eMap 2.0: A web-based platform for identifying electron transfer pathways in proteins and protein families

eMap is a web based application for predicting electron/hole transfer pathways in proteins based on their crystal structures. The predictions are based on the Pathways model, where each hop between electron transfer active (ETA) moiety is described through a tunneling inspired penalty function. This is eloquently rendered in the framework of graph theory, where each ETA moietie is represented by a node, and the edge lengths are related to the penalty function. eMap 2.0 takes this one step further by constructing graphs for multiple proteins, and then finds common subgraphs using frequent subgraph mining (FSM), specifically gSpan. Lastly, eMap 2.0 utilizes sequence and structural similarity measures to analyze the frequent subgraph mining results. Here, we show how this powerful method has been successfully utilized to rapidly provide insight regarding conserved pathways within protein families, to identify structures with mutations within protein families, and to differentiate between active and inactive structures.