Preface Progress in molecular biology and studies of small molecule binding to nu- cleic acids have been inextricably linked. A testament to that fact is the inclusion of eight papers directly concerned with drug-DNA interactions among the recently published list of the 100 most cited articles in the Journal of Molecular Biology. Few other scientific areas are as well represented on that list. Small molecules have perhaps taught us more about DNA than DNA has taught us about small molecules. Watson, for example, notes in the Molecular Biology of the Gene that the "fact that intercalation occurs so readily indicates that it is energetically favored [and] is additional evidence for the metastability of the double-helical structure its ability to assume many inherently unstable configurations that normally revert quickly back to the standard B conformation." From that point of view, intercalation pro- vided one of the very first indications of the plasticity of DNA, an area that has blossomed to reveal an incredible diversity of structural forms. Perhaps the most widespread interest in small molecules that bind to nucleic acids stems from their potential as useful pharmaceutical agents. Indeed, some of the very best anticancer drugs are well-documented DNA binders. While interest in drug-DNA interactions has at times waned, recent advances in chemical synthesis, analytical instrumenta- tion to measure binding, and structural biology have greatly enhanced the potential for rational design of new therapeutic compounds. Accordingly, studies on the in- teraction of small molecules with nucleic acids have taken on new life and have helped spawn several emergent biotechnology companies dedicated to exploiting the promise of making new types of pharmaceuticals targeted at nucleic acids. The aim of this volume is to consolidate key methods for studying ligand- nucleic acid interactions, both old and new, into a convenient source. Accordingly, we have solicited from experts in a variety of disciplines articles that concisely but completely describe useful methods and strategies for studying small molecule binding to nucleic acids. Techniques that are useful now range from biophysical and chemical approaches to methods rooted in molecular and cell biology. We hope that this volume will serve as a useful compendium of methods both to newcomers entering the field as well as to scientists already actively engaged in research in this area. JONATHAN B. CHAIRES MICHAEL J. WARING xiii Contributors to Volume 340 Article numbers are in parentheses following the names of contributors. Affiliations listed are current. CHRISTIAN BAILLY (24, 31), INSERM U-524, and Laboratoire de Pharmaco- logie Antitumorale du Centre Oscar Lambret IRCL, 59045 Lille, France ALBERT S. BENIGHT (8), Department of Chemistry, University of Illinois, Chicago, Illinois 60607 and DNA Codes LLC, Chicago, Illinois 60601 LAWRENCE A. BOTTOMLEY (11), School of Chemistry and Biochemistry, Georgia In- stitute of Technology, Atlanta, Georgia 30332 SOPHIA Y. B REUSEGEM (10), Laboratoryfi~r Fluorescence Dynamics, Department of Physics, University of Illinois, Urbana, Illinois 61801 JONATHAN B. CHAIRES (1, 5, 27), De- partment of Biochemistry, University of Mississippi Medical Center, Jackson, Mississippi 39216 YEN CHOO (30), Gendaq Limited, London NW7 lAD, United Kingdom BABUR Z. CHOWDHRY (6), School of Chem- ical and Life Sciences, University of Greenwich, London SE18 6PF, United Kingdom ROBERT M. CLEGG (10), Laboratory for Fluorescence Dynamics, Department of Physics, University of Illinois, Urbana, Illinois 61801 DONALD M. CROTHERS (3, 23), Depart- ment of Chemistry, Yale University, New Haven, Connecticut 06520-8107 MARK S. CUBBERLEY (28), Department of Chemistry and Biochemistry, University of Texas, Austin, Texas 78712 CARLEEN M. CULL1NANE (23), Pharma- cology and Developmental Therapeutics Unit, Peter MacCallum Cancer Institute, Victoria 3002, Australia SUZANNE M. CUTrS, (23), Department of Biochemistry, La Trobe University, Bun- doora, Victoria 3083, Australia JAMES C. DABROWIAK (21), Department of Chemistry, Center for Science and Tech- nology, Syracuse University, Syracuse, New York 13244 TINA M. DAVIS (2), Department of Chem- istry, Georgia State University, Atlanta, Georgia 30303 PETER B. DERVAN (22), Department of Chemistry, California Institute of Tech- nology, Pasadena, California 91125 MAGDALENA ERIKSSON (4), Department of Physical Chemistry, Chalmers University of Technology, Gothenburg SE-41296, Sweden, and Department of BiD- chemistry, University of Gothenburg, Gothenburg SE-40530, Sweden CHRISTOPHE ESCUDI~ (16), Laboratoire de Biophysique, INSERM U201, CNRS UMR 8646, Museum National d'Histoire Naturelle, 75231 Paris Cedex 05, France IZABELA FOKT (27), M. D. Anderson Can- cer Center, University of Texas, Houston, Texas 77030 KEITH R. Fox (20), Division of Biochemistry and Molecular Biology, School of Bio- logical Sciences, University of Southamp- ton, Southampton S016 7PX, United Kingdom x CONTRIBUTORS TO VOLUME 340 THI~RI~SE GARESTIER (16), Laboratoire de Biophysique, 1NSERM U201, CNRS UMR 8646, Museum National d'Histoire Naturelle, 75231 Paris Cedex 05, France JERRY GOOD1SMAN (21), Department of Chemistry, Center for Science and Tech- nology, Syracuse University, Syracuse, New York 13244 DAVID E. GRAVES (18), Department of Chemistry, University of Mississippi, University, Mississippi 38677 KEITH A. GRIMALDI (17), CRC Drug-DNA Interactions Research Group, Royal Free and University College Medical School, University College London, London WI P 8BT, United Kingdom VLAD1M1R M. GUELEV (28), Department of Chemistry and Biochemistry, Universi~" of Texas, Austin, Texas 78712 IHTSHAMUL HAG (6), Krebs Institute for Biomolecular Science, Department of Chemisto, University of Sheffield, Sheffield $3 7HF, United Kingdom JOHN A. HARTLEY (17), CRC Drug-DNA Interactions Research Group, Royal Free and University College Medical School, University College London, London W1P 8BT, United Kingdom PAUL B. HOPKINS (19), Department of Chemistry, University of Washington, Seattle, Washington 98195 LAURENCE H. HURLEY (29), College of Pharmacy, University of Arizona, Tucson, Arizona 85721 and Arizona Cancer Cen- ter, Tucson, Arizona 85724 MARK ISALAN (30), Gendaq Limited, London NW7 laD, United Kingdom BRENT L. IVERSON (28), Department of Chemistry and Biochemistry, University of Texas, Austin, Texas 78712 TERENCE C. JENKINS (6), Yorkshire Cancer Research Laboratory of Drug Design, Cancer Research Group, University of Bradford, Bradford BD7 1DP, United Kingdom BESIK I. KANKIA (7), Department of Pharmaceutical Sciences, University ~f Nebraska Medical Center, Omaha, Nebraska 68198 ASMITA KUMAR (33), Department of Bio- chemistry, University of Mississippi, Jackson, Mississippi 39216 DONALD W. KUPKE (7), Department of Chemistrry, University of Virginia, Char- lottesville, Virginia 22901 ANDREW N. LANE (12), Division of Molecu- lar Structure, National Institute for Med- ical Research, London NW7 IAA, United Kingdom GREGORY H. LENO (33), lnfgen Incorpo- rated, DeForest, Wisconsin 53532 PETER T. LILLEHEI (l l), School of Chem- istry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332 R. SCOTT LOKEY (28), Department of Chemistry and Biochemistr); University of Texas, Austin, Texas 78712 FRANK G. LOONTIENS (10), Laboratory for Biochemistry, WEVIO, University of Gent, Gent 9000, Belgium RYAN A. LUCE (19), Department of Chem- istr); University of Washington, Seattle, Washington 98195 CHRISTOPHE MARCHAND (32), Laboratory of Molecular Pharmacology, Division of Basic Sciences, National Cancer In- stitute, National Institutes of Health, Bethesda, Maryland 20892 LUIS A. MARKY (7), Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska 68198 CLAIRE J. MCGURK (17), CRC Drug-DNA Interactions Research Group, Royal Free and University College Medical School, University College London, London WI P 8BT, United Kingdom CONTRIBUTORS TO VOLUME 340 xi PETER J. MCHUGH (17), CRC Drug-DNA Interactions Research Group, Royal Free and University College Medical School, University College London, London W1P 8BT, United Kingdom MARK P. MCPIKE (21), Department of Chemistry, Center for Science and Tech- nolog); Syracuse University, Syracuse, New York 13244 MEREDITH M. MURR (28), Department of Chemistry and Biochemistry, Universi~ of Texas, Austin, Texas 78712 NOURI NEAMATI (32), Laboratory of Molec- ular Pharmacology, Division of Basic Sciences, National Cancer Institute, Na- tional Institutes of Health, Bethesda, Maryland 20892 JAROSLAV NESETI~IL (8), Department of Applied Mathematics, Faculty of Math- ematics and Physics, Charles Universi~, 118 O0 Praha 1, Czech Republic PETER E. NIELSEN (15), Department of Medical Biochemistry and Genetics, The Panum Institute, University of Copen- hagen, Copenhagen DK-2200, Denmark BENGT NORD~N (4), Department of Phys- ical Chemistry, Chalmers University of Technology, Gothenburg SE-41296, Sweden RICHARD OWCZARZY (8), Department of Chemistry, University of Illinois, Chicago, Illinois 60607, and Integrated DNA Technologies, Coralville, Iowa 52241 PETR PAN(~OSKA (8), Department of Chem- istry, University of Illinois, Chicago, Illinois 60607, and Center for Discrete Mathematics, Applied Computer Science and Applications DIMAT1A, Charles University, Prague, Czech Republic, and DNA Codes LLC, Chicago, Illinois 60601 MARY ELIZABETH PEEK (13), School of Chemistry and Biochemistry, Georgia In- stitute of Technology, Atlanta, Georgia 30332 DON R. PHILLIPS (23), Department of Biochemistry, LaTrobe Universit3; Bundoora, Victoria 3083, Australia YVES POMMIER (32), Laboratory of Molec- ular Pharmacolog); Division of Basic Sciences, National Cancer Institute, Na- tional Institutes of Health, Bethesda, Maryland 20892 JOSl~ PORTUGAL (25, 27), Departamento de Biologia Molecular y Celular, lnstituto de Biologia Molecular de Barcelona, CSIC, Barcelona 08034, Spain WALDEMAR PRIEBE (27), M. D. Ander- son Cancer Center, University of Texas, Houston, Texas 77030 TERESA PRZEWLOKA (27), M. D. Ander- son Cancer Center, University of Texas, Houston, Texas 77030 PETER REGENFUSS (10), Laboratory for Fluorescence Dynamics, Department of Physics, Universi~' of Illinois, Urbana, Illinois 61801 JINSONG REN (5), Department of Biochem- istry, University of Mississippi Medical Center, Jackson, Mississippi 39216 PETER V. RICCELLI (8), Department of Chemistry, University of Illinois, Chicago, Illinois 60607, and DNA Codes LLC, Chicago, Illinois 60601 RICHARD D. SHEARDY (26), Department of Chemistry and Biochemistry, Seton Hall Universit); South Orange, New Jersey 07079 ANGELA M. SNOW (26), Memorial High School, Elmwood Park, New Jersey 07407 CHARLES H. SPINK (9), Department of Chemistry, State University of New York, Cortland, New York 13045 DAEKYU SUN (29), Institute for Drug De- velopment, San Antonio, Texas 78245 JIAN-SHENG SUN (16), Laboratoire de Biophysique, INSERM U201, CNRS UMR 8646, Museum National d'Histoire Naturelle, 75231 Paris Cedex 05, France xii CONTRIBUTORS TO VOLUME 340 MICHAEL J. TILBY (17), Cancer Research Unit, Medical School, University of New- castle Upon Tyne, Newcastle NE2 4HH, United Kingdom JOHN W. TRAUGER (22), Department of Chemistry, California Institute of Technology, Pasadena, California 91125 JOHN O. TRENT (14, 27), James Gra- ham Brown Cancer Center, Department of Medicine, University of Louisville, Louisville, Kentucky 40202 PETER M. VALLONE (8), Department of Chemistry, University of Illinois, Chicago, Illinois 60607 and National Institute of Standards" and Technology, Biotechnology Division, Gaithersburg, Mao, land 20899 MICHAEL J. WARING (20, 24), Department of Pharmacology, University of Cam- bridge, Cambridge CB2 IQJ, United Kingdom SUSAN E. WELLMAN (9), Department of Pharmacology and Toxicolog), Uni- versity of Mississippi Medical Center, Jackson, Mississippi 39216 LOREN DEAN WILLIAMS (13), School of Chemistry and Biochemistry, Georgia In- stitute of Technology, Atlanta, Georgia 30332 W. DAVID WILSON (2), Department of Chemistry, Georgia State University, Atlanta, Georgia 30303 HONGZH1 XU (33), Department of Biochem- istry, University of Mississippi, Jackson, Mississippi 39216 STEVEN M. ZEMAN (3), Department of Chemistry, Yale University, New Haven, Connecticut 06520 [1] ANALYSTS OF LIGAND-DNA BINDING ISOTHERMS 3 [1] Analysis and Interpretation of Ligand-DNA Binding Isotherms By JONATHAN B. CHA1RES Introduction To attain a reasonable understanding of any ligand-receptor interaction, it is necessary to answer the questions posed by Scatchard ~ more than 50 years ago: "How many? How tightly? Where? Why? What of it?" The first two Questions (and in part the third) can be answered by equilibrium binding studies, and are the pri- mary focus of this chapter. The remaining questions concisely express the concerns of structural and functional studies, and may be addressed by X-ray crystallogra- phy, nuclear magnetic resonance (NMR) techniques, molecular modeling, and a variety of chemical and molecular biological methods. Macromolecular binding is a phenomenon of general interest, and the underlying general principles are the same for ligand binding to proteins or to nucleic acids. A number of excellent general treatments of macromolecular binding are available that explain the un- derlying physical chemistry in detail .2-6 What distinguishes the binding of small molecules to DNA from their binding to proteins is the need to account for behav- ior arising from the lattice properties of linear DNA molecules. Various neighbor exclusion models have evolved to cope with that complexity, and are described. An excellent discussion of the principles of nucleic acid binding interactions is provided by Bloomfield et al. 7 Determination of the binding constant K allows the binding free energy change, AG, to be calculated by the standard Gibbs equation, AG = - RT In K, where R is the gas constant and T is the temperature in degrees Kelvin. From studies of the temperature dependence of the binding constant, or (preferably) by calorimetric studies, the binding enthalpy (AH) may be obtained. The binding free energy may then be partitioned into its enthalpic and entropic components, AG = AH TAS, where AS is the entropy change. Knowledge of these thermodynamic parameters I G. Scatchard, Ann. N.Y. Acad. Sci. 51,660 (1949). 2 j. T. Edsall and J. Wyman, "Biophysical Chemistry." Academic Press, New York, 1958. 3 j. Wyman and S. J. Gill, "Binding and Linkage." University Science Books, Mill Valley, California, 1990. 41. M. Klotz, "Ligand Receptor Energetics." John Wiley & Sons, New York, 1997. 5 E. diCera, "Thermodynamic Theory of Site-Specific Binding Processes in Biological Macro- molecules." Cambridge University Press, Cambridge, 1995. 6 G. Weber, "Protein Interactions." Chapman & Hall, New York, 1992. 7 V. A. Bloomfield, D. M. Crothers, and J. Ignacio Tinoco, "Nucleic Acids: Structures, Properties and Functions," 1st Ed. University Science Books, Sausalito, California, 2000. Copyright © 2001 by Academic Press All rights of reproduction in any form reserved. METHODS IN ENZYMOLOGY, VOL. 340 0076-6879/00 $35.00 4 BIOPHYSICAL APPROACHES [ 11 provides a firm foundation for understanding the molecular forces that govern the binding reaction, allowing one to begin to address Scatchard's question "Why?" Details of attempts to parse binding free energies for ligand-DNA interactions in order to understand the contribution of various molecular forces are described in publications from this and other laboratories, s- 12 The aim of this chapter is to offer a concise guide for the analysis and interpre- tation of ligand-DNA binding isotherms. Methods for experimentally obtaining binding data are not discussed because detailed, practical descriptions of experi- mental protocols are available. 13 15 In this chapter, examples of binding data are taken from results obtained in the author's laboratory with the anticancer agent daunomycin (daunorubicin). Daunomycin is perhaps the best-characterized DNA intercalator, and its binding to a wide variety of DNA sequences and structures has been thoroughly investigated. ~ 6,17 Model-Independent Approaches Figure 1 shows the results from two types of binding experiments, each of which addresses one of Scatcbard's queries as directly as possible. The method of continuous variations Is-a1 may be used to construct a so-called Job plot (Fig. 1A). Binding stoichiometries may be determined from such plots without recourse to any assumed binding model. For the data shown in Fig. 1A for the interaction of daunomycin with calf thymus DNA, an inflection near 0.2 mol fraction ligand indicates a binding stoichiometry of one ligand per 3 or 4 base pairs. The exact stoichiometry from the inflection at 0.21 mol fraction is (1.0 - 0.21)/0.21 = 3.76 base pairs. This value represents the predominant binding mode, although an s j. B. Chaires, Anticancer Drug Des. 11,569 (1996). 9 j. B. Chaires, Biopolymers 44, 201 (1997). l01. Haq, J. E. Ladbury, B. Z. Chowdhry, T. C. Jenkins, and J. B. Chaires, J. Mol. Biol. 271,244 (1997). II j. Ren, T. C. Jenkins, and J. B. Chaires, Biochemistry 39, 8439 (2000). 12 S. Mazur, F. A. Tanious, D. Ding, A. Kumar, D. W. Boykin, I. J. Simpson, S. Neidle, and W. D. Wilson, J. Mol. Biol. 300, 321 (2000). 13 X. Qu and J. B. Chaires, Methods Enzymol. 321, 353 (2000). L4 T. C. Jenkins, in "Drug-DNA Interaction Protocols" (K. R. Fox, ed.), Vol. 90, pp. 195-218. Humana Press, Totowa, New Jersey, 1997. 15 p. C. Dedon, in "Current Protocols in Nucleic Acid Chemistry" (S. L. Beaucage, D. E. Bergstrom, G. D. Glick, and R. A. Jones, eds.), Vol. 1, pp. 8.2.1-8.2.8. John Wiley & Sons, New York, 2000. 16 j. B. Chaires, in "Advances in DNA Sequence Specific Agents" (L. H. Hurley, ed.), Vol. 2, pp. 141- 167. JAI Press, Greenwich, Connecticut, 1996. 17 j. B. Chaires, Biophys. Chem. 35, 191 (1990). 18 E Job, Ann. Chim. (Paris) 9, 113 (1928). 19 C. Y. Huang, Methods Enzymol. 87, 509 (1982). 2o A. Waiters, Biomed. Biochim. Acta 44, 132t (1985). 21 E G. Loontiens, E Regenfuss, A. Zechel, L. Dumortier, and R. M. Clegg, Biochemistry 29, 9029 (1990). [1] ANALYSIS OF LIGAND-DNA BINDING ISOTHERMS 5 1.0 -200 -400 -600 -800 I I I I I / 0.0 0.2 0.4 0.6 0.8 Mole Fraction Daunomycin 1.2 , , , , , , 200 0.8 g t 0.6 0.4 0.2 o.o • B ,I,I I I -20 -18 -16 -14 -12 -t0 In Cf FIG. I. Daunomycin binding to calf thymus DNA. (A) Job plot obtained from fluorescence titration studies. A F is the difference in fluorescence emission intensity between solutions of daunomycin alone and in the presence of DNA. The minimum indicates a binding stoichiometry of 3 or 4 base pairs. (B) Binding isotherm for the daunomycin calf thymus DNA interaction. The fractional saturation was calculated assuming a 3-bp binding site. The abscissa is the natural logarithm of the free daunomycin concentration. inflection near 0.5-0.6 mol fraction indicates an additional binding mode at higher drug concentrations. The results shown here, based on fluorescence data, agree well with data based on absorbance changes. 2° The Job plot thus answers the question "How many?" directly. In studies of ligand-DNA interactions, this method has been underutilized and its advantages largely unappreciated. In the case of multiple binding modes, the method of continuous variations is particularly valuable, and clearly reveals complexities in the binding process. Published examples for the groove-binder Hoechst 3325821 and for the bisintercalating anthracycline WP63122 illustrate the value of the method in cases of complicated, multimode binding interactions. Figure 1B shows a titration binding isotherm for the daunomycin-calf thymus DNA interaction. In this form, the fractional occupancy of binding sites is shown as a function of the natural logarithm of the free daunomycin concentration (Ct-). The fractional occupancy was calculated from the experimentally determined binding 22 F. Leng, W. Priebe, and J. B. Chaires, Biochemistry 37, 1743 (1998). 6 BIOPHYSICAL APPROACHES [ 1] ratio r (moles daunomycin bound per mole base pair) and the binding stoichio- metry was determined from the Job plot shown in Fig. 1A. The form of the plot shown in Fig. 1B is regarded by some 3 as the most fundamental representation of binding data because the logarithm of the free ligand activity is proportional to the chemical potential of the ligand. For simple binding to identical, noninteracting sites, titration binding curves should be symmetric about a midpoint located at a ligand concentration that is the reciprocal of the association binding constant, and should cover a span of 1.8 lOgl0 units (4.14 In units) in going from 0.1 to 0.9 fractional saturation. 3'4'6 The data shown in Fig. 1B cover a span of 5.4 in units (2.4 log~0 units) and represent an essentially complete binding titration curve. The span is greater than expected for simple binding, which indicates negative cooperativity, neighbor exclusion, or heterogeneity of binding sites. Perhaps the main advantage of the data shown in Fig. 1B is that they may be analyzed in a model-independent way by using the Wyman concept of median ligand activity. 3'5 The free energy of ligation (AGx) to go from a state where no ligand is bound to a degree of saturation of k? is given by Eq. (1): 2 P AGx = RT Jo In Cfg~" (1) where RT has its usual meaning. The pronounced advantage of Eq. (1) is that it provides a free energy estimate to attain any degree of saturation without recourse to any specific binding model. Numerical integration of the data in Fig. 1 B yields an estimate of AGx = -7.8 kcal mol I for the full ligation of a daunomycin binding site. Free energies derived from binding constants obtained by curve fitting to specific models must agree with this model-independent value if the model is reasonable. Neighbor Exclusion Models Figure 2 shows data for the daunomycin-calf thymus DNA interaction in the form of a Scatchard plot, J by far the most common representation of binding data for ligand-DNA interactions. To explain the curvature in such plots, a variety of neighbor exclusion models were proposed, 23'24 and these have become the most commonly used models for the interpretation of binding isotherms. Neighbor exclusion models assume (in their simplest form) that the DNA lattice consists of an array of identical and noninteracting potential binding sites. The base pair is commonly defined as the lattice binding site for duplex DNA. Ligand binding to any one site occludes neighboring sites from binding as defined by the site size n. As the lattice approaches saturation, the probability of finding a stretch 23 D. M. Crothers, Biopolymers 6, 575 (1968). 24 j. D. McGhee and R H. yon Hippel, J. Mol. Biol. 86, 469 (1974). [ 1] ANALYSIS OF LIGAND-DNA BINDING ISOTHERMS 7 8.0x10 5 , , , I , , I 6.0xl 0 s 4.0xl 0 s G~ C3 2.0x10 5 0.0 "',O • • o~',~ e~ I I I I I I I 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 r FIG. 2. Scatchard plot for the daunomycin-calf thymus DNA interaction. The solid line is the best fit of the neighbor exclusion model [Eq. (2)] to the experimental data yielding the parameters shown in Table I. The dashed line is the best fit with the exclusion parameter constrained to an integral value of 3. of unoccupied DNA n base pairs long decreases, producing the curvature seen in Fig. 2. The curvature does not result from a decrease in the intrinsic binding affinity, but rather arises from the decreased probability of finding a free site of the appropriate size. McGhee and von Hippe124 derived a closed form equation that embodies the neighbor exclusion model [Eq. (2)]: r I 1 "r ]°' = K(1 - nr) 1 ; J (2) where K is the association constant for ligand binding to an isolated lattice site, n is [...]... technique for characterizing nucleic acid- small molecule interactions Although SPR biosensors have been commercially available for more than a decade, their application to nucleic acid- small molecule systems is just developing Only a handful of SPR articles describing macromolecule-small molecule interactions have been published to date, and only a few of these focus on nucleic acid- small molecule systems.48... Nucleic Acids Res 22, 357 (1994) 38 L Dassonneville, E Hamy, P Colson, C Houssier, and C Bailly, Nucleic Acids Res 25, 4487 (1997) 39 j E Draper and T C Gluick, Methods Enzymol 259, 281 (1995) 4o D S Pilch, M A Kirolos, X Liu, G E Plum, and K J Breslauer, Biochemistry 34, 9962 (1995) 41 U Sehlstedt, P Aich, J Bergman, H Vallberg, B Norden, and A Graslund, J Mol Biol 278, 31 (1998) [21 RNA INTERACTIONS. .. McGhee-von Hippel model, positive cooperativity arises from ligand-ligand interactions while the DNA lattice remains in a single conformation For protein binding to DNA, such ligand-ligand interactions might be visualized as protein-protein contacts formed when adjacent lattice sites are occupied For small molecule ligands, although such interactions could also occur, it is less easy to ascribe a molecular... nucleic acid- small molecules have begun to appear, to our knowledge, a comprehensive guide for investigating nucleic acid- small molecule systems through SPR has not been published to date For this reason and because of the commercial availability of high-sensitivity SPR instruments that are amenable for studying these systems, we have focused this review on how to study RNA-small molecule interactions. .. binding of about 1 ng of protein and 0.8 ng of nucleic acid surface concentration per millimeter squared 53,56,57 The greater response per nanogram of nucleic acid is a result of their generally higher refractive index increment with respect to proteins Small molecules can have quite different refractive index increments (RIIs) than proteins and nucleic acids and the importance of this difference is discussed... hands, neither strategy yielded enough immobilized nucleic acid for small molecule studies It appears that the negative charge on the carboxymethyl dextran inhibits sufficient immobilization of the negative nucleic acid even at extremes of salt and pH in reasonable time periods We were, however, able to quantitatively immobilize a 5'-thiolated nucleic acid directly onto a gold surface, using the method outlined... Nair, D G Myszka, and D R Davis, Nucleic Acids Res 28, 1935 (2000) 64 C I Webster, M A Cooper, L C Packman, D H Williams, and J C Gray, Nucleic Acids Res 28, 1618 (2000~[ 65 T M Heme and M J Tarlov, J Am Chem Soc 119, 8916 (1997) 30 BIOPHYSICALAPPROACHES [2] type of immobilization proceeds We are currently working on a new method for covalently immobilizing nucleic acid onto a modified sensor chip that... it is desirable to immobilize a different nucleic acid sequence In the meantime, however, immobilization through the biotin-streptavidin affinity complex is the recommended strategy to efficiently and reproducibly immobilize nucleic acids for SPR experiments The next question that must be addressed in sensor chip surface preparation is how much nucleic acid to immobilize For kinetic experiments it is... Biochem 265, 340 (1998) 53 Biacore, "BIACoreBIAapplicationsHandbook."Biacore, Uppsala, Sweden, June 1994 [2] RNA INTERACTIONS Description of Surface Plasmon Resonance 27 Biosensors SPR biosensors employ surface plasmon resonance to qualitatively and/or quantitatively describe molecular interactions Although several companies now offer SPR biosensors, 54 currently, instruments from BIAcore (Uppsala,... require substantially more material than spectrophotometric methods, and they have difficulty measuring large binding constants Gel band shift has been the most widely used method for studying nucleic acid- ligand interactions 5,35 Providing that the RNA-small molecule complex can be separated from free RNA (i.e., there is a detectable band shift from drug binding) and that the binding kinetics are relatively . molecule binding to nu- cleic acids have been inextricably linked. A testament to that fact is the inclusion of eight papers directly concerned with drug-DNA interactions among the recently. nucleic acids stems from their potential as useful pharmaceutical agents. Indeed, some of the very best anticancer drugs are well-documented DNA binders. While interest in drug-DNA interactions. nucleic acids have taken on new life and have helped spawn several emergent biotechnology companies dedicated to exploiting the promise of making new types of pharmaceuticals targeted at nucleic acids.