Quadratic Optimization-Based Nonlinear Control for Protein Conformation Prediction

Predicting the final folded structure of protein molecules and simulating their folding pathways is crucial importance for designing viral drugs studying diseases such as Alzheimer's at molecular level. To this end, letter investigates problem conformation prediction under constraint avoiding high-entropy-loss routes during folding. Using well-established kinetostatic compliance (KCM)-based nonlinear dynamics a molecule, formulates pointwise optimal control synthesis cast quadratic program (QP). It shown that KCM torques in literature can be utilized defining reference vector field QP-based generation problem. The resulting torque inputs will close to KCM-based guaranteed constrained by predetermined bound; hence, are avoided while energy molecule decreased.