Mevalonate pathway is of important clinical, pharmaceutical and biotechnological relevance.However, lack of the understanding of the phosphorylation mechanism of the kinases in this pathway has limited rationally engineering the kinases in industry. Here the phosphorylation reaction mechanism of a representative kinase in the mevalonate pathway, phosphomevalonate kinase, was studied by using molecular dynamics and hybrid QM/MM methods. We find that a conserved residue (Ser106) is reorientated to anchor ATP via a stable H-bond interaction. In addition, Ser213 located on the α-helix at the catalytic site is repositioned to further approach the substrate, facilitating the proton transfer during the phosphorylation. Furthermore, we elucidate that Lys101 functions to neutralize the negative charge developed at the β-, γ-bridging oxygen atom of ATP during phosphoryl transfer. We demonstrate that the dissociative catalytic reaction occurs via a direct phosphorylation pathway. This is the first study on the phosphorylation mechanism of a mevalonate pathway kinase. The elucidation of the catalytic mechanism not only sheds light on the common catalytic mechanism of GHMP kinase superfamily, but also provides the structural basis for engineering the mevalonate pathway kinases to further exploit their applications in the production of a wide range of fine chemicals such as biofuels or pharmaceuticals.3
This paper proposes a novel method for optimizing the Cauer-type thermal network model considering both the temperature influence on the extraction of parameters and the errors caused by the physical structure. In terms of prediction of the transient junction temperature and the steady-state junction temperature, the conventional Cauer-type parameters are modified, and the general method for estimating junction temperature is studied by using the adaptive thermal network model. The results show that junction temperature estimated by our adaptive Cauer-type thermal network model is more accurate than that of the conventional model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.