STRUCTURE - FUNCTION AND KINETICS OF AAA+ ATPASES

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Why do defects in molecular machines (AAA+ ATPases) cause disease? These protein machines convert ATP hydrolysis into mechanical work. Both human cells and disease causing pathogens use this work to physically manipulate proteins or DNA to dismantle and reassemble membranes or other organelles, to replicate DNA and traverse cell division, to repair damaged proteins, or to regulate gene expression. We do not know how these molecular machines convert ATP hydrolysis into mechanical work. Our research focuses on one subset of AAA+ ATPAses, the bacterial-enhancer-binding proteins (EBPs) which use their ATPase activities to regulate transcription of genes needed for harmful activites (diseases, crop damage) or helpful ones (nitrogen fixation, environmental remediation, hydrogen or other metabolite production). In a prior project, we established two mechanisms for regulating the EBP ATPases, and began defining structural changes occuring in their catalytic cycle. The current project completes that objective, also extending it to address the underlying mechanism via structure function studies of mutant forms of ATPase. An unexpected outcome was the discovery of a second form of the ATPase that hydrolyzes ADP to AMP. This novel activity for AAA+ ATPases was discovered because SAXS data showed ADP causing the same conformational changes in a mutant of the ATPase that are caused by ATP binding to the wild type protein. Chromatographic separation of the ATPase from the apyrase form yielded for the first time a crystal structure of the ATP-bound form of this particular AAA+ ATPase, allowing us to further interpret prior SAXS data.