DOCSLIB.ORG

Synthesis and a Combined Simil

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Synthesis and a Combined Simil Er et al. Chemistry Central Journal (2018) 12:121 https://doi.org/10.1186/s13065-018-0485-3 Chemistry Central Journal RESEARCH ARTICLE Open Access An integrated approach towards the development of novel antifungal agents containing thiadiazole: synthesis and a combined similarity search, homology modelling, molecular dynamics and molecular docking study Mustafa Er1*, Abdulati Miftah Abounakhla1, Hakan Tahtaci1, Ali Hasin Bawah1, Süleyman Selim Çınaroğlu2, Abdurrahman Onaran3 and Abdulilah Ece4* Abstract Background: This study aims to synthesise and characterise novel compounds containing 2-amino-1,3,4-thiadiazole and their acyl derivatives and to investigate antifungal activities. Similarity search, molecular dynamics and molecular docking were also studied to fnd out a potential target and enlighten the inhibition mechanism. Results: As a frst step, 2-amino-1,3,4-thiadiazole derivatives (compounds 3 and 4) were synthesised with high yields (81 and 84%). The target compounds (6a–n and 7a–n) were then synthesised with moderate to high yields (56–87%) by reacting 3 and 4 with various acyl chloride derivatives (5a–n). The synthesized compounds were characterized using the IR, 1H-NMR, 13C-NMR, Mass, X-ray (compound 7n) and elemental analysis techniques. Later, the in vitro anti- fungal activities of the synthesised compounds were determined. The inhibition zones exhibited by the compounds against the tested fungi, their minimum fungicidal activities, minimum inhibitory concentration and the lethal dose values ­(LD50) were determined. The compounds exhibited moderate to high levels of activity against all tested pathogens. Finally, in silico modelling was used to enlighten inhibition mechanism using ligand and structure-based methods. As an initial step, similarity search was carried out and the resulting proteins that belong to Homo sapiens were used as reference in sequence similarity search to fnd the corresponding amino acid sequences in target organ- isms. Homology modelling was used to construct the protein structure. The stabilised protein structure obtained from molecular dynamics simulation was used in molecular docking. Conclusion: The overall results presented here might be a good starting point for the identifcation of novel and more active compounds as antifungal agents. Keywords: 2-Amino-1,3,4-thiadiazole, Acylation, Antifungal, Homology modelling, Molecular dynamics, Molecular docking *Correspondence: [email protected]; [email protected] 1 Department of Chemistry, Faculty of Science, Karabuk University, 78050 Karabuk, Turkey 4 Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Biruni University, 34010 Istanbul, Turkey Full list of author information is available at the end of the article © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat​iveco​mmons​.org/licen​ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat​iveco​mmons​.org/ publi​cdoma​in/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Er et al. Chemistry Central Journal (2018) 12:121 Page 2 of 21 Background compounds, especially those containing nitrogen and sul- Due to widespread of infectious diseases killing mil- phur atoms, have a variety of biological activities [1–3]. lions of people, the need for new active, safer and more Tiadiazole is a fve-membered heterocyclic ring sys- potential antimicrobial agents has increased dramati- tem which contains two nitrogen and one sulphur atom cally. Accordingly, researchers focus on synthesising with the molecular formula of C2H2N2S. 1,3,4-Tiadia- novel compounds and their derivatives having diferent zole and its derivatives have become the focus of atten- physiochemical properties which promises high activi- tion in drug, agriculture and material chemistry due to ties with no or fewer side efects. Heterocyclic com- their high activity in 2′ and 5′ positions in substitution pounds are widespread in nature and are used in many reactions [4, 5]. felds. It has been known for many years that heterocyclic Te two-electron donor nitrogen system (–N=C–S) and hydrogen-binding domain allow for great structural Scheme 1 Synthetic route for the synthesis of the target compounds (6a–n, 7a–n) Er et al. Chemistry Central Journal (2018) 12:121 Page 3 of 21 stability and is known to be the component responsible Computer Aided Drug Design helps to design novel for biological activity [6, 7]. and active compounds which also have fewer side efects. 1,3,4-Tiadiazole and its derivatives have an important In that respect, in silico molecular modelling has been place among compounds with hetero rings containing playing an increasingly important role in the develop- nitrogen and sulphur atoms and have been extensively ment and synthesis of new drug substances and in under- used in pharmaceutics due to their biological activity standing the basis of drug-target protein interactions such as antifungal, antibacterial, antioxidant, anti-infam- [21–23]. matory, anticonvulsant, antituberculosis, and antiprolif- In the light of the literature survey, the purpose of this erative activities [8–20]. study is to synthesise a number of compounds with dif- Te drug design begins with the synthesis of a com- ferent substituted groups containing 1,3,4-thiadiazoles pound that exhibits a promising biological profle (lead ring and their acyl derivatives, to investigate their anti- compound), then the activity profle is optimised and fungal activities and fnally to discuss the inhibition fnally ends with chemical synthesis of this fnal com- mechanism by means of computational tools. pound (drug candidate). Scheme 2 The formation mechanism for the target compounds (6a–n and 7a–n) Er et al. Chemistry Central Journal (2018) 12:121 Page 4 of 21 Results and discussion and 4. All the synthesised 28 compounds (6a–n and 7a– Chemistry n) were obtained in moderate to good yields (56–87%). In the frst part of the study, the thiadiazole compounds Te synthetic route employed to synthesise these com- (3 and 4) were synthesised from the reaction of the com- pounds is given in Scheme 1 and the formation mecha- pounds 1 or 2 (purchased) with the thiosemicarbazide in nism is shown in Scheme 2. trifuoroacetic acid (TFA) at 60 °C. Te compounds 3 and As can be seen from the reaction mechanism in 4 were obtained as specifed in the literature [24, 25]. Scheme 2, the main reaction proceeds through a typical Te acyl derivatives of thiadiazole, which are the target nucleophilic acyl substitution reaction. compounds of the study, were obtained from the reac- Te structure of the compounds obtained were eluci- 1 13 tions of acyl derivatives (5a–n) with the compounds 3 dated using the FT-IR, H NMR, C NMR, elemental Table 1 Inhibition zones of compounds against plant pathogens Compounds Mean zone of inhibition (mm)a Fusarium oxysporum f. sp. lycopersici Monilia fructigena Alternaria solani Doses (µg/ml) Doses (µg/ml) Doses (µg/ml) 500 1000 500 1000 500 1000 C 0 0.00 0 0.00 0 0.00 − ± ± ± 3 10.12 0.91 12.35 0.52 14.16 0.80 18.19 0.86 12.45 0.49 14.81 0.56 ± ± ± ± ± ± 4 14.67 0.93 17.81 1.02 11.19 0.59 14.25 0.54 9.35 0.33 13.18 1.25 ± ± ± ± ± ± 6a 13.19 0.67 17.08 0.72 13.40 0.23 15.88 0.41 10.76 0.29 13.31 0.84 ± ± ± ± ± ± 6b 10.92 0.22 15.68 0.97 16.87 0.32 20.08 0.40 10.40 0.42 14.61 0.37 ± ± ± ± ± ± 6c 13.83 0.30 17.82 0.09 16.31 1.36 18.34 0.34 10.70 0.83 14.73 0.94 ± ± ± ± ± ± 6d 11.27 0.53 15.33 0.36 14.44 3.38 18.09 1.67 9.18 0.59 11.73 0.34 ± ± ± ± ± ± 6e 11.11 0.61 15.14 1.02 12.20 0.74 17.17 1.20 14.27 3.18 17.15 1.68 ± ± ± ± ± ± 6f 13.95 0.58 17.30 0.73 14.45 0.60 18.65 0.51 9.74 0.63 15.21 1.15 ± ± ± ± ± ± 6g 15.51 0.28 18.53 0.39 16.08 0.19 18.30 0.16 13.44 1.00 16.92 0.12 ± ± ± ± ± ± 6h 15.25 0.30 19.14 0.40 11.59 0.58 15.13 1.68 9.57 0.30 11.94 0.35 ± ± ± ± ± ± 6i 10.33 1.29 13.88 1.08 12.37 3.66 17.40 1.21 9.96 0.33 12.56 0.34 ± ± ± ± ± ± 6j 13.31 0.87 18.80 0.74 15.28 0.85 17.93 0.50 11.37 1.38 15.27 1.29 ± ± ± ± ± ± 6k 12.47 0.78 16.67 0.94 19.95 1.49 20.52 1.24 11.16 0.20 15.19 0.90 ± ± ± ± ± ± 6l 13.25 1.59 17.52 0.45 11.44 0.31 15.84 0.39 7.31 0.03 10.73 0.08 ± ± ± ± ± ± 6m 13.69 1.28 18.69 1.28 11.37 1.22 16.59 1.15 11.10 0.36 14.61 0.56 ± ± ± ± ± ± 6n 14.36 0.44 17.76 0.16 12.71 0.52 18.23 0.58 12.05 0.29 15.96 0.16 ± ± ± ± ± ± 7a 13.48 1.07 18.51 1.71 14.31 0.33 17.99 0.29 11.29 0.25 14.01 1.11 ± ± ± ± ± ± 7b 13.40 1.39 17.98 0.58 16.83 1.89 20.04 0.95 10.67 0.48 13.73 0.89 ± ± ± ± ± ± 7c 15.71 1.25 19.51 0.78 15.34 0.27 17.64 0.38 10.18 0.59 14.10 1.64 ± ± ± ± ± ± 7d 11.39 0.04 14.80 0.45 14.95 0.32 17.72 0.23 10.69 0.64 12.57 0.63 ± ± ± ± ± ± 7e 13.48 0.30 17.33 0.52 10.73 0.51 16.83 0.36 10.90 0.32 16.24 0.26 ± ± ± ± ± ± 7f 13.31 0.31 16.56 0.61 12.42 1.43 16.54 0.79 8.02 0.60 10.88 0.37 ± ± ± ± ± ± 7g 12.22 0.29 15.91 0.63 11.90 0.71 21.23 0.97 12.19 0.52 15.88 1.13 ± ± ± ± ± ± 7h 14.68 0.94 18.13 0.46 11.65 0.89 17.34 0.78 7.72 0.44 10.87 0.44 ± ± ± ± ± ± 7i 12.57 0.41 15.81 0.51 14.84 0.23 17.67 0.11 9.04 0.46 11.01 0.55 ± ± ± ± ± ± 7j 11.19 0.95 16.40 0.55 11.77 0.86 20.16 1.81 9.94 0.26 15.38 0.05 ± ± ± ± ± ± 7k 11.97 1.30 15.90 1.00 12.61 2.09 16.66 0.94 8.92 1.22 11.38 0.49 ± ± ± ± ± ± 7l 13.55 0.37 16.38 0.31 9.36 0.92 17.36 0.24 9.90 0.21 12.71 0.79 ± ± ± ± ± ± 7m 13.59 1.88 16.82 0.14 10.17 1.15 16.06 1.46 6.86 0.63 11.54 0.41 ± ± ± ± ± ± 7n 13.65 0.69 17.54 0.52 17.31 1.02 18.74 0.31 12.50 0.45 18.19 0.84 ± ± ± ± ± ± C 25.00 1.32 25.00 0.98 25.00 0.53 + ± ± ± Inhibition zone (IZ) standard deviation (SD); C , positive control (Thiram); C , negative control (DMSO) ± + − a Mean of three assays Er et al.
Load more

Recommended publications
  • Identifying of Selective Agonists Targeting Lxrβ from Terpene Compounds of Alismatis Rhizoma
    Identifying of selective agonists targeting LXRβ from terpene compounds of Alismatis Rhizoma Chuanjiong Lin Sichuan University Jianzong Li ( [email protected] ) Sichuan University Chuanfang Wu Sichuan University Jinku Bao Sichuan University Original paper Keywords: Hyperlipidemia, LXRα, LXRβ, molecular docking, molecular dynamics simulations, agonist, Alismatis Rhizoma Posted Date: February 1st, 2021 DOI: https://doi.org/10.21203/rs.3.rs-164666/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published at Journal of Molecular Modeling on February 22nd, 2021. See the published version at https://doi.org/10.1007/s00894-021-04699-z. Page 1/40 Abstract Hyperlipidemia is thought as an important contributor to coronary disease, diabetes and fatty liver. Liver X receptors β (LXRβ) was considered as a validated target for hyperlipidemia therapy due to its role in regulating cholesterol homeostasis and immunity. However, many current drugs applied in clinic are not selectively targeting LXRβ and they can also activate LXRα which activate SREBP-1c worked as activator of lipogenic genes. Therefore, exploiting agonists selectively targeting LXRβ are urgent. Here, computational tools were used to screen potential agonists selectively targeting LXRβ from 112 terpenes of Alismatis Rhizoma. Firstly, structural analysis between selective and nonselective agonists were used to explore key residues of selective binding with LXRβ. Our data indicated that Phe271, Ser278, Met312, His435, Trp457 were important to compounds binding with LXRβ, suggesting that engaging ligand interaction with these residues may provide directions for development of ligands with improved selective proles.
    [Show full text]
  • Design, Synthesis and Evaluation of Bitopic Arylpiperazine-Phthalimides As Selective Dopamine D3 Receptor Agonists
    Electronic Supplementary Material (ESI) for MedChemComm. This journal is © The Royal Society of Chemistry 2018 Design, Synthesis and Evaluation of Bitopic Arylpiperazine-phthalimides as Selective Dopamine D3 Receptor Agonists Yongkai Caoa,b,c,1, Ningning Sunb,1, Jiumei Zhangc,1, Zhiguo Liud, Yi-zhe Tangc, Zhengzhi Wuc,*, Kyeong-Man Kimb,* and Seung Hoon Cheonb, a Integrated Chinese and Western Medicine Postdoctoral Research Station, Jinan University, Guangzhou 510632, China b College of Pharmacy and Research Institute of Drug Development, Chonnam National University, Gwangju 500-757, Republic of Korea c The First Affiliated Hospital of Shenzhen University, Shenzhen 518035,China d Chemical Biology Research at School of Pharmaceutical sciences, Wenzhou Medical University, Wenzhou 325035, China 1. Docking The SYBYL-X 2.0 program was used for ligand sketching, hydrogen addition, and minimization with the Trips force field and Gasteriger-Huckel charges.1 The dopaminergic receptors, D3R (PDB code: 3PBL) and D2R (PDB code: 6C38), were refined using the Biopolymer module implemented in SYBYL-X 2.0. After the removal of all the ligands and water molecules, the N- and C-termini were treated with charges. Subsequently, hydrogens were added and staged minimizations were performed using AMBER7_FF99 force field and Gasteriger-Marsili charges. The most selective D3R ligand among the identified compounds, compound 9i, was docked into the refined D2R 2 and D3R with the program LeDock (www.lephar.com). Briefly, a rectangular box was generated in the LeDockGUI, a free graphics user interface of VMD, based on the binding pockets of eticlopride in D3R and risperidone in D2R. The compound 9i was docked into the dopaminergic receptors using LeDock program and for each ligands, 30 poses were generated and clustered by a RMSD cutoff of 1 Å.
    [Show full text]
  • Molecular Docking : Current Advances and Challenges
    ARTÍCULO DE REVISIÓN © 2018 Universidad Nacional Autónoma de México, Facultad de Estudios Superiores Zaragoza. This is an Open Access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). TIP Revista Especializada en Ciencias Químico-Biológicas, 21(Supl. 1): 65-87, 2018. DOI: 10.22201/fesz.23958723e.2018.0.143 MOLECULAR DOCKING: CURRENT ADVANCES AND CHALLENGES Fernando D. Prieto-Martínez,1a Marcelino Arciniega2 and José L. Medina-Franco1b 1Facultad de Química, Departamento de Farmacia, Universidad Nacional Autónoma de México, Avenida Universidad # 3000, Delegación Coyoacán, Ciudad de México 04510, México 2Instituto de Fisiología Celular, Departamento de Bioquímica y Biología Estructural, Universidad Nacional Autónoma de México E-mails: [email protected], [email protected],[email protected] ABSTRACT Automated molecular docking aims at predicting the possible interactions between two molecules. This method has proven useful in medicinal chemistry and drug discovery providing atomistic insights into molecular recognition. Over the last 20 years methods for molecular docking have been improved, yielding accurate results on pose prediction. Nonetheless, several aspects of molecular docking need revision due to changes in the paradigm of drug discovery. In the present article, we review the principles, techniques, and algorithms for docking with emphasis on protein-ligand docking for drug discovery. We also discuss current approaches to address major challenges of docking. Key Words: chemoinformatics, computer-aided drug design, drug discovery, structure-activity relationships. Acoplamiento Molecular: Avances Recientes y Retos RESUMEN El acoplamiento molecular automatizado tiene como objetivo proponer un modelo de unión entre dos moléculas. Este método ha sido útil en química farmacéutica y en el descubrimiento de nuevos fármacos por medio del entendimiento de las fuerzas de interacción involucradas en el reconocimiento molecular.
    [Show full text]
  • Use of QSAR Global Models and Molecular Docking for Developing New
    Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 25 October 2019 Use of QSAR global models and molecular docking for developing new inhibitors of c-src tyrosine kinase Robert Ancuceanu1, Bogdan Tamba*2, Cristina Silvia Stoicescu3, Mihaela Dinu1 1Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania 2Advanced Research and Development Center for Experimental Medicine (CEMEX), Grigore T. Popa University of Medicine and Pharmacy of Iasi, Romania ([email protected]); 3Institute of Physical Chemistry "Ilie Murgulescu", Bucharest, Romania Abstract Prototype of a family of at least nine members, c-src tyrosine kinase is a therapeutically interesting target, because its inhibition might be of interest not only in a number of malignancies, but also in a diverse array of conditions, from neurodegenerative pathologies to certain viral infections. Computational methods in drug discovery are considerably cheaper than conventional methods and offer opportunities of screening very large numbers of compounds in conditions that would be simply impossible within the wet lab experimental settings. We have explored the use of global QSAR models and molecular ligand docking in the discovery of new c-src tyrosine kinase inhibitors. Using a data set of 1038 compounds from ChEMBL and 19 blocks of molecular descriptors, we have developed over 200 QSAR classification models, based on six machine learning algorithms and 17 feature selection methods. We have selected 49 with reasonably good performance (positive predictive value and balanced accuracy higher than 70% in nested cross validation) and the models were assembled by stacking with a simple majority vote and used for the virtual screening of over the “named” ZINC data set (over 100,000 compounds).
    [Show full text]
  • Computer?Aided Docking: an Invaluable Tool in Drug Discovery
    IJPCBS 2017, 7(4), 453-458 Nagaraju Pappula et al. ISSN: 2249-9504 INTERNATIONAL JOURNAL OF PHARMACEUTICAL, CHEMICAL AND BIOLOGICAL SCIENCES Available online at www.ijpcbs.com Review Article COMPUTER‐AIDED DOCKING: AN INVALUABLE TOOL IN DRUG DISCOVERY AND MOLECULAR BIOLOGY Nagaraju Pappula*, Ravichandra Sharabu and Pradeep Kumar Thadiboina Hindu College of Pharmacy, Amaravathi Road, Guntur – 522 002, Andhra Pradesh, India. ABSTRACT Docking is a pharmacologically important tool in the field of drugs designing and computational biology. It works with the basic understanding of structure prediction of intermolecular complex formed between drug and its target molecule. The aim of ligand-receptor docking is to identify the pivotal active binding sites of a ligand with a protein of already known three-dimensional structures. Molecular docking is a computational procedure that aims to predict the favored orientation of a ligand to its macromolecular target when these are bound to each other to form a stable complex. The present review focused on importance of docking and its applications in drug innovation. The relevant basic theories including sampling algorithms, scoring functions are summarized. The differences in and performances of available docking software are also discussed. Keywords: Dock, Drug discovery, Scoring and Lipinski rule. INTRODUCTION coordinates. Furthermore, for flexible ligand Computational docking or computer‐aided docking, we should also define ligand bonds that docking is a tremendously valuable tool to gain are rotatable. All this will be done in a tool called an understanding of protein-ligand interactions Auto Dock Tools (ADT). which is important for the drug discovery 1-3. Docking server integrates a number of Procedure8,9 computational chemistry software specifically Step-1 aimed at correctly calculating parameters4 Receptor building – The receptor complex is needed at different steps of the docking downloaded from RCSB PDB.
    [Show full text]
  • Recent Advances in in Silico Target Fishing
    molecules Review Recent Advances in In Silico Target Fishing Salvatore Galati 1 , Miriana Di Stefano 1 , Elisa Martinelli 1, Giulio Poli 1,* and Tiziano Tuccinardi 1,2 1 Department of Pharmacy, University of Pisa, 56126 Pisa, Italy; [email protected] (S.G.); [email protected] (M.D.S.); [email protected] (E.M.); [email protected] (T.T.) 2 Center for Biotechnology, Sbarro Institute for Cancer Research and Molecular Medicine, College of Science and Technology, Temple University, Philadelphia, PA 19122, USA * Correspondence: [email protected]; Tel.: +39-0502219603 Abstract: In silico target fishing, whose aim is to identify possible protein targets for a query molecule, is an emerging approach used in drug discovery due its wide variety of applications. This strategy allows the clarification of mechanism of action and biological activities of compounds whose target is still unknown. Moreover, target fishing can be employed for the identification of off targets of drug candidates, thus recognizing and preventing their possible adverse effects. For these reasons, target fishing has increasingly become a key approach for polypharmacology, drug repurposing, and the identification of new drug targets. While experimental target fishing can be lengthy and difficult to implement, due to the plethora of interactions that may occur for a single small-molecule with different protein targets, an in silico approach can be quicker, less expensive, more efficient for specific protein structures, and thus easier to employ. Moreover, the possibility to use it in combination with docking and virtual screening studies, as well as the increasing number of web-based tools that have been recently developed, make target fishing a more appealing method for drug discovery.
    [Show full text]
  • Unusual Prenylated Stilbene Derivatives with PTP1B Inhibitory Activity from Artocarpus Styracifolius
    Published online: 2019-10-11 Original Papers Unusual Prenylated Stilbene Derivatives with PTP1B Inhibitory Activity from Artocarpus styracifolius Authors Wenyan Li 1,ZhongjiPu2, Wenfang Yi 1,QingeMa1, Qinhua Lin 3, Guoyue Zhong 1, Pengcheng Yao 1,GangRen1 Affiliations Supporting information available online at 1 Research Center of Natural Resources of Chinese Medicinal http://www.thieme-connect.de/products Materials and Ethnic Medicine, Jiangxi University of Tradi- tional Chinese Medicine, Nanchang, China ABSTRACT 2 School of Life Science and Biotechnology, Dalian University of Technology, Dalian, China In an effort to identify agents from natural products that in- 3 School of Pharmacy, Gannan Health Vocational College, hibit protein tyrosine phosphatase 1B (PTP1B), 5 new preny- Ganzhou, China lated stilbenes, (±)-styrastilbene A (1), styrastilbene B (2), and (±)-styrastilbenes C–E(3, 4,and7),alongwith4known Key words structurally related compounds (5, 6, 8,and9), were isolated Artocarpus styracifolius, Moraceae, prenylated stilbene, from the roots of Artocarpus styracifolius.Theirstructures diabetes, PTP1B inhibitory activity, molecular docking were elucidated by spectroscopic methods, including 1D and 2D nuclear magnetic resonance (NMR), high-resolution elec- received May 29, 2019 trospray ionization mass spectrometry (HRESIMS), ultraviolet revised August 28, 2019 (UV), and infrared (IR). Based on these isolates, a new plausi- accepted September 12, 2019 ble biosynthetic pathway for the unusual stilbene derivatives 3–8 with a tetracyclic ring system is proposed. Among these Bibliography compounds, 1–3, 8,and9 displayed significant PTP1B inhib- DOI https://doi.org/10.1055/a-1013-1417 itory effects with IC50 values ranging from 2.40 (95% confi- Published online October 11, 2019 | Planta Med 2019; 85: dence interval [CI]: 2.21–2.59) to 8.80 (95% CI: 8.28–9.32) 1263–1274 © Georg Thieme Verlag KG Stuttgart · New York | µM.
    [Show full text]
  • Possible SARS-Coronavirus 2 Inhibitor Revealed by Simulated Molecular Docking to Viral Main Protease and Host Toll-Like Receptor
    Research Article For reprint orders, please contact: [email protected] Possible SARS-coronavirus 2 inhibitor revealed by simulated molecular docking to viral main protease and host toll-like receptor Xiaopeng Hu1,2 , Xin Cai1, Xun Song2, Chenyang Li2, Jia Zhao1, Wenli Luo1, Qian Zhang2, Ivo Otte Ekumi1 & Zhendan He*,2 1Department of Science and Education, Shenzhen Samii Medical Center, Shenzhen, China 2Guangdong Key Laboratory for Genome Stability & Human Disease Prevention, School of Pharmaceutical Sciences, Shenzhen Key Laboratory of Novel Natural Health Care Products, Innovation Platform for Natural Small Molecule Drugs, Engineering Laboratory of Shenzhen Natural Small Molecule Innovative Drugs, Shenzhen University Health Science Center, Shenzhen 518060, China *Author for correspondence: [email protected] Aim: SARS-coronavirus 2 main protease (Mpro) and host toll-like receptors (TLRs) were targeted to screen potential inhibitors among traditional antiviral medicinal plants. Materials & methods: LeDock software was adopted to determine the binding energy between candidate molecules and selected protein pock- ets. Enrichment analyses were applied to illustrate potential pharmacology networks of active molecules. Results: The citrus flavonoid rutin was identified to fit snugly into the Mpro substrate-binding pocket and to present a strong interaction with TLRs TLR2, TLR6 and TLR7. One-carbon metabolic process and nitrogen metabolism ranked high as potential targets toward rutin. Conclusion: Rutin may influence vi- ral functional
    [Show full text]
  • A Modular, Virtual Screening-Led Approach
    The design, synthesis and evaluation of Nrf2-Keap1 PPI inhibitors: a modular, virtual screening-led approach Thesis submitted for the degree of Maser of Philosophy (MPhil) in Medicinal Chemistry Clément Martin Leopold Bechtler Primary Supervisor: Dr Geoffrey Wells Secondary Supervisor: Prof Frank Kozielski School of Pharmacy UCL - University College London 2 Plagiarism statement This report describes research conducted in the UCL School of Pharmacy under the supervision of Dr Geoffrey Wells. I certify that the research described is original and that any parts of the work that have been conducted by collaboration are clearly indicated. I also certify that I have written all the text herein and have clearly indicated by suitable citation any part of this report that hast already appeared in publication. Clément Bechtler 08.10.2017 3 4 Abstract Nrf2 (nuclear factor erythroid 2-related factor 2) is a cap’n’collar bZIP transcription factor and is the main activator of the transcription of over 100 genes that play roles in responses to oxidative stress and detoxifying xenobiotics. The main control of Nrf2 levels is exercised by Keap1 (Kelch- like ECH-associated protein 1) which facilitates the ubiquitination of Nrf2 and therefore its degradation. Keap1 is oxidation-sensitive and upon exposure to oxidants, it changes its conformation and binds Nrf2 tightly. Consequently, de novo-synthesised Nrf2 can accumulate. Following its discovery, Nrf2 received most attention in relation to cancer. Over the time, however, its implication in other pathologies have been more and more acknowledged, namely in inflammation and most importantly in neurodegenerative diseases. Especially Parkinson’s disease (PD), which is the second most common neurodegenerative disease, caused by the progressive loss of dopaminergic neurons in the substantia nigra, has been linked to oxidative stress.
    [Show full text]
  • Identification of Flavone and Its Derivatives As Potential Inhibitors of Transcriptional Regulator Lasr of Pseudomonas Aeruginosa Using Virtual Screening
    bioRxiv preprint doi: https://doi.org/10.1101/523381; this version posted January 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Identification of flavone and its derivatives as potential inhibitors of transcriptional regulator LasR of Pseudomonas aeruginosa using virtual screening Narek Abelyan1, Hovakim Grabski1, Susanna Tiratsuyan1,2 Email addresses: [email protected] , [email protected] , [email protected] 1 Institute of Biomedicine and Pharmacy, Russian-Armenian University 2 Faculty of Biology, Yerevan State University bioRxiv preprint doi: https://doi.org/10.1101/523381; this version posted January 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract Antibiotic resistance is a global problem nowadays and in 2017 the World Health Organization published the list of bacteria for which treatment are urgently needed, where Pseudomonas aeruginosa is of critical priority. Current therapies lack efficacy because this organism creates biofilms conferring increased resistance to antibiotics and host immune responses. The strategy is to “not kill, but disarm” the pathogen and resistance will be developed slowly. It has been shown that LasI/LasR system is the main component of the quorum sensing system in P. aeruginosa. LasR is activated by the interaction with its native autoinducer.
    [Show full text]
  • Peptogrid—Rescoring Function for Autodock Vina to Identify New Bioactive Molecules from Short Peptide Libraries
    molecules Communication PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries Arthur O. Zalevsky 1,2,3,* , Alexander S. Zlobin 1,3, Vasilina R. Gedzun 4 , Roman V. Reshetnikov 2, Maxim L. Lovat 5, Anton V. Malyshev 4, Igor I. Doronin 4, Gennady A. Babkin 4 and Andrey V. Golovin 1,2,6 1 Faculty of Bioengineering, Lomonosov Moscow State University, Moscow 119234, Russia; [email protected] (A.S.Z.); [email protected] (A.V.G.) 2 Ineractomics Lab, Institute of Molecular Medicine, Sechenov First Moscow State Medical University, Moscow 119146, Russia; [email protected] 3 Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia 4 Lactocore Inc., Plymouth, MI 48170, USA; [email protected] (V.R.G.); [email protected] (A.V.M.); [email protected] (I.I.D.); [email protected] (G.A.B.) 5 Department of Human and Animal Physiology, Faculty of Biology, Lomonosov Moscow State University, Moscow 119899, Russia; [email protected] 6 Faculty of Computer Science, National Research University Higher School of Economics, Moscow 101000, Russia * Correspondence: [email protected]; Tel.: +7-926-829-9066 Received: 26 November 2018; Accepted: 9 January 2019; Published: 13 January 2019 Abstract: Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site.
    [Show full text]
  • Improving Reliability of the Virtual Screening Process for Human Dihydroorotate Dehydrogenase Enzyme by Combination of the Ensemble and Consensus Docking Approaches
    Improving reliability of the virtual screening process for human dihydroorotate dehydrogenase enzyme by combination of the ensemble and consensus docking approaches Garri Chilingaryan1,*, Narek Abelyan2,4, Arsen Sargsyan1, Karen Nazaryan1, Andre Serobian4, and Hovakim Zakaryan1,3 1Institute of Molecular Biology of NAS RA, Yerevan, 0014, Armenia 2Russian-Armenian University, Yerevan, 0051, Armenia 3Denovo Sciences, Yerevan, 0033, Armenia 4Advanced Solutions Center, Foundation for Armenian Science and Technology, Yerevan, 0033, Armenia *g [email protected] ABSTRACT The inconsistencies in the performance of the virtual screening (VS) process, depending on the used software and structural conformation of the protein, is a challenging issue in the drug design and discovery field. Varying performance, especially in terms of early recognition of the potential hit compounds, negatively affects the whole process and leads to unnecessary waste of the time and resources. Appropriate application of the ensemble docking and consensus-scoring approaches can significantly increase reliability of the VS results. Dihydroorotate dehydrogenase (DHODH) is a key enzyme in the pyrimidine biosynthesis pathway. It is considered as a valuable therapeutic target in cancer, autoimmune and viral diseases. Based on the conducted benchmark study and analysis of the effect of different combinations of the applied methods and approaches, here we suggested a structure-based virtual screening (SBVS) workflow that can be used to increase the reliability of VS. Introduction The hDHODH is a rate-limiting enzyme of the de novo pyrimidine synthesis pathway. The enzyme catalyzes the oxidation of dihydroorotate to orotate, which is essential for the production of uridine monophosphate1,2 (Fig. 1). Inhibition of hDHODH results in pyrimidine depletion, thereby starving the cell of the essential nucleotides required in the cell cycle.
    [Show full text]