Negative-strand RNA viruses: genetic engineering and applications.

The negative-strand RNA viruses are a broad group of animal viruses that comprise several important human pathogens, including influenza, measles, mumps, rabies, respiratory syncytial, Ebola, and hantaviruses. The development of new strategies to genetically manipulate the genomes of negative-strand RNA viruses has provided us with new tools to study the structure-function relationships of the viral components and their contributions to the pathogenicity of these viruses. It is also now possible to envision rational approaches--based on genetic engineering techniques--to design live attenuated vaccines against some of these viral agents. In addition, the use of different negative-strand RNA viruses as vectors to efficiently express foreign polypeptides has also become feasible, and these novel vectors have potential applications in disease prevention as well as in gene therapy.

Identification of receptor-binding domains on human interleukin 5 and design of an interleukin 5-derived receptor antagonist.

A detailed structure-function analysis of human interleukin 5 (hIL5) has been performed. The hIL5 receptor is composed of two different polypeptide chains, the alpha and beta subunits. The alpha subunit alone is sufficient for ligand binding, but association with the beta subunit leads to a 2- to 3-fold increase in binding affinity. The beta chain is shared with the receptors for IL3 and granulocyte/macrophage-colony-stimulating factor--hence the descriptor beta C (C for common). All hIL5 mutants were analyzed in a solid-phase binding assay for hIL5R alpha interaction and in a proliferation assay using IL5-dependent cell lines for receptor-complex activation. Most residues affecting binding to the receptor alpha subunit were clustered in a loop connecting beta-strand 1 and helix B (mutants H38A, K39A, and H41A), in beta-strand 2 (E89A and R91A; weaker effect for E90A) and close to the C terminus (T109A, E110A, W111S, and I112A). Mutations at one position, E13 (Glu13), caused a reduced activation of the hIL5 receptor complex. In the case of E13Q, only 0.05% bioactivity was detected on a hIL5-responsive subclone of the mouse promyelocytic cell line FDC-P1. Moreover, on hIL5-responsive TF1 cells, the same mutant was completely inactive and proved to have antagonistic properties. Interactions of this mutant with both receptor subunits were nevertheless indistinguishable from those of nonmutated hIL5 by crosslinking and Scatchard plot analysis of transfected COS-1 cells.

Structure-based conformational preferences of amino acids

Proteins can be very tolerant to amino acid substitution, even within their core. Understanding the factors responsible for this behavior is of critical importance for protein engineering and design. Mutations in proteins have been quantified in terms of the changes in stability they induce. For example, guest residues in specific secondary structures have been used as probes of conformational preferences of amino acids, yielding propensity scales. Predicting these amino acid propensities would be a good test of any new potential energy functions used to mimic protein stability. We have recently developed a protein design procedure that optimizes whole sequences for a given target conformation based on the knowledge of the template backbone and on a semiempirical potential energy function. This energy function is purely physical, including steric interactions based on a Lennard-Jones potential, electrostatics based on a Coulomb potential, and hydrophobicity in the form of an environment free energy based on accessible surface area and interatomic contact areas. Sequences designed by this procedure for 10 different proteins were analyzed to extract conformational preferences for amino acids. The resulting structure-based propensity scales show significant agreements with experimental propensity scale values, both for α-helices and β-sheets. These results indicate that amino acid conformational preferences are a natural consequence of the potential energy we use. This confirms the accuracy of our potential and indicates that such preferences should not be added as a design criterion.