Tracing changes in protonation: a prerequisite to factorize thermodynamic data of inhibitor binding to aldose reductase

Mutational Studies of Aldose Reductase to Trace a Transient Pocket Opening and to Explain Ligand Affinity Cliffs

Human aldose reductase, a target for the development of inhibitors for preventing diabetic complications, displays a transient specificity pocket which opens upon binding with specific, potent inhibitors. We investigated the opening mechanism of this pocket by mutating leucine residues involved in the gate keeping mechanism to alanine. Two isostructural inhibitors distinguished only by a single nitro to carboxy group replacement, have a 1000-fold difference in their binding affinity to the wild type. This difference is reduced to 10-fold in the mutated variants as the nitro derivative loses in affinity but conserves binding to the open transient pocket. The affinity of the carboxylate analog is minimally altered but the analog binding preference changes from the closed to open state of the transient pocket. Differences in the solvation properties of ligands and the transient pocket as well as changes from induced fit to conformational selections provide an explanation for the altered behavior of the ligands with respect to their binding to the different variants.

Quantifying cooperative multisite binding in the hub protein LC8 through Bayesian inference

Multistep protein-protein interactions underlie most biological processes, but their characterization through methods such as isothermal titration calorimetry (ITC) is largely confined to simple models that provide little information on the intermediate, individual steps. In this study, we primarily examine the essential hub protein LC8, a small dimer that binds disordered regions of 100+ client proteins in two symmetrical grooves at the dimer interface. Mechanistic details of LC8 binding have remained elusive, hampered in part by ITC data analyses employing simple models that treat bivalent binding as a single event with a single binding affinity. We build on existing Bayesian ITC approaches to quantify thermodynamic parameters for multi-site binding interactions impacted by significant uncertainty in protein concentration. Using a two-site binding model, we identify positive cooperativity with high confidence for LC8 binding to multiple client peptides. In contrast, application of an identical model to the two-site binding between the coiled-coil NudE dimer and the intermediate chain of dynein reveals little evidence of cooperativity. We propose that cooperativity in the LC8 system drives the formation of saturated induced-dimer structures, the functional units of most LC8 complexes. In addition to these system-specific findings, our work advances general ITC analysis in two ways. First, we describe a previously unrecognized mathematical ambiguity in concentrations in standard binding models and clarify how it impacts the precision with which binding parameters are determinable in cases of high uncertainty in analyte concentrations. Second, building on observations in the LC8 system, we develop a system-agnostic heat map of practical parameter identifiability calculated from synthetic data which demonstrates that the ability to determine microscopic binding parameters is strongly dependent on both the parameters themselves and experimental conditions. The work serves as a foundation for determination of multi-step binding interactions, and we outline best practices for Bayesian analysis of ITC experiments.

Pharmacophore Modeling of Targets Infested with Activity Cliffs via Molecular Dynamics Simulation Coupled with QSAR and Comparison with other Pharmacophore Generation Methods: KDR as Case Study

Activity cliffs (ACs) are defined as pairs of structurally similar compounds with large difference in their potencies against certain biotarget. We recently proposed that potent AC members induce significant entropically-driven conformational modifications of the target that unveil additional binding interactions, while their weakly-potent counterparts are enthalpically-driven binders with little influence on the protein target. We herein propose to extract pharmacophores for ACs-infested target(s) from molecular dynamics (MD) frames of purely "enthalpic" potent binder(s) complexed within the particular target. Genetic function algorithm/machine learning (GFA/ML) can then be employed to search for the best possible combination of MD pharmacophore(s) capable of explaining bioactivity variations within a list of inhibitors. We compared the performance of this approach with established ligand-based and structure-based methods. Kinase inserts domain receptor (KDR) was used as a case study. KDR plays a crucial role in angiogenic signaling and its inhibitors have been approved in cancer treatment. Interestingly, GFA/ML selected, MD-based, pharmacophores were of comparable performances to ligand-based and structure-based pharmacophores. The resulting pharmacophores and QSAR models were used to capture hits from the national cancer institute list of compounds. The most active hit showed anti-KDR IC50 of 2.76 µM.

In Search of Differential Inhibitors of Aldose Reductase

Aldose reductase, classified within the aldo-keto reductase family as AKR1B1, is an NADPH dependent enzyme that catalyzes the reduction of hydrophilic as well as hydrophobic aldehydes. AKR1B1 is the first enzyme of the so-called polyol pathway that allows the conversion of glucose into sorbitol, which in turn is oxidized to fructose by sorbitol dehydrogenase. The activation of the polyol pathway in hyperglycemic conditions is generally accepted as the event that is responsible for a series of long-term complications of diabetes such as retinopathy, cataract, nephropathy and neuropathy. The role of AKR1B1 in the onset of diabetic complications has made this enzyme the target for the development of molecules capable of inhibiting its activity. Virtually all synthesized compounds have so far failed as drugs for the treatment of diabetic complications. This failure may be partly due to the ability of AKR1B1 to reduce alkenals and alkanals, produced in oxidative stress conditions, thus acting as a detoxifying agent. In recent years we have proposed an alternative approach to the inhibition of AKR1B1, suggesting the possibility of a differential inhibition of the enzyme through molecules able to preferentially inhibit the reduction of either hydrophilic or hydrophobic substrates. The rationale and examples of this new generation of aldose reductase differential inhibitors (ARDIs) are presented.

Which Properties Allow Ligands to Open and Bind to the Transient Binding Pocket of Human Aldose Reductase?

The transient specificity pocket of aldose reductase only opens in response to specific ligands. This pocket may offer an advantage for the development of novel, more selective ligands for proteins with similar topology that lack such an adaptive pocket. Our aim was to elucidate which properties allow an inhibitor to bind in the specificity pocket. A series of inhibitors that share the same parent scaffold but differ in their attached aromatic substituents were screened using ITC and X-ray crystallography for their ability to occupy the pocket. Additionally, we investigated the electrostatic potentials and charge distribution across the attached terminal aromatic groups with respect to their potential to bind to the transient pocket of the enzyme using ESP calculations. These methods allowed us to confirm the previously established hypothesis that an electron-deficient aromatic group is an important prerequisite for opening and occupying the specificity pocket. We also demonstrated from our crystal structures that a pH shift between 5 and 8 does not affect the binding position of the ligand in the specificity pocket. This allows for a comparison between thermodynamic and crystallographic data collected at different pH values.

Overview of the SAMPL6 host-guest binding affinity prediction challenge

Accurately predicting the binding affinities of small organic molecules to biological macromolecules can greatly accelerate drug discovery by reducing the number of compounds that must be synthesized to realize desired potency and selectivity goals. Unfortunately, the process of assessing the accuracy of current computational approaches to affinity prediction against binding data to biological macromolecules is frustrated by several challenges, such as slow conformational dynamics, multiple titratable groups, and the lack of high-quality blinded datasets. Over the last several SAMPL blind challenge exercises, host-guest systems have emerged as a practical and effective way to circumvent these challenges in assessing the predictive performance of current-generation quantitative modeling tools, while still providing systems capable of possessing tight binding affinities. Here, we present an overview of the SAMPL6 host-guest binding affinity prediction challenge, which featured three supramolecular hosts: octa-acid (OA), the closely related tetra-endo-methyl-octa-acid (TEMOA), and cucurbit[8]uril (CB8), along with 21 small organic guest molecules. A total of 119 entries were received from ten participating groups employing a variety of methods that spanned from electronic structure and movable type calculations in implicit solvent to alchemical and potential of mean force strategies using empirical force fields with explicit solvent models. While empirical models tended to obtain better performance than first-principle methods, it was not possible to identify a single approach that consistently provided superior results across all host-guest systems and statistical metrics. Moreover, the accuracy of the methodologies generally displayed a substantial dependence on the system considered, emphasizing the need for host diversity in blind evaluations. Several entries exploited previous experimental measurements of similar host-guest systems in an effort to improve their physical-based predictions via some manner of rudimentary machine learning; while this strategy succeeded in reducing systematic errors, it did not correspond to an improvement in statistical correlation. Comparison to previous rounds of the host-guest binding free energy challenge highlights an overall improvement in the correlation obtained by the affinity predictions for OA and TEMOA systems, but a surprising lack of improvement regarding root mean square error over the past several challenge rounds. The data suggests that further refinement of force field parameters, as well as improved treatment of chemical effects (e.g., buffer salt conditions, protonation states), may be required to further enhance predictive accuracy.

Bayesian analysis of isothermal titration calorimetry for binding thermodynamics

Isothermal titration calorimetry (ITC) is the only technique able to determine both the enthalpy and entropy of noncovalent association in a single experiment. The standard data analysis method based on nonlinear regression, however, provides unrealistically small uncertainty estimates due to its neglect of dominant sources of error. Here, we present a Bayesian framework for sampling from the posterior distribution of all thermodynamic parameters and other quantities of interest from one or more ITC experiments, allowing uncertainties and correlations to be quantitatively assessed. For a series of ITC measurements on metal:chelator and protein:ligand systems, the Bayesian approach yields uncertainties which represent the variability from experiment to experiment more accurately than the standard data analysis. In some datasets, the median enthalpy of binding is shifted by as much as 1.5 kcal/mol. A Python implementation suitable for analysis of data generated by MicroCal instruments (and adaptable to other calorimeters) is freely available online.

Price for Opening the Transient Specificity Pocket in Human Aldose Reductase upon Ligand Binding: Structural, Thermodynamic, Kinetic, and Computational Analysis

Insights into the thermodynamic and kinetic signature of the transient opening of a protein-binding pocket resulting from accommodation of suitable substituents attached to a given parent ligand scaffold are presented. As a target, we selected human aldose reductase, an enzyme involved in the development of late-stage diabetic complications. To recognize a large scope of substrate molecules, this reductase opens a transient specificity pocket. The pocket-opening step was studied by X-ray crystallography, microcalorimetry, and surface plasmon resonance using a narrow series of 2-carbamoyl-phenoxy-acetic acid derivatives. Molecular dynamics simulations suggest that pocket opening occurs only once an appropriate substituent is attached to the parent scaffold. Transient pocket opening of the uncomplexed protein is hardly recorded. Hydration-site analysis suggests that up to five water molecules entering the opened pocket cannot stabilize this state. Sole substitution with a benzyl group stabilizes the opened state, and the energetic barrier for opening is estimated to be ∼5 kJ/mol. Additional decoration of the pocket-opening benzyl substituent with a nitro group results in a huge enthalpy-driven potency increase; on the other hand, an isosteric carboxylic acid group reduces the potency 1000-fold, and binding occurs without pocket opening. We suggest a ligand induced-fit mechanism for the pocket-opening step, which, however, does not represent the rate-determining step in binding kinetics.

Binding Pose Flip Explained via Enthalpic and Entropic Contributions

The anomalous binding modes of five highly similar fragments of TIE2 inhibitors, showing three distinct binding poses, are investigated. We report a quantitative rationalization for the changes in binding pose based on molecular dynamics simulations. We investigated five fragments in complex with the transforming growth factor β receptor type 1 kinase domain. Analyses of these simulations using Grid Inhomogeneous Solvation Theory (GIST), pK_A calculations, and a tool to investigate enthalpic differences upon binding unraveled the various thermodynamic contributions to the different binding modes. While one binding mode flip can be rationalized by steric repulsion, the second binding pose flip revealed a different protonation state for one of the ligands, leading to different enthalpic and entropic contributions to the binding free energy. One binding pose is stabilized by the displacement of entropically unfavored water molecules (binding pose determined by solvation entropy), ligands in the other binding pose are stabilized by strong enthalpic interactions, overcompensating the unfavorable water entropy in this pose (binding pose determined by enthalpic interactions). This analysis elucidates unprecedented details determining the flipping of the binding modes, which can elegantly explain the experimental findings for this system.

Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge

Small molecule distribution coefficients between immiscible nonaqueuous and aqueous phases-such as cyclohexane and water-measure the degree to which small molecules prefer one phase over another at a given pH. As distribution coefficients capture both thermodynamic effects (the free energy of transfer between phases) and chemical effects (protonation state and tautomer effects in aqueous solution), they provide an exacting test of the thermodynamic and chemical accuracy of physical models without the long correlation times inherent to the prediction of more complex properties of relevance to drug discovery, such as protein-ligand binding affinities. For the SAMPL5 challenge, we carried out a blind prediction exercise in which participants were tasked with the prediction of distribution coefficients to assess its potential as a new route for the evaluation and systematic improvement of predictive physical models. These measurements are typically performed for octanol-water, but we opted to utilize cyclohexane for the nonpolar phase. Cyclohexane was suggested to avoid issues with the high water content and persistent heterogeneous structure of water-saturated octanol phases, since it has greatly reduced water content and a homogeneous liquid structure. Using a modified shake-flask LC-MS/MS protocol, we collected cyclohexane/water distribution coefficients for a set of 53 druglike compounds at pH 7.4. These measurements were used as the basis for the SAMPL5 Distribution Coefficient Challenge, where 18 research groups predicted these measurements before the experimental values reported here were released. In this work, we describe the experimental protocol we utilized for measurement of cyclohexane-water distribution coefficients, report the measured data, propose a new bootstrap-based data analysis procedure to incorporate multiple sources of experimental error, and provide insights to help guide future iterations of this valuable exercise in predictive modeling.

Structural Determinants of the Selectivity of 3-Benzyluracil-1-acetic Acids toward Human Enzymes Aldose Reductase and AKR1B10

The human enzymes aldose reductase (AR) and AKR1B10 have been thoroughly explored in terms of their roles in diabetes, inflammatory disorders, and cancer. In this study we identified two new lead compounds, 2-(3-(4-chloro-3-nitrobenzyl)-2,4-dioxo-3,4-dihydropyrimidin-1(2H)-yl)acetic acid (JF0048, 3) and 2-(2,4-dioxo-3-(2,3,4,5-tetrabromo-6-methoxybenzyl)-3,4-dihydropyrimidin-1(2H)-yl)acetic acid (JF0049, 4), which selectively target these enzymes. Although 3 and 4 share the 3-benzyluracil-1-acetic acid scaffold, they have different substituents in their aryl moieties. Inhibition studies along with thermodynamic and structural characterizations of both enzymes revealed that the chloronitrobenzyl moiety of compound 3 can open the AR specificity pocket but not that of the AKR1B10 cognate. In contrast, the larger atoms at the ortho and/or meta positions of compound 4 prevent the AR specificity pocket from opening due to steric hindrance and provide a tighter fit to the AKR1B10 inhibitor binding pocket, probably enhanced by the displacement of a disordered water molecule trapped in a hydrophobic subpocket, creating an enthalpic signature. Furthermore, this selectivity also occurs in the cell, which enables the development of a more efficient drug design strategy: compound 3 prevents sorbitol accumulation in human retinal ARPE-19 cells, whereas 4 stops proliferation in human lung cancer NCI-H460 cells.

Structural basis for 18-β-glycyrrhetinic acid as a novel non-GSH analog glyoxalase I inhibitor

AIM

Glyoxalase I (GLOI), a glutathione (GSH)-dependent enzyme, is overexpressed in tumor cells and related to multi-drug resistance in chemotherapy, making GLOI inhibitors as potential anti-tumor agents. But the most studied GSH analogs exhibit poor pharmacokinetic properties. The aim of this study was to discover novel non-GSH analog GLOI inhibitors and analyze their binding mechanisms.

METHODS

Mouse GLOI (mGLOI) was expressed in BL21 (DE3) pLysS after induction with isopropyl-β-D-1-thiogalactopyranoside and purified using AKTA FPLC system. An in vitro mGLOI enzyme assay was used to screen a small pool of compounds containing carboxyl groups. Crystal structure of the mGLOI-inhibitor complex was determined at 2.3 Å resolution. Molecular docking study was performed using Discovery Studio 2.5 software package.

RESULTS

A natural compound 18-β-glycyrrhetinic acid (GA) and its derivative carbenoxolone were identified as potent competitive non-GSH analog mGLOI inhibitors with Ki values of 0.29 μmol/L and 0.93 μmol/L, respectively. Four pentacyclic triterpenes (ursolic acid, oleanolic acid, betulic acid and tripterine) showed weak activities (mGLOI inhibition ratio <25% at 10 μmol/L) and other three (maslinic acid, corosolic acid and madecassic acid) were inactive. The crystal structure of the mGLOI-GA complex showed that the carboxyl group of GA mimicked the γ-glutamyl residue of GSH by hydrogen bonding to the glutamyl sites (residues Arg38B, Asn104B and Arg123A) in the GSH binding site of mGLOI. The extensive van der Waals interactions between GA and the surrounding residues also contributed greatly to the binding of GA and mGLOI.

CONCLUSION

This work demonstrates a carboxyl group to be an important functional feature of non-GSH analog GLOI inhibitors.

Identification of novel aldose reductase inhibitors based on carboxymethylated mercaptotriazinoindole scaffold

Fifteen compounds, sharing an indole-1-acetic acid moiety as a common fragment, were selected from commercial databases for testing aldose reductase inhibition. 3-Mercapto-5H-1,2,4-triazino[5,6-b]indole-5-acetic acid (13) was the most promising inhibitor, with an IC50 in the submicromolar range and high selectivity, relative to aldehyde reductase. The crystal structure of aldose reductase complexed with 13 revealed an interaction pattern explaining its high affinity. Physicochemical parameters underline the excellent "leadlikeness" of 13 as a promising candidate for further structure optimizations.

Probing the molecular and structural elements of ligands binding to the active site versus an allosteric pocket of the human farnesyl pyrophosphate synthase

In order to explore the interactions of bisphosphonate ligands with the active site and an allosteric pocket of the human farnesyl pyrophosphate synthase (hFPPS), substituted indole and azabenzimidazole bisphosphonates were designed as chameleon ligands. NMR and crystallographic studies revealed that these compounds can occupy both sub-pockets of the active site cavity, as well as the allosteric pocket of hFPPS in the presence of the enzyme's Mg(2+) ion cofactor. These results are consistent with the previously proposed hypothesis that the allosteric pocket of hFPPS, located near the active site, plays a feed-back regulatory role for this enzyme.

Chasing protons: how isothermal titration calorimetry, mutagenesis, and pKa calculations trace the locus of charge in ligand binding to a tRNA-binding enzyme

Drug molecules should remain uncharged while traveling through the body and crossing membranes and should only adopt charged state upon protein binding, particularly if charge-assisted interactions can be established in deeply buried binding pockets. Such strategy requires careful pKa design and methods to elucidate whether and where protonation-state changes occur. We investigated the protonation inventory in a series of lin-benzoguanines binding to tRNA-guanine transglycosylase, showing pronounced buffer dependency during ITC measurements. Chemical modifications of the parent scaffold along with ITC measurements, pKa calculations, and site-directed mutagenesis allow elucidating the protonation site. The parent scaffold exhibits two guanidine-type portions, both likely candidates for proton uptake. Even mutually compensating effects resulting from proton release of the protein and simultaneous uptake by the ligand can be excluded. Two adjacent aspartates induce a strong pKa shift at the ligand site, resulting in protonation-state transition. Furthermore, an array of two parallel H-bonds avoiding secondary repulsive effects contributes to the high-affinity binding of the lin-benzoguanines.

Modulation of aldose reductase inhibition by halogen bond tuning

In this paper, we studied a designed series of aldose reductase (AR) inhibitors. The series was derived from a known AR binder, which had previously been shown to form a halogen bond between its bromine atom and the oxygen atom of the Thr-113 side chain of AR. In the series, the strength of the halogen bond was modulated by two factors, namely bromine-iodine substitution and the fluorination of the aromatic ring in several positions. The role of the single halogen bond in AR-ligand binding was elucidated by advanced binding free energy calculations involving the semiempirical quantum chemical Hamiltonian. The results were complemented with ultrahigh-resolution X-ray crystallography and IC50 measurements. All of the AR inhibitors studied were shown by X-ray crystallography to bind in an identical manner. Further, it was demonstrated that it was possible to decrease the IC50 value by about 1 order of magnitude by tuning the strength of the halogen bond by a monoatomic substitution. The calculations revealed that the protein-ligand interaction energy increased upon the substitution of iodine for bromine or upon the addition of electron-withdrawing fluorine atoms to the ring. However, the effect on the binding affinity was found to be more complex due to the change of the solvation/desolvation properties within the ligand series. The study shows that it is possible to modulate the strength of a halogen bond in a protein-ligand complex as was designed based on the previous studies of low-molecular-weight complexes.

Development of aldose reductase inhibitors for the treatment of inflammatory disorders

INTRODUCTION

Accumulating evidence attributes a significant role to aldose reductase (ALR2) in the pathogenesis of several inflammatory pathologies. Aldose reductase inhibitors (ARIs) were found to attenuate reactive oxygen species (ROS) production both in vitro and in vivo. Thus, they disrupt signaling cascades that lead to the production of cytokines/chemokines, which induce and exacerbate inflammation. As a result, ARIs might hold a significant therapeutic potential as alternate anti-inflammatory drugs.

AREAS COVERED

The authors present a comprehensive review of the current data that support the central role of ALR2 in several inflammatory pathologies (i.e., diabetes, cancer, sepsis, asthma and ocular inflammation). Further, the authors describe the potential underlying molecular mechanisms and provide a commentary on the status of ARIs in this field.

EXPERT OPINION

It is important that future efforts focus on delineating all the steps of the molecular mechanism that implicates ALR2 in inflammatory pathologies. At the same time, utilizing the previous efforts in the field of ARIs, several candidates that have been proven safe in the clinic may be evaluated for their clinical significance as anti-inflammatory medication. Finally, structurally novel ARIs, designed to target specifically the proinflammatory subpocket of ALR2, should be pursued.

Protonation and pK changes in protein-ligand binding

Formation of protein-ligand complexes causes various changes in both the receptor and the ligand. This review focuses on changes in pK and protonation states of ionizable groups that accompany protein-ligand binding. Physical origins of these effects are outlined, followed by a brief overview of the computational methods to predict them and the associated corrections to receptor-ligand binding affinities. Statistical prevalence, magnitude and spatial distribution of the pK and protonation state changes in protein-ligand binding are discussed in detail, based on both experimental and theoretical studies. While there is no doubt that these changes occur, they do not occur all the time; the estimated prevalence varies, both between individual complexes and by method. The changes occur not only in the immediate vicinity of the interface but also sometimes far away. When receptor-ligand binding is associated with protonation state change at particular pH, the binding becomes pH dependent: we review the interplay between sub-cellular characteristic pH and optimum pH of receptor-ligand binding. It is pointed out that there is a tendency for protonation state changes upon binding to be minimal at physiologically relevant pH for each complex (no net proton uptake/release), suggesting that native receptor-ligand interactions have evolved to reduce the energy cost associated with ionization changes. As a result, previously reported statistical prevalence of these changes - typically computed at the same pH for all complexes - may be higher than what may be expected at optimum pH specific to each complex. We also discuss whether proper account of protonation state changes appears to improve practical docking and scoring outcomes relevant to structure-based drug design. An overview of some of the existing challenges in the field is provided in conclusion.

Targeting the blind spot of polycationic nanocarrier-based siRNA delivery

Polycationic nanocarriers attract increasing attention to the field of siRNA delivery. We investigated the self-assembly of siRNA vs pDNA with polycations, which are broadly used for nonviral gene and siRNA delivery. Although polyethyleneimine (PEI) was routinely adopted as siRNA carrier based on its efficacy in delivering pDNA, it has not been investigated yet why PEI efficiently delivers pDNA to cells but is controversially discussed in terms of efficacy for siRNA delivery. We are the first to investigate the self-assembly of PEI/siRNA vs PEI/pDNA and the steps of complexation and aggregation through different levels of hierarchy on the atomic and molecular scale with the novel synergistic use of molecular modeling, molecular dynamics simulation, isothermal titration calorimetry, and other characterization techniques. We are also the fist to elucidate atomic interactions, size, shape, stoichiometry, and association dynamics for polyplexes containing siRNA vs pDNA. Our investigation highlights differences in the hierarchical mechanism of formation of related polycation-siRNA and polycation-pDNA complexes. The results of fluorescence quenching assays indicated a biphasic behavior of siRNA binding with polycations where molecular reorganization of the siRNA within the polycations occurred at lower N/P ratios (nitrogen/phosphorus). Our results, for the first time, emphasize a biphasic behavior in siRNA complexation and the importance of low N/P ratios, which allow for excellent siRNA delivery efficiency. Our investigation highlights the formulation of siRNA complexes from a thermodynamic point of view and opens new perspectives to advance the rational design of new siRNA delivery systems.

Who cares for the protons?

It is tempting to use standard protonation states for the analysis of protein-ligand interactions. Two different pK(a) calculation methods, PROPKA (protein pK(a)) and MCCE (multi conformation continuum electrostatics), were applied to challenge this convenient behavior. As data basis, we selected five recently approved drugs for which structural information of the protein-drug complex is available. We analyzed the pK(a) calculations in terms of a measure termed BIPS (binary protonation states) recently introduced by us. Both methods agree in detecting the majority of the sites with atypical BIPS values. However, when using only one method, some of the atypcial BIPS value would have been missed. Therefore, we recommend using both methods to set such an interpretation on a solid basis.

Progresses in the pursuit of aldose reductase inhibitors: the structure-based lead optimization step

Aldose reductase (ALR2) is a crucial enzyme in the development of the major complications of diabetes mellitus. Very recently it has been demonstrated that the ARL2 inhibitor, fidarestat, significantly prevents inflammatory signals (TNF-α, LPS) that cause cancer (colon, breast, prostate and lung), metastasis, asthma, and other inflammatory diseases. Currently, fidarestat is in phase III clinical trial for diabetic neuropathy and was found to be safe. Thus the finding of novel, potent ARL2 inhibitors is today more than in the past in great demand as they can pave the way for a novel therapeutic approach for a number of diseases besides the diabetes. Herein, starting from the virtual screening-derived ALR2 inhibitor S12728 (1), a rational receptor-based lead optimization has been undertaken. The design and synthetic efforts here reported led to the discovery of several new compounds endowed with low micromolar/submicromolar activities.

Blind, one-eyed, or eagle-eyed? pKa calculations during blind predictions with staphylococcal nuclease

In the current contribution, the performance of Poisson-Boltzmann-based pK(a) calculations of SNase mutants as part of a blind prediction exercise facilitated by the pK(a) cooperative ("pK(a) _coop") is described. A one parameter setting ("quick&dirty" approach) is used to provide an industry perspective where strong time constraints are frequently encountered. On the one hand, results are analyzed in terms of root mean square deviation performance. Furthermore, the pK(a) calculations are assessed for their ability to properly assign protonation state. For this purpose, a new measure called BIPS (binary protonation state at physiological pH) is introduced. Significant differences were found with both comparison measures based on the class of residues examined. In addition, the performance of PROPKA3 as well as the NULL model is examined on the same data set. Finally, pK(a) calculations on SNase mutants with available structural information have been performed and provide support for our calculation methods. The performance on this subset is better than on the pK(a) cooperative mutation data. In the pK(a) _coop data, no structural information on the generated mutants is available. This suggests the occurrence of a substantial structural rearrangement on the insertion of additional charged groups into SNase, which leads to improved prediction quality.

Ligand-induced fit affects binding modes and provokes changes in crystal packing of aldose reductase

BACKGROUND

Flexibility is a common feature of proteins. For human aldose reductase, a variety of conformers have been observed in crystalline complexes with different inhibitors.

METHODS

A study of crystal structures and isothermal titration calorimetry was performed on wild type and mutated aldose reductase.

RESULTS AND CONCLUSIONS

Though the interaction to the mutated residue Thr113 does not directly alter the binding mode of zopolrestat to aldose reductase, a shift of its basic scaffold is induced which affects the interaction with a flexible loop and introduces disorder. With the related inhibitor IDD393, two distinct binding site conformations result in two different crystal forms: While a backbone flip of the same residues as for zopolrestat is present in both crystal forms, a considerable side-chain movement of a phenylalanine is observed for only one crystal form. In consequence, residual mobility of adjacent amino acids is increased and some crystal contacts are prevented which reinforces different crystal packing. The structure of a benzothiazepine reveals a protein conformer, where this phenylalanine is further relocated resulting in the same altered crystal packing. Differences in the thermodynamic signature recorded for the various complexes relate to the structural differences.

GENERAL SIGNIFICANCE

Crystal structures are accepted as "gold standard" for the interpretation of protein geometry, however, they are only one possible structure and can be influenced by crystal packing. In reverse, ligand binding can affect protein conformation and determine crystal packing. The phenomenon of such "polymorphic forms" is well appreciated, however rarely understood at the molecular level.

Estimating binding affinities by docking/scoring methods using variable protonation states

To investigate the effects of multiple protonation states on protein-ligand recognition, we generated alternative protonation states for selected titratable groups of ligands and receptors. The selection of states was based on the predicted pK(a) of the unbound receptor and ligand and the proximity of titratable groups of the receptor to the binding site. Various ligand tautomer states were also considered. An independent docking calculation was run for each state. Several protocols were examined: using an ensemble of all generated states of ligand and receptor, using only the most probable state of the unbound ligand/receptor, and using only the state giving the most favorable docking score. The accuracies of these approaches were compared, using a set of 176 protein-ligand complexes (15 receptors) for which crystal structures and measured binding affinities are available. The best agreement with experiment was obtained when ligand poses from experimental crystal structures were used. For 9 of 15 receptors, using an ensemble of all generated protonation states of the ligand and receptor gave the best correlation between calculated and measured affinities.

Tracing the detail: how mutations affect binding modes and thermodynamic signatures of closely related aldose reductase inhibitors

Improvements on the computational methods for affinity prediction from the structure of protein-ligand complexes require a better understanding of the nature of molecular interactions and biomolecular recognition principles. In the present contribution, the binding of two chemically closely related human aldose reductase inhibitors had been studied by high-resolution X-ray analysis (0.92-1.35 Ǻ) and isothermal titration calorimetry against a series of single-site mutants of the wild-type protein. A crucial threonine thought to be involved in a short bromine-to-oxygen halogen bond to the inhibitors in the wild type has been mutated to the structurally similar residues alanine, cysteine, serine and valine. Overall, structurally, the binding mode of the inhibitors is conserved; however, small but significant geometrical adaptations are observed as a consequence of the spatial and electronic changes at the mutation site. They involve the opening of a central bond angle and shifts in consequence of the lost or gained halogen bonds. Remarkably, the tiny structural changes are responded by partly strong modulation of the thermodynamic profiles. Even though the free energy of binding is maximally perturbed by only 7 kJ/mol, much stronger modulations and shifts in the enthalpy and entropy signatures are revealed, which indicate a pronounced enthalpy/entropy compensation. However, an explanatory correlation can be detected when facing these perturbances against the small structural changes. This also provides deeper insights into how single-site mutations can alter the selectivity profile of closely related ligands against a target protein.

Non-additivity of functional group contributions in protein-ligand binding: a comprehensive study by crystallography and isothermal titration calorimetry

Additivity of functional group contributions to protein-ligand binding is a very popular concept in medicinal chemistry as the basis of rational design and optimized lead structures. Most of the currently applied scoring functions for docking build on such additivity models. Even though the limitation of this concept is well known, case studies examining in detail why additivity fails at the molecular level are still very scarce. The present study shows, by use of crystal structure analysis and isothermal titration calorimetry for a congeneric series of thrombin inhibitors, that extensive cooperative effects between hydrophobic contacts and hydrogen bond formation are intimately coupled via dynamic properties of the formed complexes. The formation of optimal lipophilic contacts with the surface of the thrombin S3 pocket and the full desolvation of this pocket can conflict with the formation of an optimal hydrogen bond between ligand and protein. The mutual contributions of the competing interactions depend on the size of the ligand hydrophobic substituent and influence the residual mobility of ligand portions at the binding site. Analysis of the individual crystal structures and factorizing the free energy into enthalpy and entropy demonstrates that binding affinity of the ligands results from a mixture of enthalpic contributions from hydrogen bonding and hydrophobic contacts, and entropic considerations involving an increasing loss of residual mobility of the bound ligands. This complex picture of mutually competing and partially compensating enthalpic and entropic effects determines the non-additivity of free energy contributions to ligand binding at the molecular level.

Binding of small-molecule ligands to proteins: "what you see" is not always "what you get"

We review insights from computational studies of affinities of ligands binding to proteins. The power of structural biology is in translating knowledge of protein structures into insights about their forces, binding, and mechanisms. However, the complementary power of computer modeling is in showing "the rest of the story" (i.e., how motions and ensembles and alternative conformers and the entropies and forces that cannot be seen in single molecular structures also contribute to binding affinities). Upon binding to a protein, a ligand can bind in multiple orientations; the protein or ligand can be deformed by the binding event; waters, ions, or cofactors can have unexpected involvement; and conformational or solvation entropies can sometimes play large and otherwise unpredictable roles. Computer modeling is helping to elucidate these factors.

Correlation of binding constants and molecular modelling of inhibitors in the active sites of aldose reductase and aldehyde reductase

Aldose reductase (ALR2) belongs to the aldo-keto reductase (AKR) superfamily of enzymes, is the first enzyme involved in the polyol pathway of glucose metabolism and has been linked to the pathologies associated with diabetes. Molecular modelling studies together with binding constant measurements for the four inhibitors Tolrestat, Minalrestat, quercetin and 3,5-dichlorosalicylic acid (DCL) were used to determine the type of inhibition, and correlate inhibitor potency and binding energies of the complexes with ALR2 and the homologous aldehyde reductase (ALR1), another member of the AKR superfamily. Our results show that the four inhibitors follow either uncompetitive or non-competitive inhibition pattern of substrate reduction for ALR1 and ALR2. Overall, there is correlation between the IC(50) (concentration giving 50% inhibition) values of the inhibitors for the two enzymes and the binding energies (DeltaH) of the enzyme-inhibitor complexes. Additionally, the results agree with the detailed structural information obtained by X-ray crystallography suggesting that the difference in inhibitor binding for the two enzymes is predominantly mediated by non-conserved residues. In particular, Arg312 in ALR1 (missing in ALR2) contributes favourably to the binding of DCL through an electrostatic interaction with the inhibitor's electronegative halide atom and undergoes a conformational change upon Tolrestat binding. In ALR2, Thr113 (Tyr116 in ALR1) forms electrostatic interactions with the fluorobenzyl moiety of Minalrestat and the 3- and 4-hydroxy groups on the phenyl ring of quercetin. Our modelling studies suggest that Minalrestat's binding to ALR1 is accompanied by a conformational change including the side chain of Tyr116 to achieve the selectivity for ALR1 over ALR2.

A survey of the year 2007 literature on applications of isothermal titration calorimetry

Elucidation of the energetic principles of binding affinity and specificity is a central task in many branches of current sciences: biology, medicine, pharmacology, chemistry, material sciences, etc. In biomedical research, integral approaches combining structural information with in-solution biophysical data have proved to be a powerful way toward understanding the physical basis of vital cellular phenomena. Isothermal titration calorimetry (ITC) is a valuable experimental tool facilitating quantification of the thermodynamic parameters that characterize recognition processes involving biomacromolecules. The method provides access to all relevant thermodynamic information by performing a few experiments. In particular, ITC experiments allow to by-pass tedious and (rarely precise) procedures aimed at determining the changes in enthalpy and entropy upon binding by van't Hoff analysis. Notwithstanding limitations, ITC has now the reputation of being the "gold standard" and ITC data are widely used to validate theoretical predictions of thermodynamic parameters, as well as to benchmark the results of novel binding assays. In this paper, we discuss several publications from 2007 reporting ITC results. The focus is on applications in biologically oriented fields. We do not intend a comprehensive coverage of all newly accumulated information. Rather, we emphasize work which has captured our attention with originality and far-reaching analysis, or else has provided ideas for expanding the potential of the method.

Merging the binding sites of aldose and aldehyde reductase for detection of inhibitor selectivity-determining features

Inhibition of human aldose reductase (ALR2) evolved as a promising therapeutic concept to prevent late complications of diabetes. As well as appropriate affinity and bioavailability, putative inhibitors should possess a high level of selectivity for ALR2 over the related aldehyde reductase (ALR1). We investigated the selectivity-determining features by gradually mapping the residues deviating between the binding pockets of ALR1 and ALR2 into the ALR2 binding pocket. The resulting mutational constructs of ALR2 (eight point mutations and one double mutant) were probed for their influence towards ligand selectivity by X-ray structure analysis of the corresponding complexes and isothermal titration calorimetry (ITC). The binding properties of these mutants were evaluated using a ligand set of zopolrestat, a related uracil derivative, IDD388, IDD393, sorbinil, fidarestat and tolrestat. Our study revealed induced-fit adaptations within the mutated binding site as an essential prerequisite for ligand accommodation related to the selectivity discrimination of the ligands. However, our study also highlights the limits of the present understanding of protein-ligand interactions. Interestingly, binding site mutations not involved in any direct interaction to the ligands in various cases show significant effects towards their binding thermodynamics. Furthermore, our results suggest the binding site residues deviating between ALR1 and ALR2 influence ligand affinity in a complex interplay, presumably involving changes of dynamic properties and differences of the solvation/desolvation balance upon ligand binding.