mechanism of the ALK mutant system. The calculated binding free energy was consistent with the experimental results. Per-residue binding free energy decomposition showed that the predicted hot-spot residues (LEU1122, LEU/PHE1198, MET1199, GLY1202 and LEU1256) were almost identical across systems. Especially, the GLU1197 residue played an important role in inducing drug-resistance for both inhibitors. The electrostatic interaction of GLU1197, PHE1198 and MET1199 mainly resulted in the resistances of the L1198F and C1156Y/L1198F mutations to 5P8. And the van der Waals interaction energy of LEU1256 residue, and electrostatic energy and entropy change of GLU1197 resulted in the resistances of the C1156Y mutations to VGH. The indicated origins of the drug-resistance in the ALK systems provide a theoretical foundation for the design of potent inhibitors.

Binding Mechanism of Thrombin-Ligand Systems Investigated by a Polarized Protein-Specific Charge Force Field and Interaction Entropy Method.

In this study, 2 groups of 10 modified ligand systems with modified P3 and P2 side chains are used to study the binding mechanism with thrombin. Experimental results show that the binding affinity is enhanced by complex ligand side chains. The binding free energy obtained from the polarized protein-specific charge (PPC) force field combined with the newly developed interaction entropy (IE) method is consistent with the experimental values with a high correlation coefficient. On the contrary, poor correlation is obtained using the traditional normal mode (Nmode) method for calculating the entropy change. Furthermore, the binding free energy and hot-spot residue energy are decomposed, and the common hot-spot residues in the two groups of systems are Trp50, Leu96, Ile179, Asp199, Cyx201, Ser226, Trp227, Gly228, and Gly230. The electrostatic and van der Waals interaction energies were found to be the main contributors in the binding energy difference. CH-π and CH-CH interactions of Leu96 ligands are significantly related to the energy change due to the modified side chain, and the hydrogen bond between Asp199 and the ligand provides a strong electrostatic interaction, contributing to the binding free energy. Investigating the B-factor, principal component, and binding pocket also explains the change in the binding affinity caused by the modified side chains in ligands from the viewpoint of conformational change. This study demonstrates that the new IE method is superior to the Nmode method in the predicting binding free energy and emphasizes the importance of electronic polarization in molecular dynamics simulation. Moreover, from the viewpoint of energy and structure analysis, this study reveals the origin of the change in binding free energy in modified ligands with different binding sites.

Metal-Templated Design: Enantioselective Hydrogen-Bond-Driven Catalysis Requiring Only Parts-per-Million Catalyst Loading.

Based on a metal-templated approach using a rigid and globular structural scaffold in the form of a bis-cyclometalated octahedral iridium complex, an exceptionally active hydrogen-bond-mediated asymmetric catalyst was developed and its mode of action investigated by crystallography, NMR, computation, kinetic experiments, comparison with a rhodium congener, and reactions in the presence of competing H-bond donors and acceptors. Relying exclusively on weak forces, the enantioselective conjugate reduction of nitroalkenes can be executed at catalyst loadings as low as 0.004 mol% (40 ppm), representing turnover numbers of up to 20 250. A rate acceleration by the catalyst of 2.5 × 10(5) was determined. The origin of the catalysis is traced to an effective stabilization of developing charges in the transition state by carefully orchestrated hydrogen-bonding and van der Waals interactions between catalyst and substrates. This study demonstrates that the proficiency of asymmetric catalysis merely driven by hydrogen-bonding and van der Waals interactions can rival traditional activation through direct transition metal coordination of the substrate.