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      Comparative structural modeling and inference of conserved protein classes in Drosophila seminal fluid

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      Proceedings of the National Academy of Sciences
      Proceedings of the National Academy of Sciences

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          Abstract

          The constituents of seminal fluid are a complex mixture of proteins and other molecules, most of whose functions have yet to be determined and many of which are rapidly evolving. As a step in elucidating the roles of these proteins and exposing potential functional similarities hidden by their rapid evolution, we performed comparative structural modeling on 28 of 52 predicted seminal proteins produced in the Drosophila melanogaster male accessory gland. Each model was characterized by defining residues likely to be important for structure and function. Comparisons of known protein structures with predicted accessory gland proteins (Acps) revealed similarities undetectable by primary sequence alignments. The structures predict that Acps fall into several categories: regulators of proteolysis, lipid modifiers, immunity/protection, sperm-binding proteins, and peptide hormones. The comparative structural modeling approach indicates that major functional classes of mammalian and Drosophila seminal fluid proteins are conserved, despite differences in reproductive strategies. This is particularly striking in the face of the rapid protein sequence evolution that characterizes many reproductive proteins, including Drosophila and mammalian seminal proteins.

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          Most cited references59

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          The rapid evolution of reproductive proteins.

          Many genes that mediate sexual reproduction, such as those involved in gamete recognition, diverge rapidly, often as a result of adaptive evolution. This widespread phenomenon might have important consequences, such as the establishment of barriers to fertilization that might lead to speciation. Sequence comparisons and functional studies are beginning to show the extent to which the rapid divergence of reproductive proteins is involved in the speciation process.
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            Protein structure prediction and structural genomics.

            Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.
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              FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties.

              FUGUE, a program for recognizing distant homologues by sequence-structure comparison (http://www-cryst.bioc.cam.ac.uk/fugue/), has three key features. (1) Improved environment-specific substitution tables. Substitutions of an amino acid in a protein structure are constrained by its local structural environment, which can be defined in terms of secondary structure, solvent accessibility, and hydrogen bonding status. The environment-specific substitution tables have been derived from structural alignments in the HOMSTRAD database (http://www-cryst.bioc. cam.ac.uk/homstrad/). (2) Automatic selection of alignment algorithm with detailed structure-dependent gap penalties. FUGUE uses the global-local algorithm to align a sequence-structure pair when they greatly differ in length and uses the global algorithm in other cases. The gap penalty at each position of the structure is determined according to its solvent accessibility, its position relative to the secondary structure elements (SSEs) and the conservation of the SSEs. (3) Combined information from both multiple sequences and multiple structures. FUGUE is designed to align multiple sequences against multiple structures to enrich the conservation/variation information. We demonstrate that the combination of these three key features implemented in FUGUE improves both homology recognition performance and alignment accuracy. Copyright 2001 Academic Press.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                September 14 2004
                September 14 2004
                September 02 2004
                September 14 2004
                : 101
                : 37
                : 13542-13547
                Article
                10.1073/pnas.0405579101
                518759
                15345744
                f8dfb71a-0b4e-4b9d-9039-697b75b0e319
                © 2004
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