Conformational and docking studies of acyl homoserine lactones as a robust method to investigate bioactive conformations

A method aiming at investigating possible bioactive conformations of acyl homoserine lactone (AHL) quorum sensing (QS) modulators is established. The method relies on the exhaustive conformational analysis of AHLs by varying torsion angles around the amide group then on the selection of the closest conformation to those known from co-crystallized XRD data of AHL-receptor complexes. These latter are then docked as rigid ligand within the receptor binding site, leading to interactions with binding site residues which are highly consistent as compared with the data arising from XRD studies. The method is first validated using AHLs for which XRD data of their complexes with their cognate receptor are available, then extended to examples for which the binding mode is still unknown.Three compounds were used to validate the method: hexanoyl homoserine lactone (HHL) as an example of autoinducer, 3-oxo-butanoyl homoserine lactone (OBHL), as a representative model of 3-oxo-AHLs, and 4-(4-chlorophenoxy)butanoyl homoserine lactone (CPOBHL) as an example of a QS inhibitor. The conformational analysis of these three compounds to their cognate protein (TraR, SdiA, LasR and CviR) provides the data which enable the next rigid docking step. Further rigid docking of the closest conformations compared to the known bioactive ones within the binding sites allows to recover the expected binding mode with high precision (atomic RMSD < 2 Å). This “conformational analysis/torsion angle filter/rigid ligand docking” method was then used for investigating three non-natural AHL-type QS inhibitors without known co-crystallized XRD structures, namely was 2-hexenoyl homoserine lactone (HenHL), 3-oxo-4-phenylbutanoyl homoserine lactone (OPBHL) and 3-(4-bromophenyl)propanoyl homoserine lactone (BPPHL). Results provide insights into their possible binding mode by identifying specific interactions with some key residues within the receptor binding site, allowing discussion of their biological activity.     

Schiff bases of indoline-2,3-dione: potential novel inhibitors of Mycobacterium tuberculosis (Mtb) DNA gyrase

In the present study a series of Schiff bases of indoline-2,3-dione were synthesized and investigated for their Mtb gyrase inhibitory activity. Promising inhibitory activity was demonstrated with some of these derivatives, which exhibited IC(50) values ranging from 50-157 mM. The orientation and the ligand-receptor interactions of such molecules within the Mtb DNA gyrase A subunit active site were investigated applying a multi-step docking protocol using Molecular Operating Environment (MOE) and Autodock4 docking software. The results revealed the importance of the isatin moiety and the connecting side chain for strong interactions with the enzyme active site. Among the tested compounds the terminal aromatic ring benzofuran showed the best activity. Promising new leads for developing a novel class of Mtb gyrase inhibitors were obtained from Schiff bases of indoline-2,3-dione.     

Identification of novel Plasmodium falciparum PI4KB inhibitors as potential anti-malarial drugs: Homology modeling,molecular docking and molecular dynamics simulations

The current study was set to discover selective Plasmodium falciparum phosphatidylinositol-4-OH kinase type III beta (pfPI4KB) inhibitors as potential antimalarial agents using combined structure-based and ligand-based drug discovery approach. A comparative model of pfPI4KB was first constructed and validated using molecular docking techniques. Performance of Autodock4.2 and Vina4 software in predicting the inhibitor-PI4KB binding mode and energy was assessed based on two Test Sets: Test Set I contained five ligands with resolved crystal structures with PI4KB, while Test Set II considered eleven compounds with known IC50 value towards PI4KB. The outperformance of Autodock as compared to Vina was reported, giving a correlation coefficient (R²) value of 0.87 and 0.90 for Test Set I and Test Set II, respectively. Pharmacophore-based screening was then conducted to identify drug-like molecules from ZINC database with physicochemical similarity to two potent pfPI4KB inhibitors –namely cpa and cpb. For each query inhibitor, the best 1000 hits in terms of TanimotoCombo scores were selected and subjected to molecular docking and molecular dynamics (MD) calculations. Binding energy was then estimated using molecular mechanics–generalized Born surface area (MM-GBSA) approach over 50 ns MD simulations of the inhibitor-pfPI4KB complexes. According to the calculated MM-GBSA binding energies, ZINC78988474 and ZINC20564116 were identified as potent pfPI4KB inhibitors with binding energies better than those of cpa and cpb, with ΔG_binding ≥ −34.56 kcal/mol. The inhibitor-pfPI4KB interaction and stability were examined over 50 ns MD simulation; as well the selectivity of the identified inhibitors towards pfPI4KB over PI4KB was reported.     

Importance of ligand conformational energies in carbohydrate docking: Sorting the wheat from the chaff

Docking algorithms that aim to be applicable to a broad range of ligands suffer reduced accuracy because they are unable to incorporate ligand‐specific conformational energies. Here, we develop a set of Carbohydrate Intrinsic (CHI) energy functions that quantify the conformational properties of oligosaccharides, based on the values of their glycosidic torsion angles. The relative energies predicted by the CHI energy functions mirror the conformational distributions of glycosidic linkages determined from a survey of oligosaccharide‐protein complexes in the protein data bank. Addition of CHI energies to the standard docking scores in Autodock 3, 4.2, and Vina consistently improves pose ranking of oligosaccharides docked to a set of anticarbohydrate antibodies. The CHI energy functions are also independent of docking algorithm, and with minor modifications, may be incorporated into both theoretical modeling methods, and experimental NMR or X‐ray structure refinement programs. © 2013 Wiley Periodicals, Inc.     

Docking flexible molecules: A case study of three proteins

A genetic algorithm (GA) conformation search method is used to dock a series of flexible molecules into one of three proteins. The proteins examined are thermolysin (tmn), carboxypeptidase A (cpa), and dihydrofolate reductase (dfr). In the latter two proteins, the crystal ligand was redocked. For thermolysin, we docked eight ligands into a protein conformation derived from a single crystal structure. The bound conformations of the other ligands in tmn are known. In the cpa and dfr cases, and in seven of the eight tmn ligands, the GA docking method found conformations within 1.6 Å root mean square (rms) of the relaxed crystal conformation. © 1995 John Wiley & Sons, Inc.     

Protein-ligand docking against non-native protein conformers

In the validation of protein-ligand docking protocols, performance is mostly measured against native protein conformers, i.e. each ligand is docked into the protein conformation from the structure that contained that ligand. In real-life applications, however, ligands are docked against non-native conformations of the protein, i.e. the apo structure or a structure of a different protein-ligand complex. Here, we have constructed an extensive test set for assessing docking performance against non-native protein conformations. This new test set is built on the Astex Diverse Set (which we recently constructed for assessing native docking performance) and contains 1112 non-native structures for 65 drug targets. Using the protein-ligand docking program GOLD, the Astex Diverse Set and the new Astex Non-native Set, we established that, whereas docking performance (top-ranked solution within 2 A rmsd of the experimental binding mode) is approximately 80% for native docking, this drops to 61% for non-native docking. A similar drop-off is observed for sampling performance (any solution within 2 A): 91% for native docking vs 72% for non-native docking. No significant differences were observed between docking performance against apo and nonapo structures. We found that, whereas small variations in protein conformation are generally tolerated by our rigid docking protocol, larger protein movements result in a catastrophic drop-off in performance. Some docking performance and nearly all sampling performance can be recovered by considering dockings produced against a small number of non-native structures simultaneously. Docking against non-native structures of complexes containing ligands that are similar to the docked ligand also significantly improves both docking performance and sampling performance.     

Role of bridging water molecules in GSK3β-inhibitor complexes: insights from QM/MM, MD, and molecular docking studies

The role of water molecules is increasingly gaining interest in drug design, and several studies have highlighted their paramount contributions to the specificity and the affinity of ligand binding. In this study, we employ the two-layer ONIOM-based quantum mechanics/molecular mechanics (QM/MM) calculations, molecular dynamics (MD) simulations, and molecular docking studies to investigate the effect of bridging water molecules at the GSK3β-inhibitors interfaces. The results obtained from the ONIOM geometry optimization and AIM analysis corroborated the presence of bridging water molecules that form hydrogen bonds with protein side chain of Thr138 and/or backbone of Gln185, and mediate interactions with inhibitors in the 10 selected GSK3β-inhibitor complexes. Subsequently, MD simulations carried out on a representative system of 1R0E demonstrated that the bridging water molecule is stable at the GSK3β-inhibitor interface and appears to contribute to the stability of the protein-inhibitor interactions. Furthermore, molecular docking studies of GSK3β-inhibitor complexes indicated that the inhibitors can increase binding affinities and the better docked conformation of inhibitors can be obtained by inclusion of the bridging water molecules, especially for the flexible inhibitors, in docking experiments into individual protein conformations. Our results elucidate the importance of bridging water molecules at the GSK3β-inhibitor interfaces and suggest that they might prove useful in rational drug design.     

The nonenzymatic activation of isoniazid by MnIII-pyrophosphate in the presence of NADH produces the inhibition of the enoyl-ACP reductase InhA from Mycobacterium tuberculosis

The antituberculosis drug isoniazid (INH) is quickly oxidized by stoichiometric amounts of manganese(III)-pyrophosphate. In the presence of the nicotinamide coenzyme, the INH oxidation produced the formation of INH-NAD(H) adducts and allowed the in vitro inhibition of the enoyl-acyl carrier protein reductase InhA, an INH target in the biosynthetic pathway for mycolic acids. Manganese(III)-pyrophosphate is an efficient alternative oxidant to mimic the activity of the Mycobacterium tuberculosis KatG catalase-peroxidase and will be useful for further mechanistic studies of INH activation and for structural investigations on reactive INH species and resulting InhA inhibitors.     

Machine learning optimization of cross docking accuracy

Performance of small molecule automated docking programs has conceptually been divided into docking -, scoring -, ranking - and screening power, which focuses on the crystal pose prediction, affinity prediction, ligand ranking and database screening capabilities of the docking program, respectively. Benchmarks show that different docking programs can excel in individual benchmarks which suggests that the scoring function employed by the programs can be optimized for a particular task. Here the scoring function of Smina is re-optimized towards enhancing the docking power using a supervised machine learning approach and a manually curated database of ligands and cross docking receptor pairs. The optimization method does not need associated binding data for the receptor-ligand examples used in the data set and works with small train sets. The re-optimization of the weights for the scoring function results in a similar docking performance with regard to docking power towards a cross docking test set. A ligand decoy based benchmark indicates a better discrimination between poses with high and low RMSD. The reported parameters for Smina are compatible with Autodock Vina and represent ready-to-use alternative parameters for researchers who aim at pose prediction rather than affinity prediction.     

Insight into crucial inhibitor–enzyme interaction of arylamides as novel direct inhibitors of the enoyl ACP reductase (InhA) from Mycobacterium tuberculosis: computer-aided molecular design

Abstract  

The enoyl ACP reductase enzyme (InhA) involved in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis is an attractive target enzyme for antitubercular drug development. Arylamide derivatives are a novel class of InhA inhibitors used to overcome the drug-resistance problem of isoniazid, the frontline drug for tuberculosis treatment. Their remarkable property of inhibiting the InhA enzyme directly without requiring any coenzyme, makes them especially appropriate for the design of new antibacterials. In order to find a sound binding conformation for the different arylamide analogs, molecular docking experiments were performed with subsequent QSAR investigations. The X-ray conformation of one arylamide within its cocrystallized complex with InhA was used as a starting conformation for the docking experiments. The results thus obtained are perfectly consistent (rmsd = 0.73 ?) with the results from X-ray analysis. A thorough investigation of the arylamide binding modes with InhA provided ample information about structural requirements for appropriate inhibitor–enzyme interactions. Three different QSAR models were established using two three-dimensional (CoMFA and CoMSIA) and one two-dimensional (HQSAR) techniques. With statistically ensured models, the QSAR results obtained had high correlation coefficients between molecular structure properties of 28 arylamide derivatives and their biological activity. Molecular fragment contributions to the biological activity of arylamides could be obtained from the HQSAR model. Finally, a graphic interpretation designed in different contour maps provided coincident information about the ligand–receptor interaction thus offering guidelines for syntheses of novel analogs with enhanced biological activity.     

Postprocessing of docked protein-ligand complexes using implicit solvation models

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.     

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments.     

Flexible matching of test ligands to a 3D pharmacophore using a molecular superposition force field: Comparison of predicted and experimental conformations of inhibitors of three enzymes

Summary A computer procedure TFIT, which uses a molecular superposition force field to flexibly match test compounds to a 3D pharmacophore, was evaluated to find out whether it could reliably predict the bioactive conformations of flexible ligands. The program superposition force field optimizes the overlap of those atoms of the test ligand and template that are of similar chemical type, by applying an attractive force between atoms of the test ligand and template which are close together and of similar type (hydrogen bonding, charge, hydrophobicity). A procedure involving Monte Carlo torsion perturbations, followed by torsional energy minimization, is used to find conformations of the test ligand which cominimize the internal energy of the ligand and the superposition energy of ligand and template. The procedure was tested by applying it to a series of flexible ligands for which the bioactive conformation was known experimentally. The 15 molecules tested were inhibitors of thermolysin, HIV-1 protease or endothiapepsin for which X-ray structures of the bioactive conformation were available. For each enzyme, one of the molecules served as a template and the others, after being conformationally randomized, were fitted. The fitted conformation was then compared to the known binding geometry. The matching procedure was successful in predicting the bioactive conformations of many of the structures tested. Significant deviation from experimental results was found only for parts of molecules where it was readily apparent that the template did not contain sufficient information to accurately determine the bioactive conformation.     

Ligand docking and binding site analysis with PyMOL and Autodock/Vina

Docking of small molecule compounds into the binding site of a receptor and estimating the binding affinity of the complex is an important part of the structure-based drug design process. For a thorough understanding of the structural principles that determine the strength of a protein/ligand complex both, an accurate and fast docking protocol and the ability to visualize binding geometries and interactions are mandatory. Here we present an interface between the popular molecular graphics system PyMOL and the molecular docking suites Autodock and Vina and demonstrate how the combination of docking and visualization can aid structure-based drug design efforts.     

A proposed model of Mycobacterium avium complex dihydrofolate reductase and its utility for drug design

A homology model of Mycobacterium avium complex dihydrofolate reductase (MAC DHFR) was constructed on the basis of the X-ray crystal structure of Mycobacterium tuberculosis (Mtb) DHFR. The homology searching of the MAC DHFR resulted in the identification of the Mtb DHFR structure (PDB 1DF7) as the template for the model building. The MAC enzyme sequence was aligned to that of the Mtb counterpart using a modified Needleman and Wunsch methodology. The initial geometry to be modeled was copied from the template, either fully or partially depending on whether the residues were conserved or not, respectively. Using a randomized modeling procedure, 10 independent models of the target protein were built. The cartesian average of all the model structures was then refined using molecular mechanics. The resulting model was assessed for stereochemical quality using a Ramachandran plot and by analyzing the consistency of the model with the experimental data. The structurally and functionally important residues were identified from the model. Further, 5-deazapteridines recently reported as inhibitors of MAC DHFR were docked into the active site of the developed model. All the seven inhibitors used in the docking study have a similar docking mode at the active site. The network of hydrogen bonds around the 2,4-diamino-5-deazapteridine ring was found to be crucial for the binding of the inhibitors with the active site residues. The 5-methyl group of the inhibitors was located in a narrow hydrophobic pocket at the bottom of the active site. The relative values of the three torsion angles of the inhibitors were found to be important for the proper orientation of the inhibitor functional groups into the active site.     

吡咯烷类胞液型磷脂酶A2抑制剂的比较分子力场分析

胞液型磷脂酶A2能引发关节炎，针对胞液型磷脂酶A2的抑制剂有可能成为治疗关节炎的特效药，因此引起了广泛的关注.文章对于吡咯烷类胞液型磷脂酶A2抑制剂进行了三维定量构效关系研究，利用比较分子力场分析构建了该类分子的定量构效关系，得到三维等值线图，为胞液型磷脂酶A2抑制剂的进一步改造提供了有益的启示.     

Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors

A semiempirical quantum mechanical PM6-DH2 method accurately covering the dispersion interaction and H-bonding was used to score fifteen structurally diverse CDK2 inhibitors. The geometries of all the complexes were taken from the X-ray structures and were reoptimised by the PM6-DH2 method in continuum water. The total scoring function was constructed as an estimate of the binding free energy, i.e., as a sum of the interaction enthalpy, interaction entropy and the corrections for the inhibitor desolvation and deformation energies. The applied scoring function contains a clear thermodynamical terms and does not involve any adjustable empirical parameter. The best correlations with the experimental inhibition constants (ln K _i) were found for bare interaction enthalpy (r ² = 0.87) and interaction enthalpy corrected for ligand desolvation and deformation energies (r ² = 0.77); when the entropic term was considered, however, the correlation becomes worse but still acceptable (r ² = 0.52). The resulting correlation based on the PM6-DH2 scoring function is better than previously published function based on various docking/scoring, SAR studies or advanced QM/MM approach, however, the robustness is limited by number of available experimental data used in the correlation. Since a very similar correlation between the experimental and theoretical results was found also for a different system of the HIV-1 protease, the suggested scoring function based on the PM6-DH2 method seems to be applicable in drug design, even if diverse protein–ligand complexes have to be ranked.     

Binding affinity of substituted ureido‐benzenesulfonamide ligands to the carbonic anhydrase receptor: A theoretical study of enzyme inhibition

The binding properties of a series of benzenesulfonamide inhibitors (4‐substituted‐ureido‐benzenesulfonamides, UBSAs) of human carbonic anhydrase II (hCA II) enzyme with active site residues have been studied using a hybrid quantum mechanical/molecular mechanical (QM/MM) model. To account for the important docking interactions between the UBSAs ligand and hCA II enzyme, a molecular docking program AutoDock Vina is used. The molecular docking results obtained by AutoDock Vina revealed that the docked conformer has root mean square deviation value less than 1.50 Å compared to X‐ray crystal structures. The inhibitory activity of UBSA ligands against hCA II is found to be in good agreement with the experimental results. The thermodynamic parameters for inhibitor binding show that hydrogen bonding, hydrophilic, and hydrophobic interactions play a major role in explaining the diverse inhibitory range of these derivatives. Additionally, natural bond orbital analysis is performed to characterize the ligand–metal charge transfer stability. The insights gained from this study have great potential to design new hCA‐II inhibitor, 4‐[3‐(1‐p‐Tolyl‐4‐trifluoromethyl‐1H‐pyrazol‐3‐yl)‐ureido]‐benzenesulfonamide, which belongs to the family of UBSA inhibitors and shows similar type of inhibitor potency with hCA II. This work also reveals that a QM/MM model and molecular docking method are computationally feasible and accurate for studying substrate–protein inhibition. © 2013 Wiley Periodicals, Inc.     

CoMFA 3D-QSAR analysis of HIV-1 RT nonnucleoside inhibitors, TIBO derivatives based on docking conformation and alignment

HIV-1 RT is one of the key enzymes in the duplication of HIV-1. Inhibitors of HIV-1 RT are classified as nonnucleoside RT inhibitors (NNRTIs) and nucleoside analogues. NNRTIs bind in a region not associated with the active site of the enzyme. Within the NNRTI category, there is a set of inhibitors commonly referred to as TIBO inhibitors. Fifty TIBO inhibitors were used in the work to build 3-D QSAR models. The two known crystal structures of complexes are used to investigate and validate the docking protocol. The results show that the docking simulations reproduce the crystal complexes very well with RMSDs of approximately 1 A and approximately 0.6 A for 1REV and 1COU, respectively. The alignment of molecules and "active" conformation selection are the key to a successful 3D-QSAR model by CoMFA. The flexible docking (Autodock3) was used on determination of "active" conformation and molecular alignment, and CoMFA and CoMSIA were used to develop 3D-QSAR models of 50 TIBOs in the work. The 3D-QSAR models demonstrate a good ability to predict the activity of studied compounds (r2 = 0.972, 0.944, q2 = 0.704, 0.776). It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the binding structure of the complex. The results demonstrate that the combination of ligand-based and receptor-based modeling is a powerful approach to build 3D-QSAR models.