skip to main content
10.1145/3156346.3156358acmotherconferencesArticle/Chapter ViewAbstractPublication PagescsbioConference Proceedingsconference-collections
research-article

In Silico Structure Based Designing of Dihydrofolate Reductase Enzyme Antagonists and Potential Small Molecules That Target DHFR Protein to Inhibit the Folic Acid Biosynthetic Pathways

Authors Info & Claims
Published:07 December 2017Publication History

ABSTRACT

Cancer has several pathways by which it is developed in our body. Among them folic acid biosynthetic pathway is one where dihydrofolate reductase (DHFR) enzyme converts dihydrofolate into tetrahydrofolate which leads to unwanted and uncontrollable growth of tissues. Our aim of this study is to design DHFR antagonistic potential small molecules that inhibits Folic Acid Biosynthetic Pathways. In this study, Human DHFR obtained from Protein Data Bank (PDB) docked with several established anticancer drugs including Afatinib, Doxorubicin, Trimetrexate, Curcumin & Trimethoprim and several potential small molecules including Acarbose, Adenosine monophosphate, Abacavir, Aceprometazine & Isoxyl; obtained from PubChem and Drug Bank respectively. PyMOL and PyRx were used to visualize, curate and dock. For validation purpose Discovery Studio and Ramachandran Plot were run. Results after docking showed best binding affinities of established anticancer drugs with Human DHFR throughout the generations for example Methotrexate to Trimethoprim. Potential small molecules which belong from different therapeutic classes.

References

  1. Berman, H.M. et al. 2014. The Protein Data Bank archive as an open data resource. Journal of Computer-Aided Molecular Design. 28, 10, 1009--1014.Google ScholarGoogle ScholarCross RefCross Ref
  2. Binkowski, T.A. et al. 2003. CASTp: Computed Atlas of Surface Topography of proteins. Nucleic Acids Research. 31, 13, 3352--3355.Google ScholarGoogle ScholarCross RefCross Ref
  3. Dallakyan, S. and Olson, A.J. 2015. Small-molecule library screening by docking with PyRx. Methods in Molecular Biology. 243--250.Google ScholarGoogle Scholar
  4. DeLano, W. 2002. PyMOL: An open-source molecular graphics tool. CCP4 Newsletter On Protein Crystallography. 700.Google ScholarGoogle Scholar
  5. Gangaraju Vamsi K. Lin Haifan 2009. Introduction to Cancer Chemotherapeutics. Nat Rev Mol Cell Biol.10 (2), 1, 116--125.Google ScholarGoogle Scholar
  6. Guex, N. and Peitsch, M.C. 1997. SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling. Electrophoresis. 18, 15, 2714--2723.Google ScholarGoogle ScholarCross RefCross Ref
  7. Knox, C. et al. 2011. DrugBank 3.0: A comprehensive resource for "Omics" research on drugs. Nucleic Acids Research. 39, SUPPL. 1, 1035--1041.Google ScholarGoogle ScholarCross RefCross Ref
  8. Li, Q. et al. 2011. PubChem as a public resource for drug discovery. Drug Discov Today. 15, 23--24, 1052--1057.Google ScholarGoogle Scholar
  9. Lovell, S.C. et al. 2003. Structure validation by C alpha geometry: phi, psi and C beta deviation. Proteins-Structure Function and Genetics. 50, 437--450.Google ScholarGoogle ScholarCross RefCross Ref
  10. O'Boyle, N.M. et al. 2011. Open Babel: An Open chemical toolbox. Journal of Cheminformatics. 3, 10, 33.Google ScholarGoogle ScholarCross RefCross Ref
  11. Polshakov, V.I. 2001. Dihydrofolate reductase: Structural aspects of mechanisms of enzyme catalysis and inhibition. Russian Chemical Bulletin. 50, 10, 1733--1751.Google ScholarGoogle ScholarCross RefCross Ref
  12. Robinson, J. et al. 2013. IPD - The Immuno Polymorphism Database. Nucleic Acids Research. 41, D1, 1234--1240.Google ScholarGoogle ScholarCross RefCross Ref
  13. Sakchaisri, K. et al. 2017. Anticancer activity of a novel small molecule tubulin inhibitor STK899704. Plos One. 12, 3, 1--18.Google ScholarGoogle ScholarCross RefCross Ref
  14. Systems, D. 2017. Biovia discovery studio. COMPREHENSIVE MODELING AND SIMULATIONS FOR LIFE SCIENCESE BIOVIA DISCOVERY STUDIO 8, 2--5.Google ScholarGoogle Scholar
  15. Tamura, K. et al. 2013. MEGA6: Molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution. 30, 12, 2725--2729.Google ScholarGoogle ScholarCross RefCross Ref
  16. Thurston, D.E. 2007. Chemistry and pharmacology of anticancer drugs. British journal of cancer. 97, 12, 1713.Google ScholarGoogle Scholar
  17. Trott, O. and Olson, A. 2010. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry. 31, 2, 455--461.Google ScholarGoogle Scholar
  18. Yu, J. et al. 2009. Roll: A new algorithm for the detection of protein pockets and cavities with a rolling probe sphere. Bioinformatics. 26, 1, 46--52. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. In Silico Structure Based Designing of Dihydrofolate Reductase Enzyme Antagonists and Potential Small Molecules That Target DHFR Protein to Inhibit the Folic Acid Biosynthetic Pathways

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        CSBio '17: Proceedings of the 8th International Conference on Computational Systems-Biology and Bioinformatics
        December 2017
        83 pages
        ISBN:9781450353502
        DOI:10.1145/3156346

        Copyright © 2017 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 December 2017

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed limited

        Acceptance Rates

        Overall Acceptance Rate23of37submissions,62%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader