Remote protein homology detection is a problem of detecting evolutionary relationship between proteins at low sequence similarity level. Among several problems in remote protein homology detection include the questions of determining which combination of multiple alignment and classification techniques is the best as well as the misalignment of protein sequences during the alignment process. Therefore, this study deals with remote protein homology detection via assessing the impact of using structural information on protein multiple alignments over sequence information. This study further presents the best combinations of multiple alignment and classification programs to be chosen. This study also improves the quality of the multiple alignments via integration of a refinement algorithm.