A precise swaying map for how promiscuous cellobiose-2-epimerase operate bi-reaction.

Promiscuous enzymes play a crucial role in organism survival and new reaction mining. However, comprehensive mapping of the catalytic and regulatory mechanisms hasn't been well studied due to the characteristic complexity. The cellobiose 2-epimerase from Caldicellulosiruptor saccharolyticus (CsCE) with complex epimerization and isomerization was chosen to comprehensively investigate the promiscuous mechanisms. Here, the catalytic frame of ring-opening, cis-enediol mediated catalysis and ring-closing was firstly determined. To map the full view of promiscuous CE, the structure of CsCE complex with the isomerized product glucopyranosyl-ß1,4-fructose was determined. Combined with computational calculation, the promiscuity was proved a precise cooperation of the double subsites, loop rearrangement, and intermediate swaying. The flexible loop was like a gear, whose structural reshaping regulates the sway of the intermediates between the two subsites of H377-H188 and H377-H247, and thus regulates the catalytic directions. The different protonated states of cis-enediol intermediate catalyzed by H188 were the key point for the catalysis. The promiscuous enzyme tends to utilize all elements at hand to carry out the promiscuous functions.

Combined Antibodies Evusheld against the SARS-CoV-2 Omicron Variants BA.1.1 and BA.5: Immune Escape Mechanism from Molecular Simulation.

The Omicron lineage of SARS-CoV-2, which was first reported in November 2021, has spread globally and become dominant, splitting into several sublineages. Experiments have shown that Omicron lineage has escaped or reduced the activity of existing monoclonal antibodies, but the origin of escape mechanism caused by mutation is still unknown. This work uses molecular dynamics and umbrella sampling methods to reveal the escape mechanism of BA.1.1 to monoclonal antibody (mAb) Tixagevimab (AZD1061) and BA.5 to mAb Cilgavimab (AZD8895), both mAbs were combined to form antibody cocktail, Evusheld (AZD7442). The binding free energy of BA.1.1-AZD1061 and BA.5-AZD8895 has been severely reduced due to multiple-site mutated Omicron variants. Our results show that the two Omicron variants, which introduce a substantial number of positively charged residues, can weaken the electrostatic attraction between the receptor binding domain (RBD) and AZD7442, thus leading to a decrease in affinity. Additionally, using umbrella sampling along dissociation pathway, we found that the two Omicron variants severely impaired the interaction between the RBD of SARS-CoV-2's spike glycoprotein (S protein) and complementary determining regions (CDRs) of mAbs, especially in CDR3H. Although mAbs AZD8895 and AZD1061 are knocked out by BA.5 and BA.1.1, respectively, our results confirm that the antibody cocktail AZD7442 retains activity against BA.1.1 and BA.5 because another antibody is still on guard. The study provides theoretical insights for mAbs interacting with BA.1.1 and BA.5 from both energetic and dynamic perspectives, and we hope this will help in developing new monoclonals and combinations to protect those unable to mount adequate vaccine responses.

Binding of berberine derivates to G-quadruplex: insight from a computational study.

Human telomerase exhibits significant activity in cancer cells relative to normal cells, which contributes to the immortal proliferation of cancer cells. To counter this, the stabilization of G-quadruplexes formed in the guanine-rich sequence of the cancer cell chromosome has emerged as a promising avenue for anti-cancer therapy. Berberine (BER), an alkaloid that is derived from traditional Chinese medicines, has shown potential for stabilizing G-quadruplexes. To investigate the atomic interactions between G-quadruplexes and BER and its derivatives, molecular dynamics simulations were conducted. Modeling the interactions between G-quadruplexes and ligands accurately is challenging due to the strong negative charge of nucleic acids. Thus, various force fields and charge models for the G-quadruplex and ligands were tested to obtain precise simulation results. The binding energies were calculated by a combination of molecular mechanics/generalized Born surface area and interaction entropy methods, and the calculated results correlated well with experimental results. B-factor and hydrogen bond analyses demonstrated that the G-quadruplex was more stable in the presence of ligands than in the absence of ligands. Calculation of the binding free energy showed that the BER derivatives bind to a G-quadruplex with higher affinity than that of BER. The breakdown of the binding free energy to per-nucleotide energies suggested that the first G-tetrad played a primary role in binding. Additionally, energy and geometric properties analyses indicated that van der Waals interactions were the most favorable interactions between the derivatives and the G-quadruplexes. Overall, these findings provide crucial atomic-level insights into the binding of G-quadruplexes and their inhibitors.

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.

Molecular Modelling of Ionic Liquids: Situations When Charge Scaling Seems Insufficient.

Charge scaling as an effective solution to the experiment-computation disagreement in molecular modelling of ionic liquids (ILs) could bring the computational results close to the experimental reference for various thermodynamic properties. According to the large-scale benchmark calculations of mass density, solvation, and water-ILs transfer-free energies in our series of papers, the charge-scaling factor of 0.8 serves as a near-optimal option generally applicable to most ILs, although a system-dependent parameter adjustment could be attempted for further improved performance. However, there are situations in which such a charge-scaling treatment would fail. Namely, charge scaling cannot really affect the simulation outcome, or minimally perturbs the results that are still far from the experimental value. In such situations, the vdW radius as an additional adjustable parameter is commonly tuned to minimize the experiment-calculation deviation. In the current work, considering two ILs from the quinuclidinium family, we investigate the impacts of this vdW-scaling treatment on the mass density and the solvation/partition thermodynamics in a fashion similar to our previous charge-scaling works, i.e., scanning the vdW-scaling factor and computing physical properties under these parameter sets. It is observed that the mass density exhibits a linear response to the vdW-scaling factor with slopes close to -1.8 g/mL. By further investigating a set of physiochemically relevant temperatures between 288 K and 348 K, we confirm the robustness of the vdW-scaling treatment in the estimation of bulk properties. The best vdW-scaling parameter for mass density would worsen the computation of solvation/partition thermodynamics, and a marginal decrease in the vdW-scaling factor is considered as an intermediate option balancing the reproductions of bulk properties and solvation thermodynamics. These observations could be understood in a way similar to the charge-scaling situation. i.e., overfitting some properties (e.g., mass density) would degrade the accuracy of the other properties (e.g., solvation free energies). Following this principle, the general guideline for applying this vdW-tuning protocol is by using values between the density-derived choice and the solvation/partition-derived solution. The charge and current vdW scaling treatments cover commonly encountered ILs, completing the protocol for accurate modelling of ILs with fixed-charge force fields.

Rational Design of a Highly Specific Prolyl Endopeptidase To Activate the Antihypertensive Effect of Peptides.

Enzymatic hydrolysis of food-derived proteins to produce bioactive peptides could activate food functions such as antihypertension. However, the diversity of enzymatic hydrolysis products can reduce bioactive peptides' efficacy. Highly specific proteases can homogenize the hydrolysis products to reduce the production of impotent peptides. In this study, we successfully obtained M. xanthus prolyl endopeptidase mutant Y451M by constraint/free molecular dynamics simulations and binding energy calculations. The specificity of Y451M for proline was increased by 286 % compared to WT, while its activity was almost unchanged. Milk-derived substrates processed with Y451M showed an antihypertensive effect that was 567 % higher than without enzymes. The ability to activate food antihypertension increased 152 % and the use of enzyme by 192 % compared with WT. Specific proteases are thus valuable tools in the processing of complex substrates to obtain bioactive peptides.

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.

A fast-slow method to treat solute dynamics in explicit solvent.

Aiming to reduce the computational cost in the current explicit solvent molecular dynamics (MD) simulation, this paper proposes a fast-slow method for the fast MD simulation of biomolecules in explicit solvent. This fast-slow method divides the entire system into two parts: a core layer (typically solute or biomolecule) and a peripheral layer (typically solvent molecules). The core layer is treated using standard MD method but the peripheral layer is treated by a slower dynamics method to reduce the computational cost. We compared four different simulation models in testing calculations for several small proteins. These include gas-phase, implicit solvent, fast-slow explicit solvent and standard explicit solvent MD simulations. Our study shows that gas-phase and implicit solvent models do not provide a realistic solvent environment and fail to correctly produce reliable dynamic structures of proteins. On the other hand, the fast-slow method can essentially reproduce the same solvent effect as the standard explicit solvent model while gaining an order of magnitude in efficiency. This fast-slow method thus provides an efficient approach for accelerating the MD simulation of biomolecules in explicit solvent.

Immune Escape Mechanisms of SARS-CoV-2 Delta and Omicron Variants against Two Monoclonal Antibodies That Received Emergency Use Authorization.

Multiple-site mutated SARS-CoV-2 Delta and Omicron variants may trigger immune escape against existing monoclonal antibodies. Here, molecular dynamics simulations combined with the interaction entropy method reveal the escape mechanism of Delta/Omicron variants to Bamlanivimab/Etesevimab. The result shows the significantly reduced binding affinity of the Omicron variant for both antibodies, due to the introduction of positively charged residues that greatly weaken their electrostatic interactions. Meanwhile, significant structural deflection induces fewer atomic contacts and an unstable binding mode. As for the Delta variant, the reduced binding affinity for Bamlanivimab is owing to the alienation of the receptor-binding domain to the main part of this antibody, and the binding mode of the Delta variant to Etesevimab is similar to that of the wild type, suggesting that Etesevimab could still be effective against the Delta variant. We hope this work will provide timely theoretical insights into developing antibodies to prevalent and possible future variants of SARS-CoV-2.

Computational Insights into the Binding Mechanism of OxyS sRNA with Chaperone Protein Hfq.

Under the oxidative stress condition, the small RNA (sRNA) OxyS that acts as essential post-transcriptional regulators of gene expression is produced and plays a regulatory function with the assistance of the RNA chaperone Hfq protein. Interestingly, experimental studies found that the N48A mutation of Hfq protein could enhance the binding affinity with OxyS while resulting in the defection of gene regulation. However, how the Hfq protein interacts with sRNA OxyS and the origin of the stronger affinity of N48A mutation are both unclear. In this paper, molecular dynamics (MD) simulations were performed on the complex structure of Hfq and OxyS to explore their binding mechanism. The molecular mechanics generalized born surface area (MM/GBSA) and interaction entropy (IE) method were combined to calculate the binding free energy between Hfq and OxyS sRNA, and the computational result was correlated with the experimental result. Per-residue decomposition of the binding free energy revealed that the enhanced binding ability of the N48A mutation mainly came from the increased van der Waals interactions (vdW). This research explored the binding mechanism between Oxys and chaperone protein Hfq and revealed the origin of the strong binding affinity of N48A mutation. The results provided important insights into the mechanism of gene expression regulation affected by protein mutations.

Anchor-Locker Binding Mechanism of the Coronavirus Spike Protein to Human ACE2: Insights from Computational Analysis.

COVID-19 has emerged as the most serious international pandemic in early 2020 and the lack of comprehensive knowledge in the recognition and transmission mechanisms of this virus hinders the development of suitable therapeutic strategies. The specific recognition during the binding of the spike glycoprotein (S protein) of coronavirus to the angiotensin-converting enzyme 2 (ACE2) in the host cell is widely considered the first step of infection. However, detailed insights on the underlying mechanism of dynamic recognition and binding of these two proteins remain unknown. In this work, molecular dynamics simulation and binding free energy calculation were carried out to systematically compare and analyze the receptor-binding domain (RBD) of six coronavirus' S proteins. We found that affinity and stability of the RBD from SARS-CoV-2 under the binding state with ACE2 are stronger than those of other coronaviruses. The solvent-accessible surface area (SASA) and binding free energy of different RBD subunits indicate an "anchor-locker" recognition mechanism involved in the binding of the S protein to ACE2. Loop 2 (Y473-F490) acts as an anchor for ACE2 recognition, and Loop 3 (G496-V503) locks ACE2 at the other nonanchoring end. Then, the charged or long-chain residues in the ß-sheet 1 (N450-F456) region reinforce this binding. The proposed binding mechanism was supported by umbrella sampling simulation of the dissociation process. The current computational study provides important theoretical insights for the development of new vaccines against SARS-CoV-2.

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.

Engineering the biomimetic cofactors of NMNH for cytochrome P450 BM3 based on binding conformation refinement.

Cytochrome P450 BM3 (BM3) is an important oxidoreductase that is widely used in drug synthesis, chemical synthesis, and other industries. However, as BM3 unquestionably increases costs by consuming a natural cofactor that unstably provides electrons, an alternative biomimetic cofactor with simpler structures represented by nicotinamide mononucleotide (NMNH) has been utilized. Currently, few reports exist on artificially modified BM3 enzymes using NMNH, especially regarding theoretical simulation and calculation. With the cognition of the mechanism in mind, we propose a strategy that optimizes and refines catalytic conformation. Based on constrained molecular dynamics simulation, the distance between N-5 of FAD flavin and C-4 of NMNH is used as a cue for the determination of improved conformation, and the potential positive mutants are subsequently screened virtually in accordance with binding free energy requirements. As a result, the K cat/K M values of the favorable mutant S848R increased to 205.38% compared to the wild-type BM3 with NMNH. These data indicate that our strategy can be applied for the specific utilization of biomimetic cofactors by oxidoreductases represented by BM3.

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.

Molecular Mechanism of Selective Binding of NMS-P118 to PARP-1 and PARP-2: A Computational Perspective.

The nuclear protein poly (ADP-ribose) polymerase-1 (PARP-1) inhibitors have been proven effective to potentiate both chemotherapeutic agents and radiotherapy. However, a major problem of most current PARP inhibitors is their lack of selectivity for PARP-1 and its closest isoform PARP-2. NMS-P118 is a highly selective PARP inhibitor that binds PARP-1 stronger than PARP-2 and has many advantages such as excellent pharmacokinetic profiles. In this study, molecular dynamics (MD) simulations of NMS-P118 in complex with PARP-1 and PARP-2 were performed to understand the molecular mechanism of its selectivity. Alanine scanning together with free energy calculation using MM/GBSA and interaction entropy reveal key residues that are responsible for the selectivity. Although the conformation of the binding pockets and NMS-P118 are very similar in PARP-1 and PARP-2, most of the hot-spot residues in PARP-1 have stronger binding free energy than the corresponding residues in PARP-2. Detailed analysis of the binding energy shows that the 4'4-difluorocyclohexyl ring on NMS-P118 form favorable hydrophobic interaction with Y889 in PARP-1. In addition, the H862 residue in PARP-1 has stronger binding free energy than H428 in PARP-2, which is due to shorter distance and stronger hydrogen bonds. Moreover, the negatively charged E763 residue in PARP-1 forms stronger electrostatic interaction energy with the positively charged NMS-P118 than the Q332 residue in PARP-2. These results rationalize the selectivity of NMS-P118 and may be useful for designing novel selective PARP inhibitors.

An Energy Optimization Strategy Based on the Perfect Conformation of Prolyl Endopeptidase for Improving Catalytic Efficiency.

Prolyl endopeptidases (PEPs) hydrolyze proteins to yield bioactive peptides and are effective in the treatment of celiac disease. However, the catalytic efficiency of PEPs still has the potential to be improved, which could further strengthen their industrial and therapeutic applications. Herein, a novel rational design strategy based on a "near-attack conformation" of the catalytic state of PEP was adopted. Constrained dynamic simulations were applied, followed by the virtual screening of potentially favorable mutants according to their binding free energy. We redesigned Sphaerobacter thermophiles PEP with high-temperature activity/stability, a wide range of pH stabilities, and high proline specificity. As a result, the kcat value of two PEP mutants (I462W and Q560Y) increased by 208.2 and 150.1%, respectively, and the kcat/KM increased by 32.7 and 6.3%, respectively. These data revealed that the PEP mutants had improved catalytic efficiency and that our strategy can be applied for enzyme engineering.

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.

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.