Multiscale molecular simulations to investigate adenylyl cyclase‐based signaling in the brain

        Abstract
        Adenylyl cyclases (ACs) play a key role in many signaling cascades. ACs catalyze the production of cyclic AMP from ATP and this function is stimulated or inhibited by the binding of their cognate stimulatory or inhibitory Gα subunits, respectively. Here we used simulation tools to uncover the molecular and subcellular mechanisms of AC function, with a focus on the AC5 isoform, extensively studied experimentally. First, quantum mechanical/molecular mechanical free energy simulations were used to investigate the enzymatic reaction and its changes upon point mutations. Next, molecular dynamics simulations were employed to assess the catalytic state in the presence or absence of Gα subunits. This led to the identification of an inactive state of the enzyme that is present whenever an inhibitory Gα is associated, independent of the presence of a stimulatory Gα. In addition, the use of coevolution‐guided multiscale simulations revealed that the binding of Gα subunits reshapes the free‐energy landscape of the AC5 enzyme by following the classical population‐shift paradigm. Finally, Brownian dynamics simulations provided forward rate constants for the binding of Gα subunits to AC5, consistent with the ability of the protein to perform coincidence detection effectively. Our calculations also pointed to strong similarities between AC5 and other AC isoforms, including AC1 and AC6. Findings from the molecular simulations were used along with experimental data as constraints for systems biology modeling of a specific AC5‐triggered neuronal cascade to investigate how the dynamics of downstream signaling depend on initial receptor activation.
        
          This article is categorized under:
          
            
              Structure and Mechanism > Computational Biochemistry and Biophysics
            
            
              Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods
            
            
              Software > Molecular Modeling