Progressive sequence model refinement by means of iterative searches is an effective technique for high sensitivity database searches and is currently employed in popular tools such as PSI-BLAST and SAM. Recently, a novel alignment algorithm has been proposed that offers features expected to improve the sensitivity of such iterative approaches, specifically a well-characterized theory of its statistics even in the presence of position-specific gap costs. Here, we demonstrate that the new hybrid alignment algorithm is ready to be used as the alignment core of PSIBLAST. In addition, we evaluate the accuracy of two proposed approaches to edge effect correction in short sequence alignment statistics that turns out to be one of the crucial issues in developing a hybrid-alignment based version of PSI-BLAST.