Protein-RNA complexes are increasingly important in our understanding of cell signaling, metabolism, and transcription. Electrostatic interactions play dominant role in stabilizing such complexes. Using conventional computational approaches, very long simulations of both bound and unbound states are required to obtain accurate estimates of complex dissociation constants (Kd). Here, we derive a simple formula that offers an alternative approach based on the theory of fluctuations. Our method extracts a strong correlate to experimental Kd values using short molecular dynamics simulations of the bound complex only. To test our method, we compared the computed relative Kd values to our experimentally measured values for the U1A-Stem Loop 2 (SL2) RNA complex, which is one of the most-studied protein-RNA complexes. Additionally we also included several experimental values from the literature, to enlarge the data set. We obtain a correlation of r = 0.93 between theoretical and measured estimates of Kd values of the mutated U1A protein-RNA complexes relative to the wild type dissociation constant. The proposed method increases the efficiency of relative Kd values estimation for multiple protein mutants, allowing its applicability to protein engineering projects.
ASJC Scopus subject areas
- Computer Science Applications
- Physical and Theoretical Chemistry