Microbial species thrive within human hosts by establishing complex associations between themselves and the host. Even though species diversity can be measured (alpha- and beta-diversity), a methodology to estimate the impact of microorganisms in human pathways is still lacking. In this work we propose a computational approach to estimate which human pathways are targeted the most by microorganisms, while also identifying which microorganisms are prominent in this targeting. Our results were consistent with literature evidence, and thus we propose this methodology as a new prospective approach to be used for screening potentially impacted pathways.