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Native states of folded proteins are characterized by a large ensemble of conformations whose relative populations and interconversion dynamics determine the functional output. This is more apparent in transcription factors that have evolved to be inherently sensitive to small perturbations, thus fine-tuning gene expression. To explore the extent to which such functional features are imprinted on the folding landscape of transcription factor ligand-binding domains (LBDs), we characterize paralogous LBDs of the nuclear receptor (NR) family employing an energetically detailed and ensemble-based Ising-like statistical mechanical model. We find that the native ensembles of the LBDs from glucocorticoid receptor, PPAγ, and thyroid hormone receptor display a remarkable diversity in the width of the native wells, the number and nature of partially structured states, and hence the degree of conformational order. Monte Carlo simulations employing the full state representation of the ensemble highlight that many of the functional conformations coexist in equilibrium, whose relative populations are sensitive to both temperature and the strength of ligand binding. Allosteric modulation of the degree of structure at a coregulator binding site on ligand binding is shown to arise via a redistribution of populations in the native ensembles of glucocorticoid and PPAγ LBDs. Our results illustrate how functional requirements can drive the evolution of conformationally diverse native ensembles in paralogs.

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Receptor for advanced glycation end products (RAGE) has been implicated in the pathophysiology of Alzheimers disease(AD) due to its ability to bind amyloid-beta (Aβ42) and mediate inflammatory response. G82S RAGE polymorphism is associated with AD but the molecular mechanism for this association is not understood. Our previous in silico study indicated a higher binding affinity for mutated G82S RAGE, which could be caused due to changes in N linked glycosylation at residue N81. To confirm this hypothesis, in the present study molecular dynamics (MD) simulations were used to simulate the wild type (WT) and G82S glycosylated structures of RAGE to identify the global structural changes and to find the binding efficiency with Aβ42 peptide. Binding pocket analysis of the MD trajectory showed that cavity/binding pocket in mutant G82S glycosylated RAGE variants is more exposed and accessible to external ligands compared to WT RAGE, which can enhance the affinity of RAGE for Aβ. To validate the above concept, an in vitro binding study was carried using SHSY5Y cell line expressing recombinant WT and mutated RAGE variant individually to which HiLyte Fluor labeled Aβ42 was incubated at different concentrations. Saturated binding kinetics method was adopted to determine the K d values for Aβ42 binding to RAGE. The K d value for Aβ42- WT and Aβ42-mutant RAGE binding were 92±40 nM (95% CI-52 to 152nM; R 2 -0.92) and 45±20 nM (95% CI -29 to 64nM; R 2 -0.93), respectively. The K d value of <100nM observed for both variants implicates RAGE as a high-affinity receptor for Aβ42 and mutant RAGE has higher affinity compared to WT. The alteration in binding affinity is responsible for activation of the inflammatory pathway as implicated by enhanced expression of TNFα and IL6 in mutant RAGE expressing cell line which gives a mechanistic view for the G82S RAGE association with AD.

30Receptor for advanced glycation end products (RAGE) has been implicated in the 31 pathophysiology of AD due to its ability to bind amyloid-beta and mediate inflammatory 32 response. G82S RAGE polymorphism is associated with AD but the molecular mechanism for 33 this association is not understood. Our previous in silico study indicated a higher binding 34 affinity for mutated G82S RAGE, which could be caused due to changes in N linked 35 glycosylation at residue N81. To confirm this hypothesis, in the present study molecular 36 dynamics (MD) simulations were used to simulate the wild type (WT) and G82S glycosylated 37 structures of RAGE to identify the global structural changes and to find the binding efficiency 38 with Aβ42 peptide. Binding pocket analysis of the MD trajectory showed that cavity/binding 39 pocket in mutant G82S glycosylated RAGE variants is more exposed and accessible to external 40 ligands compared to WT RAGE, which can enhance the affinity of RAGE for Aβ. To validate 41 the above concept, an in vitro binding study was carried using SHSY5Y cell line expressing 42 recombinant WT and mutated RAGE variant individually to which HiLyte Fluor labeled Aβ42 43 was incubated at different concentrations. Saturated binding kinetics method was adopted to 44 determine the K d values for Aβ42 binding to RAGE. The K d value for Aβ42-WT and Aβ42-45 mutant RAGE binding were 92±40 nM (95% CI-52 to 152nM; R 2 -0.92) and 45±20 nM (95% 46 CI -29 to 64nM; R 2 -0.93), respectively. The K d value of <100nM observed for both variants 47 implicates RAGE as a high-affinity receptor for Aβ42 and mutant RAGE has higher affinity 48 compared to WT. The alteration in binding affinity is responsible for activation of the 49 inflammatory pathway as implicated by enhanced expression of TNFα and IL6 in mutant 50 RAGE expressing cell line which gives a mechanistic view for the G82S RAGE association 51 with AD. 52 54 Receptor for Advanced Glycation End-products (RAGE) belongs to the immunoglobulin 55 superfamily, which interacts with various ligands and plays an important role in several 56 pathological conditions [1]. Due to alternative splicing, various isoforms are generated such as 57 full-length RAGE (fRAGE), secretory RAGE (sRAGE) and dominant negative RAGE 58 (DNRAGE) and they bind to the ligands with similar affinity. The fRAGE consist of 59 extracellular, hydrophobic transmembrane, and cytoplasmic domains, whereas sRAGE lacks a 60 transmembrane domain. Extracellular domain has three immunoglobulins like domains namely 61 variable (V) domain and two constant (C1 & C2) domains. The structural analysis of the ligand-62 binding domain within the V-domain structure of fRAGE indicates a hydrophobic cavity that 63 is bordered by cationic residues and a flexible region (Thr55-Pro71). The flexible region 64 allows further plasticity within the hydrophobic cavity, thereby promoting hydrostatic 65 interactions with RAGE ligands [2,3] 66 Initiation of signal transduction upon the interaction of RAGE with its specific ligands helps...