Supplementary data are available at Bioinformatics online.

In this paper we briefly review some of the recent progress made by ourselves and others in developing methods for predicting the structures of transmembrane proteins from amino acid sequence. Transmembrane proteins are an important class of proteins involved in many diverse biological functions, many of which have great impact in terms of disease mechanism and drug discovery. Despite their biological importance, it has proven very difficult to solve the structures of these proteins by experimental techniques, and so there is a great deal of pressure to develop effective methods for predicting their structure. The methods we discuss range from methods for transmembrane topology prediction to new methods for low resolution folding simulations in a knowledge-based force field. This potential is designed to reproduce the properties of the lipid bilayer. Our eventual aim is to apply these methods in tandem so that useful three-dimensional models can be built for a large fraction of the transmembrane protein domains in whole proteomes.

Although both Rasl and Ras2 activate adenylyl cyclase in yeast, a number of differences can be observed regarding their function in the cAMP pathway. To explore the relative contribution of conserved and variable domains in determining these differences, chimeric RASJ-RAS2 orRAS2-RAS] genes were constructed by swapping the sequences encoding the variable C-terminal domains. These constructs were expressed in a cdc25ts rasi ras2 strain. Biochemical data show that the difference in efficacy of adenylyl cyclase activation between the two Ras proteins resides in the highly conserved N-terminal domain. This finding is supported by the observation that Ras2A, in which the C-terminal domain of Ras2 has been deleted, is a more potent activator of the yeast adenylyl cyclase than RaslA, in which the C-terminal domain of Rasl has been deleted. These observations suggest that amino acid residues other than the highly conserved residues of the effector domain within the N terminus may determine the efficiency of functional interaction with adenylyl cyclase. Similar levels of intracellular cAMP were found in Rasl, Rasl-Ras2, RaslA, Ras2, and Ras2-Rasl strains throughout the growth curve. This was found to result from the higher expression of Rasl and Rasl-Ras2, which compensate for their lower efficacy in activating adenylyl cyclase. These results suggest that the difference between the Rasl and the Ras2 phenotype is not due to their different efficacy in activating the cAMP pathway and that the divergent Cterminal domains are responsible for these differences, through interaction with other regulatory elements.Ras is a member of a highly conserved family of proteins acting as molecular switches in signal transduction pathways that control normal growth and differentiation (1). Ras cycles between an active GTP-bound and an inactive GDP-bound form (2). Guanine nucleotide binding is regulated by GDP-GTP exchange factors (GEFs), which promote the conversion to the active GTP-bound form, and GTPase-activating proteins (GAPs), which stimulate the intrinsic GTPase, resulting in the conversion to the inactive GDP-bound form (3). Mutations activating Ras impair the intrinsic GTPase, leading to constitutive binding to GTP irrespective of GEF or GAP activities.The cAMP pathway in the yeast Saccharomyces cerevisiae has been extensively studied as a model for understanding Ras function. S. cerevisiae possesses two Ras homologs, Rasl and Ras2 (4, 5), which mediate guanine nucleotide-dependent activation of adenylyl cyclase (6). Yeast cells lacking active Ras proteins fail to produce cAMP and are not viable (6, 7).Yeast Ras function is regulated by the CDC25 gene product, the yeast Ras GEF (8,9), and by the Iral and Ira2 genes, which are related to GAP (10,11 (14).While the N-terminal 180 amino acids of yeast Rasl and Ras2 are 91% homologous, no similarity is found between the C termini, except for the last 4 amino acids, which are crucial for processing and anchorage of Ras to the plasma membrane (15) and are conserved among all R...

The molecular chaperone Hsp90 is a ubiquitous ATPase-directed protein responsible for the activation and structural stabilization of a large clientele of proteins. As such, Hsp90 has emerged as a suitable candidate for the treatment of a diverse set of diseases, such as cancer and neurodegeneration. The inhibition of the chaperone through ATP-competitive inhibitors, however, was shown to lead to undesirable side effects. One strategy to alleviate this problem is the development of molecules that are able to disrupt specific protein–protein interactions, thus modulating the activity of Hsp90 only in the particular cellular pathway that needs to be targeted. Here, we exploit novel computational and theoretical approaches to design a set of peptides that are able to bind Hsp90 and compete for its interaction with the co-chaperone Cdc37, which is found to be responsible for the promotion of cancer cell proliferation. In spite of their capability to disrupt the Hsp90–Cdc37 interaction, no important cytotoxicity was observed in human cancer cells exposed to designed compounds. These findings imply the need for further optimization of the compounds, which may lead to new ways of interfering with the Hsp90 mechanisms that are important for tumour growth.

Designing peptides for protein-protein interaction inhibition is of significant interest in computer-aided drug design. Such inhibitory peptides could mimic and compete with the binding of the partner protein to the inhibition target. Experimental peptide design is a laborious, time consuming, and expensive multi-step process. Therefore, in silico peptide design can be beneficial for achieving this task. We present a novel algorithm, Pep-Whisperer, which aims to design inhibitory peptides for proteinprotein interaction. The desirable peptides would have a relatively high predicted binding affinity to the target protein in a given protein-protein complex. The algorithm outputs linear peptides which are based on an initial template. The template could either be a peptide which is retrieved from the interaction site, or a patch of nonconsecutive amino acids from the protein-protein interface which is completed to a linear peptide by short polyalanine linkers. In addition, the algorithm takes into consideration the conservation of the amino acids in the ligand-protein binding site by using evolutionary information for choosing the preferred amino acids in each position of the designed peptide. Our algorithm was able to design peptides with high predicted binding affinity to the target protein. The method is fully automated and available as a web server at http://bioinfo3d.cs.tau.ac.il/PepWhisperer/.