Displaying publications 81 - 100 of 256 in total

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  1. Converting differential-equation models of biological systems to membrane computing
    Muniyandi RC, Zin AM, Sanders JW
    Biosystems, 2013 Dec;114(3):219-26.
    PMID: 24120990 DOI: 10.1016/j.biosystems.2013.09.008
    This paper presents a method to convert the deterministic, continuous representation of a biological system by ordinary differential equations into a non-deterministic, discrete membrane computation. The dynamics of the membrane computation is governed by rewrite rules operating at certain rates. That has the advantage of applying accurately to small systems, and to expressing rates of change that are determined locally, by region, but not necessary globally. Such spatial information augments the standard differentiable approach to provide a more realistic model. A biological case study of the ligand-receptor network of protein TGF-β is used to validate the effectiveness of the conversion method. It demonstrates the sense in which the behaviours and properties of the system are better preserved in the membrane computing model, suggesting that the proposed conversion method may prove useful for biological systems in particular.
    Matched MeSH terms: Ligands
  2. Fulltext Docking Studies and Molecular Dynamics Simulation of Ipomoea batatas L. Leaves Compounds as Lipoxygenase (LOX) Inhibitor
    Yeni Y, Supandi S, Dwita LP, Suswandari S, Shaharun MS, Sambudi NS
    J Pharm Bioallied Sci, 2020 Nov;12(Suppl 2):S836-S840.
    PMID: 33828386 DOI: 10.4103/jpbs.JPBS_103_20
    Background: Inflammatory mediators produced by cyclooxygenase (COX) and lipoxygenase (LOX) pathways are responsible for many human diseases, such as cancer, arthritis, and neurological disorders. Flavonoid-containing plants, such as Ipomoea batatas leaves, have shown potential anti-inflammatory activity.

    Objectives: This study aimed to predict the actions of 10 compounds in I. batatas leaves, which are YGM-0a [cyanidin 3-0-sophoroside-5-0-glucosede], YGM-0f [cyanidin 3-O-(2-0-(6-0-(E)-p-coumaroyl-β-D-glucopyranosyl)-β-D-glucopyranoside)-5-0-β-D-glucopyranoside], YGM-1a [cyanidin 3-(6,6'-caffeylp-hydroxybenzoylsophoroside) -5-glucoside], YGM-1b [cyanidin 3-(6,6'-dicaffeylsophor-oside)-5-glucoside], YGM-2 [cyanidin 3-(6-caffeylsophoroside)-5-glucoside], YGM-3 [cyanidin 3-(6,6'-caffeyl-ferulylsophoroside)-5-glucoside], YGM-4b [peonidin 3-(6,6'-dicaffeylsophoroside)-5- glucoside], YGM-5a [peonidin 3-(6,6'-caffeylphydroxybenzo-ylsophoroside)-5-gluco-side], YGM-5b [cyanidin 3-6-caffeylsophoroside)-5-glucosede], and YGM-6 [peonidin 3-(6,6'-caffeylferulylsophoroside)-5-glucoside] as LOX inhibitors, and also predict the stability of ligand-LOX complex.

    Materials and Methods: The compounds were screened through docking studies using PLANTS. Also, the molecular dynamics simulation was conducted using GROMACS at 310K.

    Results: The results showed that the most significant binding affinity toward LOX was shown by YGM-0a and YGM-0a, and the LOX complex in molecular dynamics simulation showed stability for 20 ns.

    Conclusion: Based on Docking Studies and Molecular Dynamics Simulation of I. Batatas Leaves compounds, YGM-0a was shown to be the most probable LOX inhibitor.

    Matched MeSH terms: Ligands
  3. Testosterone decreases the expression of endometrial pinopode and L-selectin ligand (MECA-79) in adult female rats during uterine receptivity period
    Mokhtar HM, Giribabu N, Muniandy S, Salleh N
    Int J Clin Exp Pathol, 2014;7(5):1967-76.
    PMID: 24966906
    Pinopode, a progesterone-dependent endometrial projection which appears during uterine receptivity period, participates in blastocyst implantation. Blastocyst loosely attaches to pinopode via L-selectin ligand (MECA-79). We hypothesized that pinopode and MECA-79 expressions were affected by testosterone. Therefore, the effect of testosterone on pinopode and MECA-79 expressions during uterine receptivity period were investigated.
    Matched MeSH terms: Ligands
  4. Fulltext Ligand-based virtual screening using Bayesian inference network and reweighted fragments
    Ahmed A, Abdo A, Salim N
    ScientificWorldJournal, 2012;2012:410914.
    PMID: 22623895 DOI: 10.1100/2012/410914
    Many of the similarity-based virtual screening approaches assume that molecular fragments that are not related to the biological activity carry the same weight as the important ones. This was the reason that led to the use of Bayesian networks as an alternative to existing tools for similarity-based virtual screening. In our recent work, the retrieval performance of the Bayesian inference network (BIN) was observed to improve significantly when molecular fragments were reweighted using the relevance feedback information. In this paper, a set of active reference structures were used to reweight the fragments in the reference structure. In this approach, higher weights were assigned to those fragments that occur more frequently in the set of active reference structures while others were penalized. Simulated virtual screening experiments with MDL Drug Data Report datasets showed that the proposed approach significantly improved the retrieval effectiveness of ligand-based virtual screening, especially when the active molecules being sought had a high degree of structural heterogeneity.
    Matched MeSH terms: Ligands*
  5. Ligand expansion in ligand-based virtual screening using relevance feedback
    Abdo A, Saeed F, Hamza H, Ahmed A, Salim N
    J Comput Aided Mol Des, 2012 Mar;26(3):279-87.
    PMID: 22249773 DOI: 10.1007/s10822-012-9543-4
    Query expansion is the process of reformulating an original query to improve retrieval performance in information retrieval systems. Relevance feedback is one of the most useful query modification techniques in information retrieval systems. In this paper, we introduce query expansion into ligand-based virtual screening (LBVS) using the relevance feedback technique. In this approach, a few high-ranking molecules of unknown activity are filtered from the outputs of a Bayesian inference network based on a single ligand molecule to form a set of ligand molecules. This set of ligand molecules is used to form a new ligand molecule. Simulated virtual screening experiments with the MDL Drug Data Report and maximum unbiased validation data sets show that the use of ligand expansion provides a very simple way of improving the LBVS, especially when the active molecules being sought have a high degree of structural heterogeneity. However, the effectiveness of the ligand expansion is slightly less when structurally-homogeneous sets of actives are being sought.
    Matched MeSH terms: Ligands
  6. New fragment weighting scheme for the Bayesian inference network in ligand-based virtual screening
    Abdo A, Salim N
    J Chem Inf Model, 2011 Jan 24;51(1):25-32.
    PMID: 21155550 DOI: 10.1021/ci100232h
    Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in the Bayesian network are encoded using a set of conditional probability distributions, which can be estimated by the fragment weighting function, a function of the frequencies of the fragments in the molecule or the reference structure as well as throughout the collection. The weighting function combines one or more fragment weighting schemes. In this paper, we have investigated five different weighting functions and present a new fragment weighting scheme. Later on, these functions were modified to combine the new weighting scheme. Simulated virtual screening experiments with the MDL Drug Data Report (23) and maximum unbiased validation data sets show that the use of new weighting scheme can provide significantly more effective screening when compared with the use of current weighting schemes.
    Matched MeSH terms: Ligands
  7. Fulltext Hybrid-Enhanced Siamese Similarity Models in Ligand-Based Virtual Screen
    Altalib MK, Salim N
    Biomolecules, 2022 Nov 20;12(11).
    PMID: 36421733 DOI: 10.3390/biom12111719
    Information technology has become an integral aspect of the drug development process. The virtual screening process (VS) is a computational technique for screening chemical compounds in a reasonable amount of time and cost. The similarity search is one of the primary tasks in VS that estimates a molecule's similarity. It is predicated on the idea that molecules with similar structures may also have similar activities. Many techniques for comparing the biological similarity between a target compound and each compound in the database have been established. Although the approaches have a strong performance, particularly when dealing with molecules with homogenous active structural, they are not enough good when dealing with structurally heterogeneous compounds. The previous works examined many deep learning methods in the enhanced Siamese similarity model and demonstrated that the Enhanced Siamese Multi-Layer Perceptron similarity model (SMLP) and the Siamese Convolutional Neural Network-one dimension similarity model (SCNN1D) have good outcomes when dealing with structurally heterogeneous molecules. To further improve the retrieval effectiveness of the similarity model, we incorporate the best two models in one hybrid model. The reason is that each method gives good results in some classes, so combining them in one hybrid model may improve the retrieval recall. Many designs of the hybrid models will be tested in this study. Several experiments on real-world data sets were conducted, and the findings demonstrated that the new approaches outperformed the previous method.
    Matched MeSH terms: Ligands
  8. Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database
    Al-Khdhairawi A, Sanuri D, Akbar R, Lam SD, Sugumar S, Ibrahim N, et al.
    Comput Biol Chem, 2023 Feb;102:107800.
    PMID: 36516617 DOI: 10.1016/j.compbiolchem.2022.107800
    Antimicrobial peptides (AMPs) are short peptides with a broad spectrum of antimicrobial activity. They play a key role in the host innate immunity of many organisms. The growing threat of microorganisms resistant to antimicrobial agents and the lack of new commercially available antibiotics have made in silico discovery of AMPs increasingly important. Machine learning (ML) has improved the speed and efficiency of AMP discovery while reducing the cost of experimental approaches. Despite various ML platforms developed, there is still a lack of integrative use of ML platforms for AMP discovery from publicly available protein databases. Therefore, our study aims to screen potential AMPs with antibiofilm properties from databases using ML platforms, followed by protein-peptide molecular docking analysis and molecular dynamics (MD) simulations. A total of 5850 peptides classified as non-AMP were screened from UniProtKB and analyzed using various online ML platforms (e.g., CAMPr3, DBAASP, dPABBs, Hemopred, and ToxinPred). Eight potential AMP peptides against Klebsiella pneumoniae with antibiofilm, non-toxic and non-hemolytic properties were then docked to MrkH, a transcriptional regulator of type 3 fimbriae involved in biofilm formation. Five of eight peptides bound more strongly than the native MrkH ligand when analyzed using HADDOCK and HPEPDOCK. Following the docking studies, our MD simulated that a Neuropeptide B (Peptide 3) bind strongly to the MrkH active sites. The discovery of putative AMPs that exceed the binding energies of the native ligand underscores the utility of the combined ML and molecular simulation strategies for discovering novel AMPs with antibiofilm properties.
    Matched MeSH terms: Ligands
  9. Fulltext A Quantum-Based Similarity Method in Virtual Screening
    Al-Dabbagh MM, Salim N, Himmat M, Ahmed A, Saeed F
    Molecules, 2015;20(10):18107-27.
    PMID: 26445039 DOI: 10.3390/molecules201018107
    One of the most widely-used techniques for ligand-based virtual screening is similarity searching. This study adopted the concepts of quantum mechanics to present as state-of-the-art similarity method of molecules inspired from quantum theory. The representation of molecular compounds in mathematical quantum space plays a vital role in the development of quantum-based similarity approach. One of the key concepts of quantum theory is the use of complex numbers. Hence, this study proposed three various techniques to embed and to re-represent the molecular compounds to correspond with complex numbers format. The quantum-based similarity method that developed in this study depending on complex pure Hilbert space of molecules called Standard Quantum-Based (SQB). The recall of retrieved active molecules were at top 1% and top 5%, and significant test is used to evaluate our proposed methods. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Simulated virtual screening experiment show that the effectiveness of SQB method was significantly increased due to the role of representational power of molecular compounds in complex numbers forms compared to Tanimoto benchmark similarity measure.
    Matched MeSH terms: Ligands
  10. Quantum probability ranking principle for ligand-based virtual screening
    Al-Dabbagh MM, Salim N, Himmat M, Ahmed A, Saeed F
    J Comput Aided Mol Des, 2017 Apr;31(4):365-378.
    PMID: 28220440 DOI: 10.1007/s10822-016-0003-4
    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
    Matched MeSH terms: Ligands
  11. Fulltext Crystal structure of bis-(aceto-phenone 4-benzoyl-thio-semicarbazonato-κ(2) N (1),S)nickel(II)
    Kadir FK, Shamsuddin M, Rosli MM
    Acta Crystallogr E Crystallogr Commun, 2016 May 1;72(Pt 5):760-3.
    PMID: 27308036 DOI: 10.1107/S2056989016006873
    In the asymmetric unit of the title complex, [Ni(C16H14N3OS)2], the nickel ion is tetra-coordinated in a distorted square-planar geometry by two independent mol-ecules of the ligand which act as mononegative bidentate N,S-donors and form two five-membered chelate rings. The ligands are in trans (E) conformations with respect to the C=N bonds. The close approach of hydrogen atoms to the Ni(2+) atom suggests anagostic inter-actions (Ni⋯H-C) are present. The crystal structure is built up by a network of two C-H⋯O inter-actions. One of the inter-actions forms inversion dimers and the other links the mol-ecules into infinite chains parallel to [100]. In addition, a weak C-H⋯π inter-action is also present.
    Matched MeSH terms: Ligands
  12. The achievement of ligand-functionalized organic/polymeric nanoparticles for treating multidrug resistant cancer
    Lee WH, Loo CY, Leong CR, Young PM, Traini D, Rohanizadeh R
    Expert Opin Drug Deliv, 2017 08;14(8):937-957.
    PMID: 27759437 DOI: 10.1080/17425247.2017.1247804
    INTRODUCTION: The effectiveness of conventional cancer chemotherapy is hampered by the occurrence of multidrug resistance (MDR) in tumor cells. Although many studies have reported the development of novel MDR chemotherapeutic agents, clinical success is lacking owing to the high associated toxicity. Nanoparticle-based delivery of chemotherapeutic drugs has emerged as alternative approach to treat MDR cancers via exploitation of leaky vasculature in the tumor microenvironment. Accordingly, functionalization of nanoparticles with target specific ligands can be employed to achieve significant improvements in the treatment of MDR cancer. Areas covered: This review focuses on the recent advances in the functionalization of nanocarriers with specific ligands, including antibodies, transferrin, folate, and peptides to overcome MDR cancer. The limitations of effective ligand-functionalized nanoparticles as well as therapeutic successes in ligand targeting are covered in the review. Expert opinion: Targeting MDR tumors with ligand-functionalized nanoparticles is a promising approach to improve the treatment of cancer. With this approach, higher drug concentrations at targeted sites would be achieved with lower dosage frequencies and reduced side effects in comparison to existing formulations of chemotherapeutic drugs. However, potential toxicities and immunological responses to ligands should be carefully reviewed for viable options in for future MDR cancer treatment.
    Matched MeSH terms: Ligands
  13. Evolutionary trace analysis at the ligand binding site of laccase
    Mohamad SB, Ong AL, Ripen AM
    Bioinformation, 2008 Jun 18;2(9):369-72.
    PMID: 18795108
    Laccase belongs to the family of blue multi-copper oxidases and are capable of oxidizing a wide range of aromatic compounds. Laccases have industrial applications in paper pulping or bleaching and hydrocarbon bioremediation as a biocatalyst. We describe the design of a laccase with broader substrate spectrum in bioremediation. The application of evolutionary trace (ET) analysis of laccase at the ligand binding site for optimal design of the enzyme is described. In this attempt, class specific sites from ET analysis were mapped onto known crystal structure of laccase. The analysis revealed 162PHE as a critical residue in structure function relationship studies.
    Matched MeSH terms: Ligands
  14. Fulltext Plasmodium-infected erythrocytes induce secretion of IGFBP7 to form type II rosettes and escape phagocytosis
    Lee WC, Russell B, Sobota RM, Ghaffar K, Howland SW, Wong ZX, et al.
    Elife, 2020 Feb 18;9.
    PMID: 32066522 DOI: 10.7554/eLife.51546
    In malaria, rosetting is described as a phenomenon where an infected erythrocyte (IRBC) is attached to uninfected erythrocytes (URBC). In some studies, rosetting has been associated with malaria pathogenesis. Here, we have identified a new type of rosetting. Using a step-by-step approach, we identified IGFBP7, a protein secreted by monocytes in response to parasite stimulation, as a rosette-stimulator for Plasmodium falciparum- and P. vivax-IRBC. IGFBP7-mediated rosette-stimulation was rapid yet reversible. Unlike type I rosetting that involves direct interaction of rosetting ligands on IRBC and receptors on URBC, the IGFBP7-mediated, type II rosetting requires two additional serum factors, namely von Willebrand factor and thrombospondin-1. These two factors interact with IGFBP7 to mediate rosette formation by the IRBC. Importantly, the IGFBP7-induced type II rosetting hampers phagocytosis of IRBC by host phagocytes.
    Matched MeSH terms: Ligands
  15. Fulltext Green Biosynthesis, Antioxidant, Antibacterial, and Anticancer Activities of Silver Nanoparticles of Luffa acutangula Leaf Extract
    Nallappan D, Fauzi AN, Krishna BS, Kumar BP, Reddy AVK, Syed T, et al.
    Biomed Res Int, 2021;2021:5125681.
    PMID: 34631882 DOI: 10.1155/2021/5125681
    Studies on green biosynthesis of newly engineered nanoparticles for their prominent medicinal applications are being the torch-bearing concerns of the state-of-the-art research strategies. In this concern, we have engineered the biosynthesized Luffa acutangula silver nanoparticles of flavonoid O-glycosides in the anisotropic form isolated from aqueous leave extracts of Luffa acutangula, a popular traditional and ayurvedic plant in south-east Asian countries. These were structurally confirmed by Ultraviolet-visible (UV-Vis), Fourier transform infrared spectroscopy accessed with attenuated total reflection (FTIR-ATR) spectral analyses followed by the scanning electron microscopic (SEM) and the X-ray diffraction (XRD) crystallographic studies and found them with the face-centered cubic (fcc) structure. Medicinally, we have explored their significant antioxidant (DPPH and ABTS assays), antibacterial (disc diffusion assay on E. coli, S. aureus, B. subtilis, S. fecilis, and S. boydii), and anticancer (MTT assay on MCF-7, MDA-MB-231, U87, and DBTRG cell lines) potentialities which augmented the present investigation. The molecular docking analysis of title compounds against 3NM8 (DPPH) and 1DNU (ABTS) proteins for antioxidant activity; 5FGK (Gram-Positive Bacteria) and 1AB4 (Gram-Negative Bacteria) proteins for antibacterial activity; and 4GBD (MCF-7), 5FI2 (MDA-MB-231), 1D5R (U87), and 5TIJ (DBTRG) proteins for anticancer activity has affirmed the promising ligand-protein binding interactions among the hydroxy groups of the title compounds and aspartic acid of the concerned enzymatic proteins. The binding energy varying from -9.1645 to -7.7955 for Cosmosioside (1, Apigenin-7-glucoside) and from -9.2690 to -7.8306 for Cynaroside (2, Luteolin-7-glucoside) implies the isolated compounds as potential bioactive compounds. In addition, the performed studies like QSAR, ADMET, bioactivity properties, drug scores, and toxicity risks confirmed them as potential drug candidates and aspartic acid receptor antagonists. This research auxiliary augmented the existing array of phytological nanomedicines with new drug candidates that are credible with multiple bioactivities.
    Matched MeSH terms: Ligands
  16. Docking of noncompetitive inhibitors into dengue virus type 2 protease: understanding the interactions with allosteric binding sites
    Othman R, Kiat TS, Khalid N, Yusof R, Newhouse EI, Newhouse JS, et al.
    J Chem Inf Model, 2008 Aug;48(8):1582-91.
    PMID: 18656912 DOI: 10.1021/ci700388k
    A group of flavanones and their chalcones, isolated from Boesenbergia rotunda L., were previously reported to show varying degrees of noncompetitive inhibitory activities toward Dengue virus type 2 (Den2) protease. Results obtained from automated docking studies are in agreement with experimental data in which the ligands were shown to bind to sites other than the active site of the protease. The calculated K(i) values are very small, indicating that the ligands bind quite well to the allosteric binding site. Greater inhibition by pinostrobin, compared to the other compounds, can be explained by H-bonding interaction with the backbone carbonyl of Lys74, which is bonded to Asp75 (one of the catalytic triad residues). In addition, structure-activity relationship analysis yields structural information that may be useful for designing more effective therapeutic drugs against dengue virus infections.
    Matched MeSH terms: Ligands
  17. Fulltext Highly Active Cellulose-Supported Poly(hydroxamic acid)-Cu(II) Complex for Ullmann Etherification
    Jian Fui C, Xin Ting T, Sarjadi MS, Amin Z, Sarkar SM, Musta B, et al.
    ACS Omega, 2021 Mar 16;6(10):6766-6779.
    PMID: 33748590 DOI: 10.1021/acsomega.0c05840
    Highly active natural pandanus-extracted cellulose-supported poly(hydroxamic acid)-Cu(II) complex 4 was synthesized. The surface of pandanus cellulose was modified through graft copolymerization using purified methyl acrylate as a monomer. Then, copolymer methyl acrylate was converted into a bidentate chelating ligand poly(hydroxamic acid) via a Loosen rearrangement in the presence of an aqueous solution of hydroxylamine. Finally, copper species were incorporated into poly(hydroxamic acid) via the adsorption process. Cu(II) complex 4 was fully characterized by Fourier transform infrared (FTIR), field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray (EDX), transmission electron microscopy (TEM), inductively coupled plasma optical emission spectrometry (ICP-OES), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) analyses. The cellulose-supported Cu(II) complex 4 was successfully applied (0.005 mol %) to the Ullmann etherification of aryl, benzyl halides, and phenacyl bromide with a number of aromatic phenols to provide the corresponding ethers with excellent yield [benzyl halide (70-99%); aryl halide (20-90%)]. Cu(II) complex 4 showed high stability and was easily recovered from the reaction mixture. It could be reused up to seven times without loss of its original catalytic activity. Therefore, Cu(II) complex 4 can be commercially utilized for the preparation of various ethers, and this synthetic technique could be a part in the synthesis of natural products and medicinal compounds.
    Matched MeSH terms: Ligands
  18. Fulltext In silico homology modelling and identification of Tousled-Like Kinase 1 Inhibitors for Glioblastoma therapy via high throughput virtual screening proteinligand docking
    Kamariah Ibrahim, Abubakar Danjuma Abdullahi, Nor Azian Abdul Murad, Roslan Harun, Rahman Jamal
    Asia-Pacific Journal of Molecular Medicine, 2018;8(1):1-14.
    MyJurnal
    Glioblastoma multiforme (GBM) is a high-grade brain tumor of which the survival patients remain poor.
    Tousled-like kinase 1 (TLK1), a serine-threonine kinase, was identified to be overexpressed in cancers such
    as GBM. TLK1 plays an important role in controlling survival pathways. To date, there is no structure
    available for TLK1 as well as its inhibitors. We aimed to create a homology model of TLK1 and to identify
    suitable molecular inhibitors that are likely to bind and inhibit TLK1 activity via in silico high-throughput
    virtual screening (HTVS) protein-ligand docking. The 3D homology models of TLK1 were derived from
    various servers. All models were evaluated using Swiss Model QMEAN server. Validation was performed
    using multiple tools. Energy minimization was performed using YASARA. Subsequently, HTVS was
    performed using Molegro Virtual Docker 6.0 and ligands derived from ligand.info database. Drug-like
    molecules were filtered using ADME-Tox filtering program. Best homology model was obtained from the
    Aurora B kinase (PDB ID:4B8M) derived from Xenopus levias structure that share sequence similarity with
    human TLK1. Two compounds were identified from HTVS to be the potential inhibitors as it did not violate
    the Lipinski rule of five and the CNS-based filter as a potential drug-like molecule for GBM
    Matched MeSH terms: Ligands
  19. Bis[1-(pyridin-2-yl)ethanone-kappa N 4-phenylthiosemicarbazonato-kappa 2N4,S]manganese(II)
    Usman A, Razak IA, Chantrapromma S, Fun HK, Sreekanth A, Sivakumar S, et al.
    Acta Crystallogr C, 2002 Sep;58(Pt 9):m461-3.
    PMID: 12205370
    One half of the molecule of the title complex, [Mn(C(14)H(13)N(4)S)(2)], is related to the other half by a twofold axis passing through the Mn atom. This high-spin Mn atom is six-coordinated, in an octahedral geometry, by the azomethine N, the pyridyl N and the thiolate S atom of two planar 1-(pyridin-2-yl)ethanone N(4)-phenylthiosemicarbazone ligands. In the crystal, the molecules are interconnected by N-H.S and C-H.N interactions, forming a three-dimensional network.
    Matched MeSH terms: Ligands
  20. Unraveling the Role of Receptor for Advanced Glycation End Products (RAGE) and Its Ligands in Myasthenia Gravis
    Angelopoulou E, Paudel YN, Piperi C
    ACS Chem Neurosci, 2020 03 04;11(5):663-673.
    PMID: 32017530 DOI: 10.1021/acschemneuro.9b00678
    Myasthenia gravis (MG) is an autoimmune T cell-dependent B cell-mediated disorder of the neuromuscular junction (NMJ) characterized by fluctuating skeletal muscle weakness, most commonly attributed to pathogenic autoantibodies against postsynaptic nicotinic acetylcholine receptors (AChRs). Although MG pathogenesis is well-documented, there are no objective biomarkers that could effectively correlate with disease severity or MG clinical subtypes, and current treatment approaches are often ineffective. The receptor for advanced glycation end products (RAGE) is a multiligand cell-bound receptor highly implicated in proinflammatory responses and autoimmunity. Preclinical evidence demonstrates that RAGE and its ligand S100B are upregulated in rat models of experimental autoimmune myasthenia gravis (EAMG). S100B-mediated RAGE activation has been shown to exacerbate EAMG, by enhancing T cell proinflammatory responses, aggravating T helper (Th) subset imbalance, increasing AChR-specific T cell proliferative capacity, and promoting the production of antibodies against AChRs from the spleen. Soluble sRAGE and esRAGE, acting as decoys of RAGE ligands, are found to be significantly reduced in MG patients. Moreover, MG has been associated with increased serum levels of S100A12, S100B and HMGB1. Several studies have shown that the presence of thymic abnormalities, the onset age of MG, and the duration of the disease may affect the levels of these proteins in MG patients. Herein, we discuss the emerging role of RAGE and its ligands in MG immunopathogenesis, their clinical significance as promising biomarkers, as well as the potential therapeutic implications of targeting RAGE signaling in MG treatment.
    Matched MeSH terms: Ligands
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