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

Dynamics of nucleoplasm in human leukemia cells: A thrust towards designing anti-leukemic agents

The human inosine monophosphate dehydrogenase (hIMPDH) is a metabolic enzyme that possesses a unique ability to self-assemble into higher-order structures, forming cytoophidia. The hIMPDH II isoform is more active in chronic myeloid leukemia (CML) cancer cells, making it a promising target for anti-leukemic therapy. However, the structural details and molecular mechanisms of the dynamics of hIMPDHcytoophidia assembly in vitro need to be better understood, and it is crucial to reconstitute the computational nucleoplasm model with cytophilic-like polymers in vitro to characterize their structure and function. Finally, a computational model and its dynamics of the nucleoplasm for CML cells have been proposed in this short review. This research on nucleoplasm aims to aid the scientific community's understanding of how metabolic enzymes like hIMPDH function in cancer and normal cells. However, validating and justifying the computational results from modeling and simulation with experimental data is essential. The new insights gained from this research could explain the structure/topology, geometrical, and electronic consequences of hIMPDH inhibitors on leukemic and normal cells. They could lead to further advancements in the knowledge of nucleoplasmic chemical reaction dynamics.

Structural and thermodynamic properties of conserved water molecules in Mpro native: A combined approach by MD simulation and Grid Inhomogeneous Solvation Theory

The new viral strains of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are continuously rising, becoming more virulent, and transmissible. Therefore, the development of new antiviral drugs is essential. Due to its significant role in the viral life cycle of SARS-CoV-2, the main protease (Mpro) enzyme is a leading target for antiviral drug design. The Mpro monomer consists of domain DI, DII, and DI-DII interface. Twenty-one conserved water molecules (W4-W24) are occupied at these domains according to multiple crystal structure analyses. The crystal and MD structures reveal the presence of eight conserved water sites in domain DI, DII and remaining in the DI-DII interface. Grid-based inhomogeneous fluid solvation theory (GIST) was employed on MD structures of Mpro native to predict structural and thermodynamic properties of each conserved water site for focusing to identify the specific conserved water molecules that can easily be displaced by proposed ligands. Finally, MD water W13 is emerged as a promising candidate for water mimic drug design due to its low mean interaction energy, loose binding character with the protein, and its involvement in a water-mediated H-bond with catalytic His41 via the interaction Thr25(OG)---W13---W---His41(NE2). In this context, water occupancy, relative interaction energy, entropy, and topologies of W13 are thermodynamically acceptable for the water displacement method. Therefore, the strategic use of W13's geometrical position in the DI domain may be implemented for drug discovery against COVID disease by designing new ligands with appropriately oriented chemical groups to mimic its structural, electronic, and thermodynamic properties.

Free Energy Density of a Fluid and Its Role in Solvation and Binding

The concept that a fluid has a position-dependent free energy density appears in the literature but has not been fully developed or accepted. We set this concept on an unambiguous theoretical footing via the following strategy. First, we set forth four desiderata that should be satisfied by any definition of the position-dependent free energy density, f(R), in a system comprising only a fluid and a rigid solute: its volume integral, plus the fixed internal energy of the solute, should be the system free energy; it deviates from its bulk value, fbulk, near a solute but should asymptotically approach fbulk with increasing distance from the solute; it should go to zero where the solvent density goes to zero; and it should be well-defined in the most general case of a fluid made up of flexible molecules with an arbitrary interaction potential. Second, we use statistical thermodynamics to formulate a definition of the free energy density that satisfies these desiderata. Third, we show how any free energy density satisfying the desiderata may be used to analyze molecular processes in solution. In particular, because the spatial integral of f(R) equals the free energy of the system, it can be used to compute free energy changes that result from the rearrangement of solutes as well as the forces exerted on the solutes by the solvent. This enables the use of a thermodynamic analysis of water in protein binding sites to inform ligand design. Finally, we discuss related literature and address published concerns regarding the thermodynamic plausibility of a position-dependent free energy density. The theory presented here has applications in theoretical and computational chemistry and may be further generalizable beyond fluids, such as to solids and macromolecules.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

Local Water Content in Polymer Gels Measured with Super-Resolved Fluorescence Lifetime Imaging

Water molecules play an important role in the structure, function, and dynamics of (bio-) materials. A direct access to the number of water molecules in nanoscopic volumes can thus give new molecular insights into materials and allow for fine-tuning their properties in sophisticated applications. The determination of the local water content has become possible by the finding that H2 O quenches the fluorescence of red-emitting dyes. Since deuterated water, D2 O, does not induce significant fluorescence quenching, fluorescence lifetime measurements performed in different H2 O/D2 O-ratios yield the local water concentration. We combined this effect with the recently developed fluorescence lifetime single molecule localization microscopy imaging (FL-SMLM) in order to nanoscopically determine the local water content in microgels, i.e. soft hydrogel particles consisting of a cross-linked polymer swollen in water. The change in water content of thermo-responsive microgels when changing from their swollen state at room temperature to a collapsed state at elevated temperature could be analyzed. A clear decrease in water content was found that was, to our surprise, rather uniform throughout the entire microgel volume. Only a slightly higher water content around the dye was found in the periphery with respect to the center of the swollen microgels.

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.

Binding Thermodynamics of Fourth-Generation EGFR Inhibitors Revealed by Absolute Binding Free Energy Calculations

The overexpression or mutation of the kinase domain of the epidermal growth factor receptor (EGFR) is strongly associated with non-small-cell lung cancer (NSCLC). EGFR tyrosine kinase inhibitors (TKIs) have proven to be effective in treating NSCLC patients. However, EGFR mutations can result in drug resistance. To elucidate the mechanisms underlying this resistance and inform future drug development, we examined the binding affinities of BLU-945, a recently reported fourth-generation TKI, to wild-type EGFR (EGFRWT) and its double-mutant (L858R/T790M; EGFRDM) and triple-mutant (L858R/T790M/C797S; EGFRTM) forms. We compared the binding affinities of BLU-945, BLU-945 analogues, CH7233163 (another fourth-generation TKI), and erlotinib (a first-generation TKI) using absolute binding free energy calculations. Our findings reveal that BLU-945 and CH7233163 exhibit binding affinities to both EGFRDM and EGFRTM stronger than those of erlotinib, corroborating experimental data. We identified K745 and T854 as the key residues in the binding of fourth-generation EGFR TKIs. Electrostatic forces were the predominant driving force for the binding of fourth-generation TKIs to EGFR mutants. Furthermore, we discovered that the incorporation of piperidinol and sulfone groups in BLU-945 substantially enhanced its binding capacity to EGFR mutants. Our study offers valuable theoretical insights for optimizing fourth-generation EGFR TKIs.

Resolving binding pathways and solvation thermodynamics of plant hormone receptors

Plant hormones are small molecules that regulate plant growth, development, and responses to biotic and abiotic stresses. They are specifically recognized by the binding site of their receptors. In this work, we resolved the binding pathways for eight classes of phytohormones (auxin, jasmonate, gibberellin, strigolactone, brassinosteroid, cytokinin, salicylic acid, and abscisic acid) to their canonical receptors using extensive molecular dynamics simulations. Furthermore, we investigated the role of water displacement and reorganization at the binding site of the plant receptors through inhomogeneous solvation theory. Our findings predict that displacement of water molecules by phytohormones contributes to free energy of binding via entropy gain and is associated with significant free energy barriers for most systems analyzed. Also, our results indicate that displacement of unfavorable water molecules in the binding site can be exploited in rational agrochemical design. Overall, this study uncovers the mechanism of ligand binding and the role of water molecules in plant hormone perception, which creates new avenues for agrochemical design to target plant growth and development.

De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO

By mediating interatomic interactions, water molecules play a major role in protein-protein, protein-DNA and protein-ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein-protein interfaces.

Structural conservation of antibiotic interaction with ribosomes

The ribosome is a major target for clinically used antibiotics, but multidrug resistant pathogenic bacteria are making our current arsenal of antimicrobials obsolete. Here we present cryo-electron-microscopy structures of 17 distinct compounds from six different antibiotic classes bound to the bacterial ribosome at resolutions ranging from 1.6 to 2.2 Å. The improved resolution enables a precise description of antibiotic-ribosome interactions, encompassing solvent networks that mediate multiple additional interactions between the drugs and their target. Our results reveal a high structural conservation in the binding mode between antibiotics with the same scaffold, including ordered water molecules. Water molecules are visualized within the antibiotic binding sites that are preordered, become ordered in the presence of the drug and that are physically displaced on drug binding. Insight into RNA-ligand interactions will facilitate development of new antimicrobial agents, as well as other RNA-targeting therapies.

Discovery and structural characterization of monkeypox virus methyltransferase VP39 inhibitors reveal similarities to SARS-CoV-2 nsp14 methyltransferase

Monkeypox is a disease with pandemic potential. It is caused by the monkeypox virus (MPXV), a double-stranded DNA virus from the Poxviridae family, that replicates in the cytoplasm and must encode for its own RNA processing machinery including the capping machinery. Here, we present crystal structures of its 2'-O-RNA methyltransferase (MTase) VP39 in complex with the pan-MTase inhibitor sinefungin and a series of inhibitors that were discovered based on it. A comparison of this 2'-O-RNA MTase with enzymes from unrelated single-stranded RNA viruses (SARS-CoV-2 and Zika) reveals a conserved sinefungin binding mode, implicating that a single inhibitor could be used against unrelated viral families. Indeed, several of our inhibitors such as TO507 also inhibit the coronaviral nsp14 MTase.

In Silico Evaluation of the Thr58-Associated Conserved Water with KRAS Switch-II Pocket Binders

The KRAS switch-II pocket (SII-P) has proven to be one of the most successful tools for targeting KRAS with small molecules to date. This has been demonstrated with several KRAS(G12C)-targeting covalent inhibitors, already resulting in two FDA-approved drugs. Several earlier-stage compounds have also been reported to engage KRAS SII-P with other position 12 mutants, including G12D, G12S, and G12R. A highly conserved water molecule exists in the KRAS SII-P, linking Thr58 of switch-II and Gly10 of β1 sheet. This conserved water is also present in the cocrystal structures of most of the disclosed small-molecule inhibitors but is only displaced by a handful of SII-P binders. Here, we evaluated the conserved water molecule energetics by the WaterMap for the SII-P binders with publicly disclosed structures and studied the water behavior in the presence of selected inhibitors by microsecond timescale molecular dynamics (MD) simulations using two water models (total simulation time of 120 μs). Our data revealed the high-energy nature of this hydration site when coexisting with an SII-P binder and that there is a preference for a single isolated hydration site in this location within the most advanced compounds. Furthermore, water displacement was only achieved with a few disclosed compounds and was suboptimal, as for instance a cyanomethyl group as a water displacer appears to introduce repulsion with the native conformation of Thr58. These results suggested that this conserved water should be considered more central when designing new inhibitors, especially in the design of noncovalent inhibitors targeting the SII-P.

Quantum Mechanical-Cluster Approach to Solve the Bioisosteric Replacement Problem in Drug Design

Bioisosteres are molecules that differ in substituents but still have very similar shapes. Bioisosteric replacements are ubiquitous in modern drug design, where they are used to alter metabolism, change bioavailability, or modify activity of the lead compound. Prediction of relative affinities of bioisosteres with computational methods is a long-standing task; however, the very shape closeness makes bioisosteric substitutions almost intractable for computational methods, which use standard force fields. Here, we design a quantum mechanical (QM)-cluster approach based on the GFN2-xTB semi-empirical quantum-chemical method and apply it to a set of H → F bioisosteric replacements. The proposed methodology enables advanced prediction of biological activity change upon bioisosteric substitution of -H with -F, with the standard deviation of 0.60 kcal/mol, surpassing the ChemPLP scoring function (0.83 kcal/mol), and making QM-based ΔΔG estimation comparable to ∼0.42 kcal/mol standard deviation of in vitro experiment. The speed of the method and lack of tunable parameters makes it affordable in current drug research.

Enhanced Grand Canonical Sampling of Occluded Water Sites Using Nonequilibrium Candidate Monte Carlo

Water molecules play a key role in many biomolecular systems, particularly when bound at protein-ligand interfaces. However, molecular simulation studies on such systems are hampered by the relatively long time scales over which water exchange between a protein and solvent takes place. Grand canonical Monte Carlo (GCMC) is a simulation technique that avoids this issue by attempting the insertion and deletion of water molecules within a given structure. The approach is constrained by low acceptance probabilities for insertions in congested systems, however. To address this issue, here, we combine GCMC with nonequilibium candidate Monte Carlo (NCMC) to yield a method that we refer to as grand canonical nonequilibrium candidate Monte Carlo (GCNCMC), in which the water insertions and deletions are carried out in a gradual, nonequilibrium fashion. We validate this new approach by comparing GCNCMC and GCMC simulations of bulk water and three protein binding sites. We find that not only is the efficiency of the water sampling improved by GCNCMC but that it also results in increased sampling of ligand conformations in a protein binding site, revealing new water-mediated ligand-binding geometries that are not observed using alternative enhanced sampling techniques.

Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data

The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structures over the entire protein surface remains difficult. To compensate for this incompleteness, we developed a three-dimensional convolutional neural network to predict the probability distribution of hydration water molecules on the hydrophilic and hydrophobic surfaces, and in the cavities of proteins. The neural network was optimized using the distribution patterns of protein atoms around the hydration water molecules identified in the high-resolution X-ray crystal structures. We examined the feasibility of the neural network using water sites in the protein crystal structures that were not included in the datasets. The predicted distribution covered most of the experimentally identified hydration sites, with local maxima appearing in their vicinity. This computational approach will help to highlight the relevance of hydration structures to the biological functions and dynamics of proteins.

Uncovering water effects in protein-ligand recognition: importance in the second hydration shell and binding kinetics

Developing a ligand with high affinity for a specific protein target is essential for drug design, and water molecules are well known to play a key role in protein-drug recognition. However, predicting the role of particularly ordered water molecules in drug binding remains challenging. Furthermore, hydration free energy contributed from the water network, including the second shell of water molecules, is far from being well studied. In this research we focused on these aspects to accurately and efficiently evaluate water effects in protein-ligand binding affinity. We developed a new strategy using a free-energy calculation method, VM2. We successfully predicted the stable ordered water molecules in a number of protein systems: PDE 10a, HSP90, tryptophan synthase (TRPS), CDK2 and Factor Xa. In some of these, the second shell of water molecules appeared to be critical in protein-ligand binding. We also applied the strategy to largely improve binding free energy calculation using the MM/PBSA method. When applying MM/PBSA alone for two systems, CDK2 and Factor Xa, the computed binding free energy resulted in poor to moderate R² values with experimental data. However, including water free energy correction greatly improved the free energy calculation. Furthermore, our work helped to explain how xk263 is a 1000 times faster binder to HIVp than ritonavir, a potentially useful tool for investigating binding kinetics. Our studies reveal the importance of fully considering water effects in therapeutic developments in pharmaceutical and biotechnology industries and for fundamental research in protein-ligand recognition.

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.

Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data

This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.

Absolute Binding Free Energy Calculations for Buried Water Molecules

Water often plays a key role in mediating protein-ligand interactions. Understanding contributions from active-site water molecules to binding thermodynamics of a ligand is important in predicting binding free energies for ligand optimization. In this work, we tested a non-equilibrium switching method for absolute binding free energy calculations on water molecules in binding sites of 13 systems. We discuss the lessons we learned about identified issues that affected our calculations and ways to address them. This work fits with our larger focus on how to do accurate ligand binding free energy calculations when water rearrangements are very slow, such as rearrangements due to ligand modification (as in relative free energy calculations) or ligand binding (as in absolute free energy calculations). The method studied in this work can potentially be used to account for limited water sampling via providing endpoint corrections to free energy calculations using our calculated binding free energy of water.

The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS

The Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.

Enhancing sampling of water rehydration upon ligand binding using variants of grand canonical Monte Carlo

Water plays an important role in mediating protein-ligand interactions. Water rearrangement upon a ligand binding or modification can be very slow and beyond typical timescales used in molecular dynamics (MD) simulations. Thus, inadequate sampling of slow water motions in MD simulations often impairs the accuracy of the accuracy of ligand binding free energy calculations. Previous studies suggest grand canonical Monte Carlo (GCMC) outperforms normal MD simulations for water sampling, thus GCMC has been applied to help improve the accuracy of ligand binding free energy calculations. However, in prior work we observed protein and/or ligand motions impaired how well GCMC performs at water rehydration, suggesting more work is needed to improve this method to handle water sampling. In this work, we applied GCMC in 21 protein-ligand systems to assess the performance of GCMC for rehydrating buried water sites. While our results show that GCMC can rapidly rehydrate all selected water sites for most systems, it fails in five systems. In most failed systems, we observe protein/ligand motions, which occur in the absence of water, combine to close water sites and block instantaneous GCMC water insertion moves. For these five failed systems, we both extended our GCMC simulations and tested a new technique named grand canonical nonequilibrium candidate Monte Carlo (GCNCMC). GCNCMC combines GCMC with the nonequilibrium candidate Monte Carlo (NCMC) sampling technique to improve the probability of a successful water insertion/deletion. Our results show that GCNCMC and extended GCMC can rehydrate all target water sites for three of the five problematic systems and GCNCMC is more efficient than GCMC in two out of the three systems. In one system, only GCNCMC can rehydrate all target water sites, while GCMC fails. Both GCNCMC and GCMC fail in one system. This work suggests this new GCNCMC method is promising for water rehydration especially when protein/ligand motions may block water insertion/removal.

Water: new aspect of hydrogen bonding in the solid state

All water-water contacts in the crystal structures from the Cambridge Structural Database with d _OO ≤ 4.0 Å have been found. These contacts were analysed on the basis of their geometries and interaction energies from CCSD(T)/CBS calculations. The results show 6729 attractive water-water contacts, of which 4717 are classical hydrogen bonds (d _OH ≤ 3.0 Å and α ≥ 120°) with most being stronger than -3.3 kcal mol^-1. Beyond the region of these hydrogen bonds, there is a large number of attractive interactions (2062). The majority are antiparallel dipolar interactions, where the O-H bonds of two water molecules lying in parallel planes are oriented antiparallel to each other. Developing geometric criteria for these antiparallel dipoles (β₁, β₂ ≥ 160°, 80 ≤ α ≤ 140° and T _HOHO > 40°) yielded 1282 attractive contacts. The interaction energies of these antiparallel oriented water molecules are up to -4.7 kcal mol^-1, while most of the contacts have interaction energies in the range -0.9 to -2.1 kcal mol^-1. This study suggests that the geometric criteria for defining attractive water-water interactions should be broader than the classical hydrogen-bonding criteria, a change that may reveal undiscovered and unappreciated interactions controlling molecular structure and chemistry.

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and x-ray diffraction at room temperature

The nonstructural protein 3 (NSP3) macrodomain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Mac1) removes adenosine diphosphate (ADP) ribosylation posttranslational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the coronavirus disease 2019 pandemic. Here, we determined neutron and x-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase the potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a reevaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

Spatially Resolved Hydration Thermodynamics in Biomolecular Systems

Water is essential for the structure, dynamics, energetics, and thus the function of biomolecules. It is a formidable challenge to elicit, in microscopic detail, the role of the solvation-related driving forces of biomolecular processes, such as the enthalpy and entropy contributions to the underlying free-energy landscape. In this Perspective, we discuss recent developments and applications of computational methods that provide a spatially resolved map of hydration thermodynamics in biomolecular systems and thus yield atomic-level insights to guide the interpretation of experimental observations. An emphasis is on the challenge of quantifying the hydration entropy, which requires characterization of both the motions of the biomolecules and of the water molecules in their surrounding.

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and X-ray diffraction at room temperature

The NSP3 macrodomain of SARS CoV 2 (Mac1) removes ADP-ribosylation post-translational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the COVID-19 pandemic. Here, we determined neutron and X-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site, and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a re-evaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

Structure-affinity relationships of reversible proline analog inhibitors targeting proline dehydrogenase

Proline dehydrogenase (PRODH) catalyzes the first step of proline catabolism, the FAD-dependent oxidation of L-proline to Δ¹-pyrroline-5-carboxylate. PRODH plays a central role in the metabolic rewiring of cancer cells, which has motivated the discovery of inhibitors. Here, we studied the inhibition of PRODH by 18 proline-like compounds to understand the structural and chemical features responsible for the affinity of the best-known inhibitor, S-(-)-tetrahydro-2-furoic acid (1). The compounds were screened, and then six were selected for more thorough kinetic analysis: cyclobutane-1,1-dicarboxylic acid (2), cyclobutanecarboxylic acid (3), cyclopropanecarboxylic acid (4), cyclopentanecarboxylic acid (16), 2-oxobutyric acid (17), and (2S)-oxetane-2-carboxylic acid (18). These compounds are competitive inhibitors with inhibition constants in the range of 1.4-6 mM, compared to 0.3 mM for 1. Crystal structures of PRODH complexed with 2, 3, 4, and 18 were determined. All four inhibitors bind in the proline substrate site, but the orientations of their rings differ from that of 1. The binding of 3 and 18 is accompanied by compression of the active site to enable nonpolar contacts with Leu513. Compound 2 is unique in that the additional carboxylate displaces a structurally conserved water molecule from the active site. Compound 18 also destabilizes the conserved water, but by an unexpected non-steric mechanism. The results are interpreted using a chemical double mutant thermodynamic cycle. This analysis revealed unanticipated synergism between ring size and hydrogen bonding to the conserved water. These structure-affinity relationships provide new information relevant to the development of new inhibitor design strategies targeting PRODH.

Structured Waters Mediate Small Molecule Binding to G-Quadruplex Nucleic Acids

The role of G-quadruplexes in human cancers is increasingly well-defined. Accordingly, G-quadruplexes can be suitable drug targets and many small molecules have been identified to date as G-quadruplex binders, some using computer-based design methods and co-crystal structures. The role of bound water molecules in the crystal structures of G-quadruplex-small molecule complexes has been analyzed in this study, focusing on the water arrangements in several G-quadruplex ligand complexes. One is the complex between the tetrasubstituted naphthalene diimide compound MM41 and a human intramolecular telomeric DNA G-quadruplex, and the others are in substituted acridine bimolecular G-quadruplex complexes. Bridging water molecules form most of the hydrogen-bond contacts between ligands and DNA in the parallel G-quadruplex structures examined here. Clusters of structured water molecules play essential roles in mediating between ligand side chain groups/chromophore core and G-quadruplex. These clusters tend to be conserved between complex and native G-quadruplex structures, suggesting that they more generally serve as platforms for ligand binding, and should be taken into account in docking and in silico studies.

Biotin's Lessons in Drug Design

At the heart of drug design is the discovery of molecules that bind with high affinity to their drug targets. Biotin forms the strongest known noncovalent ligand-protein interactions with avidin and streptavidin, achieving femtomolar and picomolar affinities, respectively. This is made even more exceptional because biotin achieves this with a meagre molecular weight of 240 Da. Surprisingly, the approaches by which biotin achieves this are not in the standard repertoire of current medicinal chemistry practice. Biotin's biggest lesson is the importance of nonclassical H-bonds in protein-ligand complexes. Most of biotin's affinity stems from its flexible valeric acid side chain that forms CH-π, CH-O, and classical H-bonds with the lipophilic region of the binding pocket. Biotin also utilizes an oxyanion hole, a sulfur-centered H-bond, and water solvation in the bound state to achieve its potency. The facets and advantages of biotin's approach to binding should be more widely adopted in drug design.