Functional genomics of intracellular peptide recognition domains with combinatorial biology methods

Understanding binding affinity and specificity of modular protein domains: A focus in ligand design for the polyproline-binding families

Within the modular protein domains there are five families that recognize proline-rich sequences: SH3, WW, EVH1, GYF and UEV domains. This chapter reviews the main strategies developed for the design of ligands for these families, including peptides, peptidomimetics and drugs. We also describe some studies aimed to understand the molecular reasons responsible for the intrinsic affinity and specificity of these domains.

Advances in Protein-Based Materials: From Origin to Novel Biomaterials

Biomaterials play a very important role in biomedicine and tissue engineering where they directly affect the cellular activities and their microenvironment . Myriad of techniques have been employed to fabricate a vast number natural, artificial and recombinant polymer s in order to harness these biomaterials in tissue regene ration , drug delivery and various other applications. Despite of tremendous efforts made in this field during last few decades, advanced and new generation biomaterials are still lacking. Protein based biomaterials have emerged as an attractive alternatives due to their intrinsic properties like cell to cell interaction , structural support and cellular communications. Several protein based biomaterials like, collagen , keratin , elastin , silk protein and more recently recombinant protein s are being utilized in a number of biomedical and biotechnological processes. These protein-based biomaterials have enormous capabilities, which can completely revolutionize the biomaterial world. In this review, we address an up-to date review on the novel, protein-based biomaterials used for biomedical field including tissue engineering, medical science, regenerative medicine as well as drug delivery. Further, we have also emphasized the novel fabrication techniques associated with protein-based materials and implication of these biomaterials in the domain of biomedical engineering .

Optimization of the process of inverted peptides (PIPEPLUS) to screen PDZ domain ligands

PDZ domains play crucial roles in cell signaling processes and are therefore attractive targets for the development of therapeutic inhibitors. In many cases, C-terminal peptides are the physiological binding partners of PDZ domains. To identify both native ligands and potential inhibitors we have screened arrays synthesized by the process of inverted peptides (PIPE), a variant of SPOT synthesis that generates peptides with free C-termini. Here, we present the development of a new functionalized cellulose membrane as solid support along with the optimized PIPEPLUS technology. Improved resolution and accuracy of the synthesis were shown with peptide arrays containing both natural and non-natural amino acids. These new screening possibilities will advance the development of active, selective and metabolically stable PDZ interactors.

Learning from nature - novel synthetic biology approaches for biomaterial design

Many biomaterials constructed today are complex chemical structures that incorporate biologically active components derived from nature, but the field can still be said to be in its infancy. The need for materials that bring sophisticated properties of structure, dynamics and function to medical and non-medical applications will only grow. Increasing appreciation of the functionality of biological systems has caused biomaterials researchers to consider nature for design inspiration, and many examples exist of the use of biomolecular motifs. Yet evolution, nature's only engine for the creation of new designs, has been largely ignored by the biomaterials community. Molecular evolution is an emerging tool that enables one to apply nature's engineering principles to non-natural situations using variation and selection. The purpose of this review is to highlight the most recent advances in the use of molecular evolution in synthetic biology applications for biomaterial engineering, and to discuss some of the areas in which this approach may be successfully applied in the future.

Designing ECM-mimetic materials using protein engineering

The natural extracellular matrix (ECM), with its multitude of evolved cell-instructive and cell-responsive properties, provides inspiration and guidelines for the design of engineered biomaterials. One strategy to create ECM-mimetic materials is the modular design of protein-based engineered ECM (eECM) scaffolds. This modular design strategy involves combining multiple protein domains with different functionalities into a single, modular polymer sequence, resulting in a multifunctional matrix with independent tunability of the individual domain functions. These eECMs often enable decoupled control over multiple material properties for fundamental studies of cell-matrix interactions. In addition, since the eECMs are frequently composed entirely of bioresorbable amino acids, these matrices have immense clinical potential for a variety of regenerative medicine applications. This brief review demonstrates how fundamental knowledge gained from structure-function studies of native proteins can be exploited in the design of novel protein-engineered biomaterials. While the field of protein-engineered biomaterials has existed for over 20years, the community is only now beginning to fully explore the diversity of functional peptide modules that can be incorporated into these materials. We have chosen to highlight recent examples that either (i) demonstrate exemplary use as matrices with cell-instructive and cell-responsive properties or (ii) demonstrate outstanding creativity in terms of novel molecular-level design and macro-level functionality.

Peptide array X-linking (PAX): a new peptide-protein identification approach

Many protein interaction domains bind short peptides based on canonical sequence consensus motifs. Here we report the development of a peptide array-based proteomics tool to identify proteins directly interacting with ligand peptides from cell lysates. Array-formatted bait peptides containing an amino acid-derived cross-linker are photo-induced to crosslink with interacting proteins from lysates of interest. Indirect associations are removed by high stringency washes under denaturing conditions. Covalently trapped proteins are subsequently identified by LC-MS/MS and screened by cluster analysis and domain scanning. We apply this methodology to peptides with different proline-containing consensus sequences and show successful identifications from brain lysates of known and novel proteins containing polyproline motif-binding domains such as EH, EVH1, SH3, WW domains. These results suggest the capacity of arrayed peptide ligands to capture and subsequently identify proteins by mass spectrometry is relatively broad and robust. Additionally, the approach is rapid and applicable to cell or tissue fractions from any source, making the approach a flexible tool for initial protein-protein interaction discovery.

PDZ domains and their binding partners: structure, specificity, and modification

PDZ domains are abundant protein interaction modules that often recognize short amino acid motifs at the C-termini of target proteins. They regulate multiple biological processes such as transport, ion channel signaling, and other signal transduction systems. This review discusses the structural characterization of PDZ domains and the use of recently emerging technologies such as proteomic arrays and peptide libraries to study the binding properties of PDZ-mediated interactions. Regulatory mechanisms responsible for PDZ-mediated interactions, such as phosphorylation in the PDZ ligands or PDZ domains, are also discussed. A better understanding of PDZ protein-protein interaction networks and regulatory mechanisms will improve our knowledge of many cellular and biological processes.

A survey of yeast genomic assays for drug and target discovery

Over the past decade, the development and application of chemical genomic assays using the model organism Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of known drugs and novel small molecules in vivo. These assays identify drug target candidates, genes involved in buffering drug target pathways and also help to define the general cellular response to small molecules. In this review, we examine current yeast chemical genomic assays and summarize the potential applications of each approach.

Regulatory Binding Partners and Complexes of NHE3

NHE3 is the brush-border (BB) Na+/H+exchanger of small intestine, colon, and renal proximal tubule which is involved in large amounts of neutral Na+absorption. NHE3 is a highly regulated transporter, being both stimulated and inhibited by signaling that mimics the postprandial state. It also undergoes downregulation in diarrheal diseases as well as changes in renal disorders. For this regulation, NHE3 exists in large, multiprotein complexes in which it associates with at least nine other proteins. This review deals with short-term regulation of NHE3 and the identity and function of its recognized interacting partners and the multiprotein complexes in which NHE3 functions.

Computer-aided design of modular protein devices: Boolean AND gene activation

Many potentially useful synthetic gene networks require the expression of an engineered gene if and only if two different DNA-binding proteins exist in sufficient concentration. While some natural and engineered systems activate gene expression according to a logical AND-like behavior, they often utilize allosteric or cooperative protein-protein interactions, rendering their components unsuitable for a toolbox of modular parts for use in multiple applications. Here, we develop a quantitative model to demonstrate that a small system of interacting fusion proteins, called a protein device, can activate an engineered gene according to the Boolean AND behavior while using only modular protein domains and DNA sites. The fusion proteins are created from transactivating, DNA-binding, non-DNA binding, and protein-protein interaction domains along with the corresponding peptide ligands. Using a combined kinetic and thermodynamic model, we identify the characteristics of the molecular components and their rates of constitutive production that maximize the fidelity of AND behavior. These AND protein devices facilitate the creation of complex genetic programs and may be used to create gene therapies, biosensors and other biomedical and biotechnological applications that turn on gene expression only when multiple DNA-binding proteins are simultaneously present.

Structure-based Prediction of bZIP Partnering Specificity

Predicting protein interaction specificity from sequence is an important goal in computational biology. We present a model for predicting the interaction preferences of coiled-coil peptides derived from bZIP transcription factors that performs very well when tested against experimental protein microarray data. We used only sequence information to build atomic-resolution structures for 1711 dimeric complexes, and evaluated these with a variety of functions based on physics, learned empirical weights or experimental coupling energies. A purely physical model, similar to those used for protein design studies, gave reasonable performance. The results were improved significantly when helix propensities were used in place of a structurally explicit model to represent the unfolded reference state. Further improvement resulted upon accounting for residue-residue interactions in competing states in a generic way. Purely physical structure-based methods had difficulty capturing core interactions accurately, especially those involving polar residues such as asparagine. When these terms were replaced with weights from a machine-learning approach, the resulting model was able to correctly order the stabilities of over 6000 pairs of complexes with greater than 90% accuracy. The final model is physically interpretable, and suggests specific pairs of residues that are important for bZIP interaction specificity. Our results illustrate the power and potential of structural modeling as a method for predicting protein interactions and highlight obstacles that must be overcome to reach quantitative accuracy using a de novo approach. Our method shows unprecedented performance in predicting protein-protein interaction specificity accurately using structural modeling and suggests that predicting coiled-coil interactions generally may be within reach.

Discovery of antagonist peptides against bacterial helicase-primase interaction in B. stearothermophilus by reverse yeast three-hybrid

Developing small-molecule antagonists against protein-protein interactions will provide powerful tools for mechanistic/functional studies and the discovery of new antibacterials. We have developed a reverse yeast three-hybrid approach that allows high-throughput screening for antagonist peptides against essential protein-protein interactions. We have applied our methodology to the essential bacterial helicase-primase interaction in Bacillus stearothermophilus and isolated a unique antagonist peptide. This peptide binds to the primase, thus excluding the helicase and inhibiting an essential interaction in bacterial DNA replication. We provide proof of principle that our reverse yeast three-hybrid method is a powerful "one-step" screen tool for direct high-throughput antagonist peptide selection against any protein-protein interaction detectable by traditional yeast two-hybrid systems. Such peptides will provide useful "leads" for the development of new antibacterials.

Bioinformatics in microbial biotechnology--a mini review

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics--sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics--identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Binding mode and transcriptional activation potential of high affinity ligands for the CBP KIX domain

We recently described a pair of ligands, PPKID4(P) (4(P)) and PPKID6(U) (6(U)), which present the alpha-helical functional epitope found on helix B of the CREB KID activation domain (KID(P)) on a pancreatic fold protein scaffold. 4(P) and 6(U) bind the natural target of KID(P), the KIX domain of the coactivator CBP, with equilibrium dissociation constants between 515 nM and 1.5 microM and compete effectively with KID(P) for binding to CBP KIX (KIX). Here we present a detailed investigation of the binding mode, orientation, and transcriptional activation potential of 4(P) and 6(U). Equilibrium binding experiments using a panel of well-characterized KIX variants support a model in which 4(P) binds KIX in a manner that closely resembles that of KID(P) but 6(U) binds an overlapping, yet distinct region of the protein. Equilibrium binding experiments using a judiciously chosen panel of 4(P) variants containing alanine or sarcosine substitutions along the putative alpha- or PPII helix of 4(P) support a model in which 4(P) folds into a pancreatic fold structure upon binding to KIX. Transcriptional activation assays performed in HEK293 cells using GAL4 DNA-binding domain fusion proteins indicate that 4(P) functions as a potent activator of p300/CBP-dependent transcription. Notably, 6(U) is a less potent transcriptional activator in this context than 4(P)despite the similarity of their affinities for CBP KIX. This final result suggests that thermodynamic affinity is an important, although not exclusive, criterion controlling the level of KIX-dependent transcriptional activation.

PROTEOMICS

The genome sequences of important model systems are available and the focus is now shifting to large-scale experiments enabled by this data. Following in the footsteps of genomics, we have functional genomics, proteomics, and even metabolomics, roughly paralleling the biological hierarchy of the transcription, translation, and production of small molecules. Proteomics is initially concerned with determining the structure, expression, localization, biochemical activity, interactions, and cellular roles of as many proteins as possible. There has been great progress owing to novel instrumentation, experimental strategies, and bioinformatics methods. The area of protein-protein interactions has been especially fruitful. First pass interaction maps of some model organisms exist, and the proteins in many important organelles are about to be determined. Researchers are also beginning to integrate large-scale data sets from various "omics" disciplines in targeted investigations of specific biomedical areas and in pursuit of a general framework for systems biology.

A novel emulsion mixture for in vitro compartmentalization of transcription and translation in the rabbit reticulocyte system

Emulsion formulations used for in vitro compartmentalization (IVC) methods were found to be incompatible with protein expression in the rabbit reticulocyte (RRL) system, causing rapid discoloration and translation shutdown. Here we identify possible causes and describe a novel water-in-oil emulsion which abolished discoloration and allowed high-level in-emulsion expression of active luciferase and human telomerase using the RRL. This novel emulsion greatly expands the range of potential protein targets for IVC.