Molecular Docking of Diminazene Ligands to DNA Minor Groove

Feb 23, 2018 - division undergraduate students to the basics of computer-aided drug ..... contact with the ligands are labeled. Journal of Chemical Ed...
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Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove Yana Kholod, Erin Hoag, Katlynn Muratore, and Dmytro Kosenkov* Department of Chemistry and Physics, Monmouth University, 400 Cedar Avenue, West Long Branch, New Jersey 07764, United States S Supporting Information *

ABSTRACT: The reported project-based laboratory unit introduces upperdivision undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The purpose of this laboratory unit is to dock diminazene and its derivatives to DNA, to estimate their binding energies, and to elucidate details of DNA− ligand intermolecular interactions. The computational procedure also helps to screen binding capabilities of DNA ligands. KEYWORDS: Upper-Division Undergraduate, Physical Chemistry, Laboratory Instruction, Computer-Based Learning, Computational Chemistry, Drugs/Pharmaceuticals, Medicinal Chemistry, Biochemistry

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INTRODUCTION

ment and adoption of research-based undergraduate science curricula.

Revisions to Physical Chemistry and Computational Chemistry Curricula

Computer-Aided Drug Discovery

Computer-aided drug discovery (CADD) has become an integral part of common protocols for initial screening and evaluation of potential drug candidates.11 Molecular docking is an essential technique in CADD that helps to perform a conformational search of ligands and binding modes of the ligands to target biomolecules (DNA, proteins, etc.).11−13 With modern advancements in computer hardware and the availability of free software packages (e.g., AutoDock package),14−16 undergraduate students have opportunities for exposure to the basics of molecular modeling17 and CADD.18 This helps students relate abstract concepts learned in general, organic, and physical chemistry courses to be applied to realistic biomolecular systems. (e.g., DNA, proteins). In the present laboratory unit, students model molecular structures of organic ligands, DNA molecules, and DNA−ligand intermolecular interactions. Students use a widespread CADD technique, molecular docking based on classical mechanics force-fields, which enables exploration of large DNA−ligand systems with hardware resources available in an undergraduate computational chemistry laboratory. The technique has been shown to provide reliable results in predicting DNA−ligand binding modes and energies.19 Despite widespread usage of the molecular docking technique in CADD, there are no presently published laboratory units on molecular docking in undergraduate chemical education, with a notable exception18 that

Integration of research-based activities into laboratory courses is among the top strategies being employed to improve STEM education.1 Integration of research-based projects into undergraduate curricula helps engage students in research at early stages of their careers2 and has an impact similar to that of experiential education and internships in research laboratories.3 The positive impact of research-based projects in analytical,4 organic chemistry,2 and biochemistry5 has been demonstrated. The highly positive impact of course-based undergraduate research experiences for nonscience majors has been reported as well.6 Despite the proven, prominent benefits of research experiences for undergraduates, the implementation of such activities into undergraduate chemistry curricula is challenging and requires substantial investments of time and resources from faculty and departments as compared with traditional laboratories. A major undertaking in the School of Science at Monmouth University is associated with curriculum reform. Our group is actively involved in the initiative to revise our physical and computational chemistry sequence via modernization of the laboratory components of those courses. Specific improvements include integration of active learning techniques, research-based activities, and research-driven laboratory units.7,8 This effort is also a part of a broader Cottrell Scholars Collaborative project on “Promoting Adoption of Research and Inquiry-Based Lab Curricula”9 and efforts of the Molecular Education and Research Consortium in Undergraduate Computational Chemistry (MERCURY) consortium10 toward the develop© XXXX American Chemical Society and Division of Chemical Education, Inc.

Received: December 29, 2017 Revised: February 23, 2018

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DOI: 10.1021/acs.jchemed.7b00989 J. Chem. Educ. XXXX, XXX, XXX−XXX

Journal of Chemical Education

Laboratory Experiment

details the application of AutoDock to evaluate binding affinity of cyclin-dependent kinase type-2 inhibitors. Currently, some basic molecular modeling exercises are included in general chemistry courses. For example, freshman students at Monmouth University investigate molecular structures and hydrogen bonding in double-helix DNA using Spartan software20 in general chemistry laboratory. These activities are commonly followed by more elaborate computational laboratories offered in upper-division undergraduate courses (e.g., organic,21 inorganic chemistry,22 and biochemistry23). In the present laboratory unit, students apply their basic skills in molecular modeling to build organic ligands, followed by molecular docking simulations of interactions of those ligands with a DNA molecule. The theoretical background of the molecular docking technique is covered in the lecture component of the computational chemistry course.24 As molecular docking is based on classical mechanics, it can be mostly explained without invoking quantum chemistry. That makes it accessible for students who have not yet taken physical chemistry or quantum mechanics (e.g., biology majors).

Figure 1. Structures of diminazene (DMZ), triazene-1 (TRZ1), and triazene-2 (TRZ2) ligands.

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LEARNING OBJECTIVES In the reported laboratory unit, students elucidate the factors that determine affinity of DNA minor groove binders to DNA. Students employ a computer-aided drug discovery approach to study given minor groove binder molecules, and they critically asses their ability to bind to a DNA minor groove. Upon completion of this project, students will be able to do the following. • Describe molecular docking as a CADD tool. • Apply computational chemistry software (e.g., GaussView) to build 3D models of organic ligands that bind to DNA minor grooves. • Employ molecular docking software (e.g., AutoDock) to model binding of organic ligands to DNA. • Analyze conformations of free and docked to DNA ligands. • Evaluate binding energies of DNA minor groove binders.

DNA Minor Groove Binding

Binding of small organic ligands to DNA is among the widely used strategies for development of novel antitumor therapeutics.19,25,26 One of the critical aspects of rational drug design is synthesis of ligands that bind selectively to a particular secondary structure of DNA (e.g., double-stranded vs Gquadruplex) and are specific to a particular DNA sequence (e.g., AT- vs GC-rich regions).25,26 Most small molecules ( TRZ1 > TRZ2, which is explained by intermolecular (van der Waals and Hydrogen bonding) interactions. Despite the relative complexity of computational procedures, students demonstrated a strong interest in participating in the laboratory activity and willingness to explore properties of ligands and their binding to DNA. Also, involvement of student research collaborators in the development and implementation

REFERENCES

(1) President’s Council of Advisors on Science and Technology. Engage To Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics; Executive Office of the President: Washington, D.C., 2012; https:// obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ pcast-engage-to-excel-final_2-25-12.pdf (accessed February 2018). (2) Fuller, A. A. Combinatorial Solid-Phase Synthesis of Aromatic Oligoamides: A Research-Based Laboratory Module for Undergraduate Organic Chemistry. J. Chem. Educ. 2016, 93 (5), 953−957. (3) Corwin, L. A.; Graham, M. J.; Dolan, E. L. Modeling CourseBased Undergraduate Research Experiences: An Agenda for Future Research and Evaluation. CBE Life Sci. Educ. 2015, 14 (1), es1−es13. (4) Kerr, M. A.; Yan, F. Incorporating Course-Based Undergraduate Research Experiences into Analytical Chemistry Laboratory Curricula. J. Chem. Educ. 2016, 93 (4), 658−662. (5) Bering, C. L.; Kuhns, J. J.; Rowlett, R. Purification of Bovine Carbonic Anhydrase by Affinity Chromatography: An Undergraduate Biochemistry Laboratory Experiment. J. Chem. Educ. 1998, 75 (8), 1021−1024. (6) Ballen, C. J.; Blum, J. E.; Brownell, S.; Hebert, S.; Hewlett, J.; Klein, J. R.; McDonald, E. A.; Monti, D. L.; Nold, S. C.; Slemmons, K. E.; Soneral, P. A. G.; Cotner, S. A Call to Develop Course-Based E

DOI: 10.1021/acs.jchemed.7b00989 J. Chem. Educ. XXXX, XXX, XXX−XXX

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Undergraduate Research Experiences (CUREs) for Nonmajors Courses. CBE Life Sci. Educ. 2017, 16 (2), mr2−7. (7) Kosenkov, D.; Shaw, J.; Zuczek, J.; Kholod, Y. Transient Absorption Spectroscopy of Cis-Trans Isomerization of N,NDimethyl-4,4′-Azodianiline with 3D-Printed Temperature Controlled Sample Holder. J. Chem. Educ. 2016, 93 (7), 1299−1304. (8) Famularo, N.; Kholod, Y.; Kosenkov, D. Integrating Chemistry Laboratory Instrumentation into the Industrial Internet: Building, Programming, and Experimenting with an Automatic Titrator. J. Chem. Educ. 2016, 93 (1), 175−181. (9) Cottrell Scholars. Cottrell Scholars Collaborative; Research Corporation for Science Advancement, 2017. http://rescorp.org/ cottrell-scholars/cottrell-scholars-collaborative (accessed February 2018). (10) Molecular Education and Research Consortium in Undergraduate Computational Chemistry (MERCURY); Mercury Consortium, 2018. https://mercuryconsortium.org/ (accessed February 2018). (11) Bajorath, J. Computer-Aided Drug Discovery [version 1; referees: 3 approved]. F1000Research 2015, 4, 630. (12) de Ruyck, J.; Brysbaert, G.; Blossey, R.; Lensink, M. F. Molecular Docking as a Popular Tool in Drug Design, an In Silico Travel. Adv. Appl. Bioinform. Chem. 2016, 9, 1−11. (13) Chaudhary, K. K.; Mishra, N. A Review on Molecular Docking: Novel Tool for Drug Discovery. JSM Chem. 2016, 4 (3), 1029. (14) Morris, G. M.; Huey, R.; Lindstrom, W.; Sanner, M. F.; Belew, R. K.; Goodsell, D. S.; Olson, A. J. Autodock4 and AutoDockTools4: Automated Docking with Selective Receptor Flexibility. J. Comput. Chem. 2009, 30, 2785−2791. (15) Alcaro, S.; Musetti, C. Identification and Characterization of New DNA G-Quadruplex Binders Selected by a Combination of Ligand and Structure-Based Virtual Screening Approaches. J. Med. Chem. 2013, 56, 843−855. (16) Gauto, D. F.; Petruk, A. A.; Modenutti, C. P.; Blanco, J. I.; Di Lella, S.; Marti, M. A. Solvent Structure Improves Docking Prediction in Lectin−Carbohydrate Complexes. Glycobiology 2013, 23, 241−258. (17) Shields, G. C. The Physical Chemistry Sequence at Liberal Arts Colleges: The Lake Forest College Approach. J. Chem. Educ. 1994, 71 (11), 951−953. (18) Helgren, T. R.; Hagen, T. J. Demonstration of AutoDock as an Educational Tool for Drug Discovery. J. Chem. Educ. 2017, 94 (3), 345−349. (19) Prato, G.; Silvent, S.; Saka, S.; Lamberto, M.; Kosenkov, D. Thermodynamics of Binding of Di- and Tetrasubstituted Naphthalene Diimide Ligands to DNA G-Quadruplex. J. Phys. Chem. B 2015, 119 (8), 3335−3347. (20) Hehre, W.; Ohlinger, S. Spartan Tutorial and User’s Guide; Wavefunction, Inc.: Irvine, CA, 2010. (21) Best, K. T.; Li, D.; Helms, E. D. Molecular Modeling of an Electrophilic Addition Reaction with “Unexpected” Regiochemistry. J. Chem. Educ. 2017, 94 (7), 936−940. (22) Montgomery, C. D. Fischer and Schrock Carbene Complexes: A Molecular Modeling Exercise. J. Chem. Educ. 2015, 92 (10), 1653− 1660. (23) McLaughlin, K. J. Understanding Structure: A Computer-Based Macromolecular Biochemistry Lab Activity. J. Chem. Educ. 2017, 94 (7), 903−906. (24) Leach, A. R. Molecular Modelling: Principles and Applications, 2nd ed.; Pearson: New York, 2001. (25) Wang, C.; Carter-Cooper, B.; Du, Y.; Zhou, J.; Saeed, M. A.; Liu, J.; Guo, M.; Roembke, B.; Mikek, C.; Lewis, E. A.; Lapidus, R. G.; Sintim, H. O. Alkyne-Substituted Diminazene as G-Quadruplex Binders with Anticancer Activities. Eur. J. Med. Chem. 2016, 118, 266−275. (26) Zhou, J.; Le, V.; Kalia, D.; Nakayama, S.; Mikek, C.; Lewis, E. A.; Sintim, H. O. Diminazene or Berenil, a Classic Duplex Minor Groove Binder, Binds to G-Quadruplexes with Low Nanomolar Dissociation Constants and the Amidine Groups are Also Critical for G-quadruplex Binding. Mol. BioSyst. 2014, 10 (10), 2724−2734.

(27) Cai, X.; Gray, P. J., Jr.; Von Hoff, D. D. DNA Minor Groove Binders: Back in the Groove. Cancer Treat. Rev. 2009, 35 (5), 437− 450. (28) Neidle, S. DNA Minor-Groove Recognition by Small Molecules. Nat. Prod. Rep. 2001, 18 (3), 291−309. (29) GaussView, Version 5; Dennington, R., Keith, T., Millam, J., Eds.; Semichem Inc.: Shawnee Mission, KS, 2009. (30) Hertwig, R. H.; Koch, W. On the Parameterization of the Local Correlation Functional: What is Becke-3-LYP? Chem. Phys. Lett. 1997, 268, 345−351. (31) Ditchfield, R.; Hehre, W. J.; Pople, J. A. Self-Consistent Molecular-Orbital Methods. IX. An Extended Gaussian-Type Basis for Molecular-Orbital Studies of Organic Molecules. J. Chem. Phys. 1971, 54, 724−728. (32) Hehre, W. J.; Ditchfield, R.; Pople, J. A. Self-Consistent Molecular Orbital Methods. XII. Further Extensions of Gaussian-Type Basis Sets for Use in Molecular Orbital Studies of Organic Molecules. J. Chem. Phys. 1972, 56, 2257−2261. (33) Rassolov, V. A.; Ratner, M. A.; Pople, J. A.; Redfern, P. C.; Curtiss, L. A. 6-31G* Basis Set for Third-Row Atoms. J. Comput. Chem. 2001, 22, 976−984. (34) Hariharan, P. C.; Pople, J. A. The Influence of Polarization Functions on Molecular Orbital Hydrogenation Energies. Theoret. Chim. Acta 1973, 28, 213−222. (35) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, O.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, revision D.01; Gaussian, Inc.: Wallingford, CT, 2009. (36) Schmidt, M. W.; Baldridge, K. K.; Boatz, J. A.; Elbert, S. T.; Gordon, M. S.; Jensen, J. H.; Koseki, S.; Matsunaga, N.; Nguyen, K. A.; Su, S.; Windus, T. L.; Dupuis, M.; Montgomery, J. A. General Atomic and Molecular Electronic Structure System. J. Comput. Chem. 1993, 14, 1347−1363. (37) Gordon, M. S.; Schmidt, M. W. Advances in Electronic Structure Theory: GAMESS a Decade Later. In Theory and Applications of Computational Chemistry: The First Forty Years; Dykstra, C.E., Frenking, G., Kim, K.S., Scuseria, G.E., Eds.; Elsevier: Amsterdam, 2005; pp 1167−1189. (38) Brown, D. G.; Sanderson, M. R.; Skelly, J. V.; Jenkins, T. C.; Brown, T.; Garman, E.; Stuart, D. I.; Neidle, S. Crystal Structure of a Berenil-Dodecanucleotide Complex: the Role of Water in SequenceSpecific Ligand Binding. EMBO J. 1990, 9 (4), 1329−1334. (39) ArgusLab; ArgusLab, 2018. http://www.arguslab.com/arguslab. com/ArgusLab.html (accessed February 2018). (40) Lindorff-Larsen, K.; Piana, S.; Palmo, K.; Maragakis, P.; Klepeis, J. L.; Dror, R. O.; Shaw, D. E. Improved Side-Chain Torsion Potentials for the Amber ff99SB Protein Force Field. Proteins: Struct., Funct., Genet. 2010, 78, 1950−1958. (41) AutoDock 4.2 User Guide; The Scripps Research Institute, 2018. http://autodock.scripps.edu/faqs-help/manual/autodock-4-2-userguide (accessed February 2018).

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DOI: 10.1021/acs.jchemed.7b00989 J. Chem. Educ. XXXX, XXX, XXX−XXX