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This study examines the non-monotonic (U-shaped, inverted U-shaped or curvilinear) relationship between the corporate governance (CG) and bank performance of commercial banks operating across four countries whose CG framework is based on the OECD principals of CG. Using a dataset of 4230 bank-years observation from 2012–2021, the study shows that governance–performance relations may be non-monotonic but not U-shaped using a two-line approach and the Robin Hood algorithm. In addition, this study, using feasible generalized least squares (FGLS), empirically shows that the interaction effect of CEO duality on governance–performance relations in financial institutions is curvilinear and significantly moderates and reverses these impacts. The findings reveal that, in financial institutions with CEO duality, there is a far more modest association between CG and performance, which has an inverted-U shape and is curvilinear. The findings are consistent with arguments advanced by resource dependence and stewardship theory that, although duality might increase bank performance through joint leadership, it can benefit the bank in the presence of unity of command. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state‐of‐the‐art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph‐based modeling approach, where we first build substructures from NMR‐derived distance‐geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance‐geometry constraints. One‐shot structure building is rarely undertaken for large and sparse data systems, but our data‐driven bottom‐up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state‐of‐art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein‐folds covering 38–282 length structures shows minimal experimental‐constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state‐of‐art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure–function. Our work is thus useful in building enhanced NMR‐evidence‐based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference. [ABSTRACT FROM AUTHOR]