Intriguing role of water in protein-ligand binding studied by neutron crystallography on trypsin complexes

Databases of ligand-binding pockets and protein-ligand interactions

Many research groups and institutions have created a variety of databases curating experimental and predicted data related to protein-ligand binding. The landscape of available databases is dynamic, with new databases emerging and established databases becoming defunct. Here, we review the current state of databases that contain binding pockets and protein-ligand binding interactions. We have compiled a list of such databases, fifty-three of which are currently available for use. We discuss variation in how binding pockets are defined and summarize pocket-finding methods. We organize the fifty-three databases into subgroups based on goals and contents, and describe standard use cases. We also illustrate that pockets within the same protein are characterized differently across different databases. Finally, we assess critical issues of sustainability, accessibility and redundancy.

Aldose reductase inhibitory and antiglycation properties of phytoconstituents of Cichorium intybus: Potential therapeutic role in diabetic retinopathy

Diabetic vascular complication including diabetic retinopathy is a major morbidity in Saudia Arabia. The polyol pathway aka aldose reductase (AR) pathway has gained significant association with diabetic retinopathy with regard to chronically enhanced glucose metabolism. Considerable research has been put forth to develop more effective therapeutic strategies to overcome the overwhelming challenges of vascular complications associated with diabetes. In this regard, constituents of Cichorium intybus can offer strong AR inhibitory potential because of their strong antidiabetic properties. Therefore, aim of this study was to investigate the AR inhibitory as well as antiglycation potential of C. intybus extract/compounds. The preliminary in vitro results showed that methanolic extract of C. intybus could significantly inhibit AR enzyme and advanced glycation end product formation. Eventually, based on previous studies and reviews, we selected one hundred fifteen C. intybus root constituents and screened them through Lipinski's rule of five and ADMET analysis. Later, after molecular docking analysis of eight compounds, five best were selected for molecular dynamics simulation to deduce their binding affinity with the AR enzyme. Finally, three out of five compounds were further tested in vitro for their AR inhibitory potential and antiglycation properties. Enzyme assay and kinetic studies showed that all the three tested compounds were having potent AR inhibitory properties, although to a lesser extent than ellagic acid and tolrestat. Similarly, kaempferol showed strong antiglycation property equivalent to ellagic acid, but greater than aminoguanidine. Intriguingly, significant reduction in sorbitol accumulation in RBCs by the tested compounds substantiated strong AR inhibition by these compounds. Moreover, decrease in sorbitol accumulation under high glucose environment also signifies the potential application of these compounds in diabetic retinopathy and other vascular complications. Thus, in sum, the in silico and in vitro studies combinedly showed that C. intybus root is a treasure for therapeutic compounds and can be explored further for drug development against diabetic retinopathy.

Targeting Monkeypox Virus Methyltransferase: Virtual Screening of Natural Compounds from Middle-Eastern Medicinal Plants

Monkeypox is an infectious disease resulting from the monkeypox virus, and its fatality rate varies depending on the virus clade and the location of the outbreak. In monkeypox virus, methyltransferase (MTase) plays a crucial role in modifying the cap structure of viral mRNA. This alteration assists the virus in evading the host's immune system, enhances viral protein synthesis, and ultimately enables successful infection and replication within host cells. Given the significance of MTase in viral infection and spread within the host, our study aimed to identify a natural inhibitor for this enzyme using docking and molecular dynamic (MD) simulations. We collected a total of 12,971 natural compounds from 200 medicinal plants in the Middle East. After eliminating duplicate compounds, we had 5,749 unique ligand conformers, which we then subjected to high-throughput virtual screening against MTase. The most promising hits were further evaluated using the extra-precision (XP) tool. The affinity of these hits was also assessed by Prime-Molecular Mechanics/Generalized Born Surface Area (MMGBSA) tool. The analysis revealed that two standard controls (sinefungin and TO1119) and two Middle-Eastern compounds (folic acid and 1,2,4,6-tetragalloylglucose) exhibited the best XP docking scores. According to Prime MMGBSA calculations, the Middle-Eastern compounds showed higher affinities, with values of - 60.61 kcal/mol for 1,2,4,6-tetragalloylglucose and - 51.87 kcal/mol for folic acid, surpassing the controls (TO1119 at - 35.71 kcal/mol and sinefungin at - 31.51 kcal/mol). In the majority of Molecular dynamic (MD) simulations, folic acid exhibited demonstrated greater stability than sinefungin. Further investigation revealed that folic acid occupied a critical position in the active site of MTase, which reduced its interaction with the mRNA substrate. Based on these findings, it can be concluded that folic acid is a highly promising natural compound for potential use in the cost-effective treatment of monkeypox virus. The identification of folic acid as a potential antiviral agent highlights the importance of nature in providing new therapeutic uses that have significant implications for global health, particularly in regions where monkeypox viral outbreaks are prevalent. However, it is essential to note that further wet-lab validations are necessary to confirm its efficacy for treatment in a medical context.

Multi-combined QSAR, molecular docking, molecular dynamics simulation, and ADMET of Flavonoid derivatives as potent cholinesterase inhibitors

In searching for a new and efficient therapeutic agent against Alzheimer's disease, a Quantitative structure-activity relationship (QSAR) was derived for 45 Flavonoid derivatives recently synthesized and evaluated as cholinesterase inhibitors. The multiple linear regression method (MLR) was adopted to develop an adequate mathematical model that describes the relationship between a variety of molecular descriptors of the studied compounds and their biological activities (cholinesterase inhibitors). Golbraikh and Tropsha criteria were applied to verify the validity of the built model. The built MLR model was statistically reliable, robust, and predictive (R2 = 0.801, Q2cv = 0.876, R2test = 0.824). Dreiding energy and Molar Refractivity were the major factors that govern the Anti-cholinesterase activity. These results were further exploited to design a new series of Flavonoid derivatives with higher Anti-cholinesterase activities than the existing ones. Thereafter, molecular docking and molecular dynamic studies were performed to predict the binding types of the designed compounds and to investigate their stability at the active site of the Butyrylcholinestérase BuChE protein. The negative and low binding affinity calculated for all designed compounds shows that designed compound 1 has a favorable affinity for the 4TPK. Moreover, molecular dynamics simulation studies confirmed the stability of designed compound 1 in the active pocket of 4TPK over 100 ns. Finally, the ADMET analysis was incorporated to analyze the pharmacokinetics and toxicity parameters. The designed compounds were found to meet the ADMET descriptor criteria at an acceptable level having respectable intestinal permeability and water solubility and can reach the intended destinations.Communicated by Ramaswamy H. Sarma.

Do All Paths Lead to Rome? How Reliable is Umbrella Sampling Along a Single Path?

Molecular dynamics (MD) simulations are widely applied to estimate absolute binding free energies of protein-ligand and protein-protein complexes. A routinely used method for binding free energy calculations with MD is umbrella sampling (US), which calculates the potential of mean force (PMF) along a single reaction coordinate. Surprisingly, in spite of its widespread use, few validation studies have focused on the convergence of the free energy computed along a single path for specific cases, not addressing the reproducibility of such calculations in general. In this work, we therefore investigate the reproducibility and convergence of US along a standard distance-based reaction coordinate for various protein-protein and protein-ligand complexes, following commonly used guidelines for the setup. We show that repeating the complete US workflow can lead to differences of 2-20 kcal/mol in computed binding free energies. We attribute those discrepancies to small differences in the binding pathways. While these differences are unavoidable in the established US protocol, the popularity of the latter could hint at a lack of awareness of such reproducibility problems. To test if the convergence of PMF profiles can be improved if multiple pathways are sampled simultaneously, we performed additional simulations with an adaptive-biasing method, here the accelerated weight histogram (AWH) approach. Indeed, the PMFs obtained from AHW simulations are consistent and reproducible for the systems tested. To the best of our knowledge, our work is the first to attempt a systematic assessment of the pitfalls in one the most widely used protocols for computing binding affinities. We anticipate therefore that our results will provide an incentive for a critical reassessment of the validity of PMFs computed with US, and make a strong case to further benchmark the performance of adaptive-biasing methods for computing binding affinities.

Insights into the terahertz response of L-glutamic acid and its receptor

L-Glutamic acid (L-Glu) is a basic unit of proteins and also serves as an important neurotransmitter in the central nervous system. Its structural properties are critical for biological functions and selective receptor recognition. Although this molecule has been extensively studied, the low frequency vibrational behavior that is closely related to conformational changes and the intermolecular interactions between L-Glu and its receptors are still unclear. In this study, we acquired the fingerprint spectrum of L-Glu by using air plasma terahertz (THz) time-domain spectroscopy in the 0.5-18 THz range. The low frequency vibrational characteristics of L-Glu were investigated through density functional theory (DFT) calculations. The THz responses of the ligand binding domain of the NMDAR-L-Glu complex were studied by the ONIOM method, with a focus on discussing the normal modes and interactions of ligand L-Glu and water molecules. The results illustrate that THz spectroscopy exhibits a sensitive response to the influence of L-Glu on the structure of the NMDAR. The water molecules in proteins have various strong vibration modes in the THz band, showing specificity, diversity and complexity of vibrational behavior. There is potential for influencing and regulating the structural stability of the NMDAR-L-Glu complex through water molecules.

Dynamics of receptor activation by agonists

How do agonists turn on receptors? The model system we have used to address this question is the adult-type skeletal muscle nicotinic acetylcholine receptor. This ligand-gated ion channel has two orthosteric sites (for neurotransmitters) in the extracellular domain linked to an allosteric site (a gate) in the transmembrane domain. The goal of this perspective is to summarize how measurements of agonist binding energy reveal the dynamics of the neurotransmitter sites and the fundamental link between binding and gating.

Adaptive Response to Solvation in Flexible Molecules: Oligo Hydrates of 4-Hydroxy-2-butanone

Structural changes induced by water play a pivotal role in chemistry and biology but remain challenging to predict, measure, and control at molecular level. Here we explore size-governed gas-phase water aggregation in the flexible molecule 4-hydroxy-2-butanone, modeling the conformational adaptability of flexible substrates to host water scaffolds and the preference for sequential droplet growth. The experiment was conducted using broadband rotational spectroscopy, rationalized with quantum chemical calculations. Two different isomers were observed experimentally from the di- to the pentahydrates (4-hydroxy-2-butanone-(H2O)n=2-5), including the 18O isotopologues for the di- and trihydrates. Interestingly, to accommodate water molecules effectively, the heavy atom skeleton of 4-hydroxy-2-butanone reshapes in every observed isomer and does not correspond to the stable conformer of the free monomer. All solvates initiate from the alcohol group (proton donor) but retain the carbonyl group as secondary binding point. The water scaffolds closely resemble those found in the pure water clusters, balancing between the capability of 4-hydroxy-2-butanone for steering the orientation and position of the water molecules and the ability of water to modulate the monomer's conformation. The present work thus provides an accurate molecular description on how torsionally flexible molecules dynamically adapt to water along progressing solvation.

Binding Affinity Determination in Drug Design: Insights from Lock and Key, Induced Fit, Conformational Selection, and Inhibitor Trapping Models

Binding affinity is a fundamental parameter in drug design, describing the strength of the interaction between a molecule and its target protein. Accurately predicting binding affinity is crucial for the rapid development of novel therapeutics, the prioritization of promising candidates, and the optimization of their properties through rational design strategies. Binding affinity is determined by the mechanism of recognition between proteins and ligands. Various models, including the lock and key, induced fit, and conformational selection, have been proposed to explain this recognition process. However, current computational strategies to predict binding affinity, which are based on these models, have yet to produce satisfactory results. This article explores the connection between binding affinity and these protein-ligand interaction models, highlighting that they offer an incomplete picture of the mechanism governing binding affinity. Specifically, current models primarily center on the binding of the ligand and do not address its dissociation. In this context, the concept of ligand trapping is introduced, which models the mechanisms of dissociation. When combined with the current models, this concept can provide a unified theoretical framework that may allow for the accurate determination of the ligands' binding affinity.

In vitro and silico studies of geraniin interfering with HSV-2 replication by targeting glycoprotein D

Residues ASN94 and GLN41 presented the highest frequency in molecular docking tests. The geraniin-glycoprotein D(gD) complexes was stable with RMSD(root mean square deviation)value less than 0.3 nm. The Molecular dynamic (MD) simulations revealed stable hydrogen bonds between gD and geraniin. Root mean square fluctuation (RMSF) values were less than 0.15 nm around the interface of geraniin-gD complex. In virucidal assays showed a much higher anti-HSV-2 inhibition activity of geraniin as compared to acyclovir(ACV).Human immunodeficiency virus transactivator (HIV-TAT) treatment significantly enhanced HSV-2 replication and lethal effect on HaCaT cells. The inhibitory rate of geraniin against HSV-2 coinfected with HIV-TAT was significantly decreased. The immunofluorescence results also revealed that HSV-2 gD expression presented a green fluorescence on HaCaT cells membranes and showed clear downregulation in geraniin-treated cells, but was expressed clearly on cell membranes under geraniin, HSV-2 and HIV-TAT cotreatment. The anti-apoptotic effect from geraniin persisted after 72 h, while the anti-apoptotic effect from geraniin diminished when HIV-TAT and geraniin were combined.

1H/17O Chemical Shift Waves in Carboxyl-Bridged Hydrogen Bond Networks in Organic Solids

We report solid-state 1H and 17O NMR results for four 17O-labeled organic compounds each containing an extensive carboxyl-bridged hydrogen bond (CBHB) network in the crystal lattice: tetrabutylammonium hydrogen di-[17O2]salicylate (1), [17O4]quinolinic acid (2), [17O4]dinicotinic acid (3), and [17O2]Gly/[17O2]Gly·HCl cocrystal (4). The 1H isotropic chemical shifts found for protons involved in different CBHB networks are between 8.2 and 20.5 ppm, which reflect very different hydrogen-bonding environments. Similarly, the 17O isotropic chemical shifts found for the carboxylate oxygen atoms in CBHB networks, spanning a large range between 166 and 341 ppm, are also remarkably sensitive to the hydrogen-bonding environments. We introduced a simple graphical representation in which 1H and 17O chemical shifts are displayed along the H and O atomic chains that form the CBHB network. In such a depiction, because wavy patterns are often observed, we refer to these wavy patterns as 1H/17O chemical shift waves. Typical patterns of 1H/17O chemical shift waves in CBHB networks are discussed. The reported 1H and 17O NMR parameters for the CBHB network models examined in this study can serve as benchmarks to aid in spectral interpretation for CBHB networks in proteins.

An Ensemble Classifiers for Improved Prediction of Native-Non-Native Protein-Protein Interaction

In this study, we present an innovative approach to improve the prediction of protein-protein interactions (PPIs) through the utilization of an ensemble classifier, specifically focusing on distinguishing between native and non-native interactions. Leveraging the strengths of various base models, including random forest, gradient boosting, extreme gradient boosting, and light gradient boosting, our ensemble classifier integrates these diverse predictions using a logistic regression meta-classifier. Our model was evaluated using a comprehensive dataset generated from molecular dynamics simulations. While the gains in AUC and other metrics might seem modest, they contribute to a model that is more robust, consistent, and adaptable. To assess the effectiveness of various approaches, we compared the performance of logistic regression to four baseline models. Our results indicate that logistic regression consistently underperforms across all evaluated metrics. This suggests that it may not be well-suited to capture the complex relationships within this dataset. Tree-based models, on the other hand, appear to be more effective for problems involving molecular dynamics simulations. Extreme gradient boosting (XGBoost) and light gradient boosting (LightGBM) are optimized for performance and speed, handling datasets effectively and incorporating regularizations to avoid over-fitting. Our findings indicate that the ensemble method enhances the predictive capability of PPIs, offering a promising tool for computational biology and drug discovery by accurately identifying potential interaction sites and facilitating the understanding of complex protein functions within biological systems.

Mycosporine-Like Amino Acids as a Potential Inhibitor of Tyrosinase-Related Protein 1: Computational Screening, Pharmacokinetics, and Molecular Dynamics Simulation

Melanin is the major pigment responsible for the coloring of mammalian skin, hair, and eyes to defend against ultraviolet radiation. However, excessive melanin production has resulted in numerous types of hyperpigmentation disorders. Tyrosinase-related protein 1 (TYRP1) is a transmembrane glycoprotein enzyme found in many organisms, including humans, that plays an important role in melanogenesis. Thus, controlling the enzyme activity of TYRP1 with tyrosinase inhibitors is a vital step in the treatment of hyperpigmentation problems in humans. In the present investigation, virtual screening, pharmacokinetics, drug docking, and molecular dynamics (MD) simulation were used to find the most potent drug as an inhibitor of TYRP1 to effectively treat hyperpigmentation disorder. The 3D structure of TYRP1 was retrieved from the Protein Data Bank (PDB) database (PDB ID: 5M8M) and validated by the Ramachandran plot. Pharmacokinetics and drug-likeness showed that mycosporine 2 glycine (M2G) and shinorine (SHI) were the best compounds over other ligands in the same (P-1) structural pose. However, MD simulations of the M2G showed the highest CDOCKER interaction energy (-45.182 kcal/mol) and binding affinity (-65.0529 kcal/mol) as compared to SHI and reference drugs. The molecular binding modes RMSD and RMSF plots have exhibited more relevance to the M2G ligand in comparison to other drug ligands. The bioactivity and ligand efficiency profiles revealed that M2G is the most effective compound as a TYRP1 inhibitor. Thus, M2G could be used as a most effective drug for developing valuable sunscreen products to cure hyperpigmentation-related diseases.

HydraProt: A New Deep Learning Tool for Fast and Accurate Prediction of Water Molecule Positions for Protein Structures

Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibrant research area. In this paper, we introduce HydraProt (deep Hydration of Proteins), a novel methodology for predicting precise positions of water molecule oxygen atoms around protein structures, leveraging two interconnected deep learning architectures: a 3D U-net and a Multi-Layer Perceptron (MLP). Our approach starts by introducing a coarse voxel-based representation of the protein, which allows for rapid sampling of candidate water positions via the 3D U-net. These water positions are then assessed by embedding the water-protein relationship in the Euclidean space by means of an MLP. Finally, a postprocessing step is applied to further refine the MLP predictions. HydraProt surpasses existing state-of-the-art approaches in terms of precision and recall and has been validated on large data sets of protein structures. Notably, our method offers rapid inference runtime and should constitute the method of choice for protein structure studies and drug discovery applications. Our pretrained models, data, and the source code required to reproduce these results are accessible at https://github.com/azamanos/HydraProt.

Elucidating the binding mechanisms of GABA and Muscimol as an avenue to discover novel GABA-mimetic small molecules

Gamma-aminobutyric acid (GABA) signaling is the principal inhibitory pathway in the central nervous system. It is critical in neuronal cell proliferation and fate determination. Any aberration in GABA inhibition results in psychiatric and neurological diseases. Thus, modulating GABAergic neurotransmission has become the basis of drug therapy for psychiatric and several neurological diseases. Though GABA and muscimol are classical inhibitors of GABA receptors, the search for novel inhibitors continues unabated. In this study, the binding mechanism of GABA and muscimol was elucidated and applied in the search for small molecule GABAergic inhibitors using comprehensive computational techniques. It was revealed that a high-affinity binding of GABA and muscimol was mediated by a water molecule involving α1Thr129 and then stabilized by strong interactions including salt bridges with β2Glu155 and α1Arg66 amidst hydrogen bonds, π-π stacking, and π -cation interactions with other residues. The binding of GABA and muscimol was also characterized by stability and deeper penetration into the hydrophobic core of the protein which resulted in conformational changes of the binding pocket and domain, by inducing correlated motions of the residues. Thermodynamics analysis showed GABA and muscimol exhibited total binding free energies of -19.85 ± 8.83 Kcal/mol and -26.55 ± 3.42 Kcal/mol, respectively. A pharmacophore model search, based on the energy contributions of implicating binding residues, resulted in the identification of ZINC68604167, ZINC19735138, ZINC04202466, ZINC00901626, and ZINC01532854 as potential GABA-mimetic compounds from metabolites and natural products libraries. This study has elucidated the binding mechanisms of GABA and muscimol and successfully applied in the identification of GABA-mimetic compounds.Communicated by Ramaswamy H. Sarma.

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.

In silico modeling revealed phytomolecules derived from Cymbopogon citratus (DC.) leaf extract as promising candidates for malaria therapy

The emergence of varying levels of resistance to currently available antimalarial drugs significantly threatens global health. This factor heightens the urgency to explore bioactive compounds from natural products with a view to discovering and developing newer antimalarial drugs with novel mode of actions. Therefore, we evaluated the inhibitory effects of sixteen phytocompounds from Cymbopogon citratus leaf extract against Plasmodium falciparum drug targets such as P. falciparum circumsporozoite protein (PfCSP), P. falciparum merozoite surface protein 1 (PfMSP1) and P. falciparum erythrocyte membrane protein 1 (PfEMP1). In silico approaches including molecular docking, pharmacophore modeling and 3D-QSAR were adopted to analyze the inhibitory activity of the compounds under consideration. The molecular docking results indicated that a compound swertiajaponin from C. citratus exhibited a higher binding affinity (-7.8 kcal/mol) to PfMSP1 as against the standard artesunate-amodiaquine (-6.6 kcal/mol). Swertiajaponin also formed strong hydrogen bond interactions with LYS29, CYS30, TYR34, ASN52, GLY55 and CYS28 amino acid residues. In addition, quercetin another compound from C. citratus exhibited significant binding energies -6.8 and -8.3 kcal/mol with PfCSP and PfEMP1, respectively but slightly lower than the standard artemether-lumefantrine with binding energies of -7.4 kcal/mol against PfCSP and -8.7 kcal/mol against PfEMP1. Overall, the present study provides evidence that swertiajaponin and other phytomolecules from C. citratus have modulatory properties toward P. falciparum drug targets and thus may warrant further exploration in early drug discovery efforts against malaria. Furthermore, these findings lend credence to the folkloric use of C. citratus for malaria treatment.Communicated by Ramaswamy H. Sarma.

Molecular interactions of antibodies with PD-1/PD-L1 proteins

Aim: To compare the protein-protein interactions of antibodies targeting PD-1 and its ligand (PD-L1) with their targets in an attempt to explain the antibodies' binding affinity. Materials & methods: The structural features of complexes between pembrolizumab, nivolumab, durvalumab, atezolizumab, avelumab and PD-1/PD-L1 are described, with the use of software and based on crystallographic data. Results: Pembrolizumab has more structural features, including the number and type of the bonds and total binding surface area, which could rationalize its different clinical behavior compared with nivolumab. Similarly, protein-protein interactions with PD-L1 differ among durvalumab, atezolizumab and avelumab. Conclusion: Differential protein-protein interactions between antibodies and PD-1/PD-L1 may indicate differential clinical activity; however, further research is needed to provide evidence.

Water network chemistry to exploit the nature of catalytic water molecules in Mtb DNA gyrase: a computational study to understand the binding mechanism of fluoroquinolones

The dynamics of DNA gyrase and mutants of DNA gyrA such as G88A, A90V, S91P, D94A, D94G, D94N, D94Y; and double-point mutant (S91P-D94G), are meticulously investigated using computational approaches. Molecular dynamics (MD) and hydration thermodynamics have shed light on the fundamental, mechanistic basis of mutations on the conformational stability of Quinolone Binding Pocket (QBP) of DNA gyrase. Analysis of MD results revealed the displacement of a single crystal water molecule (HOH201) from the catalytic site of wild-type (WT) and mutants of DNA gyrA. This prompted our research group to probe the five crystal water molecules present in the QBP of the enzyme using water thermodynamics. Hydration thermodynamics analysis revealed the displacement of HOH201 due to unstable thermodynamic signatures. Further, the analysis highlighted significant changes in thermodynamic signatures and locations of five crystal water hydration sites upon mutation. Integrated MD simulations and water thermodynamics provided promising insights into the conformational changes and inaccessibility of the catalytic water molecule that can influence the design of DNA gyrase inhibitors.Communicated by Ramaswamy H. Sarma.

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.

Annonaceous acetogenins as promising DNA methylation inhibitors to prevent and treat leukemogenesis - an in silico approach

Leukemia is a haematological malignancy affecting blood and bone marrow, ranking 10th among the other common cancers. DNA methylation is an epigenetic dysregulation that plays a critical role in leukemogenesis. DNA methyltransferases (DNMTs) such as DNMT1, DNMT3A and DNMT3B are the key enzymes catalysing DNA methylation. Inhibition of DNMT1 with secondary metabolites from medicinal plants helps reverse DNA methylation. The present study focuses on inhibiting DNMT1 protein (PDB ID: 3PTA) with annonaceous acetogenins through in-silico studies. The docking and molecular dynamic (MD) simulation study was carried out using Schrödinger Maestro and Desmond, respectively. These compounds' drug likeliness, ADMET properties and bioactivity scores were analysed. About 76 different acetogenins were chosen for this study, among which 17 showed the highest binding energy in the range of -8.312 to -10.266 kcal/mol. The compounds with the highest negative binding energy were found to be annohexocin (-10.266 kcal/mol), isoannonacinone (-10.209 kcal/mol) and annonacin (-9.839 kcal/mol). MD simulation results reveal that annonacin remains stable throughout the simulation time of 100 ns and also binds to the catalytic domain of DNMT1 protein. From the above results, it can be concluded that annonacin has the potential to inhibit the DNA methylation process and prevent leukemogenesis.Communicated by Ramaswamy H. Sarma.

Elucidation of the structural basis for ligand binding and translocation in conserved insect odorant receptor co-receptors

In numerous insects, the olfactory receptor family forms a unique class of heteromeric cation channels. Recent progress in resolving the odorant receptor structures offers unprecedented opportunities for deciphering their molecular mechanisms of ligand recognition. Unexpectedly, these structures in apo or ligand-bound states did not reveal the pathway taken by the ligands between the extracellular space and the deep internal cavities. By combining molecular modeling with electrophysiological recordings, we identified amino acids involved in the dynamic entry pathway and the binding of VUAA1 to Drosophila melanogaster's odorant receptor co-receptor (Orco). Our results provide evidence for the exact location of the agonist binding site and a detailed and original mechanism of ligand translocation controlled by a network of conserved residues. These findings would explain the particularly high selectivity of Orcos for their ligands.

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.

Modern Alchemical Free Energy Methods for Drug Discovery Explained

This Perspective provides a contextual explanation of the current state-of-the-art alchemical free energy methods and their role in drug discovery as well as highlights select emerging technologies. The narrative attempts to answer basic questions about what goes on "under the hood" in free energy simulations and provide general guidelines for how to run simulations and analyze the results. It is the hope that this work will provide a valuable introduction to students and scientists in the field.

The temperature-dependence of host-guest binding thermodynamics: experimental and simulation studies

The thermodynamic parameters of host-guest binding can be used to describe, understand, and predict molecular recognition events in aqueous systems. However, interpreting binding thermodynamics remains challenging, even for these relatively simple molecules, as they are determined by both direct and solvent-mediated host-guest interactions. In this contribution, we focus on the contributions of water to binding by studying binding thermodynamics, both experimentally and computationally, for a series of nearly rigid, electrically neutral host-guest systems and report the temperature-dependent thermodynamic binding contributions ΔGb(T), ΔHb(T), ΔSb(T), and ΔCp,b. Combining isothermal titration calorimetry (ITC) measurements with molecular dynamics (MD) simulations, we provide insight into the binding forces at play for the macrocyclic hosts cucurbit[n]uril (CBn, n = 7-8) and β-cyclodextrin (β-CD) with a range of guest molecules. We find consistently negative changes in heat capacity on binding (ΔCp,b) for all systems studied herein - as well as for literature host-guest systems - indicating increased enthalpic driving forces for binding at higher temperatures. We ascribe these trends to solvation effects, as the solvent properties of water deteriorate as temperature rises. Unlike the entropic and enthalpic contributions to binding, with their differing signs and magnitudes for the classical and non-classical hydrophobic effect, heat capacity changes appear to be a unifying and more general feature of host-guest complex formation in water. This work has implications for understanding protein-ligand interactions and other complex systems in aqueous environments.

Free energy along drug-protein binding pathways interactively sampled in virtual reality

We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art 'human-in-the-loop' iMD-VR framework to generate a diverse range of protein-ligand unbinding pathways, benefitting from the sophistication of human spatial and chemical intuition. Stage two involves using the iMD-VR-sampled pathways as initial guesses for defining a path-based reaction coordinate from which we can obtain a corresponding free energy profile using FE methods. To investigate the performance of the method, we apply iMD-VR-FE to investigate the unbinding of a benzamidine ligand from a trypsin protein. The binding free energy calculated using iMD-VR-FE is similar for each pathway, indicating internal consistency. Moreover, the resulting free energy profiles can distinguish energetic differences between pathways corresponding to various protein-ligand conformations (e.g., helping to identify pathways that are more favourable) and enable identification of metastable states along the pathways. The two-step iMD-VR-FE approach offers an intuitive way for researchers to test hypotheses for candidate pathways in biomolecular systems, quickly obtaining both qualitative and quantitative insight.

Precursor template-induced egg white-derived peptides self-assembly for the enhancement of curcumin: Structure, environmental stability, and bioavailability

Natural multicomponent peptides with abundant bioactivity, varied sizes, and tunable interaction potential are available for rational designing novel self-assembled delivery carriers. Herein, we exploited zein-hyaluronic acid nanoparticles (Z-HA NPs) with a predetermined ordered structure as precursor templates to induce the self-assembly of egg white-derived peptides (EWDP) to generate stable spherical architectures for the enhancement of curcumin (Cur). The resulting Z-EWDP-HA NPs encapsulated hydrophobic Cur through robust hydrogen bonding and hydrophobic interactions with high encapsulation efficiency (97.38% at pH 7.0). The NPs presented superior Cur aqueous solubility, redispersibility, and photothermal stability. More importantly, the self-assembled EWDP could exert synergistic antioxidant activity with Cur and enhance the bioaccessibility of Cur. Meanwhile, the favorable biocompatibility and membrane affinity of EWDP further prolonged residence and time-controlled release feature of Cur in the small intestine. Precursor template-induced multicomponent peptides' self-assembly provides an efficient and controllable strategy for co-enhanced bioactivity and self-assembly capacity of peptides, which could dramatically broaden the functionalization of multicomponent peptides hydrolyzed from natural food proteins.

OneOPES, a Combined Enhanced Sampling Method to Rule Them All

Enhanced sampling techniques have revolutionized molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system's dynamics and recover the original system's statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multireplica simulations and CV-based enhanced sampling. This method efficiently accelerates the phase space sampling without the need for ideal CVs, extensive parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein-ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems.

Natural photosensitizers potentiate the targeted antimicrobial photodynamic therapy as the Monkeypox virus entry inhibitors: An in silico approach

BACKGROUND

Monkeypox is a viral zoonotic disease that has emerged as a threat to public health. Currently, there is no treatment approved specifically targeting Monkeypox disease. Hence, it is essential to identify and develop therapeutic approaches to the Monkeypox virus. In the current in silico paper, we comprehensively involve using computer simulations and modeling to insights and predict hypotheses on the potential of natural photosensitizers-mediated targeted antimicrobial photodynamic therapy (aPDT) against D8L as a Monkeypox virus protein involved in viral cell entry.

MATERIALS AND METHODS

In the current study, computational techniques such as molecular docking were combined with in silico ADMET predictions to examine how Curcumin (Cur), Quercetin (Qct), and Riboflavin (Rib) as the natural photosensitizers bind to the D8L protein in Monkeypox virus, as well as to determine pharmacokinetic properties of these photosensitizers.

RESULTS

The three-dimensional structure of the D8L protein in the Monkeypox virus was constructed using homology modeling (PDB ID: 4E9O). According to the physicochemical properties and functional characterization, 4E9O was a stable protein with the nature of a hydrophilic structure. The docking studies employing a three-dimensional model of 4E9O with natural photosensitizers exhibited good binding affinity. D8L protein illustrated the best docking score (-7.6 kcal/mol) in relation to the Rib and displayed good docking scores in relation to the Cur (-7.0 kcal/mol) and Qct (-7.5 kcal/mol).

CONCLUSIONS

The findings revealed that all three photosensitizers were found to obey the criteria of Lipinski's rule of five and displayed drug-likeness. Moreover, all the tested photosensitizers were found to be non-hepatotoxic and non-cytotoxic. In summary, our investigation identified Cur, Qct, and Rib could efficiently interact with D8L protein with a strong binding affinity. It can be concluded that aPDT using these natural photosensitizers may be considered an adjuvant treatment against Monkeypox disease.

Antimicrobial Activity and Molecular Docking Studies of the Biotransformation of Diterpene Acanthoic Acid Using the Fungus Xylaria sp

Biotransformations are reactions mediated by microorganisms, such as fungi. These bioreactions have high chemo- and stereoselectivity on organic substrates and can be applied in the search for new bioactive compounds. In this study, acanthoic acid (AA) was biotransformed using the fungus Xylaria sp., giving the novel compound 3β,7β-dihydroxyacanthoic acid (S1). Both the AA and the product S1 were tested against Gram-positive and Gram-negative bacteria. To identify and validate possible biological targets as enzymes or proteins involved in the activity observed in vitro, we used the molecular docking method. Hydroxylation at the C-3 and C-7 positions of the biotransformation product enhanced its activity against Escherichia coli as well as its binding affinity and interactions with superoxide dismutase 1 (SOD1; PDB ID 4A7G). Based on our results, the SOD1 enzyme was suggested to be a possible target for the antioxidant activity of product S1.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.

Triamcinolone Acetonide Produced by Bacillus velezensis YEBBR6 Exerts Antagonistic Activity Against Fusarium oxysporum f. sp. Cubense: A Computational Analysis

Fusarium oxysporum f. sp. cubense is one of the most severe and threatening pathogens of bananas, causing "Panama wilt" worldwide. Confrontation assay of Foc antagonistic bacterial endophyte, Bacillus velezensis YEBBR6, with the Foc and GC-MS profiling of excised agar from the zone of inhibition, led to the unveiling of secondary metabolites produced by the endophyte. To refine the probable antifungal compounds among the numerous biomolecules formed during their di-trophic interaction with the pathogen, fungal protein targets were modeled, and docking studies (AutoDock Vina module of the PyRx 0.8 server) were done with all the compounds. Triamcinolone acetonide exhibited the most excellent affinity for the protein targets among the compounds studied. It had a maximum binding affinity of 11.2 kcal/mol for XRN2 (5' → 3'). Further, the protein-ligand complex formation kinetics was done through Molecular Dynamic Simulation studies. Graphs for the RMSD, RMSF, Rg, potential energy, and SASA were generated, and the values during the simulation period suggested the stability of the biomolecule as a complex with the protein. This indicated Triamcinolone acetonide's potential ability to act as a functional disrupter of the target protein and likely an antifungal molecule. Further, the biomolecule was tested for its activity against Foc by screening in the wet lab through the poisoned plate technique, and it was found to be fully inhibitory to the growth of the pathogen at 1000 ppm.

Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor

Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.

Investigation of molecular details of a bacterial cationic amino acid transporter (GkApcT) during arginine transportation using molecular dynamics simulation and umbrella sampling techniques

CONTEXT

Cationic amino acid transporters (CATs) facilitate arginine transport across membranes and maintain its levels in various tissues and organs, but their overexpression has been associated with severe cancers. A recent study identified the alternating access mechanism and critical residues involved in arginine transportation in a cationic amino acid transporter from Geobacillus kaustophilus (GkApcT). Here, we used molecular dynamics (MD) simulation methods to investigate the transportation mechanism of arginine (Arg) through GkApcT. The results revealed that arginine strongly interacts with specific binding site residues (Thr43, Asp111, Glu115, Lys191, Phe231, Ile234, and Asp237). Based on the umbrella sampling, the main driving force for arginine transport is the polar interactions of the arginine with channel-lining residues. An in-depth description of the dissociation mechanism and binding energy analysis brings valuable insight into the interactions between arginine and transporter residues, facilitating the design of effective CAT inhibitors in cancer cells.

METHODS

The membrane-protein system was constructed by uploading the prokaryotic CAT (PDB ID: 6F34) to the CHARMM-GUI web server. Molecular dynamics simulations were done using the GROMACS package, version 5.1.4, with the CHARMM36 force field and TIP3P water model. The MM-PBSA approach was performed for determining the arginine binding free energy. Furthermore, the hotspot residues were identified through per-residue decomposition analysis. The characteristics of the channel such as bottleneck radius and channel length were analyzed using the CaverWeb 1.1 web server. The proton wire inside the transporter was investigated based on the classic Grotthuss mechanism. We also investigated the atomistic details of arginine transportation using the path-based free energy umbrella sampling technique (US).

Agonist efficiency links binding and gating in a nicotinic receptor

Receptors signal by switching between resting (C) and active (O) shapes ('gating') under the influence of agonists. The receptor's maximum response depends on the difference in agonist binding energy, O minus C. In nicotinic receptors, efficiency (η) represents the fraction of agonist binding energy applied to a local rearrangement (an induced fit) that initiates gating. In this receptor, free energy changes in gating and binding can be interchanged by the conversion factor η. Efficiencies estimated from concentration-response curves (23 agonists, 53 mutations) sort into five discrete classes (%): 0.56 (17), 0.51(32), 0.45(13), 0.41(26), and 0.31(12), implying that there are 5 C versus O binding site structural pairs. Within each class efficacy and affinity are corelated linearly, but multiple classes hide this relationship. η unites agonist binding with receptor gating and calibrates one link in a chain of coupled domain rearrangements that comprises the allosteric transition of the protein.

Cloning and characterization of Aedes aegypti blood downregulated chymotrypsin II

Aedes aegypti adult and larval blood downregulated chymotrypsin II was cloned, sequenced and its 3D conformation modeled. Cloning of the enzymes from adult and larval guts indicated that both genes sit at the same location on Chromosome 2. Genomic analyses showed that larval and adult genes are the same and both have four exons and three introns that are located on an 8.32 Kb DNA in direction with the Ae. aegypti genome. The adult and larval transcript synthesis is controlled by alternative splicing explaining small difference in the amino acids sequences. Chymotrypsin II that was extracted from guts of sugar-fed and at 48 after blood feeding showed a pH optimum of 4-5 with a broad shoulder of activity from pH 6 to 10. Dot blot analyses show that the enzyme's transcript is downregulated after females take a blood meal and upregulated at 48 h after the blood meal. A Chymotrypsin II transcript was also detected in the larval gut during different times of larval developmental stages, indication that Ae. aegypti chymotrypsin II is synthesized by adults and larval guts. The possibility that JH III and 20HE play an active role in the regulation is discussed.

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

Improving binding entropy by higher ligand symmetry? - A case study with human matriptase

Understanding different contributions to the binding entropy of ligands is of utmost interest to better predict affinity and the thermodynamic binding profiles of protein-ligand interactions and to develop new strategies for ligand optimization. To these means, the largely neglected effects of introducing higher ligand symmetry, thereby reducing the number of energetically distinguishable binding modes on binding entropy using the human matriptase as a model system, were investigated. A set of new trivalent phloroglucinol-based inhibitors that address the roughly symmetric binding site of the enzyme was designed, synthesized, and subjected to isothermal titration calorimetry. These highly symmetric ligands that can adopt multiple indistinguishable binding modes exhibited high entropy-driven affinity in line with affinity-change predictions.

In silico design of novel CDK2 inhibitors through QSAR, ADMET, molecular docking and molecular dynamics simulation studies

The present study aims to investigate about the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the DFT method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R2 = 0.725, R2adj = 0.653, MSE = 0.060, R2test = 0.827, Q2cv = 0.536). The energy EHOMO orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Further, new Thiazole derivatives have been designed and their activities and pharmacokinetic properties have been predicted using the validated QSAR model. The designed molecules were then assessed to molecular docking (MD), and molecular dynamic (MDs) simulation accompanied by the calculation of the binding affinity using MMPBSA script according to 100 ns a simulation trajectory, to study both their affinity and their stability towards CDK2 as a target protein for the cancer disease treatment. This research concluded with the identification of four new CDK2 inhibitors which are A1, A3, A5, and A6 showing good pharmacokinetic properties. The MDs results revealed that the newly designed compound A5 remained stable in the active center of the discovered CDK2 protein, indicating its potential as a novel inhibitor for the treatment of hepatocellular carcinoma. The current findings may eventually contribute to the development of robust CDK2 inhibitors in the future.Communicated by Ramaswamy H. Sarma.

Predicting Protein-Ligand Binding and Unbinding Kinetics with Biased MD Simulations and Coarse-Graining of Dynamics: Current State and Challenges

The prediction of drug-target binding and unbinding kinetics that occur on time scales between milliseconds and several hours is a prime challenge for biased molecular dynamics simulation approaches. This Perspective gives a concise summary of the theory and the current state-of-the-art of such predictions via biased simulations, of insights into the molecular mechanisms defining binding and unbinding kinetics as well as of the extraordinary challenges predictions of ligand kinetics pose in comparison to binding free energy predictions.

Probing a Hydrogen-π Interaction Involving a Trapped Water Molecule in the Solid State

The detection and characterization of trapped water molecules in chemical entities and biomacromolecules remains a challenging task for solid materials. We herein present proton-detected solid-state Nuclear Magnetic Resonance (NMR) experiments at 100 kHz magic-angle spinning and at high static magnetic-field strengths (28.2 T) enabling the detection of a single water molecule fixed in the calix[4]arene cavity of a lanthanide complex by a combination of three types of non-covalent interactions. The water proton resonances are detected at a chemical-shift value close to zero ppm, which we further confirm by quantum-chemical calculations. Density Functional Theory calculations pinpoint to the sensitivity of the proton chemical-shift value for hydrogen-π interactions. Our study highlights how proton-detected solid-state NMR is turning into the method-of-choice in probing weak non-covalent interactions driving a whole branch of molecular-recognition events in chemistry and biology.

Cannabis detection with solid sensors and paper-based immunoassays by conjugating antibodies to nanocellulose

Highly sensitive and specific diagnostics for cannabis usage are essential for rapid on-site screening for illicit drug usage. To improve the sensitivity of THC immunoassays, a proper immobilization of the sensing elements on the sensor substrate is critical. In this work, we demonstrated the utilization of EDC/NHS coupling chemistry with nanocellulose to obtain efficient anchor layers for the immobilization of anti-immune complex antibodies on surfaces. In our approach, the high surface-to-volume ratio, OH-group-rich surface, and high hygroscopicity of TOCNF enable efficient surface functionalization and enhance water permeation inside the nanocellulose network structure, offering a hydrophilic spacer for the sensing antibodies. THC detection was shown in both SPR (surface plasmon resonance technique) and paper-based sensing systems. In SPR, antibody immobilization and the related interactions with the target molecule complex with 1-10 μg/mL THC were followed in-situ in aqueous environment, revealing robust attachment of the antibody to the nanocellulose layer and preserved bioactivity. Additionally, quantitative THC detection was enabled on paper substrate by colorimetric means by employing labeled anti-THC Fab antibody fragments as detection antibodies. THC detection efficiency of covalently linked biointerface was superior compared to the performance of physically linked biointerface. The chemical conjugation of anti-IC to nanocellulose allowed efficient binding, whereas supramolecular conjugation led to insufficient binding, highlighting the relevance of the developed nanocellulose-based anchor layer.

Accounting for Solvation Correlation Effects on the Thermodynamics of Water Networks in Protein Cavities

Macromolecular recognition and ligand binding are at the core of biological function and drug discovery efforts. Water molecules play a significant role in mediating the protein-ligand interaction, acting as more than just the surrounding medium by affecting the thermodynamics and thus the outcome of the binding process. As individual water contributions are impossible to measure experimentally, a range of computational methods have emerged to identify hydration sites in protein pockets and characterize their energetic contributions for drug discovery applications. Even though several methods model solvation effects explicitly, they focus on determining the stability of specific water sites independently and neglect solvation correlation effects upon replacement of clusters of water molecules, which typically happens in hit-to-lead optimization. In this work, we rigorously determine the conjoint effects of replacing all combinations of water molecules in protein binding pockets through the use of the RE-EDS multistate free-energy method, which combines Hamiltonian replica exchange (RE) and enveloping distribution sampling (EDS). Applications on the small bovine pancreatic trypsin inhibitor and four proteins of the bromodomain family illustrate the extent of solvation correlation effects on water thermodynamics, with the favorability of replacement of the water sites by pharmacophore probes highly dependent on the composition of the water network and the pocket environment. Given the ubiquity of water networks in biologically relevant protein targets, we believe our approach can be helpful for computer-aided drug discovery by providing a pocket-specific and a priori systematic consideration of solvation effects on ligand binding and selectivity.

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.

Arginine transportation mechanism through cationic amino acid transporter 1: insights from molecular dynamics studies

Metabolic and signaling mechanisms in mammalian cells are facilitated by the transportation of L-arginine (Arg) across the plasma membrane through cationic amino acid transporter (CAT) proteins. Due to a lack of argininosuccinate synthase (ASS) activity in various tumor cells such as acute myeloid leukemia, acute lymphocytic leukemia, and chronic lymphocytic leukemia, these tumor entities are arginine-auxotrophic and therefore depend on the uptake of the amino acid arginine. Cationic amino acid transporter-1 (CAT-1) is the leading arginine importer expressed in the aforementioned tumor entities. Hence, in the present study, to investigate the transportation mechanism of arginine in CAT-1, we performed molecular dynamics (MD) simulation methods on the modeled human CAT-1. The MM-PBSA approach was conducted to determine the critical residues interacting with arginine within the corresponding binding site of CAT-1. In addition, we found out that the water molecules have the leading role in forming the transportation channel within CAT-1. The conductive structure of CAT-1 was formed only when the water molecules were continuously distributed across the channel. Steered molecular dynamics (SMD) simulation approach showed various energy barriers against arginine transportation through CAT-1, especially while crossing the bottlenecks of the related channel. These findings at the molecular level might shed light on identifying the crucial amino acids in the binding of arginine to eukaryotic CATs and also provide fundamental insights into the arginine transportation mechanisms through CAT-1. Understanding the transportation mechanism of arginine is essential to developing CAT-1 blockers, which can be potential medications for some types of cancers.Communicated by Ramaswamy H. Sarma.

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.

Molecular dynamics simulations provide structural insight into binding of cyclic dinucleotides to human STING protein

Human stimulator of interferon genes (hSTING) is a signaling adaptor protein that triggers innate immune system by response to cytosolic DNA and second messenger cyclic dinucleotides (CDNs). Natural CDNs contain purine nucleobase with different phosphodiester linkage types (3'-3', 2'-2' or mixed 2'-3'-linkages) and exhibit different binding affinity towards hSTING, ranging from micromolar to nanomolar. High-affinity CDNs are considered as suitable candidates for treatment of chronic hepatitis B and cancer. We have used molecular dynamics simulations to investigate dynamical aspects of binding of natural CDNs (specifically, 2'-2'-cGAMP, 2'-3'-cGAMP, 3'-3'-cGAMP, 3'-3'-c-di-AMP, and 3'-3'-c-di-GMP) with hSTING^wt protein. Our results revealed that CDN/hSTING^wt interactions are controlled by the balance between fluctuations (conformational changes) in the CDN ligand and the protein dynamics. Binding of different CDNs induces different degrees of conformational/dynamics changes in hSTING^wt ligand binding cavity, especially in α₁-helices, the so-called lid region and α₂-tails. The ligand residence time in hSTING^wt protein pocket depends on different contribution of R232 and R238 residues interacting with oxygen atoms of phosphodiester groups in ligand, water distribution around interacting charged centers (in protein residues and ligand) and structural stability of closed conformation state of hSTING^wt protein. These findings may perhaps guide design of new compounds modulating hSTING activity.Communicated by Ramaswamy H. Sarma.

Water Network in the Binding Pocket of Fluorinated BPTI-Trypsin Complexes─Insights from Simulation and Experiment

Structural waters in the S1 binding pocket of β-trypsin are critical for the stabilization of the complex of β-trypsin with its inhibitor bovine pancreatic trypsin inhibitor (BPTI). The inhibitor strength of BPTI can be modulated by replacing the critical lysine residue at the P1 position by non-natural amino acids. We study BPTI variants in which the critical Lys15 in BPTI has been replaced by α-aminobutyric acid (Abu) and its fluorinated derivatives monofluoroethylglycine (MfeGly), difluoroethylglycine (DfeGly), and trifluoroethylglycine (TfeGly). We investigate the hypothesis that additional water molecules in the binding pocket can form specific noncovalent interactions with the fluorinated side chains and thereby act as an extension of the inhibitors. We report potentials of mean force (PMF) of the unbinding process for all four complexes and enzyme activity inhibition assays. Additionally, we report the protein crystal structure of the Lys15MfeGly-BPTI-β-trypsin complex (pdb: 7PH1). Both experimental and computational data show a stepwise increase in inhibitor strength with increasing fluorination of the Abu side chain. The PMF additionally shows a minimum for the encounter complex and an intermediate state just before the bound state. In the bound state, the computational analysis of the structure and dynamics of the water molecules in the S1 pocket shows a highly dynamic network of water molecules that does not indicate a rigidification or stabilizing trend in regard to energetic properties that could explain the increase in inhibitor strength. The analysis of the energy and the entropy of the water molecules in the S1 binding pocket using grid inhomogeneous solvation theory confirms this result. Overall, fluorination systematically changes the binding affinity, but the effect cannot be explained by a persistent water network in the binding pocket. Other effects, such as the hydrophobicity of fluorinated amino acids and the stability of the encounter complex as well as the additional minimum in the potential of mean force in the bound state, likely influence the affinity more directly.

Development of Chitosan/Gelatin-Based Hydrogels Incorporated with Albumin Particles

The research subject of this paper are natural polymer-based hydrogels modified with albumin particles. The proteins were obtained via the salt-induced precipitation method, and next characterized using dynamic light scattering (DLS), UV-Vis spectroscopy and FT-IR spectroscopy. The most favorable composition showing monodispersity and particles with a size lower than 40 nm was selected for modification of hydrogels. Such systems were obtained via the photopolymerization performed under the influence of UV radiation using diacrylate poly(ethylene glycol) as a crosslinking agent and 2-hydroxy-2-methylpropiophenone as a photoinitiator. Next, the hydrogels' swelling ability, mechanical properties, wettability and surface morphology were characterized. Moreover, FT-IR spectroscopy, incubation studies in simulated physiological liquids, pro-inflammatory activity analysis and MTT reduction assay with L929 murine fibroblasts were performed. The release profiles of proteins from hydrogels were also verified. Materials modified with proteins showed higher swelling ability, increased flexibility even by 50% and increased surface hydrophilicity. Hydrogels' contact angles were within the range 62-69° while the tensile strength of albumin-containing hydrogels was approx. 0.11 MPa. Furthermore, the possibility of the effective release of protein particles from hydrogels in acidic environment (approximately 70%) was determined. Incubation studies showed hydrogels' stability and lack of their degradation in tested media. The viability of fibroblasts was 89.54% for unmodified hydrogel, and approx. 92.73% for albumin-modified hydrogel, and such an increase indicated the positive impact of the albumin on murine fibroblast proliferation.

Pyrazole-Based Thrombin Inhibitors with a Serine-Trapping Mechanism of Action: Synthesis and Biological Activity

New antithrombotic drugs are needed to combat thrombosis, a dangerous pathology that causes myocardial infarction and ischemic stroke. In this respect, thrombin (FIIa) represents an important drug target. We herein report the synthesis and biological activity of a series of 1H-pyrazol-5-amine-based thrombin inhibitors with a serine-trapping mechanism of action. Among synthesized compounds, flexible acylated 1H-pyrazol-5-amines 24e, 34a, and 34b were identified as potent 16-80 nM thrombin inhibitors, which showed practically no off-targeting effect against other physiologically relevant serine proteases. To prove that synthesized compounds are covalent thrombin inhibitors, the most potent derivative 24e (FIIa IC₅₀ = 16 nM) was studied in a mass-shift assay, where it has been shown that 24e transfers its acyl moiety (pivaloyl) to the catalytic Ser195 of thrombin. Performed herein docking studies also confirmed the covalent mechanism of thrombin inhibition by synthesized compounds. Acylated aminopyrazoles found during this study showed only limited effects on plasma coagulation in activated partial thrombin time (aPTT) and prothrombin time (PT) in vitro assays. However, such thrombin inhibitors are expected to have virtually no effect on bleeding time and can be used as a starting point for developing a safer alternative to traditional non-covalent anticoagulants.