A database and tools for 3-D protein structure comparison and alignment using the Combinatorial Extension (CE) algorithm

The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure–structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure–structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.

NOMAD: a versatile strategy for in vitro DNA manipulation applied to promoter analysis and vector design.

Molecular analysis of complex modular structures, such as promoter regions or multi-domain proteins, often requires the creation of families of experimental DNA constructs having altered composition, order, or spacing of individual modules. Generally, creation of every individual construct of such a family uses a specific combination of restriction sites. However, convenient sites are not always available and the alternatives, such as chemical resynthesis of the experimental constructs or engineering of different restriction sites onto the ends of DNA fragments, are costly and time consuming. A general cloning strategy (nucleic acid ordered assembly with directionality, NOMAD; WWW resource locator http:@Lmb1.bios.uic.edu/NOMAD/NOMAD.htm l) is proposed that overcomes these limitations. Use of NOMAD ensures that the production of experimental constructs is no longer the rate-limiting step in applications that require combinatorial rearrangement of DNA fragments. NOMAD manipulates DNA fragments in the form of "modules" having a standardized cohesive end structure. Specially designed "assembly vectors" allow for sequential and directional insertion of any number of modules in an arbitrary predetermined order, using the ability of type IIS restriction enzymes to cut DNA outside of their recognition sequences. Studies of regulatory regions in DNA, such as promoters, replication origins, and RNA processing signals, construction of chimeric proteins, and creation of new cloning vehicles, are among the applications that will benefit from using NOMAD.

Mutational analysis of NM23-H2/NDP kinase identifies the structural domains critical to recognition of a c-myc regulatory element.

NM23-H2, a presumed regulator of tumor metastasis in humans, is a hexameric protein with both enzymatic (NDP kinase) and regulatory (transcriptional activation) activity. While the structure and catalytic mechanisms have been well characterized, the mode of DNA binding is not known. We examined this latter function in a site-directed mutational study and identified residues and domains essential for the recognition of a c-myc regulatory sequence. Three amino acids, Arg-34, Asn-69, and Lys-135, were found among 30 possibilities to be critical for DNA binding. Two of these, Asn-69 and Lys-135, are not conserved between NM23 variants differing in DNA-binding potential, suggesting that DNA recognition resides partly in nonconserved amino acids. All three DNA-binding defective mutant proteins are active enzymatically and appear to be stable hexamers, suggesting that they perform at the level of DNA recognition and that separate functional domains exist for enzyme catalysis and DNA binding. In the context of the known crystal structure of NM23-H2, the DNA-binding residues are located within distinct structural motifs in the monomer, which are exposed to the surface near the 2-fold axis of adjacent subunits in the hexamer. These findings are explained by a model in which NM23-H2 binds DNA with a combinatorial surface consisting of the "outer" face of the dimer. Chemical crosslinking data support a dimeric DNA-binding mode by NM23-H2.

Identification of a hexapeptide inhibitor of the human immunodeficiency virus integrase protein by using a combinatorial chemical library.

Integration of human immunodeficiency virus (HIV) DNA into the human genome requires the virus-encoded integrase (IN) protein, and therefore the IN protein is a suitable target for antiviral strategies. To find a potent HIV IN inhibitor, we screened a "synthetic peptide combinatorial library." We identified a hexapeptide with the sequence HCKFWW that inhibits IN-mediated 3'-processing and integration with an IC50 of 2 microM. The peptide is active on IN proteins from other retroviruses such as HIV-2, feline immunodeficiency virus, and Moloney murine leukemia virus, supporting the notion that a conserved region of IN is targeted. The hexapeptide was also tested in the disintegration reaction. This phosphoryl-transfer reaction can be carried out by the catalytic core of IN alone, and the peptide HCKFWW was found to inhibit this reaction, suggesting that the hexapeptide acts at or near the catalytic site of IN. Identification of an IN hexapeptide inhibitor provides proof of concept for the approach, and, moreover, this peptide may be useful for structure-function analysis of IN.

Analysis of RNA-binding proteins by in vitro genetic selection: identification of an amino acid residue important for locking U1A onto its RNA target.

An in vitro genetic system was developed as a rapid means for studying the specificity determinants of RNA-binding proteins. This system was used to investigate the origin of the RNA-binding specificity of the mammalian spliceosomal protein U1A. The U1A domain responsible for binding to U1 small nuclear RNA was locally mutagenized and displayed as a combinatorial library on filamentous bacteriophage. Affinity selection identified four U1A residues in the mutagenized region that are important for specific binding to U1 hairpin II. One of these residues (Leu-49) disproportionately affects the rates of binding and release and appears to play a critical role in locking the protein onto the RNA. Interestingly, a protein variant that binds more tightly than U1A emerged during the selection, showing that the affinity of U1A for U1 RNA has not been optimized during evolution.

Sample size determination in combinatorial chemistry.

Combinatorial chemistry is gaining wide appeal as a technique for generating molecular diversity. Among the many combinatorial protocols, the split/recombine method is quite popular and particularly efficient at generating large libraries of compounds. In this process, polymer beads are equally divided into a series of pools and each pool is treated with a unique fragment; then the beads are recombined, mixed to uniformity, and redivided equally into a new series of pools for the subsequent couplings. The deviation from the ideal equimolar distribution of the final products is assessed by a special overall relative error, which is shown to be related to the Pearson statistic. Although the split/recombine sampling scheme is quite different from those used in analysis of categorical data, the Pearson statistic is shown to still follow a chi2 distribution. This result allows us to derive the required number of beads such that, with 99% confidence, the overall relative error is controlled to be less than a pregiven tolerable limit L1. In this paper, we also discuss another criterion, which determines the required number of beads so that, with 99% confidence, all individual relative errors are controlled to be less than a pregiven tolerable limit L2 (0 < L2 < 1).

Quantitative analysis and characterization of biofunctionalized fluorescent silica particles

A strategy for the production and subsequent characterization of biofunctionalized silica particles is presented. The particles were engineered to produce a bifunctional material capable of both (a) the attachment of fluorescent dyes for particle encoding and (b) the sequential modification of the surface of the particles to couple oligonucleotide probes. A combination of microscopic and analytical methods is implemented to demonstrate that modification of the particles with 3-aminopropyl trimethoxysilane results in an even distribution of amine groups across the particle surface. Evidence is provided to indicate that there are negligible interactions between the bound fluorescent dyes and the attached biomolecules. A unique approach was adopted to provide direct quantification of the oligonucleotide probe loading on the particle surface through X-ray photoelectron spectroscopy, a technique which may have a major impact for current researchers and users of bead-based technologies. A simple hybridization assay showing high sequence specificity is included to demonstrate the applicability of these particles to DNA screening.

Discovery of active proteins directly from combinatorial randomized protein libraries without display, purification or sequencing:identification of novel zinc finger proteins.

We have successfully linked protein library screening directly with the identification of active proteins, without the need for individual purification, display technologies or physical linkage between the protein and its encoding sequence. By using 'MAX' randomization we have rapidly constructed 60 overlapping gene libraries that encode zinc finger proteins, randomized variously at the three principal DNA-contacting residues. Expression and screening of the libraries against five possible target DNA sequences generated data points covering a potential 40,000 individual interactions. Comparative analysis of the resulting data enabled direct identification of active proteins. Accuracy of this library analysis methodology was confirmed by both in vitro and in vivo analyses of identified proteins to yield novel zinc finger proteins that bind to their target sequences with high affinity, as indicated by low nanomolar apparent dissociation constants.

Increased diversity of libraries from libraries: chemoinformatic analysis of bis-diazacyclic libraries

Combinatorial libraries continue to play a key role in drug discovery. To increase structural diversity, several experimental methods have been developed. However, limited efforts have been performed so far to quantify the diversity of the broadly used diversity-oriented synthetic (DOS) libraries. Herein we report a comprehensive characterization of 15 bis-diazacyclic combinatorial libraries obtained through libraries from libraries, which is a DOS approach. Using MACCS keys, radial and different pharmacophoric fingerprints as well as six molecular properties, it was demonstrated the increased structural and property diversity of the libraries from libraries over the individual libraries. Comparison of the libraries to existing drugs, NCI Diversity and the Molecular Libraries Small Molecule Repository revealed the structural uniqueness of the combinatorial libraries (mean similarity < 0.5 for any fingerprint representation). In particular, bis-cyclic thiourea libraries were the most structurally dissimilar to drugs retaining drug-like character in property space. This study represents the first comprehensive quantification of the diversity of libraries from libraries providing a solid quantitative approach to compare and contrast the diversity of DOS libraries with existing drugs or any other compound collection.

Analysis of key predistribution schemes in wireless sensor networks

Combinatorial designs are used for designing key predistribution schemes that are applied to wireless sensor networks in communications. This helps in building a secure channel. Private-key cryptography helps to determine a common key between a pair of nodes in sensor networks. Wireless sensor networks using key predistribution schemes have many useful applications in military and civil operations. When designs are efficiently implemented on sensor networks, blocks with unique keys will be the result. One such implementation is a transversal design which follows the principle of simple key establishment. Analysis of designs and modeling the key schemes are the subjects of this project.

Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.

GRASP and statistical bounds for heuristic solutions to combinatorial problems

The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few metaheuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial optimization remains an open question. This work complements the existing literature on statistical bounds by testing them on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds has previously been found reliable when obtained from the Genetic algorithm whereas in this work they found less reliable. Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently unknown.

Climbing Combinatorial Fitness Landscapes

International audience

Tools For Spatiotemporally Specific Proteomic Analysis In Multicellular Organisms

The emergence of mass spectrometry-based proteomics has revolutionized the study of proteins and their abundances, functions, interactions, and modifications. However, in a multicellular organism, it is difficult to monitor dynamic changes in protein synthesis in a specific cell type within its native environment. In this thesis, we describe methods that enable the metabolic labeling, purification, and analysis of proteins in specific cell types and during defined periods in live animals. We first engineered a eukaryotic phenylalanyl-tRNA synthetase (PheRS) to selectively recognize the unnatural L-phenylalanine analog p-azido-L-phenylalanine (Azf). Using Caenorhabditis elegans, we expressed the engineered PheRS in a cell type of choice (i.e. body wall muscles, intestinal epithelial cells, neurons, pharyngeal muscles), permitting proteins in those cells -- and only those cells -- to be labeled with azides. Labeled proteins are therefore subject to "click" conjugation to cyclooctyne-functionalized affnity probes, separation from the rest of the protein pool and identification by mass spectrometry. By coupling our methodology with heavy isotopic labeling, we successfully identified proteins -- including proteins with previously unknown expression patterns -- expressed in targeted subsets of cells. While cell types like body wall or pharyngeal muscles can be targeted with a single promoter, many cells cannot; spatiotemporal selectivity typically results from the combinatorial action of multiple regulators. To enhance spatiotemporal selectivity, we next developed a two-component system to drive overlapping -- but not identical -- patterns of expression of engineered PheRS, restricting labeling to cells that express both elements. Specifically, we developed a split-intein-based split-PheRS system for highly efficient PheRS-reconstitution through protein splicing. Together, these tools represent a powerful approach for unbiased discovery of proteins uniquely expressed in a subset of cells at specific developmental stages.

Raman microscopy of formamide-intercalated kaolinites treated by controlled-rate thermal analysis technology

Raman spectroscopy of formamide-intercalated kaolinites treated using controlled-rate thermal analysis technology (CRTA), allowing the separation of adsorbed formamide from intercalated formamide in formamide-intercalated kaolinites, is reported. The Raman spectra of the CRTA-treated formamide-intercalated kaolinites are significantly different from those of the intercalated kaolinites, which display a combination of both intercalated and adsorbed formamide. An intense band is observed at 3629 cm-1, attributed to the inner surface hydroxyls hydrogen bonded to the formamide. Broad bands are observed at 3600 and 3639 cm-1, assigned to the inner surface hydroxyls, which are hydrogen bonded to the adsorbed water molecules. The hydroxyl-stretching band of the inner hydroxyl is observed at 3621 cm-1 in the Raman spectra of the CRTA-treated formamide-intercalated kaolinites. The results of thermal analysis show that the amount of intercalated formamide between the kaolinite layers is independent of the presence of water. Significant differences are observed in the CO stretching region between the adsorbed and intercalated formamide.