Water mediated ligand functional group cooperativity: the contribution of a methyl group to binding affinity is enhanced by a COO(-) group through changes in the structure and thermodynamics of the hydration waters of ligand-thermolysin complexes

The application of WaterMap-guided structure-based virtual screening in novel drug discovery

INTRODUCTION

Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface.

AREAS COVERED

In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023.

EXPERT OPINION

In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.

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.

Water Networks in Complexes between Proteins and FDA-Approved Drugs

Water molecules at protein-ligand interfaces are often of significant pharmaceutical interest, owing in part to the entropy which can be released upon the displacement of an ordered water by a therapeutic compound. Protein structures may not, however, completely resolve all critical bound water molecules, or there may be no experimental data available. As such, predicting the location of water molecules in the absence of a crystal structure is important in the context of rational drug design. Grand canonical Monte Carlo (GCMC) is a computational technique that is gaining popularity for the simulation of buried water sites. In this work, we assess the ability of GCMC to accurately predict water binding locations, using a dataset that we have curated, containing 108 unique structures of complexes between proteins and Food and Drug Administration (FDA)-approved small-molecule drugs. We show that GCMC correctly predicts 81.4% of nonbulk crystallographic water sites to within 1.4 Å. However, our analysis demonstrates that the reported performance of water prediction methods is highly sensitive to the way in which the performance is measured. We also find that crystallographic water sites with more protein/ligand hydrogen bonds and stronger electron density are more reliably predicted by GCMC. An analysis of water networks revealed that more than half of the structures contain at least one ligand-contacting water network. In these cases, displacement of a water site by a ligand modification might yield unexpected results if the larger network is destabilized. Cooperative effects between waters should therefore be explicitly considered in structure-based drug design.

Water molecules at protein-drug interfaces: computational prediction and analysis methods

The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.

Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein-ligand interactions and quantitative structure-activity relationship studies

It is frequently mentioned that QSARs have not generally lived up to expectations, especially in cases where high predictability is expected yet failed to deliver satisfactory results. Even though outliers can provide an increased opportunity in drug discovery research, outliers in SAR and QSAR can contort predictions and affect the accuracy if proper attention is not given. The percentages of outliers in QSARs have not changed appreciably over the last decade. In our previous studies, we suggested two possible sources of outliers in SAR and QSAR. In this paper, we suggest an additional possible source of outliers in QSAR. We presented several literature examples that show one or more water molecules that play a critical role in protein-ligand binding interactions as observed in their crystal structures. These examples illustrate that failing to account for the effects of water molecules in protein-ligand interactions could mislead interpretation and possibly yield outliers in SAR and QSAR. Examples include cases where QSAR, considering the role of water molecules in protein-ligand crystal structures, provided deeper insight into the understanding and interpretation of the developed QSAR.

Synthetic Methods of Phosphonopeptides

Phosphonopeptides are phosphorus analogues of peptides and have been widely applied as enzyme inhibitors and antigens to induce catalytic antibodies. Phosphonopeptides generally contain one aminoalkylphosphonic acid residue and include phosphonopeptides with C-terminal aminoalkylphosphonic acids and phosphonopeptides with a phosphonamidate bond. The phosphonamidate bond in the phosphonopeptides is generally formed via phosphonylation with phosphonochloridates, condensation with coupling reagents and enzymes, and phosphinylation followed by oxidation. Pseudo four-component condensation reaction of amides, aldehydes, alkyl dichlorophosphites, and amino/peptide esters is an alternative, convergent, and efficient strategy for synthesis of phosphonopeptides through simultaneous construction of aminoalkylphosphonic acids and formation of the phosphonamidate bond. This review focuses on the synthetic methods of phosphonopeptides containing a phosphonamidate bond.

Prediction of water positions in the binding sites of proteins based on collections of multi-source heterogeneous atoms

Water molecules play an important role in mediating the interactions between proteins and ligands. However, it is difficult to distinguish the key water molecules directly because they are widely and irregularly distributed. Based on the results of statistical analysis, a composite tetrahedral model is proposed to predict the potential hydration sites in the binding sites of crystal structures. By analyzing the different protein atoms and ligand atoms that interact with water molecules, the unified representation and measurement of these multi-source heterogeneous atoms in the multi-dimensional feature space were adopted. The potential hydration sites could be predicted based on the results of the preference analysis and the shape-matching method. A test set was used to evaluate the model performance and extensive comparison with the tetrahedral-water-cluster model and Dowser++ revealed that the composite tetrahedral model can not only predict the potential sites of multiple key water molecules in the binding sites but also has a better prediction accuracy.

Nonadditivity Analysis

We introduce the statistics behind a novel type of SAR analysis named "nonadditivity analysis". On the basis of all pairs of matched pairs within a given data set, the approach analyzes whether the same transformations between related molecules have the same effect, i.e., whether they are additive. Assuming that the experimental uncertainty is normally distributed, the additivities can be analyzed with statistical rigor and sets of compounds can be found that show significant nonadditivity. Nonadditivity analysis can not only detect nonadditivity, potential SAR outliers, and sets of key compounds but also allow estimating an upper limit of the experimental uncertainty in the data set. We demonstrate how complex SAR features that inform medicinal chemistry can be found in large SAR data sets. Finally, we show how the upper limit of experimental uncertainty for a given biochemical assay can be estimated without the need for repeated measurements of the same protein-ligand system.

Water in protein hydration and ligand recognition

This review describes selected basics of water in biomolecular recognition. We focus on a qualitative understanding of the most important physical aspects, how these change in magnitude between bulk water and protein environment, and how the roles that water plays for proteins arise from them. These roles include mechanical support, thermal coupling, dielectric screening, mass and charge transport, and the competition with a ligand for the occupation of a binding site. The presence or absence of water has ramifications that range from the thermodynamic binding signature of a single ligand up to cellular survival. The large inhomogeneity in water density, polarity and mobility around a solute is hard to assess in experiment. This is a source of many difficulties in the solvation of protein models and computational studies that attempt to elucidate or predict ligand recognition. The influence of water in a protein binding site on the experimental enthalpic and entropic signature of ligand binding is still a point of much debate. The strong water‐water interaction in enthalpic terms is counteracted by a water molecule's high mobility in entropic terms. The complete arrest of a water molecule's mobility sets a limit on the entropic contribution of a water displacement process, while the solvent environment sets limits on ligand reactivity.

Overview of Recent Strategic Advances in Medicinal Chemistry

Introducing novel strategies, concepts, and technologies that speed up drug discovery and the drug development cycle is of great importance both in the highly competitive pharmaceutical industry as well as in academia. This Perspective aims to present a "big-picture" overview of recent strategic innovations in medicinal chemistry and drug discovery.

Cooperativity effect of the ππ interaction between drug and DNA on intercalative binding induced by H-bonds: a QM/QTAIM investigation of the curcuminadenineH2O model system

In order to reveal the nature of intercalative binding of drug to DNA, the cooperativity effect of the ππ interaction was investigated in the curcuminadenineH2O model system by applying a combined QM and QTAIM computational approach. The H-bonds between the electron-donating group of curcumin and adenine induce the formation of the ππ stacking. The introduction of H2O weakens the H-bonding and ππ interactions, leading to an anti-cooperativity effect, as is confirmed by the AIM (atoms in molecules) and RDG (reduced density gradient) analysis. Thus, it can be inferred that the anti-cooperative effect is the main driving force for the intercalative binding of drug to DNA bases, which is in agreement with many experimental phenomena. Therefore, the designed DNA-targeted intercalating drugs should possess not only hydrophobic moieties, but also strong electron-donating groups bound to the DNA bases with H-bonds, which can slow the variation rates of the strengths of the H-bonding and ππ interactions between drug and DNA bases in the anti-cooperative process, leading to the intercalation formation. The enthalpy change is the major factor driving the positive thermodynamic cooperativity.

Effects of the Hofmeister series of sodium salts on the solvent properties of water

The solvent features of water (solvent dipolarity/polarizability, π*, hydrogen bond donor acidity, α, and hydrogen bond acceptor basicity, β) were examined in aqueous solutions of Na₂SO₄, NaF, CH₃COONa, NaCl, NaBr, NaI, and NaClO₄ at concentrations of each salt from 0 to 1.0 M (up to 2.0 M for NaClO₄). The solvent features of water in solutions of different concentrations for each salt were found to be linearly related as π* = z + aα + bβ. The coefficients of this relationship were suggested to represent the signature of the salt effect on the solvent features of water. The normalized distances for each salt were calculated using glucose as a reference compound. These distances may be used as the relative measures of the salt-water interactions. It is demonstrated that the distances for all salts examined are interrelated with structural water entropies and static polarizabilities of anions. It is shown that the distance may be used as a measure of the relative effects of salts on precipitation of ferric oxide, excessive chemical potential of propanol in salt solutions, surface tension, and viscosity. The distance represents the relative measure of the salt effect on the solvent features of water in a salt solution. The examples presented confirm that the approach used does enable us to characterize the differences between the effects of salts in the Hofmeister series on the properties of water.

Replica-Exchange and Standard State Binding Free Energies with Grand Canonical Monte Carlo

The ability of grand canonical Monte Carlo (GCMC) to create and annihilate molecules in a given region greatly aids the identification of water sites and water binding free energies in protein cavities. However, acceptance rates without the application of biased moves can be low, resulting in large variations in the observed water occupancies. Here, we show that replica-exchange of the chemical potential significantly reduces the variance of the GCMC data. This improvement comes at a negligible increase in computational expense when simulations comprise of runs at different chemical potentials. Replica-exchange GCMC is also found to substantially increase the precision of water binding free energies as calculated with grand canonical integration, which has allowed us to address a missing standard state correction.

Water Sites, Networks, And Free Energies with Grand Canonical Monte Carlo

Water molecules play integral roles in the formation of many protein-ligand complexes, and recent computational efforts have been focused on predicting the thermodynamic properties of individual waters and how they may be exploited in rational drug design. However, when water molecules form highly coupled hydrogen-bonding networks, there is, as yet, no method that can rigorously calculate the free energy to bind the entire network or assess the degree of cooperativity between waters. In this work, we report theoretical and methodological developments to the grand canonical Monte Carlo simulation technique. Central to our results is a rigorous equation that can be used to calculate efficiently the binding free energies of water networks of arbitrary size and complexity. Using a single set of simulations, our methods can locate waters, estimate their binding affinities, capture the cooperativity of the water network, and evaluate the hydration free energy of entire protein binding sites. Our techniques have been applied to multiple test systems and compare favorably to thermodynamic integration simulations and experimental data. The implications of these methods in drug design are discussed.

Rational Design of Benzylidenehydrazinyl-Substituted Thiazole Derivatives as Potent Inhibitors of Human Dihydroorotate Dehydrogenase with in Vivo Anti-arthritic Activity

Human dihydroorotate dehydrogenase (hDHODH) is an attractive therapeutic target for the treatment of rheumatoid arthritis, transplant rejection and other autoimmune diseases. Based on the X-ray structure of hDHODH in complex with lead compound 7, a series of benzylidenehydrazinyl-substituted thiazole derivatives as potent inhibitors of hDHODH were designed and synthesized, of which 19 and 30 were the most potent with IC₅₀ values in the double-digit nanomolar range. Moreover, compound 19 displayed significant anti-arthritic effects and favorable pharmacokinetic profiles in vivo. Further X-ray structure and SAR analyses revealed that the potencies of the designed inhibitors were partly attributable to additional water-mediated hydrogen bond networks formed by an unexpected buried water between hDHODH and the 2-(2-methylenehydrazinyl)thiazole scaffold. This work not only elucidates promising scaffolds targeting hDHODH for the treatment of rheumatoid arthritis, but also demonstrates that the water-mediated hydrogen bond interaction is an important factor in molecular design and optimization.

Molecular recognition in chemical and biological systems

Structure-based ligand design in medicinal chemistry and crop protection relies on the identification and quantification of weak noncovalent interactions and understanding the role of water. Small-molecule and protein structural database searches are important tools to retrieve existing knowledge. Thermodynamic profiling, combined with X-ray structural and computational studies, is the key to elucidate the energetics of the replacement of water by ligands. Biological receptor sites vary greatly in shape, conformational dynamics, and polarity, and require different ligand-design strategies, as shown for various case studies. Interactions between dipoles have become a central theme of molecular recognition. Orthogonal interactions, halogen bonding, and amide⋅⋅⋅π stacking provide new tools for innovative lead optimization. The combination of synthetic models and biological complexation studies is required to gather reliable information on weak noncovalent interactions and the role of water.

A B3LYP and MP2(full) theoretical investigation into cooperativity effects, aromaticity and thermodynamic properties in the Na(+)⋯benzonitrile⋯H2O ternary complex

The cooperativity effects between H-bonding and Na(+)⋯π or Na(+)⋯σ interactions in Na(+)⋯benzonitrile⋯H2O complexes were investigated using the B3LYP and MP2(full) methods with 6-311++G(2d,p) and aug-cc-pVTZ basis sets. The thermodynamic cooperativity and the influence of this cooperativity on aromaticity was evaluated by nucleus-independent chemical shifts (NICS). The results showed that the influence of the Na(+)⋯σ or Na(+)⋯π interaction on the hydrogen bond is more pronounced than that of the latter on the former. The cooperativity effect appeared in the Na(+)⋯σ interaction complex while the anti-cooperativity effect tended to be in the Na(+)⋯π system. The change in enthalpy is the major factor driving cooperativity. Thermodynamic cooperativity is not in accordance with the cooperativity effect evaluated by the change of interaction energy. The ring aromaticity of is weakened while the bond dissociation energy (BDE) of the C-CN bond increases upon ternary complex formation. The cooperativity effect (E coop) correlates with R c (NICS(1)ternary/NICS(1)binary) and ΔΔδ (Δδ ternary - Δδ binary) involving the ring and C ≡ N bond, as well as R BDE(C-CN) [BDE(C-CN)ternary/BDE(C-CN)binary], respectively. AIM (atoms in molecules) analysis confirms the existence of cooperativity.