Ellagic acid: A potent glyoxalase-I inhibitor with a unique scaffold

AbstractThe glyoxalase system, particularly glyoxalase-I (GLO-I), has been approved as a potential target for cancer treatment. In this study, a set of structurally diverse polyphenolic natural compounds were investigated as potential GLO-I inhibitors. Ellagic acid was found, computationally and experimentally, to be the most potent GLO-I inhibitor among the tested compounds which showed an IC50 of 0.71 mmol L−1. Its binding to the GLO-I active site seemed to be mainly driven by ionic interaction via its ionized hydroxyl groups with the central Zn ion and Lys156, along with other numerous hydrogen bonding and hydrophobic interactions. Due to its unique and rigid skeleton, it can be utilized to search for other novel and potent GLO-I inhibitors via computational approaches such as pharmacophore modeling and similarity search methods. Moreover, an inspection of the docked poses of the tested compounds showed that chlorogenic acid and dihydrocaffeic acid could be considered as lead compounds worthy of further optimization.

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Exploration of Novel Xanthine Oxidase Inhibitors Based on 1,6-Dihydropyrimidine-5-Carboxylic Acids by an Integrated in Silico Study

International Journal of Molecular Sciences ◽

10.3390/ijms22158122 ◽

2021 ◽

Vol 22 (15) ◽

pp. 8122

Author(s):

Na Zhai ◽

Chenchen Wang ◽

Fengshou Wu ◽

Liwei Xiong ◽

Xiaogang Luo ◽

...

Keyword(s):

Xanthine Oxidase ◽

Carboxylic Acids ◽

Hydrophobic Interactions ◽

Pharmacophore Model ◽

3D Qsar ◽

Md Simulations ◽

Pharmacophore Modeling ◽

Binding Modes ◽

Comfa Model ◽

Validation Parameters

Xanthine oxidase (XO) is an important target for the effective treatment of hyperuricemia-associated diseases. A series of novel 2-substituted 6-oxo-1,6-dihydropyrimidine-5-carboxylic acids (ODCs) as XO inhibitors (XOIs) with remarkable activities have been reported recently. To better understand the key pharmacological characteristics of these XOIs and explore more hit compounds, in the present study, the three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking, pharmacophore modeling, and molecular dynamics (MD) studies were performed on 46 ODCs. The constructed 3D-QSAR models exhibited reliable predictability with satisfactory validation parameters, including q2 = 0.897, R2 = 0.983, rpred2 = 0.948 in a CoMFA model, and q2 = 0.922, R2 = 0.990, rpred2 = 0.840 in a CoMSIA model. Docking and MD simulations further gave insights into the binding modes of these ODCs with the XO protein. The results indicated that key residues Glu802, Arg880, Asn768, Thr1010, Phe914, and Phe1009 could interact with ODCs by hydrogen bonds, π-π stackings, or hydrophobic interactions, which might be significant for the activity of these XOIs. Four potential hits were virtually screened out using the constructed pharmacophore model in combination with molecular dockings and ADME predictions. The four hits were also found to be relatively stable in the binding pocket by MD simulations. The results in this study might provide effective information for the design and development of novel XOIs.

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Pharmacophore modeling, virtual computational screening and biological evaluation studies

10.7287/peerj.preprints.2721 ◽

2017 ◽

Author(s):

Serena Dotolo ◽

Angelo Facchiano

Keyword(s):

Molecular Mechanisms ◽

Prediction Models ◽

Pharmacophore Modeling ◽

Biological Evaluation ◽

Bioactive Molecules ◽

Investigational Drug ◽

Discovery Studio ◽

Lead Compounds ◽

Computational Screening ◽

Computational Strategy

Drug discovery process plays an important role in identifying new investigational drug-likes and developing new potential inhibitors related to a determinate target, in biopharmaceutical field [1]. An alternative promising and efficient used to identify new active substances is Pharmacophore modeling method.We defined a new computational strategy protocol characterized by the use of bioinformatics online tools and by the application of locally installed tools, for lead candidates generation-optimization able to reduce the cycle time and cost of this process and to promote the next steps of study [2].Hence, we have tried to apply this new computational procedure, in a more detailed screening, of small bioactive molecules, searching and identifying new candidates as “lead compounds”, potentially able to inhibit biological target AKT1 human protein and its related molecular mechanisms [3].The workflow executed in our work has been characterized by a multi-step design, which concerns different topics: search in PDB database of a model structure for AKT1, pharmacophore modeling and virtual computational screening, biological evaluation divided in two parts (molecular validation of selected compounds and study of physical-chemical properties related to pharmacokinetic/pharmacodynamics prediction models). All these step have been performed through PHARMIT (http://pharmit.csb.pitt.edu) and Discovery Studio 4.5 platform.We selected the PDB structure 3O96 as the reference complex (protein-ligand), and we analyzed it by means of PHARMIT and Discovery Studio, to generate four different “pharmacophore models” with four different list of natural compounds.It is performed a thorough screening of compounds applying several filters, to find some good candidates as possible natural AKT1 allosteric inhibitors.The compounds that match a well-defined pharmacophore have been analyzed through direct molecular docking, for selecting only the best candidates and studying the protein-ligand interactions. Selected compounds have been investigated in more details, to trace their origin, by their chemical-physical properties.This information can help us to predict some plausible enzyme-catalyzed reaction pathways, through PathPred web-server and KEGG compound database, in order to highlight the most important reactions for biosynthesis of compounds and obtain PharmacoKinetics/PharmacoDynamics (PK/PD) models, to investigate the ADMET properties of these lead compounds and to study their behavior in some biological systems, for the next experimental assays.This new computational strategy has been very efficient in showing what could be good “lead compounds” and potential natural inhibitors of AKT1 and PI3K/AKT1 signaling cascade. Therefore, the next steps could be the experimental analysis of pharmacokinetics-pharmacodynamics and toxicity properties “in vitro/in vivo”, in order to evaluate the results obtained “in silico”.

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The potential of magnetisation transfer NMR to monitor the dissolution process of cellulose in cold alkali

Cellulose ◽

10.1007/s10570-019-02728-y ◽

2019 ◽

Vol 26 (18) ◽

pp. 9403-9412 ◽

Cited By ~ 1

Author(s):

Maria Gunnarsson ◽

Merima Hasani ◽

Diana Bernin

Keyword(s):

Hydrophobic Interactions ◽

Dissolution Process ◽

Mechanistic Study ◽

Dissolution Mechanism ◽

Hydroxyl Groups ◽

Similar Amount ◽

Magnetisation Transfer ◽

Promising Alternative ◽

Nmr Methods ◽

Increasing Temperature

Abstract Cellulose is the most important biopolymer on earth and, when derived from e.g. wood, a promising alternative to for example cotton, which exhibits a large environmental burden. The replacement depends, however, on an efficient dissolution process of cellulose. Cold aqueous alkali systems are attractive but these solvents have peculiarities, which might be overcome by understanding the acting mechanisms. Proposed dissolution mechanisms are for example the breakage of hydrophobic interactions and partly deprotonation of the cellulose hydroxyl groups. Here, we performed a mechanistic study using equimolar aqueous solutions of LiOH, NaOH and KOH to elucidate the dissolution process of microcrystalline cellulose (MCC). The pH was the highest for KOH(aq) followed by NaOH(aq) and LiOH(aq). We used a combination of conventional and advanced solution-state NMR methods to monitor the dissolution process of MCC by solely increasing the temperature from − 10 to 5 °C. KOH(aq) dissolved roughly 25% of the maximum amount of MCC while NaOH(aq) and LiOH(aq) dissolved up to 70%. Water motions on nanoscale timescales present in non-frozen water, remained unaffected on the addition of MCC. Magnetisation transfer (MT) NMR experiments monitored the semi-rigid MCC as a function of temperature. Interestingly, although NaOH(aq) and LiOH(aq) were able to dissolve a similar amount at 5 °C, MT spectra revealed differences with increasing temperature, suggesting a difference in the swollen state of MCC in LiOH(aq) already at − 10 °C. Furthermore, MT NMR shows a great potential to study the water exchange dynamics with the swollen and semi-rigid MCC fraction in these systems, which might give valuable insights into the dissolution mechanism in cold alkali.

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Ellagic Acid Derivatives from Syzygium cumini Stem Bark: Investigation of their Antiplasmodial Activity

Natural Product Communications ◽

10.1177/1934578x0900401012 ◽

2009 ◽

Vol 4 (10) ◽

pp. 1934578X0900401 ◽

Cited By ~ 3

Author(s):

Claudia A. Simões-Pires ◽

Sandra Vargas ◽

Andrew Marston ◽

Jean-Robert Ioset ◽

Marçal Q. Paulo ◽

...

Keyword(s):

Mechanism Of Action ◽

Ellagic Acid ◽

Stem Bark ◽

Antimalarial Drugs ◽

Antiplasmodial Activity ◽

Hydroxyl Groups ◽

Syzygium Cumini ◽

Free Hydroxyl ◽

Ellagic Acid Derivatives

Bioguided fractionation of Syzygium cumini (Myrtaceae) bark decoction for antiplasmodial activity was performed, leading to the isolation of three known ellagic acid derivatives (ellagic acid, ellagic acid 4-O-α-L-2″-acetylrhamnopyranoside, 3-O-methylellagic acid 3′-O-α-L-rhamnopyranoside), as well as the new derivative 3-O-methylellagic acid 3′-O-β-D-glucopyranoside. Activity investigation was based on the reduction of P. falciparum (PfK1) parasitaemia in vitro and the inhibition of β-hematin formation, a known mechanism of action of some antimalarial drugs. Among the investigated ellagic acid derivatives, only ellagic acid was able to reduce P. falciparum parasitaemia in vitro and inhibit β-hematin formation, suggesting that free hydroxyl groups are necessary for activity within this class of compounds.

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Strategy for Designing Selective Lysosomal Acid α-Glucosidase Inhibitors: Binding Orientation and Influence on Selectivity

Molecules ◽

10.3390/molecules25122843 ◽

2020 ◽

Vol 25 (12) ◽

pp. 2843 ◽

Cited By ~ 1

Author(s):

Atsushi Kato ◽

Izumi Nakagome ◽

Mizuki Hata ◽

Robert J. Nash ◽

George W. J. Fleet ◽

...

Keyword(s):

Alkyl Chain ◽

Hydrophobic Interactions ◽

Antiviral Agents ◽

Design Strategy ◽

Docking Study ◽

Piperidine Ring ◽

Hydroxyl Groups ◽

Storage Site ◽

Molecular Docking Study ◽

Lysosomal Acid

Deoxynojirimycin (DNJ) is the archetypal iminosugar, in which the configuration of the hydroxyl groups in the piperidine ring truly mimic those of d-glucopyranose; DNJ and derivatives have beneficial effects as therapeutic agents, such as anti-diabetic and antiviral agents, and pharmacological chaperones for genetic disorders, because they have been shown to inhibit α-glucosidases from various sources. However, attempts to design a better molecule based solely on structural similarity cannot produce selectivity between α-glucosidases that are localized in multiple organs and tissues, because the differences of each sugar-recognition site are very subtle. In this study, we provide the first example of a design strategy for selective lysosomal acid α-glucosidase (GAA) inhibitors focusing on the alkyl chain storage site. Our design of α-1-C-heptyl-1,4-dideoxy-1,4-imino-l-arabinitol (LAB) produced a potent inhibitor of the GAA, with an IC50 value of 0.44 µM. It displayed a remarkable selectivity toward GAA (selectivity index value of 168.2). A molecular dynamic simulation study revealed that the ligand-binding conformation stability gradually improved with increasing length of the α-1-C-alkyl chain. It is noteworthy that α-1-C-heptyl-LAB formed clearly different interactions from DNJ and had favored hydrophobic interactions with Trp481, Phe525, and Met519 at the alkyl chain storage pocket of GAA. Moreover, a molecular docking study revealed that endoplasmic reticulum (ER) α-glucosidase II does not have enough space to accommodate these alkyl chains. Therefore, the design strategy focusing on the shape and acceptability of long alkyl chain at each α-glucosidase may lead to the creation of more selective and practically useful inhibitors.

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Preliminary Characterization of a Ni2+-Activated and Mycothiol-Dependent Glyoxalase I Enzyme from Streptomyces coelicolor

Inorganics ◽

10.3390/inorganics7080099 ◽

2019 ◽

Vol 7 (8) ◽

pp. 99 ◽

Cited By ~ 1

Author(s):

Uthaiwan Suttisansanee ◽

John F. Honek

Keyword(s):

Leishmania Major ◽

Homo Sapiens ◽

Streptomyces Coelicolor ◽

Glyoxalase I ◽

Glyoxalase System ◽

Genetic Studies ◽

Preliminary Characterization ◽

Glyoxalase Ii ◽

Activation Profile

The glyoxalase system consists of two enzymes, glyoxalase I (Glo1) and glyoxalase II (Glo2), and converts a hemithioacetal substrate formed between a cytotoxic alpha-ketoaldehyde, such as methylglyoxal (MG), and an intracellular thiol, such as glutathione, to a non-toxic alpha-hydroxy acid, such as d-lactate, and the regenerated thiol. Two classes of Glo1 have been identified. The first is a Zn2+-activated class and is exemplified by the Homo sapiens Glo1. The second class is a Ni2+-activated enzyme and is exemplified by the Escherichia coli Glo1. Glutathione is the intracellular thiol employed by Glo1 from both these sources. However, many organisms employ other intracellular thiols. These include trypanothione, bacillithiol, and mycothiol. The trypanothione-dependent Glo1 from Leishmania major has been shown to be Ni2+-activated. Genetic studies on Bacillus subtilis and Corynebacterium glutamicum focused on MG resistance have indicated the likely existence of Glo1 enzymes employing bacillithiol or mycothiol respectively, although no protein characterizations have been reported. The current investigation provides a preliminary characterization of an isolated mycothiol-dependent Glo1 from Streptomyces coelicolor. The enzyme has been determined to display a Ni2+-activation profile and indicates that Ni2+-activated Glo1 are indeed widespread in nature regardless of the intracellular thiol employed by an organism.

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Combination of pharmacophore modeling and 3D-QSAR analysis of potential glyoxalase-I inhibitors as anticancer agents

Computational Biology and Chemistry ◽

10.1016/j.compbiolchem.2019.03.011 ◽

2019 ◽

Vol 80 ◽

pp. 102-110 ◽

Cited By ~ 7

Author(s):

Mahmoud A. Al-Sha'er ◽

Qosay A. Al-Balas ◽

Mohammad A. Hassan ◽

Ghazi A. Al Jabal ◽

Ammar M. Almaaytah

Keyword(s):

Anticancer Agents ◽

3D Qsar ◽

Pharmacophore Modeling ◽

Glyoxalase I ◽

Qsar Analysis

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Glyoxalase I – structure, function and a critical role in the enzymatic defence against glycation

Biochemical Society Transactions ◽

10.1042/bst0311343 ◽

2003 ◽

Vol 31 (6) ◽

pp. 1343-1348 ◽

Cited By ~ 411

Author(s):

P.J. Thornalley

Keyword(s):

Metal Ion ◽

Catalytic Mechanism ◽

Critical Role ◽

Glyoxalase I ◽

Water Molecules ◽

Glyoxalase System ◽

E Coli ◽

Antimalarial Agents

Glyoxalase I is part of the glyoxalase system present in the cytosol of cells. The glyoxalase system catalyses the conversion of reactive, acyclic α-oxoaldehydes into the corresponding α-hydroxyacids. Glyoxalase I catalyses the isomerization of the hemithioacetal, formed spontaneously from α-oxoaldehyde and GSH, to S-2-hydroxyacylglutathione derivatives [RCOCH(OH)-SG→RCH(OH)CO-SG], and in so doing decreases the steady-state concentrations of physiological α-oxoaldehydes and associated glycation reactions. Physiological substrates of glyoxalase I are methylglyoxal, glyoxal and other acyclic α-oxoaldehydes. Human glyoxalase I is a dimeric Zn2+ metalloenzyme of molecular mass 42 kDa. Glyoxalase I from Escherichia coli is a Ni2+ metalloenzyme. The crystal structures of human and E. coli glyoxalase I have been determined to 1.7 and 1.5 Å resolution. The Zn2+ site comprises two structurally equivalent residues from each domain – Gln-33A, Glu-99A, His-126B, Glu-172B and two water molecules. The Ni2+ binding site comprises His-5A, Glu-56A, His-74B, Glu-122B and two water molecules. The catalytic reaction involves base-catalysed shielded-proton transfer from C-1 to C-2 of the hemithioacetal to form an ene-diol intermediate and rapid ketonization to the thioester product. R- and S-enantiomers of the hemithioacetal are bound in the active site, displacing the water molecules in the metal ion primary co-ordination shell. It has been proposed that Glu-172 is the catalytic base for the S-substrate enantiomer and Glu-99 the catalytic base for the R-substrate enantiomer; Glu-172 then reprotonates the ene-diol stereospecifically to form the R-2-hydroxyacylglutathione product. By analogy with the human enzyme, Glu-56 and Glu-122 may be the bases involved in the catalytic mechanism of E. coli glyoxalase I. The suppression of α-oxoaldehyde-mediated glycation by glyoxalase I is particularly important in diabetes and uraemia, where α-oxoaldehyde concentrations are increased. Decreased glyoxalase I activity in situ due to the aging process and oxidative stress results in increased glycation and tissue damage. Inhibition of glyoxalase I pharmacologically with specific inhibitors leads to the accumulation of α-oxoaldehydes to cytotoxic levels; cell-permeable glyoxalase I inhibitors are antitumour and antimalarial agents. Glyoxalase I has a critical role in the prevention of glycation reactions mediated by methylglyoxal, glyoxal and other α-oxoaldehydes in vivo.

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Molecular insight into isoform specific inhibition of PI3K-α and PKC-η with dietary agents through an ensemble pharmacophore and docking studies

Scientific Reports ◽

10.1038/s41598-021-90287-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Baki Vijaya Bhaskar ◽

Aluru Rammohan ◽

Tirumalasetty Munichandra Babu ◽

Gui Yu Zheng ◽

Weibin Chen ◽

...

Keyword(s):

Binding Energy ◽

Anticancer Agents ◽

Drug Targets ◽

Binding Pocket ◽

Pharmacophore Modeling ◽

Boswellic Acid ◽

Lead Compounds ◽

Donor And Acceptor ◽

In Silico Studies ◽

Dietary Agents

AbstractDietary compounds play an important role in the prevention and treatment of many cancers, although their specific molecular mechanism is not yet known. In the present study, thirty dietary agents were analyzed on nine drug targets through in silico studies. However, nine dietary scaffolds, such as silibinin, flavopiridol, oleandrin, ursolic acid, α-boswellic acid, β-boswellic acid, triterpenoid, guggulsterone, and oleanolic acid potentially bound to the cavity of PI3K-α, PKC-η, H-Ras, and Ras with the highest binding energy. Particularly, the compounds silibinin and flavopiridol have been shown to have broad spectrum anticancer activity. Interestingly, flavopiridol was embedded in the pockets of PI3K-α and PKC-η as bound crystal inhibitors in two different conformations and showed significant interactions with ATP binding pocket residues. However, complex-based pharmacophore modeling achieved two vital pharmacophoric features namely, two H-bond acceptors for PI3K-α, while three are hydrophobic, one cat-donor and one H-bond donor and acceptor for PKC-η, respectively. The database screening with the ChemBridge core library explored potential hits on a valid pharmacophore query. Therefore, to optimize perspective lead compounds from the hits, which were subjected to various constraints such as docking, MM/GBVI, Lipinski rule of five, ADMET and toxicity properties. Henceforth, the top ligands were sorted out and examined for vital interactions with key residues, arguably the top three promising lead compounds for PI3K-α, while seven for PKC-η, exhibiting binding energy from − 11.5 to − 8.5 kcal mol−1. Therefore, these scaffolds could be helpful in the development of novel class of effective anticancer agents.

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Drug discovery by integration of pharmacophore modeling, virtual screening and biological evaluation by means of bioinformatics resources

10.7287/peerj.preprints.2639v1 ◽

2016 ◽

Author(s):

Serena Dotolo ◽

Angelo Facchiano

Keyword(s):

Molecular Dynamics ◽

Drug Discovery ◽

Virtual Screening ◽

Development Process ◽

Chemical Space ◽

Pharmacophore Modeling ◽

Biological Evaluation ◽

Lead Compounds ◽

Computational Screening ◽

Computational Strategy

Drug discovery is a step-by-step process very important in biopharmaceutical field. We are interested in identifying new investigational drug-likes as potential inhibitors of determinate biological-therapeutic targets, trying to decrease the side effects and to safeguard the human health. However, it is a long and very expensive process. Therefore, we are using a new computational strategy, based on Pharmacophore modeling, to select bioactive substances (natural or synthetic), through the integration of bioinformatics online tools and local resource and platforms, in order to include into the strategy also knowledge from high-throughput studies, for new potential lead compounds generation-optimization, trying to accelerate the early phase of the drug development process. The protocol of this new computational strategy is characterized by a multi-step design focused on: 1) screening in RCSB-PDB for a crystal structure of a specific biological target, suitable for the following steps; 2) pharmacophore modeling and virtual computational screening, by using public domain databases of bioactive compounds, as the ZINC12 database [5], in order to find a promising molecule that could become a new potential medicine. 3) molecular and biological evaluation, to check the compounds selected by virtual screening, for their biological properties through public databases, as PubChem Compound, SciFinder, and Chemicalize to trace their origin and underline their most important physical-chemical features, PathPred (an enzyme-catalyzed metabolic pathway predictor server) to highlight and identify their biosynthetic-metabolic pathways and investigating the biotransformation of best candidates, analyzing their metabolites and their potential biological activity. Moreover, ADMET/toxicity predictor server applying the Lipinski-Veber filter are used to calculate the bioavailability the ADMET/toxicity properties. After this check, only molecules with good bioavailability, good predicted activity and good ADMET properties are considered as hits compounds or drug-likes to direct the design of next experimental assays [6]. Finally, the lead compounds selected are analyzed through molecular dynamics simulations. 4) simulations of molecular dynamics on the best lead compounds, to investigate atomic details of protein-compound molecular interactions in different conditions (different organic solutions, organisms and systems). REFERENCES [1] Dubey A, Facchiano A, Ramteke PW, Marabotti A. “In silico approach to find chymase inhibitors among biogenic compounds.” Future Med Chem. 2016; 8(8):841-51 [2] Dubey A, Marabotti A, Ramteke PW, Facchiano A. "Interaction of human chymase with ginkgolides, terpene trilactones of Ginkgo biloba investigated by molecular docking simulations.” Biochem Biophys Res Commun. 2016; 473(2):449-54. [3] Katara P. “Role of bioinformatics and pharmacogenomics in drug discovery and development process”. Netw Model Anal Health Inform Bioinforma 2013; 2: 225-230. [4] Sunseri J. and Koes D. R. “Pharmit: Interactive Exploration of Chemical Space”.Nucl. Acids Res. 2016; 44(W1): W442-448. [5] Irwin J.J. and Shoichet B.K. “ZINC- A free database of Commercially Available Compounds for Virtual Screening”. J.Chem.Inf.Model. 2005; 45: 177-182. [6] Kaserer T., Beck K. R., Akram M., Odermatt A., Schuster D. “Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Application Exemplified on Hydroxysteroid Dehydrogenases”.Molecules 2015; 20: 22799–22832.

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