We have developed a method to capture the essential conformational dynamics of folded biopolymers using statistical analysis of coarse-grained segment-segment contacts. Previously, the residue-residue contact analysis of simulation trajectories was successfully applied to the detection of conformational switching motions in biomolecular complexes. However, the application to large protein systems (larger than 1000 amino acid residues) is challenging using the description of residue contacts. Also, the residue-based method cannot be used to compare proteins with different sequences. To expand the scope of the method, we have tested several coarse-graining schemes that group a collection of consecutive residues into a segment. The definition of these segments may be derived from structural and sequence information, while the interaction strength of the coarse-grained segment-segment contacts is a function of the residue-residue contacts. We then perform covariance calculations on these coarse-grained contact matrices. We monitored how well the principal components of the contact matrices is preserved using various rendering functions. The new method was demonstrated to assist the reduction of the degrees of freedom for describing the conformation space, and it potentially allows for the analysis of a system that is approximately tenfold larger compared with the corresponding residue contact-based method. This method can also render a family of similar proteins into the same conformational space, and thus can be used to compare the structures of proteins with different sequences.

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Nuclear hormone receptors (NR) are transcription factors that relay cellular signals through distinct multiprotein assemblies. Hormonal signals produce structural changes within NRs that determine the composition of the interacting proteins. NRs are characteristically modular proteins. At the N terminus is an intrinsically disordered N‐terminal domain (NTD) followed by a DNA‐binding domain (DBD). The DBD recognizes DNA sites at the promoter of specific genes. At the C terminus is the ligand‐binding domain (LBD) which also contains a dimerization interface. Agonist binding to the LBD results in conformational changes associated with a transcriptionally active state where the LBD rearranges to create a docking site for transcriptional regulator proteins such as the steroid receptor coactivator 1 (SRC1). Whereas the general events involved in NR‐mediated gene transcription are well understood, fundamental issues remain unsolved. For instance, details of how the NR transcription factors recognize DNA sequences near the transcribed gene, so acting to ensure the optimal assembly of proteins actively involved in transcription, are still unknown. With the thyroid hormone receptor‐α (TRα) as a model system, our studies are aimed to uncover how NRs recognize specific DNA sites to secure optimal gene transcription. To achieve our objectives, we have employed a combination of structural biophysics and in cellulo assays. We utilize single‐molecule microscopy using optical tweezers, computational simulations of molecular dynamics and cell‐based transcription activity assays. With these techniques, we characterize how DNA sequences distant from the canonical binding site of TRα can regulate transcriptional activity.