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.     

Design, synthesis, and biochemical evaluation of 1,5,6,7-tetrahydro-6,7-dioxo-9-D-ribitylaminolumazines bearing alkyl phosphate substituents as inhibitors of lumazine synthase and riboflavin synthase

The last two steps in the biosynthesis of riboflavin, an essential metabolite that is involved in electron transport, are catalyzed by lumazine synthase and riboflavin synthase. To obtain structural probes and inhibitors of these two enzymes, two ribityllumazinediones bearing alkyl phosphate substituents were synthesized. The synthesis involved the generation of the ribityl side chain, the phosphate side chain, and the lumazine system in protected form, followed by the simultaneous removal of three different types of protecting groups. The products were designed as intermediate analogue inhibitors of lumazine synthase that would bind to its phosphate-binding site as well as its lumazine binding site. Both compounds were found to be effective inhibitors of Bacillus subtilislumazine synthase as well as Escherichia coli riboflavin synthase. Molecular modeling of the binding of one of the two compounds provided a structural explanation for how these compounds are able to effectively inhibit both enzymes. In phosphate-free buffer, the phosphate moieties of the inhibitors were found to contribute positively to their binding to Mycobacterium tuberculosis lumazine synthase, resulting in very potent inhibitors with Ki values in the low nanomolar range. The additional carbonyl in the dioxolumazine system versus the purinetrione system was found to make a positive contribution to its binding to E. coli riboflavin synthase.     

Accurate prediction of protonation state as a prerequisite for reliable MM-PB(GB)SA binding free energy calculations of HIV-1 protease inhibitors

Binding free energies were calculated for the inhibitors lopinavir, ritonavir, saquinavir, indinavir, amprenavir, and nelfinavir bound to HIV-1 protease. An MMPB/SA-type analysis was applied to conformational samples from 3 ns explicit solvent molecular dynamics simulations of the enzyme-inhibitor complexes. Binding affinities and the sampled conformations of the inhibitor and enzyme were compared between different HIV-1 protease protonation states to find the most likely protonation state of the enzyme in the complex with each of the inhibitors. The resulting set of protonation states leads to good agreement between calculated and experimental binding affinities. Results from the MMPB/SA analysis are compared with an explicit/implicit hybrid scheme and with MMGB/SA methods. It is found that the inclusion of explicit water molecules may offer a slight advantage in reproducing absolute binding free energies while the use of the Generalized Born approximation significantly affects the accuracy of the calculated binding affinities.     

In silico binding free energy predictability by using the linear interaction energy (LIE) method: bromobenzimidazole CK2 inhibitors as a case study

Protein kinase CK2 is essential for cell viability, and its control regards a broad series of cellular events such as gene expression, RNA, and protein synthesis. Evidence of its involvement in tumor development and viral replication indicates CK2 as a potential target of antineoplastic and antiviral drugs. In this study the Linear Interaction Energy (LIE) Method with the Surface Generalized Born (SGB) continuum solvation model was used to study several bromobenzimidazole CK2 inhibitors. This methodology, developed by Aqvist, finds a plausible compromise between accuracy and computational speed in evaluating binding free energy (DeltaGbind) values. In this study, two different free binding energy models, named "CK2scoreA" and "CK2scoreB", were developed using 22 inhibitors as the training set in a stepwise approach useful to appropriately select both the tautomeric form and the starting binding position of each inhibitor. Both models are statistically acceptable. Indeed, the better one is characterized by a correlation coefficient (r2) of 0.81, and the predictive accuracy was 0.65 kcal/mol. The corresponding validation, using an external test set of 16 analogs, showed a correlation coefficient (q2) of 0.68 and a prediction root-mean-square error of 0.78 kcal/mol. In this case, the LIE approach has been proved to be an efficient methodology to rationalize the difference of activity, the key interactions, and the different possible binding modes of this specific class of potent CK2 inhibitors.     

Effects of Water Placement on Predictions of Binding Affinities for p38α MAP Kinase Inhibitors

Monte Carlo free energy perturbation (MC/FEP) calculations have been applied to compute the relative binding affinities of 17 congeneric pyridazo-pyrimidinone inhibitors of the protein p38α MAP kinase. Overall correlation with experiment was found to be modest when the complexes were hydrated using a traditional procedure with a stored solvent box. Significant improvements in accuracy were obtained when the MC/FEP calculations were repeated using initial solvent distributions optimized by the water placement algorithm JAWS. The results underscore the importance of accurate placement of water molecules in a ligand binding site for the reliable prediction of relative free energies of binding.     

VEGFR2活性腔性质以及与抑制剂的结合模式研究

VEGFR2介导肿瘤诱导的血管生成作用, 是抑制肿瘤生长和转移的新靶点. 为深入探讨VEGFR2活性腔性质以及与抑制剂的结合模式, 采用多拷贝同时搜寻法(MCSS)研究VEGFR2活性腔的性质, 然后用分子对接方法对5个已上临床的VEGFR抑制剂与VEGFR2活性腔进行对接计算, 讨论它们的结合模式, 确定与配体结合相关的关键残基. 研究发现: 疏水腔I, II是配体结合的关键区域, 残基Glu915, Cys917是关键的氢键作用位点, Lys866, Glu883和Asp1044形成的极性区域对提高配体亲合力很重要, 疏水腔III和极性腔IV是额外增强配体结合力的区域, IV区的Arg1030可提供额外的氢键作用位点. 本研究可为全新VEGFR2抑制剂的合理药物设计提供理论依据, 为寻找新的抗肿瘤药物奠定基础.     

Allosteric inhibition of the protein-protein interaction between the leukemia-associated proteins Runx1 and CBFbeta

The two subunits of core binding factor (Runx1 and CBFbeta) play critical roles in hematopoiesis and are frequent targets of chromosomal translocations found in leukemia. The binding of the CBFbeta-smooth muscle myosin heavy chain (SMMHC) fusion protein to Runx1 is essential for leukemogenesis, making this a viable target for treatment. We have developed inhibitors with low micromolar affinity which effectively block binding of Runx1 to CBFbeta. NMR-based docking shows that these compounds bind to CBFbeta at a site displaced from the binding interface for Runx1, that is, these compounds function as allosteric inhibitors of this protein-protein interaction, a potentially generalizable approach. Treatment of the human leukemia cell line ME-1 with these compounds shows decreased proliferation, indicating these are good candidates for further development.     

Calculation of ligand binding free energies from molecular dynamics simulations

A recently developed method for predicting binding affinities in ligand–receptor complexes, based on interaction energy averaging and conformational sampling by molecular dynamics simulation, is presented. Polar and nonpolar contributions to the binding free energy are approximated by a linear scaling of the corresponding terms in the average intermolecular interaction energy for the bound and free states of the ligand. While the method originally assumed the validity of electrostatic linear response, we show that incorporation of systematic deviations from linear response derived from free energy perturbation calculations enhances the accuracy of the approach. The method is applied to complexes of wild-type and mutant human dihydrofolate reductases with 2,4-diaminopteridine and 2,4-diaminoquinazoline inhibitors. It is shown that a binding energy accuracy of about 1 kcal/mol is attainable even for multiply ionized compounds, such as methotrexate, for which electrostatic interactions energies are very large. © 1998 John Wiley & Sons, Inc. Int J Quant Chem 69: 77–88, 1998     

Validation of the AmpC β-lactamase binding site and identification of inhibitors with novel scaffolds

AmpC β-lactamase confers resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds that inhibit the enzyme is considered crucial to the development of novel antibacterial therapies. Given the highly solvent-exposed active site, it is important to study the induced-fit movements and water-mediated interactions to improve docking accuracy and virtual screening enrichments in structure-based design of new AmpC inhibitors. Here, we tested multiple models of the AmpC binding site to investigate the importance of conserved water molecules and binding site plasticity on molecular docking. The results indicate that at least one conserved water molecule greatly improves the binding pose predictions and virtual screening enrichments of known noncovalent AmpC inhibitors. The best model was tested prospectively in the virtual screening of about 6 million commercially available compounds. Sixty-one chemically diverse top-scoring compounds were experimentally tested, which led to the identification of seven previously unknown inhibitors. These findings validate the essential features of the AmpC binding site for molecular recognition and are useful for further optimization of identified inhibitors.     

Protein surface-assisted enhancement in the binding affinity of an inhibitor for recombinant human carbonic anhydrase-II

We elaborate on a novel strategy for enhancing the binding affinity of an active-site directed inhibitor by attaching a tether group, designed to interact with the surface-exposed histidine residue(s) of enzymes. In this approach, we have utilized the recombinant form of human carbonic anhydrase-II (hCA-II) as the enzyme source and benzenesulfonamide and its derivatives as inhibitors. The steady-state kinetic and the ligand binding data revealed that the attachment of iminodiacetate (IDA)-Cu(2+) to benzenesulfonamide (via a triethylene glycol spacer) enhanced its binding affinity for hCA-II by about 40-fold. No energetic contribution of either IDA or triethylene glycol spacer was found (at least in the ground state of the enzyme-inhibitor complex) when Cu(2+) was stripped off from the tether group-conjugated sulfonamide derivative. Arguments are presented that the overall strategy of enhancing the binding affinities of known inhibitors by attaching the IDA-Cu(2+) groups to interact with the surface-exposed histidine residues will find a general application in designing the isozyme-specific inhibitors as potential drugs.     

Detection of small-molecule enzyme inhibitors with peptides isolated from phage-displayed combinatorial peptide libraries

BACKGROUND: The rapidly expanding list of pharmacologically important targets has highlighted the need for ways to discover new inhibitors that are independent of functional assays. We have utilized peptides to detect inhibitors of protein function. We hypothesized that most peptide ligands identified by phage display would bind to regions of biological interaction in target proteins and that these peptides could be used as sensitive probes for detecting low molecular weight inhibitors that bind to these sites. RESULTS: We selected a broad range of enzymes as targets for phage display and isolated a series of peptides that bound specifically to each target. Peptide ligands for each target contained similar amino acid sequences and competition analysis indicated that they bound one or two sites per target. Of 17 peptides tested, 13 were found to be specific inhibitors of enzyme function. Finally, we used two peptides specific for Haemophilus influenzae tyrosyl-tRNA synthetase to show that a simple binding assay can be used to detect small-molecule inhibitors with potencies in the micromolar to nanomolar range. CONCLUSIONS: Peptidic surrogate ligands identified using phage display are preferentially targeted to a limited number of sites that inhibit enzyme function. These peptides can be utilized in a binding assay as a rapid and sensitive method to detect small-molecule inhibitors of target protein function. The binding assay can be used with a variety of detection systems and is readily adaptable to automation, making this platform ideal for high-throughput screening of compound libraries for drug discovery.     

Inhibition Mechanism of Hydroxyproline-like Small Inhibitors to Disorder HIF-VHL Interaction by Molecular Dynamic Simulations and Binding Free Energy Calculations

Protein-protein interactions are vital for a wide range of biological processes. The interactions between the hypoxia-inducible factor and von Hippel Lindau (VHL) are attractive drug targets for ischemic heart disease. In order to disrupt this interaction, the strategy to target VHL binding site using a hydroxyproline-like (pro-like) small molecule has been reported. In this study, we focused on the inhibition mechanism between the pro-like inhibitors and the VHL protein, which were investigated via molecular dynamics simulations and binding free energy calculations. It was found that pro-like inhibitors showed a strong binding affinity toward VHL. Binding free energy calculations and free energy decompositions suggested that the modification of various regions of pro-like inhibitors may provide useful information for future drug design.     

Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations

The Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) methods calculate binding free energies for macromolecules by combining molecular mechanics calculations and continuum solvation models. To systematically evaluate the performance of these methods, we report here an extensive study of 59 ligands interacting with six different proteins. First, we explored the effects of the length of the molecular dynamics (MD) simulation, ranging from 400 to 4800 ps, and the solute dielectric constant (1, 2, or 4) on the binding free energies predicted by MM/PBSA. The following three important conclusions could be observed: (1) MD simulation length has an obvious impact on the predictions, and longer MD simulation is not always necessary to achieve better predictions. (2) The predictions are quite sensitive to the solute dielectric constant, and this parameter should be carefully determined according to the characteristics of the protein/ligand binding interface. (3) Conformational entropy often show large fluctuations in MD trajectories, and a large number of snapshots are necessary to achieve stable predictions. Next, we evaluated the accuracy of the binding free energies calculated by three Generalized Born (GB) models. We found that the GB model developed by Onufriev and Case was the most successful model in ranking the binding affinities of the studied inhibitors. Finally, we evaluated the performance of MM/GBSA and MM/PBSA in predicting binding free energies. Our results showed that MM/PBSA performed better in calculating absolute, but not necessarily relative, binding free energies than MM/GBSA. Considering its computational efficiency, MM/GBSA can serve as a powerful tool in drug design, where correct ranking of inhibitors is often emphasized.     

Prediction and analysis of binding affinities for chemically diverse HIV-1 PR inhibitors by the modified SAFE_p approach

One of the biggest challenges in the "in silico" screening of enzyme ligands is to have a protocol that could predict the ligand binding free energies. In our group we have developed a very simple screening function (referred to as solvent accessibility free energy of binding predictor, SAFE_p) which we have applied previously to the study of peptidic HIV-1 protease (HIV-1 PR) inhibitors and later to cyclic urea type HIV-1 PR inhibitors. In this work, we have extended the SAFE_p protocol to a chemically diverse set of HIV-1 PR inhibitors with binding constants that differ by several orders of magnitude. The resulting function is able to reproduce the ranking and in many cases the value of the inhibitor binding affinities for the HIV-1 PR, with accuracy comparable with that of costlier protocols. We also demonstrate that the binding pocket SAFE_p analysis can contribute to the understanding of the physical forces that participate in ligand binding. The analysis tools afforded by our protocol have allowed us to identify an induced fit phenomena mediated by the inhibitor and have demonstrated that larger fragments do not necessarily contribute the most to the binding free energy, an outcome partially brought about by the substantial role the desolvation penalty plays in the energetics of binding. Finally, we have revisited the effect of the Asp dyad protonation state on the predicted binding affinities.     

Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors

An increasing number of docking/scoring programs are available that use different sampling and scoring algorithms. A reliable scoring function is the crucial element of such approaches. Comparative studies are needed to evaluate their current capabilities. DOCK4 with force field and PMF scoring as well as FlexX were used to evaluate the predictive power of these docking/scoring approaches to identify the correct binding mode of 61 MMP-3 inhibitors in a crystal structure of stromelysin and also to rank them according to their different binding affinities. It was found that DOCK4/PMF scoring performs significantly better than FlexX and DOCK4/FF in both ranking ligands and predicting their binding modes. Most notably, DOCK4/PMF was the only scoring/docking approach that found a significant correlation between binding affinity and predicted score of the docked inhibitors. However, comparing only those cases where the correct binding mode was identified (scoring highest among sampled poses), FlexX showed the best `fine tuning' (lowest rmsd) in predicted binding modes. The results suggest that not so much the sampling procedure but rather the scoring function is the crucial element of a docking program.     

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1′ pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC₅₀ value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.     

Molecular modeling study of checkpoint kinase 1 inhibitors by multiple docking strategies and prime/MM-GBSA calculation

Developing chemicals that inhibit checkpoint kinase 1 (Chk1) is a promising adjuvant therapeutic to improve the efficacy and selectivity of DNA-targeting agents. Reliable prediction of binding-free energy and binding affinity of Chk1 inhibitors can provide a guide for rational drug design. In this study, multiple docking strategies and Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA) calculation were applied to predict the binding mode and free energy for a series of benzoisoquinolinones as Chk1 inhibitors. Reliable docking results were obtained using induced-fit docking and quantum mechanics/molecular mechanics (QM/MM) docking, which showed superior performance on both ligand binding pose and docking score accuracy to the rigid-receptor docking. Then, the Prime/MM-GBSA method based on the docking complex was used to predict the binding-free energy. The combined use of QM/MM docking and Prime/MM-GBSA method could give a high correlation between the predicted binding-free energy and experimentally determined pIC(50) . The molecular docking combined with Prime/MM-GBSA simulation can not only be used to rapidly and accurately predict the binding-free energy of novel Chk1 inhibitors but also provide a novel strategy for lead discovery and optimization targeting Chk1.     

Structure–activity relationships of diphenyl-ether as protoporphyrinogen oxidase inhibitors: insights from computational simulations

Protoporphyrinogen oxidase (PPO, EC 1.3.3.4), which has been identified as a significant target for a great family of herbicides with diverse chemical structures, is the last common enzyme responsible for the seventh step in the biosynthetic pathway to heme and chlorophyll. Among the existing PPO inhibitors, diphenyl-ether is the first commercial family of PPO inhibitors and used as agriculture herbicides for decades. Most importantly, diphenyl-ether inhibitors have been found recently to possess the potential in Photodynamic therapy (PDT) to treat cancer. Herein, molecular dynamics simulations, approximate free energy calculations and hydrogen bond energy calculations were integrated together to uncover the structure–activity relationships of this type of PPO inhibitors. The calculated binding free energies are correlated very well with the values derived from the experimental k _i data. According to the established computational models and the results of approximate free energy calculation, the substitution effects at different position were rationalized from the view of binding free energy. Some outlier (e.g. LS) in traditional QSAR study can also be explained reasonably. In addition, the hydrogen bond energy calculation and interaction analysis results indicated that the carbonyl oxygen on position-9 and the NO₂ group at position-8 are both vital for the electrostatic interaction with Arg98, which made a great contribution to the binding free energy. These insights from computational simulations are not only helpful for understanding the molecular mechanism of PPO-inhibitor interactions, but also beneficial to the future rational design of novel promising PPO inhibitors.