Metabolic network analysis will play a major role in �Systems Biology� in the future as they represent the backbone of molecular activity within the cell. Recent studies have taken a comparative approach toward interpreting these networks, contrasting networks of different species and molecular types, and under varying conditions. We have developed a robust algorithm to calculate shortest path in the metabolic network using metabolite chemical structure information. A divide and conquer technique using Maximal Common Subgraph (MCS) approach and binary fingerprint was used to map each substrate onto its corresponding product. Then for the calculation of the shortest paths (using modified Breadth First Search algorithm) the two biochemical criteria �local� and �global� structural similarity were used, where �local similarity� is defined as the similarity between two intermediate molecules and �global similarity� is defined as the amount of conserved structure found between the source metabolite and the destination metabolites after a series of reaction steps. The pathway alignment was introduced to find enzyme(s) preference in the pathway of various organisms (a local and global outlook to metabolic networks). This was also used to predict potentially missing enzymes in the pathway. A novel concept called �load points� and �choke points� identifies hot spots in the network. This was used to find important enzymes in the pathogens metabolic network for potential drug targets
