Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions

Article

Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions Graphical Abstract

Authors Xu Liu, David C. Speckhard, Tyson R. Shepherd, ..., C. Andrew Fowler, Lokesh Gakhar, Ernesto J. Fuentes

Correspondence [email protected]

In Brief The role of conformational dynamics in molecular recognition remains controversial. In a model PDZ domain system, Liu et al. show that conformational dynamics plays a distinct role in protein-ligand interactions. Fast motions contribute to the entropy of binding and slow motions relate to binding specificity.

Highlights d

The QM PDZ/Caspr4 structure reveals p p and p-anion interactions

d

Remodeled binding pocket and electrostatics explain the QM PDZ/NRXN1 affinity

d

Conformational entropy from NMR dynamics correlates with binding entropy from ITC

d

Slow, microsecond to millisecond motions suggest a conformational selection model of ligand recognition

Liu et al., 2016, Structure 24, 1–14 December 6, 2016 ª 2016 Elsevier Ltd. http://dx.doi.org/10.1016/j.str.2016.08.019

Accession Numbers 4NXP 4NXQ 4NXR

Please cite this article in press as: Liu et al., Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions, Structure (2016), http:// dx.doi.org/10.1016/j.str.2016.08.019

Structure

Article Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions Xu Liu,1,6,7 David C. Speckhard,2 Tyson R. Shepherd,1,6,8 Young Joo Sun,1,6 Sarah R. Hengel,1,6 Liping Yu,1,3,6 C. Andrew Fowler,3,6 Lokesh Gakhar,1,4,6 and Ernesto J. Fuentes1,5,6,9,* 1Department

of Biochemistry, University of Iowa, Iowa City, IA 52242-1109, USA of Chemistry, Loras College, Dubuque, IA 52004-0178, USA 3Carver College of Medicine Medical Nuclear Magnetic Resonance Facility 4Protein Crystallography Facility 5Holden Comprehensive Cancer Center University of Iowa, Iowa City, IA 52242-1109, USA 6Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA 52242-1109, USA 7Present address: Department of Biochemistry, Emory University, Atlanta, GA 30322-4250, USA 8Present address: Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 9Lead Contact *Correspondence: [email protected] http://dx.doi.org/10.1016/j.str.2016.08.019 2Department

SUMMARY

Conformational dynamics has an established role in enzyme catalysis, but its contribution to ligand binding and specificity is largely unexplored. Here we used the Tiam1 PDZ domain and an engineered variant (QM PDZ) with broadened specificity to investigate the role of structure and conformational dynamics in molecular recognition. Crystal structures of the QM PDZ domain both free and bound to ligands showed structural features central to binding (enthalpy), while nuclear-magnetic-resonancebased methyl relaxation experiments and isothermal titration calorimetry revealed that conformational entropy contributes to affinity. In addition to motions relevant to thermodynamics, slower microsecond to millisecond switching was prevalent in the QM PDZ ligand-binding site consistent with a role in ligand specificity. Our data indicate that conformational dynamics plays distinct and fundamental roles in tuning the affinity (conformational entropy) and specificity (excited-state conformations) of molecular interactions. More broadly, our results have important implications for the evolution, regulation, and design of protein-ligand interactions.

INTRODUCTION Molecular recognition is critical for the function and regulation of signal transduction in cells. Over the last several decades tremendous effort has been expended to rigorously understand the structural, thermodynamic, and dynamic bases for proteinprotein interactions. Although many insights have been obtained from these studies, the role of conformational dynamics is poorly understood. In particular, the connection between conforma-

tional dynamics and binding specificity remains elusive. Seminal studies with calmodulin (Frederick et al., 2007; Marlow et al., 2010) and catabolite activator protein (CAP) (Tzeng and Kalodimos, 2012) have established a role for fast (picosecond to nanosecond) dynamics in modulating conformational entropy and thus affinity, yet the generality of this relationship has not been established. Similarly, the contribution of slower (microsecond to millisecond) motions to the binding mechanism has received attention. Most studies have focused on enzymes and relating microsecond to millisecond motions to kinetics (Henzler-Wildman and Kern, 2007; Lisi and Loria, 2016; Palmer, 2015). Recent efforts have begun to analyze the mechanisms of binding, particularly attempting to distinguish between conformational selection and induced fit models (Boehr et al., 2009; Chakrabarti et al., 2016; Clore, 2014). In spite of these studies, experimental evidence connecting slower motions, excited states, and binding specificity is lacking. Thus, a major factor motivating the study presented here is to delineate the potential role(s) of fast and slow conformational dynamics in molecular recognition. PDZ (PSD-95/Dlg/ZO-1) domains are small globular proteinprotein interaction domains consisting of
80–90 amino acids that predominantly recognize the C terminus of their binding partners. These modular domains have been excellent model systems for investigating the details of molecular specificity (Lee and Zheng, 2010). Several large-scale proteomic studies have redefined the general classification of PDZ domain ligands and have shown that specificity is optimized over the entire ligand-binding site and tuned across the proteome to minimize cross-reactivity (Chen et al., 2008; Stiffler et al., 2007; Tonikian et al., 2008). Thus, PDZ/peptide interactions feature epistasis (i.e., context dependence) and therefore specificity results from a precise combination of interactions throughout the entire binding interface (Ernst et al., 2009, 2010; Liu et al., 2013; Melero et al., 2014; Shepherd et al., 2011; Stiffler et al., 2007). Structural analyses of PDZ complexes provide ample support for this idea (Ernst et al., 2014; Lee and Zheng, 2010). In contrast to the structural characterization of PDZ domains, relatively few studies on their conformational dynamics have Structure 24, 1–14, December 6, 2016 ª 2016 Elsevier Ltd. 1

Please cite this article in press as: Liu et al., Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions, Structure (2016), http:// dx.doi.org/10.1016/j.str.2016.08.019

Figure 1. Design of the QM PDZ Domain (A) Space-filling model of the Tiam1 PDZ in complex with SDC1 peptide ligand (PDB: 4GVD). Residues that form the S0 and S-2 specificity pockets are labeled and colored in red. (B) Primary sequence alignment of the human Tiam1, QM, and mouse Tiam2 PDZ domains. Secondary structure is indicated by rectangles (a helix) and arrows (b strand). The six residues labeled in (A) are highlighted in the sequence alignment. The four mutations in the QM are colored yellow. An asterisk represents conserved residues; a colon represents conservation between residues with strongly similar properties; a period represents conservation between residues with weakly similar properties.

been published. Computational and solution nuclear magnetic resonance (NMR) spin relaxation studies indicate that PDZ domains contain energetic and dynamic ‘‘hot spots’’ that are distributed throughout the domain at the ligand-binding site and distally (Fuentes et al., 2004; Law et al., 2009; Lockless and Ranganathan, 1999; Ota and Agard, 2005). These hot spot regions coincide with protein ‘‘sectors’’ that describe functionally correlated residues in tertiary structures of proteins and map to residues critical for specificity (Fuentes et al., 2004; Halabi et al., 2009; McLaughlin et al., 2012). Collectively, these studies provide evidence for a correlation between structure, dynamics, and specificity. T cell lymphoma invasion and metastasis genes 1 (TIAM1) and 2 (TIAM2) encode for guanine nucleotide exchange factor proteins specific for the Rac1 GTPase (Chiu et al., 1999). Tiam1 and 2 are large, modular proteins containing several protein-protein interaction domains, including a single PDZ domain. The Tiam1/2 PDZ domains share
28% amino acid sequence identity and display distinct but overlapping specificity (Shepherd et al., 2011). For instance, the interaction between the Tiam1 PDZ domain and a C-terminal peptide from the adhesion receptor neurexin1 (NRXN1) is weak (Kd
2.4 mM), whereas the affinity of the Tiam2 PDZ domain for NRXN1 is
500-fold tighter (Kd
5 mM). In contrast, both the Tiam1 and Tiam2 PDZ domains bind tightly to a C-terminal peptide from Caspr4 (related to the NRXN1 receptor family) with Kd values of
18 and 3 mM, respectively (Shepherd et al., 2011). Previously, we determined the structure of the Tiam1 PDZ domain in complex with a C-terminal peptide from syndecan 1 (SDC1), which showed that ligand specificity was determined by the S0 and S-2 binding pockets, specific for the ultimate (P0) and antepenultimate (P-2) amino acids of the peptide (Figure 1A) (Liu et al., 2013; Shepherd 2 Structure 24, 1–14, December 6, 2016

et al., 2010). Further studies revealed that substitution of four non-conserved residues in the S0 and S-2 binding pockets of the Tiam1 PDZ domain with the analogous residues found in the Tiam2 PDZ domain (i.e., Tiam1 quadruple mutant or QM PDZ) was sufficient to switch the ligand-binding specificity from Tiam1 to that of the Tiam2 PDZ domain (Figure 1B) (Shepherd and Fuentes, 2011; Shepherd et al., 2011). As such, the affinity of the QM PDZ domain was
50-fold tighter for NRXN1 and
5-fold weaker for SDC1 compared with the Tiam1 PDZ domain. However, the structural and energetic mechanism(s) underlying this specificity switch and the role of conformational dynamics remain unknown. In this work, we determined the structural, thermodynamic, and dynamic origins of the engineered specificity of the QM PDZ domain. Using a panel of peptide ligands, we established that the QM PDZ domain has a broadened ligand specificity biased toward that of the Tiam2 PDZ domain. Crystal structures of the QM PDZ domain free and bound to C-terminal peptides derived from the proteins Caspr4 and NRXN1 revealed novel binding interactions, primarily through a mutated phenylalanine residue in the S0 pocket and a glutamic acid residue in the S-2 pocket. NMR-based methyl relaxation analyses coupled with isothermal titration calorimetry (ITC) provided evidence for increased dynamics that correlated with changes in conformational entropy. Finally, the QM PDZ domain had pronounced motions on the microsecond to millisecond timescale, suggesting a relationship with binding specificity. Taken together, our data provide a near complete thermodynamic and structural model for the engineered binding specificity of the QM PDZ domain. Importantly, we find that conformational dynamics contributes significantly to both the thermodynamics and specificity of binding.

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be surprisingly low (0.82 kcal/mol; Figure S1B), suggesting a large fraction (
20%) might be unfolded at 25 C. However, no evidence for unfolding was seen in the 1H-15N-HSQC spectrum, even at lower contours. Together, these data confirm that the four mutations destabilized the QM PDZ domain but did not cause gross structural changes.

Figure 2. Chemical Shift Changes in the QM PDZ Domain Overlaid 1H-15N HSQC spectra of QM (blue) and Tiam1 PDZ (red) domains. Residues with the largest changes in chemical shift are labeled and indicated by arrows. See also Figures S1 and S3.

RESULTS Structure and Stability Changes in the QM PDZ Domain To probe the effects of mutations on the structure of the QM PDZ domain in solution, we collected a 1H-15N-heteronuclear single quantum coherence (HSQC) spectrum (Figure 2). Overall, the QM PDZ domain had well-dispersed chemical shifts in the 1H and 15N dimensions, suggesting an intact global fold. We were able to assign the majority of non-proline backbone amide resonances by standard triple-resonance experiments with the exception of four residues (Y858, E880, S908, and S909), the resonances of which were broadened beyond detection. Comparison of the Tiam1 and QM PDZ domain spectra showed that the chemical shifts of most residues did not change, indicating that there was no gross structural alteration. However, several chemical shift differences between the Tiam1 and QM PDZ domains were apparent and clustered around the site of the mutations (L911M, K912E, L915F, and L920V). In particular, residues in the a2 helix (residues F914, S916, Q917, and S919) and F860 located in the b2 strand had large perturbed chemical shifts (Figure 2). In addition, several minor peaks were visible at low contour levels. Although we were not able to assign these peaks, they likely result from alternate conformations or local unfolding as they disappear upon titration with peptide ligand (data not shown). To assess the thermodynamic stability of the QM PDZ domain, we performed thermal and chemical denaturation experiments. The change in molar ellipticity at 222 nm was monitored as a function of temperature or guanidinium hydrochloride concentration. Temperature denaturation data showed that the midpoint of denaturation (Tm) for the Tiam1 PDZ was 5 C higher than the QM (Tm,WT = 47.8 C ± 0.5 C and Tm,QM = 42.7 C ± 0.6 C). Consistent with this, the chemical denaturation data showed that the QM mutant was destabilized by 1.78 ± 0.09 kcal/mol (Figure S1). The stability of the QM was found to

The QM PDZ Domain Has Broadened Ligand Specificity Similar to the Tiam2 PDZ Domain We previously determined the binding specificity of the QM PDZ domain using three representative peptide ligands (Shepherd et al., 2011). To thoroughly probe the specificity profile of the QM PDZ, we tested the binding of seven additional dansyllabeled peptides by fluorescence anisotropy (Figure 3 and Table S1). Figure 3 shows representative binding curves and the determined affinities of the QM PDZ domain for ten peptides. These data show that the QM PDZ domain bound six peptides with improved affinity (lower Kd), while four peptides had poorer affinity (higher Kd) compared with the Tiam1 PDZ domain. Further comparison indicates that the changes in affinity of the QM PDZ tended toward those of the Tiam2 PDZ domain for nine out of ten peptides (Table S1). The sole exception was CADM1, which did not bind the Tiam2 PDZ domain but showed
14fold improved affinity for QM compared with the Tiam1 PDZ domain. Finally, if one uses 200 mM as a cutoff for very weak binding, the QM PDZ domain bound eight peptides, while Tiam1 and Tiam2 PDZ each bound six peptides with only four common to both. These data indicate the QM PDZ domain has a broader specificity than either the Tiam1 or the Tiam2 PDZ domains with a clear bias toward the specificity of the Tiam2 PDZ domain. We used ITC to gain insight into the thermodynamics of the QM PDZ/Caspr4 interaction (Figure 4A). The Kd of the QM PDZ for the Caspr4 ligand was determined to be
38 mM, which is approximately 2-fold weaker than the value obtained by fluorescence anisotropy measurements (Kd = 18.3 ± 1 mM). This is consistent with the differences found previously due to the influence of the dansyl chloride moiety used in the fluorescence experiments (Liu et al., 2013). The free energy of binding (DG) for Tiam1 PDZ/Caspr4 (Liu et al., 2013) and QM PDZ/Caspr4 interactions was similar (
6 kcal/mol); however, the enthalpy and entropy differed significantly (Figure 4B). Caspr4 binding to the Tiam1 PDZ was an entropically driven process, whereas Caspr4 binding to the QM PDZ was enthalpically driven. These data indicate that the Tiam1 and QM PDZ domains use distinct thermodynamic strategies to achieve nearly identical affinity. Crystal Structures of the Free and Ligand-Bound Forms of the QM PDZ Domain To investigate the structural origin of the QM PDZ binding specificity switch, we solved the crystal structures of the PDZ domain free and in complex with two peptide ligands. The structure of the free QM PDZ domain was refined to a resolution of 2.3 A˚ (Table 1). The QM PDZ domain has a prototypical PDZ domain structure, containing five b strands and two a helices arranged in a b sandwich fold (Figure 5A). Similar to the Tiam1 PDZ structure, the electron density of the b1-b2 loop (residues 851–856) was not visible, suggesting conformational heterogeneity in this loop. The structural overlay of Ca atoms found in secondary structure (excluding the a2 helix) between the Tiam1 and QM Structure 24, 1–14, December 6, 2016 3

Please cite this article in press as: Liu et al., Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions, Structure (2016), http:// dx.doi.org/10.1016/j.str.2016.08.019

Figure 3. The QM PDZ Domain Switched Ligand Binding Specificity

Has

(A) Representative binding curves for the interaction between the QM PDZ domain and dansylated peptides derived from the syndecan family (SDC1-4), Caspr4, neurexin1 (NRXN1), and CADM1. (B) Summary of QM PDZ/peptide binding data. The sequence of each peptide and the determined dissociation constant (Kd) is indicated. Fold change represents Kd(WT)/Kd(QM). The Kd values reflect the mean and SD from at least three technical replicates. See also Figure S3 and Table S1.

PDZ domains indicated very little variation, having a root-meansquare deviation (RMSD) of 0.22 A˚. However, closer inspection revealed that the a2 helix had the largest RMSD (residues 908– 920 with an RMSD of 0.80 A˚) caused by a displacement of the helix away from the binding pocket (Figure 5A and Table S2). Taken together, the overall fold of QM PDZ domain was intact but local structural perturbations occurred near the site of the mutations in the a2 helix. To gain insight into how the QM PDZ domain was able to interact with ligands, we determined the structure of two QM PDZ/ligand complexes. We first solved the crystal structure of the QM PDZ domain bound to a C-terminal peptide from Caspr4 (Ac-ENQKEYFFCOO-). The asymmetric unit of the crystal contained three PDZ domain complexes and the structure was refined to a resolution of 2.1 A˚ (Table 1). Chain A contained the most complete electron density for the ligand (P0 to P-6 residues) and thus we chose to present its structure; however, all conclusions are supported by the three complexes in the unit cell. The QM PDZ/Caspr4 structure had an identical fold to the free QM PDZ domain (the Ca RMSD was 0.40 A˚) (Figure S2 and Table S2). The electron density for the b1-b2 loop was observable, with apparent hydrogen bonding between backbone amides of Y858-G859 (b1-b2 loop) and the C-terminal (P0) carboxylate group in the ligand, suggesting that the ligand binding stabilizes 4 Structure 24, 1–14, December 6, 2016

a single conformation in the b1-b2 loop region (Figure 5B). Additional backbone hydrogen-bonding interactions between the peptide and residues along the b2 strand of QM PDZ (residues 860–865) were observed. In particular, the side chains of mutated residues in the a2 helix facilitated recognition of the Caspr4 peptide by altering the S0 and S-2 binding pockets and introducing new interactions. Notably, the benzene ring of the Phe at the Caspr4 P0 position made a ‘‘paralleldisplaced’’ p-p interaction (McGaughey et al., 1998) with the aromatic ring introduced by the L915F mutation in the S0 binding pocket (Figure 5B). In addition to this p-p stacking, the structure suggests that an anion-p interaction (Jackson et al., 2007) occurs between the E912 side-chain oxygens and the edge of the P0 phenylalanine benzene ring located
4.0 A˚ away. Strikingly, the E912 side chain was flipped
90 from its original orientation in the absence of ligand. Similarly, the side chain of M911 (from the L911M mutation) was flipped
180 such that the sulfur atom approached the P-2 tyrosine ring allowing for a favorable S-p interaction (Valley et al., 2012) in the S-2 pocket. These observations are consistent with HSQC-based peptide titrations that showed chemical shift perturbations of residues in the a2 helix and b2 strand, particularly in F915, E912, and F860 (Figures S3A and S3C). We also determined the structure of the QM PDZ/NRXN1 (Dan-NKDKEYYVcoo-) complex to gain insight into the 50-fold increase in the binding affinity of the QM PDZ domain for the NRXN1 ligand. This structure was refined to a resolution of 1.90 A˚ and the asymmetric unit contained one copy of the QM PDZ/NRXN1 complex (Table 1). As expected, the entire NRXN1 peptide interacted with the b2 strand (residues 858– 866) in the PDZ domain through hydrogen-bonding interactions along the backbone (Figure 5C). Compared with the Tiam1 PDZ/ SDC1 structure (Liu et al., 2013), the S0 and S-2 binding pockets in the QM PDZ domain underwent unique changes upon binding NRXN1. For instance, the S0 pocket formed by the side chains of residues Y858, F860, L915, and L920 was enlarged by 20 A˚2 of accessible solvent area providing additional room for the bulkier Val side chain at P0 in the NRXN1 ligand. Moreover, the L911M

Please cite this article in press as: Liu et al., Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions, Structure (2016), http:// dx.doi.org/10.1016/j.str.2016.08.019

Figure 4. Thermodynamic Analysis of the QM PDZ/Caspr4 Domain Interaction by ITC (A) Thermogram and integrated titration curve for the Caspr4 ligand bound to the QM PDZ domain. (B) Thermodynamic parameters for the Tiam1 PDZ/Caspr4 and QM PDZ/ Caspr4 interactions at 298 K. Each parameter represents the mean and SD from three technical replicates. See also Table S5.

and K912E mutations expanded the S-2 pocket by
9 A˚2 to accommodate Tyr at P-2 in NRXN1. In addition to these changes, a favorable electrostatic interaction between lysine at P-4 in NRXN1 and E912 in the QM PDZ was evident with a distance between lysine nitrogen (NZ) and glutamate oxygen (OE1) of
5 A˚. Collectively, the QM PDZ/NRXN1 structure showed that the four mutations caused an enlargement of the S0 and S-2 hydrophobic pockets and a favorable electrostatic interaction. Moreover, solution NMR binding studies were consistent with the observations seen in the QM PDZ/NRXN1 structure (Figures S3B and S3D). Importantly, NMR binding studies showed that the QM PDZ domain had distinct responses upon binding the Caspr4 and NRXN1 peptides, reflecting the unique structural interactions observed in the crystal structures (Figure S3E). Changes in Fast Timescale Backbone Dynamics of the QM PDZ Domain NMR-based investigations allow for the study of protein motions over a wide range of timescales (i.e., dynamics) to probe conformational fluctuations that are not readily observed in crystal structures. Here, we employed 15N-based spin relaxation methods to monitor the changes in backbone amide dynamics in the picosecond to nanosecond timescale of the QM PDZ domain in solution. Longitudinal and transverse 15N-relaxation

times and {1H}-15N nuclear Overhauser effects were measured at two magnetic field strengths followed by model-free analysis to yield an order parameter (S2) and timescale of motion (te) for each backbone amide N-H bond vector. S2 can range from 0 (completely unrestricted) to 1 (completely rigid), indicating the degree of motional restriction. The S2 values for residues in the free QM PDZ ranged from 0.20 to 0.92 with an average of 0.80. A plot of S2 as a function of protein sequence revealed several regions with depressed S2 values indicating enhanced mobility (Figure 6A). These regions included the N and C termini, b1-b2 loop (residues 852–857), b2-b3 loop (residues 869–871), and b4-a2 loop (residues 905–907). Also noteworthy, residues in the b2 strand displayed chemical exchange (Rex) indicating conformational exchange in the microsecond to millisecond timescale (Figure 6B). Comparison of the order parameters of the apo QM and Tiam1 PDZ domains (DS2QM-WT = S2QM,apo  S2WT,apo) identified residues with changes in dynamics (Figure 6C). We deemed the change significant if DS2QM-WT was 2-fold greater than the propagated error. Only a few residues met this criterion and they are located in the b1-b2 loop, the b3-a1 region (residues 877 and 884), and the b4-a2 loop (residues 902, 903, and 910). Interestingly, the DS2QM-WT for many residues was found to be less than 0, signifying that QM PDZ had increased dynamic motions along the backbone in the picosecond to nanosecond regime (Figure 6C). In addition, residues in the b2 strand from 860 to 865 had significant chemical exchange (DRex, QM-WT > 0), indicative of ‘‘slow’’ motions in QM that were absent in the Tiam1 PDZ domain. Finally, analysis of the relaxation data for the free QM PDZ domain gave an overall correlation time (tm) of 7.58 ± 0.03 ns, significantly longer than that determined previously for the Tiam1 PDZ domain (tm = 6.38 ± 0.02 ns) (Liu et al., 2013), indicating that the Tiam1 PDZ domain is more compact compared with the QM PDZ domain. Next, we examined the influence of the Caspr4 peptide binding on dynamics. Analysis of the QM PDZ/Caspr4 relaxation data resulted in a tm of 6.92 ± 0.03 ns, implying the complex is more compact than the free QM PDZ domain. The plot of order parameter versus sequence upon Caspr4 binding (DS2QM, Caspr4-Apo = S2QM, Caspr4-bound  S2QM, Apo) showed residues with changes in dynamics induced by ligand binding (Figure 6D). In particular, DS2QM, Caspr4-Apo > 0 revealed QM residues whose dynamic motions were dampened upon Caspr4 binding. This is similar to the previously reported results for the wild-type (WT) PDZ upon Caspr4 binding (Liu et al., 2013). This dampening effect was also seen in the chemical exchange (DRex, QM, Caspr4-Apo < 0), indicating an overall quenching of both fast and slow timescale dynamics in the Caspr4-bound state. Again, this was similar to that observed for the WT PDZ/Caspr4 complex (Liu et al., 2013). Comparison of the backbone dynamics for the WT and QM PDZ/Caspr4 complexes indicates only small changes in both order parameters and Rex (Rex < 1 s1) (Figure S4). Thus, overall the 15N-spin relaxation data showed that the fast timescale (picosecond to nanosecond) backbone dynamics of the WT and QM PDZ domains, either free or complexed with Caspr4, were similar, having only subtle differences. The most noteworthy finding was that apo QM displayed conformational exchange on the microsecond to millisecond timescale, which Structure 24, 1–14, December 6, 2016 5

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Table 1. Crystallographic Data Collection and Refinement Statistics QM PDZ

QM PDZ/Caspr4

QM PDZ/NRXN1

Data Collection Statistics Temperature (K) Wavelength (A˚)

100

100

100

1.542

1.000

1.000

Space group

P3221

P21

P212121

Unit cell parameters a, b, c (A˚)

45.84, 45.84, 71.36

51.08, 50.82, 53.04

26.36, 50.32, 61.94

a, b, g ( )

90.00, 90.00, 120.00

90.00, 92.29, 90.00

90.00, 90.00, 90.00

Molecules per asymmetric unit Resolution range (A˚)

1

3

1

19.85–2.30 (2.38–2.30)a

37.52–2.10 (2.21–2.10)

39.06–1.90 (1.94–1.90)

I/s(I)

7.7 (2.1)

13.9 (3.9)

39.7 (11.0)

Completeness (%)

93.9 (97.3)

99.4 (100.0)

98.7 (87.1)

Rmerge (%)b

10.4 (42.1)

8.1 (38.3)

3.5 (14.1)

Redundancy

3.18 (3.17)

3.7 (3.8)

6.7 (4.4)

Refinement Details Resolution (A˚)

2.30

2.10

1.90

Rwork/Rfree (%)c

21.69/25.78

18.51/23.56

15.24/18.73

Protein (peptide)

666 (0)

2092 (187)

714 (92)

Water

47

160

99

No. of atoms

B factor average (A˚2) Protein (main chain)

31.0 (30.2)

27.0 (25.7)

11.86 (10.49)

Peptide

0

36.8

13.77

Water

36.2

29.7

20.22

RMSD from Ideal Geometry (Overall) Bond lengths (A˚)

0.0057

0.0082

0.0118

Bond angles ( )

1.0991

1.1662

1.3759

Dihedral angles ( )

16.205

12.501

14.061

Planarity ( )

0.0035

0.0060

0.0053

Chirality ( )

0.0661

0.0520

0.0449

Most favored

97.56

99.30

98.98

Additionally allowed

2.44

0.70

1.02

Disallowed

0

0

0

Ramachandran Plot (% Residues)

RMSD, root-mean-square deviation. Values in parentheses are for the highest-resolution shell. One crystal was used for each data collection. b Rmerge = SjIi  hIij/SIi, where Ii is the intensity of the ith observation, and hIi is the mean intensity of the reflections. c R = SjFobs  Fcalcj/SjFobsj, crystallographic R factor, where all reflections belong to a test set of randomly selected data. a

was not present in either the apo WT or WT/Caspr4 and QM/ Caspr4 complexes. Global Changes in Fast Timescale Side-Chain Dynamics of the QM PDZ Domain Deuterium-based relaxation experiments provide access to fast timescale motions of methyl-bearing side chains. Many studies have shown that side-chain dynamics are more heterogeneous, potentially revealing distinct information not available through the analysis of backbone motions (Wand, 2013). Comparison of the picosecond to nanosecond dynamic changes of methylbearing side chains between the Tiam1 and QM PDZ domains showed a global reduction in S2axis with average values of S2axis of 0.45 and 0.51 for the for the QM and Tiam1 PDZ do6 Structure 24, 1–14, December 6, 2016

mains, respectively (Liu et al., 2013). Closer inspection revealed a near uniform reduction in order parameter (DS2 axis, QM-WT < 0) for the QM PDZ domain and several residues with modulation of te (Figures 7A and 7B). Changes in dynamics parameters were deemed significant if they were 2-fold greater than the propagated errors. Residues with changes in S2 were mapped onto the structure of the QM PDZ domain (Figure 7C and Table S3). The affected residues were distributed throughout the PDZ domain, both near the site of mutations (b2-a2 region, where the ligand binds) and distally (b3-a1 region and b1-b2 loop). The most pronounced changes in dynamics occurred at A854b and T857g2 in the b1-b2 loop (or carboxylate-binding loop), T881g2 in the b3-a1 region, and L873d2 in the ligand-binding groove.

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Figure 5. Structures of the QM PDZ Domain Free and Bound to Caspr4 and NRXN1 Peptides (A) Ribbon representation of the QM PDZ (pink) and Tiam1 PDZ (PDB: 3KZD) (gray) domains. Side chains of the four residues mutated in this study are labeled in red and shown as sticks. The dashed line represents residues without interpretable electron density in both structures. (B) Structural model of the QM PDZ/Caspr4 complex showing backbone and side-chain interactions. PDZ domain residues involved in peptide binding are colored yellow and labeled, while the Caspr4 peptide is colored cyan. The zoomedin view on the right shows several unique interactions denoted by dotted lines. The conformation of the four mutated residues in the apo QM (pink) and Caspr4-bound (yellow) structures are shown for comparison. (C) Structural model of the QM PDZ/NRXN1 complex showing backbone and side-chain interactions. PDZ domain residues involved in peptide binding are colored yellow and labeled, while the NRXN1 peptide is colored green. The zoomedin view on the right shows several interactions and the conformation of the four mutated residues in the apo QM (pink) and NRXN1-bound (yellow) structures. See also Figure S2 and Table S2.

the response of the methyl groups to Caspr4 binding in the Tiam1 and QM PDZ domains was very similar. Analysis of a two-way contingency table comparing the number of methyl groups having significant or no change in DS2axis indicated that the two PDZ domains had a similar pattern (Table S4). Taken together, the methyl side-chain dynamics data indicates that the QM PDZ domain is more dynamic than the Tiam1 PDZ domain, but upon binding the peptide ligand the dynamics of the two complexes are indistinguishable.

Changes in side-chain dynamics due to Caspr4 binding were also probed. The average S2axis value for methyl groups in the QM PDZ/Caspr4 complex was very similar to the Tiam1 PDZ/ Caspr4 complex (0.53 compared with 0.55, respectively) (Table S3) (Liu et al., 2013). Comparison of the changes in order parameter (DS2 axis, QM/Caspr4-free QM) and te showed that motions were quenched upon Caspr4 binding: i.e., Caspr4 binding had a global effect on the PDZ dynamics (Figures 7D–7F). In addition,

Slow Conformational Switching in the QM PDZ Domain Analysis of the QM PDZ 15N-spin relaxation data indicated that several residues exhibited conformational exchange (Rex), suggesting slower microsecond to millisecond motions (Figure 6B). We sought to rigorously quantify these motions using 15 N-Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiments (Loria et al., 1999; Mulder et al., 2001). No significant Rex (Rex > 2 s1) was found in the Tiam1 PDZ domain, free (Figure 8A) or when complexed with Caspr4 (Figure S5A). In contrast, 26 residues had Rex in the free QM PDZ domain (Figure 8B and Table 2 and Figure S6) that was quenched upon binding Caspr4 (Figure S5B). The free QM PDZ relaxation curves were fit to the general Carver-Richards expression (Carver and Richards, 1972) resulting in a global Structure 24, 1–14, December 6, 2016 7

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Figure 6. Fast, Picosecond to Nanosecond, Timescale Backbone Dynamics of the QM PDZ Domain (A and B) The order parameter (S2), timescale of motion (te, C), and chemical exchange (Rex, D) of the free QM PDZ domain is plotted against backbone amide residue. The secondary structure is shown on the top of the graph. Regions with enhanced dynamics are shaded in gray. (C and D) The changes of order parameter (DS2, B) and chemical exchange (DRex, D) in the Tiam1 PDZ (WT) domain caused by the four mutations (C) and those in the QM PDZ domain caused by Casrpr4 binding (D). Error bars for each parameter represent the propagated uncertainty determined from Monte Carlo simulations. Symbols for residues that experience significant changes in a particular parameter (>2-fold the propagated error) are colored black in (C) and (D). An asterisk indicates that the data for either the free or bound state was analyzed using a dynamic model that did not include a Rex term. See also Figures S4 and S5.

exchange rate (kex = k1 + k-1), residue-specific chemical shift change (Du), and the populations of major and minor states (pA and pB, respectively). The data fitting yielded kex = 1,082 ± 29 s1 and pA = 0.974 ± 0.002 (Table 2). Residues with Rex were mapped onto the structure of the QM PDZ (Figure 8C). Rex was distributed mostly around the ligand-binding pocket in the a2 helix (e.g., residues 911, 912, 915, 916, and 919) that contained three of the mutated residues (i.e., L911M, K912E, and L915F) and the b2 strand (residues 860–865) as initially suggested by the backbone relaxation data. Residues containing Rex were also found in loop regions, including residues 854 and 857 in the b1-b2 loop, residue 878 in the b3-a1 loop, residue 889 in the a1-b4 loop, and residues 904, 906, and 907 in the b4-a2 loop. DISCUSSION Remodeled Binding Pockets and Novel Interactions Contribute to QM PDZ Specificity Comparison of the QM PDZ domain structures complexed with the NRXN1- and Caspr4-bound peptides showed that the four 8 Structure 24, 1–14, December 6, 2016

mutations in QM combined to remodel the S0 and S-2 pockets to support novel interactions that contribute to specificity. The QM PDZ/NRXN1 structure (Figure 5C) showed an expansion of the S0 pocket, consistent with biochemical data indicating a preference for amino acids with larger side chains at the P0 position of the peptide (Figure 3). Similarly, the QM PDZ/Caspr4 structure showed that substitutions in the S0 pocket supported new interactions not previously available. In particular, the L915F substitution was involved in p-p stacking and an anion-p interaction (Figure 5B). The QM PDZ structures also revealed new interactions mediated by the substitutions in the S-2 pocket. In the QM PDZ/ NRXN1 complex, an electrostatic interaction was identified between E912 and Lys at P-4 (Figure 5C). Consistent with the structure, previous binding data showed that this interaction is an important determinant for QM PDZ/NRXN1 interactions as the L911M/K912E variant in the S-2 pocket accounted for
1.3 kcal/mol of favorable binding energy (Shepherd et al., 2011). This charge-pair interaction also played a critical role in determining the specificity of the QM PDZ for other peptides

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Figure 7. Fast, Picosecond to Nanosecond, Timescale Methyl-bearing Side-Chain Dynamics in the QM PDZ Domain (A–C) The change in S2axis and te in the QM PDZ domain compared with the Tiam1 PDZ domain (WT). (D–F) The change in S2axis and te in the QM PDZ domain upon binding Caspr4. Black colored bars indicate residues that experience significant (>2-fold the propagated error) changes in this parameter. The error bars represent propagated uncertainty as derived from Monte Carlo simulations. Methyl groups exhibiting changes in dynamics are mapped onto structural models (C) and (F) of the free and Caspr4-bound QM PDZ domains, respectively. The methyl groups (spheres) are colored in a continuous gradient from red to blue, with their intensity scaling to the magnitude of DS2axis. The Caspr4 peptide is shown in cyan. Methyl groups that had a significant Dte but no DS2axis are shown as spheres and colored yellow. Residues Y858, F860, M911, E912, F915, and V920 are shown as sticks and colored yellow. See also Tables S3–S5.

(Figure 3) as was seen previously for the Tiam1 PDZ domain toward SDC peptides (Liu et al., 2013). Here, the QM PDZ preference for SDC peptides was reversed such that the SDC2 isoform bound tighter (with the K at P-4) than the SDC1 and SDC3 (with the E at P-4) peptides. These data clearly show that electrostatics play a key role in defining PDZ binding and that manipulation of residues in the S-2 pocket can modulate specificity. The QM PDZ/Caspr4 structure provided insight into how substitutions in the S0 and S-2 pockets can synergize to fine-tune specificity. In particular, the structure revealed an anion-p interaction between the E912 side chain and Phe at P0 in the S0

pocket and a sulfur-p interaction mediated by the M911 side chain in the S-2 pocket. Importantly, this network of interactions connected the peptide ligand to both the S0 and S-2 pockets, suggesting an important role for the anion-p interaction in Caspr4 binding. Indeed, anion-p interactions can stabilize binding interactions by
2 kcal/mol (Philip et al., 2011). Our binding data support the importance of this interaction, as the Caspr4 P0 F/A mutant, which disrupts anion-p and p-p stacking interactions, weakened the binding affinity by
9-fold (
0.6 kcal/mol) relative to Caspr4 (Figure 3). The QM PDZ/Caspr4 structure also indicated that a sulfur-p interaction occurred between the Structure 24, 1–14, December 6, 2016 9

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Figure 8. Slow, Microsecond to Millisecond, Timescale Motions in the QM PDZ Domain (A and B) Representative CPMG relaxation dispersion curves are shown for the Tiam1 and QM PDZ domains, respectively. Individual curves for each residue with Rex are shown in Figure S6, while their fitted parameters are indicated in Table 2. Data collected at 800 MHz (closed circle) and 500 MHz (open circle) are shown. Error bars were determined by the analysis of peak intensities from duplicate experiments. (C) Residues with Rex in the QM PDZ domain are labeled and colored in red. The six residues shown in Figure 1 have their side chains displayed. Those colored yellow did not have Rex. See also Figures S4 and S5.

methionine sulfur atom of M911 and the phenyl ring of Tyr at P-2 (Figure 5B). Methionine-aromatic pairs are prevalent in one-third of all known structures and are often found to stabilize proteinligand interactions (Valley et al., 2012). However, in the context of the QM PDZ/Caspr4 complex it appears that this interaction is of only modest importance, as the L911M mutant provided only
0.2 kcal/mol of stability to the Caspr4 interaction (Shepherd et al., 2011). The interactions described above provide a structural role for how the four substitutions in the QM PDZ domain cooperate to bind the Caspr4 peptide ligand. Our previous binding data are consistent with the structural data but indicate that the energetics of individual interactions alone is not sufficient to explain overall binding (Shepherd et al., 2011). For instance, the p-p stacking interactions mediated by F915 (in both the L915F and L915F/L920V substitutions) destabilize binding to Caspr4 by
0.7 kcal/mol, while the K912E and the L911M/K912E substitutions were also destabilizing to Caspr4 binding by
0.7 and
0.2 kcal/mol, respectively. Yet, together the four mutations (QM) marginally stabilized binding (0.02 kcal/mol) relative to the Tiam1 PDZ domain. Thus, Caspr4 binding to the QM PDZ domain results from structural cooperativity between the four mutations, a result that a priori would be very difficult to predict. Collectively, these results reinforce the role of epistasis in PDZ domain interactions and highlight the difficulty in predicting (and designing) protein-protein interactions. Additional insight into the energetics of Caspr4 binding to the QM PDZ domain comes from ITC data (Figure 4). Consistent with the biochemical binding data and the structure, the ITC experiments indicated that the binding of QM PDZ to Caspr4 was an 10 Structure 24, 1–14, December 6, 2016

enthalpically driven process, while binding to Tiam1 PDZ was entropically driven. This classic enthalpy-entropy compensation is consistent with the new interactions revealed in the QM PDZ/ Caspr4 structure but also indicates that entropy can play an important role in tuning affinity. Changes in Fast Methyl Side-Chain Dynamics Correlate with Changes in Conformational Entropy of Caspr4 Binding Although the structures of QM PDZ/NRXN1 and QM PDZ/ Caspr4 help rationalize the switched specificity found in the QM, NMR-based studies suggested that fast timescale (picosecond to nanosecond) dynamics also play a role. In particular, we found enhanced fast timescale motions in the backbone and methyl groups throughout the QM PDZ domain (Figures 6 and 7). Furthermore, the methyl side-chain motions in both the apo Tiam1 and QM PDZ domains were dampened by Caspr4 binding (Figure 7) and essentially indistinguishable (Table S3). Thus, despite the differences in the Tiam1 and QM PDZ apo state dynamics there was a high degree of similarity in the dynamics once bound to Caspr4. Together, these results suggest that the increase in dynamics in the apo QM state might modulate conformational entropy, and thus the energetics of binding (Li et al., 1996; Yang and Kay, 1996). Indeed, multiple studies have shown a remarkable correlation between the entropy of binding obtained from ITC experiments and the conformational entropy derived from methyl side-chain order parameters (Kasinath et al., 2013; Marlow et al., 2010; Tzeng and Kalodimos, 2012). Thus, the pronounced changes in fast timescale dynamic motions found in the Tiam1 and QM PDZ domains may reflect

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Table 2. Fitted Parameters of 15N-CPMG Relaxation Dispersion Curves for the QM PDZ Domain Residue

Du (ppm)

R02B ðS1 Þ (500 MHz)

R02B ðS1 Þ (800 MHz)

843

0.841 ± 0.037

11.76 ± 0.07

14.05 ± 0.07

848

0.969 ± 0.045

12.76 ± 0.10

15.29 ± 0.10

851

1.624 ± 0.092

14.04 ± 0.15

18.92 ± 0.22

854

0.685 ± 0.045

12.76 ± 0.11

14.89 ± 0.10

857

1.367 ± 0.078

11.95 ± 0.16

15.05 ± 0.21

860

1.888 ± 0.194

20.08 ± 0.56

29.39 ± 0.86

861

2.110 ± 0.166

17.04 ± 0.32

25.79 ± 0.53

863

1.788 ± 0.105

13.63 ± 0.16

17.20 ± 0.21

865

1.559 ± 0.080

13.50 ± 0.12

16.78 ± 0.15

872

1.236 ± 0.059

12.89 ± 0.10

15.50 ± 0.11

875

1.026 ± 0.048

14.12 ± 0.12

16.27 ± 0.12

876

1.305 ± 0.069

13.82 ± 0.16

17.46 ± 0.19

878

2.899 ± 0.213

15.47 ± 0.28

24.91 ± 0.37

879

1.473 ± 0.073

13.60 ± 0.14

16.65 ± 0.18

883

1.517 ± 0.076

14.98 ± 0.13

20.32 ± 0.17

889

0.793 ± 0.037

13.02 ± 0.07

15.19 ± 0.07

898

0.692 ± 0.032

12.34 ± 0.07

14.63 ± 0.07

904

0.710 ± 0.028

11.20 ± 0.04

13.79 ± 0.05

906

0.709 ± 0.028

10.47 ± 0.05

12.48 ± 0.04

907

1.107 ± 0.043

10.63 ± 0.08

13.46 ± 0.09

911

0.841 ± 0.034

11.78 ± 0.06

14.25 ± 0.06

912

0.970 ± 0.044

11.65 ± 0.08

14.21 ± 0.11

915

1.657 ± 0.079

13.17 ± 0.13

18.46 ± 0.18

916

0.962 ± 0.043

11.73 ± 0.07

14.08 ± 0.07

919

0.865 ± 0.034

11.61 ± 0.05

14.31 ± 0.06

924

1.143 ± 0.052

13.45 ± 0.11

15.01 ± 0.11

Results from global fitting of data with kex = 1,082 ± 29 s1 and pA = 0.974 ± 0.002. The error for each parameter was estimated from Monte Carlo simulations.

different entropic contributions to the Caspr4 binding processes as seen in the ITC data (Figure 4). To test this hypothesis, we sought to estimate the change in entropy between the Tiam1- and QM-bound Caspr4 complexes seen in the ITC data (Figure 4B). In principle, the entropy change could arise from a number of factors, including differences in solvent or conformational entropy. If the entropy from solvent release upon ligand binding is assumed to be similar in both PDZ/Caspr4 complexes, which is reasonable given that both the ligand and protein are nearly identical, then the change in entropy may be due to conformational entropy. Estimates of the entropy of solvation (DSsol) calculated based on the surface area buried by the peptide (Hilser et al., 2006) using the QM PDZ/ Caspr4 crystal structure and a homology model of the Tiam1 PDZ/Caspr4 complex were very similar, reinforcing this assumption (Table S5). Conformational entropy was estimated using the approach used by Wand and colleagues that empirically relates DS2axis to conformational entropy (DSconf) (Kasinath et al., 2013). Using this approach, TDSconf,WT and TDSconf,QM were determined to be +3.34 and +7.26 kcal/mol, respectively (Tables S3 and S5). Remarkably, calculation of the change in

TDStot,WT-QM from estimates of solvent and conformational entropy yielded a value of 4.54 kcal/mol, which is within 10% of value obtained by ITC (4.13 kcal/mol) (Figure 4B and Table S5). Furthermore, the contribution from solvent was small, indicating that the change in binding entropy between the Tiam1 and QM PDZ Caspr4 complexes can be attributed almost entirely to a change in conformational entropy. Importantly, this result originates from the enhanced picosecond to nanosecond motions in the apo QM, as the Tiam1 and QM Caspr4 complexes have virtually identical dynamics. These results, along with published data on calmodulin (Frederick et al., 2007; Marlow et al., 2010) and CAP (Tzeng and Kalodimos, 2012), provide compelling evidence in support of a general role for fast timescale dynamics in tuning the entropic contribution of ligand affinity. Moreover, we note that the origin of this effect is in side-chain dynamics rather than the backbone as seen in several other studies (Marlow et al., 2010; Tzeng and Kalodimos, 2009). Together, our data suggest that fast timescale dynamics play a role in dictating affinity as the QM PDZ displayed enhanced picosecond to nanosecond dynamics that correlated with changes in binding thermodynamics. Slow Conformational Switching Correlates with Specificity Changes in the QM PDZ Domain The four mutations introduced into the QM PDZ domain induced slow (microsecond to millisecond) timescale motions along the backbone. The 26 residues with microsecond to millisecond motions (Rex) mapped primarily to the a2 helix and b1-b2 and b2-b3 loops (i.e., the ligand-binding groove) with the only exception being T843, L889, and V924 located in b1, a2/b4 loop, and b5, respectively (Figure 8C). Interestingly, these three residues connect to the binding site via sequential van der Waals interactions to residue F860 in the binding site. These results are similar to the slow timescale dynamics found in the ligand-free AF-6 and Par6 PDZ domains. In the AF-6 PDZ domain, there were fewer (
16) residues with conformational exchange and these sites were limited to the b2 and a2 regions of the binding groove suggesting a role in specificity (Niu et al., 2007). In contrast, both the Par6 PDZ and the CRIB-PDZ bidomain showed extensive slow conformational exchange (32 and 47 residues, respectively). Moreover, this conformational exchange was linked to the local unfolding of the b1-b2 and b2-b3 loops to promote access of the so-called L/K switch to its high-affinity state for binding to target peptides (Whitney et al., 2011, 2013). These authors went on to argue that this local unfolding event is a key aspect of Cdc42 GTPase regulation (through CRIB binding) of PDZ binding affinity. The QM PDZ domain shares similar features found in both AF-6 and the Par6, in particular, conformational exchange in the ligand-binding site near the b2-b3 loop and a2 helix. Similar to Par6, we propose that the four mutations in the QM PDZ domain induce a transient, local unfolding event at the ligandbinding site that occurs on the microsecond to millisecond timescale. In turn, this conformational flexibility provides the plasticity to assume multiple conformations leading to broadened ligand specificity. In principle, this notion is consistent with the conformational selection; however, the induced fit model cannot be ruled out without additional kinetics experiments (Chakrabarti et al., 2016; Gianni et al., 2014; Hammes et al., 2009; Vogt et al., 2014; Weikl and Paul, 2014). More Structure 24, 1–14, December 6, 2016 11

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broadly, our data support a functional role for microsecond to millisecond conformational dynamics in modulating specificity. It is now appreciated that both increased flexibility and lowered stability can contribute to the evolution of protein function (Bloom et al., 2006; Tokuriki and Tawfik, 2009). Here, we show that the QM PDZ domain variant has the hallmark of a protein with ‘‘evolved’’ function (i.e., novel specificity): the QM has increased flexibility on both fast and slow timescales and lowered stability coincident with a broadened specificity toward peptide ligands. These data provide insight into the potential mechanism by which these two features couple to support protein evolution. In particular, lowered stability (whether global or local) supports access to a wide range of conformational substates that facilitate populating conformations relevant for novel specificity (Gonzalez et al., 2016). Thus, the QM variant might be regarded as a key intermediate in the evolutionary trajectory between the Tiam1 and Tiam2 PDZ domains. This notion is supported by our previous analysis of sequence conservation of the Tiam-family PDZ domains that showed the identity of the four residues in the QM segregate into four distinct Tiam subfamilies with Tiam1 and Tiam2 at the extremes (Shepherd et al., 2011). The onset of large-scale evolutionary datasets (Aakre et al., 2015; Raman et al., 2016) should provide new and interesting opportunities to probe the role of conformational dynamics in molecular evolution. Conclusions Conformational dynamics has been established in enzyme function but its role in molecular recognition is controversial. We present a study describing the structural and dynamic origin for the engineered specificity of the Tiam1 PDZ domain harboring four mutations in the ligand-binding pocket. The crystal structures of the QM PDZ alone and in complex with ligands provided insight into the enthalpic component of the interaction, revealing that specificity was obtained, in part, through expansion of the S0 and S-2 binding pockets and the acquisition of several new interactions (e.g., p-p, anion-p, and salt bridges). Importantly, NMR relaxation experiments indicated that conformational dynamics also plays a fundamental role in molecular recognition. Fast (picosecond to nanosecond) timescale dynamics contributed to the thermodynamics (conformational entropy) of the interaction, while slower (microsecond to millisecond) dynamics were critical for specificity (excited-state conformations). Together, our results provide an unprecedented view of how structure and conformational dynamics combine to govern the thermodynamics and specificity of molecular recognition. Finally, on a practical level, our data have implications for protein design where conformational dynamics should be an important factor to consider when designing novel protein-protein interactions or identifying cryptic sites to be targeted by small-molecule modulators. EXPERIMENTAL PROCEDURES Protein Expression and Purification The Tiam1 and QM PDZ proteins were expressed and purified as described previously (Shepherd et al., 2011). 15N and 15N, 13C uniform isotopic labeling of the proteins was achieved by growing cells in M9 minimal medium that contained 15NH4Cl (99%) and D-glucose (U-13C-99%). Minimal medium containing 15NH4Cl (99%), D-glucose (U-13C-99%), and 60% 2H2O was used to produce random, fractionally labeled 2H-methyl proteins.

12 Structure 24, 1–14, December 6, 2016

In Vitro Binding Measurements Fluorescence anisotropy binding experiments were performed as reported previously (Shepherd and Fuentes, 2011). Additional details of these procedures can be found in the Supplemental Experimental Procedures. ITC Isothermal titration experiments were performed as reported previously (Liu et al., 2013). Additional details of these procedures can be found in the Supplemental Experimental Procedures. Crystallization and Data Collection The details of crystallization and data collection of the apo QM PDZ domain and complexes bound to NRXN1 and Caspr4 peptides are provided in the Supplemental Experimental Procedures. Structure Determination and Refinement Detailed procedures for crystal structure determination and refinement are provided in the Supplemental Experimental Procedures. NMR Spectroscopy NMR experiments were carried out at 298 K (calibrated with methanol) on Bruker Avance II 500 MHz (RT probe), 800 MHz (CryoProbe) and Varian Inova 600 MHz (RT probe) spectrometers equipped with 1H/15N/13C probes and z axis pulsed-field gradients. Chemical shifts for non-proline backbone residues, side-chain methyl groups, and prochiral methyl groups were assigned by 3D triple-resonance experiments as described previously (Liu et al., 2013). NMR titration experiments were performed in phosphate buffer (20 mM NaPO4, 50 mM NaCl [pH 6.8]) containing 0.5 mM 15N-labeled QM PDZ. A series of 2D 1H-15N-HSQC spectra were recorded with an increasing amount of concentrated Caspr4 or NRXN1 ligand added in eight steps until the final molar ratio of QM PDZ to ligand was 1:5. All NMR data were processed using NMRPipe (Delaglio et al., 1995) and analyzed using NMRView (Johnson and Blevins, 1994). The QM PDZ/Caspr4 samples for fast timescale dynamics experiments were prepared by adding small amounts of concentrated peptide to 1 mM PDZ domain until saturation (the final molar ratio of PDZ to ligand was 1:5). The complex was lyophilized and resuspended in 90% H2O/10% D2O prior to NMR analysis. Backbone 15N T1, T2, and {1H}-15N nuclear Overhauser effect data and side-chain 2H T1 and T1r data at 500 and 600 MHz for free and Caspr4-bound PDZ QM, respectively, were collected using standard (15N) and 2H-methyl relaxation experiments as described previously (Liu et al., 2013). For each experiment, nine relaxation time points and three duplicates were collected. Relaxation rate constants (R1 or R2) were best fit to a single exponential function using in-house programs. 15 N relaxation dispersion experiments were performed at 500 and 800 MHz using a relaxation-compensated CPMG experiment (Loria et al., 1999; Mulder et al., 2001). The total relaxation time was 60 ms in the CPMG train and the effective field strength was modulated by altering the delay between CPMG pulses. A total of 12 experiments and two duplicates were collected in an interleaved manner at each magnetic field with a delay time ranging from 0.68 to 15 ms. A reference experiment without relaxation delay was collected to calculate the R2,eff values. Relaxation Analysis The Lipari-Szabo model-free approach was used to characterize the backbone dynamics in the picosecond to nanosecond timescale (Lipari and Szabo, 1982a, 1982b). Global correlation times (tm) were determined to be 7.58 ± 0.03 and 6.92 ± 0.03 ns for the free QM PDZ and the Caspr4-bound complexes. Backbone dynamic parameters were fit to the five standard models using FAST-Modelfree (Cole and Loria, 2003), assuming a 1H-15N bond distance of 1.02 A˚ and a 15N chemical shift anisotropy of 170 ppm. Akaike’s information criterion (Chen et al., 2004) was used for model selection and gave similar results as FAST-Modelfree. In all, 81/88 and 82/88 non-proline amides were analyzed for the free and Caspr4-bound QM PDZ, respectively. The program relxn2.2 (Lee et al., 1999) was used for the analysis of the motions of side-chain methyl groups. Errors in the fitted parameters were estimated using Monte Carlo simulations. Of 56 methyl groups, 54 and 48 were analyzed, respectively, for the free QM PDZ and the Caspr4-bound complex to obtain S2axis and te.

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Peak intensities for relaxation dispersion experiments were obtained using the program SPARKY (Goddard and Kneller, 2007). Residues with resonance overlap or weak intensities were not analyzed. In all, 73/88 and 72/88 non-proline amides were analyzed for the Tiam1 and QM PDZ domains, respectively. R2,eff values at each field (500 and 800 MHz) were calculated by Equation 1 (Mulder et al., 2001),
 1 Icpmg ln R2;eff = (Equation 1) T I0 where T is the total relaxation time, Icpmg and I0 are peak intensities from spectra at each relaxation delay and reference, respectively. Only residues with a change in R2,eff value greater than 2 Hz over the series of effective field strengths were further analyzed. The intensities were best fit to both a simple two-state model and a model with no exchange. An F test (acritical = 0.01) was used to identify residues with statistically significant chemical exchange. Finally, exchange parameters were determined by fitting the data to the Carver-Richards expression (Equation 2) (Carver and Richards, 1972),
  1 1 R02A + R02B + kex  R2;eff ð1 t cp Þ = cosh1 ½D + coshðh + Þ  D cosðh Þ  2 t cp   1 J + 2Du2 D± = ± 1 +   1=2 2 J2 + z2 
 1=2 1=2  t cp ± J + J2 + z2 h ± = pffiffiffi 2 2  2 J = R02A  R02B  pA kex + pB kex  Du2 + 4pA pB kex   0 z = 2Du R2A  R02B  pA kex + pB kex (Equation 2) where pA and pB are the populations of the major and minor states, Du and kex are the difference in chemical shift and the rate of exchange between the two states, respectively (Carver and Richards, 1972; Palmer et al., 2001). Fits were performed using the program exrate2.0 (Mauldin et al., 2009). Errors in the fitted parameters were determined by Monte Carlo simulations. Comparison of the chi-squared values of individual residue (local) and all residue (global) fits indicated that a global exchange process best fit the data. The fitted global (kex and pA) and individual (Du and R02B ) parameters are reported in Table 2. ACCESSION NUMBERS The atomic coordinates and structure factor amplitudes for the free QM PDZ, QM PDZ/Caspr4, and QM PDZ/NRXN1 structures have been deposited in the PDB under accession codes PDB: 4NXP, 4NXQ, and 4NXR, respectively. SUPPLEMENTAL INFORMATION Supplemental Information includes Supplemental Results, Supplemental Experimental Procedures, six figures, and five tables and can be found with this article online at http://dx.doi.org/10.1016/j.str.2016.08.019. AUTHOR CONTRIBUTIONS Conceptualization, E.J.F. and X.L.; Methodology, E.J.F. and X.L.; Investigation, X.L., D.C.S., T.R.S., Y.J.S., S.R.H., L.Y., C.A.F., L.G., and E.J.F.; Writing – Original Draft, X.L. and E.J.F.; Writing – Review & Editing, E.J.F. and X.L.; Funding Acquisition, E.J.F. and X.L.; Supervision, E.J.F. ACKNOWLEDGMENTS The authors thank members of the Fuentes Lab, Dr. Miles Pufall and Dr. Maria Spies for helpful discussions and comments on the manuscript. We thank Dr. Andrew Lee and Dr. Paul Sapienza for access to and support in using NMR relaxation software. We are grateful to Dr. Jay Nix and the staff at beamline 4.2.2 at the Advanced Light Source, Lawrence Berkeley National Laboratory. The X-ray crystallography software used in the project was installed and configured by SBGrid. The Roy J. Carver Charitable Trust is acknowledged for funding of the Carver College of Medicine Medical Nuclear Magnetic Reso-

nance Facility. X.L. was supported by an American Heart Association Predoctoral Fellowship (E155500). E.J.F. was supported in part by the American Heart Association (0835261N and 15GRNT25740021). D.C.S. was supported by a supplement to NSF CAREER Award (MCB-0953080) (to E.J.F.). T.R.S. was supported in part by a NIH graduate training grant in Pharmacology (GM067795) and Biotechnology (GM008365). Received: January 27, 2016 Revised: July 27, 2016 Accepted: September 30, 2016 Published: October 27, 2016 REFERENCES Aakre, C.D., Herrou, J., Phung, T.N., Perchuk, B.S., Crosson, S., and Laub, M.T. (2015). Evolving new protein-protein interaction specificity through promiscuous intermediates. Cell 163, 594–606. Bloom, J.D., Labthavikul, S.T., Otey, C.R., and Arnold, F.H. (2006). Protein stability promotes evolvability. Proc. Natl. Acad. Sci. USA 103, 5869–5874. Boehr, D.D., Nussinov, R., and Wright, P.E. (2009). The role of dynamic conformational ensembles in biomolecular recognition. Nat. Chem. Biol. 5, 789–796. Carver, J.P., and Richards, R.E. (1972). General two-site solution for chemical exchange produced dependence of T2 upon Carr-Purcell pulse separation. J. Magn. Reson. 6, 89–105. Chakrabarti, K.S., Agafonov, R.V., Pontiggia, F., Otten, R., Higgins, M.K., Schertler, G.F., Oprian, D.D., and Kern, D. (2016). Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis. Cell Rep. 14, 32–42. Chen, J., Brooks, C.L., 3rd, and Wright, P.E. (2004). Model-free analysis of protein dynamics: assessment of accuracy and model selection protocols based on molecular dynamics simulation. J. Biomol. NMR 29, 243–257. Chen, J.R., Chang, B.H., Allen, J.E., Stiffler, M.A., and MacBeath, G. (2008). Predicting PDZ domain-peptide interactions from primary sequences. Nat. Biotechnol. 26, 1041–1045. Chiu, C.Y., Leng, S., Martin, K.A., Kim, E., Gorman, S., and Duhl, D.M. (1999). Cloning and characterization of T-cell lymphoma invasion and metastasis 2 (TIAM2), a novel guanine nucleotide exchange factor related to TIAM1. Genomics 61, 66–73. Clore, G.M. (2014). Interplay between conformational selection and induced fit in multidomain protein-ligand binding probed by paramagnetic relaxation enhancement. Biophys. Chem. 186, 3–12. Cole, R., and Loria, J.P. (2003). FAST-Modelfree: a program for rapid automated analysis of solution NMR spin-relaxation data. J. Biomol. NMR 26, 203–213. Delaglio, F., Grzesiek, S., Vuister, G.W., Zhu, G., Pfeifer, J., and Bax, A. (1995). NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J. Biomol. NMR 6, 277–293. Ernst, A., Sazinsky, S.L., Hui, S., Currell, B., Dharsee, M., Seshagiri, S., Bader, G.D., and Sidhu, S.S. (2009). Rapid evolution of functional complexity in a domain family. Sci. Signal. 2, ra50. Ernst, A., Gfeller, D., Kan, Z., Seshagiri, S., Kim, P.M., Bader, G.D., and Sidhu, S.S. (2010). Coevolution of PDZ domain-ligand interactions analyzed by highthroughput phage display and deep sequencing. Mol. Biosyst. 6, 1782–1790. Ernst, A., Appleton, B.A., Ivarsson, Y., Zhang, Y., Gfeller, D., Wiesmann, C., and Sidhu, S.S. (2014). A structural portrait of the PDZ domain family. J. Mol. Biol. 426, 3509–3519. Frederick, K.K., Marlow, M.S., Valentine, K.G., and Wand, A.J. (2007). Conformational entropy in molecular recognition by proteins. Nature 448, 325–329. Fuentes, E.J., Der, C.J., and Lee, A.L. (2004). Ligand-dependent dynamics and intramolecular signaling in a PDZ domain. J. Mol. Biol. 335, 1105–1115. Gianni, S., Dogan, J., and Jemth, P. (2014). Distinguishing induced fit from conformational selection. Biophys. Chem. 189, 33–39. Goddard, T.D., and Kneller, D.G. (2007). SPARKY 3 (University of California, San Francisco).

Structure 24, 1–14, December 6, 2016 13

Please cite this article in press as: Liu et al., Distinct Roles for Conformational Dynamics in Protein-Ligand Interactions, Structure (2016), http:// dx.doi.org/10.1016/j.str.2016.08.019

Gonzalez, M.M., Abriata, L.A., Tomatis, P.E., and Vila, A.J. (2016). Optimization of conformational dynamics in an epistatic evolutionary trajectory. Mol. Biol. Evol. 33, 1768–1776. Halabi, N., Rivoire, O., Leibler, S., and Ranganathan, R. (2009). Protein sectors: evolutionary units of three-dimensional structure. Cell 138, 774–786. Hammes, G.G., Chang, Y.C., and Oas, T.G. (2009). Conformational selection or induced fit: a flux description of reaction mechanism. Proc. Natl. Acad. Sci. USA 106, 13737–13741. Henzler-Wildman, K., and Kern, D. (2007). Dynamic personalities of proteins. Nature 450, 964–972. Hilser, V.J., Garcia-Moreno, E.B., Oas, T.G., Kapp, G., and Whitten, S.T. (2006). A statistical thermodynamic model of the protein ensemble. Chem. Rev. 106, 1545–1558. Jackson, M.R., Beahm, R., Duvvuru, S., Narasimhan, C., Wu, J., Wang, H.N., Philip, V.M., Hinde, R.J., and Howell, E.E. (2007). A preference for edgewise interactions between aromatic rings and carboxylate anions: the biological relevance of anion-quadrupole interactions. J. Phys. Chem. B 111, 8242– 8249. Johnson, B.A., and Blevins, R.A. (1994). NMRView: a computer program for the visualization and analysis of NMR data. J. Biomol. NMR 4, 603–614.

veals extensive epistasis in molecular recognition. Proc. Natl. Acad. Sci. USA 111, 15426–15431. Mulder, F.A., Skrynnikov, N.R., Hon, B., Dahlquist, F.W., and Kay, L.E. (2001). Measurement of slow (ms-ms) time scale dynamics in protein side chains by 15 N relaxation dispersion NMR spectroscopy: application to Asn and Gln residues in a cavity mutant of T4 lysozyme. J. Am. Chem. Soc. 123, 967–975. Niu, X., Chen, Q., Zhang, J., Shen, W., Shi, Y., and Wu, J. (2007). Interesting structural and dynamical behaviors exhibited by the AF-6 PDZ domain upon Bcr peptide binding. Biochemistry 46, 15042–15053. Ota, N., and Agard, D.A. (2005). Intramolecular signaling pathways revealed by modeling anisotropic thermal diffusion. J. Mol. Biol. 351, 345–354. Palmer, A.G., 3rd (2015). Enzyme dynamics from NMR spectroscopy. Acc. Chem. Res. 48, 457–465. Palmer, A.G., 3rd, Kroenke, C.D., and Loria, J.P. (2001). Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Methods Enzymol. 339, 204–238. Philip, V., Harris, J., Adams, R., Nguyen, D., Spiers, J., Baudry, J., Howell, E.E., and Hinde, R.J. (2011). A survey of aspartate-phenylalanine and glutamatephenylalanine interactions in the protein data bank: searching for anion-p pairs. Biochemistry 50, 2939–2950.

Kasinath, V., Sharp, K.A., and Wand, A.J. (2013). Microscopic insights into the NMR relaxation-based protein conformational entropy meter. J. Am. Chem. Soc. 135, 15092–15100.

Raman, A.S., White, K.I., and Ranganathan, R. (2016). Origins of allostery and evolvability in proteins: a case study. Cell 166, 468–480.

Law, A.B., Fuentes, E.J., and Lee, A.L. (2009). Conservation of side-chain dynamics within a protein family. J. Am. Chem. Soc. 131, 6322–6323.

Shepherd, T.R., and Fuentes, E.J. (2011). Structural and thermodynamic analysis of PDZ-ligand interactions. Methods Enzymol. 488, 81–100.

Lee, H.J., and Zheng, J.J. (2010). PDZ domains and their binding partners: structure, specificity, and modification. Cell Commun. Signal. 8, 1–18.

Shepherd, T.R., Klaus, S.M., Liu, X., Ramaswamy, S., DeMali, K.A., and Fuentes, E.J. (2010). The Tiam1 PDZ domain couples to Syndecan1 and promotes cell-matrix adhesion. J. Mol. Biol. 398, 730–746.

Lee, A.L., Flynn, P.F., and Wand, A.J. (1999). Comparison of 2H and 13C NMR relaxation techniques for the study of protein methyl group dynamics in solution. J. Am. Chem. Soc. 121, 2891–2902. Li, Z., Raychaudhuri, S., and Wand, A.J. (1996). Insights into the local residual entropy of proteins provided by NMR relaxation. Protein Sci. 5, 2647–2650. Lipari, G., and Szabo, A. (1982a). Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 2. Analysis of experimental results. J. Am. Chem. Soc. 104, 4559–4570. Lipari, G., and Szabo, A. (1982b). Model-free approach to the interpretation of nuclear magnetic resonance relaxation in macromolecules. 1. Theory and range of validity. J. Am. Chem. Soc. 104, 4546–4559. Lisi, G.P., and Loria, J.P. (2016). Using NMR spectroscopy to elucidate the role of molecular motions in enzyme function. Prog. Nucl. Magn. Reson. Spectrosc. 92–93, 1–17. Liu, X., Shepherd, T.R., Murray, A.M., Xu, Z., and Fuentes, E.J. (2013). The structure of the Tiam1 PDZ domain/phospho-syndecan1 complex reveals a ligand conformation that modulates protein dynamics. Structure 21, 342–354.

Shepherd, T.R., Hard, R.L., Murray, A.M., Pei, D., and Fuentes, E.J. (2011). Distinct ligand specificity of the Tiam1 and Tiam2 PDZ domains. Biochemistry 50, 1296–1308. Stiffler, M.A., Chen, J.R., Grantcharova, V.P., Lei, Y., Fuchs, D., Allen, J.E., Zaslavskaia, L.A., and MacBeath, G. (2007). PDZ domain binding selectivity is optimized across the mouse proteome. Science 317, 364–369. Tokuriki, N., and Tawfik, D.S. (2009). Protein dynamism and evolvability. Science 324, 203–207. Tonikian, R., Zhang, Y., Sazinsky, S.L., Currell, B., Yeh, J.H., Reva, B., Held, H.A., Appleton, B.A., Evangelista, M., Wu, Y., et al. (2008). A specificity map for the PDZ domain family. PLoS Biol. 6, e239. Tzeng, S.R., and Kalodimos, C.G. (2009). Dynamic activation of an allosteric regulatory protein. Nature 462, 368–372. Tzeng, S.R., and Kalodimos, C.G. (2012). Protein activity regulation by conformational entropy. Nature 488, 236–240.

Lockless, S.W., and Ranganathan, R. (1999). Evolutionarily conserved pathways of energetic connectivity in protein families. Science 286, 295–299.

Valley, C.C., Cembran, A., Perlmutter, J.D., Lewis, A.K., Labello, N.P., Gao, J., and Sachs, J.N. (2012). The methionine-aromatic motif plays a unique role in stabilizing protein structure. J. Biol. Chem. 287, 34979–34991.

Loria, J.P., Rance, M., and Palmer, A.G. (1999). A relaxation-compensated Carr-Purcell-Meiboom-Gill sequence for characterizing chemical exchange by NMR spectroscopy. J. Am. Chem. Soc. 121, 2331–2332.

Vogt, A.D., Pozzi, N., Chen, Z., and Di Cera, E. (2014). Essential role of conformational selection in ligand binding. Biophys. Chem. 186, 13–21.

Marlow, M.S., Dogan, J., Frederick, K.K., Valentine, K.G., and Wand, A.J. (2010). The role of conformational entropy in molecular recognition by calmodulin. Nat. Chem. Biol. 6, 352–358.

Wand, A.J. (2013). The dark energy of proteins comes to light: conformational entropy and its role in protein function revealed by NMR relaxation. Curr. Opin. Struct. Biol. 23, 75–81.

Mauldin, R.V., Carroll, M.J., and Lee, A.L. (2009). Dynamic dysfunction in dihydrofolate reductase results from antifolate drug binding: modulation of dynamics within a structural state. Structure 17, 386–394.

Weikl, T.R., and Paul, F. (2014). Conformational selection in protein binding and function. Protein Sci. 23, 1508–1518.

McGaughey, G.B., Gagne, M., and Rappe, A.K. (1998). p-stacking interactions. Alive and well in proteins. J. Biol. Chem. 273, 15458–15463. McLaughlin, R.N., Jr., Poelwijk, F.J., Raman, A., Gosal, W.S., and Ranganathan, R. (2012). The spatial architecture of protein function and adaptation. Nature 491, 138–142. Melero, C., Ollikainen, N., Harwood, I., Karpiak, J., and Kortemme, T. (2014). Quantification of the transferability of a designed protein specificity switch re-

14 Structure 24, 1–14, December 6, 2016

Whitney, D.S., Peterson, F.C., and Volkman, B.F. (2011). A conformational switch in the CRIB-PDZ module of Par-6. Structure 19, 1711–1722. Whitney, D.S., Peterson, F.C., Kovrigin, E.L., and Volkman, B.F. (2013). Allosteric activation of the Par-6 PDZ via a partial unfolding transition. J. Am. Chem. Soc. 135, 9377–9383. Yang, D., and Kay, L.E. (1996). Contributions to conformational entropy arising from bond vector fluctuations measured from NMR-derived order parameters: application to protein folding. J. Mol. Biol. 263, 369–382.