Entropy-driven cAMP-dependent Allosteric Control of Inhibitory Interactions in Exchange Proteins Directly Activated by cAMP

Abstract

Exchange proteins directly activated by cAMP (EPACs) are guanine nucleotide-exchange factors for the small GTPases Rap1 and Rap2 and represent a key receptor for the ubiquitous cAMP second messenger in eukaryotes. The cAMP-dependent activation of apoEPAC is typically rationalized in terms of a preexisting equilibrium between inactive and active states. Structural and mutagenesis analyses have shown that one of the critical determinants of the EPAC activation equilibrium is a cluster of salt bridges formed between the catalytic core and helices ␣1 and ␣2 at the N terminus of the cAMP binding domain and commonly referred to as ionic latch (IL). The IL stabilizes the inactive states in a closed topology in which access to the catalytic domain is sterically occluded by the regulatory moiety. However, it is currently not fully understood how the IL is allosterically controlled by cAMP. Chemical shift mapping studies consistently indicate that cAMP does not significantly perturb the structure of the IL spanning sites within the regulatory region, pointing to cAMPdependent dynamic modulations as a key allosteric carrier of the cAMP-signal to the IL sites. Here, we have therefore investigated the dynamic profiles of the EPAC1 cAMP binding domain in its apo, cAMP-bound, and Rp-cAMPS phosphorothioate antagonistbound forms using several 15 N relaxation experiments. Based on the comparative analysis of dynamics in these three states, we have proposed a model of EPAC activation that incorporates the dynamic features allosterically modulated by cAMP and shows that cAMP binding weakens the IL by increasing its entropic penalty due to dynamic enhancements.The exchange protein directly activated by cAMP (EPAC) 3 is one of the key receptors for the ancient and ubiquitous cAMP second messenger in mammals (1-3). The interaction of cAMP with EPAC results in the activation of the guanine-nucleotide exchange in the small GTPases Rap1 and Rap2 (1, 2), leading to the cAMP-dependent control of a wide array of critical signaling pathways underlying diverse cellular functions, ranging from insulin secretion to memory enhancement and cell adhesion (4 -10). Two cAMP-dependent EPAC isoforms are currently known (Fig. 1a). Both EPAC1 and -2 are multidomain proteins with an N-terminal regulatory region (RR), including the cAMP binding domains (CBDs) and a C-terminal catalytic region (CR), containing a CDC25-homology module (CDC25HD) that functions as a guanine-nucleotide-exchange factor (GEF) (Fig. 1a). In both EPAC isoforms the cAMP dependence of the GEF function is implemented through the CBD at the C terminus of the RR (Fig. 1, a and b) irrespective of the DEP domain, which serves the primary purpose of controlling the membrane localization of EPAC (4, 9).The cAMP-dependent structural changes underlying the regulatory function of the EPAC CBD have been previously mapped by the crystal structures of several structurally homologous CBDs solved in the apo and cAMP-bound states (11-18). These CBD structures consistently show that the main confo...

Mechanism of cAMP Partial Agonism in Protein Kinase G (PKG)

“…Considering the rigidity typically exhibited by the inner ␤-strands (i.e. ␤3, ␤4, ␤7, and ␤8) of the ␤-barrel of CNB domains (27,46), R 1 R 2 and/or J(0) values significantly greater than the inner-␤-strand average were considered indicative of the presence of millisecond-microsecond backbone dynamics, whereas R 1 R 2 , J(0), and/or HN-NOE values significantly less than the inner-␤-strand average, and/or J( H ϩ N ) values significantly greater than the inner-␤-strand average, are indicative of the presence of picosecond-nanosecond backbone dynamics. Differences in the R 1 R 2 and J(0) values between dif-ferent samples of PKG I␤(219 -369) were deemed significant if the error bars of the compared data points did not overlap one another.…”

“…To further examine PKG I␤(219 -369) dynamics, backbone 15 N relaxation (R 1 , R 2 , HN-NOE) and hydrogen exchange (H/D and H/H) NMR data for the apo, cAMP-, and cGMP-bound samples of PKG I␤(219 -369) were acquired and analyzed using a protocol similar to that described previously (13,46,47), with the T 1 and T 2 data sets acquired as pseudo-three-dimensional matrices (48). Reduced spectral densities (RSDs) were then computed from the 15 N relaxation rates as described previously (13,46,47).…”

“…Reduced spectral densities (RSDs) were then computed from the 15 N relaxation rates as described previously (13,46,47). Considering the rigidity typically exhibited by the inner ␤-strands (i.e.…”

Signaling through dynamic linkers as revealed by PKA

“…Assignments were obtained either through triple-resonance 3D experiments [i.e., HNCO, HNCA, HN(CO)CA, CBCA(CO)NH, and HNCACB] (47) and/or through spectral comparisons, if no ambiguities were present. HN NOE data were acquired as previously reported (48,49) and processed without linear prediction. A 10-s recycle delay was used to include a 5-s proton saturation period.…”

NMR reveals novel mechanisms of protein activity regulation

“…[33][34][35] Numerous examples are currently available highlighting the inextricable link between protein dynamics and allostery 8,36 . Long-range allosteric coupling between sites through changes in internal dynamics were seen between the nucleotide-binding cleft and the preprotein-binding site in SecA ATPase, 37 between the coordination Na þ site and exosite I in thrombin that regulates enzyme's specificity, 38 between the substrate-binding site and distal loop in dihydrofolate reductase, 39 between the mixed lineage leukemia)-and c-Myb binding sites of the KIX domain of CREB-binding protein, 40 in PDZ signaling domains, 41 the serine protease inhibitor eglin c, 42 upon binding of barstar to the RNase barnase, 43 in the interaction between the Rho GTPasebinding domain and Rac1, 44 upon cyclic nucleotide binding to the exchange protein activated by cAMP, 45,46 a in V-type allosteric enzyme, 47 and in protein kinase A, 48,49 only to mention few recent examples from a long list of systems characterized over the years. Dynamic changes in these systems were accompanied by varying extent of structural changes, ranging from minimal to substantial.…”