Predicting Sequence of Events upon Ligand Binding Using PMT Model: A Case Study of Adenylate Kinase

Abstract

Conformational transitions play a crucial role during the reaction cycle of many enzymes. In the case of adenylate kinase (AK), binding of ATP and AMP induces a conformational change where the closing of the LID and NMP domains over the core domain is followed by the phosphate transfer from ATP to ADP. This conformational change is rate-limiting for the enzymatic reaction, and AK is thought to be in equilibrium between open and close states. In this work, we studied the sequence of events along the conformational transition pathway. Using the Perturbation-based Markovian Transmission (PMT) model [Lu and Liang, PLOS Computational Biology, 2009], we study each of the 45 intermediate conformations available in PDB. We apply an initial perturbation on the binding domains of the enzyme, whose transmission is modeled as a Markovian Process. The dynamics of the probability flow is then computed by solving the Master Equation using a Krylov subspace method. From the landscape of time-evolving probability flow of all residues upon initial perturbation, we calculated the information entropy and related parameter for each residue. By analyzing time-dependent changes in entropy of residues located within or are in-contact with the LID/NMP domains, we predicted contacts that would break first for each conformation. Using the initial open state conformation only we are able to identify the next conformation along the conformation transition pathway with an average accuracy of 85% in predicted bond breakage We also predicted a set of critical residues with distinct dynamic behavior that are important in ligand binding.