The serpins (serine proteinase inhibitors) are a superfamily of proteins (350 -500 amino acids in size) that fold into a conserved structure and employ a unique suicide substrate-like inhibitory mechanism. The serpins were last reviewed in 1994 (1). More recent studies show: 1) an expanded distribution within the kingdoms of metazoa and plantae, as well as certain viruses, 2) a surprising effect on the covalently bound target proteinase, and 3) novel biochemical and biological functions.Most serpins inhibit serine proteinases of the chymotrypsin family. However, cross-class inhibitors have been identified. The viral serpin CrmA and, to a lesser extent, PI9 (SERPINB9) inhibit the cysteine proteinase, caspase 1 (2), and SCCA1

A defining property of cytotoxic lymphocytes is their expression and regulated secretion of potent toxins, including the pore-forming protein perforin and serine protease granzymes. Until recently, mechanisms of pore formation and granzyme transfer into the target cell were poorly understood, but advances in structural and cellular biology have now begun to unravel how synergy between perforin and granzymes brings about target cell death. These and other advances are demonstrating the surprisingly broad pathophysiological roles of the perforin–granzyme pathway, and this has important implications for understanding immune homeostasis and for developing immunotherapies for cancer and other diseases. In particular, we are beginning to define and understand a range of human diseases that are associated with a failure to deliver active perforin to target cells. In this Review, we discuss the current understanding of the structural, cellular and clinical aspects of perforin and granzyme biology.

We present a comprehensive alignment and phylogenetic analysis of the serpins, a superfamily of proteins with known members in higher animals, nematodes, insects, plants, and viruses. We analyze, compare, and classify 219 proteins representative of eight major and eight minor subfamilies, using a novel technique of consensus analysis. Patterns of sequence conservation characterize the family as a whole, with a clear relationship to the mechanism of function. Variations of these patterns within phylogenetically distinct groups can be correlated with the divergence of structure and function. The goals of this work are to provide a carefully curated alignment of serpin sequences, to describe patterns of conservation and divergence, and to derive a phylogenetic tree expressing the relationships among the members of this family. We extend earlier studies by Huber and Carrell as well as by Marshall, after whose publication the serpin family has grown functionally, taxonomically, and structurally. We used gene and protein sequence data, crystal structures, and chromosomal location where available. The results illuminate structure-function relationships in serpins, suggesting roles for conserved residues in the mechanism of conformational change. The phylogeny provides a rational evolutionary framework to classify serpins and enables identification of conserved amino acids. Patterns of conservation also provide an initial point of comparison for genes identified by the various genome projects. New homologs emerging from sequencing projects can either take their place within the current classification or, if necessary, extend it.

Multiple structural alignment is a fundamental problem in structural genomics. In this article, we define a reliable and robust algorithm, MUSTANG (MUltiple STructural AligNment AlGorithm), for the alignment of multiple protein structures. Given a set of protein structures, the program constructs a multiple alignment using the spatial information of the C(alpha) atoms in the set. Broadly based on the progressive pairwise heuristic, this algorithm gains accuracy through novel and effective refinement phases. MUSTANG reports the multiple sequence alignment and the corresponding superposition of structures. Alignments generated by MUSTANG are compared with several handcurated alignments in the literature as well as with the benchmark alignments of 1033 alignment families from the HOMSTRAD database. The performance of MUSTANG was compared with DALI at a pairwise level, and with other multiple structural alignment tools such as POSA, CE-MC, MALECON, and MultiProt. MUSTANG performs comparably to popular pairwise and multiple structural alignment tools for closely related proteins, and performs more reliably than other multiple structural alignment methods on hard data sets containing distantly related proteins or proteins that show conformational changes.