Uncovering the pharmacological mechanisms of Patchouli essential oil for treating ulcerative colitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Pogostemonis Herba has long been used in traditional Chinese medicine to treat inflammatory disorders. Patchouli essential oil (PEO) is the primary component of Pogostemonis Herba, and it has been suggested to offer curative potential when applied to treat ulcerative colitis (UC). However, the pharmacological mechanisms of PEO for treating UC remain to be clarified. AIM OF THE STUDY: To elucidate the pharmacological mechanisms of PEO for treating UC. METHODS AND RESULTS: In the present study, transcriptomic and network pharmacology approaches were combined to clarify the mechanisms of PEO for treating UC. Our results reveal that rectal PEO administration in UC model mice significantly alleviated symptoms of UC. In addition, PEO effectively suppressed colonic inflammation and oxidative stress. Mechanistically, PEO can ameliorate UC mice by modulating gut microbiota, inhibiting inflammatory targets (OPTC, PTN, IFIT3, EGFR, and TLR4), and inhibiting the PI3K-AKT pathway. Next, the 11 potential bioactive components that play a role in PEO's anti-UC mechanism were identified, and the therapeutic efficacy of the pogostone (a bioactive component) in UC mice was partially validated. CONCLUSION: This study highlights the mechanisms through which PEO can treat UC, providing a rigorous scientific foundation for future efforts to develop and apply PEO for treating UC.

Network Pharmacology and Molecular Dynamics Simulations Reveal the Mechanism of Total Alkaloid Components in Anisodus tanguticus (Maxim.) Pascher in Treating Inflammation and Pain.

This study aimed to elucidate the mechanism that total alkaloids in Anisodus tanguticus (AT)(Maxim.) Pascher play anti-inflammatory and analgesic effects. In this paper, the anti-inflammatory effect in the total alkaloids of AT was confirmed via lipopolysaccharide (LPS)-induced inflammation model in RAW 264.7 cells and the main components of AT were immediately analyzed by UPLC/MS. Disease targets were obtained in GeneCards and DisGeNET. Targets of major compounds were searched in ETCM, TCMSP and other databases. The protein-protein interaction (PPI) network was constructed using STRING database, and Cytoscape was used for core targets screening. GO and KEGG enrichment analysis were performed using Daivid database. Sailvina was used for molecular docking. Molecular dynamics simulation analysis was performed using the Amber 20 program. The results showed that the main components in AT were anisodamine, atropine, fabiatrin, scopolamine, scopoletin and scopolin, possibly exerting anti-inflammatory and analgesic effects through pathways such as EGFR tyrosine kinase inhibitor resistance and IL-17 signaling pathway. Fabiatrin and scopolin could be potential drugs with good anti-inflammatory and analgesic effects.

Molecular Interactions of the Pioneer Transcription Factor GATA3 With DNA.

The GATA3 transcription factor is a pioneer transcription factor that is critical in the development, proliferation, and maintenance of several immune cell types. Identifying the detailed conformational dynamics and interactions of this transcription factor, as well as its clinically important population variants will allow us to unravel its mode of action. In this study, we analyze the molecular interactions of the GATA3 transcription factor bound to dsDNA as well as three clinically important population variants by atomistic molecular dynamics simulations. We identify the effect of the variants on the DNA conformational dynamics and delineate the differences compared to the wildtype transcription factor that could be related to impaired function. We highlight the structural plasticity in the binding of the GATA3 transcription factor and identify important DNA-protein contacts. Although the DNA-protein contacts are persistent and appear to be stable, they exhibit nanosecond timescale fluctuations and several binding/unbinding events. Further, we identify differential DNA binding in the three variants and show that the N-terminal binding is reduced in two of the variants. Our results indicate that reduced minor groove width and DNA diameter are important hallmarks for the binding of GATA3. Our work is an important step towards understanding the functional dynamics of the GATA3 protein and its clinically significant population variants.

Hydrogen Bond Network Shaping Proton Penetration Behavior across Two-Dimensional Nanoporous Materials.

In this study, we investigate aqueous proton penetration behavior across four types of two-dimensional (2D) nanoporous materials with similar pore sizes using extensive ReaxFF molecular dynamics simulations. The results reveal significant differences in proton penetration energy barriers among the four kinds of 2D materials, despite their comparable pore sizes. Our analysis indicates that these variations in energy barriers stem from differences in the hydrogen bond (HB) network formed between the 2D nanoporous materials and the aqueous environment. The HB network can be classified into two categories: those formed between the surface of the 2D nanoporous materials and the aqueous environment, and those formed between the edge atoms of the nanopores and the water molecules inside the pores. A strong HB network formed between the surface of the 2D nanoporous materials and the aqueous environment induces an orientational preference of water molecules, resulting in an aggregated water layer with high density. This high-density water region traps protons, making it difficult for them to escape and penetrate the nanopores. On the other hand, a strong HB network formed between the edge atoms of the nanopores and the water molecules inside the pores impedes the rotation and migration of water molecules, further inhibiting proton penetration behavior. To facilitate the proton penetration process, in addition to a sufficiently large pore size, a weak HB network between the 2D nanoporous material and the aqueous environment is necessary.

The Endocannabinoid Peptide RVD-Hemopressin Is a TRPV1 Channel Blocker.

Neurotransmission is critical for brain function, allowing neurons to communicate through neurotransmitters and neuropeptides. RVD-hemopressin (RVD-Hp), a novel peptide identified in noradrenergic neurons, modulates cannabinoid receptors CB1 and CB2. Unlike hemopressin (Hp), which induces anxiogenic behaviors via transient receptor potential vanilloid 1 (TRPV1) activation, RVD-Hp counteracts these effects, suggesting that it may block TRPV1. This study investigates RVD-Hp's role as a TRPV1 channel blocker using HEK293 cells expressing TRPV1-GFP. Calcium imaging and patch-clamp recordings demonstrated that RVD-Hp reduces TRPV1-mediated calcium influx and TRPV1 ion currents. Molecular docking and dynamics simulations indicated that RVD-Hp interacts with TRPV1's selectivity filter, forming stable hydrogen bonds and van der Waals contacts, thus preventing ion permeation. These findings highlight RVD-Hp's potential as a therapeutic agent for conditions involving TRPV1 activation, such as pain and anxiety.

Ultrasound-Assisted Preparation of Hyaluronic Acid-Based Nanocapsules with an Oil Core.

Liquid-core nanocapsules (NCs) coated with amphiphilic hyaluronic acid (AmHA) have been proposed for the preparation of drug and food formulations. Herein, we focused on the use of ultrasound techniques to (i) optimize the polysaccharide chain length with respect to the properties of NCs stabilized with AmHAs and (ii) form oil-core nanocapsules with a coating composed of AmHAs. The results indicate that sonication is a convenient and effective method that allows for a controlled reduction in HA molecular weight. The initial (H-HA) and degraded (L-HA) polysaccharides were then reacted with dodecylamine to obtain hydrophobic HA derivatives (HA-C12s). Then, NCs were prepared based on HA-C12s using ultrasound-assisted emulsification of glyceryl triacetate oil. The nanocapsules coated with L-HA-C12 showed greater stability compared to the longer-chain polysaccharide. Molecular dynamics (MD) simulations revealed that HA-C12 readily adsorbs at the water-oil interphase, adopting a more compact conformation compared to that in the aqueous phase. The dodecyl groups are immersed in the oil droplet, while the main polysaccharide chain remaining in the aqueous phase forms hydrogen bonds or water bridges with the polar part of the triglycerides, thus increasing the stability of the NC. Our research underscores the usefulness of ultrasound technology in preparing suitable formulations of bioactive substances.

Discovering potential asthma therapeutics targeting hematopoietic prostaglandin D2 synthase: An integrated computational approach.

Allergic asthma, a chronic inflammatory illness that affects millions worldwide, has serious economic and health consequences. Despite advances in therapy, contemporary treatments have poor efficacy and negative effects. This study investigates hematopoietic prostaglandin D2 synthase (HPGDS) as a potential target for novel asthma therapies. Targeting HPGDS may provide innovative treatment methods. A library of phytochemicals was used to find putative HPGDS inhibitors by structure-based and ligand-based virtual screening. Among the 2295 compounds screened, four compounds (ZINC208828240, ZINC95627530, ZINC14727536, and ZINC14711790) demonstrated strong binding affinities of -10.4, -10.3, -9.2, -9.1 kcal/mol respectively with key residues, suggesting their potential as a highly effective HPGDS inhibitor. Molecular dynamics (MD) simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) computations were further performed to evaluate the stability and binding affinity of the complexes. MD simulations and MMPBSA confirmed that compound ZINC14711790 showed high stability and binding affinity (binding energy -31.52 kcal/mol) than other compounds, including HQL-79, suggesting that this compound might be used as promising inhibitors to treat asthma. RMSD and RMSF analysis also revealed that ZINC14711790 exhibited strong dynamic stability. The findings of this study show the efficacy of ZINC14711790 as HPGDS inhibitors with high binding affinity, dynamic stability, and appropriate ADMET profile.

Machine-Learning-Assisted Design of Deep Eutectic Solvents Based on Uncovered Hydrogen Bond Patterns.

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportunities. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the HB properties of 38 known DES and 111 known non-DES systems using their molecular dynamics (MD) simulation trajectories. The analysis reveals that DES systems have two unique features compared to non-DES systems: The DESs have ① more imbalance between the numbers of the two intra-component HBs and ② more and stronger inter-component HBs. Based on these results, we develop 30 ML models using ten algorithms and three types of HB-based descriptors. The model performance is first benchmarked using the average and minimal receiver operating characteristic (ROC)-area under the curve (AUC) values. We also analyze the importance of individual features in the models, and the results are consistent with the simulation-based statistical analysis. Finally, we validate the models using the experimental data of 34 systems. The extra trees forest model outperforms the other models in the validation, with an ROC-AUC of 0.88. Our work illustrates the importance of HBs in DES formation and shows the potential of ML in discovering new DESs.

Computational Mutagenesis and Inhibition of Staphylococcus aureus AgrA LytTR Domain Using Phenazine Scaffolds: Insight From a Biophysical Study.

Biofilm formation by Staphylococcus aureus is a major challenge in clinical settings due to its role in persistent infections. The AgrA protein, a key regulator in biofilm development, is a promising target for therapeutic intervention. This study investigates the antibiofilm potential of halogenated phenazine compounds by targeting AgrA and explores their molecular interactions to provide insights for drug development. We employed molecular docking, molecular dynamics simulations, and computational mutagenesis to evaluate the binding of halogenated phenazine compounds (C1 to C7, HP, and HP-14) to AgrA. Binding free energy analysis was performed to assess the affinity of these compounds for the AgrA-DNA complex. Additionally, the impact of these compounds on AgrA's structural conformation and salt bridge interactions was examined. The binding-free energy analysis revealed that all compounds enhance binding affinity compared to the Apo form of AgrA, which has a ΔGbind of -80.75 kcal/mol. The strongest binding affinities were observed with compounds C7 (-113.84 kcal/mol), HP-14 (-115.23 kcal/mol), and HP (-112.28 kcal/mol), highlighting their effectiveness. Molecular dynamics simulations demonstrated that these compounds bind at the hydrophobic cleft of AgrA, disrupting essential salt bridge interactions between His174-Glu163 and His174-Glu226. This disruption led to structural conformational changes and reduced DNA binding affinity, aligning with experimental findings on biofilm inhibition. The halogenated phenazine compounds effectively inhibit biofilm formation by targeting AgrA, disrupting its DNA-binding function. The study supports the potential of these compounds as antibiofilm agents and provides a foundation for rational drug design targeting the AgrA-DNA interaction. Future research should focus on further optimizing these lead compounds and exploring additional active sites on AgrA to develop novel treatments for biofilm-associated infections.

Exploring the Origins of Association of Poly(acrylic acid) Polyelectrolyte with Lysozyme in Aqueous Environment through Molecular Simulations and Experiments.

This study provides a detailed picture of how a protein (lysozyme) complexes with a poly(acrylic acid) polyelectrolyte (PAA) in water at the atomic level using a combination of all-atom molecular dynamics simulations and experiments. The effect of PAA and temperature on the protein's structure is explored. The simulations reveal that a lysozyme's structure is relatively stable except from local conformational changes induced by the presence of PAA and temperature increase. The effect of a specific thermal treatment on the complexation process is investigated, revealing both structural and energetic changes. Certain types of secondary structures (i.e., α-helix) are found to undergo a partially irreversible shift upon thermal treatment, which aligns qualitatively with experimental observations. This uncovers the origins of thermally induced aggregation of lysozyme with PAA and points to new PAA/lysozyme bonds that are formed and potentially enhance the stability in the complexes. As the temperature changes, distinct amino acids are found to exhibit the closest proximity to PAA, resulting into different PAA/lysozyme interactions; consequently, a different complexation pathway is followed. Energy calculations reveal the dominant role of electrostatic interactions. This detailed information can be useful for designing new biopolymer/protein materials and understanding protein function under immobilization of polyelectrolytes and upon mild denaturation processes.

Force Fields, Quantum-Mechanical- and Molecular-Dynamics-Based Descriptors of Radiometal-Chelator Complexes.

Radiopharmaceuticals are currently a key tool in cancer diagnosis and therapy. Metal-based radiopharmaceuticals are characterized by a radiometal-chelator moiety linked to a bio-vector that binds the biological target (e.g., a protein overexpressed in a particular tumor). The right match between radiometal and chelator influences the stability of the complex and the drug's efficacy. Therefore, the coupling of the radioactive element to the correct chelator requires consideration of several features of the radiometal, such as its oxidation state, ionic radius, and coordination geometry. In this work, we systematically investigated about 120 radiometal-chelator complexes taken from the Cambridge Structural Database. We considered 25 radiometals and about 30 chelators, featuring both cyclic and acyclic geometries. We used quantum mechanics methods at the density functional theoretical level to generate the general AMBER force field parameters and to perform 1 µs-long all-atom molecular dynamics simulations in explicit water solution. From these calculations, we extracted several key molecular descriptors accounting for both electronic- and dynamical-based properties. The whole workflow was carefully validated, and selected test-cases were investigated in detail. Molecular descriptors and force field parameters for the complexes considered in this study are made freely available, thus enabling their use in predictive models, molecular modelling, and molecular dynamics investigations of the interaction of compounds with macromolecular targets. Our work provides new insights in understanding the properties of radiometal-chelator complexes, with a direct impact for rational drug design of this important class of drugs.

Integration of Hydrogen-Deuterium Exchange Mass Spectrometry with Molecular Dynamics Simulations and Ensemble Reweighting Enables High Resolution Protein-Ligand Modeling.

Hydrogen-Deuterium exchange mass spectrometry's (HDX-MS) utility in identifying and characterizing protein-small molecule interaction sites has been established. The regions that are seen to be protected from exchange upon ligand binding indicate regions that may be interacting with the ligand, giving a qualitative understanding of the ligand binding pocket. However, quantitatively deriving an accurate high-resolution structure of the protein-ligand complex from the HDX-MS data remains a challenge, often limiting its use in applications such as small molecule drug design. Recent efforts have focused on the development of methods to quantitatively model Hydrogen-Deuterium exchange (HDX) data from computationally modeled structures to garner atomic level insights from peptide-level resolution HDX-MS. One such method, HDX ensemble reweighting (HDXer), employs maximum entropy reweighting of simulated HDX data to experimental HDX-MS to model structural ensembles. In this study, we implement and validate a workflow which quantitatively leverages HDX-MS data to accurately model protein-small molecule ligand interactions. To that end, we employ a strategy combining computational protein-ligand docking, molecular dynamics simulations, HDXer, and dimensional reduction and clustering approaches to extract high-resolution drug binding poses that most accurately conform with HDX-MS data. We apply this workflow to model the interaction of ERK2 and FosA with small molecule compounds and inhibitors they are known to bind. In five out of six of the protein-ligand pairs tested, the HDX derived protein-ligand complexes result in a ligand root-mean-square deviation (RMSD) within 2.5 Å of the known crystal structure ligand.

A review of intact glycopeptide enrichment and glycan separation through hydrophilic interaction liquid chromatography stationary phase materials.

Protein glycosylation, one of the most important biologically relevant post-translational modifications for biomarker discovery, faces analytical challenges due to heterogeneous glycosite, diverse glycans, and mass spectrometry limitations. Glycopeptide enrichment by removing abundant hydrophobic peptides helps overcome some of these obstacles. Hydrophilic interaction liquid chromatography (HILIC), known for its selectivity, glycan separations, intact glycopeptide enrichment, and compatibility with mass spectrometry, has seen recent advancements in stationary phases like Amide-80, glycoHILIC, amino acids or peptides for improved HILIC-based glycopeptide analysis. Utilization of these materials can improve glycopeptide enrichment through solid-phase extraction and separation via high-performance liquid chromatography. Additionally, using glycopeptides themselves to modify HILIC stationary phases holds promise for improving selectivity and sensitivity in glycosylation analysis. Additionally, HILIC has capability to assess the information about glycosites and structural information of glycans. This review summarizes recent breakthroughs in HILIC stationary materials, highlighting their impact on glycopeptide analysis. Ongoing research on advanced materials continues to refine HILIC's performance, solidifying its value as a tool for exploring protein glycosylation.

Discovery of Indole-Thiourea Derivatives as Tyrosinase Inhibitors: Synthesis, Biological Evaluation, Kinetic Studies, and In Silico Analysis.

Tyrosinase, a key enzyme in melanin synthesis, represents a crucial therapeutic target for hyperpigmentation disorders due to excessive melanin production. This study aimed to design and evaluate a series of indole-thiourea derivatives by conjugating thiosemicarbazones with strong tyrosinase inhibitory activity to indole. Among these derivatives, compound 4b demonstrated tyrosinase inhibitory activity with an IC50 of 5.9 ± 2.47 µM, outperforming kojic acid (IC50 = 16.4 ± 3.53 µM). Kinetic studies using Lineweaver-Burk plots confirmed competitive inhibition by compound 4b. Its favorable ADMET and drug-likeness properties make compound 4b a promising therapeutic candidate with a reduced risk of toxicity. Molecular docking revealed that the compounds bind strongly to mushroom tyrosinase (mTYR) and human tyrosinase-related protein 1 (TYRP1), with compound 4b showing superior binding energies of -7.0 kcal/mol (mTYR) and -6.5 kcal/mol (TYRP1), surpassing both kojic acid and tropolone. Molecular dynamics simulations demonstrated the stability of the mTYR-4b complex with low RMSD and RMSF and consistent Rg and SASA values. Persistent strong hydrogen bonds with mTYR, along with favorable Gibbs free energy and MM/PBSA calculations (-19.37 kcal/mol), further support stable protein-ligand interactions. Overall, compound 4b demonstrated strong tyrosinase inhibition and favorable pharmacokinetics, highlighting its potential for treating pigmentary disorders.

Molecular Dynamics Simulation Combined with Neural Relationship Inference and Markov Model to Reveal the Relationship between Conformational Regulation and Bioluminescence Properties of Gaussia Luciferase.

Gaussia luciferase (Gluc) is currently known as the smallest naturally secreted luciferase. Due to its small molecular size, high sensitivity, short half-life, and high secretion efficiency, it has become an ideal reporter gene and is widely used in monitoring promoter activity, studying protein-protein interactions, protein localization, high-throughput drug screening, and real-time monitoring of tumor occurrence and development. Although studies have shown that different Gluc mutations exhibit different bioluminescent properties, their mechanisms have not been further investigated. The purpose of this study is to reveal the relationship between the conformational changes of Gluc mutants and their bioluminescent properties through molecular dynamics simulation combined with neural relationship inference (NRI) and Markov models. Our results indicate that, after binding to the luciferin coelenterazine (CTZ), the α-helices of the 109-119 residues of the Gluc Mutant2 (GlucM2, the flash-type mutant) are partially unraveled, while the α-helices of the same part of the Gluc Mutant1 (GlucM1, the glow-type mutant) are clearly formed. The results of Markov flux analysis indicate that the conformational differences between glow-type and flash-type mutants when combined with luciferin substrate CTZ mainly involve the helicity change of α7. The most representative conformation and active pocket distance analysis indicate that compared to the flash-type mutant GlucM2, the glow-type mutant GlucM1 has a higher degree of active site closure and tighter binding. In summary, we provide a theoretical basis for exploring the relationship between the conformational changes of Gluc mutants and their bioluminescent properties, which can serve as a reference for the modification and evolution of luciferases.

Molecular Investigation of the Self-Assembly Mechanism Underlying Polydopamine Coatings: The Synergistic Effect of Typical Building Blocks Acting on Interfacial Adhesion.

Polydopamine (PDA) is well known as a mussel-inspired adhesive material composed of oligomeric heteropolymers. However, the conventional eumelanin-like structural assumption of PDA seems deficient in explaining its interfacial adhesion. To determine the decisive mechanism of PDA coating formation, experiments and simulations were performed in this study. 5,6-Dihydroxyindole (DHI), the signature building block of eumelanin, was introduced as the control group. Various typical building blocks in PDA were quantified by physicochemical characterizations, and the polar-group-dominated interfacial interaction was evaluated by classic molecular dynamics and metadynamics methods. Aminoethyl has been proven to be the key functional group inducing the adsorption of PDA on the hydroxylated silica substrates, while DHI shows limited adhesion to the substrate due to the absence of aminoethyl as the catechol-indole structure of DHI exhibits poor affinity to the silica surface. Pyrrole carboxylic acid, as an oxidative product detected from PDA/DHI, is unfavorable for its adhesion to silica substrates. Overall, the coating formation and self-aggregating precipitation of PDA are two competitive aminoethyl-consuming paths; thus, the in situ oxidative coupling of dopamine is indispensable for the PDA coating preparation. The collected PDA precipitates can no longer present satisfactory coating forming behavior, resulting from a shortage of aminoethyl moieties.

High-Pressure CO2 and CH4 Transport in Smooth Crystalline Silica Mesopores: A Molecular Dynamics Study.

In this study, we use molecular dynamics (MD) simulation to study pressure-driven CO2 and CH4 flows and their slippage behaviors in ß-cristobalite mesopores. The result illustrates that both CO2 and CH4 have an apparent adsorption layer on pore surface. However, significant differences in gas slippage are observed: CH4 flow shows considerable slippage, while it is negligible for CO2 flow. This disparity is attributed to the collective effect of gas molecular configurations and surface structure. The linear molecular structure of CO2 allows it to align perpendicular to the surface, even penetrating into the surface. Notably, the perpendicular orientation of CO2 molecules is energetically favored near the center of the equilateral triangle formed by adjacent oxygen atoms on ß-cristobalite surface. Conversely, the symmetric molecular structure of CH4, coupled with its larger size, prevents its penetration into pore surfaces. Therefore, despite smooth crystalline surfaces, CO2 topological accessible plane is much more curved than that of CH4. Consequently, CO2 displays hesitating motions undergoing rotational movements, which significantly hinders its slippage. This study highlights the collective influences of gas molecular characteristics and surface structure on gas slippage, affording important insights into gas sequestration and the development of functional materials for gas separation.

On the solvation properties of menthol-thymol mixtures. A Molecular Dynamics Investigation.

Using classical molecular dynamics, we have investigated the solvation of catechol, resorcinol, hydroquinone and 1,4-benzoquinone at infinite dilution, in a series of menthol - thymol mixtures in which the molar fraction of thymol (xTHY) has been increased by steps of 0.1, from 0 (pure menthol) to 1 (pure thymol). The evolution of the solvation shell around the solutes reveals that when xTHY is increased, the average number of hydrogen bonds (HB) where the solute acts as HB acceptor (HBA) and the solvent as HB donor (HBD) increases, while the amount of HB, in which the solute acts as HBD and the solvent as HBA, decreases. Overall, the total number of HBs between the different benzenediols and the solvent decreases with an increase of xTHY, while for benzoquinone the total number of HB increases. This points to the fact that "acidic" or HBD molecules are better solvated in mixtures with high menthol proportion, while "basic" or HBA molecules, are better solvated in thymol rich mixtures. The results reported herein follow the same trends as experimentally reported Kamlet-Taft parameters and present insights on how the composition of these "deep eutectic" mixtures maybe tweaked in order to optimize their solvation properties.

An integrative characterisation of proline cis and trans conformers in a disordered peptide.

Intrinsically disordered proteins (IDPs) often contain proline residues, which undergo cis/trans isomerisation. While molecular dynamics (MD) simulations have the potential to fully characterise the proline cis and trans sub-ensembles, they are limited by the slow timescales of isomerisation and force field inaccuracies. Nuclear magnetic resonance (NMR) spectroscopy can report on ensemble-averaged observables for both the cis-proline and trans-proline states, but a full atomistic characterisation of these conformers is challenging. Given the importance of proline cis/trans isomerisation for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle X-ray scattering (SAXS) to characterise the two sub-ensembles of the ORF6 C-terminal region (ORF6CTR) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB-disp, and CHARMM36m, which are all optimised for disordered proteins. Each simulation was run for an accumulated time of 180-220 µs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis-P57 populations predicted from metadynamic simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamic simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis-P57 and trans-P57 conformations of ORF6CTR are extremely dynamic and that interdisciplinary approaches combining both multi-scale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterised by either approach in isolation.

Stereo-selectivity of enantiomeric inhibitors to ubiquitin-specific protease 7 (USP7) dissected by molecular docking, molecular dynamics simulations, and binding free energy calculations.

The ubiquitin-specific protease 7 (USP7), as a member of deubiquitination enzymes, represents an attractive therapeutic target for various cancers, including prostate cancer and liver cancer. The change of the inhibitor stereocenter from the S to R stereochemistry (S-ALM → R-ALM34) markedly improved USP7 inhibitory activity. However, the molecular mechanism for the stereo-selectivity of enantiomeric inhibitors to USP7 is still unclear. In this work, molecular docking, molecular dynamics (MD) simulations, molecular mechanics/Generalized-Born surface area (MM/GBSA) calculations, and free energy landscapes were performed to address this mystery. MD simulations revealed that S-ALM34 showed a high degree of conformational flexibility compared to the R-ALM34 counterpart, and S-ALM34 binding led to the enhanced intradomain motions of USP7, especially the BL1 and BL2 loops and the two helices α4 and α5. MM/GBSA calculations showed that the binding strength of R-ALM34 to USP7 was stronger than that of S-ALM34 by - 4.99 kcal/mol, a similar trend observed by experimental data. MM/GBSA free energy decomposition was further performed to differentiate the ligand-residue spectrum. These analyses not only identified the hotspot residues interacting with R-ALM34, but also revealed that the hydrophobic interactions from F409, K420, H456, and Y514 play the major determinants in the binding of R-ALM34 to USP7. This result is anticipated to shed light on energetic basis and conformational dynamics information to aid in the design of more potent and selective inhibitors targeting USP7.