Template-based comparative analysis is a viable approach to the prediction and annotation of pathways in genomes. Methods based solely on sequence similarity may not be effective enough; functional and structural information such as protein-DNA interactions and operons can prove useful in improving the prediction accuracy. In this paper, we present a novel approach to predicting pathways by seeking high overall sequence similarity, functional and structural consistency between the predicted pathways and their templates. In particular, the prediction problem is formulated into finding the maximum independent set (MIS) in the graph constructed based on operon or interaction structures as well as homologous relationships of the involved genes. On such graphs, the MIS problem is solved efficiently via non-trivial tree decomposition of the graphs. The developed algorithm is evaluated based on the annotation of 40 pathways in Escherichia coli (E. coli) K12 using those in Bacillus subtilis (B. subtilis) 168 as templates. It demonstrates overall accuracy that outperforms those of the methods based solely on sequence similarity or using structural information of the genome with integer programming.