Design and evolution of artificial M13 coat proteins

Using simple design and selective pressure, we have evolved an artificial M13 bacteriophage coat protein. M13 coat proteins first reside in the bacterial inner membrane and subsequently surround the DNA core of the assembled virus. The artificial coat protein (ACP) was designed and evolved to mimic both functions of the natural M13 coat proteins, but with an inverted orientation. ACP is a non-functional coat protein because it is not required for the production of phage particles. Instead, it incorporates into a phage coat which still requires all the natural coat proteins for structural integrity. In contrast with other M13 coat proteins, which can display polypeptides as amino-terminal fusions, ACP permits the carboxy-terminal display of large polypeptides. The results suggest that viruses can co-opt host membrane proteins to acquire new coat proteins and thus new functions. In particular, M13 bacteriophage can be engineered for new functions, such as carboxy-terminal phage display.     

Predicting the conformations of peptides and proteins in early evolution

Considering that short, mainly heterochiral, polypeptides with a high glycine content are expected to have played a prominent role in evolution at the earliest stage of life before nucleic acids were available, we review recent knowledge about polypeptide three-dimensional structure to predict the types of conformations they would have adopted. The possible existence of such structures at this time leads to a consideration of their functional significance, and the consequences for the course of evolution. This article was reviewed by Bill Martin, Eugene Koonin and Nick Grishin.     

Synthetic peptides as artificial receptors towards proteins from genetically modified organisms

The aim of this work was the preparation of peptide ligands with good affinity and selectivity towards proteins from genetically modified organisms, namely neomycin phosphotransferase II (Npt II) and the endotoxin Cry1A. A 12x12 combinatorial solid phase synthesis in aqueous medium was performed to prepare peptide libraries. From this library, two dipeptides with binding properties towards the chosen ligands (Pro-Lys for Npt II, K(eq) 7.59x10(4)M(-1); Trp-Gln for Cry 1A, K(eq) 4.35x10(4)M(-1)) were selected as scaffolds for the synthesis of new tetrapeptide libraries. The equilibrium constants of the newly selected tetrapeptides increased slightly respect to the dipeptides (Pro-Lys-His-Phe for Npt II, K(eq) 7.88x10(4)M(-1); Trp-Gln-Ala-Phe for Cry 1A, K(eq) 5.65x10(4)M(-1)), but selectivity towards other proteins (wheat gliadins, bovine gamma-globulins, bovine serum albumin and chicken ovalbumin) became higher. It was demonstrated that selected tetrapeptides recognised well the ligands also in presence of very complex mixtures of potentially interfering proteins, such as whole cell lysates. This approach can be considered as a general method to obtain tailor-made reagents with antibody-like binding properties towards biomacromolecules.     

Multiplexed absolute quantification in proteomics using artificial QCAT proteins of concatenated signature peptides

Absolute quantification in proteomics usually involves simultaneous determination of representative proteolytic peptides and stable isotope-labeled analogs. The principal limitation to widespread implementation of this approach is the availability of standard signature peptides in accurately known amounts. We report the successful design and construction of an artificial gene encoding a concatenation of tryptic peptides (QCAT protein) from several chick (Gallus gallus) skeletal muscle proteins and features for quantification and purification.     

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called “physics and chemistry-driven artificial neural network (Phys-Chem ANN)”, to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the “hidden layers” are no longer virtual “neurons”, but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.     

In vitro selection as a powerful tool for the applied evolution of proteins and peptides

New in vitro methods for the applied evolution of protein structure and function complement conventional cellular and phage-based methods. Strategies employing the direct physical linkage of genotype and phenotype, and the compartmental association of gene and product to select desired properties are discussed, and recent useful applications are described. Engineering of antibodies and other proteins, selection from cDNA libraries, and the creation of functional protein domains from completely random starting sequences illustrate the value of the in vitro approaches. Also discussed is an emerging new direction for in vitro display technology: the self-assembly of protein arrays.     

A possible role of exon-shuffling in the evolution of signal peptides of human proteins

It was recently shown that there is a predominance of phase 1 introns near the cleavage site of signal peptides encoded by human genes. It was suggested that this biased distribution was due to intron insertion at AGmid R:G proto-splice sites. However, we found that there is no disproportional excess of AGmid R:G that would support insertion at proto-splice sites. In fact, all nGmid R:G sites are enriched in the vicinity of the cleavage site. Additional analyses support an alternative scenario in which exon-shuffling is largely responsible for such excess of phase 1 introns.     

Selection strategies and artificial evolution

Summary Artificial selection results in biolgical changes, creating artificial evolution. When using selection indexes, the artificial evolution depends on the relative economic (or other) weight of traits in the breeding objective, and on the phenotypic and genetic variances and covariances among these traits and the traits recorded in the selection index. As shown here, the selection strategy (in this case, individual selection versus progeny test selection) can also have marked effects on the kind of artificial evolution produced. Thus, where economic weights are uncertain, choice between alternative selection strategies might take into account the different types of animal or plant resulting.     

Simulated evolution and artificial selection

A highly simplified evolving system was investigated by computer simulation. The genetic complement of each simulated organism in the population was represented by a single chromosome that consisted of a string of symbols. Individual fitness was measured as the number of symbols that corresponded to a specified rule. Reproduction was simulated with a non-breeding algorithm and two variants of a breeding algorithm, and was subject to random point mutations. In each generation, selection was effected by replacing the less fit members of the population with offspring of the more fit. The size of the population and the fraction replaced, though under experimental control, were constant for each simulation run. It was found that even such a simplified system is able to mimic a variety of properties observed in natural systems. In addition, the effect of the simulation parameters on the course of fitness increase provides a basis for using a genetic algorithm as an optimization technique.     

Apoptosis-inducing antifungal peptides and proteins

Despite the availability of various classes of antimycotics, the treatment of patients with systemic fungal infections is challenging. Therefore the development of new antifungals is urgently required. Promising new antifungal candidates are antimicrobial peptides. In the present review, we provide an overview of antifungal peptides isolated from plants, insects, amphibians and mammals that induce apoptosis. Their antifungal spectrum, mode of action and toxicity are discussed in more detail.     

Plant-derived antifungal proteins and peptides

Plants produce potent constitutive and induced antifungal compounds to complement the structural barriers to microbial infection. Approximately 250,000-500,000 plant species exist, but only a few of these have been investigated for antimicrobial activity. Nevertheless, a wide spectrum of compound classes have been purified and found to have antifungal properties. The commercial potential of effective plant-produced antifungal compounds remains largely unexplored. This review article presents examples of these compounds and discusses their properties.     

Mass spectrometry of peptides and proteins

This tutorial article introduces mass spectrometry (MS) for peptide fragmentation and protein identification. The current approaches being used for protein identification include top-down and bottom-up sequencing. Top-down sequencing, a relatively new approach that involves fragmenting intact proteins directly, is briefly introduced. Bottom-up sequencing, a traditional approach that fragments peptides in the gas phase after protein digestion, is discussed in more detail. The most widely used ion activation and dissociation process, gas-phase collision-activated dissociation (CAD), is discussed from a practical point of view. Infrared multiphoton dissociation (IRMPD) and electron capture dissociation (ECD) are introduced as two alternative dissociation methods. For spectral interpretation, the common fragment ion types in peptide fragmentation and their structures are introduced; the influence of instrumental methods on the fragmentation pathways and final spectra are discussed. A discussion is also provided on the complications in sample preparation for MS analysis. The final section of this article provides a brief review of recent research efforts on different algorithmic approaches being developed to improve protein identification searches.     

NMR spectroscopy of peptides and proteins

High resolution nuclear magnetic resonance (NMR) spectroscopy is the only method available for determining the three-dimensional structures of peptides and proteins in solution at atomic resolution. This article deals with a range of practical considerations associated with such studies, including sample preparation, instrumental setup, one- and two-dimensional NMR methods, interpretation of spectral data, and structure calculations.     

Gas-phase hydrolysis of proteins and peptides

A simplified gas-phase hydrolysis procedure for proteins and peptides is described. The apparatus consists of a glass vacuum desiccator, a ceramic plate, and a Teflon ring. The method was shown to give reproducible compositions for hydrolysis of human serum albumin and microanalysis of α-melanocyte stimulating hormone including the quantitation of as little as one residue of tryptophan. It minimizes sample handling and allows for the simultaneous hydrolysis of a large number of samples.     

More than the sum of their parts: on the evolution of proteins from peptides

Despite their seemingly endless diversity, proteins adopt a limited number of structural forms. It has been estimated that 80% of proteins will be found to adopt one of only about 400 folds, most of which are already known. These folds are largely formed by a limited 'vocabulary' of recurring supersecondary structure elements, often by repetition of the same element and, increasingly, elements similar in both structure and sequence are discovered. This suggests that modern proteins evolved by fusion and recombination from a more ancient peptide world and that many of the core folds observed today may contain homologous building blocks. The peptides forming these building blocks would not in themselves have had the ability to fold, but would have emerged as cofactors supporting RNA-based replication and catalysis (the 'RNA world'). Their association into larger structures and eventual fusion into polypeptide chains would have allowed them to become independent of their RNA scaffold, leading to the evolution of a novel type of macromolecule: the folded protein.