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Koumpoura C, Nguyen M, Bijani C, Vendier L, Salina EG, Buroni S, Degiacomi G, Cojean S, Loiseau PM, Benoit-Vical F, García-Sosa AT, Baltas M. Design of Anti-infectious Agents from Lawsone in a Three-Component Reaction with Aldehydes and Isocyanides. ACS OMEGA 2022; 7:35635-35655. [PMID: 36249398 PMCID: PMC9558256 DOI: 10.1021/acsomega.2c03421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/07/2022] [Indexed: 06/16/2023]
Abstract
The first effective synthetic approach to naphthofuroquinones via a reaction involving lawsone, various aldehydes, and three isocyanides under microwave irradiation afforded derivatives in moderate to good yields. In addition, for less-reactive aldehydes, two naphtho-enaminodione quinones were obtained for the first time, as result of condensation between lawsone and isocyanides. X-ray structure determination for 9 and 2D-NMR spectra of 28 confirmed the obtained structures. All compounds were evaluated for their anti-infectious activities against Plasmodium falciparum, Leishmania donovani, and Mycobacterium tuberculosis. Among the naphthofuroquinone series, 17 exhibited comparatively the best activity against P. falciparum (IC50 = 2.5 μM) and M. tuberculosis (MIC = 9 μM) with better (P. falciparum) or equivalent (M. tuberculosis) values to already-known naphthofuroquinone compounds. Among the two naphtho-enaminodione quinones, 28 exhibited a moderate activity against P. falciparum with a good selectivity index (SI > 36) while also a very high potency against L. donovani (IC50 = 3.5 μM and SI > 28), rendering it very competitive to the reference drug miltefosine. All compounds were studied through molecular modeling on their potential targets for P. falciparum, Pfbc1, and PfDHODH, where 17 showed the most favorable interactions.
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Affiliation(s)
- Christina
L. Koumpoura
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
| | - Michel Nguyen
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
| | - Christian Bijani
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
| | - Laure Vendier
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
| | - Elena G. Salina
- Bach
Institute of Biochemistry, Research Center
of Biotechnology of the Russian Academy of Sciences, Moscow 119071, Russia
| | - Silvia Buroni
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Giulia Degiacomi
- Department
of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, Pavia 27100, Italy
| | - Sandrine Cojean
- Antiparasite
Chemotherapy, UMR 8076 CNRS BioCIS, Faculty of Pharmacy, University
Paris-Saclay, Châtenay-Malabry 92290, France
| | - Philippe M. Loiseau
- Antiparasite
Chemotherapy, UMR 8076 CNRS BioCIS, Faculty of Pharmacy, University
Paris-Saclay, Châtenay-Malabry 92290, France
| | - Françoise Benoit-Vical
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
| | - Alfonso T. García-Sosa
- Department
of Molecular Technology, Institute of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Michel Baltas
- Laboratoire
de Chimie de Coordination du CNRS−UPR8241, Inserm ERL 1289
Team “New antiplasmodial molecules and pharmacological approaches”, 205 route de Narbonne, BP 44099, Toulouse Cedex 31077, France
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Alov P, Al Sharif M, Aluani D, Chegaev K, Dinic J, Divac Rankov A, Fernandes MX, Fusi F, García-Sosa AT, Juvonen R, Kondeva-Burdina M, Padrón JM, Pajeva I, Pencheva T, Puerta A, Raunio H, Riganti C, Tsakovska I, Tzankova V, Yordanov Y, Saponara S. A Comprehensive Evaluation of Sdox, a Promising H2S-Releasing Doxorubicin for the Treatment of Chemoresistant Tumors. Front Pharmacol 2022; 13:831791. [PMID: 35321325 PMCID: PMC8936434 DOI: 10.3389/fphar.2022.831791] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/25/2022] [Indexed: 12/11/2022] Open
Abstract
Sdox is a hydrogen sulfide (H2S)-releasing doxorubicin effective in P-glycoprotein-overexpressing/doxorubicin-resistant tumor models and not cytotoxic, as the parental drug, in H9c2 cardiomyocytes. The aim of this study was the assessment of Sdox drug-like features and its absorption, distribution, metabolism, and excretion (ADME)/toxicity properties, by a multi- and transdisciplinary in silico, in vitro, and in vivo approach. Doxorubicin was used as the reference compound. The in silico profiling suggested that Sdox possesses higher lipophilicity and lower solubility compared to doxorubicin, and the off-targets prediction revealed relevant differences between Dox and Sdox towards several cancer targets, suggesting different toxicological profiles. In vitro data showed that Sdox is a substrate with lower affinity for P-glycoprotein, less hepatotoxic, and causes less oxidative damage than doxorubicin. Both anthracyclines inhibited CYP3A4, but not hERG currents. Unlike doxorubicin, the percentage of zebrafish live embryos at 72 hpf was not affected by Sdox treatment. In conclusion, these findings demonstrate that Sdox displays a more favorable drug-like ADME/toxicity profile than doxorubicin, different selectivity towards cancer targets, along with a greater preclinical efficacy in resistant tumors. Therefore, Sdox represents a prototype of innovative anthracyclines, worthy of further investigations in clinical settings.
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Affiliation(s)
- Petko Alov
- Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Merilin Al Sharif
- Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Denitsa Aluani
- Department of Pharmacology, Pharmacotherapy and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria
| | - Konstantin Chegaev
- Department of Drug Science and Technology, University of Torino, Torino, Italy
| | - Jelena Dinic
- Department of Neurobiology, Institute for Biological Research Siniša Stanković, National Institute of Republic of Serbia, University of Belgrade, Belgrade, Serbia
| | - Aleksandra Divac Rankov
- Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Miguel X. Fernandes
- BioLab, Instituto Universitario de Bio-Orgánica Antonio González, Universidad de La Laguna, La Laguna, Spain
| | - Fabio Fusi
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | | | - Risto Juvonen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Magdalena Kondeva-Burdina
- Department of Pharmacology, Pharmacotherapy and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria
| | - José M. Padrón
- BioLab, Instituto Universitario de Bio-Orgánica Antonio González, Universidad de La Laguna, La Laguna, Spain
| | - Ilza Pajeva
- Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Tania Pencheva
- Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Adrián Puerta
- BioLab, Instituto Universitario de Bio-Orgánica Antonio González, Universidad de La Laguna, La Laguna, Spain
| | - Hannu Raunio
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Chiara Riganti
- Department of Oncology, University of Torino, Torino, Italy
| | - Ivanka Tsakovska
- Department of QSAR and Molecular Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Virginia Tzankova
- Department of Pharmacology, Pharmacotherapy and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria
| | - Yordan Yordanov
- Department of Pharmacology, Pharmacotherapy and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria
| | - Simona Saponara
- Department of Life Sciences, University of Siena, Siena, Italy
- *Correspondence: Simona Saponara,
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Peña-Guerrero J, Fernández-Rubio C, Burguete-Mikeo A, El-Dirany R, García-Sosa AT, Nguewa P. Discovery and Validation of Lmj_04_BRCT Domain, a Novel Therapeutic Target: Identification of Candidate Drugs for Leishmaniasis. Int J Mol Sci 2021; 22:ijms221910493. [PMID: 34638841 PMCID: PMC8508789 DOI: 10.3390/ijms221910493] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 09/13/2021] [Accepted: 09/23/2021] [Indexed: 01/09/2023] Open
Abstract
Since many of the currently available antileishmanial treatments exhibit toxicity, low effectiveness, and resistance, search and validation of new therapeutic targets allowing the development of innovative drugs have become a worldwide priority. This work presents a structure-based drug discovery strategy to validate the Lmj_04_BRCT domain as a novel therapeutic target in Leishmania spp. The structure of this domain was explored using homology modeling, virtual screening, and molecular dynamics studies. Candidate compounds were validated in vitro using promastigotes of Leishmania major, L. amazonensis, and L. infantum, as well as primary mouse macrophages infected with L. major. The novel inhibitor CPE2 emerged as the most active of a group of compounds against Leishmania, being able to significantly reduce the viability of promastigotes. CPE2 was also active against the intracellular forms of the parasites and significantly reduced parasite burden in murine macrophages without exhibiting toxicity in host cells. Furthermore, L. major promastigotes treated with CPE2 showed significant lower expression levels of several genes (α-tubulin, Cyclin CYCA, and Yip1) related to proliferation and treatment resistance. Our in silico and in vitro studies suggest that the Lmj_04_BRCT domain and its here disclosed inhibitors are new potential therapeutic options against leishmaniasis.
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Affiliation(s)
- José Peña-Guerrero
- Department of Microbiology and Parasitology, ISTUN Instituto de Salud Tropical, IdiSNA, Instituto de Investigación Sanitaria de Navarra, Universidad de Navarra, E-31008 Pamplona, Spain; (J.P.-G.); (C.F.-R.); (A.B.-M.); (R.E.-D.)
| | - Celia Fernández-Rubio
- Department of Microbiology and Parasitology, ISTUN Instituto de Salud Tropical, IdiSNA, Instituto de Investigación Sanitaria de Navarra, Universidad de Navarra, E-31008 Pamplona, Spain; (J.P.-G.); (C.F.-R.); (A.B.-M.); (R.E.-D.)
| | - Aroia Burguete-Mikeo
- Department of Microbiology and Parasitology, ISTUN Instituto de Salud Tropical, IdiSNA, Instituto de Investigación Sanitaria de Navarra, Universidad de Navarra, E-31008 Pamplona, Spain; (J.P.-G.); (C.F.-R.); (A.B.-M.); (R.E.-D.)
| | - Rima El-Dirany
- Department of Microbiology and Parasitology, ISTUN Instituto de Salud Tropical, IdiSNA, Instituto de Investigación Sanitaria de Navarra, Universidad de Navarra, E-31008 Pamplona, Spain; (J.P.-G.); (C.F.-R.); (A.B.-M.); (R.E.-D.)
| | - Alfonso T. García-Sosa
- Department of Molecular Technology, Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia
- Correspondence: (A.T.G.-S.); (P.N.); Tel.: +372-737-5270 (A.T.G.-S.); +34-948-425-600 (ext. 6434) (P.N.)
| | - Paul Nguewa
- Department of Microbiology and Parasitology, ISTUN Instituto de Salud Tropical, IdiSNA, Instituto de Investigación Sanitaria de Navarra, Universidad de Navarra, E-31008 Pamplona, Spain; (J.P.-G.); (C.F.-R.); (A.B.-M.); (R.E.-D.)
- Correspondence: (A.T.G.-S.); (P.N.); Tel.: +372-737-5270 (A.T.G.-S.); +34-948-425-600 (ext. 6434) (P.N.)
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4
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García-Sosa AT. Androgen Receptor Binding Category Prediction with Deep Neural Networks and Structure-, Ligand-, and Statistically Based Features. Molecules 2021; 26:1285. [PMID: 33652992 PMCID: PMC7956632 DOI: 10.3390/molecules26051285] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/23/2021] [Accepted: 02/24/2021] [Indexed: 01/10/2023] Open
Abstract
Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine-learning classifiers and regressors and to evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to different results, with deep neural networks (DNNs) on user-defined physicochemically relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evaluation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and prediction, improving assessment and design of compounds. Source code and data are available on github.
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5
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Machine learning, artificial intelligence, and data science breaking into drug design and neglected diseases. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1513] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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6
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Abstract
Aim: The explosion of data based technology has accelerated pattern mining. However, it is clear that quality and bias of data impacts all machine learning and modeling. Results & methodology: A technique is presented for using the distribution of first significant digits of medicinal chemistry features: logP, logS, and pKa. experimental and predicted, to assess their following of Benford's law as seen in many natural phenomena. Conclusion: Quality of data depends on the dataset sizes, diversity, and magnitudes. Profiling based on drugs may be too small or narrow; using larger sets of experimentally determined or predicted values recovers the distribution seen in other natural phenomena. This technique may be used to improve profiling, machine learning, large dataset assessment and other data based methods for better (automated) data generation and designing compounds.
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7
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Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones. Int J Mol Sci 2020; 21:ijms21103671. [PMID: 32456148 PMCID: PMC7279380 DOI: 10.3390/ijms21103671] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 05/21/2020] [Accepted: 05/21/2020] [Indexed: 12/17/2022] Open
Abstract
Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes.
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8
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Stevanovic S, Sencanski M, Danel M, Menendez C, Belguedj R, Bouraiou A, Nikolic K, Cojean S, Loiseau PM, Glisic S, Baltas M, García-Sosa AT. Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets. Molecules 2019; 24:molecules24071282. [PMID: 30986947 PMCID: PMC6480966 DOI: 10.3390/molecules24071282] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 03/20/2019] [Accepted: 03/28/2019] [Indexed: 11/24/2022] Open
Abstract
Due to the lack of approved vaccines against human leishmaniasis and the limitations of the current chemotherapy inducing side effects and drug resistance, development of new, effective chemotherapeutic agents is essential. This study describes the synthesis of a series of novel oxadiazoles and indolizine-containing compounds. The compounds were screened in silico using an EIIP/AQVN filter followed by ligand-based virtual screening and molecular docking to parasite arginase. Top hits were further screened versus human arginase and finally against an anti-target battery to tag their possible interactions with proteins essential for the metabolism and clearance of many substances. Eight candidate compounds were selected for further experimental testing. The results show measurable in vitro anti-leishmanial activity for three compounds. One compound with an IC50 value of 2.18 µM on Leishmania donovani intramacrophage amastigotes is clearly better positioned than the others as an interesting molecular template for further development of new anti-leishmanial agents.
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Affiliation(s)
- Strahinja Stevanovic
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, P.O. Box 522, 11001 Belgrade, Serbia.
| | - Milan Sencanski
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, P.O. Box 522, 11001 Belgrade, Serbia.
| | - Mathieu Danel
- ITAV, Université de Toulouse, CNRS, 31062 Toulouse, France.
| | - Christophe Menendez
- Department of Chemistry, Université de Toulouse, UPS, CNRS UMR 5068, LSPCMIB, 118 Route de Narbonne, 31062 Toulouse, France.
- CNRS, Laboratoire de Synthèse et Physico-Chimie de Molécules d'Intérêt Biologique, LSPCMIB, UMR-5068, 118 Route de Narbonne, 31062 Toulouse, France.
| | - Roumaissa Belguedj
- Department of Chemistry, Université de Toulouse, UPS, CNRS UMR 5068, LSPCMIB, 118 Route de Narbonne, 31062 Toulouse, France.
- CNRS, Laboratoire de Synthèse et Physico-Chimie de Molécules d'Intérêt Biologique, LSPCMIB, UMR-5068, 118 Route de Narbonne, 31062 Toulouse, France.
- Unité de Recherche de Chimie de l'Environnement et Moléculaire Structurale, Université Frères Mentouri, Route de Ain El Bey, 25000 Constantine, Algeria.
| | - Abdelmalek Bouraiou
- Unité de Recherche de Chimie de l'Environnement et Moléculaire Structurale, Université Frères Mentouri, Route de Ain El Bey, 25000 Constantine, Algeria.
| | - Katarina Nikolic
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, 11000 Belgrade, Serbia.
| | - Sandrine Cojean
- Antiparasitic Chemotherapy, UMR 8076 CNRS BioCIS, Faculty of Pharmacy Université Paris-Sud, Rue Jean-Baptiste Clément, F 92290 Chatenay-Malabry, France.
| | - Philippe M Loiseau
- Antiparasitic Chemotherapy, UMR 8076 CNRS BioCIS, Faculty of Pharmacy Université Paris-Sud, Rue Jean-Baptiste Clément, F 92290 Chatenay-Malabry, France.
| | - Sanja Glisic
- Laboratory for Bioinformatics and Computational Chemistry, Institute of Nuclear Sciences VINCA, University of Belgrade, P.O. Box 522, 11001 Belgrade, Serbia.
| | - Michel Baltas
- Department of Chemistry, Université de Toulouse, UPS, CNRS UMR 5068, LSPCMIB, 118 Route de Narbonne, 31062 Toulouse, France.
- CNRS, Laboratoire de Synthèse et Physico-Chimie de Molécules d'Intérêt Biologique, LSPCMIB, UMR-5068, 118 Route de Narbonne, 31062 Toulouse, France.
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9
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Borges A, Simões M, Todorović TR, Filipović NR, García-Sosa AT. Cobalt Complex with Thiazole-Based Ligand as New Pseudomonas aeruginosa Quorum Quencher, Biofilm Inhibitor and Virulence Attenuator. Molecules 2018; 23:E1385. [PMID: 29890626 PMCID: PMC6099793 DOI: 10.3390/molecules23061385] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 05/30/2018] [Accepted: 06/07/2018] [Indexed: 12/31/2022] Open
Abstract
Pseudomonas aeruginosa is one of the most dreaded human pathogens, because of its intrinsic resistance to a number of commonly used antibiotics and ability to form sessile communities (biofilms). Innovative treatment strategies are required and that can rely on the attenuation of the pathogenicity and virulence traits. The interruption of the mechanisms of intercellular communication in bacteria (quorum sensing) is one of such promising strategies. A cobalt coordination compound (Co(HL)₂) synthesized from (E)-2-(2-(pyridin-2-ylmethylene)hydrazinyl)-4-(p-tolyl)thiazole (HL) is reported herein for the first time to inhibit P. aeruginosa 3-oxo-C12-HSL-dependent QS system (LasI/LasR system) and underling phenotypes (biofilm formation and virulence factors). Its interactions with a possible target, the transcriptional activator protein complex LasR-3-oxo-C12-HSL, was studied by molecular modeling with the coordination compound ligand having stronger predicted interactions than those of co-crystallized ligand 3-oxo-C12-HSL, as well as known-binder furvina. Transition metal group 9 coordination compounds may be explored in antipathogenic/antibacterial drug design.
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Affiliation(s)
- Anabela Borges
- LEPABE, Department of Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, s/n, Porto 4200-465, Portugal.
| | - Manuel Simões
- LEPABE, Department of Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, s/n, Porto 4200-465, Portugal.
| | - Tamara R Todorović
- Faculty of Chemistry, University of Belgrade, Studentski trg 12⁻16, Belgrade 11000, Serbia.
| | - Nenad R Filipović
- Department of Chemistry and Biochemistry, Faculty of Agriculture, University of Belgrade, Nemanjina 6, Belgrade 11000, Serbia.
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10
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García-Sosa AT, Maran U. Improving the use of ranking in virtual screening against HIV-1 integrase with triangular numbers and including ligand profiling with antitargets. J Chem Inf Model 2014; 54:3172-85. [PMID: 25303089 DOI: 10.1021/ci500300u] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
A delicate balance exists between a drug molecule's toxicity and its activity. Indeed, efficacy, toxicity, and side effect problems are a common cause for the termination of drug candidate compounds and development projects. To address this, an antitarget interaction profile is built and combined with virtual screening and cross docking for new inhibitors of HIV-1 integrase, in order to consider possible off-target interactions as early as possible in a drug or hit discovery program. New ranking techniques using triangular numbers improve ranking information on the compounds and recovery of known inhibitors into the top compounds using different docking programs. This improved ranking arises from using consensus of ranks between docking programs and ligand efficiencies to derive a new rank, instead of using absolute score values, or average of ranks. The triangular number rerank also allowed the objective combination of results from several protein targets or screen conditions and several programs. Triangular number reranking conserves more information than other reranking methods such as average of scores or averages of ranks. In addition, the use of triangular numbers for reranking makes possible the use of thresholds with a justified leeway based on the number of available known inhibitors, so that the majority of the compounds above the threshold in ranks compare to the compounds that have known experimentally determined biological activity. The battery of anti- or off-targets can be tailored to specific molecular or drug design challenges. In silico filters can thus be deployed in successive stages, for prefiltering, activity profiling, and for further analysis and triaging of libraries of compounds.
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12
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García-Sosa AT, Tulp I, Langel K, Langel Ü. Peptide-ligand binding modeling of siRNA with cell-penetrating peptides. BIOMED RESEARCH INTERNATIONAL 2014; 2014:257040. [PMID: 25147791 PMCID: PMC4131515 DOI: 10.1155/2014/257040] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2014] [Accepted: 05/15/2014] [Indexed: 12/04/2022]
Abstract
The binding affinity of a series of cell-penetrating peptides (CPP) was modeled through docking and making use of the number of intermolecular hydrogen bonds, lipophilic contacts, and the number of sp3 molecular orbital hybridization carbons. The new ranking of the peptides is consistent with the experimentally determined efficiency in the downregulation of luciferase activity, which includes the peptides' ability to bind and deliver the siRNA into the cell. The predicted structures of the complexes of peptides to siRNA were stable throughout 10 ns long, explicit water molecular dynamics simulations. The stability and binding affinity of peptide-siRNA complexes was related to the sidechains and modifications of the CPPs, with the stearyl and quinoline groups improving affinity and stability. The reranking of the peptides docked to siRNA, together with explicit water molecular dynamics simulations, appears to be well suited to describe and predict the interaction of CPPs with siRNA.
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Affiliation(s)
| | - Indrek Tulp
- Institute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, Estonia
| | - Kent Langel
- Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia
| | - Ülo Langel
- Institute of Technology, University of Tartu, Nooruse 1, 50411 Tartu, Estonia
- Department of Neurochemistry, Stockholm University, 106 91 Stockholm, Sweden
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García-Sosa AT. Hydration Properties of Ligands and Drugs in Protein Binding Sites: Tightly-Bound, Bridging Water Molecules and Their Effects and Consequences on Molecular Design Strategies. J Chem Inf Model 2013; 53:1388-405. [DOI: 10.1021/ci3005786] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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García-Sosa AT, Maran U. Drugs, non-drugs, and disease category specificity: organ effects by ligand pharmacology. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:319-331. [PMID: 23534612 DOI: 10.1080/1062936x.2013.773373] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Important understanding can be gained from using molecular biology-based and chemistry-based techniques together. Bayesian classifiers have thus been developed in the present work using several statistically significant molecular properties of compiled datasets of drugs and non-drugs, including their disease category or organ. The results show they provide a useful classification and simplicity of several different ligand efficiencies and molecular properties. Early recall of drugs among non-drugs using the classifiers as a ranking tool is also provided. As the chemical space of compounds is addressed together with their anatomical characterization, chemical libraries can be improved to select for specific organ or disease. Eventually, by including even finer detail, the method may help in designing libraries with specific pharmacological or toxicological target chemical space. Alternatively, a lack of statistically significant differences in property density distributions may help in further describing compounds with possibility of activity on several organs or disease groups, and given their very similar or considerably overlapping chemical space, therefore wanted or unwanted side-effects. The overlaps between densities for several properties of organs or disease categories were calculated by integrating the area under the curves where they intersect. The naïve Bayesian classifiers are readily built, fast to score, and easily interpretable.
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Affiliation(s)
- A T García-Sosa
- Institute of Chemistry, University of Tartu, Tartu, Estonia.
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15
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La Pensée L, Sabbani S, Sharma R, Bhamra I, Shore E, Chadwick AE, Berry NG, Firman J, Araujo NC, Cabral L, Cristiano MLS, Bateman C, Janneh O, Gavrila A, Wu YH, Hussain A, Ward SA, Stocks PA, Cosstick R, O'Neill PM. Artemisinin-polypyrrole conjugates: synthesis, DNA binding studies and preliminary antiproliferative evaluation. ChemMedChem 2013; 8:709-18. [PMID: 23495190 DOI: 10.1002/cmdc.201200536] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2012] [Indexed: 11/06/2022]
Abstract
Greater than the sum of its parts: Artemisinins are currently in phase I-II clinical trials against breast, colorectal and non-small-cell lung cancers. In an attempt to offer increased specificity, a series of hybrid artemisinin-polypyrrole minor groove binder conjugates are described. DNA binding/modelling studies and preliminary biological evaluation give insights into their mechanism of action and the potential of this strategy.
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Affiliation(s)
- Louise La Pensée
- Department of Chemistry, University of Liverpool, Crown Street, Liverpool L69 7ZD, UK
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16
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García-Sosa AT, Oja M, Hetényi C, Maran U. DrugLogit: logistic discrimination between drugs and nondrugs including disease-specificity by assigning probabilities based on molecular properties. J Chem Inf Model 2012; 52:2165-80. [PMID: 22830445 DOI: 10.1021/ci200587h] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The increasing knowledge of both structure and activity of compounds provides a good basis for enhancing the pharmacological characterization of chemical libraries. In addition, pharmacology can be seen as incorporating both advances from molecular biology as well as chemical sciences, with innovative insight provided from studying target-ligand data from a ligand molecular point of view. Predictions and profiling of libraries of drug candidates have previously focused mainly on certain cases of oral bioavailability. Inclusion of other administration routes and disease-specificity would improve the precision of drug profiling. In this work, recent data are extended, and a probability-based approach is introduced for quantitative and gradual classification of compounds into categories of drugs/nondrugs, as well as for disease- or organ-specificity. Using experimental data of over 1067 compounds and multivariate logistic regressions, the classification shows good performance in training and independent test cases. The regressions have high statistical significance in terms of the robustness of coefficients and 95% confidence intervals provided by a 1000-fold bootstrapping resampling. Besides their good predictive power, the classification functions remain chemically interpretable, containing only one to five variables in total, and the physicochemical terms involved can be easily calculated. The present approach is useful for an improved description and filtering of compound libraries. It can also be applied sequentially or in combinations of filters, as well as adapted to particular use cases. The scores and equations may be able to suggest possible routes for compound or library modification. The data is made available for reuse by others, and the equations are freely accessible at http://hermes.chem.ut.ee/~alfx/druglogit.html.
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García-Sosa AT, Sild S, Takkis K, Maran U. Combined Approach Using Ligand Efficiency, Cross-Docking, and Antitarget Hits for Wild-Type and Drug-Resistant Y181C HIV-1 Reverse Transcriptase. J Chem Inf Model 2011; 51:2595-611. [DOI: 10.1021/ci200203h] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
| | - Sulev Sild
- Institute of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Kalev Takkis
- Institute of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
| | - Uko Maran
- Institute of Chemistry, University of Tartu, Ravila 14a, Tartu 50411, Estonia
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18
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Stark JL, Powers R. Application of NMR and molecular docking in structure-based drug discovery. Top Curr Chem (Cham) 2011; 326:1-34. [PMID: 21915777 DOI: 10.1007/128_2011_213] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.
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Affiliation(s)
- Jaime L Stark
- Department of Chemistry, University of Nebraska, Lincoln, NE 68588-0304, USA
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19
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Yuriev E, Agostino M, Ramsland PA. Challenges and advances in computational docking: 2009 in review. J Mol Recognit 2010; 24:149-64. [DOI: 10.1002/jmr.1077] [Citation(s) in RCA: 223] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2010] [Revised: 07/20/2010] [Accepted: 07/21/2010] [Indexed: 12/12/2022]
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Piir G, Sild S, Roncaglioni A, Benfenati E, Maran U. QSAR model for the prediction of bio-concentration factor using aqueous solubility and descriptors considering various electronic effects. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2010; 21:711-729. [PMID: 21120758 DOI: 10.1080/1062936x.2010.528596] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
The in silico modelling of bio-concentration factor (BCF) is of considerable interest in environmental sciences, because it is an accepted indicator for the accumulation potential of chemicals in organisms. Numerous QSAR models have been developed for the BCF, and the majority utilize the octanol/water partition coefficient (log P) to account for the penetration characteristics of the chemicals. The present work used descriptors from a variety of software packages for the development of a multi-linear regression model to estimate BCF. The modelled data set of 473 diverse compounds covers a wide range of log BCF values. In the proposed QSAR model, most of the variation is described by the calculated solubility in water. Other contributing descriptors describe, for instance, hydrophobic surface area, hydrogen bonding and other electronic effects. The model was validated internally by using a variety of statistical approaches. Two external validations were also performed. For the former validation, a subset from the same data source was used. The 2nd external validation was based on an independent data set collected from different resources. All validations showed the consistency of the model. The applicability domain of the model was discussed and described and a thorough outlier analysis was performed.
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Affiliation(s)
- G Piir
- Institute of Chemistry, University of Tartu, Tartu, Estonia
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