Modulation of aldose reductase inhibition by halogen bond tuning

Halogen Bonding Hot Spots as a Constraint in Virtual Screening: A Case Study of 5-HT7R

The recently developed and used molecular modeling approach to search for privileged amino acids for halogen bonding (XB hot spots) through XSAR sets has been applied to 5-HT7R. Herein, among all identified 5-HT7R XB hot spots, the S5x42 was employed in a virtual screening protocol as a constraint. Through a designed virtual screening protocol, 63 XSAR sets (156 compounds) were selected from more than 8 million commercially available compounds and examined using in vitro assay toward 5-HT7R. A 68% accuracy was found in predicting halogenated derivatives with higher affinity for 5-HT7R than their unsubstituted analogs. Moreover, it was observed that a halogen bond formed between S5x42 and a chlorine atom at the 3-position of the arylpiperazine fragment caused the most remarkable, 35.4-fold increase in binding affinity for 5-HT7R when compared to the nonhalogenated analog. Interestingly, molecular dynamics simulations showed the formation of a bifurcated halogen bond with S5x42.

Structural Insights on the Role of Halogen Bonding in Protein MEK Kinase-Inhibitor Complexes

Kinases are enzymes that play a critical role in governing essential biological processes. Due to their pivotal involvement in cancer cell signaling, they have become key targets in the development of anti-cancer drugs. Among these drugs, those containing the 2,4-dihalophenyl moiety demonstrated significant potential. Here we show how this moiety, particularly the 2-fluoro-4-iodophenyl one, is crucial for the structural stability of the formed drug-enzyme complexes. Crystallographic analysis of reported kinase-inhibitor complex structures highlights the role of the halogen bonding that this moiety forms with specific residues of the kinase binding site. This interaction is not limited to FDA-approved MEK inhibitors, but it is also relevant for other kinase inhibitors, indicating its broad relevance in the design of this class of drugs.

Drug screening identifies aldose reductase as a novel target for treating cisplatin-induced hearing loss

Cisplatin is a frequently used chemotherapeutic medicine for cancer treatment. Permanent hearing loss is one of the most serious side effects of cisplatin, but there are few FDA-approved medicines to prevent it. We applied high-through screening and target fishing and identified aldose reductase, a key enzyme of the polyol pathway, as a novel target for treating cisplatin ototoxicity. Cisplatin treatment significantly increased the expression level and enzyme activity of aldose reductase in the cochlear sensory epithelium. Genetic knockdown or pharmacological inhibition of aldose reductase showed a significant protective effect on cochlear hair cells. Cisplatin-induced overactivation of aldose reductase led to the decrease of NADPH/NADP+ and GSH/GSSG ratios, as well as the increase of oxidative stress, and contributed to hair cell death. Results of target prediction, molecular docking, and enzyme activity detection further identified that Tiliroside was an effective inhibitor of aldose reductase. Tiliroside was proven to inhibit the enzymatic activity of aldose reductase via competitively interfering with the substrate-binding region. Both Tiliroside and another clinically approved aldose reductase inhibitor, Epalrestat, inhibited cisplatin-induced oxidative stress and subsequent cell death and thus protected hearing function. These findings discovered the role of aldose reductase in the pathogenesis of cisplatin-induced deafness and identified aldose reductase as a new target for the prevention and treatment of hearing loss.

Modes and model building in SHELXE

Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson-Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.

C-H Groups as Donors in Hydrogen Bonds: A Historical Overview and Occurrence in Proteins and Nucleic Acids

Hydrogen bonds constitute a unique type of non-covalent interaction, with a critical role in biology. Until fairly recently, the canonical view held that these bonds occur between electronegative atoms, typically O and N, and that they are mostly electrostatic in nature. However, it is now understood that polarized C-H groups may also act as hydrogen bond donors in many systems, including biological macromolecules. First recognized from physical chemistry studies, C-H…X bonds were visualized with X-ray crystallography sixty years ago, although their true significance has only been recognized in the last few decades. This review traces the origins of the field and describes the occurrence and significance of the most important C-H…O bonds in proteins and nucleic acids.

Jellybean Quantum Dots in Silicon for Qubit Coupling and On-Chip Quantum Chemistry

The small size and excellent integrability of silicon metal-oxide-semiconductor (SiMOS) quantum dot spin qubits make them an attractive system for mass-manufacturable, scaled-up quantum processors. Furthermore, classical control electronics can be integrated on-chip, in-between the qubits, if an architecture with sparse arrays of qubits is chosen. In such an architecture qubits are either transported across the chip via shuttling or coupled via mediating quantum systems over short-to-intermediate distances. This paper investigates the charge and spin characteristics of an elongated quantum dot-a so-called jellybean quantum dot-for the prospects of acting as a qubit-qubit coupler. Charge transport, charge sensing, and magneto-spectroscopy measurements are performed on a SiMOS quantum dot device at mK temperature and compared to Hartree-Fock multi-electron simulations. At low electron occupancies where disorder effects and strong electron-electron interaction dominate over the electrostatic confinement potential, the data reveals the formation of three coupled dots, akin to a tunable, artificial molecule. One dot is formed centrally under the gate and two are formed at the edges. At high electron occupancies, these dots merge into one large dot with well-defined spin states, verifying that jellybean dots have the potential to be used as qubit couplers in future quantum computing architectures.

Engineering the ligand specificity of the human galectin-1 by incorporation of tryptophan analogs

Galectin-1 is a β-galactoside-binding lectin with manifold biological functions. A single tryptophan residue (W68) in its carbohydrate binding site plays a major role in ligand binding and is highly conserved among galectins. To fine tune galectin-1 specificity, we introduced several non-canonical tryptophan analogs at this position of human galectin-1 and analyzed the resulting variants using glycan microarrays. Two variants containing 7-azatryptophan and 7-fluorotryptophan showed a reduced affinity for 3'-sulfated oligosaccharides. Their interaction with different ligands was further analyzed by fluorescence polarization competition assay. Using molecular modeling we provide structural clues that the change in affinities comes from modulated interactions and solvation patterns. Thus, we show that the introduction of subtle atomic mutations in the ligand binding site of galectin-1 is an attractive approach for fine-tuning its interactions with different ligands.

Perspective on the Structural Basis for Human Aldo-Keto Reductase 1B10 Inhibition

Human aldo-keto reductase 1B10 (AKR1B10) is overexpressed in many cancer types and is involved in chemoresistance. This makes AKR1B10 to be an interesting drug target and thus many enzyme inhibitors have been investigated. High-resolution crystallographic structures of AKR1B10 with various reversible inhibitors were deeply analyzed and compared to those of analogous complexes with aldose reductase (AR). In both enzymes, the active site included an anion-binding pocket and, in some cases, inhibitor binding caused the opening of a transient specificity pocket. Different structural conformers were revealed upon inhibitor binding, emphasizing the importance of the highly variable loops, which participate in the transient opening of additional binding subpockets. Two key differences between AKR1B10 and AR were observed regarding the role of external loops in inhibitor binding. The first corresponded to the alternative conformation of Trp112 (Trp111 in AR). The second difference dealt with loop A mobility, which defined a larger and more loosely packed subpocket in AKR1B10. From this analysis, the general features that a selective AKR1B10 inhibitor should comply with are the following: an anchoring moiety to the anion-binding pocket, keeping Trp112 in its native conformation (AKR1B10-like), and not opening the specificity pocket in AR.

Structure-Activity Relationship Studies of Hydantoin-Cored Ligands for Smoothened Receptor

An underside binding site was recently identified in the transmembrane domain of smoothened receptor (SMO). Herein, we report efforts in the exploration of new insights into the interactions between the ligand and SMO. The hydantoin core in the middle of the parent compound was found to be highly conservative in chirality, ring size, and substituents. On each benzene at two ends, a plethora of variations, particularly halogen substitutions, were introduced and investigated. Analysis of the structure-activity relationship revealed miscellaneous halogen effects. The ligands with double halogen substituents exhibit remarkably enhanced potency, providing promising candidates that potentially overcome the common drug resistance and useful heavy-atom labeled chemical tools for co-crystallization studies of SMO.

A new density-modification procedure extending the application of the recent |ρ|-based phasing algorithm to larger crystal structures

The incorporation of the new peakness-enhancing fast Fourier transform compatible ipp procedure (ipp = inner-pixel preservation) into the recently published SM algorithm based on |ρ| [Rius (2020). Acta Cryst A76, 489-493] improves its phasing efficiency for larger crystal structures with atomic resolution data. Its effectiveness is clearly demonstrated via a collection of test crystal structures (taken from the Protein Data Bank) either starting from random phase values or by using the randomly shifted modulus function (a Patterson-type synthesis) as initial ρ estimate. It has been found that in the presence of medium scatterers (e.g. S or Cl atoms) crystal structures with 1500 × c atoms in the unit cell (c = number of centerings) can be routinely solved. In the presence of strong scatterers like Fe, Cu or Zn atoms this number increases to around 5000 × c atoms. The implementation of this strengthened SM algorithm is simple, since it only includes a few easy-to-adjust parameters.

Modulating the Efficacy of Carbonic Anhydrase Inhibitors through Fluorine Substitution

The insertion of fluorine atoms and/or fluoroalkyl groups can lead to many beneficial effects in biologically active molecules, such as enhanced metabolic stability, bioavailability, lipophilicity, and membrane permeability, as well as a strengthening of protein-ligand binding interactions. However, this "magic effect" of fluorine atom(s) insertion can often be meaningless. Taking advantage of the wide range of data coming from the quest for carbonic anhydrase (CA) fluorinated inhibitors, this Minireview attempts to give "general guidelines" on how to wisely insert fluorine atom(s) within an inhibitor moiety to precisely enhance or disrupt ligand-protein interactions, depending on the target location of the fluorine substitution in the ligand. Multiple approaches such as ITC, kinetic and inhibition studies, X-ray crystallography, and NMR spectroscopy are useful in dissecting single binding contributions to the overall observed effect. The exploitation of innovative directions made in the field of protein and ligand-based fluorine NMR screening is also discussed to avoid misconduct and finely tune the exploitation of selective fluorine atom insertion in the future.

Tuning the activity of known drugs via the introduction of halogen atoms, a case study of SERT ligands - Fluoxetine and fluvoxamine

The selective serotonin reuptake inhibitors (SSRIs), acting at the serotonin transporter (SERT), are one of the most widely prescribed antidepressant medications. All five approved SSRIs possess either fluorine or chlorine atoms, and there is a limited number of reports describing their analogs with heavier halogens, i.e., bromine and iodine. To elucidate the role of halogen atoms in the binding of SSRIs to SERT, we designed a series of 22 fluoxetine and fluvoxamine analogs substituted with fluorine, chlorine, bromine, and iodine atoms, differently arranged on the phenyl ring. The obtained biological activity data, supported by a thorough in silico binding mode analysis, allowed the identification of two partners for halogen bond interactions: the backbone carbonyl oxygen atoms of E493 and T497. Additionally, compounds with heavier halogen atoms were found to bind with the SERT via a distinctly different binding mode, a result not presented elsewhere. The subsequent analysis of the prepared XSAR sets showed that E493 and T497 participated in the largest number of formed halogen bonds. The XSAR library analysis led to the synthesis of two of the most active compounds (3,4-diCl-fluoxetine 42, SERT K_i = 5 nM and 3,4-diCl-fluvoxamine 46, SERT K_i = 9 nM, fluoxetine SERT K_i = 31 nM, fluvoxamine SERT K_i = 458 nM). We present an example of the successful use of a rational methodology to analyze binding and design more active compounds by halogen atom introduction. 'XSAR library analysis', a new tool in medicinal chemistry, was instrumental in identifying optimal halogen atom substitution.

Aldose reductase and protein tyrosine phosphatase 1B inhibitors as a promising therapeutic approach for diabetes mellitus

Diabetes mellitus is a metabolic disease characterized by high blood glucose levels and usually associated with several chronic pathologies. Aldose reductase and protein tyrosine phosphatase 1B enzymes have identified as two novel molecular targets associated with the onset and progression of type II diabetes and related comorbidities. Although many inhibitors against these enzymes have already found in the field of diabetic mellitus, the research for discovering more effective and selective agents with optimal pharmacokinetic properties continues. In addition, dual inhibition of these target proteins has proved as a promising therapeutic approach. A variety of diverse scaffolds are presented in this review for the future design of potent and selective inhibitors of aldose reductase and protein tyrosine phosphatase 1B based on the most important structural features of both enzymes. The discovery of novel dual aldose reductase and protein tyrosine phosphatase 1B inhibitors could be effective therapeutic molecules for the treatment of insulin-resistant type II diabetes mellitus. The methods used comprise a literature survey and X-ray crystal structures derived from Protein Databank (PDB). Despite the available therapeutic options for type II diabetes mellitus, the inhibitors of aldose reductase and protein tyrosine phosphatase 1B could be two promising approaches for the effective treatment of hyperglycemia and diabetes-associated pathologies. Due to the poor pharmacokinetic profile and low in vivo efficacy of existing inhibitors of both targets, the research turned to more selective and cell-permeable agents as well as multi-target molecules.

SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design

Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.

Phosphine Oxides as Spectroscopic Halogen Bond Descriptors: IR and NMR Correlations with Interatomic Distances and Complexation Energy

An extensive series of 128 halogen-bonded complexes formed by trimethylphosphine oxide and various F-, Cl-, Br-, I- and At-containing molecules, ranging in energy from 0 to 124 kJ/mol, is studied by DFT calculations in vacuum. The results reveal correlations between R–X⋅⋅⋅O=PMe₃ halogen bond energy ΔE, X⋅⋅⋅O distance r, halogen’s σ-hole size, QTAIM parameters at halogen bond critical point and changes of spectroscopic parameters of phosphine oxide upon complexation, such as ³¹P NMR chemical shift, ΔδP, and P=O stretching frequency, Δν. Some of the correlations are halogen-specific, i.e., different for F, Cl, Br, I and At, such as ΔE(r), while others are general, i.e., fulfilled for the whole set of complexes at once, such as ΔE(ΔδP). The proposed correlations could be used to estimate the halogen bond properties in disordered media (liquids, solutions, polymers, glasses) from the corresponding NMR and IR spectra.

Advances in Docking

BACKGROUND

Design of small molecules which are able to bind to the protein responsible for a disease is the key step of the entire process of the new medicine discovery. Atomistic computer modeling can significantly improve effectiveness of such design. The accurate calculation of the free energy of binding a small molecule (a ligand) to the target protein is the most important problem of such modeling. Docking is one of the most popular molecular modeling methods for finding ligand binding poses in the target protein and calculating the protein-ligand binding energy. This energy is used for finding the most active compounds for the given target protein. This short review aims to give a concise description of distinctive features of docking programs focusing on computation methods and approximations influencing their accuracy.

METHODS

This review is based on the peer-reviewed research literature including author's own publications. The main features of several representative docking programs are briefly described focusing on their characteristics influencing docking accuracy: force fields, energy calculations, solvent models, algorithms of the best ligand pose search, global and local optimizations, ligand and target protein flexibility, and the simplifications made for the docking accelerating. Apart from other recent reviews focused mainly on the performance of different docking programs, in this work, an attempt is made to extract the most important functional characteristics defining the docking accuracy. Also a roadmap for increasing the docking accuracy is proposed. This is based on the new generation of docking programs which have been realized recently. These programs and respective new global optimization algorithms are described shortly.

RESULTS

Several popular conventional docking programs are considered. Their search of the best ligand pose is based explicitly or implicitly on the global optimization problem. Several algorithms are used to solve this problem, and among them, the heuristic genetic algorithm is distinguished by its popularity and an elaborate design. All conventional docking programs for their acceleration use the preliminary calculated grids of protein-ligand interaction potentials or preferable points of protein and ligand conjugation. These approaches and commonly used fitting parameters restrict strongly the docking accuracy. Solvent is considered in exceedingly simplified approaches in the course of the global optimization and the search for the best ligand poses. More accurate approaches on the base of implicit solvent models are used frequently for more careful binding energy calculations after docking. The new generation of docking programs are developed recently. They find the spectrum of low energy minima of a protein-ligand complex including the global minimum. These programs should be more accurate because they do not use a preliminary calculated grid of protein-ligand interaction potentials and other simplifications, the energy of any conformation of the molecular system is calculated in the frame of a given force field and there are no fitting parameters. A new docking algorithm is developed and fulfilled specially for the new docking programs. This algorithm allows docking a flexible ligand into a flexible protein with several dozen mobile atoms on the base of the global energy minimum search. Such docking results in improving the accuracy of ligand positioning in the docking process. The adequate choice of the method of molecular energy calculations also results in the better docking positioning accuracy. An advancement in the application of quantum chemistry methods to docking and scoring is revealed.

CONCLUSION

The findings of this review confirm the great demand in docking programs for discovery of new medicine substances with the help of molecular modeling. New trends in docking programs design are revealed. These trends are focused on the increase of the docking accuracy at the expense of more accurate molecular energy calculations without any fitting parameters, including quantum-chemical methods and implicit solvent models, and by using new global optimization algorithms which make it possible to treat flexibility of ligands and mobility of protein atoms simultaneously. Finally, it is shown that all the necessary prerequisites for increasing the docking accuracy can be accomplished in practice.

Vitamin K1 prevents diabetic cataract by inhibiting lens aldose reductase 2 (ALR2) activity

This study investigated the potential of vitamin K1 as a novel lens aldose reductase inhibitor in a streptozotocin-induced diabetic cataract model. A single, intraperitoneal injection of streptozotocin (STZ) (35 mg/kg) resulted in hyperglycemia, activation of lens aldose reductase 2 (ALR2) and accumulation of sorbitol in eye lens which could have contributed to diabetic cataract formation. However, when diabetic rats were treated with vitamin K1 (5 mg/kg, sc, twice a week) it resulted in lowering of blood glucose and inhibition of lens aldose reductase activity because of which there was a corresponding decrease in lens sorbitol accumulation. These results suggest that vitamin K1 is a potent inhibitor of lens aldose reductase enzyme and we made an attempt to understand the nature of this inhibition using crude lens homogenate as well as recombinant human aldose reductase enzyme. Our results from protein docking and spectrofluorimetric analyses clearly show that vitamin K1 is a potent inhibitor of ALR2 and this inhibition is primarily mediated by the blockage of DL-glyceraldehyde binding to ALR2. At the same time docking also suggests that vitamin K1 overlaps at the NADPH binding site of ALR2, which probably shows that vitamin K1 could possibly bind both these sites in the enzyme. Another deduction that we can derive from the experiments performed with pure protein is that ALR2 has three levels of affinity, first for NADPH, second for vitamin K1 and third for the substrate DL-glyceraldehyde. This was evident based on the dose-dependency experiments performed with both NADPH and DL-glyceraldehyde. Overall, our study shows the potential of vitamin K1 as an ALR2 inhibitor which primarily blocks enzyme activity by inhibiting substrate interaction of the enzyme. Further structural studies are needed to fully comprehend the exact nature of binding and inhibition of ALR2 by vitamin K1 that could open up possibilities of its therapeutic application.

Replacement of Protein Binding-Site Waters Contributes to Favorable Halogen Bond Interactions

Halogen bond interaction between a protein electronegative atom and a ligand halogen atom is increasingly attracting attention in the field of structure-based drug design. Nevertheless, gaps in understanding make it desirable to better examine the role of forces governing the formation of favorable halogen bond interactions, and the development of effective and efficient computational approaches to "design in" favorable halogen bond interactions in lead optimization process are warranted. Here, we analyzed the binding-site water properties of crystal structures with characterized halogen bond interactions between ligand halogen atoms and protein backbone carbonyl groups and, thus, found that halogen atoms involved in halogen bond interactions frequently replace calculated binding-site waters upon ligand binding. Moreover, we observed that the preferential directionality of halogen bond interactions aligns well with the orientations of these replaced waters, and these replaced waters exhibited differential energetic characteristics as compared to waters that are displaced by halogen atoms that do not form halogen bond interactions. Our discovery that replacement of calculated binding-site waters contributes to the formation of favorable halogen bond interactions suggests a practical approach for rational drug design utilizing halogen bond interactions with protein backbone carbonyl groups.

Halogen bonding in halocarbon-protein complexes and computational tools for rational drug design

Introduction: Halogens have a prominent role in drug design. Often used as a mean to improve ADME properties, they are also becoming a tool in protein-ligand recognition given their ability to form a non-covalent interaction, termed halogen bond, where halogens act as electrophilic species interacting with electron-rich partners. Rational drug design of halogen-bonding lead molecules requires an accurate description of halocarbon-protein complexes by computational tools though not all methods are able to tackle this non-covalent interaction. Areas covered: The authors present a review of computational methodologies that can be used to properly describe halogen bonds in the context of protein-ligand complexes, providing also insights on how these methods can be used in the context of computer-aided drug design. Expert opinion: Although in the last few years many computational tools, ranging from fast screening methods to the more expensive QM calculations, have been developed to tackle the halogen bonding phenomenon, they are not yet standard in the literature. This will eventually change as official software distributions are including support for halogen bonding in their methods. Tackling desolvation of halogenated species seems to be a good strategy to improve the accuracy of computational methods, that will be more commonly used prior to laboratory work in the future.

Revisiting the halogen bonding between phosphodiesterase type 5 and its inhibitors

Halogenated ligands are nowadays commonly designed in order to increase their potency against protein targets. Although novel computational methods of evaluating the affinity of such halogenated inhibitors have emerged, they still lack the sufficient accuracy, which is especially noticeable in the case of empirical scoring functions, being the method of choice in the drug design process. Here, we evaluated a series of halogenated inhibitors of phosphodiesterase type 5 with ab initio methods, revealing the physical nature of ligand binding and determining the components of interaction energy that are essential for proper inhibitor ranking. In particular, a nonempirical scoring model combining long-range contributions to the interaction energy provided a significant correlation with experimental binding potency, outperforming a number of commonly used empirical scoring functions. Considering the low computational cost associated with remarkable predictive abilities of the aforementioned model, it could be used for rapid assessment of the ligand affinity in the process of rational design of novel halogenated compounds.

Amino Acid Hot Spots of Halogen Bonding: A Combined Theoretical and Experimental Case Study of the 5-HT7 Receptor

A computational approach combining a structure-activity relationship library of halogenated and the corresponding unsubstituted ligands (called XSAR) with QM-based molecular docking and binding free energy calculations was used to search for amino acids frequently targeted by halogen bonding (hot spots) in a 5-HT₇R as a case study. The procedure identified two sets of hot spots, extracellular (D2.65, T2.64, and E7.35) and transmembrane (C3.36, T5.39, and S5.42), which were further verified by a synthesized library of halogenated arylsulfonamide derivatives of (aryloxy)ethylpiperidines. It was found that a halogen bond formed between T5.39 and a bromine atom at 3-position of the aryloxy fragment caused the most remarkable, 35-fold increase in binding affinity for 5-HT₇R when compared to the nonhalogenated analog. The proposed paradigm of halogen bonding hot spots was additionally verified on D₄ dopamine receptor showing that it can be used in rational drug design/optimization for any protein target.

Halogen bonding for the design of inhibitors by targeting the S1 pocket of serine proteases

Halogen bonding (or X bonding) has attracted increasing interest due to its significant role in molecular recognition in biological systems. Trypsin-like serine proteases have many physiological and pathophysiological functions. There is therefore extensive interest in generating specific inhibitors for pharmacological intervention in their enzymatic activity. We study here if it is possible to use halogenated compounds as the P1 group to bind to the S1 specificity pocket of trypsin-like serine proteases to avoid the low bioavailability of the amidine or guanidine P1 group that is typically used in many inhibitors. We used 4-chlorobenzylamine (ClBA), 4-bromobenzylamine (BrBA) and 4-iodobenzylamine (IBA) as probes to test their binding modes to a trypsin-like serine protease, urokinase-type plasminogen activator (uPA), which has been recognized as a marker for breast cancer and an important target for inhibitor development. The results showed that these compounds inhibited uPA with stronger efficacies compared with their non-halogenated analogues. We also determined the high-resolution crystal structures of uPA in complex with BrBA and IBA, respectively. The structures revealed that BrBA bound to the S1 pocket of uPA via halogen bonds, but IBA did not make halogen bonds with uPA, demonstrating that the iodine may not be the best choice as a target moiety for serine proteases. These results advocate halogen bonding, especially bromine bonding, as an efficient strategy for the future design of novel inhibitors against trypsin-like serine proteases to provide strong potency and promote bioavailability.

Superior Performance of the SQM/COSMO Scoring Functions in Native Pose Recognition of Diverse Protein-Ligand Complexes in Cognate Docking

General and reliable description of structures and energetics in protein-ligand (PL) binding using the docking/scoring methodology has until now been elusive. We address this urgent deficiency of scoring functions (SFs) by the systematic development of corrected semiempirical quantum mechanical (SQM) methods, which correctly describe all types of noncovalent interactions and are fast enough to treat systems of thousands of atoms. Two most accurate SQM methods, PM6-D3H4X and SCC-DFTB3-D3H4X, are coupled with the conductor-like screening model (COSMO) implicit solvation model in so-called "SQM/COSMO" SFs and have shown unique recognition of native ligand poses in cognate docking in four challenging PL systems, including metalloprotein. Here, we apply the two SQM/COSMO SFs to 17 diverse PL complexes and compare their performance with four widely used classical SFs (Glide XP, AutoDock4, AutoDock Vina, and UCSF Dock). We observe superior performance of the SQM/COSMO SFs and identify challenging systems. This method, due to its generality, comparability across the chemical space, and lack of need for any system-specific parameters, gives promise of becoming, after comprehensive large-scale testing in the near future, a useful computational tool in structure-based drug design and serving as a reference method for the development of other SFs.

Halogen Bonding in Nucleic Acid Complexes

Halogen bonding (X-bonding) has attracted notable attention among noncovalent interactions. This highly directional attraction between a halogen atom and an electron donor has been exploited in knowledge-based drug design. A great deal of information has been gathered about X-bonds in protein-ligand complexes, as opposed to nucleic acid complexes. Here we provide a thorough analysis of nucleic acid complexes containing either halogenated building blocks or halogenated ligands. We analyzed close contacts between halogens and electron-rich moieties. The phosphate backbone oxygen is clearly the most common halogen acceptor. We identified 21 X-bonds within known structures of nucleic acid complexes. A vast majority of the X-bonds is formed by halogenated nucleobases, such as bromouridine, and feature excellent geometries. Noncovalent ligands have been found to form only interactions with suboptimal interaction geometries. Hence, the first X-bonded nucleic acid binder remains to be discovered.

Explicit treatment of active-site waters enhances quantum mechanical/implicit solvent scoring: Inhibition of CDK2 by new pyrazolo[1,5-a]pyrimidines

We present comprehensive testing of solvent representation in quantum mechanics (QM)-based scoring of protein-ligand affinities. To this aim, we prepared 21 new inhibitors of cyclin-dependent kinase 2 (CDK2) with the pyrazolo[1,5-a]pyrimidine core, whose activities spanned three orders of magnitude. The crystal structure of a potent inhibitor bound to the active CDK2/cyclin A complex revealed that the biphenyl substituent at position 5 of the pyrazolo[1,5-a]pyrimidine scaffold was located in a previously unexplored pocket and that six water molecules resided in the active site. Using molecular dynamics, protein-ligand interactions and active-site water H-bond networks as well as thermodynamics were probed. Thereafter, all the inhibitors were scored by the QM approach utilizing the COSMO implicit solvent model. Such a standard treatment failed to produce a correlation with the experiment (R² = 0.49). However, the addition of the active-site waters resulted in significant improvement (R² = 0.68). The activities of the compounds could thus be interpreted by taking into account their specific noncovalent interactions with CDK2 and the active-site waters. In summary, using a combination of several experimental and theoretical approaches we demonstrate that the inclusion of explicit solvent effects enhance QM/COSMO scoring to produce a reliable structure-activity relationship with physical insights. More generally, this approach is envisioned to contribute to increased accuracy of the computational design of novel inhibitors.

IDD388 Polyhalogenated Derivatives as Probes for an Improved Structure-Based Selectivity of AKR1B10 Inhibitors

Human enzyme aldo-keto reductase family member 1B10 (AKR1B10) has evolved as a tumor marker and promising antineoplastic target. It shares high structural similarity with the diabetes target enzyme aldose reductase (AR). Starting from the potent AR inhibitor IDD388, we have synthesized a series of derivatives bearing the same halophenoxyacetic acid moiety with an increasing number of bromine (Br) atoms on its aryl moiety. Next, by means of IC₅₀ measurements, X-ray crystallography, WaterMap analysis, and advanced binding free energy calculations with a quantum-mechanical (QM) approach, we have studied their structure-activity relationship (SAR) against both enzymes. The introduction of Br substituents decreases AR inhibition potency but improves it in the case of AKR1B10. Indeed, the Br atoms in ortho position may impede these drugs to fit into the AR prototypical specificity pocket. For AKR1B10, the smaller aryl moieties of MK181 and IDD388 can bind into the external loop A subpocket. Instead, the bulkier MK184, MK319, and MK204 open an inner specificity pocket in AKR1B10 characterized by a π-π stacking interaction of their aryl moieties and Trp112 side chain in the native conformation (not possible in AR). Among the three compounds, only MK204 can make a strong halogen bond with the protein (-4.4 kcal/mol, using QM calculations), while presenting the lowest desolvation cost among all the series, translated into the most selective and inhibitory potency AKR1B10 (IC₅₀ = 80 nM). Overall, SAR of these IDD388 polyhalogenated derivatives have unveiled several distinctive AKR1B10 features (shape, flexibility, hydration) that can be exploited to design novel types of AKR1B10 selective drugs.

Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods

We review the first successes and failures of a “new wave” of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of “enhanced”, dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects.

Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

Semiempirical (SE) methods can be derived from either Hartree-Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems.

Experimental Binding Energies in Supramolecular Complexes

On the basis of many literature measurements, a critical overview is given on essential noncovalent interactions in synthetic supramolecular complexes, accompanied by analyses with selected proteins. The methods, which can be applied to derive binding increments for single noncovalent interactions, start with the evaluation of consistency and additivity with a sufficiently large number of different host-guest complexes by applying linear free energy relations. Other strategies involve the use of double mutant cycles, of molecular balances, of dynamic combinatorial libraries, and of crystal structures. Promises and limitations of these strategies are discussed. Most of the analyses stem from solution studies, but a few also from gas phase. The empirically derived interactions are then presented on the basis of selected complexes with respect to ion pairing, hydrogen bonding, electrostatic contributions, halogen bonding, π-π-stacking, dispersive forces, cation-π and anion-π interactions, and contributions from the hydrophobic effect. Cooperativity in host-guest complexes as well as in self-assembly, and entropy factors are briefly highlighted. Tables with typical values for single noncovalent free energies and polarity parameters are in the Supporting Information.

Asymmetric bifurcated halogen bonds

Halogen bonding (XB) is being extensively explored for its potential use in advanced materials and drug design. Despite significant progress in describing this interaction by theoretical and experimental methods, the chemical nature remains somewhat elusive, and it seems to vary with the selected system. In this work we present a detailed DFT analysis of three-center asymmetric halogen bond (XB) formed between dihalogen molecules and variously 4-substituted 1,2-dimethoxybenzene. The energy decomposition, orbital, and electron density analyses suggest that the contribution of electrostatic stabilization is comparable with that of non-electrostatic factors. Both terms increase parallel with increasing negative charge of the electron donor molecule in our model systems. Depending on the orientation of the dihalogen molecules, this bifurcated interaction may be classified as 'σ-hole - lone pair' or 'σ-hole - π' halogen bonds. Arrangement of the XB investigated here deviates significantly from a recent IUPAC definition of XB and, in analogy to the hydrogen bonding, the term bifurcated halogen bond (BXB) seems to be appropriate for this type of interaction.

Targeting the protein backbone with aryl halides: systematic comparison of halogen bonding and π⋯π interactions using N-methylacetamide

Systematic plane scans reveal a seamless transition from σ-hole interactions with the carbonyl oxygen to interactions with the amide π-electrons at increasing distances.