Combinatorial Selection Research Articles

Target Self-Enhanced Selectivity in Metal-Specific DNAzymes.

Highly selective recognition of metal ions by rational ligand design is challenging, and simple metal binding by biological ligands is often obscured by nonspecific interactions. In this work, binding-triggered catalysis is used and metal selectivity is greatly increased by increasing the number of metal ions involved, as exemplified in a series of in vitro selected RNA-cleaving DNAzymes. The cleavage junction is modified with a glycyl-histidine-functionalized tertiary amine moiety to provide multiple potential metal coordination sites. DNAzymes that bind 1, 2, and 3 Zn2+ ions, increased their selectivity for Zn2+ over Co2+ ions from approximately 20-, 1000-, to 5000-fold, respectively. This study offers important insights into metal recognition by combining rational ligand design and combinatorial selection, and it provides a set of new DNAzymes with excellent selectivity for Zn2+ ions.

Combinatorial Avidity Selection of Mosaic Landscape Phages Targeted at Breast Cancer Cells—An Alternative Mechanism of Directed Molecular Evolution

Low performance of actively targeted nanomedicines required revision of the traditional drug targeting paradigm and stimulated the development of novel phage-programmed, self-navigating drug delivery vehicles. In the proposed smart vehicles, targeting peptides, selected from phage libraries using traditional principles of affinity selection, are substituted for phage proteins discovered through combinatorial avidity selection. Here, we substantiate the potential of combinatorial avidity selection using landscape phage in the discovery of Short Linear Motifs (SLiMs) and their partner domains. We proved an algorithm for analysis of phage populations evolved through multistage screening of landscape phage libraries against the MDA-MB-231 breast cancer cell line. The suggested combinatorial avidity selection model proposes a multistage accumulation of Elementary Binding Units (EBU), or Core Motifs (CorMs), in landscape phage fusion peptides, serving as evolutionary initiators for formation of SLiMs. Combinatorial selection has the potential to harness directed molecular evolution to create novel smart materials with diverse novel, emergent properties.

Systematic design of high-strength multicomponent metamaterials

The emergence of additive manufacturing, along with the introduction of the concept of metamaterials, allows the synthesis of high-performance materials with superior specific strength. With recent advances in printing multi-material structures, the design space of metamaterials has exponentially grown. Variation in dimensions of the printed metamaterials due to limitations of the manufacturing process can drastically offset their performance compared to their original design. So far, the impact of deviations in the manufactured metamaterials and their effect on their final performance has not been studied systematically. There are also no guidelines for selecting materials in a multi-material lattice structure to achieve higher mechanical performance. Here, the strength and toughness of printed single- and bimaterial lattice structures with a combinatorial selection of materials and their sensitivity to the printing parameters are studied. We show that the exterior elements dominate the overall mechanical performance of the metamaterial compared to the internal elements. We found two regimes of slow and fast softening in periodic lattices. We study the sensitivity of the mechanical performance of the printed metamaterial to variations in the thickness of internal and exterior elements in detail.

High-Throughput Platform for B-Cell Screening Based on Fluorescent Phage-Display Technology.

A system for detection of malignantly transformed cells, including follicular lymphoma Bcells, was developed and experimentally validated. The system is based on the use of bacteriophages carrying exposed ligands for pathogenic B-cell receptors. The efficiency of binding to target cells is several times higher than in systems with chemically synthesized biotinylated peptides. The new method is proposed as a noninvasive diagnostic test for mapping B-cell lymphoma and for determining the specificity of B-cell receptors and high-throughput combinatorial selection of various repertories of B cells.

Emergence of Compartments Formed from Unconventional Surfactants in Dynamic Combinatorial Libraries.

Assembly processes can drive the selection of self-assembling molecules in dynamic combinatorial libraries, yielding self-synthesizing materials. We now show how such selection in a dynamic combinatorial library made from an amphiphilic building block which, by itself, assembles into micelles, can yield membranous aggregates ranging from vesicles to sponge phases. These aggregates are made from a mixture of unconventional surfactant molecules, showing the power of dynamic combinatorial selection approaches for the discovery of new, not readily predictable, self-assembly motifs.

The Symmetric Tetravalent Sulfhydryl-Specific Linker NATBA Facilitates a Combinatorial "Tool Kit" Strategy for Phage Display-Based Selection of Functionalized Bicyclic Peptides.

The rigid conformation of constrained bicyclic peptides provides a number of advantages over larger protein-based ligands, including better chemical stability, enhanced tissue penetration, and a wider field of possible applications. Selective chemical modification strategies are able to extend the scope of applications not only in a therapeutic manner but also for the development of novel tools for protein capturing, bioimaging, and targeted drug delivery. Herein, we report the synthesis of an adamantane-based, symmetrical, tetravalent, sulfhydryl-specific peptide linker. We have developed an in vitro two-step modification strategy that allows the generation of differently functionalized bicyclic peptides. This “tool kit” strategy was applied to cyclize and functionalize a phage-encoded peptide library bearing the sequence CX6CX6C. After phage display against a model target, isolated peptides show strong consensus sequences, indicating target-specific binding. The newly developed symmetric tetravalent linker opens new avenues for the combinatorial selection and functionalization of bicyclic peptide ligands with affinity to virtually any target.

Breathprinting and Early Diagnosis of Lung Cancer.

The electronic nose (e-nose) is a promising technology as a useful addition to the currently available modalities to achieve lung cancer diagnosis. The e-nose can assess the volatile organic compounds detected in the breath and derived from the cellular metabolism. Volatile organic compounds can be analyzed to identify the individual chemical elements as well as their pattern of expression to reproduce a sensorial combination similar to a fingerprint (breathprint). The e-nose can be used alone, mimicking the combinatorial selectivity of the human olfactory system, or as part of a multisensorial platform. This review analyzes the progress made by investigators interested in this technology as well as the perspectives for its future utilization.

Versatile exclusion-based sample preparation platform for integrated rare cell isolation and analyte extraction.

Rare cell populations provide a patient-centric tool to monitor disease treatment, response, and resistance. However, understanding rare cells is a complex problem, which requires cell isolation/purification and downstream molecular interrogation - processes challenged by non-target populations, which vary patient-to-patient and change with disease. As such, cell isolation platforms must be amenable to a range of sample types while maintaining high efficiency and purity. The multiplexed technology for automated extraction (mTAE) is a versatile magnetic bead-based isolation platform that facilitates positive, negative, and combinatorial selection with integrated protein staining and nucleic acid isolation. mTAE is validated by isolating circulating tumor cells (CTCs) - a model rare cell population - from breast and prostate cancer patient samples. Negative selection yielded high efficiency capture of CTCs while positive selection yielded higher purity with an average of only 95 contaminant cells captured per milliliter of processed whole blood. With combinatorial selection, an overall increase in capture efficiency was observed, highlighting the potential significance of integrating multiple capture approaches on a single platform. Following capture (and staining), on platform nucleic acid extraction enabled the detection of androgen receptor-related transcripts from CTCs isolated from prostate cancer patients. The flexibility (e.g. negative, positive, combinatorial selection) and capabilities (e.g. isolation, protein staining, and nucleic acid extraction) of mTAE enable users to freely interrogate specific cell populations, a capability required to understand the potential of emerging rare cell populations and readily adapt to the heterogeneity presented across clinical samples.

Abstract B43: Validation of a network-based strategy for the optimization of combinatorial target selection in breast cancer therapy

Abstract Network-based strategies provided by systems biology are attractive tools for cancer therapy. Modulation of cancer networks by anticancer drugs may alter the response of malignant cells and/or drive network reorganization into the inhibition of cancer progression. Previously, using systems biology approach and cancer signaling networks, we identified the top 5 highly expressed and connected proteins (HSP90AB1, CSNK2B, TK1, YWHAB, and VIM) in the invasive MDA-MB-231 breast cancer cell line. Here, we have knocked down the expression of these proteins, individually or together using siRNAs. The transfected cell lines were assessed for in vitro cell growth, colony formation, migration, and invasion relative to control transfected MDA-MB-231, the noninvasive MCF-7 breast carcinoma cell line, and the nontumoral mammary epithelial cell line MCF-10A. The knockdown of the top-5 upregulated connectivity hubs successfully inhibited the in vitro proliferation, colony formation, anchorage independence, migration, and invasion in MDA-MB-231 cells, with minimal effects in the control transfected MDA-MB-231 cells or MCF-7 and MCF-10A cells. The in vitro validation of bioinformatics predictions regarding optimized multitarget selection for therapy suggests that protein expression levels together with protein-protein interaction network analysis may provide an optimized combinatorial target selection for a highly effective antimetastatic precision therapy in triple-negative breast cancer. This approach increases the ability to identify not only druggable hubs as essential targets for cancer survival, but also interactions most susceptible to synergistic drug action. The data provided in this report constitute a preliminary step toward the personalized clinical application of our strategy to optimize the therapeutic use of anticancer drugs. Citation Format: Tatiana Martins Tilli, Nicolas Carels, Jack Adam Tuszynski, Manijeh Pasdar. Validation of a network-based strategy for the optimization of combinatorial target selection in breast cancer therapy [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr B43.

Trust Based Quality Awareness Using Combinatorial Auction Web Service Selection In Service Based Systems

With the immense growth and development of the computing exemplar in service-based systems (SBS), the establishment of the engineering architectures has taken new standards. The computation of trust parameter has become vital and essential to measure the quality of services in such service-based systems. This becomes critical and challenging to the success of multi-tier cloud services. Various approaches have been put forth using the quality aware selection mechanisms, but reliability is a major issue in such systems. In order to establish a more reliable service-based systems, the concept of trust awareness is proposed in the present research work and trust-based quality aware selection using combinatorial auction for service oriented systems is presented. Simulation analysis show that the trust-based quality aware service selection scheme provide better accuracy, high success rate, less cost and reduced overhead than the normal combinatorial auction service selection schemes.

Combinatorial selection of a two-dimensional 3d-TM-tetracyanoquinodimethane (TM-TCNQ) monolayer as a high-activity nanocatalyst for CO oxidation.

The CO oxidation reaction on single 3d-transition metal catalytic sites in experimentally realized tetracyanoquinodimethane (TM-TCNQ) monolayers (TM = Sc-Zn) is systematically investigated by means of first-principles calculations. Considering the stabilities, adsorption characteristics and thermodynamics of all the ten candidates (Sc-Zn), Sc-TCNQ is found to display the lowest activation energies and yield the highest catalytic activity for room temperature CO oxidation. Exploring the Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms, we find that the rate-limiting step of CO oxidation catalyzed by Sc-TCNQ (CO + O2* → OOCO*) can follow the LH mechanism with free energy barriers as low as 0.73 eV at 300 K. The second step of CO + O* → CO2 can occur with rather small energy barriers via either LH or ER mechanisms. The high activity of Sc-TCNQ can be attributed to its unique structural and electronic features by possessing high stability, optimum adsorption energies with adsorbates, and fast reaction kinetics. These results have significant implications for the synthesis of two-dimensional single atom catalysis for CO oxidation with low-cost and high activity at low temperature.

Feature reduction for classification of daily activities through kinematic data from smartphones

Abstract Linear acceleration and angular rotation data measured from a human body can provide insights on how a person moves. These kinematic data are typically analyzed and used to understand disease progression associated with movement disorders. Time and frequency domain features extracted from such data are often of large dimensions and not feasible for implementation on resource-constraint devices. In this paper, we propose two optimal feature selection schemes that can better characterize the kinematic measurements to distinguish the movements of a person. One of the proposed approach is based on principal component analysis and the other is based on combinatorial high frequency feature selection from multi-classification algorithms to reduce the features required to maintain high activity prediction rate. We apply three classification algorithms to differentiate the activities a subject was engaged in. Results show the features can be reduced from 561 to 15 with above 84% activity prediction accuracy.

Joint Hybrid Tx–Rx Design for Wireless Backhaul With Delay-Outage Constraint in Massive MIMO Systems

This paper studies joint design of mixed-timescale hybrid precoding and combining to maximize the effective capacity for wireless backhaul in massive multiple-input multiple-output (MIMO) systems. Specifically, radio frequency (RF) analog processing is adaptive to statistical channel state information (CSI) while digital baseband processing is updated with instantaneous effective CSI. Equipped with traditional MIMO solutions at the baseband, the issue of RF design for both unconstrained-modulus and constant-modulus elements is addressed. Under the jointly correlated channel model, the objective function does not have a closed-form expression. In the unconstrained case, we derive the optimal RF solution structures, which lead to a combinatorial eigenmode selection formulation. Such an NP-hard problem is solved to near-optimality by semi-definite relaxation. In view of the additional difficulty posed by the non-convex modulus constraint, we exploit the problem structure to construct the constant-modulus design from the unconstrained-modulus solution which is cast as a problem of joint matrix approximation and solved by low-complexity Jacobi-like algorithms. Numerical results show that under loose and stringent delay-outage constraints, the mixed-timescale hybrid designs deliver effective rates comparable with other perfect CSI-based state-of-the-art baselines.

Identification and characterization of preferred DNA-binding sites for the Thermus thermophilus transcriptional regulator FadR.

One of the primary transcriptional regulators of fatty acid homeostasis in many prokaryotes is the protein FadR. To better understand its biological function in the extreme thermophile Thermus thermophilus HB8, we sought to first determine its preferred DNA-binding sequences in vitro using the combinatorial selection method Restriction Endonuclease Protection, Selection, and Amplification (REPSA) and then use this information to bioinformatically identify potential regulated genes. REPSA determined a consensus FadR-binding sequence 5´-TTRNACYNRGTNYAA-3´, which was further characterized using quantitative electrophoretic mobility shift assays. With this information, a search of the T. thermophilus HB8 genome found multiple operons potentially regulated by FadR. Several of these were identified as encoding proteins involved in fatty acid biosynthesis and degradation; however, others were novel and not previously identified as targets of FadR. The role of FadR in regulating these genes was validated by physical and functional methods, as well as comparative genomic approaches to further characterize regulons in related organisms. Taken together, our study demonstrates that a systematic approach involving REPSA, biophysical characterization of protein-DNA binding, and bioinformatics can be used to postulate biological roles for potential transcriptional regulators.

Metal Sensing by DNA.

Metal ions are essential to many chemical, biological, and environmental processes. In the past two decades, many DNA-based metal sensors have emerged. While the main biological role of DNA is to store genetic information, its chemical structure is ideal for metal binding via both the phosphate backbone and nucleobases. DNA is highly stable, cost-effective, easy to modify, and amenable to combinatorial selection. Two main classes of functional DNA were developed for metal sensing: aptamers and DNAzymes. While a few metal binding aptamers are known, it is generally quite difficult to isolate such aptamers. On the other hand, DNAzymes are powerful tools for metal sensing since they are selected based on catalytic activity, thus bypassing the need for metal immobilization. In the last five years, a new surge of development has been made on isolating new metal-sensing DNA sequences. To date, many important metals can be selectively detected by DNA often down to the low parts-per-billion level. Herein, each metal ion and the known DNA sequences for its sensing are reviewed. We focus on the fundamental aspect of metal binding, emphasizing the distinct chemical property of each metal. Instead of reviewing each published sensor, a high-level summary of signaling methods is made as a separate section. In principle, each signaling strategy can be applied to many DNA sequences for designing sensors. Finally, a few specific applications are highlighted, and future research opportunities are discussed.

Combinatorial selection for replicable RNA by Qβ replicase while maintaining encoded gene function.

Construction of a complex artificial self-replication system is challenging in the field of in vitro synthetic biology. Recently, we developed a translation-coupled RNA replication system, wherein an artificial genomic RNA replicates with the Qβ RNA replicase gene encoded on itself. The challenge is to introduce additional genes into the RNA to develop a complex system that mimics natural living systems. However, most RNA sequence encoding genes are not replicable by the Qβ replicase owing to its requirement for strong secondary structures throughout the RNA sequence that are absent in most genes. In this study, we establish a new combinatorial selection method to find an RNA sequence with secondary structures and functional amino acid sequences of the encoded gene. We selected RNA sequences based on their in vitro replication and in vivo gene functions. First, we used the α-domain gene of β-galactosidase as a model-encoding gene, with functional selection based on blue-white screening. Through the combinatorial selection, we developed more replicable RNAs while maintaining the function of the encoded α-domain. The selected sequence improved the affinity between the minus strand RNA and Qβ replicase. Second, we established an in vivo selection method applicable to a broader range of genes by using an Escherichia coli strain with one of the essential genes complemented with a plasmid. We performed the combinatorial selection using an RNA encoding serS and obtained more replicable RNA encoding functional serS gene. These results suggest that combinatorial selection methods are useful for the development of RNA sequences replicable by Qβ replicase while maintaining the encoded gene function.

Combinatorial portfolio selection with the ELECTRE III method: case study of the stock exchange of Thailand

Various techniques of portfolio selection are applied to interpret the status of the market and predict the market's future trend, but they are not beneficial to small investors because these techniques should be administered by an expert. In addition, these techniques cannot help investors compare business on ambiguity multi-criteria and desire accumulation of data about the market. Therefore, portfolio selection with two significant financial ratios using the ELECTRE III method is proposed for small investors to make trading decisions. In order to demonstrate the effectiveness of this research, it is compared to the situation where a fix-percentage allocation existed and data was collected from the stock exchange of Thailand (SET). Empirical results show that portfolio selection with the ELECTRE III method offer significantly better ranking performance than the fix-percentage allocation method.

Combinatorial portfolio selection with the ELECTRE III method: case study of the stock exchange of Thailand

Combinatorial portfolio selection with the ELECTRE III method: case study of the stock exchange of Thailand

Neutrophil-Secreted Proteinase 3 Mediates Metastasis of Prostate Cancer Cells Expressing RAGE to the Bone Marrow

Human prostate cancer non-randomly metastasizes to the bone marrow, but the biological basis for such site-specific tropism remains largely unresolved. Differential expression of molecules in the bone marrow microenvironment "niche" has recently been proposed to play a role. In previous work, combinatorial selection of random peptide libraries in end-of-life cancer patients has revealed an unexpected interaction between the receptor for advanced glycation end products (RAGE), a molecule expressed on malignant cell surfaces in advanced prostate cancer, and proteinase 3 (PR3), a serine protease abundantly present on neutrophils and promyelocytes within the bone marrow microenvironment. Because RAGE is selectively overexpressed in prostate cancer bone metastases, we hypothesize here that its specific binding to PR3 might mediate homing of prostate cancer cells to the bone marrow. We demonstrate that PR3 non-proteolytically binds to RAGE on prostate cancer cell surfaces and thereby promotes tumor cell activation and motility. We also show that the downstream signal transduction cascade triggered by RAGE/PR3 binding involves p44/42 (Erk1/2) and JNK1 phosphorylation. Finally, we use a mouse model of experimental metastasis to demonstrate that RAGE protein expression on human prostate cancer cells promotes their homing to bone marrow within a short time frame. These results validate a functional protein interaction between RAGE and PR3 and uncover a mechanism through which neutrophils mediate prostate cancer cell metastasis to the skeleton. DisclosuresSergeeva:Astellas: Patents & Royalties. Molldrem:Astellas Pharma: Patents & Royalties.

Advancing Drug Formulation Additives toward Precision Additives with Release Mediating Peptide Interlayer.

Amphiphilic drug formulation additives based on palmitic acid-modified poly(ethylene glycol) (Pal-PEG) are combined with a tailored drug binding peptide that is positioned at the hydrophobic-hydrophilic interface. The peptide originates from combinatorial selection and enables precise modulation of the drug release profiles. While Pal provides a cost-effective reservoir for drug storage, the PEG realizes solubility and shielding. The precision additives reach high payloads close to 1:1, rendering a photosensitizer water-soluble and providing adjustable drug activation kinetics by fine-tuning the peptide interface layer.