Semiempirical Quantum Mechanical Method PM6-DH2X Describes the Geometry and Energetics of CK2-Inhibitor Complexes Involving Halogen Bonds Well, While the Empirical Potential Fails

SQM2.20: Semiempirical quantum-mechanical scoring function yields DFT-quality protein-ligand binding affinity predictions in minutes

Accurate estimation of protein-ligand binding affinity is the cornerstone of computer-aided drug design. We present a universal physics-based scoring function, named SQM2.20, addressing key terms of binding free energy using semiempirical quantum-mechanical computational methods. SQM2.20 incorporates the latest methodological advances while remaining computationally efficient even for systems with thousands of atoms. To validate it rigorously, we have compiled and made available the PL-REX benchmark dataset consisting of high-resolution crystal structures and reliable experimental affinities for ten diverse protein targets. Comparative assessments demonstrate that SQM2.20 outperforms other scoring methods and reaches a level of accuracy similar to much more expensive DFT calculations. In the PL-REX dataset, it achieves excellent correlation with experimental data (average R2 = 0.69) and exhibits consistent performance across all targets. In contrast to DFT, SQM2.20 provides affinity predictions in minutes, making it suitable for practical applications in hit identification or lead optimization.

Improving protein-ligand docking results using the Semiempirical quantum mechanics: testing on the PDBbind 2016 core set

Molecular docking techniques are routinely employed for predicting ligand binding conformations and affinities in the in silico phase of the drug design and development process. In this study, a reliable semiempirical quantum mechanics (SQM) method, PM7, was employed for geometry optimization of top-ranked poses obtained from two widely used docking programs, AutoDock4 and AutoDock Vina. The PDBbind core set (version 2016), which contains high-quality crystal protein - ligand complexes with their corresponding experimental binding affinities, was used as an initial dataset in this research. It was shown that docking pose optimization improves the accuracy of pose predictions and is very useful for the refinement of docked complexes via removing clashes between ligands and proteins. It was also demonstrated that AutoDock Vina achieves a higher sampling power than AutoDock4 in generating accurate ligand poses (RMSD ≤ 2.0 Å), while AutoDock4 exhibits a better ranking power than AutoDock Vina. Finally, a new protocol based on a combination of the results obtained from the two docking programs was proposed for structure-based virtual screening studies, which benefits from the robust sampling abilities of AutoDock Vina and the reliable ranking performance of AutoDock4.Communicated by Ramaswamy H. Sarma.

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.

Computational methods for calculation of protein-ligand binding affinities in structure-based drug design

Drug design is an expensive and time-consuming process. Any method that allows reducing the time the costs of the drug development project can have great practical value for the pharmaceutical industry. In structure-based drug design, affinity prediction methods are of great importance. The majority of methods used to predict binding free energy in protein-ligand complexes use molecular mechanics methods. However, many limitations of these methods in describing interactions exist. An attempt to go beyond these limits is the application of quantum-mechanical description for all or only part of the analyzed system. However, the extensive use of quantum mechanical (QM) approaches in drug discovery is still a demanding challenge. This chapter briefly reviews selected methods used to calculate protein-ligand binding affinity applied in virtual screening (VS), rescoring of docked poses, and lead optimization stage, including QM methods based on molecular simulations.

QM/MM Well-Tempered Metadynamics Study of the Mechanism of XBP1 mRNA Cleavage by Inositol Requiring Enzyme 1α RNase

A range of in silico methodologies were herein employed to study the unconventional XBP1 mRNA cleavage mechanism performed by the unfolded protein response (UPR) mediator Inositol Requiring Enzyme 1α (IRE1). Using Protein-RNA molecular docking along with a series of extensive restrained/unrestrained atomistic molecular dynamics (MD) simulations, the dynamical behavior of the system was evaluated and a reliable model of the IRE1/XBP1 mRNA complex was constructed. From a series of well-converged quantum mechanics molecular mechanics well-tempered metadynamics (QM/MM WT-MetaD) simulations using the Grimme dispersion interaction corrected semiempirical parametrization method 6 level of theory (PM6-D3) and the AMBER14SB-OL3 force field, the free energy profile of the cleavage mechanism was determined, along with intermediates and transition state structures. The results show two distinct reaction paths based on general acid-general base type mechanisms, with different activation energies that perfectly match observations from experimental mutagenesis data. The study brings unique atomistic insights into the cleavage mechanism of XBP1 mRNA by IRE1 and clarifies the roles of the catalytic residues H910 and Y892. Increased understanding of the details in UPR signaling can assist in the development of new therapeutic agents for its modulation.

Using the Semiempirical Quantum Mechanics in Improving the Molecular Docking: A Case Study with CDK2

In this study, we use some modified semiempirical quantum mechanics (SQM) methods for improving the molecular docking process. To this end, the three popular SQM Hamiltonians, PM6, PM6-D3H4X, and PM7 are employed for geometry optimization of some binding modes of ligands docked into the human cyclin-dependent kinase 2 (CDK2) by two widely used docking tools, AutoDock and AutoDock Vina. The results were analyzed with two different evaluation metrics: the symmetry-corrected heavy-atom RMSD and the fraction of recovered ligand-protein contacts. It is shown that the evaluation of the fraction of recovered contacts is more useful to measure the similarity between two structures when interacting with a protein. It was also found that AutoDock is more successful than AutoDock Vina in producing the correct ligand poses (RMSD≤2.0 Å) and ranking of the poses. It is also demonstrated that the ligand optimization at the SQM level improves the docking results and the SQM structures have a significantly better fit to the observed crystal structures. Finally, the SQM optimizations reduce the number of close contacts in the docking poses and successfully remove most of the clash or bad contacts between ligand and protein.

Quantum Chemical Calculation of Molecular and Periodic Peptide and Protein Structures

Special-purpose classical force fields (FFs) provide good accuracy at very low computational cost, but their application is limited to systems for which potential energy functions are available. This excludes most metal-containing proteins or those containing cofactors. In contrast, the GFN2-xTB semiempirical quantum chemical method is parametrized for almost the entire periodic table. The accuracy of GFN2-xTB is assessed for protein structures with respect to experimental X-ray data. Furthermore, the results are compared with those of two special-purpose FFs, HF-3c, PM6-D3H4X, and PM7. The test sets include proteins without any prosthetic groups as well as metalloproteins. Crystal packing effects are examined for a set of smaller proteins to validate the molecular approach. For the proteins without prosthetic groups, the special purpose FF OPLS-2005 yields the smallest overall RMSD to the X-ray data but GFN2-xTB provides similarly good structures with even better bond-length distributions. For the metalloproteins with up to 5000 atoms, a good overall structural agreement is obtained with GFN2-xTB. The full geometry optimizations of protein structures with on average 1000 atoms in wall-times below 1 day establishes the GFN2-xTB method as a versatile tool for the computational treatment of various biomolecules with a good accuracy/computational cost ratio.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.

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.

Design and synthesis of new antitumor agents with the 1,7-epoxycyclononane framework. Study of their anticancer action mechanism by a model compound

This article describes the design, synthesis and biological evaluation of a new family of antitumor agents having the 1,7-epoxycyclononane framework. We have developed a versatile synthetic methodology that allows the preparation of a chemical library with structural diversity and in good yield. The synthetic methodology has been scaled up to the multigram level and can be developed in an enantioselective fashion. The study in vitro of a model compound, in front of the cancer cell lines HL-60 and MCF-7, showed a growth inhibitory effect better than that of cisplatin. The observation of cancer cells by fluorescence microscopy showed the presence of apoptotic bodies and a degradation of microtubules. The study of cell cycle and mechanism of death of cancer cells by flow cytometry indicates that the cell cycle arrested at the G₀/G₁ phase and that the cells died by apoptosis preferably over necrosis. A high percentage of apoptotic cells at the subG₀/G₁ level was observed. This indicates that our model compound does not behave as an antimitotic agent like nocodazole, used as a reference, which arrests the cell cycle at G₂/M phase. The interaction of anticancer agents with DNA molecules was evaluated by atomic force microscopy, circular dichroism and electrophoresis on agarose gel. The results indicate that the model compound has not DNA as a target molecule. The in silico study of the model compound showed a potential good oral bioavailability.

Fragment-based quantum mechanical calculation of protein-protein binding affinities

The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc.

Synthesis of the 10-oxabicyclo[5.2.1]decane framework present in bioactive natural products

The present work deals with the synthesis of the 10-oxabicyclo[5.2.1]decane framework present in bioactive natural products like physalins, with potential as antitumor agents. This synthetic methodology involves several key reactions: (a) synthesis of polyfunctionalized cycloheptenones by [4 + 3] cycloaddition reactions of furan precursors with oxyallyl cations; (b) Nicholas reaction with propargyl cations stabilized as dicobalt hexacarbonyl complexes; (c) demetallation and hydration of the resulting acetylenes; (d) stereoconvergent aldol cyclization to generate a key oxatricyclic intermediate and (e) a β-fragmentation process that affords, under hypoiodite photolysis, the desired product with moderate to good yield. The final compounds are the result of a radicalary β-fragmentation at the level of C2-C6 with respect to the tertiary hydroxyl group on C6, with an unexpected contraction from a ten- to a nine-membered ring system, via a radical addition to the carbonyl group on C4. The synthetic methodology has been scaled up to multigram level with good overall yield. Further biological, biochemical and biophysical studies are being carried out in our laboratory on these 1,7-epoxycyclononane derivatives to determine the potential of this kind of oxabicyclic compound as future hits and/or leads for the development of new anticancer drugs. The preliminary evaluation of the anticancer activity of the representative synthesized compounds, against the leukaemia cancer cell lines K-562 and SR, shows a promising activity with a GI₅₀ = 0.01 μM and a LC₅₀ = 7.4 μM for a conveniently functionalized 10-oxabicyclo[5.2.1]decane.

Looking Back, Looking Forward at Halogen Bonding in Drug Discovery

Halogen bonding has emerged at the forefront of advances in improving ligand: receptor interactions. In particular the newfound ability of this extant non-covalent-bonding phenomena has revolutionized computational approaches to drug discovery while simultaneously reenergizing synthetic approaches to the field. Here we survey, via examples of classical applications involving halogen atoms in pharmaceutical compounds and their biological hosts, the unique advantages that halogen atoms offer as both Lewis acids and Lewis bases.

Combined Docking with Classical Force Field and Quantum Chemical Semiempirical Method PM7

Results of the combined use of the classical force field and the recent quantum chemical PM7 method for docking are presented. Initially the gridless docking of a flexible low molecular weight ligand into the rigid target protein is performed with the energy function calculated in the MMFF94 force field with implicit water solvent in the PCM model. Among several hundred thousand local minima, which are found in the docking procedure, about eight thousand lowest energy minima are chosen and then energies of these minima are recalculated with the recent quantum chemical semiempirical PM7 method. This procedure is applied to 16 test complexes with different proteins and ligands. For almost all test complexes such energy recalculation results in the global energy minimum configuration corresponding to the ligand pose near the native ligand position in the crystalized protein-ligand complex. A significant improvement of the ligand positioning accuracy comparing with MMFF94 energy calculations is demonstrated.

Multistep Modeling Strategy To Improve the Binding Affinity Prediction of PET Tracers to Aβ42: Case Study with Styrylbenzoxazole Derivatives

Positron emission tomography (PET) tracers play an important role in the diagnosis of Alzheimer's disease, a condition that leads to progressive dementia and memory loss. A high binding affinity and specificity of the PET tracers to amyloid oligomers and fibrils are crucial for their successful application as diagnostic agents. In this sense, it is essential to design PET tracers with enhanced binding affinities, which can lead to more precise and earlier detection of Alzheimer's disease conditions. The application of in silico methodology for the design and development of efficient PET tracers may serve as an important route to improved Alzheimer's disease diagnosis. In this work, the performance of widely used computational methods is explored for predicting experimental binding affinities of styrylbenzoxazole (SB) derivatives against a common amyloid protofibril. By performing docking, molecular dynamics, and quantum chemistry calculations in sequence their combined predictive performance is explored. The present work emphasizes the merits as well as limitations of these simulation strategies in the realm of designing PET tracers for Alzheimer's disease diagnosis.

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.

Exponential repulsion improves structural predictability of molecular docking

Molecular docking is a powerful tool for theoretical prediction of the preferred conformation and orientation of small molecules within protein active sites. The obtained poses can be used for estimation of binding energies, which indicate the inhibition effect of designed inhibitors, and therefore might be used for in silico drug design. However, the evaluation of ligand binding affinity critically depends on successful prediction of the native binding mode. Contemporary docking methods are often based on scoring functions derived from molecular mechanical potentials. In such potentials, nonbonded interactions are typically represented by electrostatic interactions between atom-centered partial charges and standard 6-12 Lennard-Jones potential. Here, we present implementation and testing of a scoring function based on more physically justified exponential repulsion instead of the standard Lennard-Jones potential. We found that this scoring function significantly improved prediction of the native binding modes in proteins bearing narrow active sites such as serine proteases and kinases. © 2016 Wiley Periodicals, Inc.

The molecular shape and the field similarities as criteria to interpret SAR studies for fragment-based design of platinum(IV) anticancer agents. Correlation of physicochemical properties with cytotoxicity

Molecular shape similarity and field similarity have been used to interpret, in a qualitative way, the structure-activity relationships in a selected series of platinum(IV) complexes with anticancer activity. MM and QM calculations have been used to estimate the electron density, electrostatic potential maps, partial charges, dipolar moments and other parameters to correlate the stereo-electronic properties with the differential biological activity of complexes. Extended Electron Distribution (XED) field similarity has been also evaluated for the free 1,4-diamino carrier ligands, in a fragment-based drug design approach, comparing Connolly solvent excluded surface, hydrophobicity field surface, Van der Waals field surface, nucleophilicity field surface, electrophilicity field surface and the extended electron-distribution maxima field points. A consistency has been found when comparing the stereo-electronic properties of the studied series of platinum(IV) complexes and/or the free ligands evaluated and their in vitro anticancer activity.

Furoates and thenoates inhibit pyruvate dehydrogenase kinase 2 allosterically by binding to its pyruvate regulatory site

The last decade has witnessed the reawakening of cancer metabolism as a therapeutic target. In particular, inhibition of pyruvate dehydrogenase kinase (PDK) holds remarkable promise. Dichloroacetic acid (DCA), currently undergoing clinical trials, is a unique PDK inhibitor in which it binds to the allosteric pyruvate site of the enzyme. However, the safety of DCA as a drug is compromised by its neurotoxicity, whereas its usefulness as an investigative tool is limited by the high concentrations required to exert observable effects in cell culture. Herein, we report the identification - by making use of saturation-transfer difference NMR spectroscopy, enzymatic assays and computational methods - of furoate and thenoate derivatives as allosteric pyruvate-site-binding PDK2 inhibitors. This work substantiates the pyruvate regulatory pocket as a druggable target.

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.

Roles of the scalar and vector components of the solvation effects on the vibrational properties of hydrogen- or halogen-bond accepting stretching modes

Solvation-induced vibrational frequency shifts and infrared (IR) intensity changes of the hydrogen- or halogen-bond accepting stretching modes, especially their dependence on the angular position of the hydrogen- or halogen-bond donating molecule, are examined theoretically. Calculations are carried out for some modes of hydrogen- or halogen-bonding molecular complexes, including the S[double bond, length as m-dash]O stretch of dimethyl sulfoxide-(13)C2H2O, the C[triple bond, length as m-dash]N stretch of acetonitrileH2O, and the amide I' mode of the N-methylacetamide-d1BrNC 1 : 1 complex. It is shown that, in all the example cases dealt with in this study, the frequency shift depends rather strongly on the hydrogen- or halogen-bond angle (e.g., S[double bond, length as m-dash]OH angle), with a larger low-frequency shift as the hydrogen or halogen bond becomes more bent, indicating the generality of the results obtained for the amide I' mode of the N-methylacetamide-d1(2)H2O 1 : 1 complex in a previous study. Contrary to our vague expectation, the frequency shift is not well correlated to the hydrogen- or halogen-bond distance or strength, but nevertheless, it is well reproduced by an electrostatic interaction model if it is carefully constructed by considering the scalar and vector components separately in a reasonable way. On the basis of this electrostatic interaction model, the reason why our vague expectation is not realized is clarified, and a unified understanding is achieved on the hydration-induced high-frequency shift of the C[triple bond, length as m-dash]N stretch and the low-frequency shifts of the S[double bond, length as m-dash]O stretch and amide I'. With regard to the IR intensity, it is shown that, in some of the example cases, it also has rather strong angular position dependence. The mechanism of the IR intensity changes is estimated by analyzing the dipole derivative vector, especially its angular relation with the hydrogen or halogen bond.

The Halogen Bond

The halogen bond occurs when there is evidence of a net attractive interaction between an electrophilic region associated with a halogen atom in a molecular entity and a nucleophilic region in another, or the same, molecular entity. In this fairly extensive review, after a brief history of the interaction, we will provide the reader with a snapshot of where the research on the halogen bond is now, and, perhaps, where it is going. The specific advantages brought up by a design based on the use of the halogen bond will be demonstrated in quite different fields spanning from material sciences to biomolecular recognition and drug design.

The SQM/COSMO filter: reliable native pose identification based on the quantum-mechanical description of protein–ligand interactions and implicit COSMO solvation

Strictly uphill – in cognate docking experiments we show that a quantum mechanical description of interaction and solvation outperforms established scoring functions in sharply distinguishing the native state from decoy poses.

Predictive Models for Halogen-bond Basicity of Binding Sites of Polyfunctional Molecules

Halogen bonding (XB) strength assesses the ability of an electron-enriched group to be involved in complexes with polarizable electrophilic halogenated or diatomic halogen molecules. Here, we report QSPR models of XB of particular relevance for an efficient screening of large sets of compounds. The basicity is described by pKBI2 , the decimal logarithm of the experimental 1 : 1 (B : I2 ) complexation constant K of organic compounds (B) with diiodine (I2 ) as a reference halogen-bond donor in alkanes at 298 K. Modeling involved ISIDA fragment descriptors, using SVM and MLR methods on a set of 598 organic compounds. Developed models were then challenged to make predictions for an external test set of 11 polyfunctional compounds for which unambiguous assignment of the measured effective complexation constant to specific groups out of the putative acceptor sites is not granted. At this stage, developed models were used to predict pKBI2 of all putative acceptor sites, followed by an estimation of the predicted effective complexation constant using the ChemEqui program. The best consensus models perform well both in cross-validation (root mean squared error RMSE=0.39-0.47 logKBI2 units) and external predictions (RMSE=0.49). The SVM models are implemented on our website (http://infochim.u-strasbg.fr/webserv/VSEngine.html) together with the estimation of their applicability domain and an automatic detection of potential halogen-bond acceptor atoms.

The properties of substituted 3D-aromatic neutral carboranes: the potential for σ-hole bonding

The calculated properties of substituted carboranes such as dipole moment, polarisability, the magnitude of the σ-hole and the desolvation free energy are compared with these properties in comparable aromatic and cyclic aliphatic organic compounds. Dispersion and charge transfer energies are similar. However, the predicted strength of the halogen bonds with the same electron donor (based on the magnitude of the σ-hole) is larger for neutral C-vertex halogen-substituted carboranes than for their organic counterparts. Furthermore, the desolvation penalties of substituted carboranes are smaller than those of the corresponding organic compounds, which should further strengthen the halogen bonds of the former in the solvent. It is predicted that substituted carboranes have the potential to form stronger halogen bonds than comparable aromatic hydrocarbons, which will be even more pronounced in the medium. This theoretical study thus lays ground for the rational engineering of halogen bonding in inorganic crystals as well as in biomolecular complexes.

Malonate-based inhibitors of mammalian serine racemase: kinetic characterization and structure-based computational study

Overactivation of NMDA receptors has been implicated in various neuropathological conditions, including brain ischaemia, neurodegenerative disorders and epilepsy. Production of d-serine, an NMDA receptor co-agonist, from l-serine is catalyzed in vivo by the pyridoxal-5'-phosphate (PLP)-dependent enzyme serine racemase. Specific inhibition of this enzyme has been proposed as a promising strategy for treatment of neurological conditions caused by NMDA receptor dysfunction. Here we present the synthesis and activity analysis of a series of malonate-based inhibitors of mouse serine racemase (mSR). The compounds possessed IC50 values ranging from 40 ± 11 mM for 2,2-bis(hydroxymethyl)malonate down to 57 ± 1 μM for 2,2-dichloromalonate, the most effective competitive mSR inhibitor known to date. The structure-activity relationship of the whole series in the human orthologue (hSR) was interpreted using Glide docking, WaterMap analysis of hydration and quantum mechanical calculations based on the X-ray structure of the hSR/malonate complex. Docking into the hSR active site with three thermodynamically favourable water molecules was able to discern qualitatively between good and weak inhibitors. Further improvement in ranking was obtained using advanced PM6-D3H4X/COSMO semiempirical quantum mechanics-based scoring which distinguished between the compounds with IC50 better/worse than 2 mM. We have thus not only found a new potent hSR inhibitor but also worked out a computer-assisted protocol to rationalize the binding affinity which will thus aid in search for more effective SR inhibitors. Novel, potent hSR inhibitors may represent interesting research tools as well as drug candidates for treatment of diseases associated with NMDA receptor overactivation.

Synthesis, biological evaluation and SAR studies of novel bicyclic antitumor platinum(IV) complexes

The present study describes the synthesis, anticancer activity and SAR studies of novel platinum(IV) complexes having 1,2-bis(aminomethyl)carbobicyclic or oxabicyclic carrier ligands, bearing chlorido and/or hydroxido ligands in axial position and chlorido or malonato ligands in equatorial position (labile ligands). These complexes were synthetized with the aim of obtaining new anticancer principles more soluble in water and therefore more bioavailable. Several substitution patterns on the platinum atom have been designed in order to evaluate their antiproliferative activity and to establish structure-activity relationship rules. The synthesis of platinum(IV) complexes with axial hydroxyl ligands on the platinum(IV) were carried out by reaction of K2Pt(OH)2Cl4 with the corresponding diamines. The complexes with axial chlorido ligands on the platinum(IV) atom were synthesized by direct reaction of diamines with K2PtCl6. Carboxylated complexes were synthesized by the substitution reaction of equatorial chlorido ligands by silver dicarboxylates. The most actives complexes were those having malonate as a labile ligand, no matter of the structure of the carrier ligand. Regarding the influence of the structure of the non-labile 1,4-diamine carrier ligand on the cytotoxicity, it was found that the complexes having the more lipophilic and symmetrical bicyclo[2.2.2]octane framework were much more active than those having an oxygen or methylene bridge.

The relative roles of electrostatics and dispersion in the stabilization of halogen bonds

In this work we highlight recent work aimed at the characterization of halogen bonds. Here we discuss the origins of the σ-hole, the modulation of halogen bond strength by changing of neighboring chemical groups (i.e. halogen bond tuning), the performance of various computational methods in treating halogen bonds, and the strength and character of the halogen bond, the dihalogen bond, and two hydrogen bonds in bromomethanol dimers (which serve as model complexes) are compared. Symmetry adapted perturbation theory analysis of halogen bonding complexes indicates that halogen bonds strongly depend on both dispersion and electrostatics. The electrostatic interaction that occurs between the halogen σ-hole and the electronegative halogen bond donor is responsible for the high degree of directionality exhibited by halogen bonds. Because these noncovalent interactions have a strong dispersion component, it is important that the computational method used to treat a halogen bonding system be chosen very carefully, with correlated methods (such as CCSD(T)) being optimal. It is also noted here that most forcefield-based molecular mechanics methods do not describe the halogen σ-hole, and thus are not suitable for treating systems with halogen bonds. Recent attempts to improve the molecular mechanics description of halogen bonds are also discussed.

Biomolecular halogen bonds

Halogens are atypical elements in biology, but are common as substituents in ligands, including thyroid hormones and inhibitors, which bind specifically to proteins and nucleic acids. The short-range, stabilizing interactions of halogens - now seen as relatively common in biology - conform generally to halogen bonds characterized in small molecule systems and as described by the σ-hole model. The unique properties of biomolecular halogen bonds (BXBs), particularly in their geometric and energetic relationship to classic hydrogen bonds, make them potentially powerful tools for inhibitor design and molecular engineering. This chapter reviews the current research on BXBs, focusing on experimental studies on their structure-energy relationships, how these studies inform the development of computational methods to model BXBs, and considers how BXBs can be applied to the rational design of more effective inhibitors against therapeutic targets and of new biological-based materials.

Quantum mechanics-based scoring rationalizes the irreversible inactivation of parasitic Schistosoma mansoni cysteine peptidase by vinyl sulfone inhibitors

The quantum mechanics (QM)-based scoring function that we previously developed for the description of noncovalent binding in protein-ligand complexes has been modified and extended to treat covalent binding of inhibitory ligands. The enhancements are (i) the description of the covalent bond breakage and formation using hybrid QM/semiempirical QM (QM/SQM) restrained optimizations and (ii) the addition of the new ΔG(cov)' term to the noncovalent score, describing the "free" energy difference between the covalent and noncovalent complexes. This enhanced QM-based scoring function is applied to a series of 20 vinyl sulfone-based inhibitory compounds inactivating the cysteine peptidase cathepsin B1 of the Schistosoma mansoni parasite (SmCB1). The available X-ray structure of the SmCB1 in complex with a potent vinyl sulfone inhibitor K11017 is used as a template to build the other covalently bound complexes and to model the derived noncovalent complexes. We present the correlation of the covalent score and its constituents with the experimental binding data. Four outliers are identified. They contain bulky R1' substituents structurally divergent from the template, which might induce larger protein rearrangements than could be accurately modeled. In summary, we propose a new computational approach and an optimal protocol for the rapid evaluation and prospective design of covalent inhibitors with a conserved binding mode.