Flexibility and molecular recognition in the immune system

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<ul><li><p>Flexibility and molecular recognition in theimmune systemRalph Jimenez, Georgina Salazar, Kim K. Baldridge, and Floyd E. Romesberg</p><p>Department of Chemistry, The Scripps Research Institute, 10550 North Torrey Pines Road, Mail Drop CVN22, La Jolla, CA 92037; and San DiegoSupercomputer Center and University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505</p><p>Edited by Peter G. Wolynes, University of California at San Diego, La Jolla, CA, and approved October 23, 2002 (received for review July 10, 2002)</p><p>Photon echo spectroscopy has been used to measure the responseof three antibody-binding sites to perturbation from electronicexcitation of a bound antigen, fluorescein. The three antibodiesshow motions that range in time scale from tens of femtosecondsto nanoseconds. Relative to the others, one antibody, 4-4-20,possesses a rigid binding site that likely results from a short andinflexible heavy chain complementarity-determining region 3(HCDR3) loop and a critical Tyr that acts as a molecular splint,rigidifying the antigen across its most flexible internal degree offreedom. The remaining two antibodies, 34F10 and 40G4, despitebeing generated against the same antigen, possess binding sitesthat are considerably more flexible. The more flexible combiningsites likely result from longer HCDR3 loops and a deletion in thelight chain complementarity-determining region 1 (LCDR1) thatremoves the critical Tyr residue. The binding site flexibilities mayresult in varying mechanisms of antigen recognition includinglock-and-key, induced-fit, and conformational selection.</p><p>The optimization of protein-based molecular recognition mayrequire significant conformational adjustments of the partici-pating proteins, ligands, or substrates. Several models of molecularrecognition have been proposed that are differentiated by the roleof flexibility. The lock-and-key model, where no structural op-timization of the binding partners is required, presumes that themolecules have a geometry appropriate for tight binding (1).However, there is a growing consensus that protein flexibility maybe required for optimal molecular recognition. As a result, twoalternatives to the lock-and-key mechanism explicitly considermolecular flexibility. The original model that evoked flexibility,known as induced fit, posits that after the initial formation of anunoptimized complex, the molecules structurally reorganize tooptimize binding interactions (2). A related model, conformation-al selection, hypothesizes that a small fraction of molecules existstransiently in appropriate geometries before binding (3). Althoughinduced-fit and conformational selection evoke fluctuations thatoccur before or after initial complex formation, they both aredifferentiated from the lock-and-key model by the important roleplayed by protein flexibility. Flexibility may also play an importantrole in binding specificity, because structurally distinct proteinconformations are expected to facilitate the binding of structurallydistinct molecules. The importance of flexibility in the affinity andspecificity of molecular interactions is nowhere more obvious thanin the humoral immune system, where a limited set of proteins(antibodies, Abs) must bind a virtually unlimited range of foreignmolecules (i.e., small-molecule antigens, Ags). It has been suggestedthat the immune system may accomplish this task by using a limitedset of flexible Abs that may bind a wide range of Ags (4, 5).Experiments that measure Ab and Ag flexibility would be inter-esting not only from a biophysical perspective but should alsocontribute to an understanding of molecular recognition.</p><p>There is no simple relationship between protein flexibility andthe average structure, observable by x-ray crystallography (57),or necessarily the thermal fluctuations about the average struc-ture as determined by NMR spectroscopy (810). The mostpertinent information is available from crystallographic DebyeWaller factors (11) or from NMR order parameters (10).</p><p>However, these techniques only report amplitudes, and it is nottrivial to extract the frequencies of the associated motions. Asimple and more intuitive view of flexibility would follow fromexamining how a protein responds to an applied force (1214).For example, a flexible protein will respond to a given force withlarge amplitude, low-frequency motions, whereas a more rigidprotein is expected to respond to a similar force with smalleramplitude, higher-frequency motions. The large amplitude vi-brations are the protein motions underlying the flexibility im-portant to the induced-fit and conformational selection models.Characterization of the protein response to an applied force, interms of energies, frequencies, and amplitudes, is now possiblewith a combination of biology and spectroscopy.</p><p>An appropriate chromophoric Ag may be used to elicit specificand high-affinity Abs from an organism such as a mouse. Astep-function force is applied to the protein after an excitation-induced change in Ag charge distribution and structure, whichresults in an AbAg complex that is out of equilibrium. The Abcombining site will respond to the force with protein motions thatreestablish equilibrium with the excited chromophore. The inducedprotein motions will affect the electronic transition frequency of thechromophore. The frequency distribution of these motions may bewritten as a spectral density, (), which describes the amplitude offluctuations as a function of frequency, . Thus, () provides acomplete description of the protein response to the opticallyinduced force and therefore may be used to quantitate the flexi-bility of the Ab combining site.</p><p>Over the last three decades, several time-resolved optical tech-niques for determining () have been developed. Femtosecondnonlinear spectroscopies such as three-pulse photon echo peak shift(3PEPS) spectroscopy proven to be especially useful (1517). Theexperimentally observable decay of the photon echo peak shift isknown to reflect the time scales and amplitudes of M(t), the timedomain representation of () (17). Recently, 3PEPS was used tocharacterize the dynamics of an Ab complex with the rigid chro-mophore 8-methoxypyrene-1,3,6-trisulfonate (MPTS) (15). It wassuggested that a comparison of () for multiple Ab complexes withthe same Ag would quantitate protein flexibility, and that such datawould be useful for understanding the relative contributions oflock-and-key versus induced-fit or conformational selection mech-anisms to molecular recognition.</p><p>In this study, the combining-site dynamics of three Abs thatbind fluorescein (Fl) (Fig. 1) have been characterized. Theproteins studied include Ab 4-4-20, which has been characterizedstructurally (18, 19). The combining-site reorganization energiesof the AbFl complexes are calculated from the steady-statespectra, and the 3PEPS experiment is used to determine the timescales of the motions in each complex. Protein and Ag motions,ranging in time scale from tens of femtoseconds to hundreds ofpicoseconds, were observed. The Abs are found to have com-</p><p>This paper was submitted directly (Track II) to the PNAS office.</p><p>Abbreviations: Ag, antigen; 3PEPS, three-pulse photon echo peak shift; MPTS, 8-methoxy-pyrene-1,3,6-trisulfonate; Fl, fluorescein; CDR, complementarity-determining region;HCDR3, heavy chain CDR3.</p><p>To whom correspondence should be addressed. E-mail: floyd@scripps.edu.</p><p>9297 PNAS January 7, 2003 vol. 100 no. 1 www.pnas.orgcgidoi10.1073pnas.262411399</p></li><li><p>bining sites with different flexibilities, and the molecular originsof these differences are discussed in terms of the availablestructure and sequence information. Ab initio quantum-chemistry calculations of the chromophore were used to predictthe electronic and structural effects of excitation, which was usedalong with the 4-4-20 structure, to better understand the struc-tural origins of the observed protein dynamics.</p><p>Materials and MethodsExperimental Methods. mAbs 34F10 and 40G4 were produced andpurified from hybridoma supernatants by standard methods (20).mAb 4-4-20 ascites was kindly provided by Edward Voss (Univer-sity of Illinois, Urbana-Champaign). The Abs were cloned andsequenced by standard protocols (21). The ultrafast laser sourceused in these measurements was as described (15), and onlysignificant differences are described here. A 5-kHz repetition rateTi:sapphire regenerative amplifier and optical parametric amplifierwere used. The 510-nm excitation pulses were generated by mixing</p><p>the pump beam (800 nm) with the signal beam (1,407 nm) in a typeI BBO crystal. These pulses were separated from the fundamentalswith a dichroic mirror and compressed by double-passing a pair offused silica prisms. Autocorrelations and determination of zerodelay were performed by replacing the sample cell with a 0.4-mmtype I BBO crystal and measuring the second harmonic intensity.Autocorrelation widths of 60 fs, corresponding to pulse widths of 45fs (Gaussian pulses assumed), were measured. The time-bandwidthproduct of the pulses was 0.55. Pulse energies of 210 nJ per beamwere used. Pulse energies of 20 nJ per beam had no effect on theshape of the signals. 3PEPS experiments were performed asdescribed (15).</p><p>Computational Methods. Modeling of 3PEPS data. The responsefunction formalism for calculating spectroscopic properties of amolecular system from a model of the nuclear dynamics has beendescribed extensively in the literature (16), thus only a briefsummary is given here. The system is modeled with a groundstate (S0) and a single excited electronic state (S1) coupled to aharmonic bath. In this model fluctuations are probed by follow-ing the decay of coherence created within the two-level systemby light-matter interactions.</p><p>The spectral density, (), characterizes the frequency distri-bution of vibrations coupled to the S0-to-S1 electronic transition.The spectral density is a sum of both solvent or protein fluctu-ations and chromophore vibrations. The relative weight of eachcontribution is scaled by its reorganization energy, , and itscoupling strength, 2.</p><p>i 0</p><p>d [1]</p><p>i2 </p><p>0</p><p>d2coth 2kBTi [2]Spectral dynamics of the system are contained within the line-broadening function, g(t), which may be calculated from () bythe expression</p><p>gt i0</p><p>dsint</p><p>0</p><p>dcoth 2kBT1 cost int2</p><p>2,</p><p>[3]</p><p>in which in is the inhomogeneous broadening, kB is the Bolt-zmann constant, and T is the absolute temperature. Signals forthe various time-resolved experiments such as transient absorp-tion, transient grating, or 3PEPS as well as steady-state absorp-tion spectra may be calculated from g(t) by using standardprocedures (16).Quantum-mechanical calculation of Fl vibrations. Ab initio calculationof the chromophores vibrational frequencies and excitation-induced displacements may be used to calculate Fl(). GAUSS-IAN 98 was used to calculate the ground electronic-state geometryand normal modes of vibration (HF6-31G*) as well as theexcited-state geometry (CIS6-31G*). Each ring system of thechromophore was constrained to be planar in both the groundand excited states. The interannular bond between the xantheneand phenyl rings was set to 71, as observed in the 4-4-20structure (18, 19). Displacements, j, were found by projectingthe changes in bond lengths onto the normal mode vectors (22).</p><p>Fig. 1. (Upper) Contour plot showing structural and electron-density differ-ences between S1 and S0 electronic states. The red contours indicate higherdensity in S0, whereas gold contours indicate a higher electron density in S1.The purple spheres show the atomic positions in S0, and red spheres showpositions in S1. (Lower) HF and CIS optimized energies for values of thedihedral angle defining the angle between the carboxyphenyl ring plane andthe xanthene plane (the dihedral angle is defined by atoms 8, 7, 21, and 22).</p><p>Jimenez et al. PNAS January 7, 2003 vol. 100 no. 1 93</p><p>BIO</p><p>PHYS</p><p>ICS</p></li><li><p>The reorganization energy for each vibration j, j, was deter-mined from j and the normal mode frequency, j (j 12jj</p><p>2). The calculated frequencies were scaled by 0.9. Thefrequencies and reorganization energies then were used tocalculate Fl() (Fig. 6, which is published as supporting infor-mation on the PNAS web site, www.pnas.org). Ab initio calcu-lation of Fl electrostatics were performed at the DZV(2d,p) levelof theory, and density difference analysis was performed withQMVIEW software (23).</p><p>Results3PEPS Data. 3PEPS data for Fl bound to the three Abs are shownin Fig. 2, and parameters from exponential fits are collected inTable 1. The initial peak shifts and fastest decay times are allsimilar. However, the amplitude of the fastest and slowestdynamics are different for each Ab. Each Ab had a 3- to 5-psdecay component of similar amplitude and leveled off by T 10ps to distinctly different nonzero asymptotic values. The value ofthe asymptotic peak shift was largest for Ab 4-4-20 and smallestfor Ab 34F10. The asymptotic values indicate the presence ofslow (3-ns) time-scale protein dynamics in the three Abs.</p><p>3PEPS Modeling. A model spectral density was constructed thatreproduced both the 3PEPS decay and the absorption spectrawithin the constraint of the total reorganization energy. The Agspectral density FL() was scaled to give FL 484 cm1 in eachAb, and only modes with 250 cm1 were included (suchmodes would have appeared as oscillations in the 3PEPS decaydata). The fastest dynamics in each 3PEPS decay was modeledwith a Gaussian contribution to the spectral density. The 3- to5-ps decay for each Ab was modeled with a Lorentzian compo-nent in Ab(). The asymptotic value of the peak shift for eachAb was modeled as inhomogeneous broadening (i.e., the valueof in in Eq. 3 was varied). The reorganization energies of the</p><p>Gaussian and Lorentzian components and the value of in werevaried until the best fits to the 3PEPS decay and the absorptionspectrum were achieved. The values of the parameters used toconstruct the Ab() are collected in Table 2, and comparisonsof modeled 3PEPS decays and absorption spectra with the dataare shown in Fig. 3. The spectral densities are shown in Fig. 3D.Values of in are converted to reorganization energies byassuming that they represent vibrations in the low temperaturelimit ( hin</p><p>2 2kT). The values of Ab are thus 352 cm1 for34F10, 264 cm1 for 40G4, and 224 cm1 for 4-4-20. Thesimulated absorption spectra are in excellent agreement withthose observed experimentally. The simulated 3PEPS decays arealso in good agreement with the experimental data. The largestdiscrepancies occur in the T 100 fs regime, most likely due tonon-Gaussian experimental pulses. It is difficult to assign errorsto these values, because they result from a model, not from a fitof the data. However, we note that small changes in the values,5 cm1 for and in, 25% for G, and 10% for Kubo, resulted inlarge changes in the calculated peak shift. It therefore is assumedthat the errors are somewhat less.</p><p>Some differences between the model and the data may resultfrom an Ab-...</p></li></ul>

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