ABSTRACT
The complexity of plant cell walls on different hierarchical levels still impedes the detailed understanding of biosynthetic pathways, interferes with processing in industry and finally limits applicability of cellulose materials. While there exist many challenges to readily accessing these hierarchies at (sub-) angström resolution, the development of advanced computational methods has the potential to unravel important questions in this field. Here, we summarize the contributions of molecular dynamics simulations in advancing the understanding of the physico-chemical properties of natural fibres. We aim to present a comprehensive view of the advancements and insights gained from molecular dynamics simulations in the field of carbohydrate polymers research. The review holds immense value as a vital reference for researchers seeking to undertake atomistic simulations of plant cell wall constituents. Its significance extends beyond the realm of molecular modeling and chemistry, as it offers a pathway to develop a more profound comprehension of plant cell wall chemistry, interactions, and behavior. By delving into these fundamental aspects, the review provides invaluable insights into future perspectives for exploration. Researchers within the molecular modeling and carbohydrates community can greatly benefit from this resource, enabling them to make significant strides in unraveling the intricacies of plant cell wall dynamics.
Subject(s)
Cell Wall , Cellulose , Molecular Dynamics Simulation , Polysaccharides , Cell Wall/chemistry , Cell Wall/metabolism , Cellulose/chemistry , Polysaccharides/chemistry , Plants/chemistry , Plants/metabolism , Plant Cells/chemistry , Plant Cells/metabolismABSTRACT
BACKGROUND: Cinnamomum tamala (Buch.-Ham.) T.Nees & Eberm., also known as Indian Bay leaf, holds a distinctive position in complementary and alternative medicinal systems due to its anti-inflammatory properties. However, the active constituents and key molecular targets by which C. tamala essential oil (CTEO) exerts its anti-inflammatory action remain unclear. OBJECTIVE: The present study used network pharmacology and experimental validation to investigate the mechanism of CTEO in the treatment of inflammation. METHODS: GC-MS analysis was used to identify the constituents of CTEO. The key constituents and core targets of CTEO against inflammation were obtained by network pharmacology. The binding mechanism between the active compounds and inflammatory genes was ascertained by molecular docking and molecular dynamics simulation analysis. The pharmacological mechanism predicted by network pharmacology was verified in lipopolysaccharide-stimulated murine macrophage (RAW 264.7) cell lines. RESULTS: Forty-nine constituents were identified by GC-MS analysis, with 44 constituents being drug-like candidates. A total of 549 compounds and 213 inflammation-related genes were obtained, revealing 68 overlapping genes between them. Compound target network analysis revealed cinnamaldehyde as the core bioactive compound with the highest degree score. PPI network analysis demonstrated Il-1ß, TNF-α, IL8, IL6 and TLR4 as key hub anti-inflammatory targets. KEGG enrichment analysis revealed a Toll-like receptor signalling pathway as the principally regulated pathway associated with inflammation. A molecular docking study showed that cinnamaldehyde strongly interacted with the Il-1ß, TNF-α and TLR-4 proteins. Molecular dynamics simulations and MMPBSA analysis revealed that these complexes are stable without much deviation and have better free energy values. In cellular experiments, CTEO showed no cytotoxic effects on RAW 264.7 murine macrophages. The cells treated with LPS exhibited significant reductions in NO, PGE2, IL-6, TNF-α, and IL-1ß levels following treatment with CTEO. Additionally, CTEO treatment reduced the ROS levels and increased the antioxidant enzymes such as SOD, GSH, GPx and CAT. Immunofluorescence analysis revealed that CTEO inhibited LPS-stimulated NF-κB nuclear translocation. The mRNA expression of TLR4, MyD88 and TRAF6 in the CTEO group decreased significantly compared to the LPS-treated group. CONCLUSION: The current findings suggest that CTEO attenuates inflammation by regulating TLR4/MyD88/NF- κB signalling pathway.
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Organophosphates constitute a major class of pesticides widely employed in agriculture to manage insect pests. Their toxicity is attributed to their ability to inhibit the functioning of acetylcholinesterase (AChE), an essential enzyme for normal nerve transmission. Organophosphates, especially chlorpyrifos, have been a key component of the integrated pest management (IPM) in onions, effectively controlling onion maggot Delia antiqua, a severe pest of onions. However, the growing concerns over the use of this insecticide on human health and the environment compelled the need for an alternative organophosphate and a potential microbial agent for bioremediation to mitigate organophosphate pesticide pollution. In the present study, chloropyrifos along with five other organophosphate insecticides, phosmet, primiphos-methyl, isofenphos, iodofenphos and tribuphos, were screened against the target protein AChE of D. antiqua using molecular modeling and docking techniques. The results revealed that iodofenphos showed the best interaction, while tribuphos had the lowest interaction with the AChE based on comparative binding energy values. Further, protein-protein interaction analysis conducted using the STRING database and Cytoscap software revealed that AChE is linked with a network of 10 different proteins, suggesting that the function of AChE is disrupted through interaction with insecticides, potentially leading to disruption within the network of associated proteins. Additionally, an in silico study was conducted to predict the binding efficiency of two organophosphate degrading enzymes, organophosphohydrolase (OpdA) from Agrobacterium radiobacter and Trichoderma harzianum paraoxonase 1 like (ThPON1-like) protein from Trichoderma harzianum, with the selected insecticides. The analysis revealed their potential to degrade the pesticides, offering a promising alternative before going for cumbersome onsite remediation.
ABSTRACT
Aim: To identify potential antischistosomal agents through 3D pharmacophore-based virtual screening of US FDA approved drugs. Materials & methods: A comprehensive virtual screening was conducted on a dataset of 10,000 FDA approved drugs, employing praziquantel as a template. Promising candidates were selected and assessed for their impact on Schistosoma mansoni viability in vitro and in vivo using S. mansoni infected mice. Results & conclusion: Among the selected drugs, betamethasone and doxazosin demonstrated in vitro efficacy, with effective concentration 50% (EC50) values ranging from 35 to 60 µM. In vivo studies revealed significant (>50%) reductions in worm burden for both drugs. These findings suggest that betamethasone and doxazosin hold promise for repurposing in treating schistosomiasis. Additionally, the study showcases a useful approach for identifying new antischistosomal drugs.
Discovering new treatments for #schistosomiasis is crucial[Formula: see text]. Our study used virtual screening to identify potential antischistosomal drugs from US FDA approved compounds [Formula: see text]. Promising results in vitro and in vivo. [Formula: see text] #drugdiscovery #tropicaldiseases.
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The comprehension of molecular structure is pivotal in chemistry education. Over the past decade, Mahidol University International College has employed various teaching tools for the introductory chemistry laboratory class. This paper outlines our evolutionary shift from traditional tools, such as plastic and plasticine models, to the integration of computer software, and ultimately to augmented reality (AR) and virtual reality (VR) tools-specifically, MoleculARweb and MolecularWebXR developed by École Polytechnique Fédérale de Lausanne researchers. In this paper, we detail the implementation of these tools in our classes and present the outcomes of student surveys. Our instructional focus encompasses VSEPR, Atomic Orbitals, Molecular Orbitals, Skeletal Formula, and Enantiomers. This paper not only serves as a model for educators in general chemistry at secondary school or university levels to incorporate technology into their classrooms but also showcases a collaborative endeavor between Swiss and Thai researchers.
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An increasing number of drugs introduced to the market and numerous repositories of compounds with confirmed activity have posed the need to revalidate the state-of-the-art rules that determine the ranges of properties the compounds should possess to become future drugs. In this study, we designed a series of two chemotypes of aryl-piperazine hydantoin ligands of 5-HT7R, an attractive target in search for innovative CNS drugs, with higher molecular weight (close to or over 500). Consequently, 14 new compounds were synthesised and screened for their receptor activity accompanied by extensive docking studies to evaluate the observed structure-activity/properties relationships. The ADMET characterisation in terms of the biological membrane permeability, metabolic stability, hepatotoxicity, cardiotoxicity, and protein plasma binding of the obtained compounds was carried out in vitro. The outcome of these studies constituted the basis for the comprehensive challenge of computational tools for ADMET properties prediction. All the compounds possessed high affinity to the 5-HT7R (Ki below 250 nM for all analysed structures) with good selectivity over 5-HT6R and varying affinity towards 5-HT2AR, 5-HT1AR and D2R. For the best compounds of this study, the expression profile of genes associated with neurodegeneration, anti-oxidant response and anti-inflammatory function was determined, and the survival of the cells (SH-SY5Y as an in vitro model of Alzheimer's disease) was evaluated. One 5-HT7R agent (32) was characterised by a very promising ADMET profile, i.e. good membrane permeability, low hepatotoxicity and cardiotoxicity, and high metabolic stability with the simultaneous high rate of plasma protein binding and high selectivity over other GPCRs considered, together with satisfying gene expression profile modulations and neural cell survival. Such encouraging properties make it a good candidate for further testing and optimisation as a potential agent in the treatment of CNS-related disorders.
ABSTRACT
Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual's tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutation's effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving a balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available at https://loschmidt.chemi.muni.cz/predictonco/ .Scientific contributionThis work presents a novel bioinformatics pipeline that integrates multiple computational tools to predict the effects of missense mutations on proteins of oncological interest. The pipeline uniquely combines fast protein modelling, stability prediction, and evolutionary analysis with virtual drug screening, while offering actionable insights for precision oncology. This comprehensive approach surpasses existing tools by automating the interpretation of mutations and suggesting potential treatments, thereby striving to bridge the gap between sequencing data and clinical application.
ABSTRACT
We previously reported on the interaction of 10-chloro-7H-benzo[de]benzo[4,5]imidazo[2,1-a]isoquinolin-7-one (10-Cl-BBQ) with the Aryl hydrocarbon Receptor (AhR) and selective growth inhibition in breast cancer cell lines. We now report on a library of BBQ analogues with substituents on the phenyl and naphthyl rings for biological screening. Herein, we show that absence of the phenyl Cl of 10-Cl-BBQ to produce the simple BBQ molecule substantially enhanced the growth inhibitory effect with GI50 values of 0.001-2.1 µM in select breast cancer cell lines MCF-7, T47D, ZR-75-1, SKBR3, MDA-MB-468, BT20, BT474 cells, while having modest effects of 2.1-7 µM in other cell lines including HT29, U87, SJ-G2, A2780, DU145, BE2-C, MIA, MDA-MB-231 or normal breast cells, MCF10A (3.2 µM). The most potent growth inhibitory effect of BBQ was observed in the triple negative cell line, MDA-MB-468 with a GI50 value of 0.001 µM, presenting a 3,200-fold greater response than in the normal MCF10A breast cells. Additions of Cl, CH3, CN to the phenyl ring and ring expansion from benzoimidazole to dihydroquinazoline hindered the growth inhibitory potency of the BBQ analogues by blocking potential sites of CYP1 oxidative metabolism, while addition of Cl or NO2 to the naphthyl rings restored potency. In a cell-based reporter assay all analogues induced 1.2 to 10-fold AhR transcription activation. Gene expression analysis confirmed the induction of CYP1 oxygenases by BBQ. The CYP1 inhibitor α-naphthoflavone, and the SULT1A1 inhibitor quercetin significantly reduced the growth inhibitory effect of BBQ, confirming the importance of both phase I and II metabolic activation for growth inhibition. Conventional molecular modelling/docking revealed no significant differences between the binding poses of the most and least active analogues. More detailed DFT analysis at the DSD-PBEP86/Def-TZVPP level of theory could not identify significant geometric or electronic changes which would account for this varied AhR activation. Generation of Fukui functions at the same level of theory showed that CYP1 metabolism will primarily occur at the phenyl head group of the analogues, and substituents within this ring lead to lower cytotoxicity.
ABSTRACT
BACKGROUND: HIV-1 produces Tat, a crucial protein for transcription, viral replication, and CNS neurotoxicity. Tat interacts with TAR, enhancing HIV reverse transcription. Subtype C Tat variants (C31S, R57S, Q63E) are associated with reduced transactivation and neurovirulence compared to subtype B. However, their precise impact on Tat-TAR binding is unclear. This study investigates how these substitutions affect Tat-TAR interaction. METHODS: We utilized molecular modelling techniques, including MODELLER, to produce precise three-dimensional structures of HIV-1 Tat protein variants. We utilized Tat subtype B as the reference or wild type, and generated Tat variants to mirror those amino acid variants found in Tat subtype C. Subtype C-specific amino acid substitutions were selected based on their role in the neuropathogenesis of HIV-1. Subsequently, we conducted molecular docking of each Tat protein variant to TAR using HDOCK, followed by molecular dynamic simulations. RESULTS: Molecular docking results indicated that Tat subtype B (TatWt) showed the highest affinity for the TAR element (-262.07), followed by TatC31S (-261.61), TatQ63E (-256.43), TatC31S/R57S/Q63E (-238.92), and TatR57S (-222.24). However, binding free energy analysis showed higher affinities for single variants TatQ63E (-349.2 ± 10.4 kcal/mol) and TatR57S (-290.0 ± 9.6 kcal/mol) compared to TatWt (-247.9 ± 27.7 kcal/mol), while TatC31S and TatC31S/R57SQ/63E showed lower values. Interactions over the protein trajectory were also higher for TatQ63E and TatR57S compared to TatWt, TatC31S, and TatC31S/R57SQ/63E, suggesting that modifying amino acids within the Arginine/Glutamine-rich region notably affects TAR interaction. Single amino acid mutations TatR57S and TatQ63E had a significant impact, while TatC31S had minimal effect. Introducing single amino acid variants from TatWt to a more representative Tat subtype C (TatC31S/R57SQ/63E) resulted in lower predicted binding affinity, consistent with previous findings. CONCLUSIONS: These identified amino acid positions likely contribute significantly to Tat-TAR interaction and the differential pathogenesis and neuropathogenesis observed between subtype B and subtype C. Additional experimental investigations should prioritize exploring the influence of these amino acid signatures on TAR binding to gain a comprehensive understanding of their impact on viral transactivation, potentially identifying them as therapeutic targets.
Subject(s)
Amino Acid Substitution , HIV-1 , Molecular Dynamics Simulation , Protein Binding , tat Gene Products, Human Immunodeficiency Virus , tat Gene Products, Human Immunodeficiency Virus/genetics , tat Gene Products, Human Immunodeficiency Virus/metabolism , tat Gene Products, Human Immunodeficiency Virus/chemistry , HIV-1/genetics , HIV-1/classification , HIV-1/metabolism , Humans , Molecular Docking Simulation , HIV Long Terminal Repeat/genetics , Amino Acids/genetics , Amino Acids/metabolism , Models, MolecularABSTRACT
Occupancy of prostate cancer (PCa) cell androgen receptors (AR) signals proliferation, therefore testosterone biosynthesis inhibitors and AR antagonists are important PCa treatments. Conversely, androgen mimics (e.g., prednisone) used in management of PCa might cause proliferation. The balance between PCa proliferation and inhibition predicts treatment success. We used in silico molecular modelling to explore interactions between ARs, androgens (testosterone, dihydrotestosterone (DHT)) and drugs used to treat (bicalutamide) and manage (dexamethasone, prednisone, hydrocortisone) PCa. We found that hydrogen (H-) bonds between testosterone, DHT and Arg752, Asn705 and Thr877 followed by ligand binding cleft hydrophobic interactions signal proliferation, whereas bicalutamide antagonism is via Phe764 interactions. Hydrocortisone, dexamethasone and prednisone H-bond Asn705 and Thr877, but not Arg752 in the absence of a water molecule. Studies with a bicalutamide agonist AR mutation showed different amino acid interactions, indicating testosterone and DHT would not promote proliferation as effectively as via the native receptor. However, hydrocortisone and bicalutamide form Arg752 and Asn705 H-bonds indicating agonism. Our results suggest that as PCa progresses the resulting mutations will change the proliferative response to androgens and their drug mimics, which have implications for the treatment of prostate cancer.
Subject(s)
Prostatic Neoplasms , Receptors, Androgen , Prostatic Neoplasms/metabolism , Prostatic Neoplasms/drug therapy , Prostatic Neoplasms/pathology , Male , Receptors, Androgen/metabolism , Humans , Anilides/pharmacology , Anilides/chemistry , Tosyl Compounds/pharmacology , Tosyl Compounds/chemistry , Tosyl Compounds/metabolism , Computer Simulation , Molecular Docking Simulation , Models, Molecular , Nitriles/chemistry , Nitriles/pharmacology , Nitriles/metabolism , Steroids/metabolism , Steroids/chemistry , Testosterone/metabolism , Testosterone/pharmacology , Protein Binding , Dihydrotestosterone/metabolismABSTRACT
Peptide-based self-assembly has been used to produce a wide range of nanostructures. While most of these systems involve self-assembly of α-peptides, more recently ß-peptides have also been shown to undergo supramolecular self-assembly, and have been used to produce materials for applications in tissue engineering, cell culture and drug delivery. In order to engineer new materials with specific structure and function, theoretical molecular modelling can provide significant insights into the collective balance of non-covalent interactions that drive the self-assembly and determine the structure of the resultant supramolecular materials under different conditions. However, this approach has only recently become feasible for peptide-based self-assembled nanomaterials, particularly those that incorporate non α-amino acids. This perspective provides an overview of the challenges associated with computational modelling of the self-assembly of ß-peptides and the recent success using a combination of experimental and computational techniques to provide insights into the self-assembly mechanisms and fully atomistic models of these new biocompatible materials.
ABSTRACT
This study introduces (S)-Opto-prop-2, a second-generation photoswitchable ligand designed for precise modulation of ß2-adrenoceptor (ß2AR). Synthesised by incorporating an azobenzene moiety with propranolol, (S)-Opto-prop-2 exhibited a high PSScis (photostationary state for cis isomer) percentage (â¼90 %) and a favourable half-life (>10 days), facilitating diverse bioassay measurements. In vitro, the cis-isomer displayed substantially higher ß2AR binding affinity than the trans-isomer (1000-fold), making (S)-Opto-prop-2 one of the best photoswitchable GPCR (G protein-coupled receptor) ligands reported so far. Molecular docking of (S)-Opto-prop-2 in the X-ray structure of propranolol-bound ß2AR followed by site-directed mutagenesis studies, identified D1133.32, N3127.39 and F2896.51 as crucial residues that contribute to ligand-receptor interactions at the molecular level. In vivo efficacy was assessed using a rabbit ocular hypertension model, revealing that the cis isomer mimicked propranolol's effects in reducing intraocular pressure, while the trans isomer was inactive. Dynamic optical modulation of ß2AR by (S)-Opto-prop-2 was demonstrated in two different cAMP bioassays and using live-cell confocal imaging, indicating reversible and dynamic control of ß2AR activity using the new photopharmacology tool. In conclusion, (S)-Opto-prop-2 emerges as a promising photoswitchable ligand for precise and reversible ß2AR modulation with light. The new tool shows superior cis-on binding affinity, one of the largest reported differences in affinity (1000-fold) between its two configurations, in vivo efficacy, and dynamic modulation. This study contributes valuable insights into the evolving field of photopharmacology, offering a potential avenue for targeted therapy in ß2AR-associated pathologies.
Subject(s)
Adrenergic beta-2 Receptor Antagonists , Receptors, Adrenergic, beta-2 , Animals , Humans , Male , Rabbits , Adrenergic beta-2 Receptor Antagonists/pharmacology , Adrenergic beta-2 Receptor Antagonists/chemistry , Adrenergic beta-Antagonists/pharmacology , Adrenergic beta-Antagonists/chemistry , Azo Compounds/chemistry , Azo Compounds/pharmacology , CHO Cells , Cricetulus , HEK293 Cells , Molecular Docking Simulation/methods , Photochemical Processes , Propranolol/pharmacology , Propranolol/chemistry , Receptors, Adrenergic, beta-2/metabolism , Receptors, Adrenergic, beta-2/chemistryABSTRACT
Tumour-derived sialoglycans, bearing the charged nonulosonic sugar sialic acid at their termini, play a critical role in tumour cell adhesion and invasion, as well as evading cell death and immune surveillance. Sialyltransferases (ST), the enzymes responsible for the biosynthesis of sialylated glycans, are highly upregulated in cancer, with tumour hypersialylation strongly correlated with tumour growth, metastasis and drug resistance. As a result, desialylation of the tumour cell surface using either targeted delivery of a pan-ST inhibitor (or sialidase) or systemic delivery of a non-toxic selective ST inhibitors are being pursued as potential new anti-metastatic strategies against multiple cancers including pancreatic, ovarian, breast, melanoma and lung cancer. Herein, we have employed molecular modelling to give insights into the selectivity observed in a series of selective ST inhibitors that incorporate a uridyl ring in place of the cytidine of the natural donor (CMP-Neu5Ac) and replace the charged phosphodiester linker of classical ST inhibitors with a neutral α-hydroxy-1,2,3-triazole linker. The inhibitory activities of the nascent compounds were determined against recombinant human ST enzymes (ST3GAL1, ST6GAL1, ST8SIA2) showing promising activity and selectivity towards specific ST sub-types. Our ST inhibitors are non-toxic and show improved synthetic accessibility and drug-likeness compared to earlier nucleoside-based ST inhibitors.
Subject(s)
Enzyme Inhibitors , Sialyltransferases , Triazoles , beta-Galactoside alpha-2,3-Sialyltransferase , Sialyltransferases/antagonists & inhibitors , Sialyltransferases/metabolism , Humans , Enzyme Inhibitors/pharmacology , Enzyme Inhibitors/chemistry , Enzyme Inhibitors/chemical synthesis , Triazoles/chemistry , Triazoles/pharmacology , Triazoles/chemical synthesis , Structure-Activity Relationship , Molecular Structure , Dose-Response Relationship, Drug , beta-D-Galactoside alpha 2-6-Sialyltransferase , Antigens, CDABSTRACT
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome encodes 29 proteins including four structural, 16 nonstructural (nsps), and nine accessory proteins (https://epimedlab.org/sars-cov-2-proteome/). Many of these proteins contain potential targetable sites for the development of antivirals. Despite the widespread use of vaccinations, the emergence of variants necessitates the investigation of new therapeutics and antivirals. Here, the EpiMed Coronabank Chemical Collection (https://epimedlab.org/crl/) was utilized to investigate potential antivirals against the nsp14 exoribonuclease (ExoN) domain. Molecular docking was performed to evaluate the binding characteristics of our chemical library against the nsp14 ExoN site. Based on the initial screen, trisjuglone, ararobinol, corilagin, and naphthofluorescein were identified as potential lead compounds. Molecular dynamics (MD) simulations were subsequently performed, with the results highlighting the stability of the lead compounds in the nsp14 ExoN site. Protein-RNA docking revealed the potential for the lead compounds to disrupt the interaction with RNA when bound to the ExoN site. Moreover, hypericin, cyanidin-3-O-glucoside, and rutin were previously identified as lead compounds targeting the papain-like protease (PLpro) naphthalene binding site. Through performing MD simulations, the stability and interactions of lead compounds with PLpro were further examined. Overall, given the critical role of the exonuclease activity of nsp14 in ensuring viral fidelity and the multifunctional role of PLpro in viral pathobiology and replication, these nsps represent important targets for antiviral drug development. Our databases can be utilized for in silico studies, such as the ones performed here, and this approach can be applied to other potentially druggable SARS-CoV-2 protein targets.
Subject(s)
Antiviral Agents , Molecular Docking Simulation , SARS-CoV-2 , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Binding Sites , SARS-CoV-2/drug effects , Humans , Exoribonucleases/metabolism , Exoribonucleases/chemistry , Viral Nonstructural Proteins/chemistry , Viral Nonstructural Proteins/antagonists & inhibitors , Viral Nonstructural Proteins/metabolism , Viral Nonstructural Proteins/genetics , Naphthalenes/chemistry , Naphthalenes/pharmacology , Protein Binding , COVID-19 Drug Treatment , Small Molecule Libraries/chemistry , Small Molecule Libraries/pharmacology , Molecular Dynamics Simulation , Protein DomainsABSTRACT
Ion-specific effects on aqueous solvation of monovalent counter ions, Na + ${^+ }$ , K + ${^+ }$ , Cl - ${^- }$ , and Br - ${^- }$ , and two model polyelectrolytes (PEs), poly(styrene sulfonate) (PSS) and poly(diallyldimethylammonium) (PDADMA) were here studied with ab initio molecular dynamics (AIMD) and classical molecular dynamics (MD) simulations based on the OPLS-aa force-field which is an empirical fixed point-charge force-field. Ion-specific binding to the PE charge groups was also characterized. Both computational methods predict similar response for the solvation of the PEs but differ notably in description of ion solvation. Notably, AIMD captures the experimentally observed differences in Cl - ${^- }$ and Br - ${^- }$ anion solvation and binding with the PEs, while the classical MD simulations fail to differentiate the ion species response. Furthermore, the findings show that combining AIMD with the computationally less costly classical MD simulations allows benefiting from both the increased accuracy and statistics reach.
ABSTRACT
Plakophilin 1 (PKP1), a member of the p120ctn subfamily of the armadillo (ARM)-repeat-containing proteins, is an important structural component of cell-cell adhesion scaffolds although it can also be ubiquitously found in the cytoplasm and the nucleus. RYBP (RING 1A and YY1 binding protein) is a multifunctional intrinsically disordered protein (IDP) best described as a transcriptional regulator. Both proteins are involved in the development and metastasis of several types of tumors. We studied the binding of the armadillo domain of PKP1 (ARM-PKP1) with RYBP by using in cellulo methods, namely immunofluorescence (IF) and proximity ligation assay (PLA), and in vitro biophysical techniques, namely fluorescence, far-ultraviolet (far-UV) circular dichroism (CD), and isothermal titration calorimetry (ITC). We also characterized the binding of the two proteins by using in silico experiments. Our results showed that there was binding in tumor and non-tumoral cell lines. Binding in vitro between the two proteins was also monitored and found to occur with a dissociation constant in the low micromolar range (~10 µM). Finally, in silico experiments provided additional information on the possible structure of the binding complex, especially on the binding ARM-PKP1 hot-spot. Our findings suggest that RYBP might be a rescuer of the high expression of PKP1 in tumors, where it could decrease the epithelial-mesenchymal transition in some cancer cells.
Subject(s)
Intrinsically Disordered Proteins , Plakophilins , Protein Binding , Humans , Plakophilins/metabolism , Plakophilins/genetics , Plakophilins/chemistry , Intrinsically Disordered Proteins/metabolism , Intrinsically Disordered Proteins/chemistry , Intrinsically Disordered Proteins/genetics , Repressor Proteins/metabolism , Repressor Proteins/chemistry , Repressor Proteins/genetics , Armadillo Domain Proteins/metabolism , Armadillo Domain Proteins/chemistry , Armadillo Domain Proteins/genetics , Protein Domains , Circular DichroismABSTRACT
BACKGROUND: Irritable bowel syndrome (IBS) is one of the most frequent and debilitating conditions leading to gastroenterological referrals. However, recommended treatments remain limited, yielding only limited therapeutic gains. Chitin-glucan (CG) is a novel dietary prebiotic classically used in humans at a dosage of 1.5-3.0 g/d and is considered a safe food ingredient by the European Food Safety Authority. To provide an alternative approach to managing patients with IBS, we performed preclinical molecular, cellular, and animal studies to evaluate the role of chitin-glucan in the main pathophysiological mechanisms involved in IBS. AIM: To evaluate the roles of CG in visceral analgesia, intestinal inflammation, barrier function, and to develop computational molecular models. METHODS: Visceral pain was recorded through colorectal distension (CRD) in a model of long-lasting colon hypersensitivity induced by an intra-rectal administration of TNBS [15 milligrams (mg)/kilogram (kg)] in 33 Sprague-Dawley rats. Intracolonic pressure was regularly assessed during the 9 wk-experiment (weeks 0, 3, 5, and 7) in animals receiving CG (n = 14) at a human equivalent dose (HED) of 1.5 g/d or 3.0 g/d and compared to negative control (tap water, n = 11) and positive control (phloroglucinol at 1.5 g/d HED, n = 8) groups. The anti-inflammatory effect of CG was evaluated using clinical and histological scores in 30 C57bl6 male mice with colitis induced by dextran sodium sulfate (DSS) administered in their drinking water during 14 d. HT-29 cells under basal conditions and after stimulation with lipopolysaccharide (LPS) were treated with CG to evaluate changes in pathways related to analgesia (µ-opioid receptor (MOR), cannabinoid receptor 2 (CB2), peroxisome proliferator-activated receptor alpha, inflammation [interleukin (IL)-10, IL-1b, and IL-8] and barrier function [mucin 2-5AC, claudin-2, zonula occludens (ZO)-1, ZO-2] using the real-time PCR method. Molecular modelling of CG, LPS, lipoteichoic acid (LTA), and phospholipomannan (PLM) was developed, and the ability of CG to chelate microbial pathogenic lipids was evaluated by docking and molecular dynamics simulations. Data were expressed as the mean ± SEM. RESULTS: Daily CG orally-administered to rats or mice was well tolerated without including diarrhea, visceral hypersensitivity, or inflammation, as evaluated at histological and molecular levels. In a model of CRD, CG at a dosage of 3 g/d HED significantly decreased visceral pain perception by 14% after 2 wk of administration (P < 0.01) and reduced inflammation intensity by 50%, resulting in complete regeneration of the colonic mucosa in mice with DSS-induced colitis. To better reproduce the characteristics of visceral pain in patients with IBS, we then measured the therapeutic impact of CG in rats with TNBS-induced inflammation to long-lasting visceral hypersensitivity. CG at a dosage of 1.5 g/d HED decreased visceral pain perception by 20% five weeks after colitis induction (P < 0.01). When the CG dosage was increased to 3.0 g/d HED, this analgesic effect surpassed that of the spasmolytic agent phloroglucinol, manifesting more rapidly within 3 wk and leading to a 50% inhibition of pain perception (P < 0.0001). The underlying molecular mechanisms contributing to these analgesic and anti-inflammatory effects of CG involved, at least in part, a significant induction of MOR, CB2 receptor, and IL-10, as well as a significant decrease in pro-inflammatory cytokines IL-1b and IL-8. CG also significantly upregulated barrier-related genes including muc5AC, claudin-2, and ZO-2. Molecular modelling of CG revealed a new property of the molecule as a chelator of microbial pathogenic lipids, sequestering gram-negative LPS and gram-positive LTA bacterial toxins, as well as PLM in fungi at the lowesr energy conformations. CONCLUSION: CG decreased visceral perception and intestinal inflammation through master gene regulation and direct binding of microbial products, suggesting that CG may constitute a new therapeutic strategy for patients with IBS or IBS-like symptoms.
Subject(s)
Chitin , Colon , Disease Models, Animal , Glucans , Irritable Bowel Syndrome , Rats, Sprague-Dawley , Visceral Pain , Animals , Irritable Bowel Syndrome/drug therapy , Irritable Bowel Syndrome/physiopathology , Male , Humans , Colon/drug effects , Colon/pathology , Rats , Visceral Pain/drug therapy , Visceral Pain/physiopathology , Visceral Pain/metabolism , Visceral Pain/etiology , Chitin/pharmacology , Glucans/pharmacology , Glucans/administration & dosage , Mice , Prebiotics/administration & dosage , Trinitrobenzenesulfonic Acid/toxicity , Intestinal Mucosa/drug effects , Intestinal Mucosa/pathology , Intestinal Mucosa/metabolism , Colitis/drug therapy , Colitis/chemically induced , Colitis/physiopathology , Colitis/pathology , HT29 CellsABSTRACT
Spectroscopic, biochemical, and computational modelling studies have been used to assess the binding capability of a set of minor groove binding (MGB) ligands against the self-complementary DNA sequences 5'-d(CGCACTAGTGCG)-3' and 5'-d(CGCAGTACTGCG)-3'. The ligands were carefully designed to target the DNA response element, 5'-WGWWCW-3', the binding site for several nuclear receptors. Basic 1D 1H NMR spectra of the DNA samples prepared with three MGB ligands show subtle variations suggestive of how each ligand associates with the double helical structure of both DNA sequences. The variations among the investigated ligands were reflected in the line shape and intensity of 1D 1H and 31P-{1H} NMR spectra. Rapid visual inspection of these 1D NMR spectra proves to be beneficial in providing valuable insights on MGB binding molecules. The NMR results were consistent with the findings from both UV DNA denaturation and molecular modelling studies. Both the NMR spectroscopic and computational analyses indicate that the investigated ligands bind to the minor grooves as antiparallel side-by-side dimers in a head-to-tail fashion. Moreover, comparisons with results from biochemical studies offered valuable insights into the mechanism of action, and antitumor activity of MGBs in relation to their structures, essential pre-requisites for future optimization of MGBs as therapeutic agents.
Subject(s)
DNA , DNA/chemistry , DNA/metabolism , Ligands , Humans , Antineoplastic Agents/chemistry , Antineoplastic Agents/pharmacology , Molecular Structure , Nucleic Acid Conformation , Binding Sites , Structure-Activity Relationship , Models, Molecular , Dose-Response Relationship, Drug , Magnetic Resonance Spectroscopy , Cell Line, TumorABSTRACT
COVID-19, the infectious disease caused by the most recently discovered coronavirus SARS- CoV-2, has caused millions of sick people and thousands of deaths all over the world. The viral positive-sense single-stranded RNA encodes 31 proteins among which the spike (S) is undoubtedly the best known. Recently, protein E has been reputed as a potential pharmacological target as well. It is essential for the assembly and release of the virions in the cell. Literature describes protein E as a voltage-dependent channel with preference towards monovalent cations whose intracellular expression, though, alters Ca2+ homeostasis and promotes the activation of the proinflammatory cascades. Due to the extremely high sequence identity of SARS-CoV-2 protein E (E-2) with the previously characterized E-1 (i.e., protein E from SARS-CoV) many data obtained for E-1 were simply adapted to the other. Recent solid state NMR structure revealed that the transmembrane domain (TMD) of E-2 self-assembles into a homo-pentamer, albeit the oligomeric status has not been validated with the full-length protein. Prompted by the lack of a common agreement on the proper structural and functional features of E-2, we investigated the specific mechanism/s of pore-gating and the detailed molecular structure of the most cryptic protein of SARS-CoV-2 by means of MD simulations of the E-2 structure and by expressing, refolding and analyzing the electrophysiological activity of the transmembrane moiety of the protein E-2, in its full length. Our results show a clear agreement between experimental and predictive studies and foresee a mechanism of activity based on Ca2+ affinity.
ABSTRACT
The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron-sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron-sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron-sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron-sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix.