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Structure-Based Virtual Screening of Hypothetical Inhibitors of the Enzyme Longiborneol Synthase—A Potential Target to Reduce Fusarium Head Blight Disease
J Mol Model (2016) 22: 163 DOI 10.1007/s00894-016-3021-1 ORIGINAL PAPER Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease E. Bresso1 & V. L ero ux 2 & M. Urban3 & K. E. Hammond-Kosack3 & B. Maigret2 & N. F. Martins1 Received: 17 December 2015 /Accepted: 27 May 2016 /Published online: 21 June 2016 # Springer-Verlag Berlin Heidelberg 2016 Abstract Fusarium head blight (FHB) is one of the most compounds from a library of 15,000 drug-like compounds. destructive diseases of wheat and other cereals worldwide. These putative inhibitors of longiborneol synthase provide a During infection, the Fusarium fungi produce mycotoxins that sound starting point for further studies involving molecular represent a high risk to human and animal health. Developing modeling coupled to biochemical experiments. This process small-molecule inhibitors to specifically reduce mycotoxin could eventually lead to the development of novel approaches levels would be highly beneficial since current treatments to reduce mycotoxin contamination in harvested grain. unspecifically target the Fusarium pathogen. Culmorin pos- sesses a well-known important synergistically virulence role Keywords Fusarium mycotoxins . Culmorin . Inhibitors . among mycotoxins, and longiborneol synthase appears to be a Homology modeling . Molecular dynamics . Ensemble key enzyme for its synthesis, thus making longiborneol syn- docking thase a particularly interesting target. This study aims to dis- cover potent and less toxic agrochemicals against FHB. These compounds would hamper culmorin synthesis by inhibiting Introduction longiborneol synthase. In order to select starting molecules for further investigation, we have conducted a structure- Fusarium head blight (FHB), caused by Fusarium based virtual screening investigation. -
Virtual Screening of the Inhibitors Targeting at the Viral Protein 40 of Ebola Virus V
Karthick et al. Infectious Diseases of Poverty (2016) 5:12 DOI 10.1186/s40249-016-0105-1 RESEARCH ARTICLE Open Access Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus V. Karthick1, N. Nagasundaram1, C. George Priya Doss1,2, Chiranjib Chakraborty1,3, R. Siva4, Aiping Lu1, Ge Zhang1 and Hailong Zhu1* Abstract Background: The Ebola virus is highly pathogenic and destructive to humans and other primates. The Ebola virus encodes viral protein 40 (VP40), which is highly expressed and regulates the assembly and release of viral particles in the host cell. Because VP40 plays a prominent role in the life cycle of the Ebola virus, it is considered as a key target for antiviral treatment. However, there is currently no FDA-approved drug for treating Ebola virus infection, resulting in an urgent need to develop effective antiviral inhibitors that display good safety profiles in a short duration. Methods: This study aimed to screen the effective lead candidate against Ebola infection. First, the lead molecules were filtered based on the docking score. Second, Lipinski rule of five and the other drug likeliness properties are predicted to assess the safety profile of the lead candidates. Finally, molecular dynamics simulations was performed to validate the lead compound. Results: Our results revealed that emodin-8-beta-D-glucoside from the Traditional Chinese Medicine Database (TCMD) represents an active lead candidate that targets the Ebola virus by inhibiting the activity of VP40, and displays good pharmacokinetic properties. Conclusion: This report will considerably assist in the development of the competitive and robust antiviral agents against Ebola infection. -
Qsar Methods Development, Virtual and Experimental Screening for Cannabinoid Ligand Discovery
QSAR METHODS DEVELOPMENT, VIRTUAL AND EXPERIMENTAL SCREENING FOR CANNABINOID LIGAND DISCOVERY by Kyaw Zeyar Myint BS, Biology, BS, Computer Science, Hampden-Sydney College, 2007 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2012 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Kyaw Zeyar Myint It was defended on August 20th, 2012 and approved by Dr. Ivet Bahar, Professor, Department of Computational and Systems Biology Dr. Billy W. Day, Professor, Department of Pharmaceutical Sciences Dr. Christopher Langmead, Associate Professor, Department of Computer Science, CMU Dissertation Advisor: Dr. Xiang-Qun Xie, Professor, Department of Pharmaceutical Sciences ii Copyright © by Kyaw Zeyar Myint 2012 iii QSAR METHODS DEVELOPMENT, VIRTUAL AND EXPERIMENTAL SCREENING FOR CANNABINOID LIGAND DISCOVERY Kyaw Zeyar Myint, PhD University of Pittsburgh, 2012 G protein coupled receptors (GPCRs) are the largest receptor family in mammalian genomes and are known to regulate wide variety of signals such as ions, hormones and neurotransmitters. It has been estimated that GPCRs represent more than 30% of current drug targets and have attracted many pharmaceutical industries as well as academic groups for potential drug discovery. Cannabinoid (CB) receptors, members of GPCR superfamily, are also involved in the activation of multiple intracellular signal transductions and their endogenous ligands or cannabinoids have attracted pharmacological research because of their potential therapeutic effects. In particular, the cannabinoid subtype-2 (CB2) receptor is known to be involved in immune system signal transductions and its ligands have the potential to be developed as drugs to treat many immune system disorders without potential psychotic side- effects. -
Fast Three Dimensional Pharmacophore Virtual Screening of New Potent Non-Steroid Aromatase Inhibitors
View metadata, citation and similar papers at core.ac.uk brought to you by CORE J. Med. Chem. 2009, 52, 143–150 143 provided by Estudo Geral Fast Three Dimensional Pharmacophore Virtual Screening of New Potent Non-Steroid Aromatase Inhibitors Marco A. C. Neves,† Teresa C. P. Dinis,‡ Giorgio Colombo,*,§ and M. Luisa Sa´ e Melo*,† Centro de Estudos Farmaceˆuticos, Laborato´rio de Quı´mica Farmaceˆutica, Faculdade de Farma´cia, UniVersidade de Coimbra, 3000-295, Coimbra, Portugal, Centro de Neurocieˆncias, Laborato´rio de Bioquı´mica, Faculdade de Farma´cia, UniVersidade de Coimbra, 3000-295, Coimbra, Portugal, and Istituto di Chimica del Riconoscimento Molecolare, CNR, 20131, Milano, Italy ReceiVed July 28, 2008 Suppression of estrogen biosynthesis by aromatase inhibition is an effective approach for the treatment of hormone sensitive breast cancer. Third generation non-steroid aromatase inhibitors have shown important benefits in recent clinical trials with postmenopausal women. In this study we have developed a new ligand- based strategy combining important pharmacophoric and structural features according to the postulated aromatase binding mode, useful for the virtual screening of new potent non-steroid inhibitors. A small subset of promising drug candidates was identified from the large NCI database, and their antiaromatase activity was assessed on an in vitro biochemical assay with aromatase extracted from human term placenta. New potent aromatase inhibitors were discovered to be active in the low nanomolar range, and a common binding mode was proposed. These results confirm the potential of our methodology for a fast in silico high-throughput screening of potent non-steroid aromatase inhibitors. Introduction built and proved to be valuable in understanding the binding 14-16 Aromatase, a member of the cytochrome P450 superfamily determinants of several classes of inhibitors. -
Bigger Is Better in Virtual Drug Screens
NEWS & VIEWS RESEARCH might no longer be elusive, but the nitrogen Doney, S. C. Biogeosciences 11, 691–708 (2014). cycle remains a treasure trove for discovery. ■ 6. Knapp, A. N., Casciotti, K. L., Berelson, W. M., Prokopenko, M. G. & Capone, D. G. Proc. Natl Acad. Sci. USA 113, 4398–4403 (2016). Nicolas Gruber is at the Institute of 7. Bonnet, S., Caffin, M., Berthelot, H. & Moutin, T. Biogeochemistry and Pollutant Dynamics, Proc. Natl Acad. Sci. USA 114, E2800–E2801 (2017). ETH Zurich, 8092 Zurich, Switzerland. 8. Wang, W.-L., Moore, J. K., Martiny, A. C. & e-mail: [email protected] Primeau, F. W. Nature 566, 205–211 (2019). 9. DeVries, T. & Primeau, F. J. Phys. Oceanogr. 41, 1. Redfield, A. C. in James Johnstone Memorial Volume 2381–2401 (2011). (ed. Daniel, R. J.) 176–192 (Univ. College Liverpool, 10. Gruber, N. in Nitrogen in the Marine Environment 50 Years Ago 1934). 2nd edn (eds Capone, D. G., Bronk, D. A., 2. Carpenter, E. J. & Capone, D. G. in Nitrogen in the Mulholland, M. R. & Carpenter, E. J.) 1–150 Test tube babies may not be just Marine Environment 2nd edn (eds Capone, D. G., (Elsevier, 2008). Bronk, D. A., Mulholland, M. R. & Carpenter, E. J.) 11. Yang, S., Gruber, N., Long, M. C. & Vogt, M. Glob. round the corner, but the day 141–198 (Elsevier, 2008). Biogeochem. Cycles 31, 1470–1487 (2017). when all the knowledge necessary 3. Gruber, N. Proc. Natl Acad. Sci. USA 113, 12. Kim, I.-N. et al. Science 346, 1102–1106 (2014). to produce them will be available 4246–4248 (2016). -
Autodock Vina Manual
4/21/2021 AutoDock Vina - molecular docking and virtual screening program Home Features Download Tutorial FAQ Manual Questions? AutoDock Vina Manual Contents Features License Tutorial Frequently Asked Questions Platform Notes and Installation Windows Linux Mac Building from Source Other Software Usage Summary Configuration File Search Space Exhaustiveness Output Advanced Options Virtual Screening History Citation Getting Help Reporting Bugs Features Accuracy AutoDock Vina significantly improves the average accuracy of the binding mode predictions compared to AutoDock 4, judging by our tests on the training set used in AutoDock 4 development.[*] Additionally and independently, AutoDock Vina has been tested against a virtual screening benchmark called the Directory of Useful Decoys by the Watowich group, and was found to be "a strong competitor against the other programs, and at the top of the pack in many cases". It should be noted that all six of the other docking programs, to which it was compared, are distributed commercially. AutoDock Tools Compatibility For its input and output, Vina uses the same PDBQT molecular structure file Binding mode prediction accuracy on the test set. format used by AutoDock. PDBQT files can be generated (interactively or in "AutoDock" refers to AutoDock 4, and "Vina" to AutoDock batch mode) and viewed using MGLTools. Other files, such as the AutoDock Vina 1. and AutoGrid parameter files (GPF, DPF) and grid map files are not needed. Ease of Use Vina's design philosophy is not to require the user to understand its implementation details, tweak obscure search parameters, cluster results or know advanced algebra (quaternions). All that is required is the structures of the molecules being docked and the specification of the search space including the binding site. -
Open Chemoinformatic Resources to Explore the Structure, Properties and Chemical Space of Cite This: RSC Adv.,2017,7,54153 Molecules
RSC Advances REVIEW View Article Online View Journal | View Issue Open chemoinformatic resources to explore the structure, properties and chemical space of Cite this: RSC Adv.,2017,7,54153 molecules a ab a Mariana Gonzalez-Medina,´ J. Jesus´ Naveja, Norberto Sanchez-Cruz´ a and Jose´ L. Medina-Franco * New technologies are shaping the way drug discovery data is analyzed and shared. Open data initiatives and web servers are assisting the analysis of the large amounts of data that we are now able to produce. The final goal is to accelerate the process of moving from new data to useful information that could lead to Received 27th October 2017 treatments for human diseases. This review discusses open chemoinformatic resources to analyze the Accepted 21st November 2017 diversity and coverage of the chemical space of screening libraries and to explore structure–activity DOI: 10.1039/c7ra11831g relationships of screening data sets. Free resources to implement workflows and representative web- rsc.li/rsc-advances based applications are emphasized. Future directions in this field are also discussed. Creative Commons Attribution 3.0 Unported Licence. 1. Introduction connections between biological activities, ligands and proteins.3 During the past few years, there has been an important increase Herein we review representative chemoinformatic tools in open data initiatives to promote the availability of free essential to explore the structure, chemical space and properties research-based tools and information.1 While there is still some of molecules. The review is focused on recent and representative resistance to open data in some chemistry and drug discovery free web-based applications. -
Structure Based Pharmacophore Modeling, Virtual Screening
www.nature.com/scientificreports OPEN Structure based pharmacophore modeling, virtual screening, molecular docking and ADMET approaches for identifcation of natural anti‑cancer agents targeting XIAP protein Firoz A. Dain Md Opo1,2, Mohammed M. Rahman3*, Foysal Ahammad4, Istiak Ahmed5, Mohiuddin Ahmed Bhuiyan2 & Abdullah M. Asiri3 X‑linked inhibitor of apoptosis protein (XIAP) is a member of inhibitor of apoptosis protein (IAP) family responsible for neutralizing the caspases‑3, caspases‑7, and caspases‑9. Overexpression of the protein decreased the apoptosis process in the cell and resulting development of cancer. Diferent types of XIAP antagonists are generally used to repair the defective apoptosis process that can eliminate carcinoma from living bodies. The chemically synthesis compounds discovered till now as XIAP inhibitors exhibiting side efects, which is making difculties during the treatment of chemotherapy. So, the study has design to identifying new natural compounds that are able to induce apoptosis by freeing up caspases and will be low toxic. To identify natural compound, a structure‑ based pharmacophore model to the protein active site cavity was generated following by virtual screening, molecular docking and molecular dynamics (MD) simulation. Initially, seven hit compounds were retrieved and based on molecular docking approach four compounds has chosen for further evaluation. To confrm stability of the selected drug candidate to the target protein the MD simulation approach were employed, which confrmed stability of the three compounds. Based on the fnding, three newly obtained compounds namely Caucasicoside A (ZINC77257307), Polygalaxanthone III (ZINC247950187), and MCULE‑9896837409 (ZINC107434573) may serve as lead compounds to fght against the treatment of XIAP related cancer, although further evaluation through wet lab is necessary to measure the efcacy of the compounds. -
Virtual Screening in Drug Design – Overview of Most Frequent Techniques
Mil. Med. Sci. Lett. (Voj. Zdrav. Listy) 2016, vol. 85(2), p. 75-79 ISSN 0372-7025 DOI: 10.31482/mmsl.2016.014 REVIEW ARTICLE VIRTUAL SCREENING IN DRUG DESIGN – OVERVIEW OF MOST FREQUENT TECHNIQUES Tomas Kucera Department of Toxicology and Military Pharmacy, Faculty of Military Health Sciences, University of Defence, Trebesska 1575, 500 01 Hradec Kralove, Czech Republic Received 22 nd May 2016. Revised 5 th June 2016. Published 14 th June 2016. Summary New and modern techniques of drug design are extensively used in parallel or instead of the classic ones. Applicability of virtual screening (VS) is growing with the computational performance. This article includes list and short description of most frequent used methods in VS. These methods are divided into two groups – ligand-based VS and structure-based VS. Ligand based methods include chemical similarity, pharmacophore and quantitative structure-activity relationship. Molecular docking and scoring are methods of the structure-based VS. Key words: virtual screening, drug design, docking, scoring, pharmacophore, fingerprint, QSAR INTRODUCTION technologies and growing computational perfor - mance [2]. The VS has three main advantages – per - Drug design is a costly and time-consuming pro - formance, price and safety – compared with traditi- cess. Some new methods are carried out in parallel onal methods or with in vitro high through-put scre - or instead of the traditional ones in the process of se - ening. It enables to test large databases of compounds arching for new drugs. This new performance tech - without the necessity to hold them. A lot of com - niques are called screening methods. We can enume- pounds predicted to be inactive can be eliminated rate e.g. -
Retro Drug Design: from Target Properties to Molecular Structures
Retro Drug Design: From Target Properties to Molecular Structures Yuhong Wang*, Sam Michael, Ruili Huang, Jinghua Zhao, Katlin Recabo, Danielle Bougie, Qiang Shu, Paul Shinn, Hongmao Sun* National Center for Advancing Translational Sciences (NCATS) 9800 Medical Center Drive, Rockville, MD 20850 *Contact information for the corresponding authors: Yuhong Wang Hongmao Sun, PhD NCATS/NIH NCATS/NIH 9800 Medical Center Dr. 9800 Medical Center Dr. Rockville, MD 20854 Rockville, MD 20854 Phone: 301-480-9855 Phone: 301-480-9839 e-mail: [email protected] e-mail: [email protected] Abstract: To generate drug molecules of desired properties with computational methods is the holy grail in pharmaceutical research. Here we describe an AI strategy, retro drug design, or RDD, to generate novel small molecule drugs from scratch to meet predefined requirements, including but not limited to biological activity against a drug target, and optimal range of physicochemical and ADMET properties. Traditional predictive models were first trained over experimental data for the target properties, using an atom typing based molecular descriptor system, ATP. Monte Carlo sampling algorithm was then utilized to find the solutions in the ATP space defined by the target properties, and the deep learning model of Seq2Seq was employed to decode molecular structures from the solutions. To test feasibility of the algorithm, we challenged RDD to generate novel drugs that can activate µ opioid receptor (MOR) and penetrate blood brain barrier (BBB). Starting from vectors of random numbers, RDD generated 180,000 chemical structures, of which 78% were chemically valid. About 42,000 (31%) of the valid structures fell into the property space defined by MOR activity and BBB permeability. -
A Chemaxon/KNIME Based Tool for Designing Chemical Libraries
A ChemAxon/KNIME based tool for designing chemical libraries Tim Parrott Brock Luty Dart NeuroScience Dart NeuroScience September 25, 2013 ChemAxon UGM Dart NeuroScience Small molecules to maintain cognitive vitality (LTM) Currently about 200 FTEs with build-out expected at 260 Privately held LLC by a single individual Scientific Computing Scientific Computing collaborates with other DNS Departments to deliver solutions that simplify and accelerate the drug discovery process. We rely on our (non-traditional) knowledge and experience in both Science and Technology to develop novel and efficient systems to meet this goal Scientific Computing Groups Computational Bioinformatics Chemistry Project Support Project Support - Modeling Philip Cheung - Target ID *Tami Marrone - SBDD/Library Design Doug Fenger - Expression Analysis / Pathways Meg McCarrick + 1 FTE James Na - Apply Methods - Novel Software algorithms Amy Shih - Pre-LO/LO/PCC - Enterprise Software (with Methods) Bill Sinko Information Methods Management Development Software Development Data / Biz Analysis - Informatics Software Development - Data Capture + 1 Group Lead Ron Blanford - Developing new methods John Jaeger - Analytics Daniel Garden - Enterprise Scale Architecture Tim Parrott - Data Access Kevin Neal - RIA (MVC) with SOA James Harr Hari Muddana - QA/Scientific Support - Extensions for ELN, Spotfire, IJC, etc Eileen Tompkins - Project Management + 1 FTE Heather Jones Background Dart NeuroScience (DNS) 200+ Scientists 50+ Chemists Parallel Synthesis Group We need a About 20 -
Virtual Screening, Docking, ADMET and System Pharmacology Studies
www.nature.com/scientificreports OPEN Virtual screening, Docking, ADMET and System Pharmacology studies on Garcinia caged Xanthone Received: 16 November 2017 Accepted: 20 March 2018 derivatives for Anticancer activity Published: xx xx xxxx Sarfaraz Alam1,2 & Feroz Khan 1,2,3 Caged xanthones are bioactive compounds mainly derived from the Garcinia genus. In this study, a structure-activity relationship (SAR) of caged xanthones and their derivatives for anticancer activity against diferent cancer cell lines such as A549, HepG2 and U251 were developed through quantitative (Q)-SAR modeling approach. The regression coefcient (r2), internal cross-validation regression coefcient (q2) and external cross-validation regression coefcient (pred_r2) of derived QSAR models were 0.87, 0.81 and 0.82, for A549, whereas, 0.87, 0.84 and 0.90, for HepG2, and 0.86, 0.83 and 0.83, for U251 respectively. These models were used to design and screened the potential caged xanthone derivatives. Further, the compounds were fltered through the rule of fve, ADMET-risk and synthetic accessibility. Filtered compounds were then docked to identify the possible target binding pocket, to obtain a set of aligned ligand poses and to prioritize the predicted active compounds. The scrutinized compounds, as well as their metabolites, were evaluated for diferent pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Finally, the top hit compound 1G was analyzed by system pharmacology approaches such as gene ontology, metabolic networks, process networks, drug target network, signaling pathway maps as well as identifcation of of-target proteins that may cause adverse reactions. Cancer is a major public health problem worldwide and is the second-leading cause of death in the United States.