The role of waters in docking strategies with incremental flexibility for carbohydrate derivatives: heat-labile enterotoxin, a multivalent test case

Molecular structure interpretation, spectroscopic (FT-IR, FT-Raman), electronic solvation (UV-Vis, HOMO-LUMO and NLO) properties and biological evaluation of (2E)-3-(biphenyl-4-yl)-1-(4-bromophenyl)prop-2-en-1-one: Experimental and computational modeling approach

In this present work, a molecule (2E)-3-(biphenyl-4-yl)-1-(4-bromophenyl) prop-2-en-1-one (3BPO) was synthesized and the structure has been characterized by using spectroscopic techniques. The most stable conformational structure of title compound has been calculated using HF-6-31G(d,p) basis set. DFT method were used through B3LYP/6-311++G(d,p) basis set to optimize the structure of the title compound. The geometrical parameters, vibrational wavenumbers and electronic properties have also been performed. The electronic properties for HOMO-LUMO, UV-Vis and MEP maps were contemplated by IEFPCM model with various solvation impacts which depends on TD-DFT ((M062X for UV and B3LYP for HOMO-LUMO, MEP)/6-311++G(d,p)) strategies. The NLO activity of title compound has been examined by solvation DFT/B3LYP technique with 6-311++G(d,p) premise set. Mean while, lone pair of donor-acceptor interactions and H bond donor/acceptor surface has been obtained by which a charge transfer mechanism can be explained. Molecular docking has been explored to comprehend the coupling transportation of the examined ligand with human folate receptor alpha in complex with folic corrosive protein (4LRH).

The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations

Misfolded Cu/Zn superoxide dismutase enzyme (SOD1) shows prion-like propagation in neuronal cells leading to neurotoxic aggregates that are implicated in amyotrophic lateral sclerosis (ALS). Tryptophan-32 (W32) in SOD1 is part of a potential site for templated conversion of wild type SOD1. This W32 binding site is located on a convex, solvent exposed surface of the SOD1 suggesting that hydration effects can play an important role in ligand recognition and binding. A recent X-ray crystal structure has revealed that 5-Fluorouridine (5-FUrd) binds at the W32 binding site and can act as a pharmacophore scaffold for the development of anti-ALS drugs. In this study, a new protocol is developed to account for structural (non-displaceable) water molecules in docking simulations and successfully applied to predict the correct docked conformation binding modes of 5-FUrd at the W32 binding site. The docked configuration is within 0.58 Å (RMSD) of the observed configuration. The docking protocol involved calculating a hydration structure around SOD1 using molecular theory of solvation (3D-RISM-KH, 3D-Reference Interaction Site Model-Kovalenko-Hirata) whereby, non-displaceable water molecules are identified for docking simulations. This protocol was also used to analyze the hydrated structure of the W32 binding site and to explain the role of solvation in ligand recognition and binding to SOD1. Structural water molecules mediate hydrogen bonds between 5-FUrd and the receptor, and create an environment favoring optimal placement of 5-FUrd in the W32 binding site.

Characterizing hydration sites in protein-ligand complexes towards the design of novel ligands

Water is an essential part of protein binding sites and mediates interactions to ligands. Its displacement by ligand parts affects the free binding energy of resulting protein-ligand complexes. Therefore the characterization of solvation properties is important for design. Of particular interest is the propensity of localized water to be favorably displaced by a ligand. This review discusses two popular computational approaches addressing these questions, namely WaterMap based on statistical mechanics analysis of MD simulations and 3D RISM based on integral equation theory of liquids. The theoretical background and recent applications in structure-based design will be presented.

Virtual screening: an in silico tool for interlacing the chemical universe with the proteome

In silico screening both in the forward (traditional virtual screening) and reverse sense (inverse virtual screening (IVS)) are helpful techniques for interlacing the chemical universe of small molecules with the proteome. The former, which is using a protein structure and a large chemical database, is well-known by the scientific community. We have chosen here to provide an overview on the latter, focusing on validation and target prioritization strategies. By comparing it to complementary or alternative wet-lab approaches, we put IVS in the broader context of chemical genomics, target discovery and drug design. By giving examples from the literature and an own example on how to validate the approach, we provide guidance on the issues related to IVS.

Roles for ordered and bulk solvent in ligand recognition and docking in two related cavities

A key challenge in structure-based discovery is accounting for modulation of protein-ligand interactions by ordered and bulk solvent. To investigate this, we compared ligand binding to a buried cavity in Cytochrome c Peroxidase (CcP), where affinity is dominated by a single ionic interaction, versus a cavity variant partly opened to solvent by loop deletion. This opening had unexpected effects on ligand orientation, affinity, and ordered water structure. Some ligands lost over ten-fold in affinity and reoriented in the cavity, while others retained their geometries, formed new interactions with water networks, and improved affinity. To test our ability to discover new ligands against this opened site prospectively, a 534,000 fragment library was docked against the open cavity using two models of ligand solvation. Using an older solvation model that prioritized many neutral molecules, three such uncharged docking hits were tested, none of which was observed to bind; these molecules were not highly ranked by the new, context-dependent solvation score. Using this new method, another 15 highly-ranked molecules were tested for binding. In contrast to the previous result, 14 of these bound detectably, with affinities ranging from 8 µM to 2 mM. In crystal structures, four of these new ligands superposed well with the docking predictions but two did not, reflecting unanticipated interactions with newly ordered waters molecules. Comparing recognition between this open cavity and its buried analog begins to isolate the roles of ordered solvent in a system that lends itself readily to prospective testing and that may be broadly useful to the community.

Structured water molecules in the binding site of bromodomains can be displaced by cosolvent

Bromodomains are α-helical bundles of approximately 110 residues that recognize acetylated lysine side chains mainly on histone tails. Bromodomains are known to play an important role in cancer and inflammation, and as such, significant efforts are being made to identify small-molecule inhibitors of these epigenetic reader proteins. Here, explicit solvent molecular dynamics (MD) simulations of two bromodomains (BAZ2B and CREBBP) are used to analyze the water molecules that seem to be conserved at the bottom of the acetyl-lysine binding site in most crystal structures of bromodomains. The MD runs suggest that the occupancy of the structured water molecules is influenced by conformational transitions of the loop that connects helices Z and A. Additional simulations in the presence of 50 molecules of cosolvent (i.e., 440 mM of dimethylsulfoxide, methanol, or ethanol) indicate that some of the structured water molecules can be displaced transiently. The residence time in the acetyl-lysine binding site is calculated to be about 1 ns, 2-5 ns, and 10-30 ns for methanol, ethanol, and dimethylsulfoxide, respectively, while the affinity of the three cosolvents for BAZ2B and CREBBP is in the range of 50-500 mM. The results described have implications for ligand design, suggesting that only structured water molecules that do not exchange with cosolvent should be maintained in crystal structures used for docking campaigns, and that hydroxy substituents should be incorporated in the ligand so as to map the structured water molecules replaced by (m)ethanol.

Free enthalpies of replacing water molecules in protein binding pockets

Water molecules in the binding pocket of a protein and their role in ligand binding have increasingly raised interest in recent years. Displacement of such water molecules by ligand atoms can be either favourable or unfavourable for ligand binding depending on the change in free enthalpy. In this study, we investigate the displacement of water molecules by an apolar probe in the binding pocket of two proteins, cyclin-dependent kinase 2 and tRNA-guanine transglycosylase, using the method of enveloping distribution sampling (EDS) to obtain free enthalpy differences. In both cases, a ligand core is placed inside the respective pocket and the remaining water molecules are converted to apolar probes, both individually and in pairs. The free enthalpy difference between a water molecule and a CH(3) group at the same location in the pocket in comparison to their presence in bulk solution calculated from EDS molecular dynamics simulations corresponds to the binding free enthalpy of CH(3) at this location. From the free enthalpy difference and the enthalpy difference, the entropic contribution of the displacement can be obtained too. The overlay of the resulting occupancy volumes of the water molecules with crystal structures of analogous ligands shows qualitative correlation between experimentally measured inhibition constants and the calculated free enthalpy differences. Thus, such an EDS analysis of the water molecules in the binding pocket may give valuable insight for potency optimization in drug design.

A force field with discrete displaceable waters and desolvation entropy for hydrated ligand docking

In modeling ligand-protein interactions, the representation and role of water are of great importance. We introduce a force field and hydration docking method that enables the automated prediction of waters mediating the binding of ligands with target proteins. The method presumes no prior knowledge of the apo or holo protein hydration state and is potentially useful in the process of structure-based drug discovery. The hydration force field accounts for the entropic and enthalpic contributions of discrete waters to ligand binding, improving energy estimation accuracy and docking performance. The force field has been calibrated and validated on a total of 417 complexes (197 training set; 220 test set), then tested in cross-docking experiments, for a total of 1649 ligand-protein complexes evaluated. The method is computationally efficient and was used to model up to 35 waters during docking. The method was implemented and tested using unaltered AutoDock4 with new force field tables.

Leveraging structural information for the discovery of new drugs: computational methods

Escalating problems with drug resistance continue to compromise the effectiveness of commercial antibiotics, necessitating the search for novel classes of antimicrobial agents. To circumvent problems with resistance, a multitarget single-pharmacophore approach has been employed to discover inhibitors that possess balanced activity against multiple target enzymes. In this chapter, we examine the application of computational techniques, in particular, structure-based drug design approaches, to design new dual-targeting antibacterial agents against bacterial topoisomerases.

A computational approach for exploring carbohydrate recognition by lectins in innate immunity

Recognition of pathogen-associated carbohydrates by a broad range of carbohydrate-binding proteins is central to both adaptive and innate immunity. A large functionally diverse group of mammalian carbohydrate-binding proteins are lectins, which often display calcium-dependent carbohydrate interactions mediated by one or more carbohydrate recognition domains. We report here the application of molecular docking and site mapping to study carbohydrate recognition by several lectins involved in innate immunity or in modulating adaptive immune responses. It was found that molecular docking programs can identify the correct carbohydrate-binding mode, but often have difficulty in ranking it as the best pose. This is largely attributed to the broad and shallow nature of lectin binding sites, and the high flexibility of carbohydrates. Site mapping is very effective at identifying lectin residues involved in carbohydrate recognition, especially with cases that were found to be particularly difficult to characterize via molecular docking. This study highlights the need for alternative strategies to examine carbohydrate–lectin interactions, and specifically demonstrates the potential for mapping methods to extract additional and relevant information from the ensembles of binding poses generated by molecular docking.

Dynamics of conserved waters in human Hsp90: implications for drug design

The flexibility of a promising protein target, human heat shock protein 90 (Hsp90), is investigated by molecular dynamics simulations. These simulations focus on: (i) the interactions between the protein and conserved water molecules; and (ii) the interactions of the ligand PU3, the conserved water molecules and the protein. This is followed by a virtual screening docking study of the PU3 family of compounds and Hsp90 incorporating several conserved water molecules.

Exploiting ordered waters in molecular docking

A current weakness in docking is the treatment of water-mediated protein-ligand interactions. We explore switching ordered water molecules "on" and "off" during docking screens of a large library. The method assumes additivity and scales linearly with the number of waters sampled despite the exponential growth in configurations. It is tested for ligand enrichment against 24 targets, exploring up to 256 water configurations. Water inclusion increased enrichment substantially for 12 targets, while most others were largely unaffected.

Structural glycobiology: a game of snakes and ladders

Oligo- and polysaccharides are infamous for being extremely flexible molecules, populating a series of well-defined rotational isomeric states under physiological conditions. Characterization of this heterogeneous conformational ensemble has been a major obstacle impeding high-resolution structure determination of carbohydrates and acting as a bottleneck in the effort to understand the relationship between the carbohydrate structure and function. This challenge has compelled the field to develop and apply theoretical and experimental methods that can explore conformational ensembles by both capturing and deconvoluting the structural and dynamic properties of carbohydrates. This review focuses on computational approaches that have been successfully used in combination with experiment to detail the three-dimensional structure of carbohydrates in a solution and in a complex with proteins. In addition, emerging experimental techniques for three-dimensional structural characterization of carbohydrate-protein complexes and future challenges in the field of structural glycobiology are discussed. The review is divided into five sections: (1) The complexity and plasticity of carbohydrates, (2) Predicting carbohydrate-protein interactions, (3) Calculating relative and absolute binding free energies for carbohydrate-protein complexes, (4) Emerging and evolving techniques for experimental characterization of carbohydrate-protein structures, and (5) Current challenges in structural glycoscience.

Multivalent drug design and inhibition of cholera toxin by specific and transient protein-ligand interactions

Multivalent inhibitors of the cholera toxin B pentamer are potential therapeutic drugs for treating cholera and serve as models for demonstrating multivalent ligand effects through a structure-based approach. A crucial yet often overlooked aspect of multivalent drug design is the length, rigidity and chemical composition of the linker used to connect multiple binding moieties. To specifically study the role of chemical linkers in multivalent ligand design, we have synthesized a series of compounds with one and two binding motifs connected by several different linkers. These compounds have affinity for and potency against the cholera toxin B pentamer despite the fact that none can simultaneously bind two toxin receptor sites. Results from saturation transfer difference NMR reveal transient, non-specific interactions between the cholera toxin and linker groups contribute significantly to overall binding affinity of monovalent compounds. However, the same random protein-ligand interactions do not appear to affect binding of bivalent molecules. Moreover, the binding affinities and potencies of these 'non-spanning' bivalent ligands appear to be wholly independent of linker length. Our detailed analysis identifies multiple effects that account for the improved inhibitory potencies of bivalent ligands and suggest approaches to further improve the activity of this class of compounds.

Ligand-protein docking with water molecules

The presence of water molecules plays an important role in the accuracy of ligand-protein docking predictions. Comprehensive docking simulations have been performed on a large set of ligand-protein complexes whose crystal structures contain water molecules in their binding sites. Only those water molecules found in the immediate vicinity of both the ligand and the protein were considered. We have investigated whether prior optimization of the orientation of water molecules in either the presence or absence of the bound ligand has any effect on the accuracy of docking predictions. We have observed a statistically significant overall increase in accuracy when water molecules are included during docking simulations and have found this to be independent of the method of optimization of the orientation of water molecules. These results confirm the importance of including water molecules whenever possible in a ligand-protein docking simulation. Our findings also reveal that prior optimization of the orientation of water molecules, in the absence of any bound ligand, does not have a detrimental effect on the improved accuracy of ligand-protein docking. This is important, given the use of docking simulations to predict the binding modes of new ligands or drug molecules.

First round of a focused library of cholera toxin inhibitors

C-Galactosides have been used as scaffolds to design a library of non-hydrolysable inhibitors of cholera toxin (CT). Test elements from the library were synthesized and found to inhibit CT binding to an asialofetuin-coated SPR chip with micromolar affinity. Preliminary results are reported.

Classification of water molecules in protein binding sites

Water molecules play a crucial role in mediating the interaction between a ligand and a macromolecular receptor. An understanding of the nature and role of each water molecule in the active site of a protein could greatly increase the efficiency of rational drug design approaches: if the propensity of a water molecule for displacement can be determined, then synthetic effort may be most profitably applied to the design of specific ligands with the displacement of this water molecule in mind. In this paper, a thermodynamic analysis of water molecules in the binding sites of six proteins, each complexed with a number of inhibitors, is presented. Two classes of water molecules were identified: those conserved and not displaced by any of the ligands, and those that are displaced by some ligands. The absolute binding free energies of 54 water molecules were calculated using the double decoupling method, with replica exchange thermodynamic integration in Monte Carlo simulations. It was found that conserved water molecules are on average more tightly bound than displaced water molecules. In addition, Bayesian statistics is used to calculate the probability that a particular water molecule may be displaced by an appropriately designed ligand, given the calculated binding free energy of the water molecule. This approach therefore allows the numerical assessment of whether or not a given water molecule should be targeted for displacement as part of a rational drug design strategy.

Catalytic site prediction and virtual screening of cytochrome P450 2D6 substrates by consideration of water and rescoring in automated docking

Automated docking strategies successfully applied to binding mode predictions of ligands in Cyt P450 crystal structures in an earlier study (de Graaf et al. J. Med. Chem. 2005, 7, 2308-2318) were used for the catalytic site prediction (CSP) of 65 substrates in a CYP2D6 homology model. The consideration of water molecules at predicted positions in the active site and the rescoring of pooled docking poses from four different docking programs (AutoDock, FlexX, GOLD-Goldscore, and GOLD-Chemscore) with the SCORE scoring function enabled the successful prediction of experimentally reported sites of catalysis of more than 80% of the substrates. Three docking algorithms (FlexX, GOLD-Goldscore, and GOLD-Chemscore) were subsequently used in combination with six scoring functions (Chemscore, DOCK, FlexX, GOLD, PMF, and SCORE) to assess the ability of docking-based virtual screening methods to prioritize known CYP2D6 substrates seeded into a drug-like chemical database (in the absence and presence of active-site water molecules). Finally, the optimal docking strategy in terms of virtual screening accuracy, GOLD-Chemscore with the consideration of active-site water (60% of known substrates recovered in the top 5% of the ranked drug-like database), was verified experimentally; it was successfully used to identify high-affinity CYP2D6 ligands among a larger proprietary database.

Exploring structurally conserved solvent sites in protein families

Protein-bound water molecules are important components of protein structure, and therefore, protein function and energetics. Although structural conservation of solvent has been studied in a few protein families, a lack of suitable computational tools has hindered more comprehensive analyses. Herein we present a semiautomated computational approach for identifying solvent sites that are conserved among proteins sharing a common three-dimensional structure. This method is tested on six protein families: (1) monodomain cytochrome c, (2) fatty-acid binding protein, (3) lactate/malate dehydrogenase, (4) parvalbumin, (5) phospholipase A2, and (6) serine protease. For each family, the method successfully identified previously known conserved solvent sites. Moreover, the method discovered 22 novel conserved solvent sites, some of which have higher degrees of conservation than the previously known sites. All six families studied had solvent sites with more than 90% conservation and these sites were invariably located in regions of the protein with very high sequence conservation. These results suggest that highly conserved solvent sites, by virtue of their proximity to conserved residues, should be considered as one of the defining three-dimensional structural characteristics of protein families and folds.

Probing molecular docking in a charged model binding site

A model binding site was used to investigate charge-charge interactions in molecular docking. This simple site, a small (180A(3)) engineered cavity in cyctochrome c peroxidase (CCP), is negatively charged and completely buried from solvent, allowing us to explore the balance between electrostatic energy and ligand desolvation energy in a system where many of the common approximations in docking do not apply. A database with about 5300 molecules was docked into this cavity. Retrospective testing with known ligands and decoys showed that overall the balance between electrostatic interaction and desolvation energy was captured. More interesting were prospective docking scre"ens that looked for novel ligands, especially those that might reveal problems with the docking and energy methods. Based on screens of the 5300 compound database, both high-scoring and low-scoring molecules were acquired and tested for binding. Out of 16 new, high-scoring compounds tested, 15 were observed to bind. All of these were small heterocyclic cations. Binding constants were measured for a few of these, they ranged between 20microM and 60microM. Crystal structures were determined for ten of these ligands in complex with the protein. The observed ligand geometry corresponded closely to that predicted by docking. Several low-scoring alkyl amino cations were also tested and found to bind. The low docking score of these molecules owed to the relatively high charge density of the charged amino group and the corresponding high desolvation penalty. When the complex structures of those ligands were determined, a bound water molecule was observed interacting with the amino group and a backbone carbonyl group of the cavity. This water molecule mitigates the desolvation penalty and improves the interaction energy relative to that of the "naked" site used in the docking screen. Finally, six low-scoring neutral molecules were also tested, with a view to looking for false negative predictions. Whereas most of these did not bind, two did (phenol and 3-fluorocatechol). Crystal structures for these two ligands in complex with the cavity site suggest reasons for their binding. That these neutral molecules do, in fact bind, contradicts previous results in this site and, along with the alkyl amines, provides instructive false negatives that help identify weaknesses in our scoring functions. Several improvements of these are considered.

The role and application of in silico docking in chemical genomics research

In silico docking techniques are being used to investigate the complementarity at the molecular level of a ligand and a protein target. As such, docking studies can be used to identify the structural features that are important for binding and for in silico screening efforts in which suitable binding partners can be identified. Here we describe a practical approach for setting up docking simulations using different docking programs. We also cover the analysis and rescoring of the obtained docking poses. Possible pitfalls in the docking studies are discussed and hints are provided to resolve commonly occurring problems.

Toward Selective Histone Deacetylase Inhibitor Design: Homology Modeling, Docking Studies, and Molecular Dynamics Simulations of Human Class I Histone Deacetylases

Histone deacetylases (HDACs) play an important role in gene transcription. Inhibitors of HDACs induce cell differentiation and suppress cell proliferation in tumor cells. Although many HDAC inhibitors have been designed and synthesized, selective inhibition for class I HDAC isoforms is a goal that has yet to be achieved. To understand the difference between class I HDAC isoforms that could be exploited for the design of isoform-specific HDAC inhibitors, we have built three-dimensional models of four class I histone deacetylases, HDAC1, HDAC2, HDAC3, and HDAC8. Comparison of the homology model of HDAC8 with the recently published X-ray structure shows excellent agreement and validates the approach. A series of HDAC inhibitors were docked to the homology models to understand the similarities and differences between the binding modes. Molecular dynamic simulations of these HDAC-inhibitor complexes indicate that the interaction between the protein surface and inhibitor is playing an important role; also some active site residues show some flexibility, which is usually not included in routine docking protocols. The implications of these results for the design of isoform-selective HDAC inhibitors are discussed.

Binding mode prediction of cytochrome p450 and thymidine kinase protein-ligand complexes by consideration of water and rescoring in automated docking

The popular docking programs AutoDock, FlexX, and GOLD were used to predict binding modes of ligands in crystallographic complexes including X-ray water molecules or computationally predicted water molecules. Isoenzymes of two different enzyme systems were used, namely cytochromes P450 (n = 19) and thymidine kinases (n = 19) and three different "water" scenarios: i.e., docking (i) into water-free active sites, (ii) into active sites containing crystallographic water molecules, and (iii) into active sites containing water molecules predicted by a novel approach based on the program GRID. Docking accuracies were determined in terms of the root-mean-square deviation (RMSD) accuracy and, newly defined, in terms of the ligand catalytic site prediction (CSP) accuracy. Consideration of both X-ray and predicted water molecules and the subsequent pooling and rescoring of all solutions (generated by all three docking programs) with the SCORE scoring function significantly improved the quality of prediction of the binding modes both in terms of RMSD and CSP accuracy.

Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by +/- 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 A RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.

On the Function of the 14 Å Long Internal Cavity of Histone Deacetylase-Like Protein: Implications for the Design of Histone Deacetylase Inhibitors

Histone deacetylases (HDACs) play an important role in gene transcription. Inhibitors of HDACs induce cell differentiation and suppress cell proliferation in tumor cells. AutoDock calculations of known and novel HDAC inhibitors as well as of several probe molecules to histone deacetylase-like protein (HDLP), using a modified scoring function for metalloproteins, demonstrate excellent agreement (R = 0.92) between experimental and computed binding constants. Analysis of the docked structures allows a determination of the different binding motifs in known inhibitors. Such calculations are a useful tool for the prediction of binding constants for new HDAC inhibitors. Exploration of the 14 A long internal cavity adjacent to the active site by docking of small molecular probes suggest that it plays a crucial role by accepting the cleaved acetate and releasing it at the far side of the cavity. The importance of the findings for the design of new inhibitors is discussed.

Specific empirical free energy function for automated docking of carbohydrates to proteins

We present an automated docking protocol specifically optimized to predict the structure and affinity of a protein-carbohydrate complex. A scoring function was developed based on a training set of 30 protein-carbohydrate complexes of known structure and affinity. Combinations of several models for hydrogen bonding, torsional entropy loss, and solvation were tested for their ability to fit the training set data, and the best model was used with AutoDock. The electrostatic empirical coefficient is larger than in a previously obtained model using a training set comprised of various types of protein-ligand complexes, indicating that electrostatic interactions play a more important role in determining the affinity between a carbohydrate and a protein. The differences in the relative weighting of the empirical coefficients in the model yields predicted free energies for the training set with a standard error of 1.403 kcal/mol. The new scoring function was tested on 17 Aspergillus niger glucoamylase inhibitors for which binding energies had been determined experimentally. Free energies of complex formation were predicted with a residual standard error of 1.101 kcal/mol. The new scoring function therefore provides a robust method for predicting free energies of formation and optimal conformations of carbohydrate-protein complexes.

A Comprehensive Docking Study on the Selectivity of Binding of Aromatic Compounds to Proteins

Generally, computer-aided drug design is focused on screening of ligand molecules for a single protein target. The screening of several proteins for a ligand is a relatively new application of molecular docking. In the present study, complexes from the Brookhaven Protein Databank were used to investigate a docking approach of protein screening. Automated molecular docking calculations were applied to reproduce 44 protein-aromatic ligand complexes (31 different proteins and 39 different ligand molecules) of the databank. All ligands were docked to all different protein targets in altogether 12090 docking runs. Based on the results of the extensive docking simulations, two relative measures, the molecular interaction fingerprint (MIF) and the molecular affinity fingerprint (MAF), were introduced to describe the selectivity of aromatic ligands to different proteins. MIF and MAF patterns are in agreement with fragment and similarity considerations. Limitations and future extension of our approach are discussed.

A substrate variant as a high-affinity, reversible inhibitor: insight from the X-ray structure of cilastatin bound to membrane dipeptidase

An analysis of the X-ray structure of cilastatin bound to membrane dipeptidase, together with docking studies, is presented here to reveal how a simple amide may act as a high-affinity, reversible, amidase inhibitor. Cilastatin binds as a normal substrate and is orientated in a perfect near-attack conformer for formation of a tetrahedral intermediate with the zinc-bound water/hydroxide. This intermediate is fated, however, only to revert to its starting components as scission of the amide bond is prevented by the precise fit of cilastatin within the active site. The cilastatin alkyl end groups that are tightly buttressed against amino acid residues on opposite sides of the active site, are aligned along the C-N reaction coordinate axis thereby preventing collapse of the intermediate via rupture of the C-N bond. Such a feature could have more general applicability in the explicit design of substrate variants as selective, tight-binding, and reversible inhibitors.

Utilising structural knowledge in drug design strategies: applications using Relibase

The concept of structure-based drug design is based upon an in-depth understanding of the principles of molecular recognition. Despite our lack of a thorough comprehension of these principles, the wealth of protein structures available opens up unprecedented possibilities for new insights from the analysis of these data. Unravelling universal rules of molecular recognition is certainly one of the most appealing goals. But our knowledge is enhanced also when studying the specific determinants that characterise single targets or target families only, and the factors governing and discriminating their recognition properties.Here, we illustrate how the structure-based design process can benefit from the consequent incorporation of database query tools. We discuss representative examples to address issues such as protein flexibility, water molecules in binding pockets, and ligand specificity as some of the most critical aspects of drug design. All studies are carried out using our database system Relibase. We also show the application of Relibase in searching for preferred geometrical patterns between interacting molecular fragments.

Structure-based approach for binding site identification on AmpC beta-lactamase

Beta-lactamases are the most widespread resistance mechanism to beta-lactam antibiotics and are an increasing menace to public health. Several beta-lactamase structures have been determined, making this enzyme an attractive target for structure-based drug design. To facilitate inhibitor design for the class C beta-lactamase AmpC, binding site "hot spots" on the enzyme were identified using experimental and computational approaches. Experimentally, X-ray crystal structures of AmpC in complexes with four boronic acid inhibitors and a higher resolution (1.72 A) native apo structure were determined. Along with previously determined structures of AmpC in complexes with five other boronic acid inhibitors and four beta-lactams, consensus binding sites were identified. Computationally, the programs GRID, MCSS, and X-SITE were used to predict potential binding site hot spots on AmpC. Several consensus binding sites were identified from the crystal structures. An amide recognition site was identified by the interaction between the carbonyl oxygen in the R1 side chain of beta-lactams and the atom Ndelta2 of the conserved Asn152. Surprisingly, this site also recognizes the aryl rings of arylboronic acids, appearing to form quadrupole-dipole interactions with Asn152. The highly conserved "oxyanion" hole defines a site that recognizes both carbonyl and hydroxyl groups. A hydroxyl binding site was identified by the O2 hydroxyl in the boronic acids, which hydrogen bonds with Tyr150 and a conserved water. A hydrophobic site is formed by Leu119 and Leu293. A carboxylate binding site was identified by the ubiquitous C3(4) carboxylate of the beta-lactams, which interacts with Asn346 and Arg349. Four water sites were identified by ordered waters observed in most of the structures; these waters form extensive hydrogen-bonding networks with AmpC and occasionally the ligand. Predictions by the computational programs showed some correlation with the experimentally observed binding sites. Several sites were not predicted, but novel binding sites were suggested. Taken together, a map of binding site hot spots found on AmpC, along with information on the functionality recognized at each site, was constructed. This map may be useful for structure-based inhibitor design against AmpC.

Principles governing the binding of a class of non-peptidic inhibitors to the SH2 domain of src studied by X-ray analysis

A total of 11 structures of the (pp60)src SH2 domain with non-peptidic inhibitors based on the same two closely related inhibitor scaffolds were determined using X-ray crystallography. Surprisingly, the inhibitors that have an IC(50) value between 4 and 2700 nM bind in three different binding modes. Structure comparisons show that the inhibitors aim to maximize the interaction between the hydrophobic substituent and the hydrophobic pY+3 pocket. This is achieved either by an alternative binding mode of the phenyl phosphate or by including water molecules that mediate the interaction between the inhibitor scaffold and a rigid surface of the SH2 domain. The combination of the rigid pY+3 pocket and the rigid protein surface to which the scaffolds bind results in severe distance and angular restraints for putative scaffolds and their substituents. The X-ray data suggest that these restraints seem to be compensated in our system by including water molecules, thereby increasing the flexibility of the system.

Efficient docking of peptides to proteins without prior knowledge of the binding site

Reliability in docking of ligand molecules to proteins or other targets is an important challenge for molecular modeling. Applications of the docking technique include not only prediction of the binding mode of novel drugs, but also other problems like the study of protein-protein interactions. Here we present a study on the reliability of the results obtained with the popular AutoDock program. We have performed systematical studies to test the ability of AutoDock to reproduce eight different protein/ligand complexes for which the structure was known, without prior knowledge of the binding site. More specifically, we look at factors influencing the accuracy of the final structure, such as the number of torsional degrees of freedom in the ligand. We conclude that the Autodock program package is able to select the correct complexes based on the energy without prior knowledge of the binding site. We named this application blind docking, as the docking algorithm is not able to "see" the binding site but can still find it. The success of blind docking represents an important finding in the era of structural genomics.

Structure-based discovery of a novel, noncovalent inhibitor of AmpC beta-lactamase

beta-lactamases are the most widespread resistance mechanisms to beta-lactam antibiotics, and there is a pressing need for novel, non-beta-lactam drugs. A database of over 200,000 compounds was docked to the active site of AmpC beta-lactamase to identify potential inhibitors. Fifty-six compounds were tested, and three had K(i) values of 650 microM or better. The best of these, 3-[(4-chloroanilino)sulfonyl]thiophene-2-carboxylic acid, was a competitive noncovalent inhibitor (K(i) = 26 microM), which also reversed resistance to beta-lactams in bacteria expressing AmpC. The structure of AmpC in complex with this compound was determined by X-ray crystallography to 1.94 A and reveals that the inhibitor interacts with key active-site residues in sites targeted in the docking calculation. Indeed, the experimentally determined conformation of the inhibitor closely resembles the prediction. The structure of the enzyme-inhibitor complex presents an opportunity to improve binding affinity in a novel series of inhibitors discovered by structure-based methods.

Structural and ICAM-1-docking properties of a cyclic peptide from the I-domain of LFA-1: an inhibitor of ICAM-1/LFA- 1-mediated T-cell adhesion

The purpose of this work was to study the conformation of cyclic peptide 1, cyclo(1,12)-Pen1-Ile2-Thr3-Asp4-Gly5-Glu6-Ala7- Thr8-Asp9-Ser10-Gly11-Cys12-OH, derived from the I-domain of the LFA-1 alpha-subunit. We found that cyclic peptide 1 can bind to the D1-domain of ICAM-1 and inhibit ICAM-1/LFA-1-mediated homotypic and heterotypic T-cell adhesion. To understand the bioactive conformation and binding requirements for cyclic peptide 1, its solution structure was studied using NMR, CD, and molecular dynamics simulations. Furthermore, possible binding properties between the cyclic peptide and the D1-domain of ICAM-1 were evaluated using docking experiments. This cyclic peptide has a stable betaII -turn at Asp4- Gly5-Glu6-Ala7 and a betaI-turn at Pen1-Ile2-Thr3-Asp4; a less stable betaV-turn is found at the C-terminal region. The beta-turn at Asp4- Gly5-Glu6-Ala7 was also found in the X-ray structure of the I-domain of LFA-1. Our CD studies showed that the peptide binds to calcium/magnesium and forms a 1:1 (peptide:calcium/magnesium) complex with low cation concentrations and multiple types of complexes with higher cation concentrations. Binding to divalent cations causes a conformational change in peptide 1; this is consistent with our previous study that binding of peptide 1 to ICAM-1 was influenced by divalent cations. Docking studies show the interaction between cyclic peptide 1 and the D1-domain of ICAM-1; it indicates that the Ile2-Thr3-Asp4-Gly4-Glu6-Ala7-Thr8 sequence interacts with the F and C strands of the D1-domain. Finally, these studies will help us design a new generation of selective peptides that may bind better to the D1-domain of ICAM-1.

Computational characterization of substrate binding and catalysis in S-adenosylhomocysteine hydrolase

S-Adenosylhomocysteine (AdoHcy) hydrolase catalyzes the reversible hydrolysis of AdoHcy to adenosine (Ado) and homocysteine (Hcy), playing an essential role in modulating the cellular Hcy levels and regulating activities of a host of methyltransferases in eukaryotic cells. This enzyme exists in an open conformation (active site unoccupied) and a closed conformation (active site occupied with substrate or inhibitor) [Turner, M. A., Yang, X., Yin, D., Kuczera, K., Borchardt, R. T., and Howell, P. L. (2000) Cell Biochem. Biophys. 33, 101-125]. To investigate the binding of natural substrates during catalysis, the computational docking program AutoDock (with confirming calculations using CHARMM) was used to predict the binding modes of various substrates or inhibitors with the closed and open forms of AdoHcy hydrolase. The results have revealed that the interaction between a substrate and the open form of the enzyme is nonspecific, whereas the binding of the substrate in the closed form is highly specific with the adenine moiety of a substrate as the main recognition factor. Residues Thr57, Glu59, Glu156, Gln181, Lys186, Asp190, Met351, and His35 are involved in substrate binding, which is consistent with the crystal structure. His55 in the docked model appears to participate in the elimination of water from Ado through the interaction with the 5'-OH group of Ado. In the same reaction, Asp131 removes a proton from the 4' position of the substrate after the oxidation-reduction reaction in the enzyme. To identify the residues that bind the Hcy moiety, AdoHcy was docked to the closed form of AdoHcy hydrolase. The Hcy tail is predicted to interact with His55, Cys79, Asn80, Asp131, Asp134, and Leu344 in a strained conformation, which may lower the reaction barrier and enhance the catalysis rate.

Synergistic inhibitory activity of alpha- and beta-LFA-1 peptides on LFA-1/ICAM-1 interaction

Interactions of cell-adhesion molecule LFA-1 and its ligand ICAM-1 play important roles during immune and inflammatory responses. Critical residues of LFA-1 for ICAM-1 binding are known to be in the I-domain of the alpha-subunit and the I-like domain of the beta-subunit. On the basis of our previous work demonstrating the inhibitory activity of I-domain cyclic peptide cLAB.L on LFA-1/ICAM-1 interaction, here we have explored the activity of I-like-domain peptide LBE on the binding mechanism of cLAB.L. LBE enhances cLAB.L binding to T-cells and epithelial cells. The adherence of T-cells to epithelial monolayers was suppressed by the two peptides. The addition of LBE to the monolayers prior to the addition cLAB.L produced a better inhibitory effect than the reverse procedure. LBE, but not cLAB.L, changes the ICAM-1 conformation, suggesting that LBE binds to ICAM-1 at sites that are distinct from these of cLAB.L and induces improved conformation in ICAM-1 for binding to cLAB.L.

Synthesis and biological evaluation of all A-ring stereoisomers of 5,6-trans-2-methyl-1,25-dihydroxyvitamin D(3) and their 20-epimers: possible binding modes of potent A-ring analogues to vitamin D receptor

BACKGROUND

The secosteroid 1 alpha,25-dihydroxyvitamin D(3) (1) has a wide variety of biological activities, which makes it a promising therapeutic agent for the treatment of cancer, psoriasis and osteoporosis. Insight into the structure-activity relationships of the A-ring of 1 is still needed to assist the development of more potent and selective analogues as candidate chemotherapeutic agents, as well as to define the molecular mode of action.

RESULTS

All possible A-ring stereoisomers of 5,6-trans-2-methyl-1,25-dihydroxyvitamin D(3) (6a-h) and their 20-epimers (7a-h) were designed and efficiently synthesized. The dependence of the affinities for vitamin D receptor (VDR) and vitamin D binding protein (DBP), as well as the HL-60 cell differentiation-inducing activity, upon the stereochemistry of the A-ring and at C20 in the side chain was evaluated.

CONCLUSIONS

The binding affinities and potency of the 5,6-trans and 5,6-cis analogues were enhanced by a 2-methyl substituent in a certain orientation. Molecular docking studies based upon the X-ray crystal structure of VDR suggested that the axial 2-methyl group would be accommodated in a pocket surrounded by hydrophobic amino acid residues in the ligand binding domain, resulting in enhanced interaction.

Molecular mechanism for agonist-promoted alpha(2A)-adrenoceptor activation by norepinephrine and epinephrine

We present a mechanism for agonist-promoted alpha(2A)-adrenergic receptor (alpha(2A)-AR) activation based on structural, pharmacological, and theoretical evidence of the interactions between phenethylamine ligands and alpha(2A)-AR. In this study, we have: 1) isolated enantiomerically pure phenethylamines that differ both in their chirality about the beta-carbon, and in the presence/absence of one or more hydroxyl groups: the beta-OH and the catecholic meta- and para-OH groups; 2) used [(3)H]UK-14,304 [5-bromo-N-(4,5-dihydro-1H-imidazol-2-yl)-6-quinoxalinamine; agonist] and [(3)H]RX821002 [2-(2-methoxy-1,4-benzodioxan-2-yl)-2-imidazoline; antagonist] competition binding assays to determine binding affinities of these ligands to the high- and low-affinity forms of alpha(2A)-AR; 3) tested the ability of the ligands to promote receptor activation by measuring agonist-induced stimulation of [(35)S]GTPgammaS binding in isolated cell membranes; and 4) used automated docking methods and our alpha(2A)-AR model to predict the binding modes of the ligands inside the alpha(2A)-AR binding site. The ligand molecules are sequentially missing different functional groups, and we have correlated the structural features of the ligands and ligand-receptor interactions with experimental ligand binding and receptor activation data. Based on the analysis, we show that structural rearrangements in transmembrane helix (TM) 5 could take place upon binding and subsequent activation of alpha(2A)-AR by phenethylamine agonists. We suggest that the following residues are important in phenethylamine interactions with alpha(2A)-AR: Asp113 (D(3.32)), Val114 (V(3.33)), and Thr118 (T(3.37)) in TM3; Ser200 (S(5.42)), Cys201 (C(5.43)), and Ser204 (S(5.46)) in TM5; Phe391 (F(6.52)) and Tyr394 (Y(6.55)) in TM6; and Phe411 (F(7.38)) and Phe412 (F(7.39)) in TM7.

Simulation of carbohydrate-protein interactions: computer-aided design of a second generation GM1 mimic

The oligosaccharide of ganglioside GM1 [Galbeta1-3GalNAcbeta1-4(NeuAcalpha2-3)Galbeta1-4Glcbeta1-1Cer] is the cellular target of two bacterial enterotoxins: the cholera toxin (CT) and the heat-labile toxin of E. coli (LT). We recently reported that the pseudosaccharide 2 [Galbeta1-3GalNAcbeta1-4(NeuAcalpha2-3)DCCHD] is a high-affinity ligand for CT. and thus a functional mimic of GM1 (Bernardi, A., Checchia, A., Brocca, P., Sonnino, S. and Zuccotto, F., J. Am. Chem. Soc., 121 (1999) 2032-2036). In this paper we describe the design of a second-generation mimic, formally obtained from 2 by inverting the configuration of a single stereocenter, thus transforming a N-acetyl galactosamine into a N-acetyl glucosamine. The design process involved modeling of the free ligand and its LT complex, followed by qualitative and quantitative comparison with the corresponding structures of 2. The protocol employed relied on both conformational search and molecular dynamics methodologies to account for the flexibility of both the ligand and the protein receptor. The conformational search of the LT:inhibitor complex showed that, compared to 2, the new compound can insert one more hydroxy group within the protein binding site. Molecular dynamics simulations showed that, in turn, this may trigger a series of rearrangements and reorientations of side chains and crystallographic water molecules in the toxin, leading to new H-bond contacts which may result in enhanced affinity of the new inhibitor. FEP calculations were performed by mutating the structure of 2 in solution and in the protein complex, and the prediction was made that the second-generation mimic should be a stronger binder than its parent compound.