Optimized Reaction Conditions for Amide Bond Formation in DNA-Encoded Combinatorial Libraries.

PubMed

Li, Yizhou; Gabriele, Elena; Samain, Florent; Favalli, Nicholas; Sladojevich, Filippo; Scheuermann, Jörg; Neri, Dario

2016-08-08

DNA-encoded combinatorial libraries are increasingly being used as tools for the discovery of small organic binding molecules to proteins of biological or pharmaceutical interest. In the majority of cases, synthetic procedures for the formation of DNA-encoded combinatorial libraries incorporate at least one step of amide bond formation between amino-modified DNA and a carboxylic acid. We investigated reaction conditions and established a methodology by using 1-ethyl-3-(3-(dimethylamino)propyl)carbodiimide, 1-hydroxy-7-azabenzotriazole and N,N'-diisopropylethylamine (EDC/HOAt/DIPEA) in combination, which provided conversions greater than 75% for 423/543 (78%) of the carboxylic acids tested. These reaction conditions were efficient with a variety of primary and secondary amines, as well as with various types of amino-modified oligonucleotides. The reaction conditions, which also worked efficiently over a broad range of DNA concentrations and reaction scales, should facilitate the synthesis of novel DNA-encoded combinatorial libraries.

Defining RNA motif-aminoglycoside interactions via two-dimensional combinatorial screening and structure-activity relationships through sequencing.

PubMed

Velagapudi, Sai Pradeep; Disney, Matthew D

2013-10-15

RNA is an extremely important target for the development of chemical probes of function or small molecule therapeutics. Aminoglycosides are the most well studied class of small molecules to target RNA. However, the RNA motifs outside of the bacterial rRNA A-site that are likely to be bound by these compounds in biological systems is largely unknown. If such information were known, it could allow for aminoglycosides to be exploited to target other RNAs and, in addition, could provide invaluable insights into potential bystander targets of these clinically used drugs. We utilized two-dimensional combinatorial screening (2DCS), a library-versus-library screening approach, to select the motifs displayed in a 3×3 nucleotide internal loop library and in a 6-nucleotide hairpin library that bind with high affinity and selectivity to six aminoglycoside derivatives. The selected RNA motifs were then analyzed using structure-activity relationships through sequencing (StARTS), a statistical approach that defines the privileged RNA motif space that binds a small molecule. StARTS allowed for the facile annotation of the selected RNA motif-aminoglycoside interactions in terms of affinity and selectivity. The interactions selected by 2DCS generally have nanomolar affinities, which is higher affinity than the binding of aminoglycosides to a mimic of their therapeutic target, the bacterial rRNA A-site. Copyright © 2013 Elsevier Ltd. All rights reserved.

Defining RNA motif–aminoglycoside interactions via two-dimensional combinatorial screening and structure–activity relationships through sequencing

PubMed Central

Velagapudi, Sai Pradeep; Disney, Matthew D.

2013-01-01

RNA is an extremely important target for the development of chemical probes of function or small molecule therapeutics. Aminoglycosides are the most well studied class of small molecules to target RNA. However, the RNA motifs outside of the bacterial rRNA A-site that are likely to be bound by these compounds in biological systems is largely unknown. If such information were known, it could allow for aminoglycosides to be exploited to target other RNAs and, in addition, could provide invaluable insights into potential bystander targets of these clinically used drugs. We utilized two-dimensional combinatorial screening (2DCS), a library-versus-library screening approach, to select the motifs displayed in a 3 × 3 nucleotide internal loop library and in a 6-nucleotide hairpin library that bind with high affinity and selectivity to six aminoglycoside derivatives. The selected RNA motifs were then analyzed using structure–activity relationships through sequencing (StARTS), a statistical approach that defines the privileged RNA motif space that binds a small molecule. StARTS allowed for the facile annotation of the selected RNA motif–aminoglycoside interactions in terms of affinity and selectivity. The interactions selected by 2DCS generally have nanomolar affinities, which is higher affinity than the binding of aminoglycosides to a mimic of their therapeutic target, the bacterial rRNA A-site. PMID:23719281

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry.

PubMed

Kim, Kyung Lock; Park, Kyeng Min; Murray, James; Kim, Kimoon; Ryu, Sung Ho

2018-05-23

Combinatorial post-translational modifications (PTMs), which can serve as dynamic "molecular barcodes", have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry

PubMed Central

2018-01-01

Combinatorial post-translational modifications (PTMs), which can serve as dynamic “molecular barcodes”, have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Cell-Based Selection Expands the Utility of DNA-Encoded Small-Molecule Library Technology to Cell Surface Drug Targets: Identification of Novel Antagonists of the NK3 Tachykinin Receptor.

PubMed

Wu, Zining; Graybill, Todd L; Zeng, Xin; Platchek, Michael; Zhang, Jean; Bodmer, Vera Q; Wisnoski, David D; Deng, Jianghe; Coppo, Frank T; Yao, Gang; Tamburino, Alex; Scavello, Genaro; Franklin, G Joseph; Mataruse, Sibongile; Bedard, Katie L; Ding, Yun; Chai, Jing; Summerfield, Jennifer; Centrella, Paolo A; Messer, Jeffrey A; Pope, Andrew J; Israel, David I

2015-12-14

DNA-encoded small-molecule library technology has recently emerged as a new paradigm for identifying ligands against drug targets. To date, this technology has been used with soluble protein targets that are produced and used in a purified state. Here, we describe a cell-based method for identifying small-molecule ligands from DNA-encoded libraries against integral membrane protein targets. We use this method to identify novel, potent, and specific inhibitors of NK3, a member of the tachykinin family of G-protein coupled receptors (GPCRs). The method is simple and broadly applicable to other GPCRs and integral membrane proteins. We have extended the application of DNA-encoded library technology to membrane-associated targets and demonstrate the feasibility of selecting DNA-tagged, small-molecule ligands from complex combinatorial libraries against targets in a heterogeneous milieu, such as the surface of a cell.

Probing a 2-aminobenzimidazole library for binding to RNA internal loops via two-dimensional combinatorial screening.

PubMed

Velagapudi, Sai Pradeep; Pushechnikov, Alexei; Labuda, Lucas P; French, Jonathan M; Disney, Matthew D

2012-11-16

There are many potential RNA drug targets in bacterial, viral, and human transcriptomes. However, there are few small molecules that modulate RNA function. This is due, in part, to a lack of fundamental understanding about RNA-ligand interactions including the types of small molecules that bind to RNA structural elements and the RNA structural elements that bind to small molecules. In an effort to better understand RNA-ligand interactions, we diversified the 2-aminobenzimidazole core (2AB) and probed the resulting library for binding to a library of RNA internal loops. We chose the 2AB core for these studies because it is a privileged scaffold for binding RNA based on previous reports. These studies identified that N-methyl pyrrolidine, imidazole, and propylamine diversity elements at the R1 position increase binding to internal loops; variability at the R2 position is well tolerated. The preferred RNA loop space was also determined for five ligands using a statistical approach and identified trends that lead to selective recognition.

Fidelity by design: Yoctoreactor and binder trap enrichment for small-molecule DNA-encoded libraries and drug discovery.

PubMed

Blakskjaer, Peter; Heitner, Tara; Hansen, Nils Jakob Vest

2015-06-01

DNA-encoded small-molecule library (DEL) technology allows vast drug-like small molecule libraries to be efficiently synthesized in a combinatorial fashion and screened in a single tube method for binding, with an assay readout empowered by advances in next generation sequencing technology. This approach has increasingly been applied as a viable technology for the identification of small-molecule modulators to protein targets and as precursors to drugs in the past decade. Several strategies for producing and for screening DELs have been devised by both academic and industrial institutions. This review highlights some of the most significant and recent strategies along with important results. A special focus on the production of high fidelity DEL technologies with the ability to eliminate screening noise and false positives is included: using a DNA junction called the Yoctoreactor, building blocks (BBs) are spatially confined at the center of the junction facilitating both the chemical reaction between BBs and encoding of the synthetic route. A screening method, known as binder trap enrichment, permits DELs to be screened robustly in a homogeneous manner delivering clean data sets and potent hits for even the most challenging targets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Single agent and synergistic combinatorial efficacy of first-in-class small molecule imipridone ONC201 in hematological malignancies.

PubMed

Prabhu, Varun V; Talekar, Mala K; Lulla, Amriti R; Kline, C Leah B; Zhou, Lanlan; Hall, Junior; Van den Heuvel, A Pieter J; Dicker, David T; Babar, Jawad; Grupp, Stephan A; Garnett, Mathew J; McDermott, Ultan; Benes, Cyril H; Pu, Jeffrey J; Claxton, David F; Khan, Nadia; Oster, Wolfgang; Allen, Joshua E; El-Deiry, Wafik S

2018-01-01

ONC201, founding member of the imipridone class of small molecules, is currently being evaluated in advancer cancer clinical trials. We explored single agent and combinatorial efficacy of ONC201 in preclinical models of hematological malignancies. ONC201 demonstrated (GI50 1-8 µM) dose- and time-dependent efficacy in acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), diffuse large B-cell lymphoma (DLBCL), mantle cell lymphoma (MCL), Burkitt's lymphoma, anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), Hodgkin's lymphoma (nodular sclerosis) and multiple myeloma (MM) cell lines including cells resistant to standard of care (dexamethasone in MM) and primary samples. ONC201 induced caspase-dependent apoptosis that involved activation of the integrated stress response (ATF4/CHOP) pathway, inhibition of Akt phosphorylation, Foxo3a activation, downregulation of cyclin D1, IAP and Bcl-2 family members. ONC201 synergistically reduced cell viability in combination with cytarabine and 5-azacytidine in AML cells. ONC201 combined with cytarabine in a Burkitt's lymphoma xenograft model induced tumor growth inhibition that was superior to either agent alone. ONC201 synergistically combined with bortezomib in MM, MCL and ALCL cells and with ixazomib or dexamethasone in MM cells. ONC201 combined with bortezomib in a Burkitt's lymphoma xenograft model reduced tumor cell density and improved CHOP induction compared to either agent alone. These results serve as a rationale for ONC201 single-agent trials in relapsed/refractory acute leukemia, non-Hodgkin's lymphoma, MM and combination trial with dexamethasone in MM, provide pharmacodynamic biomarkers and identify further synergistic combinatorial regimens that can be explored in the clinic.

"Anticlumping" and Other Combinatorial Effects on Clumped Isotopes: Implications for Tracing Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Yeung, L.

2015-12-01

I present a mode of isotopic ordering that has purely combinatorial origins. It can be important when identical rare isotopes are paired by coincidence (e.g., they are neighbors on the same molecule), or when extrinsic factors govern the isotopic composition of the two atoms that share a chemical bond. By itself, combinatorial isotope pairing yields products with isotopes either randomly distributed or with a deficit relative to a random distribution of isotopes. These systematics arise because of an unconventional coupling between the formation of singly- and multiply-substituted isotopic moieties. In a random distribution, rare isotopes are symmetrically distributed: Single isotopic substitutions (e.g., H‒D and D‒H in H2) occur with equal probability, and double isotopic substitutions (e.g., D2) occur according to random chance. The absence of symmetry in a bond-making complex can yield unequal numbers of singly-substituted molecules (e.g., more H‒D than D‒H in H2), which is recorded in the product molecule as a deficit in doubly-substituted moieties and an "anticlumped" isotope distribution (i.e., Δn < 0). Enzymatic isotope pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect. Chemical-kinetic isotope effects, which are related to the bond-forming transition state, arise independently and express second-order combinatorial effects. In general, both combinatorial and chemical factors are important for calculating and interpreting clumped-isotope signatures of individual reactions. In many reactions relevant to geochemical oxygen, carbon, and nitrogen cycling, combinatorial isotope pairing likely plays a strong role in the clumped isotope distribution of the products. These isotopic signatures, manifest as either directly bound isotope clumps or as features of a molecule's isotopic anatomy, could be exploited as tracers of biogeochemistry that can relate molecular mechanisms to signals observable at environmentally relevant spatial scales.

Directed Chemical Evolution with an Outsized Genetic Code

PubMed Central

Krusemark, Casey J.; Tilmans, Nicolas P.; Brown, Patrick O.; Harbury, Pehr B.

2016-01-01

The first demonstration that macromolecules could be evolved in a test tube was reported twenty-five years ago. That breakthrough meant that billions of years of chance discovery and refinement could be compressed into a few weeks, and provided a powerful tool that now dominates all aspects of protein engineering. A challenge has been to extend this scientific advance into synthetic chemical space: to enable the directed evolution of abiotic molecules. The problem has been tackled in many ways. These include expanding the natural genetic code to include unnatural amino acids, engineering polyketide and polypeptide synthases to produce novel products, and tagging combinatorial chemistry libraries with DNA. Importantly, there is still no small-molecule analog of directed protein evolution, i.e. a substantiated approach for optimizing complex (≥ 10^9 diversity) populations of synthetic small molecules over successive generations. We present a key advance towards this goal: a tool for genetically-programmed synthesis of small-molecule libraries from large chemical alphabets. The approach accommodates alphabets that are one to two orders of magnitude larger than any in Nature, and facilitates evolution within the chemical spaces they create. This is critical for small molecules, which are built up from numerous and highly varied chemical fragments. We report a proof-of-concept chemical evolution experiment utilizing an outsized genetic code, and demonstrate that fitness traits can be passed from an initial small-molecule population through to the great-grandchildren of that population. The results establish the practical feasibility of engineering synthetic small molecules through accelerated evolution. PMID:27508294

Directed differentiation of embryonic stem cells using a bead-based combinatorial screening method.

PubMed

Tarunina, Marina; Hernandez, Diana; Johnson, Christopher J; Rybtsov, Stanislav; Ramathas, Vidya; Jeyakumar, Mylvaganam; Watson, Thomas; Hook, Lilian; Medvinsky, Alexander; Mason, Chris; Choo, Yen

2014-01-01

We have developed a rapid, bead-based combinatorial screening method to determine optimal combinations of variables that direct stem cell differentiation to produce known or novel cell types having pre-determined characteristics. Here we describe three experiments comprising stepwise exposure of mouse or human embryonic cells to 10,000 combinations of serum-free differentiation media, through which we discovered multiple novel, efficient and robust protocols to generate a number of specific hematopoietic and neural lineages. We further demonstrate that the technology can be used to optimize existing protocols in order to substitute costly growth factors with bioactive small molecules and/or increase cell yield, and to identify in vitro conditions for the production of rare developmental intermediates such as an embryonic lymphoid progenitor cell that has not previously been reported.

Discovery of DNA repair inhibitors by combinatorial library profiling

PubMed Central

Moeller, Benjamin J.; Sidman, Richard L.; Pasqualini, Renata; Arap, Wadih

2011-01-01

Small molecule inhibitors of DNA repair are emerging as potent and selective anti-cancer therapies, but the sheer magnitude of the protein networks involved in DNA repair processes poses obstacles to discovery of effective candidate drugs. To address this challenge, we used a subtractive combinatorial selection approach to identify a panel of peptide ligands that bind DNA repair complexes. Supporting the concept that these ligands have therapeutic potential, we show that one selected peptide specifically binds and non-competitively inactivates DNA-PKcs, a protein kinase critical in double-strand DNA break repair. In doing so, this ligand sensitizes BRCA-deficient tumor cells to genotoxic therapy. Our findings establish a platform for large-scale parallel screening for ligand-directed DNA repair inhibitors, with immediate applicability to cancer therapy. PMID:21343400

Successful application of the dual-vector system II in creating a reliable phage-displayed combinatorial Fab library.

PubMed

Song, Suk-yoon; Hur, Byung-ung; Lee, Kyung-woo; Choi, Hyo-jung; Kim, Sung-soo; Kang, Goo; Cha, Sang-hoon

2009-03-31

The dual-vector system-II (DVS-II), which allows efficient display of Fab antibodies on phage, has been reported previously, but its practical applicability in a phage-displayed antibody library has not been verified. To resolve this issue, we created two small combinatorial human Fab antibody libraries using the DVS-II, and isolation of target-specific antibodies was attempted. Biopanning of one antibody library, termed DVFAB-1L library, which has a 1.3 x 10(7) combinatorial antibody complexity, against fluorescein-BSA resulted in successful isolation of human Fab clones specific for the antigen despite the presence of only a single light chain in the library. By using the unique feature of the DVS-II, an antibody library of a larger size, named DVFAB-131L, which has a 1.5 x 10(9) combinatorial antibody complexity, was also generated in a rapid manner by combining 1.3 x 10(7) heavy chains and 131 light chains and more diverse anti-fluorescein-BSA Fab antibody clones were successfully obtained. Our results demonstrate that the DVS-II can be applied readily in creating phage-displayed antibody libraries with much less effort, and target-specific antibody clones can be isolated reliably via light chain promiscuity of antibody molecule.

Increased Diversity of Libraries from Libraries: Chemoinformatic Analysis of Bis-Diazacyclic Libraries

PubMed Central

López-Vallejo, Fabian; Nefzi, Adel; Bender, Andreas; Owen, John R.; Nabney, Ian T.; Houghten, Richard A.; Medina-Franco, Jose L.

2011-01-01

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. PMID:21294850

Probing a 2-Aminobenzimidazole Library for Binding to RNA Internal Loops via Two-Dimensional Combinatorial Screening

PubMed Central

Velegapudi, Sai Pradeep; Pushechnikov, Alexei; Labuda, Lucas P.; French, Jonathan M.; Disney, Matthew D.

2012-01-01

There are many potential RNA drug targets in bacterial, viral, and the human transcriptomes. However, there are few small molecules that modulate RNA function. This is due, in part, to a lack of fundamental understanding about RNA-ligand interactions including the types of small molecules that bind to RNA structural elements and the RNA structural elements that bind to small molecules. In an effort to better understand RNA-ligand interactions, we diversified the 2-aminobenzimidazole core (2AB) and probed the resulting library for binding to a library of RNA internal loops. We chose the 2AB core for these studies because it is a privileged scaffold for binding RNA based on previous reports. These studies identified that N-methyl pyrrolidine, imidazole, and propylamine diversity elements at the R1 position increase binding to internal loops; variability at the R2 position is well tolerated. The preferred RNA loop space was also determined for five ligands using a statistical approach and identified trends that lead to selective recognition. PMID:22958065

A novel spiroindoline targets cell cycle and migration via modulation of microtubule cytoskeleton.

PubMed

Kumar, Naveen; Hati, Santanu; Munshi, Parthapratim; Sen, Subhabrata; Sehrawat, Seema; Singh, Shailja

2017-05-01

Natural product-inspired libraries of molecules with diverse architectures have evolved as one of the most useful tools for discovering lead molecules for drug discovery. In comparison to conventional combinatorial libraries, these molecules have been inferred to perform better in phenotypic screening against complicated targets. Diversity-oriented synthesis (DOS) is a forward directional strategy to access such multifaceted library of molecules. From a successful DOS campaign of a natural product-inspired library, recently a small molecule with spiroindoline motif was identified as a potent anti-breast cancer compound. Herein we report the subcellular studies performed for this molecule on breast cancer cells. Our investigation revealed that it repositions microtubule cytoskeleton and displaces AKAP9 located at the microtubule organization centre. DNA ladder assay and cell cycle experiments further established the molecule as an apoptotic agent. This work further substantiated the amalgamation of DOS-phenotypic screening-sub-cellular studies as a consolidated blueprint for the discovery of potential pharmaceutical drug candidates.

Directed Differentiation of Embryonic Stem Cells Using a Bead-Based Combinatorial Screening Method

PubMed Central

Tarunina, Marina; Hernandez, Diana; Johnson, Christopher J.; Rybtsov, Stanislav; Ramathas, Vidya; Jeyakumar, Mylvaganam; Watson, Thomas; Hook, Lilian; Medvinsky, Alexander; Mason, Chris; Choo, Yen

2014-01-01

We have developed a rapid, bead-based combinatorial screening method to determine optimal combinations of variables that direct stem cell differentiation to produce known or novel cell types having pre-determined characteristics. Here we describe three experiments comprising stepwise exposure of mouse or human embryonic cells to 10,000 combinations of serum-free differentiation media, through which we discovered multiple novel, efficient and robust protocols to generate a number of specific hematopoietic and neural lineages. We further demonstrate that the technology can be used to optimize existing protocols in order to substitute costly growth factors with bioactive small molecules and/or increase cell yield, and to identify in vitro conditions for the production of rare developmental intermediates such as an embryonic lymphoid progenitor cell that has not previously been reported. PMID:25251366

Dynamic combinatorial libraries: new opportunities in systems chemistry.

PubMed

Hunt, Rosemary A R; Otto, Sijbren

2011-01-21

Combinatorial chemistry is a tool for selecting molecules with special properties. Dynamic combinatorial chemistry started off aiming to be just that. However, unlike ordinary combinatorial chemistry, the interconnectedness of dynamic libraries gives them an extra dimension. An understanding of these molecular networks at systems level is essential for their use as a selection tool and creates exciting new opportunities in systems chemistry. In this feature article we discuss selected examples and considerations related to the advanced exploitation of dynamic combinatorial libraries for their originally conceived purpose of identifying strong binding interactions. Also reviewed are examples illustrating a trend towards increasing complexity in terms of network behaviour and reversible chemistry. Finally, new applications of dynamic combinatorial chemistry in self-assembly, transport and self-replication are discussed.

Linkage of Recognition and Replication Functions by Assembling Combinatorial Antibody Fab Libraries Along Phage Surfaces

NASA Astrophysics Data System (ADS)

Kang, Angray S.; Barbas, Carlos F.; Janda, Kim D.; Benkovic, Stephen J.; Lerner, Richard A.

1991-05-01

We describe a method based on a phagemid vector with helper phage rescue for the construction and rapid analysis of combinatorial antibody Fab libraries. This approach should allow the generation and selection of many monoclonal antibodies. Antibody genes are expressed in concert with phage morphogenesis, thereby allowing incorporation of functional Fab molecules along the surface of filamentous phage. The power of the method depends upon the linkage of recognition and replication functions and is not limited to antibody molecules.

Pancreatic cancer combination therapy using a BH3 mimetic and a synthetic tetracycline

PubMed Central

Quinn, Bridget A.; Dash, Rupesh; Sarkar, Siddik; Azab, Belal; Bhoopathi, Praveen; Das, Swadesh K.; Emdad, Luni; Wei, Jun; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B.

2015-01-01

Improved treatments for pancreatic cancer remain a clinical imperative. Sabutoclax, a small molecule BH3 mimetic, inhibits the function of anti-apoptotic Bcl-2 proteins. Minocycline, a synthetic tetracycline, displays antitumor activity. Here we offer evidence of the combinatorial antitumor potency of these agents in several preclinical models of pancreatic cancer. Sabutoclax induced growth arrest and apoptosis in pancreatic cancer cells and synergized with Minocycline to yield a robust mitochondria-mediated caspase-dependent cytotoxicity. This combinatorial property relied upon loss of phosphorylated Stat3 insofar as reintroduction of activated Stat3 rescued cells from toxicity. Tumor growth was inhibited potently in both immune-deficient and immune-competent models with evidence of extended survival. Overall, our results showed that that the combination of Sabutoclax and Minocycline was highly cytotoxic to pancreatic cancer cells and safely efficacious in vivo. PMID:26032425

A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor.

PubMed

Licciardello, Marco P; Ringler, Anna; Markt, Patrick; Klepsch, Freya; Lardeau, Charles-Hugues; Sdelci, Sara; Schirghuber, Erika; Müller, André C; Caldera, Michael; Wagner, Anja; Herzog, Rebecca; Penz, Thomas; Schuster, Michael; Boidol, Bernd; Dürnberger, Gerhard; Folkvaljon, Yasin; Stattin, Pär; Ivanov, Vladimir; Colinge, Jacques; Bock, Christoph; Kratochwill, Klaus; Menche, Jörg; Bennett, Keiryn L; Kubicek, Stefan

2017-07-01

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

Ligand-regulated peptides: a general approach for modulating protein-peptide interactions with small molecules.

PubMed

Binkowski, Brock F; Miller, Russell A; Belshaw, Peter J

2005-07-01

We engineered a novel ligand-regulated peptide (LiRP) system where the binding activity of intracellular peptides is controlled by a cell-permeable small molecule. In the absence of ligand, peptides expressed as fusions in an FKBP-peptide-FRB-GST LiRP scaffold protein are free to interact with target proteins. In the presence of the ligand rapamycin, or the nonimmunosuppressive rapamycin derivative AP23102, the scaffold protein undergoes a conformational change that prevents the interaction of the peptide with the target protein. The modular design of the scaffold enables the creation of LiRPs through rational design or selection from combinatorial peptide libraries. Using these methods, we identified LiRPs that interact with three independent targets: retinoblastoma protein, c-Src, and the AMP-activated protein kinase. The LiRP system should provide a general method to temporally and spatially regulate protein function in cells and organisms.

Template-based combinatorial enumeration of virtual compound libraries for lipids

PubMed Central

2012-01-01

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license. PMID:23006594

Template-based combinatorial enumeration of virtual compound libraries for lipids.

PubMed

Sud, Manish; Fahy, Eoin; Subramaniam, Shankar

2012-09-25

A variety of software packages are available for the combinatorial enumeration of virtual libraries for small molecules, starting from specifications of core scaffolds with attachments points and lists of R-groups as SMILES or SD files. Although SD files include atomic coordinates for core scaffolds and R-groups, it is not possible to control 2-dimensional (2D) layout of the enumerated structures generated for virtual compound libraries because different packages generate different 2D representations for the same structure. We have developed a software package called LipidMapsTools for the template-based combinatorial enumeration of virtual compound libraries for lipids. Virtual libraries are enumerated for the specified lipid abbreviations using matching lists of pre-defined templates and chain abbreviations, instead of core scaffolds and lists of R-groups provided by the user. 2D structures of the enumerated lipids are drawn in a specific and consistent fashion adhering to the framework for representing lipid structures proposed by the LIPID MAPS consortium. LipidMapsTools is lightweight, relatively fast and contains no external dependencies. It is an open source package and freely available under the terms of the modified BSD license.

Chemogenomics: a discipline at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

PubMed

Maréchal, Eric

2008-09-01

Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry open new fields of research for chemogenomics.

Are highly morphed peptide frameworks lurking silently in microbial genomes valuable as next generation antibiotic scaffolds?

PubMed

Walsh, Christopher T

2017-07-01

Antibiotics are a therapeutic class that, once deployed, select for resistant bacterial pathogens and so shorten their useful life cycles. As a consequence new versions of antibiotics are constantly needed. Among the antibiotic natural products, morphed peptide scaffolds, converting conformationally mobile, short-lived linear peptides into compact, rigidified small molecule frameworks, act on a wide range of bacterial targets. Advances in bacterial genome mining, biosynthetic gene cluster prediction and expression, and mass spectroscopic structure analysis suggests many more peptides, modified both in side chains and peptide backbones, await discovery. Such molecules may turn up new bacterial targets and be starting points for combinatorial or semisynthetic manipulations to optimize activity and pharmacology parameters.

Combinatorial Partial Hydrogenation Reactions of 4-Nitroacetophenone: An Undergraduate Organic Laboratory

ERIC Educational Resources Information Center

Kittredge, Kevin W.; Marine, Susan S.; Taylor, Richard T.

2004-01-01

A molecule possessing other functional groups that could be hydrogenerated is examined, where a variety of metal catalysts are evaluated under similar reaction conditions. Optimizing organic reactions is both time and labor intensive, and the use of a combinatorial parallel synthesis reactor was great time saving device, as per summary.

Combinatorial Characterization of TiO2 Chemical Vapor Deposition Utilizing Titanium Isopropoxide.

PubMed

Reinke, Michael; Ponomarev, Evgeniy; Kuzminykh, Yury; Hoffmann, Patrik

2015-07-13

The combinatorial characterization of the growth kinetics in chemical vapor deposition processes is challenging because precise information about the local precursor flow is usually difficult to access. In consequence, combinatorial chemical vapor deposition techniques are utilized more to study functional properties of thin films as a function of chemical composition, growth rate or crystallinity than to study the growth process itself. We present an experimental procedure which allows the combinatorial study of precursor surface kinetics during the film growth using high vacuum chemical vapor deposition. As consequence of the high vacuum environment, the precursor transport takes place in the molecular flow regime, which allows predicting and modifying precursor impinging rates on the substrate with comparatively little experimental effort. In this contribution, we study the surface kinetics of titanium dioxide formation using titanium tetraisopropoxide as precursor molecule over a large parameter range. We discuss precursor flux and temperature dependent morphology, crystallinity, growth rates, and precursor deposition efficiency. We conclude that the surface reaction of the adsorbed precursor molecules comprises a higher order reaction component with respect to precursor surface coverage.

Applications of SHAPES screening in drug discovery.

PubMed

Lepre, Christopher A; Peng, Jeffrey; Fejzo, Jasna; Abdul-Manan, Norzehan; Pocas, Jennifer; Jacobs, Marc; Xie, Xiaoling; Moore, Jonathan M

2002-12-01

The SHAPES strategy combines nuclear magnetic resonance (NMR) screening of a library of small drug-like molecules with a variety of complementary methods, such as virtual screening, high throughput enzymatic assays, combinatorial chemistry, X-ray crystallography, and molecular modeling, in a directed search for new medicinal chemistry leads. In the past few years, the SHAPES strategy has found widespread utility in pharmaceutical research. To illustrate a variety of different implementations of the method, we will focus in this review on recent applications of the SHAPES strategy in several drug discovery programs at Vertex Pharmaceuticals.

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

Chemical Approaches to Control Gene Expression

PubMed Central

Gottesfeld, Joel M.; Turner, James M.; Dervan, Peter B.

2000-01-01

A current goal in molecular medicine is the development of new strategies to interfere with gene expression in living cells in the hope that novel therapies for human disease will result from these efforts. This review focuses on small-molecule or chemical approaches to manipulate gene expression by modulating either transcription of messenger RNA-coding genes or protein translation. The molecules under study include natural products, designed ligands, and compounds identified through functional screens of combinatorial libraries. The cellular targets for these molecules include DNA, messenger RNA, and the protein components of the transcription, RNA processing, and translational machinery. Studies with model systems have shown promise in the inhibition of both cellular and viral gene transcription and mRNA utilization. Moreover, strategies for both repression and activation of gene transcription have been described. These studies offer promise for treatment of diseases of pathogenic (viral, bacterial, etc.) and cellular origin (cancer, genetic diseases, etc.). PMID:11097426

Combinatorial Solid-Phase Synthesis of Aromatic Oligoamides: A Research-Based Laboratory Module for Undergraduate Organic Chemistry

ERIC Educational Resources Information Center

Fuller, Amelia A.

2016-01-01

A five-week, research-based experiment suitable for second-semester introductory organic laboratory students is described. Each student designs, prepares, and analyzes a combinatorial array of six aromatic oligoamides. Molecules are prepared on solid phase via a six-step synthetic sequence, and purities and identities are determined by analysis of…

Dynamic combinatorial libraries: from exploring molecular recognition to systems chemistry.

PubMed

Li, Jianwei; Nowak, Piotr; Otto, Sijbren

2013-06-26

Dynamic combinatorial chemistry (DCC) is a subset of combinatorial chemistry where the library members interconvert continuously by exchanging building blocks with each other. Dynamic combinatorial libraries (DCLs) are powerful tools for discovering the unexpected and have given rise to many fascinating molecules, ranging from interlocked structures to self-replicators. Furthermore, dynamic combinatorial molecular networks can produce emergent properties at systems level, which provide exciting new opportunities in systems chemistry. In this perspective we will highlight some new methodologies in this field and analyze selected examples of DCLs that are under thermodynamic control, leading to synthetic receptors, catalytic systems, and complex self-assembled supramolecular architectures. Also reviewed are extensions of the principles of DCC to systems that are not at equilibrium and may therefore harbor richer functional behavior. Examples include self-replication and molecular machines.

Development of a web-based tool for automated processing and cataloging of a unique combinatorial drug screen.

PubMed

Dalecki, Alex G; Wolschendorf, Frank

2016-07-01

Facing totally resistant bacteria, traditional drug discovery efforts have proven to be of limited use in replenishing our depleted arsenal of therapeutic antibiotics. Recently, the natural anti-bacterial properties of metal ions in synergy with metal-coordinating ligands have shown potential for generating new molecule candidates with potential therapeutic downstream applications. We recently developed a novel combinatorial screening approach to identify compounds with copper-dependent anti-bacterial properties. Through a parallel screening technique, the assay distinguishes between copper-dependent and independent activities against Mycobacterium tuberculosis with hits being defined as compounds with copper-dependent activities. These activities must then be linked to a compound master list to process and analyze the data and to identify the hit molecules, a labor intensive and mistake-prone analysis. Here, we describe a software program built to automate this analysis in order to streamline our workflow significantly. We conducted a small, 1440 compound screen against M. tuberculosis and used it as an example framework to build and optimize the software. Though specifically adapted to our own needs, it can be readily expanded for any small- to medium-throughput screening effort, parallel or conventional. Further, by virtue of the underlying Linux server, it can be easily adapted for chemoinformatic analysis of screens through packages such as OpenBabel. Overall, this setup represents an easy-to-use solution for streamlining processing and analysis of biological screening data, as well as offering a scaffold for ready functionality expansion. Copyright © 2016 Elsevier B.V. All rights reserved.

Nature's combinatorial biosynthesis and recently engineered production of nucleoside antibiotics in Streptomyces.

PubMed

Chen, Shawn; Kinney, William A; Van Lanen, Steven

2017-04-01

Modified nucleosides produced by Streptomyces and related actinomycetes are widely used in agriculture and medicine as antibacterial, antifungal, anticancer and antiviral agents. These specialized small-molecule metabolites are biosynthesized by complex enzymatic machineries encoded within gene clusters in the genome. The past decade has witnessed a burst of reports defining the key metabolic processes involved in the biosynthesis of several distinct families of nucleoside antibiotics. Furthermore, genome sequencing of various Streptomyces species has dramatically increased over recent years. Potential biosynthetic gene clusters for novel nucleoside antibiotics are now apparent by analysis of these genomes. Here we revisit strategies for production improvement of nucleoside antibiotics that have defined mechanisms of action, and are in clinical or agricultural use. We summarize the progress for genetically manipulating biosynthetic pathways for structural diversification of nucleoside antibiotics. Microorganism-based biosynthetic examples are provided and organized under genetic principles and metabolic engineering guidelines. We show perspectives on the future of combinatorial biosynthesis, and present a working model for discovery of novel nucleoside natural products in Streptomyces.

Nanoscale structure-activity relationships, mode of action, and biocompatibility of gold nanoparticle antibiotics.

PubMed

Bresee, Jamee; Bond, Constance M; Worthington, Roberta J; Smith, Candice A; Gifford, Jennifer C; Simpson, Carrie A; Carter, Carly J; Wang, Guankui; Hartman, Jesse; Osbaugh, Niki A; Shoemaker, Richard K; Melander, Christian; Feldheim, Daniel L

2014-04-09

The emergence of resistance to multiple antimicrobial agents by pathogenic bacteria has become a significant global public health threat. Multi-drug-resistant (MDR) Gram-negative bacteria have become particularly problematic, as no new classes of small-molecule antibiotics for Gram-negative bacteria have emerged in over two decades. We have developed a combinatorial screening process for identifying mixed ligand monolayer/gold nanoparticle conjugates (2.4 nm diameter) with antibiotic activity. The method previously led to the discovery of several conjugates with potent activity against the Gram-negative bacterium Escherichia coli. Here we show that these conjugates are also active against MDR E. coli and MDR Klebsiella pneumoniae. Moreover, we have shown that resistance to these nanoparticles develops significantly more slowly than to a commercial small-molecule drug. These results, combined with their relatively low toxicity to mammalian cells and biocompatibility in vivo, suggest that gold nanoparticles may be viable new candidates for the treatment of MDR Gram-negative bacterial infections.

An artificial tongue fluorescent sensor array for identification and quantitation of various heavy metal ions.

PubMed

Xu, Wang; Ren, Changliang; Teoh, Chai Lean; Peng, Juanjuan; Gadre, Shubhankar Haribhau; Rhee, Hyun-Woo; Lee, Chi-Lik Ken; Chang, Young-Tae

2014-09-02

Herein, a small-molecule fluorescent sensor array for rapid identification of seven heavy metal ions was designed and synthesized, with its sensing mechanism mimicking that of a tongue. The photoinduced electron transfer and intramolecular charge transfer mechanism result in combinatorial interactions between sensor array and heavy metal ions, which lead to diversified fluorescence wavelength shifts and emission intensity changes. Upon principle component analysis (PCA), this result renders clear identification of each heavy metal ion on a 3D spatial dispersion graph. Further exploration provides a concentration-dependent pattern, allowing both qualitative and quantitative measurements of heavy metal ions. On the basis of this information, a "safe-zone" concept was proposed, which provides rapid exclusion of versatile hazardous species from clean water samples based on toxicity characteristic leaching procedure standards. This type of small-molecule fluorescent sensor array could open a new avenue for multiple heavy metal ion detection and simplified water quality analysis.

Solid-Phase and Microwave-Assisted Syntheses of 2,5-Diketopiperazines: Small Molecules with Great Potential

PubMed Central

O'Neill, J.C.; Blackwell, H. E.

2008-01-01

Diketopiperazines (DKPs) are a well-known class of heterocycles that have recently emerged as a promising biologically active scaffold. Solid-phase organic synthesis has become an important tool in the combinatorial exploration of these privileged structures, expediting the synthesis and, therefore, the discovery of active compounds. To date, certain DKPs have shown potent activities against a range of diseases and biological phenomena, including bacterial infections, various cancers, asthma, infertility, premature labor, and HIV. Recent applications of solid-phase DKP synthesis, with a particular focus on cyclative cleavage and microwave-assisted reactions, are highlighted herein. PMID:18288948

Combinatorial selection of molecular conformations and supramolecular synthons in quercetin cocrystal landscapes: a route to ternary solids

PubMed Central

Dubey, Ritesh; Desiraju, Gautam R.

2015-01-01

The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O—H⋯N and O—H⋯O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular ‘confusion’ that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution. PMID:26175900

Virtual Exploration of the Ring Systems Chemical Universe.

PubMed

Visini, Ricardo; Arús-Pous, Josep; Awale, Mahendra; Reymond, Jean-Louis

2017-11-27

Here, we explore the chemical space of all virtually possible organic molecules focusing on ring systems, which represent the cyclic cores of organic molecules obtained by removing all acyclic bonds and converting all remaining atoms to carbon. This approach circumvents the combinatorial explosion encountered when enumerating the molecules themselves. We report the chemical universe database GDB4c containing 916 130 ring systems up to four saturated or aromatic rings and maximum ring size of 14 atoms and GDB4c3D containing the corresponding 6 555 929 stereoisomers. Almost all (98.6%) of these ring systems are unknown and represent chiral 3D-shaped macrocycles containing small rings and quaternary centers reminiscent of polycyclic natural products. We envision that GDB4c can serve to select new ring systems from which to design analogs of such natural products. The database is available for download at www.gdb.unibe.ch together with interactive visualization and search tools as a resource for molecular design.

A Rapid Python-Based Methodology for Target-Focused Combinatorial Library Design.

PubMed

Li, Shiliang; Song, Yuwei; Liu, Xiaofeng; Li, Honglin

2016-01-01

The chemical space is so vast that only a small portion of it has been examined. As a complementary approach to systematically probe the chemical space, virtual combinatorial library design has extended enormous impacts on generating novel and diverse structures for drug discovery. Despite the favorable contributions, high attrition rates in drug development that mainly resulted from lack of efficacy and side effects make it increasingly challenging to discover good chemical starting points. In most cases, focused libraries, which are restricted to particular regions of the chemical space, are deftly exploited to maximize hit rate and improve efficiency at the beginning of the drug discovery and drug development pipeline. This paper presented a valid methodology for fast target-focused combinatorial library design in both reaction-based and production-based ways with the library creating rates of approximately 70,000 molecules per second. Simple, quick and convenient operating procedures are the specific features of the method. SHAFTS, a hybrid 3D similarity calculation software, was embedded to help refine the size of the libraries and improve hit rates. Two target-focused (p38-focused and COX2-focused) libraries were constructed efficiently in this study. This rapid library enumeration method is portable and applicable to any other targets for good chemical starting points identification collaborated with either structure-based or ligand-based virtual screening.

A transcription factor network coordinates attraction, repulsion, and adhesion combinatorially to control motor axon pathway selection.

PubMed

Zarin, Aref Arzan; Asadzadeh, Jamshid; Hokamp, Karsten; McCartney, Daniel; Yang, Long; Bashaw, Greg J; Labrador, Juan-Pablo

2014-03-19

Combinations of transcription factors (TFs) instruct precise wiring patterns in the developing nervous system; however, how these factors impinge on surface molecules that control guidance decisions is poorly understood. Using mRNA profiling, we identified the complement of membrane molecules regulated by the homeobox TF Even-skipped (Eve), the major determinant of dorsal motor neuron (dMN) identity in Drosophila. Combinatorial loss- and gain-of-function genetic analyses of Eve target genes indicate that the integrated actions of attractive, repulsive, and adhesive molecules direct eve-dependent dMN axon guidance. Furthermore, combined misexpression of Eve target genes is sufficient to partially restore CNS exit and can convert the guidance behavior of interneurons to that of dMNs. Finally, we show that a network of TFs, comprised of eve, zfh1, and grain, induces the expression of the Unc5 and Beaten-path guidance receptors and the Fasciclin 2 and Neuroglian adhesion molecules to guide individual dMN axons. Copyright © 2014 Elsevier Inc. All rights reserved.

A Transcription Factor Network Coordinates Attraction, Repulsion, and Adhesion Combinatorially to Control Motor Axon Pathway Selection

PubMed Central

Zarin, Aref Arzan; Asadzadeh, Jamshid; Hokamp, Karsten; McCartney, Daniel; Yang, Long; Bashaw, Greg J.; Labrador, Juan-Pablo

2014-01-01

SUMMARY Combinations of transcription factors (TFs) instruct precise wiring patterns in the developing nervous system; however, how these factors impinge on surface molecules that control guidance decisions is poorly understood. Using mRNA profiling, we identified the complement of membrane molecules regulated by the homeobox TF Even-skipped (Eve), the major determinant of dorsal motor neuron (dMN) identity in Drosophila. Combinatorial loss- and gain-of-function genetic analyses of Eve target genes indicate that the integrated actions of attractive, repulsive, and adhesive molecules direct eve-dependent dMN axon guidance. Furthermore, combined misexpression of Eve target genes is sufficient to partially restore CNS exit and can convert the guidance behavior of interneurons to that of dMNs. Finally, we show that a network of TFs, comprised of eve, zfh1, and grain, induces the expression of the Unc5 and Beaten-path guidance receptors and the Fasciclin 2 and Neuroglian adhesion molecules to guide individual dMN axons. PMID:24560702

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites.

PubMed

Vukovic, Sinisa; Brennan, Paul E; Huggins, David J

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

NASA Astrophysics Data System (ADS)

Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

2016-09-01

The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

Chemical genomics in plant biology.

PubMed

Sadhukhan, Ayan; Sahoo, Lingaraj; Panda, Sanjib Kumar

2012-06-01

Chemical genomics is a newly emerged and rapidly progressing field in biology, where small chemical molecules bind specifically and reversibly to protein(s) to modulate their function(s), leading to the delineation and subsequent unravelling of biological processes. This approach overcomes problems like lethality and redundancy of classical genetics. Armed with the powerful techniques of combinatorial synthesis, high-throughput screening and target discovery chemical genomics expands its scope to diverse areas in biology. The well-established genetic system of Arabidopsis model allows chemical genomics to enter into the realm of plant biology exploring signaling pathways of growth regulators, endomembrane signaling cascades, plant defense mechanisms and many more events.

Synthetic Biological Approaches to Natural Product Biosynthesis

PubMed Central

Winter, Jaclyn M; Tang, Yi

2012-01-01

Small molecules produced in Nature continue to be an inspiration for the development of new therapeutic agents. These natural products possess exquisite chemical diversity, which gives rise to their wide range of biological activities. In their host organism, natural products are assembled and modified by dedicated biosynthetic pathways that Nature has meticulously developed. Often times, the complex structures or chemical modifications instated by these pathways are difficult to replicate using traditional synthetic methods. An alternative approach for creating or enhancing the structural variation of natural products is through combinatorial biosynthesis. By rationally reprogramming and manipulating the biosynthetic machinery responsible for their production, unnatural metabolites that were otherwise inaccessible can be obtained. Additionally, new chemical structures can be synthesized or derivatized by developing the enzymes that carry out these complicated chemical reactions into biocatalysts. In this review, we will discuss a variety of combinatorial biosynthetic strategies, their technical challenges, and highlight some recent (since 2007) examples of rationally designed unnatural metabolites, as well as platforms that have been established for the production and modification of clinically important pharmaceutical compounds. PMID:22221832

Combinatorial Broadening Mechanism of O-H Stretching Bands in H-Bonded Molecular Clusters

NASA Astrophysics Data System (ADS)

Pitsevich, G. A.; Doroshenko, I. Yu.; Pogorelov, V. E.; Pettersson, L. G. M.; Sablinskas, V.; Sapeshko, V. V.; Balevicius, V.

2016-07-01

A new mechanism for combinatorial broadening of donor-OH stretching-vibration absorption bands in molecular clusters with H-bonds is proposed. It enables the experimentally observed increase of the O-H stretching-vibration bandwidth with increasing number of molecules in H-bonded clusters to be explained. Knowledge of the half-width of the OH stretching-vibration absorption band in the dimer and the number of H-bonds in the analyzed cluster is suffi cient in the zeroth-order approximation to estimate the O-H stretching-absorption bands in clusters containing several molecules. Good agreement between the calculated and published experimental half-widths of the OH stretching-vibration absorption bands in MeOH and PrOH clusters was obtained using this approach.

Generic strategies for chemical space exploration.

PubMed

Andersen, Jakob L; Flamm, Christoph; Merkle, Daniel; Stadler, Peter F

2014-01-01

The chemical universe of molecules reachable from a set of start compounds by iterative application of a finite number of reactions is usually so vast, that sophisticated and efficient exploration strategies are required to cope with the combinatorial complexity. A stringent analysis of (bio)chemical reaction networks, as approximations of these complex chemical spaces, forms the foundation for the understanding of functional relations in Chemistry and Biology. Graphs and graph rewriting are natural models for molecules and reactions. Borrowing the idea of partial evaluation from functional programming, we introduce partial applications of rewrite rules. A framework for the specification of exploration strategies in graph-rewriting systems is presented. Using key examples of complex reaction networks from carbohydrate chemistry we demonstrate the feasibility of this high-level strategy framework. While being designed for chemical applications, the framework can also be used to emulate higher-level transformation models such as illustrated in a small puzzle game.

Mixture-based combinatorial libraries from small individual peptide libraries: a case study on α1-antitrypsin deficiency.

PubMed

Chang, Yi-Pin; Chu, Yen-Ho

2014-05-16

The design, synthesis and screening of diversity-oriented peptide libraries using a "libraries from libraries" strategy for the development of inhibitors of α1-antitrypsin deficiency are described. The major buttress of the biochemical approach presented here is the use of well-established solid-phase split-and-mix method for the generation of mixture-based libraries. The combinatorial technique iterative deconvolution was employed for library screening. While molecular diversity is the general consideration of combinatorial libraries, exquisite design through systematic screening of small individual libraries is a prerequisite for effective library screening and can avoid potential problems in some cases. This review will also illustrate how large peptide libraries were designed, as well as how a conformation-sensitive assay was developed based on the mechanism of the conformational disease. Finally, the combinatorially selected peptide inhibitor capable of blocking abnormal protein aggregation will be characterized by biophysical, cellular and computational methods.

Application of computer assisted combinatorial chemistry in antivirial, antimalarial and anticancer agents design

NASA Astrophysics Data System (ADS)

Burello, E.; Bologa, C.; Frecer, V.; Miertus, S.

Combinatorial chemistry and technologies have been developed to a stage where synthetic schemes are available for generation of a large variety of organic molecules. The innovative concept of combinatorial design assumes that screening of a large and diverse library of compounds will increase the probability of finding an active analogue among the compounds tested. Since the rate at which libraries are screened for activity currently constitutes a limitation to the use of combinatorial technologies, it is important to be selective about the number of compounds to be synthesized. Early experience with combinatorial chemistry indicated that chemical diversity alone did not result in a significant increase in the number of generated lead compounds. Emphasis has therefore been increasingly put on the use of computer assisted combinatorial chemical techniques. Computational methods are valuable in the design of virtual libraries of molecular models. Selection strategies based on computed physicochemical properties of the models or of a target compound are introduced to reduce the time and costs of library synthesis and screening. In addition, computational structure-based library focusing methods can be used to perform in silico screening of the activity of compounds against a target receptor by docking the ligands into the receptor model. Three case studies are discussed dealing with the design of targeted combinatorial libraries of inhibitors of HIV-1 protease, P. falciparum plasmepsin and human urokinase as potential antivirial, antimalarial and anticancer drugs. These illustrate library focusing strategies.

Combinatorial fabrication and screening of organic light-emitting device arrays

NASA Astrophysics Data System (ADS)

Shinar, Joseph; Shinar, Ruth; Zhou, Zhaoqun

2007-11-01

The combinatorial fabrication and screening of 2-dimensional (2-d) small molecular UV-violet organic light-emitting device (OLED) arrays, 1-d blue-to-red arrays, 1-d intense white OLED libraries, 1-d arrays to study Förster energy transfer in guest-host OLEDs, and 2-d arrays to study exciplex emission from OLEDs is described. The results demonstrate the power of combinatorial approaches for screening OLED materials and configurations, and for studying their basic properties.

Combinatorial chemistry on solid support in the search for central nervous system agents.

PubMed

Zajdel, Paweł; Pawłowski, Maciej; Martinez, Jean; Subra, Gilles

2009-08-01

The advent of combinatorial chemistry was one of the most important developments, that has significantly contributed to the drug discovery process. Within just a few years, its initial concept aimed at production of libraries containing huge number of compounds (thousands to millions), so called screening libraries, has shifted towards preparation of small and medium-sized rationally designed libraries. When applicable, the use of solid supports for the generation of libraries has been a real breakthrough in enhancing productivity. With a limited amount of resin and simple manual workups, the split/mix procedure may generate thousands of bead-tethered compounds. Beads can be chemically or physically encoded to facilitate the identification of a hit after the biological assay. Compartmentalization of solid supports using small reactors like teabags, kans or pellicular discrete supports like Lanterns resulted in powerful sort and combine technologies, relying on codes 'written' on the reactor, and thus reducing the need for automation and improving the number of compounds synthesized. These methods of solid-phase combinatorial chemistry have been recently supported by introduction of solid-supported reagents and scavenger resins. The first part of this review discusses the general premises of combinatorial chemistry and some methods used in the design of primary and focused combinatorial libraries. The aim of the second part is to present combinatorial chemistry methodologies aimed at discovering bioactive compounds acting on diverse GPCR involved in central nervous system disorders.

Targeted estrogen delivery reverses the metabolic syndrome

PubMed Central

Finan, Brian; Yang, Bin; Ottaway, Nickki; Stemmer, Kerstin; Müller, Timo D; Yi, Chun-Xia; Habegger, Kirk; Schriever, Sonja C; García-Cáceres, Cristina; Kabra, Dhiraj G; Hembree, Jazzminn; Holland, Jenna; Raver, Christine; Seeley, Randy J; Hans, Wolfgang; Irmler, Martin; Beckers, Johannes; de Angelis, Martin Hrabě; Tiano, Joseph P; Mauvais-Jarvis, Franck; Perez-Tilve, Diego; Pfluger, Paul; Zhang, Lianshan; Gelfanov, Vasily; DiMarchi, Richard D; Tschöp, Matthias H

2013-01-01

We report the development of a new combinatorial approach that allows for peptide-mediated selective tissue targeting of nuclear hormone pharmacology while eliminating adverse effects in other tissues. Specifically, we report the development of a glucagon-like peptide-1 (GLP-1)-estrogen conjugate that has superior sex-independent efficacy over either of the individual hormones alone to correct obesity, hyperglycemia and dyslipidemia in mice. The therapeutic benefits are driven by pleiotropic dual hormone action to improve energy, glucose and lipid metabolism, as shown by loss-of-function models and genetic action profiling. Notably, the peptide-based targeting strategy also prevents hallmark side effects of estrogen in male and female mice, such as reproductive endocrine toxicity and oncogenicity. Collectively, selective activation of estrogen receptors in GLP-1–targeted tissues produces unprecedented efficacy to enhance the metabolic benefits of GLP-1 agonism. This example of targeting the metabolic syndrome represents the discovery of a new class of therapeutics that enables synergistic co-agonism through peptide-based selective delivery of small molecules. Although our observations with the GLP-1–estrogen conjugate justify translational studies for diabetes and obesity, the multitude of other possible combinations of peptides and small molecules may offer equal promise for other diseases. PMID:23142820

Combinatorial invariants and covariants as tools for conical intersections.

PubMed

Ryb, Itai; Baer, Roi

2004-12-01

The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. (c) 2004 American Institute of Physics.

Natural products and combinatorial chemistry: back to the future.

PubMed

Ortholand, Jean-Yves; Ganesan, A

2004-06-01

The introduction of high-throughput synthesis and combinatorial chemistry has precipitated a global decline in the screening of natural products by the pharmaceutical industry. Some companies terminated their natural products program, despite the unproven success of the new technologies. This was a premature decision, as natural products have a long history of providing important medicinal agents. Furthermore, they occupy a complementary region of chemical space compared with the typical synthetic compound library. For these reasons, the interest in natural products has been rekindled. Various approaches have evolved that combine the power of natural products and organic chemistry, ranging from the combinatorial total synthesis of analogues to the exploration of natural product scaffolds and the design of completely unnatural molecules that resemble natural products in their molecular characteristics.

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

cDREM: inferring dynamic combinatorial gene regulation.

PubMed

Wise, Aaron; Bar-Joseph, Ziv

2015-04-01

Genes are often combinatorially regulated by multiple transcription factors (TFs). Such combinatorial regulation plays an important role in development and facilitates the ability of cells to respond to different stresses. While a number of approaches have utilized sequence and ChIP-based datasets to study combinational regulation, these have often ignored the combinational logic and the dynamics associated with such regulation. Here we present cDREM, a new method for reconstructing dynamic models of combinatorial regulation. cDREM integrates time series gene expression data with (static) protein interaction data. The method is based on a hidden Markov model and utilizes the sparse group Lasso to identify small subsets of combinatorially active TFs, their time of activation, and the logical function they implement. We tested cDREM on yeast and human data sets. Using yeast we show that the predicted combinatorial sets agree with other high throughput genomic datasets and improve upon prior methods developed to infer combinatorial regulation. Applying cDREM to study human response to flu, we were able to identify several combinatorial TF sets, some of which were known to regulate immune response while others represent novel combinations of important TFs.

Sentence Processing in an Artificial Language: Learning and Using Combinatorial Constraints

ERIC Educational Resources Information Center

Amato, Michael S.; MacDonald, Maryellen C.

2010-01-01

A study combining artificial grammar and sentence comprehension methods investigated the learning and online use of probabilistic, nonadjacent combinatorial constraints. Participants learned a small artificial language describing cartoon monsters acting on objects. Self-paced reading of sentences in the artificial language revealed comprehenders'…

A combinatorial histidine scanning library approach to engineer highly pH-dependent protein switches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murtaugh, Megan L.; Fanning, Sean W.; Sharma, Tressa M.

2012-09-05

There is growing interest in the development of protein switches, which are proteins whose function, such as binding a target molecule, can be modulated through environmental triggers. Efforts to engineer highly pH sensitive protein-protein interactions typically rely on the rational introduction of ionizable groups in the protein interface. Such experiments are typically time intensive and often sacrifice the protein's affinity at the permissive pH. The underlying thermodynamics of proton-linkage dictate that the presence of multiple ionizable groups, which undergo a pK{sub a} change on protein binding, are necessary to result in highly pH-dependent binding. To test this hypothesis, a novelmore » combinatorial histidine library was developed where every possible combination of histidine and wild-type residue is sampled throughout the interface of a model anti-RNase A single domain VHH antibody. Antibodies were coselected for high-affinity binding and pH-sensitivity using an in vitro, dual-function selection strategy. The resulting antibodies retained near wild-type affinity yet became highly sensitive to small decreases in pH, drastically decreasing their binding affinity, due to the incorporation of multiple histidine groups. Several trends were observed, such as histidine 'hot-spots,' which will help enhance the development of pH switch proteins as well as increase our understanding of the role of ionizable residues in protein interfaces. Overall, the combinatorial approach is rapid, general, and robust and should be capable of producing highly pH-sensitive protein affinity reagents for a number of different applications.« less

Recombinant organisms for production of industrial products

PubMed Central

Adrio, Jose-Luis

2010-01-01

A revolution in industrial microbiology was sparked by the discoveries of ther double-stranded structure of DNA and the development of recombinant DNA technology. Traditional industrial microbiology was merged with molecular biology to yield improved recombinant processes for the industrial production of primary and secondary metabolites, protein biopharmaceuticals and industrial enzymes. Novel genetic techniques such as metabolic engineering, combinatorial biosynthesis and molecular breeding techniques and their modifications are contributing greatly to the development of improved industrial processes. In addition, functional genomics, proteomics and metabolomics are being exploited for the discovery of novel valuable small molecules for medicine as well as enzymes for catalysis. The sequencing of industrial microbal genomes is being carried out which bodes well for future process improvement and discovery of new industrial products. PMID:21326937

Computation of Hypersonic Shock Wave Flows of Multi-Component Reactive Gas Mixtures Using the Generalized Boltzmann Equation

DTIC Science & Technology

2009-03-27

ones like the Lennard - Jones potential with established parameters for each gas (e.g. N2 and 02), and for inelastic collisions DSMC method employs...solution of the collision integral. Lennard - Jones potential with two free parameters is used to obtain the elastic cross-section of the gas molecules...and the so called "combinatory relations" are used to obtain parameters of Lennard - Jones potential for an interaction of molecule A with molecule B

Single cell systems biology by super-resolution imaging and combinatorial labeling

PubMed Central

Lubeck, Eric; Cai, Long

2012-01-01

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

Combinatorial evolution of site- and enantioselective catalysts for polyene epoxidation

NASA Astrophysics Data System (ADS)

Lichtor, Phillip A.; Miller, Scott J.

2012-12-01

Selectivity in the catalytic functionalization of complex molecules is a major challenge in chemical synthesis. The problem is magnified when there are several possible stereochemical outcomes and when similar functional groups occur repeatedly within the same molecule. Selective polyene oxidation provides an archetypical example of this challenge. Historically, enzymatic catalysis has provided the only precedents. Although non-enzymatic catalysts that meet some of these challenges became known, a comprehensive solution has remained elusive. Here, we describe low molecular weight peptide-based catalysts, discovered through a combinatorial synthesis and screening protocol, that exhibit site- and enantioselective oxidation of certain positions of various isoprenols. This diversity-based approach, which exhibits features reminiscent of the directed evolution of enzymes, delivers catalysts that compare favourably to the state-of-the-art for the asymmetric oxidation of these compounds. Moreover, the approach culminated in catalysts that exhibit alternative-site selectivity in comparison to oxidation catalysts previously described.

Concept of combinatorial de novo design of drug-like molecules by particle swarm optimization.

PubMed

Hartenfeller, Markus; Proschak, Ewgenij; Schüller, Andreas; Schneider, Gisbert

2008-07-01

We present a fast stochastic optimization algorithm for fragment-based molecular de novo design (COLIBREE, Combinatorial Library Breeding). The search strategy is based on a discrete version of particle swarm optimization. Molecules are represented by a scaffold, which remains constant during optimization, and variable linkers and side chains. Different linkers represent virtual chemical reactions. Side-chain building blocks were obtained from pseudo-retrosynthetic dissection of large compound databases. Here, ligand-based design was performed using chemically advanced template search (CATS) topological pharmacophore similarity to reference ligands as fitness function. A weighting scheme was included for particle swarm optimization-based molecular design, which permits the use of many reference ligands and allows for positive and negative design to be performed simultaneously. In a case study, the approach was applied to the de novo design of potential peroxisome proliferator-activated receptor subtype-selective agonists. The results demonstrate the ability of the technique to cope with large combinatorial chemistry spaces and its applicability to focused library design. The technique was able to perform exploitation of a known scheme and at the same time explorative search for novel ligands within the framework of a given molecular core structure. It thereby represents a practical solution for compound screening in the early hit and lead finding phase of a drug discovery project.

Particle-Based Microarrays of Oligonucleotides and Oligopeptides.

PubMed

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F Ralf; Breitling, Frank; Loeffler, Felix F

2014-10-28

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

Particle-Based Microarrays of Oligonucleotides and Oligopeptides

PubMed Central

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K.; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F. Ralf; Breitling, Frank; Loeffler, Felix F.

2014-01-01

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches. PMID:27600347

How to synthesize macrocycles efficiently by using virtual combinatorial libraries.

PubMed

Storm, Ole; Lüning, Ulrich

2002-02-15

The selection of different diimines 4 a-c by alkaline earth ions from a virtual combinatorial library (VCL) is described. The products were stabilized by reduction to the diamines 6 a-c; this allowed easy analysis. The library can be directed toward different target molecules 6 a-c upon addition of alkaline earth ions with different radii. Competition experiments show the possibility of synthesizing the macrocycles 6 a, 6 b, and 6 c simultaneously when using Mg(2+), Ca(2+), and Ba(2+) as template ions. The scope of this thermodynamically controlled, reversible approach for macrocycle syntheses is illustrated.

Application of combinatorial biocatalysis for a unique ring expansion of dihydroxymethylzearalenone.

PubMed

Rich, Joseph O; Budde, Cheryl L; McConeghey, Luke D; Cotterill, Ian C; Mozhaev, Vadim V; Singh, Sheo B; Goetz, Michael A; Zhao, Annie; Michels, Peter C; Khmelnitsky, Yuri L

2009-06-01

Combinatorial biocatalysis was applied to generate a diverse set of dihydroxymethylzearalenone analogs with modified ring structure. In one representative chemoenzymatic reaction sequence, dihydroxymethylzearalenone was first subjected to a unique enzyme-catalyzed oxidative ring opening reaction that creates two new carboxylic groups on the molecule. These groups served as reaction sites for further derivatization involving biocatalytic ring closure reactions with structurally diverse bifunctional reagents, including different diols and diamines. As a result, a library of cyclic bislactones and bislactams was created, with modified ring structures covering chemical space and structure activity relationships unattainable by conventional synthetic means.

Rational Design of Small Molecules Targeting Oncogenic Noncoding RNAs from Sequence.

PubMed

Disney, Matthew D; Angelbello, Alicia J

2016-12-20

The discovery of RNA catalysis in the 1980s and the dissemination of the human genome sequence at the start of this century inspired investigations of the regulatory roles of noncoding RNAs in biology. In fact, the Encyclopedia of DNA Elements (ENCODE) project has shown that only 1-2% of the human genome encodes protein, yet 75% is transcribed into RNA. Functional studies both preceding and following the ENCODE project have shown that these noncoding RNAs have important roles in regulating gene expression, developmental timing, and other critical functions. RNA's diverse roles are often a consequence of the various folds that it adopts. The single-stranded nature of the biopolymer enables it to adopt intramolecular folds with noncanonical pairings to lower its free energy. These folds can be scaffolds to bind proteins or to form frameworks to interact with other RNAs. Not surprisingly, dysregulation of certain noncoding RNAs has been shown to be causative of disease. Given this as the background, it is easy to see why it would be useful to develop methods that target RNA and manipulate its biology in rational and predictable ways. The antisense approach has afforded strategies to target RNAs via Watson-Crick base pairing and has typically focused on targeting partially unstructured regions of RNA. Small molecule strategies to target RNA would be desirable not only because compounds could be lead optimized via medicinal chemistry but also because structured regions within an RNA of interest could be targeted to directly interfere with RNA folds that contribute to disease. Additionally, small molecules have historically been the most successful drug candidates. Until recently, the ability to design small molecules that target non-ribosomal RNAs has been elusive, creating the perception that they are "undruggable". In this Account, approaches to demystify targeting RNA with small molecules are described. Rather than bulk screening for compounds that bind to singular targets, which is the purview of the pharmaceutical industry and academic institutions with high throughput screening facilities, we focus on methods that allow for the rational design of small molecules toward biological RNAs. One enabling and foundational technology that has been developed is two-dimensional combinatorial screening (2DCS), a library-versus-library selection approach that allows the identification of the RNA motif binding preferences of small molecules from millions of combinations. A landscape map of the 2DCS-defined and annotated RNA motif-small molecule interactions is then placed into Inforna, a computational tool that allows one to mine these interactions against an RNA of interest or an entire transcriptome. Indeed, this approach has been enabled by tools to annotate RNA structure from sequence, an invaluable asset to the RNA community and this work, and has allowed for the rational identification of "druggable" RNAs in a target agnostic fashion.

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

DNA-Encoded Solid-Phase Synthesis: Encoding Language Design and Complex Oligomer Library Synthesis.

PubMed

MacConnell, Andrew B; McEnaney, Patrick J; Cavett, Valerie J; Paegel, Brian M

2015-09-14

The promise of exploiting combinatorial synthesis for small molecule discovery remains unfulfilled due primarily to the "structure elucidation problem": the back-end mass spectrometric analysis that significantly restricts one-bead-one-compound (OBOC) library complexity. The very molecular features that confer binding potency and specificity, such as stereochemistry, regiochemistry, and scaffold rigidity, are conspicuously absent from most libraries because isomerism introduces mass redundancy and diverse scaffolds yield uninterpretable MS fragmentation. Here we present DNA-encoded solid-phase synthesis (DESPS), comprising parallel compound synthesis in organic solvent and aqueous enzymatic ligation of unprotected encoding dsDNA oligonucleotides. Computational encoding language design yielded 148 thermodynamically optimized sequences with Hamming string distance ≥ 3 and total read length <100 bases for facile sequencing. Ligation is efficient (70% yield), specific, and directional over 6 encoding positions. A series of isomers served as a testbed for DESPS's utility in split-and-pool diversification. Single-bead quantitative PCR detected 9 × 10(4) molecules/bead and sequencing allowed for elucidation of each compound's synthetic history. We applied DESPS to the combinatorial synthesis of a 75,645-member OBOC library containing scaffold, stereochemical and regiochemical diversity using mixed-scale resin (160-μm quality control beads and 10-μm screening beads). Tandem DNA sequencing/MALDI-TOF MS analysis of 19 quality control beads showed excellent agreement (<1 ppt) between DNA sequence-predicted mass and the observed mass. DESPS synergistically unites the advantages of solid-phase synthesis and DNA encoding, enabling single-bead structural elucidation of complex compounds and synthesis using reactions normally considered incompatible with unprotected DNA. The widespread availability of inexpensive oligonucleotide synthesis, enzymes, DNA sequencing, and PCR make implementation of DESPS straightforward, and may prompt the chemistry community to revisit the synthesis of more complex and diverse libraries.

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Recombinant organisms for production of industrial products.

PubMed

Adrio, Jose-Luis; Demain, Arnold L

2010-01-01

A revolution in industrial microbiology was sparked by the discoveries of ther double-stranded structure of DNA and the development of recombinant DNA technology. Traditional industrial microbiology was merged with molecular biology to yield improved recombinant processes for the industrial production of primary and secondary metabolites, protein biopharmaceuticals and industrial enzymes. Novel genetic techniques such as metabolic engineering, combinatorial biosynthesis and molecular breeding techniques and their modifications are contributing greatly to the development of improved industrial processes. In addition, functional genomics, proteomics and metabolomics are being exploited for the discovery of novel valuable small molecules for medicine as well as enzymes for catalysis. The sequencing of industrial microbal genomes is being carried out which bodes well for future process improvement and discovery of new industrial products. © 2010 Landes Bioscience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Visco, Donald Patrick, Jr.; Faulon, Jean-Loup Michel; Roe, Diana C.

This report is a comprehensive review of the field of molecular enumeration from early isomer counting theories to evolutionary algorithms that design molecules in silico. The core of the review is a detail account on how molecules are counted, enumerated, and sampled. The practical applications of molecular enumeration are also reviewed for chemical information, structure elucidation, molecular design, and combinatorial library design purposes. This review is to appear as a chapter in Reviews in Computational Chemistry volume 21 edited by Kenny B. Lipkowitz.

Rule-based spatial modeling with diffusing, geometrically constrained molecules.

PubMed

Gruenert, Gerd; Ibrahim, Bashar; Lenser, Thorsten; Lohel, Maiko; Hinze, Thomas; Dittrich, Peter

2010-06-07

We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.

Rule-based spatial modeling with diffusing, geometrically constrained molecules

PubMed Central

2010-01-01

Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly. PMID:20529264

Multifunctional combinatorial-designed nanoparticles for nucleic acid therapy

NASA Astrophysics Data System (ADS)

Amiji, Mansoor M.

2016-05-01

Recent advances in biomedical sciences, especially in the field of human genetics, is increasingly considered to facilitate a new frontier in development of novel disease-modifying therapeutics. One of major challenges in the development of nucleic acid therapeutics is efficient and specific delivery of the molecules to the target tissue and cell upon systemic administration. In this report, I discuss our strategy to develop combinatorial-designed multifunctional nanoparticle assemblies based on natural biocompatible and biodegradable polymers for nucleic acid delivery in: (1) overcoming tumor drug resistance and (2) genetic modulation of macrophage functional phenotype from M1 to M2 in treatment of inflammatory diseases.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

Signal dimensionality and the emergence of combinatorial structure.

PubMed

Little, Hannah; Eryılmaz, Kerem; de Boer, Bart

2017-11-01

In language, a small number of meaningless building blocks can be combined into an unlimited set of meaningful utterances. This is known as combinatorial structure. One hypothesis for the initial emergence of combinatorial structure in language is that recombining elements of signals solves the problem of overcrowding in a signal space. Another hypothesis is that iconicity may impede the emergence of combinatorial structure. However, how these two hypotheses relate to each other is not often discussed. In this paper, we explore how signal space dimensionality relates to both overcrowding in the signal space and iconicity. We use an artificial signalling experiment to test whether a signal space and a meaning space having similar topologies will generate an iconic system and whether, when the topologies differ, the emergence of combinatorially structured signals is facilitated. In our experiments, signals are created from participants' hand movements, which are measured using an infrared sensor. We found that participants take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory predictability, measures of variance, and Hidden Markov Models to measure the use of structure within the signals produced and found that when topologies do not match, then there is more evidence of combinatorial structure. The results from these experiments are interpreted in the context of the differences between the emergence of combinatorial structure in different linguistic modalities (speech and sign). Copyright © 2017 Elsevier B.V. All rights reserved.

Nucleophilic catalysis of acylhydrazone equilibration for protein-directed dynamic covalent chemistry

PubMed Central

Bhat, Venugopal T.; Caniard, Anne M.; Luksch, Torsten; Brenk, Ruth; Campopiano, Dominic J.; Greaney, Michael F.

2010-01-01

Dynamic covalent chemistry uses reversible chemical reactions to set up an equilibrating network of molecules at thermodynamic equilibrium, which can adjust its composition in response to any agent capable of altering the free energy of the system. When the target is a biological macromolecule, such as a protein, the process corresponds to the protein directing the synthesis of its own best ligand. Here, we demonstrate that reversible acylhydrazone formation is an effective chemistry for biological dynamic combinatorial library formation. In the presence of aniline as a nucleophilic catalyst, dynamic combinatorial libraries equilibrate rapidly at pH 6.2, are fully reversible, and may be switched on or off by means of a change in pH. We have interfaced these hydrazone dynamic combinatorial libraries with two isozymes from the glutathione S-transferase class of enzyme, and observed divergent amplification effects, where each protein selects the best-fitting hydrazone for the hydrophobic region of its active site. PMID:20489719

An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products.

PubMed

Johnston, Chad W; Skinnider, Michael A; Wyatt, Morgan A; Li, Xiang; Ranieri, Michael R M; Yang, Lian; Zechel, David L; Ma, Bin; Magarvey, Nathan A

2015-09-28

Bacterial natural products are a diverse and valuable group of small molecules, and genome sequencing indicates that the vast majority remain undiscovered. The prediction of natural product structures from biosynthetic assembly lines can facilitate their discovery, but highly automated, accurate, and integrated systems are required to mine the broad spectrum of sequenced bacterial genomes. Here we present a genome-guided natural products discovery tool to automatically predict, combinatorialize and identify polyketides and nonribosomal peptides from biosynthetic assembly lines using LC-MS/MS data of crude extracts in a high-throughput manner. We detail the directed identification and isolation of six genetically predicted polyketides and nonribosomal peptides using our Genome-to-Natural Products platform. This highly automated, user-friendly programme provides a means of realizing the potential of genetically encoded natural products.

Identification of a small molecule inhibitor of the aminoglycoside 6'-N-acetyltransferase type Ib [AAC(6')-Ib] using mixture-based combinatorial libraries.

PubMed

Tran, Tung; Chiem, Kevin; Jani, Saumya; Arivett, Brock A; Lin, David L; Lad, Rupali; Jimenez, Verónica; Farone, Mary B; Debevec, Ginamarie; Santos, Radleigh; Giulianotti, Marc; Pinilla, Clemencia; Tolmasky, Marcelo E

2018-05-01

The aminoglycoside, 6'-N-acetyltransferase type Ib [AAC(6')-Ib] is the most widely distributed enzyme among AAC(6')-I-producing Gram-negative pathogens and confers resistance to clinically relevant aminoglycosides, including amikacin. This enzyme is therefore an ideal target for enzymatic inhibitors that could overcome resistance to aminoglycosides. The search for inhibitors was carried out using mixture-based combinatorial libraries, the scaffold ranking approach, and the positional scanning strategy. A library with high inhibitory activity had pyrrolidine pentamine scaffold and was selected for further analysis. This library contained 738,192 compounds with functionalities derived from 26 different amino acids (R1, R2 and R3) and 42 different carboxylic acids (R4) in four R-group functionalities. The most active compounds all contained S-phenyl (R1 and R3) and S-hydromethyl (R2) functionalities at three locations and differed at the R4 position. The compound containing 3-phenylbutyl at R4 (compound 206) was a robust enzymatic inhibitor in vitro, in combination with amikacin it potentiated the inhibition of growth of three resistant bacteria in culture, and it improved survival when used as treatment of Galleria mellonella infected with aac(6')-Ib-harboring Klebsiella pneumoniae and Acinetobacter baumannii strains. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

An Integrated Microfluidic Processor for DNA-Encoded Combinatorial Library Functional Screening

PubMed Central

2017-01-01

DNA-encoded synthesis is rekindling interest in combinatorial compound libraries for drug discovery and in technology for automated and quantitative library screening. Here, we disclose a microfluidic circuit that enables functional screens of DNA-encoded compound beads. The device carries out library bead distribution into picoliter-scale assay reagent droplets, photochemical cleavage of compound from the bead, assay incubation, laser-induced fluorescence-based assay detection, and fluorescence-activated droplet sorting to isolate hits. DNA-encoded compound beads (10-μm diameter) displaying a photocleavable positive control inhibitor pepstatin A were mixed (1920 beads, 729 encoding sequences) with negative control beads (58 000 beads, 1728 encoding sequences) and screened for cathepsin D inhibition using a biochemical enzyme activity assay. The circuit sorted 1518 hit droplets for collection following 18 min incubation over a 240 min analysis. Visual inspection of a subset of droplets (1188 droplets) yielded a 24% false discovery rate (1166 pepstatin A beads; 366 negative control beads). Using template barcoding strategies, it was possible to count hit collection beads (1863) using next-generation sequencing data. Bead-specific barcodes enabled replicate counting, and the false discovery rate was reduced to 2.6% by only considering hit-encoding sequences that were observed on >2 beads. This work represents a complete distributable small molecule discovery platform, from microfluidic miniaturized automation to ultrahigh-throughput hit deconvolution by sequencing. PMID:28199790

An Integrated Microfluidic Processor for DNA-Encoded Combinatorial Library Functional Screening.

PubMed

MacConnell, Andrew B; Price, Alexander K; Paegel, Brian M

2017-03-13

DNA-encoded synthesis is rekindling interest in combinatorial compound libraries for drug discovery and in technology for automated and quantitative library screening. Here, we disclose a microfluidic circuit that enables functional screens of DNA-encoded compound beads. The device carries out library bead distribution into picoliter-scale assay reagent droplets, photochemical cleavage of compound from the bead, assay incubation, laser-induced fluorescence-based assay detection, and fluorescence-activated droplet sorting to isolate hits. DNA-encoded compound beads (10-μm diameter) displaying a photocleavable positive control inhibitor pepstatin A were mixed (1920 beads, 729 encoding sequences) with negative control beads (58 000 beads, 1728 encoding sequences) and screened for cathepsin D inhibition using a biochemical enzyme activity assay. The circuit sorted 1518 hit droplets for collection following 18 min incubation over a 240 min analysis. Visual inspection of a subset of droplets (1188 droplets) yielded a 24% false discovery rate (1166 pepstatin A beads; 366 negative control beads). Using template barcoding strategies, it was possible to count hit collection beads (1863) using next-generation sequencing data. Bead-specific barcodes enabled replicate counting, and the false discovery rate was reduced to 2.6% by only considering hit-encoding sequences that were observed on >2 beads. This work represents a complete distributable small molecule discovery platform, from microfluidic miniaturized automation to ultrahigh-throughput hit deconvolution by sequencing.

Poisson Statistics of Combinatorial Library Sampling Predict False Discovery Rates of Screening

PubMed Central

2017-01-01

Microfluidic droplet-based screening of DNA-encoded one-bead-one-compound combinatorial libraries is a miniaturized, potentially widely distributable approach to small molecule discovery. In these screens, a microfluidic circuit distributes library beads into droplets of activity assay reagent, photochemically cleaves the compound from the bead, then incubates and sorts the droplets based on assay result for subsequent DNA sequencing-based hit compound structure elucidation. Pilot experimental studies revealed that Poisson statistics describe nearly all aspects of such screens, prompting the development of simulations to understand system behavior. Monte Carlo screening simulation data showed that increasing mean library sampling (ε), mean droplet occupancy, or library hit rate all increase the false discovery rate (FDR). Compounds identified as hits on k > 1 beads (the replicate k class) were much more likely to be authentic hits than singletons (k = 1), in agreement with previous findings. Here, we explain this observation by deriving an equation for authenticity, which reduces to the product of a library sampling bias term (exponential in k) and a sampling saturation term (exponential in ε) setting a threshold that the k-dependent bias must overcome. The equation thus quantitatively describes why each hit structure’s FDR is based on its k class, and further predicts the feasibility of intentionally populating droplets with multiple library beads, assaying the micromixtures for function, and identifying the active members by statistical deconvolution. PMID:28682059

Selective host molecules obtained by dynamic adaptive chemistry.

PubMed

Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

2014-02-17

Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Universal strategies for the DNA-encoding of libraries of small molecules using the chemical ligation of oligonucleotide tags

PubMed Central

Litovchick, Alexander; Clark, Matthew A; Keefe, Anthony D

2014-01-01

The affinity-mediated selection of large libraries of DNA-encoded small molecules is increasingly being used to initiate drug discovery programs. We present universal methods for the encoding of such libraries using the chemical ligation of oligonucleotides. These methods may be used to record the chemical history of individual library members during combinatorial synthesis processes. We demonstrate three different chemical ligation methods as examples of information recording processes (writing) for such libraries and two different cDNA-generation methods as examples of information retrieval processes (reading) from such libraries. The example writing methods include uncatalyzed and Cu(I)-catalyzed alkyne-azide cycloadditions and a novel photochemical thymidine-psoralen cycloaddition. The first reading method “relay primer-dependent bypass” utilizes a relay primer that hybridizes across a chemical ligation junction embedded in a fixed-sequence and is extended at its 3′-terminus prior to ligation to adjacent oligonucleotides. The second reading method “repeat-dependent bypass” utilizes chemical ligation junctions that are flanked by repeated sequences. The upstream repeat is copied prior to a rearrangement event during which the 3′-terminus of the cDNA hybridizes to the downstream repeat and polymerization continues. In principle these reading methods may be used with any ligation chemistry and offer universal strategies for the encoding (writing) and interpretation (reading) of DNA-encoded chemical libraries. PMID:25483841

Strategies for the construction and use of peptide and antibody libraries displayed on phages.

PubMed

Pini, Alessandro; Giuliani, Andrea; Ricci, Claudia; Runci, Ylenia; Bracci, Luisa

2004-12-01

Combinatorial chemistry and biology have become popular methods for the identification of bio-active molecules in drug discovery. A widely used technique in combinatorial biology is "phage display", by which peptides, antibody fragments and enzymes are displayed on the surface of bacteriophages, and can be selected by simple procedures of biopanning. The construction of phage libraries of peptides or antibody fragments provides a huge source of ligands and bio-active molecules that can be isolated from the library without laborious studies on antigen characteristics and prediction of ligand structure. This "irrational" approach for the construction of new drugs is extremely rapid and is now used by thousands of laboratories world-wide. The bottleneck in this procedure is the availability of large reliable libraries that can be used repeatedly over the years without loss of ligand expression and diversity. Construction of personalized libraries is therefore important for public and private laboratories engaged in the isolation of specific molecules for therapeutic or diagnostic use. Here we report the general strategies for constructing large phage peptide and antibody libraries, based on the experience of researchers who built the world's most widely used libraries. Particular attention is paid to advanced strategies for the construction, preservation and panning.

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

PubMed

Zhou, Yikang; Li, Gang; Dong, Junkai; Xing, Xin-Hui; Dai, Junbiao; Zhang, Chong

2018-05-01

Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using β-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

A Combinatorial Interplay Among the 1-Aminocyclopropane-1-carboxylate Isoforms Regulates Ethylene Biosynthesis in Arabidopsis thaliana

USDA-ARS?s Scientific Manuscript database

Ethylene (C2H4) is a unique plant-signaling molecule that regulates numerous developmental processes. The key enzyme in the two-step biosynthetic pathway of ethylene is 1-aminocyclopropane-1-carboxylate synthase (ACS), which catalyzes the conversion of Sadenosyl-methionine (AdoMet) to ACC, the precu...

JavaGenes: Evolving Graphs with Crossover

NASA Technical Reports Server (NTRS)

Globus, Al; Atsatt, Sean; Lawton, John; Wipke, Todd

2000-01-01

Genetic algorithms usually use string or tree representations. We have developed a novel crossover operator for a directed and undirected graph representation, and used this operator to evolve molecules and circuits. Unlike strings or trees, a single point in the representation cannot divide every possible graph into two parts, because graphs may contain cycles. Thus, the crossover operator is non-trivial. A steady-state, tournament selection genetic algorithm code (JavaGenes) was written to implement and test the graph crossover operator. All runs were executed by cycle-scavagging on networked workstations using the Condor batch processing system. The JavaGenes code has evolved pharmaceutical drug molecules and simple digital circuits. Results to date suggest that JavaGenes can evolve moderate sized drug molecules and very small circuits in reasonable time. The algorithm has greater difficulty with somewhat larger circuits, suggesting that directed graphs (circuits) are more difficult to evolve than undirected graphs (molecules), although necessary differences in the crossover operator may also explain the results. In principle, JavaGenes should be able to evolve other graph-representable systems, such as transportation networks, metabolic pathways, and computer networks. However, large graphs evolve significantly slower than smaller graphs, presumably because the space-of-all-graphs explodes combinatorially with graph size. Since the representation strongly affects genetic algorithm performance, adding graphs to the evolutionary programmer's bag-of-tricks should be beneficial. Also, since graph evolution operates directly on the phenotype, the genotype-phenotype translation step, common in genetic algorithm work, is eliminated.

The combinatorial PP1-binding consensus Motif (R/K)x( (0,1))V/IxFxx(R/K)x(R/K) is a new apoptotic signature.

PubMed

Godet, Angélique N; Guergnon, Julien; Maire, Virginie; Croset, Amélie; Garcia, Alphonse

2010-04-01

Previous studies established that PP1 is a target for Bcl-2 proteins and an important regulator of apoptosis. The two distinct functional PP1 consensus docking motifs, R/Kx((0,1))V/IxF and FxxR/KxR/K, involved in PP1 binding and cell death were previously characterized in the BH1 and BH3 domains of some Bcl-2 proteins. In this study, we demonstrate that DPT-AIF(1), a peptide containing the AIF(562-571) sequence located in a c-terminal domain of AIF, is a new PP1 interacting and cell penetrating molecule. We also showed that DPT-AIF(1) provoked apoptosis in several human cell lines. Furthermore, DPT-APAF(1) a bi-partite cell penetrating peptide containing APAF-1(122-131), a non penetrating sequence from APAF-1 protein, linked to our previously described DPT-sh1 peptide shuttle, is also a PP1-interacting death molecule. Both AIF(562-571) and APAF-1(122-131) sequences contain a common R/Kx((0,1))V/IxFxxR/KxR/K motif, shared by several proteins involved in control of cell survival pathways. This motif combines the two distinct PP1c consensus docking motifs initially identified in some Bcl-2 proteins. Interestingly DPT-AIF(2) and DPT-APAF(2) that carry a F to A mutation within this combinatorial motif, no longer exhibited any PP1c binding or apoptotic effects. Moreover the F to A mutation in DPT-AIF(2) also suppressed cell penetration. These results indicate that the combinatorial PP1c docking motif R/Kx((0,1))V/IxFxxR/KxR/K, deduced from AIF(562-571) and APAF-1(122-131) sequences, is a new PP1c-dependent Apoptotic Signature. This motif is also a new tool for drug design that could be used to characterize potential anti-tumour molecules.

Tunable Gas Sensing Gels by Cooperative Assembly

PubMed Central

Hussain, Abid; Semeano, Ana T. S.; Palma, Susana I. C. J.; Pina, Ana S.; Almeida, José; Medrado, Bárbara F.; Pádua, Ana C. C. S.; Carvalho, Ana L.; Dionísio, Madalena; Li, Rosamaria W. C.; Gamboa, Hugo; Ulijn, Rein V.; Gruber, Jonas; Roque, Ana C. A.

2017-01-01

The cooperative assembly of biopolymers and small molecules can yield functional materials with precisely tunable properties. Here, the fabrication, characterization, and use of multicomponent hybrid gels as selective gas sensors are reported. The gels are composed of liquid crystal droplets self-assembled in the presence of ionic liquids, which further coassemble with biopolymers to form stable matrices. Each individual component can be varied and acts cooperatively to tune gels’ structure and function. The unique molecular environment in hybrid gels is explored for supramolecular recognition of volatile compounds. Gels with distinct compositions are used as optical and electrical gas sensors, yielding a combinatorial response conceptually mimicking olfactory biological systems, and tested to distinguish volatile organic compounds and to quantify ethanol in automotive fuel. The gel response is rapid, reversible, and reproducible. These robust, versatile, modular, pliant electro-optical soft materials possess new possibilities in sensing triggered by chemical and physical stimuli. PMID:28747856

Targeting aerobic glycolysis: 3-bromopyruvate as a promising anticancer drug.

PubMed

Cardaci, Simone; Desideri, Enrico; Ciriolo, Maria Rosa

2012-02-01

The Warburg effect refers to the phenomenon whereby cancer cells avidly take up glucose and produce lactic acid under aerobic conditions. Although the molecular mechanisms underlying tumor reliance on glycolysis remains not completely clear, its inhibition opens feasible therapeutic windows for cancer treatment. Indeed, several small molecules have emerged by combinatorial studies exhibiting promising anticancer activity both in vitro and in vivo, as a single agent or in combination with other therapeutic modalities. Therefore, besides reviewing the alterations of glycolysis that occur with malignant transformation, this manuscript aims at recapitulating the most effective pharmacological therapeutics of its targeting. In particular, we describe the principal mechanisms of action and the main targets of 3-bromopyruvate, an alkylating agent with impressive antitumor effects in several models of animal tumors. Moreover, we discuss the chemo-potentiating strategies that would make unparalleled the putative therapeutic efficacy of its use in clinical settings.

Magnetic separation: its application in mining, waste purification, medicine, biochemistry and chemistry.

PubMed

Iranmanesh, M; Hulliger, J

2017-10-02

The use of strong magnetic field gradients and high magnetic fields generated by permanent magnets or superconducting coils has found applications in many fields such as mining, solid state chemistry, biochemistry and medical research. Lab scale or industrial implementations involve separation of macro- and nanoparticles, cells, proteins, and macromolecules down to small molecules and ions. Most promising are those attempts where the object to be separated is attached to a strong magnetic nanoparticle. Here, all kinds of specific affinity interactions are used to attach magnetic carrier particles to mainly objects of biological interest. Other attempts use a strong paramagnetic suspension for the separation of purely diamagnetic objects, such as bio-macromolecules or heavy metals. The application of magnetic separation to superconducting inorganic phases is of particular interest in combination with ceramic combinatorial chemistry to generate a library of e.g. cuprate superconductors.

Development of Cell-SELEX Technology and Its Application in Cancer Diagnosis and Therapy.

PubMed

Chen, Man; Yu, Yuanyuan; Jiang, Feng; Zhou, Junwei; Li, Yongshu; Liang, Chao; Dang, Lei; Lu, Aiping; Zhang, Ge

2016-12-10

SELEX (systematic evolution of ligands by exponential enrichment) is a process involving the progressive isolation of high selective ssDNA/RNA from a combinatorial single-stranded oligonucleotide library through repeated rounds of binding, partitioning and amplification. SELEX-derived single-stranded DNA/RNA molecules, called aptamers, are selected against a wide range of targets, including purified proteins, live cells, tissues, microorganisms, small molecules and so on. With the development of SELEX technology over the last two decades, various modified SELEX processes have been arisen. A majority of aptamers are selected against purified proteins through traditional SELEX. Unfortunately, more and more evidence showed aptamers selected against purified membrane proteins failed to recognize their targets in live cells. Cell-SELEX could develop aptamers against a particular target cell line to discriminate this cell line from others. Therefore, cell-SELEX has been widely used to select aptamers for the application of both diagnosis and therapy of various diseases, especially for cancer. In this review, the advantages and limitations of cell-SELEX and SELEX against purified protein will be compared. Various modified cell-SELEX techniques will be summarized, and application of cell-SELEX in cancer diagnosis and therapy will be discussed.

Development of Cell-SELEX Technology and Its Application in Cancer Diagnosis and Therapy

PubMed Central

Chen, Man; Yu, Yuanyuan; Jiang, Feng; Zhou, Junwei; Li, Yongshu; Liang, Chao; Dang, Lei; Lu, Aiping; Zhang, Ge

2016-01-01

SELEX (systematic evolution of ligands by exponential enrichment) is a process involving the progressive isolation of high selective ssDNA/RNA from a combinatorial single-stranded oligonucleotide library through repeated rounds of binding, partitioning and amplification. SELEX-derived single-stranded DNA/RNA molecules, called aptamers, are selected against a wide range of targets, including purified proteins, live cells, tissues, microorganisms, small molecules and so on. With the development of SELEX technology over the last two decades, various modified SELEX processes have been arisen. A majority of aptamers are selected against purified proteins through traditional SELEX. Unfortunately, more and more evidence showed aptamers selected against purified membrane proteins failed to recognize their targets in live cells. Cell-SELEX could develop aptamers against a particular target cell line to discriminate this cell line from others. Therefore, cell-SELEX has been widely used to select aptamers for the application of both diagnosis and therapy of various diseases, especially for cancer. In this review, the advantages and limitations of cell-SELEX and SELEX against purified protein will be compared. Various modified cell-SELEX techniques will be summarized, and application of cell-SELEX in cancer diagnosis and therapy will be discussed. PMID:27973403

A methodology to find the elementary landscape decomposition of combinatorial optimization problems.

PubMed

Chicano, Francisco; Whitley, L Darrell; Alba, Enrique

2011-01-01

A small number of combinatorial optimization problems have search spaces that correspond to elementary landscapes, where the objective function f is an eigenfunction of the Laplacian that describes the neighborhood structure of the search space. Many problems are not elementary; however, the objective function of a combinatorial optimization problem can always be expressed as a superposition of multiple elementary landscapes if the underlying neighborhood used is symmetric. This paper presents theoretical results that provide the foundation for algebraic methods that can be used to decompose the objective function of an arbitrary combinatorial optimization problem into a sum of subfunctions, where each subfunction is an elementary landscape. Many steps of this process can be automated, and indeed a software tool could be developed that assists the researcher in finding a landscape decomposition. This methodology is then used to show that the subset sum problem is a superposition of two elementary landscapes, and to show that the quadratic assignment problem is a superposition of three elementary landscapes.

Development of a large peptoid-DOTA combinatorial library.

PubMed

Singh, Jaspal; Lopes, Daniel; Gomika Udugamasooriya, D

2016-09-01

Conventional one-bead one-compound (OBOC) library synthesis is typically used to identify molecules with therapeutic value. The design and synthesis of OBOC libraries that contain molecules with imaging or even potentially therapeutic and diagnostic capacities (e.g. theranostic agents) has been overlooked. The development of a therapeutically active molecule with a built-in imaging component for a certain target is a daunting task, and structure-based rational design might not be the best approach. We hypothesize to develop a combinatorial library with potentially therapeutic and imaging components fused together in each molecule. Such molecules in the library can be used to screen, identify, and validate as direct theranostic candidates against targets of interest. As the first step in achieving that aim, we developed an on-bead library of 153,600 Peptoid-DOTA compounds in which the peptoids are the target-recognizing and potentially therapeutic components and the DOTA is the imaging component. We attached the DOTA scaffold to TentaGel beads using one of the four arms of DOTA, and we built a diversified 6-mer peptoid library on the remaining three arms. We evaluated both the synthesis and the mass spectrometric sequencing capacities of the test compounds and of the final library. The compounds displayed unique ionization patterns including direct breakages of the DOTA scaffold into two units, allowing clear decoding of the sequences. Our approach provides a facile synthesis method for the complete on-bead development of large peptidomimetic-DOTA libraries for screening against biological targets for the identification of potential theranostic agents in the future. © 2016 The Authors. Biopolymers Published by Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 673-684, 2016. © 2016 The Authors. Biopolymers Published by Wiley Periodicals, Inc.

Rediscovering natural products as a source of new drugs.

PubMed

Koehn, Frank E; Carter, Guy T

2005-04-01

Extract: Since the very beginnings of human medicine, physicians have relied on chemical compounds produced by animals, plants and microorganisms, so-called natural products, to treat diseases. Natural products are directly or indirectly responsible for roughly one-half of all drugs currently in use. Of the 877 small-molecule new drug molecules introduced between 1981 and 2002, 49% were natural products or natural product analogs. Despite the great success of the 70s and 80s, the pharmaceutical industry de-emphasized natural products research during the following decade. In this article, we examine the underlying reasons for the decline, and assess future prospects for natural products research in drug discovery. In the 1990s, major pharmaceutical companies moved to a lead-finding strategy based on High Throughput Screening (HTS) of very large collections (libraries) of synthetic compounds. The move arose from the belief that techniques such as combinatorial chemistry could produce larger, more cost-effective libraries with improved hit rates and quality. Additionally, advances in molecular biology, cellular biology and genomics dramatically increased the number of molecular targets, prompting shorter drug discovery timelines. In today's drug discovery environment, rapid screening and identification of potential drug molecules is essential for success. This puts traditional natural products-based programs, with their reliance on the lengthy processes of the screening of extracts library, bioassay-guided isolation of the active components, structure elucidation and subsequent production scale-up, at a competitive disadvantage.

Jeffamine derivatized TentaGel beads and poly(dimethylsiloxane) microbead cassettes for ultrahigh-throughput in situ releasable solution-phase cell-based screening of one-bead-one-compound combinatorial small molecule libraries.

PubMed

Townsend, Jared B; Shaheen, Farzana; Liu, Ruiwu; Lam, Kit S

2010-09-13

A method to efficiently immobilize and partition large quantities of microbeads in an array format in microfabricated poly(dimethylsiloxane) (PDMS) cassette for ultrahigh-throughput in situ releasable solution-phase cell-based screening of one-bead-one-compound (OBOC) combinatorial libraries is described. Commercially available Jeffamine triamine T-403 (∼440 Da) was derivatized such that two of its amino groups were protected by Fmoc and the remaining amino group capped with succinic anhydride to generate a carboxyl group. This resulting trifunctional hydrophilic polymer was then sequentially coupled two times to the outer layer of topologically segregated bilayer TentaGel (TG) beads with solid phase peptide synthesis chemistry resulting in beads with increased loading capacity, hydrophilicity, and porosity at the outer layer. We have found that such bead configuration can facilitate ultrahigh-throughput in situ releasable solution-phase screening of OBOC libraries. An encoded releasable OBOC small molecule library was constructed on Jeffamine derivatized TG beads with library compounds tethered to the outer layer via a disulfide linker and coding tags in the interior of the beads. Compound-beads could be efficiently loaded (5-10 min) into a 5 cm diameter Petri dish containing a 10,000-well PDMS microbead cassette, such that over 90% of the microwells were each filled with only one compound-bead. Jurkat T-lymphoid cancer cells suspended in Matrigel were then layered over the microbead cassette to immobilize the compound-beads. After 24 h of incubation at 37 °C, dithiothreitol was added to trigger the release of library compounds. Forty-eight hours later, MTT reporter assay was used to identify regions of reduced cell viability surrounding each positive bead. From a total of about 20,000 beads screened, 3 positive beads were detected and physically isolated for decoding. A strong consensus motif was identified for these three positive compounds. These compounds were resynthesized and found to be cytotoxic (IC(50) 50-150 μM) against two T-lymphoma cell lines and less so against the MDA-MB 231 breast cancer cell line. This novel ultrahigh-throughput OBOC releasable method can potentially be adapted to many existing 96- or 384-well solution-phase cell-based or biochemical assays.

Jeffamine Derivatized TentaGel Beads and PDMS Microbead Cassettes for Ultra-high Throughput in situ Releasable Solution-Phase Cell-based Screening of OBOC Combinatorial Small Molecule Libraries

PubMed Central

Townsend, Jared B.; Shaheen, Farzana; Liu, Ruiwu; Lam, Kit S.

2011-01-01

A method to efficiently immobilize and partition large quantities of microbeads in an array format in microfabricated polydimethylsiloxane (PDMS) cassette for high-throughput in situ releasable solution-phase cell-based screening of one-bead-one-compound (OBOC) combinatorial libraries is described. Commercially available Jeffamine triamine T-403 (∼440 Da) was derivatized such that two of its amino groups were protected by Fmoc and the remaining amino group capped with succinic anhydride to generate a carboxyl group. This resulting tri-functional hydrophilic polymer was then sequentially coupled two times to the outer layer of topologically segregated bilayer TentaGel (TG) beads with solid phase peptide synthesis chemistry, resulting in beads with increased loading capacity, hydrophilicity and porosity at the outer layer. We have found that such bead configuration can facilitate ultra high-throughput in situ releasable solution-phase screening of OBOC libraries. An encoded releasable OBOC small molecule library was constructed on Jeffamine derivatized TG beads with library compounds tethered to the outer layer via a disulfide linker and coding tags in the interior of the beads. Compound-beads could be efficiently loaded (5-10 minutes) into a 5 cm diameter Petri dish containing a 10,000-well PDMS microbead cassette, such that over 90% of the microwells were each filled with only one compound-bead. Jurkat T-lymphoid cancer cells suspended in Matrigel® were then layered over the microbead cassette to immobilize the compound-beads. After 24 hours of incubation at 37°C, dithiothreitol was added to trigger the release of library compounds. Forty-eight hours later, MTT reporter assay was used to identify regions of reduced cell viability surrounding each positive bead. From a total of about 20,000 beads screened, 3 positive beads were detected and physically isolated for decoding. A strong consensus motif was identified for these three positive compounds. These compounds were re-synthesized and found to be cytotoxic (IC50 50-150 μM) against two T-lymphoma cell lines and less so against the MDA-MB 231 breast cancer cell line. This novel ultra high-throughput OBOC releasable method can potentially be adapted to many existing 96- or 384-well solution-phase cell-based or biochemical assays. PMID:20593859

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

Quantum mechanical energy-based screening of combinatorially generated library of tautomers. TauTGen: a tautomer generator program.

PubMed

Harańczyk, Maciej; Gutowski, Maciej

2007-01-01

We describe a procedure of finding low-energy tautomers of a molecule. The procedure consists of (i) combinatorial generation of a library of tautomers, (ii) screening based on the results of geometry optimization of initial structures performed at the density functional level of theory, and (iii) final refinement of geometry for the top hits at the second-order Möller-Plesset level of theory followed by single-point energy calculations at the coupled cluster level of theory with single, double, and perturbative triple excitations. The library of initial structures of various tautomers is generated with TauTGen, a tautomer generator program. The procedure proved to be successful for these molecular systems for which common chemical knowledge had not been sufficient to predict the most stable structures.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data

PubMed Central

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/ PMID:26363020

Searching Fragment Spaces with feature trees.

PubMed

Lessel, Uta; Wellenzohn, Bernd; Lilienthal, Markus; Claussen, Holger

2009-02-01

Virtual combinatorial chemistry easily produces billions of compounds, for which conventional virtual screening cannot be performed even with the fastest methods available. An efficient solution for such a scenario is the generation of Fragment Spaces, which encode huge numbers of virtual compounds by their fragments/reagents and rules of how to combine them. Similarity-based searches can be performed in such spaces without ever fully enumerating all virtual products. Here we describe the generation of a huge Fragment Space encoding about 5 * 10(11) compounds based on established in-house synthesis protocols for combinatorial libraries, i.e., we encode practically evaluated combinatorial chemistry protocols in a machine readable form, rendering them accessible to in silico search methods. We show how such searches in this Fragment Space can be integrated as a first step in an overall workflow. It reduces the extremely huge number of virtual products by several orders of magnitude so that the resulting list of molecules becomes more manageable for further more elaborated and time-consuming analysis steps. Results of a case study are presented and discussed, which lead to some general conclusions for an efficient expansion of the chemical space to be screened in pharmaceutical companies.

Designing a multiroute synthesis scheme in combinatorial chemistry.

PubMed

Akavia, Adi; Senderowitz, Hanoch; Lerner, Alon; Shamir, Ron

2004-01-01

Solid-phase mix-and-split combinatorial synthesis is often used to produce large arrays of compounds to be tested during the various stages of the drug development process. This method can be represented by a synthesis graph in which nodes correspond to grow operations and arcs to beads transferred among the different reaction vessels. In this work, we address the problem of designing such a graph which maximizes the number of produced target compounds (namely, compounds out of an input library of desired molecules), given constraints on the number of beads used for library synthesis and on the number of reaction vessels available for concurrent grow steps. We present a heuristic based on a discrete search for solving this problem, test our solution on several data sets, explore its behavior, and show that it achieves good performance.

IR780 based nanomaterials for cancer imaging and photothermal, photodynamic and combinatorial therapies.

PubMed

Alves, Cátia G; Lima-Sousa, Rita; de Melo-Diogo, Duarte; Louro, Ricardo O; Correia, Ilídio J

2018-05-05

IR780, a molecule with a strong optical absorption and emission in the near infrared (NIR) region, is receiving an increasing attention from researchers working in the area of cancer treatment and imaging. Upon irradiation with NIR light, IR780 can produce reactive oxygen species as well as increase the body temperature, thus being a promising agent for application in cancer photodynamic and photothermal therapy. However, IR780's poor water solubility, fast clearance, acute toxicity and low tumor uptake may limit its use. To overcome such issues, several types of nanomaterials have been used to encapsulate and deliver IR780 to tumor cells. This mini-review is focused on the application of IR780 based nanostructures for cancer imaging, and photothermal, photodynamic and combinatorial therapies. Copyright © 2018 Elsevier B.V. All rights reserved.

Transmembrane delivery of anticancer drugs through self-assembly of cyclic peptide nanotubes

NASA Astrophysics Data System (ADS)

Chen, Jian; Zhang, Bei; Xia, Fei; Xie, Yunchang; Jiang, Sifan; Su, Rui; Lu, Yi; Wu, Wei

2016-03-01

Breaking the natural barriers of cell membranes achieves fast entry of therapeutics, which leads to enhanced efficacy and helps overcome multiple drug resistance. Herein, transmembrane delivery of a series of small molecule anticancer drugs was achieved by the construction of artificial transmembrane nanochannels formed by self-assembly of cyclic peptide (cyclo[Gln-(d-Leu-Trp)4-d-Leu], CP) nanotubes (CPNTs) in the lipid bilayers. Our in vitro study in liposomes indicated that the transport of molecules with sizes smaller than 1.0 nm, which is the internal diameter of the CPNTs, could be significantly enhanced by CPNTs in a size-selective and dose-dependent manner. Facilitated uptake of 5-fluorouracil (5-FU) was also confirmed in the BEL7402 cell line. On the contrary, CPs could facilitate neither the transport across liposomal membranes nor the uptake by cell lines of cytarabine, a counterevidence drug with a size of 1.1 nm. CPs had a very weak anticancer efficacy, but could significantly reduce the IC50 of 5-FU in BEL7402, HeLa and S180 cell lines. Analysis by a q test revealed that a combination of 5-FU and CP had a synergistic effect in BEL7402 at all CP levels, in S180 at CP levels higher than 64 μg mL-1, but not in HeLa, where an additive effect was observed. Temporarily, intratumoral injection is believed to be the best way for CP administration. In vivo imaging using 125I radio-labelled CP confirmed that CPNPTs were completely localized in the tumor tissues, and translocation to other tissues was negligible. In vivo anticancer efficacy was studied in the grafted S180 solid tumor model in mice, and the results indicated that tumor growth was greatly inhibited by the combinatory use of 5-FU and CP, and a synergistic effect was observed at CP doses of 0.25 mg per kg bw. It is concluded that facilitated transmembrane delivery of anticancer drugs with sizes smaller than 1.0 nm was achieved, and the synergistic anticancer effect was confirmed both in cell lines and in vivo through the combinatory use of 5-FU and CP.Breaking the natural barriers of cell membranes achieves fast entry of therapeutics, which leads to enhanced efficacy and helps overcome multiple drug resistance. Herein, transmembrane delivery of a series of small molecule anticancer drugs was achieved by the construction of artificial transmembrane nanochannels formed by self-assembly of cyclic peptide (cyclo[Gln-(d-Leu-Trp)4-d-Leu], CP) nanotubes (CPNTs) in the lipid bilayers. Our in vitro study in liposomes indicated that the transport of molecules with sizes smaller than 1.0 nm, which is the internal diameter of the CPNTs, could be significantly enhanced by CPNTs in a size-selective and dose-dependent manner. Facilitated uptake of 5-fluorouracil (5-FU) was also confirmed in the BEL7402 cell line. On the contrary, CPs could facilitate neither the transport across liposomal membranes nor the uptake by cell lines of cytarabine, a counterevidence drug with a size of 1.1 nm. CPs had a very weak anticancer efficacy, but could significantly reduce the IC50 of 5-FU in BEL7402, HeLa and S180 cell lines. Analysis by a q test revealed that a combination of 5-FU and CP had a synergistic effect in BEL7402 at all CP levels, in S180 at CP levels higher than 64 μg mL-1, but not in HeLa, where an additive effect was observed. Temporarily, intratumoral injection is believed to be the best way for CP administration. In vivo imaging using 125I radio-labelled CP confirmed that CPNPTs were completely localized in the tumor tissues, and translocation to other tissues was negligible. In vivo anticancer efficacy was studied in the grafted S180 solid tumor model in mice, and the results indicated that tumor growth was greatly inhibited by the combinatory use of 5-FU and CP, and a synergistic effect was observed at CP doses of 0.25 mg per kg bw. It is concluded that facilitated transmembrane delivery of anticancer drugs with sizes smaller than 1.0 nm was achieved, and the synergistic anticancer effect was confirmed both in cell lines and in vivo through the combinatory use of 5-FU and CP. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06804e

Structure-based design of combinatorial mutagenesis libraries

PubMed Central

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-01-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called “Structure-based Optimization of Combinatorial Mutagenesis” (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. PMID:25611189

Structure-based design of combinatorial mutagenesis libraries.

PubMed

Verma, Deeptak; Grigoryan, Gevorg; Bailey-Kellogg, Chris

2015-05-01

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called "Structure-based Optimization of Combinatorial Mutagenesis" (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states. © 2015 The Protein Society.

Micellar Surfactant Association in the Presence of a Glucoside-based Amphiphile Detected via High-Throughput Small Angle X-ray Scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanic, Vesna; Broadbent, Charlotte; DiMasi, Elaine

2016-11-14

The interactions of mixtures of anionic and amphoteric surfactants with sugar amphiphiles were studied via high throughput small angle x-ray scattering (SAXS). The sugar amphiphile was composed of Caprate, Caprylate, and Oleate mixed ester of methyl glucoside, MeGCCO. Optimal surfactant interactions are sought which have desirable physical properties, which must be identified in a cost effective manner that can access the large phase space of possible molecular combinations. X-ray scattering patterns obtained via high throughput SAXS can probe a combinatorial sample space and reveal the incorporation of MeGCCO into the micelles and the molecular associations between surfactant molecules. Such datamore » make it possible to efficiently assess the effects of the new amphiphiles in the formulation. A specific finding of this study is that formulations containing comparatively monodisperse and homogeneous surfactant mixtures can be reliably tuned by addition of NaCl, which swells the surfactant micelles with a monotonic dependence on salt concentration. In contrast, the presence of multiple different surfactants destroys clear correlations with NaCl concentration, even in otherwise similar series of formulations.« less

Ammonium and arsenic trioxide are potent facilitators of oligonucleotide function when delivered by gymnosis

PubMed Central

Zhang, Xiaowei; Castanotto, Daniela; Liu, Xueli; Shemi, Amotz; Stein, Cy A

2018-01-01

Abstract Oligonucleotide (ON) concentrations employed for therapeutic applications vary widely, but in general are high enough to raise significant concerns for off target effects and cellular toxicity. However, lowering ON concentrations reduces the chances of a therapeutic response, since typically relatively small amounts of ON are taken up by targeted cells in tissue culture. It is therefore imperative to identify new strategies to improve the concentration dependence of ON function. In this work, we have identified ammonium ion (NH4+) as a non-toxic potent enhancer of ON activity in the nucleus and cytoplasm following delivery by gymnosis. NH4+ is a metabolite that has been extensively employed as diuretic, expectorant, for the treatment of renal calculi and in a variety of other diseases. Enhancement of function can be found in attached and suspension cells, including in difficult-to-transfect Jurkat T and CEM T cells. We have also demonstrated that NH4+ can synergistically interact with arsenic trioxide (arsenite) to further promote ON function without producing any apparent increased cellular toxicity. These small, inexpensive, widely distributed molecules could be useful not only in laboratory experiments but potentially in therapeutic ON-based combinatorial strategy for clinical applications. PMID:29522198

The Importance of Being Tyrosine: Lessons in Molecular Recognition from Minimalist Synthetic Binding Proteins

PubMed Central

Koide, Shohei; Sidhu, Sachdev S.

2010-01-01

Summary Combinatorial libraries built with severely restricted chemical diversity have yielded highly functional synthetic binding proteins. Structural analyses of these minimalist binding sites have revealed the dominant role of large tyrosine residues for mediating molecular contacts and of small serine/glycine residues for providing space and flexibility. The concept of using limited residue types to construct optimized binding proteins mirrors findings in the field of small molecule drug development, where it has been proposed that most drugs are built from a limited set of side chains presented by diverse frameworks. The physicochemical properties of tyrosine make it the amino acid that is most effective for mediating molecular recognition, and protein engineers have taken advantage of these characteristics to build tyrosine-rich protein binding sites that outperform natural proteins in terms of affinity and specificity. Knowledge from preceding studies can be used to improve current designs, and thus, synthetic protein libraries will continue to evolve and improve. In the near future, it seems likely that synthetic binding proteins will supersede natural antibodies for most purposes, and moreover, synthetic proteins will enable many new applications beyond the scope of natural proteins. PMID:19298050

Highly Stereoselective Synthesis of a Compound Collection Based on the Bicyclic Scaffolds of Natural Products.

PubMed

Annamalai, Murali; Hristeva, Stanimira; Bielska, Martyna; Ortega, Raquel; Kumar, Kamal

2017-05-18

Despite the great contribution of natural products in the history of successful drug discovery, there are significant limitations that persuade the pharmaceutical industry to evade natural products in drug discovery research. The extreme scarcity as well as structural complexity of natural products renders their practical synthetic access and further modifications extremely challenging. Although other alternative technologies, particularly combinatorial chemistry, were embraced by the pharmaceutical industry to get quick access to a large number of small molecules with simple frameworks that often lack three-dimensional complexity, hardly any success was achieved in the discovery of lead molecules. To acquire chemotypes beholding structural features of natural products, for instance high sp ³ character, the synthesis of compound collections based on core-scaffolds of natural products presents a promising strategy. Here, we report a natural product inspired synthesis of six different chemotypes and their derivatives for drug discovery research. These bicyclic hetero- and carbocyclic scaffolds are highly novel, rich in sp ³ features and with ideal physicochemical properties to display drug likeness. The functional groups on the scaffolds were exploited further to generate corresponding compound collections. Synthesis of two of these collections exemplified with ca. 350 compounds are each also presented. The whole compound library is being exposed to various biological screenings within the European Lead Factory consortium.

Molecular computational elements encode large populations of small objects

NASA Astrophysics Data System (ADS)

Prasanna de Silva, A.; James, Mark R.; McKinney, Bernadine O. F.; Pears, David A.; Weir, Sheenagh M.

2006-10-01

Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1nm) and large `on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100μm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a `wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.

Molecular computational elements encode large populations of small objects.

PubMed

de Silva, A Prasanna; James, Mark R; McKinney, Bernadine O F; Pears, David A; Weir, Sheenagh M

2006-10-01

Since the introduction of molecular computation, experimental molecular computational elements have grown to encompass small-scale integration, arithmetic and games, among others. However, the need for a practical application has been pressing. Here we present molecular computational identification (MCID), a demonstration that molecular logic and computation can be applied to a widely relevant issue. Examples of populations that need encoding in the microscopic world are cells in diagnostics or beads in combinatorial chemistry (tags). Taking advantage of the small size (about 1 nm) and large 'on/off' output ratios of molecular logic gates and using the great variety of logic types, input chemical combinations, switching thresholds and even gate arrays in addition to colours, we produce unique identifiers for members of populations of small polymer beads (about 100 microm) used for synthesis of combinatorial libraries. Many millions of distinguishable tags become available. This method should be extensible to far smaller objects, with the only requirement being a 'wash and watch' protocol. Our focus on converting molecular science into technology concerning analog sensors, turns to digital logic devices in the present work.

Immobilized OBOC combinatorial bead array to facilitate multiplicative screening.

PubMed

Xiao, Wenwu; Bononi, Fernanda C; Townsend, Jared; Li, Yuanpei; Liu, Ruiwu; Lam, Kit S

2013-07-01

One-bead-one-compound (OBOC) combinatorial library screening has been broadly utilized for the last two decades to identify small molecules, peptides or peptidomimetics targeting variable screening probes such as cell surface receptors, bacteria, protein kinases, phosphatases, proteases etc. In previous screening methods, library beads were suspended in solution and screened against one single probe. Only the positive beads were tracked and isolated for additional screens and finally selected for chemical decoding. During this process, the remaining negative beads were not tracked and discarded. Here we report a novel bead immobilization method such that a bead library array can be conveniently prepared and screened in its entirety, sequentially many times with a series of distinct probes. This method not only allows us to increase the screening efficiency but also permits us to determine the binding profile of each and every library bead against a large number of target receptors. As proof of concept, we serially screened a random OBOC disulfide containing cyclic heptapeptide library with three water soluble dyes as model probes: malachite green, bromocresol purple and indigo carmine. This multiplicative screening approach resulted in a rapid determination of the binding profile of each and every bead respective to each of the three dyes. Beads that interacted with malachite green only, bromocresol purple only, or both indigo carmine and bromocresol purple were isolated, and their peptide sequences were determined with microsequencer. Ultimately, the novel OBOC multiplicative screening approach could play a key role in the enhancement of existing on-bead assays such as whole cell binding, bacteria binding, protein binding, posttranslational modifications etc. with increased efficiency, capacity, and specificity.

Virtual screening using combinatorial cyclic peptide libraries reveals protein interfaces readily targetable by cyclic peptides.

PubMed

Duffy, Fergal J; O'Donovan, Darragh; Devocelle, Marc; Moran, Niamh; O'Connell, David J; Shields, Denis C

2015-03-23

Protein-protein and protein-peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein-protein and protein-peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein-protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical "hot spot" interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.

Synthetic plant defense elicitors

PubMed Central

Bektas, Yasemin; Eulgem, Thomas

2015-01-01

To defend themselves against invading pathogens plants utilize a complex regulatory network that coordinates extensive transcriptional and metabolic reprogramming. Although many of the key players of this immunity-associated network are known, the details of its topology and dynamics are still poorly understood. As an alternative to forward and reverse genetic studies, chemical genetics-related approaches based on bioactive small molecules have gained substantial popularity in the analysis of biological pathways and networks. Use of such molecular probes can allow researchers to access biological space that was previously inaccessible to genetic analyses due to gene redundancy or lethality of mutations. Synthetic elicitors are small drug-like molecules that induce plant defense responses, but are distinct from known natural elicitors of plant immunity. While the discovery of some synthetic elicitors had already been reported in the 1970s, recent breakthroughs in combinatorial chemical synthesis now allow for inexpensive high-throughput screens for bioactive plant defense-inducing compounds. Along with powerful reverse genetics tools and resources available for model plants and crop systems, comprehensive collections of new synthetic elicitors will likely allow plant scientists to study the intricacies of plant defense signaling pathways and networks in an unparalleled fashion. As synthetic elicitors can protect crops from diseases, without the need to be directly toxic for pathogenic organisms, they may also serve as promising alternatives to conventional biocidal pesticides, which often are harmful for the environment, farmers and consumers. Here we are discussing various types of synthetic elicitors that have been used for studies on the plant immune system, their modes-of-action as well as their application in crop protection. PMID:25674095

Allosteric activation of the follicle-stimulating hormone (FSH) receptor by selective, nonpeptide agonists.

PubMed

Yanofsky, Stephen D; Shen, Emily S; Holden, Frank; Whitehorn, Erik; Aguilar, Barbara; Tate, Emily; Holmes, Christopher P; Scheuerman, Randall; MacLean, Derek; Wu, May M; Frail, Donald E; López, Francisco J; Winneker, Richard; Arey, Brian J; Barrett, Ronald W

2006-05-12

The pituitary glycoprotein hormones, luteinizing hormone and follicle-stimulating hormone (FSH), act through their cognate receptors to initiate a series of coordinated physiological events that results in germ cell maturation. Given the importance of FSH in regulating folliculogenesis and fertility, the development of FSH mimetics has been sought to treat infertility. Currently, purified and recombinant human FSH are the only FSH receptor (FSH-R) agonists available for infertility treatment. By screening unbiased combinatorial chemistry libraries, using a cAMP-responsive luciferase reporter assay, we discovered thiazolidinone agonists (EC50's = 20 microm) of the human FSH-R. Subsequent analog library screening and parallel synthesis optimization resulted in the identification of a potent agonist (EC50 = 2 nm) with full efficacy compared with FSH that was FSH-R-selective and -dependent. The compound mediated progesterone production in Y1 cells transfected with the human FSH-R (EC50 = 980 nm) and estradiol production from primary rat ovarian granulosa cells (EC50 = 10.5 nm). This and related compounds did not compete with FSH for binding to the FSH-R. Use of human FSH/thyroid-stimulating hormone (TSH) receptor chimeras suggested a novel mechanism for receptor activation through a binding site independent of the natural hormone binding site. This study is the first report of a high affinity small molecule agonist that activates a glycoprotein hormone receptor through an allosteric mechanism. The small molecule FSH receptor agonists described here could lead to an oral alternative to the current parenteral FSH treatments used clinically to induce ovarian stimulation for both in vivo and in vitro fertilization therapy.

Plant-derived flavone Apigenin: The small-molecule with promising activity against therapeutically resistant prostate cancer.

PubMed

Ganai, Shabir Ahmad

2017-01-01

Prostate cancer is the second leading cause of cancer related deaths in men in the United States. Mounting evidences suggest that in the pathophysiology of prostate cancer epigenetic modifications play a considerable role. Histone deacetylases (HDACs) have strong crosstalk with prostate cancer progression as they regulate various genes meant for tumour suppression. HDACs are emerging as striking molecular targets for anticancer drugs and therapy as their aberrant expression has been implicated in several cancers. Histone deacetylase inhibitors (HDACi), the small molecules interfering HDACs are the propitious chemotherapeutic agents as they tune the altered acetylation homeostasis for attenuating disease signalling. More than 20 HDACi have entered into the clinical trials and 4 have crossed the journey by gaining FDA approval for treating distinct haematological malignancies including multiple myeloma. Despite the therapeutic benefits, the synthetic HDACi cause detrimental side effects like atrial fibrillation, raising concerns regarding their applicability. Taking these facts into consideration the current article focused on plant-derived HDAC inhibitor Apigenin and its marvelous role in prostate cancer therapy. Moreover, the article sheds light on Apigenin induced apoptosis in various prostate cancer models. The defined inhibitor provokes apoptotic signaling in these models by multiple mechanisms like restraining HDACs, declining the levels of antiapoptotic proteins. Importantly, Apigenin hampers NF-κB signalling and down-modulates its regulated gene products for bringing therapeutic effect. Furthermore, Apigenin shows synergistic effect in combinatorial therapy and induces apoptosis even in prostate cancer models resistant to conventional therapeutic regimens. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors.

PubMed

Knehans, Tim; Schüller, Andreas; Doan, Danny N; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M S; Weil, Tanja; Vasudevan, Subhash G

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC(50) = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC(50) = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors

NASA Astrophysics Data System (ADS)

Knehans, Tim; Schüller, Andreas; Doan, Danny N.; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M. S.; Weil, Tanja; Vasudevan, Subhash G.

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC50 = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC50 = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

A Strategic Design of an Opto-Chemical Security Device with Resettable and Reconfigurable Password Based Upon Dual Channel Two-in-One Chemosensor Molecule.

PubMed

Majumdar, Tapas; Haldar, Basudeb; Mallick, Arabinda

2017-02-20

A simple strategy is proposed to design and develop an intelligent device based on dual channel ion responsive spectral properties of a commercially available molecule, harmine (HM). The system can process different sets of opto-chemical inputs generating different patterns as fluorescence outputs at specific wavelengths which can provide an additional level of protection exploiting both password and pattern recognitions. The proposed system could have the potential to come up with highly secured combinatorial locks at the molecular level that could pose valuable real time and on-site applications for user authentication.

A Strategic Design of an Opto-Chemical Security Device with Resettable and Reconfigurable Password Based Upon Dual Channel Two-in-One Chemosensor Molecule

NASA Astrophysics Data System (ADS)

Majumdar, Tapas; Haldar, Basudeb; Mallick, Arabinda

2017-02-01

A simple strategy is proposed to design and develop an intelligent device based on dual channel ion responsive spectral properties of a commercially available molecule, harmine (HM). The system can process different sets of opto-chemical inputs generating different patterns as fluorescence outputs at specific wavelengths which can provide an additional level of protection exploiting both password and pattern recognitions. The proposed system could have the potential to come up with highly secured combinatorial locks at the molecular level that could pose valuable real time and on-site applications for user authentication.

Emerging insights into resistance to BRAF inhibitors in melanoma.

PubMed

Bucheit, Amanda D; Davies, Michael A

2014-02-01

Melanoma is the most aggressive form of skin cancer. The treatment of patients with advanced melanoma is rapidly evolving due to an improved understanding of molecular drivers of this disease. Somatic mutations in BRAF are the most common genetic alteration found in these tumors. Recently, two different mutant-selective small molecule inhibitors of BRAF, vemurafenib and dabrafenib, have gained regulatory approval based on positive results in randomized phase III trials. While the development of these agents represents a landmark in the treatment of melanoma, the benefit of these agents is limited by the frequent and rapid onset of resistance. The identification of several molecular mechanisms of resistance to BRAF inhibitors is rapidly leading to the clinical testing of combinatorial strategies to improve the clinical benefit of these agents. These mechanisms, and the lessons learned from the initial testing of the BRAF inhibitors, provide multiple insights that may facilitate the development of targeted therapies against other oncogenic mutations in melanoma, as well as in other cancers. Copyright © 2013 Elsevier Inc. All rights reserved.

Engineered knottin peptides as diagnostics, therapeutics, and drug delivery vehicles.

PubMed

Kintzing, James R; Cochran, Jennifer R

2016-10-01

Inhibitor cystine-knots, also known as knottins, are a structural family of ultra-stable peptides with diverse functions. Knottins and related backbone-cyclized peptides called cyclotides contain three disulfide bonds connected in a particular arrangement that endows these peptides with high thermal, proteolytic, and chemical stability. Knottins have gained interest as candidates for non-invasive molecular imaging and for drug development as they can possess the pharmacological properties of small molecules and the target affinity and selectively of protein biologics. Naturally occurring knottins are clinically approved for treating chronic pain and GI disorders. Combinatorial methods are being used to engineer knottins that can bind to other clinically relevant targets in cancer, and inflammatory and cardiac disease. This review details recent examples of engineered knottin peptides; their use as molecular imaging agents, therapeutics, and drug delivery vehicles; modifications that can be introduced to improve peptide folding and bioactivity; and future perspectives and challenges in the field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Synthesis and cell-free cloning of DNA libraries using programmable microfluidics

PubMed Central

Yehezkel, Tuval Ben; Rival, Arnaud; Raz, Ofir; Cohen, Rafael; Marx, Zipora; Camara, Miguel; Dubern, Jean-Frédéric; Koch, Birgit; Heeb, Stephan; Krasnogor, Natalio; Delattre, Cyril; Shapiro, Ehud

2016-01-01

Microfluidics may revolutionize our ability to write synthetic DNA by addressing several fundamental limitations associated with generating novel genetic constructs. Here we report the first de novo synthesis and cell-free cloning of custom DNA libraries in sub-microliter reaction droplets using programmable digital microfluidics. Specifically, we developed Programmable Order Polymerization (POP), Microfluidic Combinatorial Assembly of DNA (M-CAD) and Microfluidic In-vitro Cloning (MIC) and applied them to de novo synthesis, combinatorial assembly and cell-free cloning of genes, respectively. Proof-of-concept for these methods was demonstrated by programming an autonomous microfluidic system to construct and clone libraries of yeast ribosome binding sites and bacterial Azurine, which were then retrieved in individual droplets and validated. The ability to rapidly and robustly generate designer DNA molecules in an autonomous manner should have wide application in biological research and development. PMID:26481354

Uncoupling of sgRNAs from their associated barcodes during PCR amplification of combinatorial CRISPR screens

PubMed Central

2018-01-01

Many implementations of pooled screens in mammalian cells rely on linking an element of interest to a barcode, with the latter subsequently quantitated by next generation sequencing. However, substantial uncoupling between these paired elements during lentiviral production has been reported, especially as the distance between elements increases. We detail that PCR amplification is another major source of uncoupling, and becomes more pronounced with increased amounts of DNA template molecules and PCR cycles. To lessen uncoupling in systems that use paired elements for detection, we recommend minimizing the distance between elements, using low and equal template DNA inputs for plasmid and genomic DNA during PCR, and minimizing the number of PCR cycles. We also present a vector design for conducting combinatorial CRISPR screens that enables accurate barcode-based detection with a single short sequencing read and minimal uncoupling. PMID:29799876

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

NASA Technical Reports Server (NTRS)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

PubMed

Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

Unitals and ovals of symmetric block designs in LDPC and space-time coding

NASA Astrophysics Data System (ADS)

Andriamanalimanana, Bruno R.

2004-08-01

An approach to the design of LDPC (low density parity check) error-correction and space-time modulation codes involves starting with known mathematical and combinatorial structures, and deriving code properties from structure properties. This paper reports on an investigation of unital and oval configurations within generic symmetric combinatorial designs, not just classical projective planes, as the underlying structure for classes of space-time LDPC outer codes. Of particular interest are the encoding and iterative (sum-product) decoding gains that these codes may provide. Various small-length cases have been numerically implemented in Java and Matlab for a number of channel models.

Target-induced formation of neuraminidase inhibitors from in vitro virtual combinatorial libraries

PubMed Central

Hochgürtel, Matthias; Kroth, Heiko; Piecha, Dorothea; Hofmann, Michael W.; Nicolau, Claude; Krause, Sonja; Schaaf, Otmar; Sonnenmoser, Gabriele; Eliseev, Alexey V.

2002-01-01

Neuraminidase, a key enzyme responsible for influenza virus propagation, has been used as a template for selective synthesis of small subsets of its own inhibitors from theoretically highly diverse dynamic combinatorial libraries. We show that the library building blocks, aldehydes and amines, form significant amounts of the library components resulting from their coupling by reductive amination only in the presence of the enzyme. The target amplifies the best hits at least 120-fold. The dynamic libraries synthesized and screened in such an in vitro virtual mode form the components that possess high inhibitory activity, as confirmed by enzyme assays with independently synthesized individual compounds. PMID:11891312

Concepts and applications of "natural computing" techniques in de novo drug and peptide design.

PubMed

Hiss, Jan A; Hartenfeller, Markus; Schneider, Gisbert

2010-05-01

Evolutionary algorithms, particle swarm optimization, and ant colony optimization have emerged as robust optimization methods for molecular modeling and peptide design. Such algorithms mimic combinatorial molecule assembly by using molecular fragments as building-blocks for compound construction, and relying on adaptation and emergence of desired pharmacological properties in a population of virtual molecules. Nature-inspired algorithms might be particularly suited for bioisosteric replacement or scaffold-hopping from complex natural products to synthetically more easily accessible compounds that are amenable to optimization by medicinal chemistry. The theory and applications of selected nature-inspired algorithms for drug design are reviewed, together with practical applications and a discussion of their advantages and limitations.

Combinatorial delivery of small interfering RNAs reduces RNAi efficacy by selective incorporation into RISC

PubMed Central

Castanotto, Daniela; Sakurai, Kumi; Lingeman, Robert; Li, Haitang; Shively, Louise; Aagaard, Lars; Soifer, Harris; Gatignol, Anne; Riggs, Arthur; Rossi, John J.

2007-01-01

Despite the great potential of RNAi, ectopic expression of shRNA or siRNAs holds the inherent risk of competition for critical RNAi components, thus altering the regulatory functions of some cellular microRNAs. In addition, specific siRNA sequences can potentially hinder incorporation of other siRNAs when used in a combinatorial approach. We show that both synthetic siRNAs and expressed shRNAs compete against each other and with the endogenous microRNAs for transport and for incorporation into the RNA induced silencing complex (RISC). The same siRNA sequences do not display competition when expressed from a microRNA backbone. We also show that TAR RNA binding protein (TRBP) is one of the sensors for selection and incorporation of the guide sequence of interfering RNAs. These findings reveal that combinatorial siRNA approaches can be problematic and have important implications for the methodology of expression and use of therapeutic interfering RNAs. PMID:17660190

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

PubMed Central

Pathan, Akbar Ali Khan; Panthi, Bhavana; Khan, Zahid; Koppula, Purushotham Reddy; Alanazi, Mohammed Saud; Sachchidanand; Parine, Narasimha Reddy; Chourasia, Mukesh

2016-01-01

Objective Kirsten rat sarcoma (K-Ras) protein is a member of Ras family belonging to the small guanosine triphosphatases superfamily. The members of this family share a conserved structure and biochemical properties, acting as binary molecular switches. The guanosine triphosphate-bound active K-Ras interacts with a range of effectors, resulting in the stimulation of downstream signaling pathways regulating cell proliferation, differentiation, and apoptosis. Efforts to target K-Ras have been unsuccessful until now, placing it among high-value molecules against which developing a therapy would have an enormous impact. K-Ras transduces signals when it binds to guanosine triphosphate by directly binding to downstream effector proteins, but in case of guanosine diphosphate-bound conformation, these interactions get disrupted. Methods In the present study, we targeted the nucleotide-binding site in the “on” and “off” state conformations of the K-Ras protein to find out suitable lead compounds. A structure-based virtual screening approach has been used to screen compounds from different databases, followed by a combinatorial fragment-based approach to design the apposite lead for the K-Ras protein. Results Interestingly, the designed compounds exhibit a binding preference for the “off” state over “on” state conformation of K-Ras protein. Moreover, the designed compounds’ interactions are similar to guanosine diphosphate and, thus, could presumably act as a potential lead for K-Ras. The predicted drug-likeness properties of these compounds suggest that these compounds follow the Lipinski’s rule of five and have tolerable absorption, distribution, metabolism, excretion and toxicity values. Conclusion Thus, through the current study, we propose targeting only “off” state conformations as a promising strategy for the design of reversible inhibitors to pharmacologically inhibit distinct conformations of K-Ras protein. PMID:27217775

Overcoming acquired BRAF inhibitor resistance in melanoma via targeted inhibition of Hsp90 with ganetespib.

PubMed

Acquaviva, Jaime; Smith, Donald L; Jimenez, John-Paul; Zhang, Chaohua; Sequeira, Manuel; He, Suqin; Sang, Jim; Bates, Richard C; Proia, David A

2014-02-01

Activating BRAF kinase mutations serve as oncogenic drivers in over half of all melanomas, a feature that has been exploited in the development of new molecularly targeted approaches to treat this disease. Selective BRAF(V600E) inhibitors, such as vemurafenib, typically induce initial, profound tumor regressions within this group of patients; however, durable responses have been hampered by the emergence of drug resistance. Here, we examined the activity of ganetespib, a small-molecule inhibitor of Hsp90, in melanoma lines harboring the BRAF(V600E) mutation. Ganetespib exposure resulted in the loss of mutant BRAF expression and depletion of mitogen-activated protein kinase and AKT signaling, resulting in greater in vitro potency and antitumor efficacy compared with targeted BRAF and MAP-ERK kinase (MEK) inhibitors. Dual targeting of Hsp90 and BRAF(V600E) provided combinatorial benefit in vemurafenib-sensitive melanoma cells in vitro and in vivo. Importantly, ganetespib overcame mechanisms of intrinsic and acquired resistance to vemurafenib, the latter of which was characterized by reactivation of extracellular signal-regulated kinase (ERK) signaling. Continued suppression of BRAF(V600E) by vemurafenib potentiated sensitivity to MEK inhibitors after acquired resistance had been established. Ganetespib treatment reduced, but not abolished, elevations in steady-state ERK activity. Profiling studies revealed that the addition of a MEK inhibitor could completely abrogate ERK reactivation in the resistant phenotype, with ganetespib displaying superior combinatorial activity over vemurafenib. Moreover, ganetespib plus the MEK inhibitor TAK-733 induced tumor regressions in vemurafenib-resistant xenografts. Overall these data highlight the potential of ganetespib as a single-agent or combination treatment in BRAF(V600E)-driven melanoma, particularly as a strategy to overcome acquired resistance to selective BRAF inhibitors.

Prospects and progress of atezolizumab in non-small cell lung cancer.

PubMed

Vansteenkiste, Johan; Wauters, Els; Park, Keunchil; Rittmeyer, Achim; Sandler, Alan; Spira, Alexander

2017-06-01

Immunotherapy has recently come to the forefront of oncology treatment as a potential means of combating cancer by restoring the body's adaptive cancer-immunity cycle. Atezolizumab is a monoclonal antibody agent that specifically targets programmed death ligand 1 (PD-L1), a key molecule in the cancer-immunity pathway, to block binding to its receptors PD-1 and B7.1. Areas covered: This review covers the role of atezolizumab in the treatment of non-small-cell lung cancer (NSCLC). Several studies have reported promising efficacy in this indication. The phase II FIR and BIRCH studies evaluated atezolizumab monotherapy across different lines of therapy in NSCLC selected by PD-L1 expression status. The randomized POPLAR and OAK trials of atezolizumab versus docetaxel in previously treated NSCLC reported improved efficacy in the atezolizumab arm. Several ongoing studies yet to report data are also described and treatment-related adverse events are discussed. Expert opinion: Clinical trials have shown that atezolizumab has a favorable risk-benefit ratio compared with standard chemotherapy in second-line treatment of non-oncogene-driven advanced NSCLC. Promising response rates and survival over 2 years has been reported in the first-line setting; however, more research is needed in this setting and in evaluating combinatorial strategies to treat NSCLC.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules.

PubMed

Kim, Seonghoon; Lee, Jumin; Jo, Sunhwan; Brooks, Charles L; Lee, Hui Sun; Im, Wonpil

2017-06-05

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Tankyrase as a Novel Molecular Target in Cancer and Fibrotic Diseases.

PubMed

Lakshmi, Tiruveedi Vijaya; Bale, Swarna; Khurana, Amit; Godugu, Chandraiah

2017-01-01

Tankyrases belong to a group of enzymes called poly ADP ribosyl polymerases (PARPs). With the advent of a new class of small molecule inhibitors of PARP for clinical use like OLAPARIB; that gained accelerated approval by the USFDA in treating ovarian and breast cancers, the horizons of the PARPs as a novel target in various disease conditions has risen. Tankyrases (PARP 5) are yet another class of PARPs that perform poly ADP ribosylation on different substrate proteins aiding in progression of many diseases like cancer, fibrosis, diabetes and neurological disorders even. Few of the substrates of Tankyrases are Telomeric Repeat binding Factor protein (TRF1), Axis Inhibitory protein (AXIN 1&2), Insulin Responsive Amino Peptidase (IRAP), Nuclear Mitotic Apparatus protein (NuMa), that become aberrantly active due to the apparent overexpression of the enzyme during hyper proliferative disease conditions like cancer, fibrosis and metabolic disorders like diabetes. Tankyrases intervene in many physiological processes like cell growth and survival by affecting the Wnt signaling pathways. On the other hand, these functions are overdone during cancer and fibrosis especially. The development of novel therapies for cancer is a never ending process pertaining to several issues associated with current anticancer drugs like development of drug resistance and toxicity. A fibrotic disease like lung fibrosis is a debilitating condition with limited treatment options and survival rate. Tankyrase inhibition by specific small molecule inhibitors can therefore become a good combinatorial or single treatment strategy in treating hyper proliferative diseases and diabetes. In light of all these concerns, this article aims to brief the role of Tankyrase and the relevance of its inhibition to overcome the hurdles faced by current treatment regimens. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

SPM for functional identification of individual biomolecules

NASA Astrophysics Data System (ADS)

Ros, Robert; Schwesinger, Falk; Padeste, Celestino; Plueckthun, Andreas; Anselmetti, Dario; Guentherodt, Hans-Joachim; Tiefenauer, Louis

1999-06-01

The identification of specific binding molecules is of increasing interest in the context of drug development based on combinatorial libraries. Scanning Probe Microscopy (SPM) is the method of choice to image and probe individual biomolecules on a surface. Functional identification of biomolecules is a first step towards screening on a single molecule level. As a model system we use recombinant single- chain Fv fragment (scFv) antibody molecules directed against the antigen fluorescein. The scFv's are covalently immobilized on a flat gold surface via the C-terminal cysteine, resulting in a high accessibility of the binding site. The antigen is immobilized covalently via a long hydrophilic spacer to the silicon nitride SPM-tip. This arrangement allows a direct measurement of binding forces. Thus, closely related antibody molecules differing in only one amino acid at their binding site could be distinguished. A novel SPM-software has been developed which combines imaging, force spectroscopic modes, and online analysis. This is a major prerequisite for future screening methods.

The film tells the story: Physical-chemical characteristics of IgG at the liquid-air interface.

PubMed

Koepf, Ellen; Schroeder, Rudolf; Brezesinski, Gerald; Friess, Wolfgang

2017-10-01

The presence of liquid-air interfaces in protein pharmaceuticals is known to negatively impact product stability. Nevertheless, the mechanisms behind interface-related protein aggregation are not yet fully understood. Little is known about the physical-chemical behavior of proteins adsorbed to the interface. Therefore, the combinatorial use of appropriate surface-sensitive analytical methods such as Langmuir trough experiments, Infrared Reflection-Absorption Spectroscopy (IRRAS), Brewster Angle Microscopy (BAM), and Atomic Force Microscopy (AFM) is highly expedient to uncover structures and events at the liquid-air interface directly. Concentration-dependent adsorption of a human immunoglobulin G (IgG) and characteristic surface-pressure/area isotherms substantiated the amphiphilic nature of the protein molecules as well as the formation of a compressible protein film at the liquid-air interface. Upon compression, the IgG molecules do not readily desorb but form a highly compressible interfacial film. IRRA spectra proved not only the presence of the protein at the interface, but also showed that the secondary structure does not change considerably during adsorption or compression. IRRAS experiments at different angles of incidence indicated that the film thickness and/or packing density increases upon compression. Furthermore, BAM images exposed the presence of a coherent but heterogeneous distribution of the protein at the interface. Topographical differences within the protein film after adsorption, compression and decompression were revealed using underwater AFM. The combinatorial use of physical-chemical, spectroscopic and microscopic methods provided useful insights into the liquid-air interfacial protein behavior and revealed the formation of a continuous but inhomogeneous film of native-like protein molecules whose topographical appearance is affected by compressive forces. Copyright © 2017 Elsevier B.V. All rights reserved.

Combination Across Domains: An MEG Investigation into the Relationship between Mathematical, Pictorial, and Linguistic Processing

PubMed Central

Bemis, Douglas K.; Pylkkänen, Liina

2013-01-01

Debates surrounding the evolution of language often hinge upon its relationship to cognition more generally and many investigations have attempted to demark the boundary between the two. Though results from these studies suggest that language may recruit domain-general mechanisms during certain types of complex processing, the domain-generality of basic combinatorial mechanisms that lie at the core of linguistic processing is still unknown. Our previous work (Bemis and Pylkkänen, 2011, 2012) used magnetoencephalography to isolate neural activity associated with the simple composition of an adjective and a noun (“red boat”) and found increased activity during this processing localized to the left anterior temporal lobe (lATL), ventro-medial prefrontal cortex (vmPFC), and left angular gyrus (lAG). The present study explores the domain-generality of these effects and their associated combinatorial mechanisms through two parallel non-linguistic combinatorial tasks designed to be as minimal and natural as the linguistic paradigm. In the first task, we used pictures of colored shapes to elicit combinatorial conceptual processing similar to that evoked by the linguistic expressions and find increased activity again localized to the vmPFC during combinatorial processing. This result suggests that a domain-general semantic combinatorial mechanism operates during basic linguistic composition, and that activity generated by its processing localizes to the vmPFC. In the second task, we recorded neural activity as subjects performed simple addition between two small numerals. Consistent with a wide array of recent results, we find no effects related to basic addition that coincide with our linguistic effects and instead find increased activity localized to the intraparietal sulcus. This result suggests that the scope of the previously identified linguistic effects is restricted to compositional operations and does not extend generally to all tasks that are merely similar in form. PMID:23293621

The Evolution of DNA-Templated Synthesis as a Tool for Materials Discovery.

PubMed

O'Reilly, Rachel K; Turberfield, Andrew J; Wilks, Thomas R

2017-10-17

Precise control over reactivity and molecular structure is a fundamental goal of the chemical sciences. Billions of years of evolution by natural selection have resulted in chemical systems capable of information storage, self-replication, catalysis, capture and production of light, and even cognition. In all these cases, control over molecular structure is required to achieve a particular function: without structural control, function may be impaired, unpredictable, or impossible. The search for molecules with a desired function is often achieved by synthesizing a combinatorial library, which contains many or all possible combinations of a set of chemical building blocks (BBs), and then screening this library to identify "successful" structures. The largest libraries made by conventional synthesis are currently of the order of 10 8 distinct molecules. To put this in context, there are 10 13 ways of arranging the 21 proteinogenic amino acids in chains up to 10 units long. Given that we know that a number of these compounds have potent biological activity, it would be highly desirable to be able to search them all to identify leads for new drug molecules. Large libraries of oligonucleotides can be synthesized combinatorially and translated into peptides using systems based on biological replication such as mRNA display, with selected molecules identified by DNA sequencing; but these methods are limited to BBs that are compatible with cellular machinery. In order to search the vast tracts of chemical space beyond nucleic acids and natural peptides, an alternative approach is required. DNA-templated synthesis (DTS) could enable us to meet this challenge. DTS controls chemical product formation by using the specificity of DNA hybridization to bring selected reactants into close proximity, and is capable of the programmed synthesis of many distinct products in the same reaction vessel. By making use of dynamic, programmable DNA processes, it is possible to engineer a system that can translate instructions coded as a sequence of DNA bases into a chemical structure-a process analogous to the action of the ribosome in living organisms but with the potential to create a much more chemically diverse set of products. It is also possible to ensure that each product molecule is tagged with its identifying DNA sequence. Compound libraries synthesized in this way can be exposed to selection against suitable targets, enriching successful molecules. The encoding DNA can then be amplified using the polymerase chain reaction and decoded by DNA sequencing. More importantly, the DNA instruction sequences can be mutated and reused during multiple rounds of amplification, translation, and selection. In other words, DTS could be used as the foundation for a system of synthetic molecular evolution, which could allow us to efficiently search a vast chemical space. This has huge potential to revolutionize materials discovery-imagine being able to evolve molecules for light harvesting, or catalysts for CO 2 fixation. The field of DTS has developed to the point where a wide variety of reactions can be performed on a DNA template. Complex architectures and autonomous "DNA robots" have been implemented for the controlled assembly of BBs, and these mechanisms have in turn enabled the one-pot synthesis of large combinatorial libraries. Indeed, DTS libraries are being exploited by pharmaceutical companies and have already found their way into drug lead discovery programs. This Account explores the processes involved in DTS and highlights the challenges that remain in creating a general system for molecular discovery by evolution.

The Evolution of DNA-Templated Synthesis as a Tool for Materials Discovery

PubMed Central

2017-01-01

Conspectus Precise control over reactivity and molecular structure is a fundamental goal of the chemical sciences. Billions of years of evolution by natural selection have resulted in chemical systems capable of information storage, self-replication, catalysis, capture and production of light, and even cognition. In all these cases, control over molecular structure is required to achieve a particular function: without structural control, function may be impaired, unpredictable, or impossible. The search for molecules with a desired function is often achieved by synthesizing a combinatorial library, which contains many or all possible combinations of a set of chemical building blocks (BBs), and then screening this library to identify “successful” structures. The largest libraries made by conventional synthesis are currently of the order of 108 distinct molecules. To put this in context, there are 1013 ways of arranging the 21 proteinogenic amino acids in chains up to 10 units long. Given that we know that a number of these compounds have potent biological activity, it would be highly desirable to be able to search them all to identify leads for new drug molecules. Large libraries of oligonucleotides can be synthesized combinatorially and translated into peptides using systems based on biological replication such as mRNA display, with selected molecules identified by DNA sequencing; but these methods are limited to BBs that are compatible with cellular machinery. In order to search the vast tracts of chemical space beyond nucleic acids and natural peptides, an alternative approach is required. DNA-templated synthesis (DTS) could enable us to meet this challenge. DTS controls chemical product formation by using the specificity of DNA hybridization to bring selected reactants into close proximity, and is capable of the programmed synthesis of many distinct products in the same reaction vessel. By making use of dynamic, programmable DNA processes, it is possible to engineer a system that can translate instructions coded as a sequence of DNA bases into a chemical structure—a process analogous to the action of the ribosome in living organisms but with the potential to create a much more chemically diverse set of products. It is also possible to ensure that each product molecule is tagged with its identifying DNA sequence. Compound libraries synthesized in this way can be exposed to selection against suitable targets, enriching successful molecules. The encoding DNA can then be amplified using the polymerase chain reaction and decoded by DNA sequencing. More importantly, the DNA instruction sequences can be mutated and reused during multiple rounds of amplification, translation, and selection. In other words, DTS could be used as the foundation for a system of synthetic molecular evolution, which could allow us to efficiently search a vast chemical space. This has huge potential to revolutionize materials discovery—imagine being able to evolve molecules for light harvesting, or catalysts for CO2 fixation. The field of DTS has developed to the point where a wide variety of reactions can be performed on a DNA template. Complex architectures and autonomous “DNA robots” have been implemented for the controlled assembly of BBs, and these mechanisms have in turn enabled the one-pot synthesis of large combinatorial libraries. Indeed, DTS libraries are being exploited by pharmaceutical companies and have already found their way into drug lead discovery programs. This Account explores the processes involved in DTS and highlights the challenges that remain in creating a general system for molecular discovery by evolution. PMID:28915003

Synthesis of small combinatorial libraries of natural products: identification and quantification of new long-chain 3-methyl-2-alkanones from the root essential oil of Inula helenium L. (Asteraceae).

PubMed

Radulović, Niko S; Denić, Marija S; Stojanović-Radić, Zorica Z

2014-01-01

Recently, a potent anti-staphylococcal activity of Inula helenium L. (Asteraceae) root essential oil was reported. Also, bioassay guided fractionation of the oil pointed to eudesmane sesquiterpene lactones and a series of unidentified constituents as the main carriers of the observed activity. To identify nine new constituents (long-chain 3-methyl-2-alkanones) from a fraction of this root essential oil with a low minimum inhibitory concentration value (0.8 µg/mL) by employing a synthetic methodology that leads to the formation of a small combinatorial library of these compounds. The identity of these constituents was inferred from mass spectral fragmentation patterns and GC retention data. A library of 3-methyl-2-alkanones (C11 -C19 homologous series) was synthesised in three steps starting from methyl acetoacetate and the corresponding alkyl halides. The synthetic library was also screened for in vitro anti-microbial activity. Gas chromatographic analyses of I. helenium essential oil samples with spiked compounds from the synthesised library corroborated the tentative identifications of the long-chain 3-methyl-2-alkanones. The availability of these anti-microbial compounds from this library made it possible to construct GC/FID calibration curves and determine their content in the plant material: 0.08 - 24.2 mg/100 g of dry roots. The small combinatorial library approach enabled the first unequivocal identification of long-chain 3-methyl-2-alkanones as plant secondary metabolites, and, also, allowed determination of not only a single compound and biological properties, but those of a group of structurally related compounds. Copyright © 2013 John Wiley & Sons, Ltd.

Widening and diversifying the proteome capture by combinatorial peptide ligand libraries via Alcian Blue dye binding.

PubMed

Candiano, Giovanni; Santucci, Laura; Petretto, Andrea; Lavarello, Chiara; Inglese, Elvira; Bruschi, Maurizio; Ghiggeri, Gian Marco; Boschetti, Egisto; Righetti, Pier Giorgio

2015-01-01

Combinatorial peptide ligand libraries (CPLLs) tend to bind complex molecules such as dyes due to their aromatic, heterocyclic, hydrophobic, and ionic nature that may affect the protein capture specificity. In this experimental work Alcian Blue 8GX, a positively charged phthalocyanine dye well-known to bind to glycoproteins and to glucosaminoglycans, was adsorbed on a chemically modified CPLL solid phase, and the behavior of the resulting conjugate was then investigated. The control and dye-adsorbed beads were used to harvest the human urinary proteome at physiological pH, this resulting in a grand total of 1151 gene products identified after the capture. Although the Alcian Blue-modified CPLL incremented the total protein capture by 115 species, it particularly enriched some families among the harvested proteins, such as glycoproteins and nucleotide-binding proteins. This study teaches that it is possible, via the two combined harvest mechanisms, to drive the CPLL capture toward the enrichment of specific protein categories.

Sensomics-Assisted Elucidation of the Tastant Code of Cooked Crustaceans and Taste Reconstruction Experiments.

PubMed

Meyer, Stefanie; Dunkel, Andreas; Hofmann, Thomas

2016-02-10

Sensory-guided fractionation by means of ultrafiltration and cation-exchange chromatography, followed by MS/MS quantitation, and taste re-engineering experiments revealed the key taste molecules coining the characteristic taste profile of the cooked meat of king prawns. Furthermore, quantitative analysis demonstrated that the taste differences between crustaceans are due to quantitative differences in the combinatorial code of tastants, rather than to qualitative differences in the tastant composition. Besides the amino acids glycine, L-proline, and L-alanine, the characteristic seafood-like sweet profile was found to be due to the sweet modulatory action of quaternary ammonium compounds, among which betaine, homarine, stachydrin, and trimethylamine-N-oxide were found as the key contributors on the basis of dose-activity considerations. Knowledge of this combinatorial tastant code provides the foundation for the development of more sophisticated crustacean flavors that are lacking any heavy metal ions and allergenic proteins present when using crustacean extracts for food flavoring.

Solid-phase synthesis and screening of N-acylated polyamine (NAPA) combinatorial libraries for protein binding.

PubMed

Iera, Jaclyn A; Jenkins, Lisa M Miller; Kajiyama, Hiroshi; Kopp, Jeffrey B; Appella, Daniel H

2010-11-15

Inhibitors for protein-protein interactions are challenging to design, in part due to the unique and complex architectures of each protein's interaction domain. Most approaches to develop inhibitors for these interactions rely on rational design, which requires prior structural knowledge of the target and its ligands. In the absence of structural information, a combinatorial approach may be the best alternative to finding inhibitors of a protein-protein interaction. Current chemical libraries, however, consist mostly of molecules designed to inhibit enzymes. In this manuscript, we report the synthesis and screening of a library based on an N-acylated polyamine (NAPA) scaffold that we designed to have specific molecular features necessary to inhibit protein-protein interactions. Screens of the library identified a member with favorable binding properties to the HIV viral protein R (Vpr), a regulatory protein from HIV, that is involved in numerous interactions with other proteins critical for viral replication. Published by Elsevier Ltd.

pK(a) based protonation states and microspecies for protein-ligand docking.

PubMed

ten Brink, Tim; Exner, Thomas E

2010-11-01

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein-ligand complexes as e.g. taken from the Protein Data Bank as well as for the setup of 3D ligand databases. It automatically assigns atom and bond types, generates different protonation, tautomeric states as well as different stereoisomers. In the revised version, pKa calculations with the ChemAxon software MARVIN are used either to determine the likeliness of a combinatorial generated protonation state or to determine the titrable atoms used in the combinatorial approach. Additionally, the MARVIN software is used to predict microspecies distributions of ligand molecules. Docking studies were performed with our recently introduced program PLANTS (Protein-Ligand ANT System) on all protomers resulting from the three different selection methods for the well established CCDC/ASTEX clean data set demonstrating the usefulness of especially the latter approach.

pKa based protonation states and microspecies for protein-ligand docking

NASA Astrophysics Data System (ADS)

ten Brink, Tim; Exner, Thomas E.

2010-11-01

In this paper we present our reworked approach to generate ligand protonation states with our structure preparation tool SPORES (Structure PrOtonation and REcognition System). SPORES can be used for the preprocessing of proteins and protein-ligand complexes as e.g. taken from the Protein Data Bank as well as for the setup of 3D ligand databases. It automatically assigns atom and bond types, generates different protonation, tautomeric states as well as different stereoisomers. In the revised version, pKa calculations with the ChemAxon software MARVIN are used either to determine the likeliness of a combinatorial generated protonation state or to determine the titrable atoms used in the combinatorial approach. Additionally, the MARVIN software is used to predict microspecies distributions of ligand molecules. Docking studies were performed with our recently introduced program PLANTS (Protein-Ligand ANT System) on all protomers resulting from the three different selection methods for the well established CCDC/ASTEX clean data set demonstrating the usefulness of especially the latter approach.

Small molecule drug A-769662 and AMP synergistically activate naive AMPK independent of upstream kinase signaling.

PubMed

Scott, John W; Ling, Naomi; Issa, Samah M A; Dite, Toby A; O'Brien, Matthew T; Chen, Zhi-Ping; Galic, Sandra; Langendorf, Christopher G; Steinberg, Gregory R; Kemp, Bruce E; Oakhill, Jonathan S

2014-05-22

The AMP-activated protein kinase (AMPK) is a metabolic stress-sensing αβγ heterotrimer responsible for energy homeostasis, making it a therapeutic target for metabolic diseases such as type 2 diabetes and obesity. AMPK signaling is triggered by phosphorylation on the AMPK α subunit activation loop Thr172 by upstream kinases. Dephosphorylated, naive AMPK is thought to be catalytically inactive and insensitive to allosteric regulation by AMP and direct AMPK-activating drugs such as A-769662. Here we show that A-769662 activates AMPK independently of α-Thr172 phosphorylation, provided β-Ser108 is phosphorylated. Although neither A-769662 nor AMP individually stimulate the activity of dephosphorylated AMPK, together they stimulate >1,000-fold, bypassing the requirement for β-Ser108 phosphorylation. Consequently A-769662 and AMP together activate naive AMPK entirely allosterically and independently of upstream kinase signaling. These findings have important implications for development of AMPK-targeting therapeutics and point to possible combinatorial therapeutic strategies based on AMP and AMPK drugs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structure-Activity Relationship Analysis of 3-phenylcoumarin-Based Monoamine Oxidase B Inhibitors

NASA Astrophysics Data System (ADS)

Rauhamäki, Sanna; Postila, Pekka A.; Niinivehmas, Sanna; Kortet, Sami; Schildt, Emmi; Pasanen, Mira; Manivannan, Elangovan; Ahinko, Mira; Koskimies, Pasi; Nyberg, Niina; Huuskonen, Pasi; Multamäki, Elina; Pasanen, Markku; Juvonen, Risto O.; Raunio, Hannu; Huuskonen, Juhani; Pentikäinen, Olli T.

2018-03-01

Monoamine oxidase B (MAO-B) catalyzes deamination of monoamines such as neurotransmitters dopamine and norepinephrine. Accordingly, small-molecule MAO-B inhibitors potentially alleviate the symptoms of dopamine-linked neuropathologies such as depression or Parkinson’s disease. Coumarin with a functionalized 3-phenyl ring system is a promising scaffold for building potent MAO-B inhibitors. Here, a vast set of 3-phenylcoumarin derivatives was designed using virtual combinatorial chemistry or rationally de novo and synthesized using microwave chemistry. The derivatives inhibited the MAO-B at 100 nM - 1 µM. The IC50 value of the most potent derivative 1 was 56 nM. A docking-based structure-activity relationship analysis summarizes the atom-level determinants of the MAO-B inhibition by the derivatives. Finally, the cross-reactivity of the derivatives was tested against monoamine oxidase A and a specific subset of enzymes linked to estradiol metabolism, known to have coumarin-based inhibitors. Overall, the results indicate that the 3-phenylcoumarins, especially derivative 1, present unique pharmacological features worth considering in future drug development.

Extracellular metabolic energetics can promote cancer progression.

PubMed

Loo, Jia Min; Scherl, Alexis; Nguyen, Alexander; Man, Fung Ying; Weinberg, Ethan; Zeng, Zhaoshi; Saltz, Leonard; Paty, Philip B; Tavazoie, Sohail F

2015-01-29

Colorectal cancer primarily metastasizes to the liver and globally kills over 600,000 people annually. By functionally screening 661 microRNAs (miRNAs) in parallel during liver colonization, we have identified miR-551a and miR-483 as robust endogenous suppressors of liver colonization and metastasis. These miRNAs convergently target creatine kinase, brain-type (CKB), which phosphorylates the metabolite creatine, to generate phosphocreatine. CKB is released into the extracellular space by metastatic cells encountering hepatic hypoxia and catalyzes production of phosphocreatine, which is imported through the SLC6A8 transporter and used to generate ATP—fueling metastatic survival. Combinatorial therapeutic viral delivery of miR-551a and miR-483-5p through single-dose adeno-associated viral (AAV) delivery significantly suppressed colon cancer metastasis, as did CKB inhibition with a small-molecule inhibitor. Importantly, human liver metastases express higher CKB and SLC6A8 levels and reduced miR-551a/miR-483 levels relative to primary tumors. We identify the extracellular space as an important compartment for malignant energetic catalysis and therapeutic targeting. Copyright © 2015 Elsevier Inc. All rights reserved.

Synthetic antimicrobial peptides as agricultural pesticides for plant-disease control.

PubMed

Montesinos, Emilio; Bardají, Eduard

2008-07-01

There is a need of antimicrobial compounds in agriculture for plant-disease control, with low toxicity and reduced negative environmental impact. Antimicrobial peptides are produced by living organisms and offer strong possibilities in agriculture because new compounds can be developed based on natural structures with improved properties of activity, specificity, biodegradability, and toxicity. Design of new molecules has been achieved using combinatorial-chemistry procedures coupled to high-throughput screening systems and data processing with design-of-experiments (DOE) methodology to obtain QSAR equation models and optimized compounds. Upon selection of best candidates with low cytotoxicity and moderate stability to protease digestion, anti-infective activity has been evaluated in plant-pathogen model systems. Suitable compounds have been submitted to acute toxicity testing in higher organisms and exhibited a low toxicity profile in a mouse model. Large-scale production can be achieved by solution organic or chemoenzymatic procedures in the case of very small peptides, but, in many cases, production can be performed by biotechnological methods using genetically modified microorganisms (fermentation) or transgenic crops (plant biofactories).

A salicylic acid-based small molecule inhibitor for the oncogenic Src homology-2 domain containing protein tyrosine phosphatase-2 (SHP2)

PubMed Central

Zhang, Xian; He, Yantao; Liu, Sijiu; Yu, Zhihong; Jiang, Zhong-Xing; Yang, Zhenyun; Dong, Yuanshu; Nabinger, Sarah C.; Wu, Li; Gunawan, Andrea M.; Wang, Lina; Chan, Rebecca J.; Zhang, Zhong-Yin

2010-01-01

The Src homology-2 domain containing protein tyrosine phosphatase-2 (SHP2) plays a pivotal role in growth factor and cytokine signaling. Gain-of-function SHP2 mutations are associated with Noonan syndrome, various kinds of leukemias and solid tumors. Thus there is considerable interest in SHP2 as a potential target for anti-cancer and anti-leukemia therapy. We report a salicylic acid-based combinatorial library approach aimed to bind both active site and unique nearby sub-pockets for enhanced affinity and selectivity. Screening of the library led to the identification of a SHP2 inhibitor II-B08 (compound 9) with highly efficacious cellular activity. Compound 9 blocks growth factor stimulated ERK1/2 activation and hematopoietic progenitor proliferation, providing supporting evidence that chemical inhibition of SHP2 may be therapeutically useful for anti-cancer and anti-leukemia treatment. X-ray crystallographic analysis of the structure of SHP2 in complex with 9 reveals molecular determinants that can be exploited for the acquisition of more potent and selective SHP2 inhibitors. PMID:20170098

Image-based drug screen identifies HDAC inhibitors as novel Golgi disruptors synergizing with JQ1

PubMed Central

Gendarme, Mathieu; Baumann, Jan; Ignashkova, Tatiana I.; Lindemann, Ralph K.; Reiling, Jan H.

2017-01-01

The Golgi apparatus is increasingly recognized as a major hub for cellular signaling and is involved in numerous pathologies, including neurodegenerative diseases and cancer. The study of Golgi stress-induced signaling pathways relies on the selectivity of the available tool compounds of which currently only a few are known. To discover novel Golgi-fragmenting agents, transcriptomic profiles of cells treated with brefeldin A, golgicide A, or monensin were generated and compared with a database of gene expression profiles from cells treated with other bioactive small molecules. In parallel, a phenotypic screen was performed for compounds that alter normal Golgi structure. Histone deacetylase (HDAC) inhibitors and DNA-damaging agents were identified as novel Golgi disruptors. Further analysis identified HDAC1/HDAC9 as well as BRD8 and DNA-PK as important regulators of Golgi breakdown mediated by HDAC inhibition. We provide evidence that combinatorial HDACi/(+)-JQ1 treatment spurs synergistic Golgi dispersal in several cancer cell lines, pinpointing a possible link between drug-induced toxicity and Golgi morphology alterations. PMID:29074567

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM)

PubMed Central

Skinnider, Michael A.; Dejong, Chris A.; Rees, Philip N.; Johnston, Chad W.; Li, Haoxin; Webster, Andrew L. H.; Wyatt, Morgan A.; Magarvey, Nathan A.

2015-01-01

Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/. PMID:26442528

Chess games: a model for RNA based computation.

PubMed

Cukras, A R; Faulhammer, D; Lipton, R J; Landweber, L F

1999-10-01

Here we develop the theory of RNA computing and a method for solving the 'knight problem' as an instance of a satisfiability (SAT) problem. Using only biological molecules and enzymes as tools, we developed an algorithm for solving the knight problem (3 x 3 chess board) using a 10-bit combinatorial pool and sequential RNase H digestions. The results of preliminary experiments presented here reveal that the protocol recovers far more correct solutions than expected at random, but the persistence of errors still presents the greatest challenge.

Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

PubMed

Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

2017-07-10

Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

A combinatorial approach of inclusion complexation and dendrimer synthesization for effective targeting EGFR-TK.

PubMed

Shende, Pravin; Patil, Sampada; Gaud, R S

2017-07-01

The aim of the present study was to use a combinatorial approach of inclusion complexation and dendrimer synthesization of gefitinib using solvent-free technique for targeting EGFR-TK to treat Non-Small-Cell Lung Cancer (NSCLC). The inclusion complex of gefitinib with β-cyclodextrin was prepared by trituration method. This complex encapsulated G4 PAMAM dendrimers were synthesized by Michael addition and amidation reactions using green chemistry and then PEGylated by conjugation reaction. FTIR and DSC confirmed the formation of inclusion complex of gefitinib and β-cyclodextrin and PEGylation of G4 PAMAM dendrimers. Gefitinib showed higher solubility, encapsulation efficiency and controlled release profile from PEGylated dendrimers compared to inclusion complex. The PEGylated dendrimers of inclusion complex of gefitinib were found to reduce hemolytic toxicity and lesser GI 50 value on Human lung cancer cell line A-549 by effective targeting EGFR-TK. A combinatorial approach of inclusion complexation and dendrimer synthesization is one of the alternative advanced approaches to treat NSCLC. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of the Implicit Combinatorial Model on Combinatorial Reasoning in Secondary School Pupils.

ERIC Educational Resources Information Center

Batanero, Carmen; And Others

1997-01-01

Elementary combinatorial problems may be classified into three different combinatorial models: (1) selection; (2) partition; and (3) distribution. The main goal of this research was to determine the effect of the implicit combinatorial model on pupils' combinatorial reasoning before and after instruction. Gives an analysis of variance of the…

DNA as Sensors and Imaging Agents for Metal Ions

PubMed Central

Xiang, Yu

2014-01-01

Increasing interests in detecting metal ions in many chemical and biomedical fields have created demands for developing sensors and imaging agents for metal ions with high sensitivity and selectivity. This review covers recent progress in DNA-based sensors and imaging agents for metal ions. Through both combinatorial selection and rational design, a number of metal ion-dependent DNAzymes and metal ion-binding DNA structures that can selectively recognize specific metal ions have been obtained. By attaching these DNA molecules with signal reporters such as fluorophores, chromophores, electrochemical tags, and Raman tags, a number of DNA-based sensors for both diamagnetic and paramagnetic metal ions have been developed for fluorescent, colorimetric, electrochemical, and surface Raman detections. These sensors are highly sensitive (with detection limit down to 11 ppt) and selective (with selectivity up to millions-fold) toward specific metal ions. In addition, through further development to simplify the operation, such as the use of “dipstick tests”, portable fluorometers, computer-readable discs, and widely available glucose meters, these sensors have been applied for on-site and real-time environmental monitoring and point-of-care medical diagnostics. The use of these sensors for in situ cellular imaging has also been reported. The generality of the combinatorial selection to obtain DNAzymes for almost any metal ion in any oxidation state, and the ease of modification of the DNA with different signal reporters make DNA an emerging and promising class of molecules for metal ion sensing and imaging in many fields of applications. PMID:24359450

An Interactive Multiobjective Programming Approach to Combinatorial Data Analysis.

ERIC Educational Resources Information Center

Brusco, Michael J.; Stahl, Stephanie

2001-01-01

Describes an interactive procedure for multiobjective asymmetric unidimensional seriation problems that uses a dynamic-programming algorithm to generate partially the efficient set of sequences for small to medium-sized problems and a multioperational heuristic to estimate the efficient set for larger problems. Applies the procedure to an…

DNA-encoded chemical libraries: advancing beyond conventional small-molecule libraries.

PubMed

Franzini, Raphael M; Neri, Dario; Scheuermann, Jörg

2014-04-15

DNA-encoded chemical libraries (DECLs) represent a promising tool in drug discovery. DECL technology allows the synthesis and screening of chemical libraries of unprecedented size at moderate costs. In analogy to phage-display technology, where large antibody libraries are displayed on the surface of filamentous phage and are genetically encoded in the phage genome, DECLs feature the display of individual small organic chemical moieties on DNA fragments serving as amplifiable identification barcodes. The DNA-tag facilitates the synthesis and allows the simultaneous screening of very large sets of compounds (up to billions of molecules), because the hit compounds can easily be identified and quantified by PCR-amplification of the DNA-barcode followed by high-throughput DNA sequencing. Several approaches have been used to generate DECLs, differing both in the methods used for library encoding and for the combinatorial assembly of chemical moieties. For example, DECLs can be used for fragment-based drug discovery, displaying a single molecule on DNA or two chemical moieties at the extremities of complementary DNA strands. DECLs can vary substantially in the chemical structures and the library size. While ultralarge libraries containing billions of compounds have been reported containing four or more sets of building blocks, also smaller libraries have been shown to be efficient for ligand discovery. In general, it has been found that the overall library size is a poor predictor for library performance and that the number and diversity of the building blocks are rather important indicators. Smaller libraries consisting of two to three sets of building blocks better fulfill the criteria of drug-likeness and often have higher quality. In this Account, we present advances in the DECL field from proof-of-principle studies to practical applications for drug discovery, both in industry and in academia. DECL technology can yield specific binders to a variety of target proteins and is likely to become a standard tool for pharmaceutical hit discovery, lead expansion, and Chemical Biology research. The introduction of new methodologies for library encoding and for compound synthesis in the presence of DNA is an exciting research field and will crucially contribute to the performance and the propagation of the technology.

A fluorescent combinatorial logic gate with Na+, H+-enabled OR and H+-driven low-medium-high ternary logic functions.

PubMed

Spiteri, Jasmine M A; Mallia, Carl J; Scerri, Glenn J; Magri, David C

2017-12-06

A novel fluorescent molecular logic gate with a 'fluorophore-spacer 1 -receptor 1 -spacer 2 -receptor 2 ' format is demonstrated in 1 : 1 (v/v) methanol/water. The molecule consists of an anthracene fluorophore, and tertiary alkyl amine and N-(2-methoxyphenyl)aza-15-crown-5 ether receptors. In the presence of threshold concentrations of H + and Na + , the molecule switches 'on' as an AND logic gate with a fluorescence quantum yield of 0.21 with proton and sodium binding constants of log β H+ = 9.0 and log β Na+ = 3.2, respectively. At higher proton levels, protonation also occurs at the anilinic nitrogen atom ether with a log β H+ = 4.2, which allows for Na + , H + -enabled OR (OR + AND circuit) and H + -driven ternary logic functions. The reported molecule is compared and contrasted to classic anthracene-based Na + and H + logic gates. We propose that such logic-based molecules could be useful tools for probing the vicinity of Na + , H + antiporters in biological systems.

Estimation of the size of drug-like chemical space based on GDB-17 data.

PubMed

Polishchuk, P G; Madzhidov, T I; Varnek, A

2013-08-01

The goal of this paper is to estimate the number of realistic drug-like molecules which could ever be synthesized. Unlike previous studies based on exhaustive enumeration of molecular graphs or on combinatorial enumeration preselected fragments, we used results of constrained graphs enumeration by Reymond to establish a correlation between the number of generated structures (M) and the number of heavy atoms (N): logM = 0.584 × N × logN + 0.356. The number of atoms limiting drug-like chemical space of molecules which follow Lipinsky's rules (N = 36) has been obtained from the analysis of the PubChem database. This results in M ≈ 10³³ which is in between the numbers estimated by Ertl (10²³) and by Bohacek (10⁶⁰).

Systemic combinatorial peptide selection yields a non-canonical iron-mimicry mechanism for targeting tumors in a mouse model of human glioblastoma

PubMed Central

Staquicini, Fernanda I.; Ozawa, Michael G.; Moya, Catherine A.; Driessen, Wouter H.P.; Barbu, E. Magda; Nishimori, Hiroyuki; Soghomonyan, Suren; Flores, Leo G.; Liang, Xiaowen; Paolillo, Vincenzo; Alauddin, Mian M.; Basilion, James P.; Furnari, Frank B.; Bogler, Oliver; Lang, Frederick F.; Aldape, Kenneth D.; Fuller, Gregory N.; Höök, Magnus; Gelovani, Juri G.; Sidman, Richard L.; Cavenee, Webster K.; Pasqualini, Renata; Arap, Wadih

2010-01-01

The management of CNS tumors is limited by the blood-brain barrier (BBB), a vascular interface that restricts the passage of most molecules from the blood into the brain. Here we show that phage particles targeted with certain ligand motifs selected in vivo from a combinatorial peptide library can cross the BBB under normal and pathological conditions. Specifically, we demonstrated that phage clones displaying an iron-mimic peptide were able to target a protein complex of transferrin and transferrin receptor (TfR) through a non-canonical allosteric binding mechanism and that this functional protein complex mediated transport of the corresponding viral particles into the normal mouse brain. We also showed that, in an orthotopic mouse model of human glioblastoma, a combination of TfR overexpression plus extended vascular permeability and ligand retention resulted in remarkable brain tumor targeting of chimeric adeno-associated virus/phage particles displaying the iron-mimic peptide and carrying a gene of interest. As a proof of concept, we delivered the HSV thymidine kinase gene for molecular-genetic imaging and targeted therapy of intracranial xenografted tumors. Finally, we established that these experimental findings might be clinically relevant by determining through human tissue microarrays that many primary astrocytic tumors strongly express TfR. Together, our combinatorial selection system and results may provide a translational avenue for the targeted detection and treatment of brain tumors. PMID:21183793

NATURAL PRODUCTS: A CONTINUING SOURCE OF NOVEL DRUG LEADS

PubMed Central

Cragg, Gordon M.; Newman, David J.

2013-01-01

1. Background Nature has been a source of medicinal products for millennia, with many useful drugs developed from plant sources. Following discovery of the penicillins, drug discovery from microbial sources occurred and diving techniques in the 1970s opened the seas. Combinatorial chemistry (late 1980s), shifted the focus of drug discovery efforts from Nature to the laboratory bench. 2. Scope of Review This review traces natural products drug discovery, outlining important drugs from natural sources that revolutionized treatment of serious diseases. It is clear Nature will continue to be a major source of new structural leads, and effective drug development depends on multidisciplinary collaborations. 3. Major Conclusions The explosion of genetic information led not only to novel screens, but the genetic techniques permitted the implementation of combinatorial biosynthetic technology and genome mining. The knowledge gained has allowed unknown molecules to be identified. These novel bioactive structures can be optimized by using combinatorial chemistry generating new drug candidates for many diseases. 4 General Significance: The advent of genetic techniques that permitted the isolation / expression of biosynthetic cassettes from microbes may well be the new frontier for natural products lead discovery. It is now apparent that biodiversity may be much greater in those organisms. The numbers of potential species involved in the microbial world are many orders of magnitude greater than those of plants and multi-celled animals. Coupling these numbers to the number of currently unexpressed biosynthetic clusters now identified (>10 per species) the potential of microbial diversity remains essentially untapped. PMID:23428572

A binary plasmid system for shuffling combinatorial antibody libraries.

PubMed

Collet, T A; Roben, P; O'Kennedy, R; Barbas, C F; Burton, D R; Lerner, R A

1992-11-01

We have used a binary system of replicon-compatible plasmids to test the potential for promiscuous recombination of heavy and light chains within sets of human Fab fragments isolated from combinatorial antibody libraries. Antibody molecules showed a surprising amount of promiscuity in that a particular heavy chain could recombine with multiple light chains with retention of binding to a protein antigen. The degree to which a given heavy chain productively paired with any light chain to bind antigen varied from 43% to 100% and depended strongly on the heavy-chain sequence. Such productive crosses resulted in a set of Fab fragments of similar apparent binding constants, which seemed to differ mainly in the amount of active Fab fragment produced in the bacterial cell. The dominance of the heavy chain in the antibody-antigen interaction was further explored in a set of directed crosses, in which heavy and light chains derived from antigen-specific clones were crossed with nonrelated heavy and light chains. In these crosses, an Fab fragment retained antigen binding only if it contained a heavy chain from an antigen-specific clone. In no case did the light chain confer detectable affinity when paired with indifferent heavy chains. The surprising promiscuity of heavy chains has ramifications for the evaluation of the diversity of combinatorial libraries made against protein antigens and should allow the combination of one such promiscuous heavy chain with an engineered light chain to form an Fab fragment carrying synthetic cofactors to assist in antibody catalysis.

A binary plasmid system for shuffling combinatorial antibody libraries.

PubMed Central

Collet, T A; Roben, P; O'Kennedy, R; Barbas, C F; Burton, D R; Lerner, R A

1992-01-01

We have used a binary system of replicon-compatible plasmids to test the potential for promiscuous recombination of heavy and light chains within sets of human Fab fragments isolated from combinatorial antibody libraries. Antibody molecules showed a surprising amount of promiscuity in that a particular heavy chain could recombine with multiple light chains with retention of binding to a protein antigen. The degree to which a given heavy chain productively paired with any light chain to bind antigen varied from 43% to 100% and depended strongly on the heavy-chain sequence. Such productive crosses resulted in a set of Fab fragments of similar apparent binding constants, which seemed to differ mainly in the amount of active Fab fragment produced in the bacterial cell. The dominance of the heavy chain in the antibody-antigen interaction was further explored in a set of directed crosses, in which heavy and light chains derived from antigen-specific clones were crossed with nonrelated heavy and light chains. In these crosses, an Fab fragment retained antigen binding only if it contained a heavy chain from an antigen-specific clone. In no case did the light chain confer detectable affinity when paired with indifferent heavy chains. The surprising promiscuity of heavy chains has ramifications for the evaluation of the diversity of combinatorial libraries made against protein antigens and should allow the combination of one such promiscuous heavy chain with an engineered light chain to form an Fab fragment carrying synthetic cofactors to assist in antibody catalysis. Images PMID:1438192

Structural alignment of protein descriptors - a combinatorial model.

PubMed

Antczak, Maciej; Kasprzak, Marta; Lukasiak, Piotr; Blazewicz, Jacek

2016-09-17

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

Host-directed combinatorial RNAi improves inhibition of diverse strains of influenza A virus in human respiratory epithelial cells.

PubMed

Estrin, Michael A; Hussein, Islam T M; Puryear, Wendy B; Kuan, Anne C; Artim, Stephen C; Runstadler, Jonathan A

2018-01-01

Influenza A virus infections are important causes of morbidity and mortality worldwide, and currently available prevention and treatment methods are suboptimal. In recent years, genome-wide investigations have revealed numerous host factors that are required for influenza to successfully complete its life cycle. However, only a select, small number of influenza strains were evaluated using this platform, and there was considerable variation in the genes identified across different investigations. In an effort to develop a universally efficacious therapeutic strategy with limited potential for the emergence of resistance, this study was performed to investigate the effect of combinatorial RNA interference (RNAi) on inhibiting the replication of diverse influenza A virus subtypes and strains. Candidate genes were selected for targeting based on the results of multiple previous independent genome-wide studies. The effect of single and combinatorial RNAi on the replication of 12 diverse influenza A viruses, including three strains isolated from birds and one strain isolated from seals, was then evaluated in primary normal human bronchial epithelial cells. After excluding overly toxic siRNA, two siRNA combinations were identified that reduced mean viral replication by greater than 79 percent in all mammalian strains, and greater than 68 percent in all avian strains. Host-directed combinatorial RNAi effectively prevents growth of a broad range of influenza virus strains in vitro, and is a potential therapeutic candidate for further development and future in vivo studies.

The disadvantage of combinatorial communication.

PubMed Central

Lachmann, Michael; Bergstrom, Carl T.

2004-01-01

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems. PMID:15556886

The disadvantage of combinatorial communication.

PubMed

Lachmann, Michael; Bergstrom, Carl T

2004-11-22

Combinatorial communication allows rapid and efficient transfer of detailed information, yet combinatorial communication is used by few, if any, non-human species. To complement recent studies illustrating the advantages of combinatorial communication, we highlight a critical disadvantage. We use the concept of information value to show that deception poses a greater and qualitatively different threat to combinatorial signalling than to non-combinatorial systems. This additional potential for deception may represent a strategic barrier that has prevented widespread evolution of combinatorial communication. Our approach has the additional benefit of drawing clear distinctions among several types of deception that can occur in communication systems.

Alignment of RNA molecules: Binding energy and statistical properties of random sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valba, O. V., E-mail: valbaolga@gmail.com; Nechaev, S. K., E-mail: sergei.nechaev@gmail.com; Tamm, M. V., E-mail: thumm.m@gmail.com

2012-02-15

A new statistical approach to the problem of pairwise alignment of RNA sequences is proposed. The problem is analyzed for a pair of interacting polymers forming an RNA-like hierarchical cloverleaf structures. An alignment is characterized by the numbers of matches, mismatches, and gaps. A weight function is assigned to each alignment; this function is interpreted as a free energy taking into account both direct monomer-monomer interactions and a combinatorial contribution due to formation of various cloverleaf secondary structures. The binding free energy is determined for a pair of RNA molecules. Statistical properties are discussed, including fluctuations of the binding energymore » between a pair of RNA molecules and loop length distribution in a complex. Based on an analysis of the free energy per nucleotide pair complexes of random RNAs as a function of the number of nucleotide types c, a hypothesis is put forward about the exclusivity of the alphabet c = 4 used by nature.« less

A Combinatorial Kin Discrimination System in Bacillus subtilis.

PubMed

Lyons, Nicholas A; Kraigher, Barbara; Stefanic, Polonca; Mandic-Mulec, Ines; Kolter, Roberto

2016-03-21

Multicellularity inherently involves a number of cooperative behaviors that are potentially susceptible to exploitation but can be protected by mechanisms such as kin discrimination. Discrimination of kin from non-kin has been observed in swarms of the bacterium Bacillus subtilis, but the underlying molecular mechanism has been unknown. We used genetic, transcriptomic, and bioinformatic analyses to uncover kin recognition factors in this organism. Our results identified many molecules involved in cell-surface modification and antimicrobial production and response. These genes varied significantly in expression level and mutation phenotype among B. subtilis strains, suggesting interstrain variation in the exact kin discrimination mechanism used. Genome analyses revealed a substantial diversity of antimicrobial genes present in unique combinations in different strains, with many likely acquired by horizontal gene transfer. The dynamic combinatorial effect derived from this plethora of kin discrimination genes creates a tight relatedness cutoff for cooperation that has likely led to rapid diversification within the species. Our data suggest that genes likely originally selected for competitive purposes also generate preferential interactions among kin, thus stabilizing multicellular lifestyles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combinatory annotation of cell membrane receptors and signalling pathways of Bombyx mori prothoracic glands

PubMed Central

Moulos, Panagiotis; Samiotaki, Martina; Panayotou, George; Dedos, Skarlatos G.

2016-01-01

The cells of prothoracic glands (PG) are the main site of synthesis and secretion of ecdysteroids, the biochemical products of cholesterol conversion to steroids that shape the morphogenic development of insects. Despite the availability of genome sequences from several insect species and the extensive knowledge of certain signalling pathways that underpin ecdysteroidogenesis, the spectrum of signalling molecules and ecdysteroidogenic cascades is still not fully comprehensive. To fill this gap and obtain the complete list of cell membrane receptors expressed in PG cells, we used combinatory bioinformatic, proteomic and transcriptomic analysis and quantitative PCR to annotate and determine the expression profiles of genes identified as putative cell membrane receptors of the model insect species, Bombyx mori, and subsequently enrich the repertoire of signalling pathways that are present in its PG cells. The genome annotation dataset we report here highlights modules and pathways that may be directly involved in ecdysteroidogenesis and aims to disseminate data and assist other researchers in the discovery of the role of such receptors and their ligands. PMID:27576083

Multibody local approximation: Application to conformational entropy calculations on biomolecules

NASA Astrophysics Data System (ADS)

Suárez, Ernesto; Suárez, Dimas

2012-08-01

Multibody type expansions like mutual information expansions are widely used for computing or analyzing properties of large composite systems. The power of such expansions stems from their generality. Their weaknesses, however, are the large computational cost of including high order terms due to the combinatorial explosion and the fact that truncation errors do not decrease strictly with the expansion order. Herein, we take advantage of the redundancy of multibody expansions in order to derive an efficient reformulation that captures implicitly all-order correlation effects within a given cutoff, avoiding the combinatory explosion. This approach, which is cutoff dependent rather than order dependent, keeps the generality of the original expansions and simultaneously mitigates their limitations provided that a reasonable cutoff can be used. An application of particular interest can be the computation of the conformational entropy of flexible peptide molecules from molecular dynamics trajectories. By combining the multibody local estimations of conformational entropy with average values of the rigid-rotor and harmonic-oscillator entropic contributions, we obtain by far a tighter upper bound of the absolute entropy than the one obtained by the broadly used quasi-harmonic method.

Multibody local approximation: application to conformational entropy calculations on biomolecules.

PubMed

Suárez, Ernesto; Suárez, Dimas

2012-08-28

Multibody type expansions like mutual information expansions are widely used for computing or analyzing properties of large composite systems. The power of such expansions stems from their generality. Their weaknesses, however, are the large computational cost of including high order terms due to the combinatorial explosion and the fact that truncation errors do not decrease strictly with the expansion order. Herein, we take advantage of the redundancy of multibody expansions in order to derive an efficient reformulation that captures implicitly all-order correlation effects within a given cutoff, avoiding the combinatory explosion. This approach, which is cutoff dependent rather than order dependent, keeps the generality of the original expansions and simultaneously mitigates their limitations provided that a reasonable cutoff can be used. An application of particular interest can be the computation of the conformational entropy of flexible peptide molecules from molecular dynamics trajectories. By combining the multibody local estimations of conformational entropy with average values of the rigid-rotor and harmonic-oscillator entropic contributions, we obtain by far a tighter upper bound of the absolute entropy than the one obtained by the broadly used quasi-harmonic method.

Antigenic variation of Anaplasma marginale msp2 occurs by combinatorial gene conversion.

PubMed

Brayton, Kelly A; Palmer, Guy H; Lundgren, Anna; Yi, Jooyoung; Barbet, Anthony F

2002-03-01

The rickettsial pathogen Anaplasma marginale establishes lifelong persistent infection in the mammalian reservoir host, during which time immune escape variants continually arise in part because of variation in the expressed copy of the immunodominant outer membrane protein MSP2. A key question is how the small 1.2 Mb A. marginale genome generates sufficient variants to allow long-term persistence in an immunocompetent reservoir host. The recombination of whole pseudogenes into the single msp2 expression site has been previously identified as one method of generating variants, but is inadequate to generate the number of variants required for persistent infection. In the present study, we demonstrate that recombination of a whole pseudogene is followed by a second level of variation in which small segments of pseudogenes recombine into the expression site by gene conversion. Evidence for four short sequential changes in the hypervariable region of msp2 coupled with the identification of nine pseudogenes from a single strain of A. marginale provides for a combinatorial number of possible expressed MSP2 variants sufficient for lifelong persistence.

Sensitive electrospray mass spectrometry analysis of one-bead-one-compound peptide libraries labeled by quaternary ammonium salts.

PubMed

Bąchor, Remigiusz; Cydzik, Marzena; Rudowska, Magdalena; Kluczyk, Alicja; Stefanowicz, Piotr; Szewczuk, Zbigniew

2012-08-01

A rapid and straightforward method for high-throughput analysis of single resin beads from one-bead-one-compound combinatorial libraries with high resolution electrospray ionization tandem mass spectrometry (HR ESI-MS/MS) is presented. The application of an efficient method of peptide derivatization by quaternary ammonium salts (QAS) formation increases ionization efficiency and reduces the detection limit, allowing analysis of trace amounts of compounds by ESI-MS. Peptides, synthesized on solid support, contain a new cleavable linker composed of a Peg spacer (9-aza-3,6,12,15-tetraoxa-10-on-heptadecanoic acid), lysine with ɛ-amino group marked by the N,N,N-triethylglycine salt, and methionine, which makes possible the selective cleavage by cyanogen bromide. Even a small portion of peptides derivatized by QAS cleaved from a single resin bead is sufficient for sequencing by HR ESI-MS/MS experiments. The developed strategy was applied to a small training library of α chymotrypsin substrates. The obtained results confirm the applicability of the proposed method in combinatorial chemistry.

Targeting KRAS-mutant non-small cell lung cancer with the Hsp90 inhibitor ganetespib.

PubMed

Acquaviva, Jaime; Smith, Donald L; Sang, Jim; Friedland, Julie C; He, Suqin; Sequeira, Manuel; Zhang, Chaohua; Wada, Yumiko; Proia, David A

2012-12-01

Mutant KRAS is a feature of more than 25% of non-small cell lung cancers (NSCLC) and represents one of the most prevalent oncogenic drivers in this disease. NSCLC tumors with oncogenic KRAS respond poorly to current therapies, necessitating the pursuit of new treatment strategies. Targeted inhibition of the molecular chaperone Hsp90 results in the coordinated blockade of multiple oncogenic signaling pathways in tumor cells and has thus emerged as an attractive avenue for therapeutic intervention in human malignancies. Here, we examined the activity of ganetespib, a small-molecule inhibitor of Hsp90 currently in clinical trials for NSCLCs in a panel of lung cancer cell lines harboring a diverse spectrum of KRAS mutations. In vitro, ganetespib was potently cytotoxic in all lines, with concomitant destabilization of KRAS signaling effectors. Combinations of low-dose ganetespib with MEK or PI3K/mTOR inhibitors resulted in superior cytotoxic activity than single agents alone in a subset of mutant KRAS cells, and the antitumor efficacy of ganetespib was potentiated by cotreatment with the PI3K/mTOR inhibitor BEZ235 in A549 xenografts in vivo. At the molecular level, ganetespib suppressed activating feedback signaling loops that occurred in response to MEK and PI3K/mTOR inhibition, although this activity was not the sole determinant of combinatorial benefit. In addition, ganetespib sensitized mutant KRAS NSCLC cells to standard-of-care chemotherapeutics of the antimitotic, topoisomerase inhibitor, and alkylating agent classes. Taken together, these data underscore the promise of ganetespib as a single-agent or combination treatment in KRAS-driven lung tumors.

Why is combinatorial communication rare in the natural world, and why is language an exception to this trend?

PubMed

Scott-Phillips, Thomas C; Blythe, Richard A

2013-11-06

In a combinatorial communication system, some signals consist of the combinations of other signals. Such systems are more efficient than equivalent, non-combinatorial systems, yet despite this they are rare in nature. Why? Previous explanations have focused on the adaptive limits of combinatorial communication, or on its purported cognitive difficulties, but neither of these explains the full distribution of combinatorial communication in the natural world. Here, we present a nonlinear dynamical model of the emergence of combinatorial communication that, unlike previous models, considers how initially non-communicative behaviour evolves to take on a communicative function. We derive three basic principles about the emergence of combinatorial communication. We hence show that the interdependence of signals and responses places significant constraints on the historical pathways by which combinatorial signals might emerge, to the extent that anything other than the most simple form of combinatorial communication is extremely unlikely. We also argue that these constraints can be bypassed if individuals have the socio-cognitive capacity to engage in ostensive communication. Humans, but probably no other species, have this ability. This may explain why language, which is massively combinatorial, is such an extreme exception to nature's general trend for non-combinatorial communication.

Examining the intersection between splicing, nuclear export and small RNA pathways.

PubMed

Nabih, Amena; Sobotka, Julia A; Wu, Monica Z; Wedeles, Christopher J; Claycomb, Julie M

2017-11-01

Nuclear Argonaute/small RNA pathways in a variety of eukaryotic species are generally known to regulate gene expression via chromatin modulation and transcription attenuation in a process known as transcriptional gene silencing (TGS). However, recent data, including genetic screens, phylogenetic profiling, and molecular mechanistic studies, also point to a novel and emerging intersection between the splicing and nuclear export machinery with nuclear Argonaute/small RNA pathways in many organisms. In this review, we summarize the field's current understanding regarding the relationship between splicing, export and small RNA pathways, and consider the biological implications for coordinated regulation of transcripts by these pathways. We also address the importance and available approaches for understanding the RNA regulatory logic generated by the intersection of these particular pathways in the context of synthetic biology. The interactions between various eukaryotic RNA regulatory pathways, particularly splicing, nuclear export and small RNA pathways provide a type of combinatorial code that informs the identity ("self" versus "non-self") and dictates the fate of each transcript in a cell. Although the molecular mechanisms for how splicing and nuclear export impact small RNA pathways are not entirely clear at this early stage, the links between these pathways are widespread across eukaryotic phyla. The link between splicing, nuclear export, and small RNA pathways is emerging and establishes a new frontier for understanding the combinatorial logic of gene regulation across species that could someday be harnessed for therapeutic, biotechnology and agricultural applications. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

The lightest organic radical cation for charge storage in redox flow batteries

PubMed Central

Huang, Jinhua; Pan, Baofei; Duan, Wentao; Wei, Xiaoliang; Assary, Rajeev S.; Su, Liang; Brushett, Fikile R.; Cheng, Lei; Liao, Chen; Ferrandon, Magali S.; Wang, Wei; Zhang, Zhengcheng; Burrell, Anthony K.; Curtiss, Larry A.; Shkrob, Ilya A.; Moore, Jeffrey S.; Zhang, Lu

2016-01-01

In advanced electrical grids of the future, electrochemically rechargeable fluids of high energy density will capture the power generated from intermittent sources like solar and wind. To meet this outstanding technological demand there is a need to understand the fundamental limits and interplay of electrochemical potential, stability, and solubility in low-weight redox-active molecules. By generating a combinatorial set of 1,4-dimethoxybenzene derivatives with different arrangements of substituents, we discovered a minimalistic structure that combines exceptional long-term stability in its oxidized form and a record-breaking intrinsic capacity of 161 mAh/g. The nonaqueous redox flow battery has been demonstrated that uses this molecule as a catholyte material and operated stably for 100 charge/discharge cycles. The observed stability trends are rationalized by mechanistic considerations of the reaction pathways. PMID:27558638

The lightest organic radical cation for charge storage in redox flow batteries.

PubMed

Huang, Jinhua; Pan, Baofei; Duan, Wentao; Wei, Xiaoliang; Assary, Rajeev S; Su, Liang; Brushett, Fikile R; Cheng, Lei; Liao, Chen; Ferrandon, Magali S; Wang, Wei; Zhang, Zhengcheng; Burrell, Anthony K; Curtiss, Larry A; Shkrob, Ilya A; Moore, Jeffrey S; Zhang, Lu

2016-08-25

In advanced electrical grids of the future, electrochemically rechargeable fluids of high energy density will capture the power generated from intermittent sources like solar and wind. To meet this outstanding technological demand there is a need to understand the fundamental limits and interplay of electrochemical potential, stability, and solubility in low-weight redox-active molecules. By generating a combinatorial set of 1,4-dimethoxybenzene derivatives with different arrangements of substituents, we discovered a minimalistic structure that combines exceptional long-term stability in its oxidized form and a record-breaking intrinsic capacity of 161 mAh/g. The nonaqueous redox flow battery has been demonstrated that uses this molecule as a catholyte material and operated stably for 100 charge/discharge cycles. The observed stability trends are rationalized by mechanistic considerations of the reaction pathways.

Time-dependent combinatory effects of active mechanical loading and passive topographical cues on cell orientation.

PubMed

Wang, Qian; Huang, Hanyang; Wei, Kang; Zhao, Yi

2016-10-01

Mechanical stretching and topographical cues are both effective mechanical stimulations for regulating cell morphology, orientation, and behaviors. The competition of these two mechanical stimulations remains largely underexplored. Previous studies have suggested that a small cyclic mechanical strain is not able to reorient cells that have been pre-aligned by relatively large linear microstructures, but can reorient those pre-aligned by small linear micro/nanostructures if the characteristic dimension of these structures is below a certain threshold. Likewise, for micro/nanostructures with a given characteristic dimension, the strain must exceed a certain magnitude to overrule the topographic cues. There are however no in-depth investigations of such "thresholds" due to the lack of close examination of dynamic cell orientation during and shortly after the mechanical loading. In this study, the time-dependent combinatory effects of active and passive mechanical stimulations on cell orientation are investigated by developing a micromechanical stimulator. The results show that the cells pre-aligned by linear micro/nanostructures can be altered by cyclic in-plane strain, regardless of the structure size. During the loading, the micro/nanostructures can resist the reorientation effects by cyclic in-plane strain while the resistive capability (measured by the mean orientation angle change and the reorientation speed) increases with the increasing characteristic dimension. The micro/nanostructures also can recover the cell orientation after the cessation of cyclic in-plane strain, while the recovering capability increases with the characteristic dimension. The previously observed thresholds are largely dependent on the observation time points. In order to accurately evaluate the combinatory effects of the two mechanical stimulations, observations during the active loading with a short time interval or endpoint observations shortly after the loading are preferred. This study provides a microengineering solution to investigate the time-dependent combinatory effects of the active and passive mechanical stimulations and is expected to enhance our understanding of cell responses to complex mechanical environments. Biotechnol. Bioeng. 2016;113: 2191-2201. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell–like diffuse large B-cell lymphoma cells

PubMed Central

Mathews Griner, Lesley A.; Guha, Rajarshi; Shinn, Paul; Young, Ryan M.; Keller, Jonathan M.; Liu, Dongbo; Goldlust, Ian S.; Yasgar, Adam; McKnight, Crystal; Boxer, Matthew B.; Duveau, Damien Y.; Jiang, Jian-Kang; Michael, Sam; Mierzwa, Tim; Huang, Wenwei; Walsh, Martin J.; Mott, Bryan T.; Patel, Paresma; Leister, William; Maloney, David J.; Leclair, Christopher A.; Rai, Ganesha; Jadhav, Ajit; Peyser, Brian D.; Austin, Christopher P.; Martin, Scott E.; Simeonov, Anton; Ferrer, Marc; Staudt, Louis M.; Thomas, Craig J.

2014-01-01

The clinical development of drug combinations is typically achieved through trial-and-error or via insight gained through a detailed molecular understanding of dysregulated signaling pathways in a specific cancer type. Unbiased small-molecule combination (matrix) screening represents a high-throughput means to explore hundreds and even thousands of drug–drug pairs for potential investigation and translation. Here, we describe a high-throughput screening platform capable of testing compounds in pairwise matrix blocks for the rapid and systematic identification of synergistic, additive, and antagonistic drug combinations. We use this platform to define potential therapeutic combinations for the activated B-cell–like subtype (ABC) of diffuse large B-cell lymphoma (DLBCL). We identify drugs with synergy, additivity, and antagonism with the Bruton’s tyrosine kinase inhibitor ibrutinib, which targets the chronic active B-cell receptor signaling that characterizes ABC DLBCL. Ibrutinib interacted favorably with a wide range of compounds, including inhibitors of the PI3K-AKT-mammalian target of rapamycin signaling cascade, other B-cell receptor pathway inhibitors, Bcl-2 family inhibitors, and several components of chemotherapy that is the standard of care for DLBCL. PMID:24469833

Modern drug discovery technologies: opportunities and challenges in lead discovery.

PubMed

Guido, Rafael V C; Oliva, Glaucius; Andricopulo, Adriano D

2011-12-01

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM).

PubMed

Skinnider, Michael A; Dejong, Chris A; Rees, Philip N; Johnston, Chad W; Li, Haoxin; Webster, Andrew L H; Wyatt, Morgan A; Magarvey, Nathan A

2015-11-16

Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

DNA Polyplexes as Combinatory Drug Carriers of Doxorubicin and Cisplatin: An In Vitro Study

PubMed Central

Kang, Han Chang; Cho, Hana; Bae, You Han

2015-01-01

Double helix nucleic acids were used as a combination drug carrier for doxorubicin (DOX), which physically intercalates with DNA double helices, and cisplatin (CDDP), which binds to DNA without an alkylation reaction. DNA interacting with DOX, CDDP, or both was complexed with positively charged, endosomolytic polymers. Compared with the free drug, the polyplexes (100 ~ 170 nm in size) delivered more drug into the cytosol and the nucleus and demonstrated similar or superior (up to a 7-fold increase) in vitro cell-killing activity. Additionally, the gene expression activities of most of the chemical drug-loaded plasmid DNA (pDNA) polyplexes were not impaired by the physical interactions between the nucleic acid and DOX/CDDP. When a model reporter pDNA (luciferase) was employed, it expressed luciferase protein at 0.7- ~ 1.4-fold the amount expressed by the polyplex with no bound drugs (a control), which indicated the fast translocation of the intercalated or bound drugs from the “carrier DNA” to the “nuclear DNA” of target cells. The proposed concept may offer the possibility of versatile combination therapies of genetic materials and small molecule drugs that bind to nucleic acids to treat various diseases. PMID:26132975

Generation of a Selective Small Molecule Inhibitor of the CBP/p300 Bromodomain for Leukemia Therapy.

PubMed

Picaud, Sarah; Fedorov, Oleg; Thanasopoulou, Angeliki; Leonards, Katharina; Jones, Katherine; Meier, Julia; Olzscha, Heidi; Monteiro, Octovia; Martin, Sarah; Philpott, Martin; Tumber, Anthony; Filippakopoulos, Panagis; Yapp, Clarence; Wells, Christopher; Che, Ka Hing; Bannister, Andrew; Robson, Samuel; Kumar, Umesh; Parr, Nigel; Lee, Kevin; Lugo, Dave; Jeffrey, Philip; Taylor, Simon; Vecellio, Matteo L; Bountra, Chas; Brennan, Paul E; O'Mahony, Alison; Velichko, Sharlene; Müller, Susanne; Hay, Duncan; Daniels, Danette L; Urh, Marjeta; La Thangue, Nicholas B; Kouzarides, Tony; Prinjha, Rab; Schwaller, Jürg; Knapp, Stefan

2015-12-01

The histone acetyltransferases CBP/p300 are involved in recurrent leukemia-associated chromosomal translocations and are key regulators of cell growth. Therefore, efforts to generate inhibitors of CBP/p300 are of clinical value. We developed a specific and potent acetyl-lysine competitive protein-protein interaction inhibitor, I-CBP112, that targets the CBP/p300 bromodomains. Exposure of human and mouse leukemic cell lines to I-CBP112 resulted in substantially impaired colony formation and induced cellular differentiation without significant cytotoxicity. I-CBP112 significantly reduced the leukemia-initiating potential of MLL-AF9(+) acute myeloid leukemia cells in a dose-dependent manner in vitro and in vivo. Interestingly, I-CBP112 increased the cytotoxic activity of BET bromodomain inhibitor JQ1 as well as doxorubicin. Collectively, we report the development and preclinical evaluation of a novel, potent inhibitor targeting CBP/p300 bromodomains that impairs aberrant self-renewal of leukemic cells. The synergistic effects of I-CBP112 and current standard therapy (doxorubicin) as well as emerging treatment strategies (BET inhibition) provide new opportunities for combinatorial treatment of leukemia and potentially other cancers. ©2015 American Association for Cancer Research.

Generation of a selective small molecule inhibitor of the CBP/p300 bromodomain for leukemia therapy

PubMed Central

Jones, Katherine; Meier, Julia; Olzscha, Heidi; Monteiro, Octovia; Martin, Sarah; Philpott, Martin; Tumber, Anthony; Filippakopoulos, Panagis; Yapp, Clarence; Wells, Christopher; Che, Ka Hing; Bannister, Andrew; Robson, Samuel; Kumar, Umesh; Parr, Nigel; Lee, Kevin; Lugo, Dave; Jeffrey, Philip; Taylor, Simon; Vecellio, Matteo L.; Bountra, Chas; Brennan, Paul E.; O’Mahony, Alison; Velichko, Sharlene; Müller, Susanne; Hay, Duncan; Daniels, Danette L.; Urh, Marjeta; La Thangue, Nicholas B.; Kouzarides, Tony; Prinjha, Rab; Schwaller, Jürg; Knapp, Stefan

2016-01-01

The histone acetyltransferases CBP/p300 are involved in recurrent leukemia-associated chromosomal translocations and are key regulators of cell growth. Therefore, efforts to generate inhibitors of CBP/p300 are of clinical value. We developed a specific and potent acetyl-lysine competitive protein-protein interaction inhibitor, I-CBP112, that targets the CBP/p300 bromodomains. Exposure of human and mouse leukemic cell lines to I-CBP112 resulted in substantially impaired colony formation and induced cellular differentiation without significant cytotoxicity. I-CBP112 significantly reduced the leukemia-initiating potential of MLL-AF9+ AML cells in a dose-dependent manner in vitro and in vivo. Interestingly, I-CBP112 increased the cytotoxic activity of BET bromodomain inhibitor JQ1 as well as doxorubicin. Collectively we report the development and preclinical evaluation of a novel, potent inhibitor targeting CBP/p300 bromodomains that impairs aberrant self-renewal of leukemic cells. The synergistic effects of I-CBP112 and current standard therapy (doxorubicin) as well as emerging treatment strategies (BET inhibition) provide new opportunities for combinatorial treatment of leukemia and potentially other cancers. PMID:26552700

Combinatorial synthesis and in vitro evaluation of a biaryl hydroxyketone library as antivirulence agents against MRSA.

PubMed

Yu, Guanping; Kuo, David; Shoham, Menachem; Viswanathan, Rajesh

2014-02-10

Antibiotic resistance coupled with decreased development of new antibiotics necessitates the search for novel antibacterial agents. Antivirulence agents offer an alternative to conventional antibiotics. In this work, we report on a family of small-molecule antivirulence agents against methicillin-resistant Staphylococcus aureus (MRSA), the most widespread bacterial pathogen. Structure-activity relationship studies led to the development of a concise synthesis of a 148-member biarylhydroxyketone library. An acylation bond-forming process afforded resorcinols (1) and aryloxy acetonitriles (2) as synthons. A Lewis-acid-activated Friedel-Crafts' acylation step involving a nitrile functionality of 2 by ZnCl2, followed by nucleophilic attack by 1 was executed to obtain biaryl hydroxyketones in excellent yields. A large number of products crystallized. This strategy affords a range of biarylhydroxyketones in a single step. This is the first collective synthetic study documenting access to this class of compounds through a single synthetic operation. In vitro efficacy of compounds in this library was evaluated by a rabbit erythrocyte hemolysis assay. The most efficacious compound, 4f-12, inhibits hemolysis by 98.1 ± 0.1% compared to control in the absence of the compound.

Approaches to the origin of life on Earth.

PubMed

Kauffman, Stuart A

2011-11-18

I discuss briefly the history of the origin of life field, focusing on the "Miller" era of prebiotic synthesis, through the "Orgel" era seeking enzyme free template replication of single stranded RNA or similar polynucleotides, to the RNA world era with one of its foci on a ribozyme with the capacity to act as a polymerase able to copy itself. I give the history of the independent invention in 1971 by T. Ganti, M. Eigen and myself of three alternative theories of the origin of molecular replication: the Chemotron, the Hypercycle, and Collectively Autocatalytic Sets, CAS, respectively. To date, only collectively autocatalytic DNA, RNA, and peptide sets have achieved molecular reproduction of polymers. Theoretical work and experimental work on CAS both support their plausibility as models of openly evolvable protocells, if housed in dividing compartments such as dividing liposomes. My own further hypothesis beyond that of CAS in themselves, of their formation as a phase transition in complex chemical reaction systems of substrates, reactions and products, where the molecules in the system are candidates to catalyze the very same reactions, now firmly established as theorems, awaits experimental proof using combinatorial chemistry to make libraries of stochastic DNA, RNA and/or polypeptides, or other classes of molecules to test the hypothesis that molecular polymer reproduction has emerged as a true phase transition in complex chemical reaction systems. I remark that my colleague Marc Ballivet of the University of Geneva and I, may have issued the first publications discussing what became combinatorial chemistry, in published issued patents in 1987, 1989 and later, in this field.

TAZ Expression as a Prognostic Indicator in Colorectal Cancer

PubMed Central

Tham, Jill M.; Zhang, Xiaoqian; Zeng, Qi; Zhang, Shu-Dong; Hong, WanJin

2013-01-01

The Hippo pathway restricts the activity of transcriptional coactivators TAZ (WWTR1) and YAP. TAZ and YAP are reported to be overexpressed in various cancers, however, their prognostic significance in colorectal cancers remains unstudied. The expression levels of TAZ and YAP, and their downstream transcriptional targets, AXL and CTGF, were extracted from two independent colon cancer patient datasets available in the Gene Expression Omnibus database, totaling 522 patients. We found that mRNA expressions of both TAZ and YAP were positively correlated with those of AXL and CTGF (p<0.05). High level mRNA expression of TAZ, AXL or CTGF significantly correlated with shorter survival. Importantly, patients co-overexpressing all 3 genes had a significantly shorter survival time, and combinatorial expression of these 3 genes was an independent predictor for survival. The downstream target genes for TAZ-AXL-CTGF overexpression were identified by Java application MyStats. Interestingly, genes that are associated with colon cancer progression (ANTXR1, EFEMP2, SULF1, TAGLN, VCAN, ZEB1 and ZEB2) were upregulated in patients co-overexpressing TAZ-AXL-CTGF. This TAZ-AXL-CTGF gene expression signature (GES) was then applied to Connectivity Map to identify small molecules that could potentially be utilized to reverse this GES. Of the top 20 small molecules identified by connectivity map, amiloride (a potassium sparing diuretic,) and tretinoin (all-trans retinoic acid) have shown therapeutic promise in inhibition of colon cancer cell growth. Using MyStats, we found that low level expression of either ANO1 or SQLE were associated with a better prognosis in patients who co-overexpressed TAZ-AXL-CTGF, and that ANO1 was an independent predictor of survival together with TAZ-AXL-CTGF. Finally, we confirmed that TAZ regulates Axl, and plays an important role in clonogenicity and non-adherent growth in vitro and tumor formation in vivo. These data suggest that TAZ could be a therapeutic target for the treatment of colon cancer. PMID:23372686

Dendritic Cytoskeletal Architecture Is Modulated by Combinatorial Transcriptional Regulation in Drosophila melanogaster.

PubMed

Das, Ravi; Bhattacharjee, Shatabdi; Patel, Atit A; Harris, Jenna M; Bhattacharya, Surajit; Letcher, Jamin M; Clark, Sarah G; Nanda, Sumit; Iyer, Eswar Prasad R; Ascoli, Giorgio A; Cox, Daniel N

2017-12-01

Transcription factors (TFs) have emerged as essential cell autonomous mediators of subtype specific dendritogenesis; however, the downstream effectors of these TFs remain largely unknown, as are the cellular events that TFs control to direct morphological change. As dendritic morphology is largely dictated by the organization of the actin and microtubule (MT) cytoskeletons, elucidating TF-mediated cytoskeletal regulatory programs is key to understanding molecular control of diverse dendritic morphologies. Previous studies in Drosophila melanogaster have demonstrated that the conserved TFs Cut and Knot exert combinatorial control over aspects of dendritic cytoskeleton development, promoting actin and MT-based arbor morphology, respectively. To investigate transcriptional targets of Cut and/or Knot regulation, we conducted systematic neurogenomic studies, coupled with in vivo genetic screens utilizing multi-fluor cytoskeletal and membrane marker reporters. These analyses identified a host of putative Cut and/or Knot effector molecules, and a subset of these putative TF targets converge on modulating dendritic cytoskeletal architecture, which are grouped into three major phenotypic categories, based upon neuromorphometric analyses: complexity enhancer, complexity shifter, and complexity suppressor. Complexity enhancer genes normally function to promote higher order dendritic growth and branching with variable effects on MT stabilization and F-actin organization, whereas complexity shifter and complexity suppressor genes normally function in regulating proximal-distal branching distribution or in restricting higher order branching complexity, respectively, with spatially restricted impacts on the dendritic cytoskeleton. Collectively, we implicate novel genes and cellular programs by which TFs distinctly and combinatorially govern dendritogenesis via cytoskeletal modulation. Copyright © 2017 by the Genetics Society of America.

Synthesis of Chemiluminescent Esters: A Combinatorial Synthesis Experiment for Organic Chemistry Students

ERIC Educational Resources Information Center

Duarte, Robert; Nielson, Janne T.; Dragojlovic, Veljko

2004-01-01

A group of techniques aimed at synthesizing a large number of structurally diverse compounds is called combinatorial synthesis. Synthesis of chemiluminescence esters using parallel combinatorial synthesis and mix-and-split combinatorial synthesis is experimented.

A Discriminative Sentence Compression Method as Combinatorial Optimization Problem

NASA Astrophysics Data System (ADS)

Hirao, Tsutomu; Suzuki, Jun; Isozaki, Hideki

In the study of automatic summarization, the main research topic was `important sentence extraction' but nowadays `sentence compression' is a hot research topic. Conventional sentence compression methods usually transform a given sentence into a parse tree or a dependency tree, and modify them to get a shorter sentence. However, this method is sometimes too rigid. In this paper, we regard sentence compression as an combinatorial optimization problem that extracts an optimal subsequence of words. Hori et al. also proposed a similar method, but they used only a small number of features and their weights were tuned by hand. We introduce a large number of features such as part-of-speech bigrams and word position in the sentence. Furthermore, we train the system by discriminative learning. According to our experiments, our method obtained better score than other methods with statistical significance.

Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.

ERIC Educational Resources Information Center

English, Lyn

1999-01-01

Assesses children's structural understanding of combinatorial problems when presented in a variety of task situations. Provides an explanatory model of students' combinatorial understandings that informs teaching and assessment. Addresses several components of children's structural understanding of elementary combinatorial problems. (Contains 50…

FLIPPER, a combinatorial probe for correlated live imaging and electron microscopy, allows identification and quantitative analysis of various cells and organelles.

PubMed

Kuipers, Jeroen; van Ham, Tjakko J; Kalicharan, Ruby D; Veenstra-Algra, Anneke; Sjollema, Klaas A; Dijk, Freark; Schnell, Ulrike; Giepmans, Ben N G

2015-04-01

Ultrastructural examination of cells and tissues by electron microscopy (EM) yields detailed information on subcellular structures. However, EM is typically restricted to small fields of view at high magnification; this makes quantifying events in multiple large-area sample sections extremely difficult. Even when combining light microscopy (LM) with EM (correlated LM and EM: CLEM) to find areas of interest, the labeling of molecules is still a challenge. We present a new genetically encoded probe for CLEM, named "FLIPPER", which facilitates quantitative analysis of ultrastructural features in cells. FLIPPER consists of a fluorescent protein (cyan, green, orange, or red) for LM visualization, fused to a peroxidase allowing visualization of targets at the EM level. The use of FLIPPER is straightforward and because the module is completely genetically encoded, cells can be optimally prepared for EM examination. We use FLIPPER to quantify cellular morphology at the EM level in cells expressing a normal and disease-causing point-mutant cell-surface protein called EpCAM (epithelial cell adhesion molecule). The mutant protein is retained in the endoplasmic reticulum (ER) and could therefore alter ER function and morphology. To reveal possible ER alterations, cells were co-transfected with color-coded full-length or mutant EpCAM and a FLIPPER targeted to the ER. CLEM examination of the mixed cell population allowed color-based cell identification, followed by an unbiased quantitative analysis of the ER ultrastructure by EM. Thus, FLIPPER combines bright fluorescent proteins optimized for live imaging with high sensitivity for EM labeling, thereby representing a promising tool for CLEM.

Hypergraph-Based Combinatorial Optimization of Matrix-Vector Multiplication

ERIC Educational Resources Information Center

Wolf, Michael Maclean

2009-01-01

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Human olfactory receptor responses to odorants

PubMed Central

Mainland, Joel D; Li, Yun R; Zhou, Ting; Liu, Wen Ling L; Matsunami, Hiroaki

2015-01-01

Although the human olfactory system is capable of discriminating a vast number of odors, we do not currently understand what chemical features are encoded by olfactory receptors. In large part this is due to a paucity of data in a search space covering the interactions of hundreds of receptors with billions of odorous molecules. Of the approximately 400 intact human odorant receptors, only 10% have a published ligand. Here we used a heterologous luciferase assay to screen 73 odorants against a clone library of 511 human olfactory receptors. This dataset will allow other researchers to interrogate the combinatorial nature of olfactory coding. PMID:25977809

Compound Libraries: Recent Advances and Their Applications in Drug Discovery.

PubMed

Gong, Zhen; Hu, Guoping; Li, Qiang; Liu, Zhiguo; Wang, Fei; Zhang, Xuejin; Xiong, Jian; Li, Peng; Xu, Yan; Ma, Rujian; Chen, Shuhui; Li, Jian

2017-01-01

Hit identification is the starting point of small-molecule drug discovery and is therefore very important to the pharmaceutical industry. One of the most important approaches to identify a new hit is to screen a compound library using an in vitro assay. High-throughput screening has made great contributions to drug discovery since the 1990s but requires expensive equipment and facilities, and its success depends on the size of the compound library. Recent progress in the development of compound libraries has provided more efficient ways to identify new hits for novel drug targets, thereby helping to promote the development of the pharmaceutical industry, especially for firstin- class drugs. A multistage and systematic research of articles published between 1986 and 2017 has been performed, which was organized into 5 sections and discussed in detail. In this review, the sources and classification of compound libraries are summarized. The progress made in combinatorial libraries and DNA-encoded libraries is reviewed. Library design methods, especially for focused libraries, are introduced in detail. In the final part, the status of the compound libraries at WuXi is reported. The progress related to compound libraries, especially drug template libraries, DELs, and focused libraries, will help to identify better hits for novel drug targets and promote the development of the pharmaceutical industry. Moreover, these libraries can facilitate hit identification, which benefits most research organizations, including academics and small companies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Single-carbon discrimination by selected peptides for individual detection of volatile organic compounds

NASA Astrophysics Data System (ADS)

Ju, Soomi; Lee, Ki-Young; Min, Sun-Joon; Yoo, Yong Kyoung; Hwang, Kyo Seon; Kim, Sang Kyung; Yi, Hyunjung

2015-03-01

Although volatile organic compounds (VOCs) are becoming increasingly recognized as harmful agents and potential biomarkers, selective detection of the organic targets remains a tremendous challenge. Among the materials being investigated for target recognition, peptides are attractive candidates because of their chemical robustness, divergence, and their homology to natural olfactory receptors. Using a combinatorial peptide library and either a graphitic surface or phenyl-terminated self-assembled monolayer as relevant target surfaces, we successfully selected three interesting peptides that differentiate a single carbon deviation among benzene and its analogues. The heterogeneity of the designed target surfaces provided peptides with varying affinity toward targeted molecules and generated a set of selective peptides that complemented each other. Microcantilever sensors conjugated with each peptide quantitated benzene, toluene and xylene to sub-ppm levels in real time. The selection of specific receptors for a group of volatile molecules will provide a strong foundation for general approach to individually monitoring VOCs.

Electronic single-molecule identification of carbohydrate isomers by recognition tunnelling

NASA Astrophysics Data System (ADS)

Im, Jongone; Biswas, Sovan; Liu, Hao; Zhao, Yanan; Sen, Suman; Biswas, Sudipta; Ashcroft, Brian; Borges, Chad; Wang, Xu; Lindsay, Stuart; Zhang, Peiming

2016-12-01

Carbohydrates are one of the four main building blocks of life, and are categorized as monosaccharides (sugars), oligosaccharides and polysaccharides. Each sugar can exist in two alternative anomers (in which a hydroxy group at C-1 takes different orientations) and each pair of sugars can form different epimers (isomers around the stereocentres connecting the sugars). This leads to a vast combinatorial complexity, intractable to mass spectrometry and requiring large amounts of sample for NMR characterization. Combining measurements of collision cross section with mass spectrometry (IM-MS) helps, but many isomers are still difficult to separate. Here, we show that recognition tunnelling (RT) can classify many anomers and epimers via the current fluctuations they produce when captured in a tunnel junction functionalized with recognition molecules. Most importantly, RT is a nanoscale technique utilizing sub-picomole quantities of analyte. If integrated into a nanopore, RT would provide a unique approach to sequencing linear polysaccharides.

Effector-Triggered Self-Replication in Coupled Subsystems.

PubMed

Komáromy, Dávid; Tezcan, Meniz; Schaeffer, Gaël; Marić, Ivana; Otto, Sijbren

2017-11-13

In living systems processes like genome duplication and cell division are carefully synchronized through subsystem coupling. If we are to create life de novo, similar control over essential processes such as self-replication need to be developed. Here we report that coupling two dynamic combinatorial subsystems, featuring two separate building blocks, enables effector-mediated control over self-replication. The subsystem based on the first building block shows only self-replication, whereas that based on the second one is solely responsive toward a specific external effector molecule. Mixing the subsystems arrests replication until the effector molecule is added, resulting in the formation of a host-effector complex and the liberation of the building block that subsequently engages in self-replication. The onset, rate and extent of self-replication is controlled by the amount of effector present. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems

DOEpatents

Van Benthem, Mark H.; Keenan, Michael R.

2008-11-11

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

Spectral monodromy of non-self-adjoint operators

NASA Astrophysics Data System (ADS)

Phan, Quang Sang

2014-01-01

In the present paper, we build a combinatorial invariant, called the "spectral monodromy" from the spectrum of a single (non-self-adjoint) h-pseudodifferential operator with two degrees of freedom in the semi-classical limit. Our inspiration comes from the quantum monodromy defined for the joint spectrum of an integrable system of n commuting self-adjoint h-pseudodifferential operators, given by S. Vu Ngoc ["Quantum monodromy in integrable systems," Commun. Math. Phys. 203(2), 465-479 (1999)]. The first simple case that we treat in this work is a normal operator. In this case, the discrete spectrum can be identified with the joint spectrum of an integrable quantum system. The second more complex case we propose is a small perturbation of a self-adjoint operator with a classical integrability property. We show that the discrete spectrum (in a small band around the real axis) also has a combinatorial monodromy. The main difficulty in this case is that we do not know the description of the spectrum everywhere, but only in a Cantor type set. In addition, we also show that the corresponding monodromy can be identified with the classical monodromy, defined by J. Duistermaat ["On global action-angle coordinates," Commun. Pure Appl. Math. 33(6), 687-706 (1980)].

Mesoporous materials and nanocrystals for enhancing the dissolution behavior of poorly water-soluble drugs.

PubMed

Santos, Helder A; Peltonen, Leena; Limnell, Tarja; Hirvonen, Jouni

2013-01-01

Advanced drug delivery formulations are presently recognized as promising tools for overcoming the adverse physicochemical properties of conventional drug molecules, such as poor water solubility, which often leads to poor drug bioavailability. Oral drug delivery is considered as the easiest and most convenient route of drug administration. However, via the current trends utilizing combinatorial chemistry and high throughput screening in drug development, new drug molecules are moving towards lipophilic and poorly water-soluble large molecules, and the oral delivery route is becoming increasingly challenging. In this context, formulation of poorly soluble and/or permeable drugs using mesoporous materials and nanocrystals technology have proven to be highly successful due to the greater surface/volume ratio of these systems, resulting in improvements in dissolution and bioavailability, as well as enhanced drug permeability. This review addresses the issues of poorly water-soluble drugs with a major focus on recent developments in the application of the mesoporous materials (e.g., porous silicon and silica) and nanocrystals in drug delivery applications. In addition, we present several recent examples of the significant potential of these materials for the pharmaceutical field.

MARCC (Matrix-Assisted Reader Chromatin Capture): an antibody-free method to enrich and analyze combinatorial nucleosome modifications

PubMed Central

Su, Zhangli

2016-01-01

Combinatorial patterns of histone modifications are key indicators of different chromatin states. Most of the current approaches rely on the usage of antibodies to analyze combinatorial histone modifications. Here we detail an antibody-free method named MARCC (Matrix-Assisted Reader Chromatin Capture) to enrich combinatorial histone modifications. The combinatorial patterns are enriched on native nucleosomes extracted from cultured mammalian cells and prepared by micrococcal nuclease digestion. Such enrichment is achieved by recombinant chromatin-interacting protein modules, or so-called reader domains, which can bind in a combinatorial modification-dependent manner. The enriched chromatin can be quantified by western blotting or mass spectrometry for the co-existence of histone modifications, while the associated DNA content can be analyzed by qPCR or next-generation sequencing. Altogether, MARCC provides a reproducible, efficient and customizable solution to enrich and analyze combinatorial histone modifications. PMID:26131849

A New Approach for Proving or Generating Combinatorial Identities

ERIC Educational Resources Information Center

Gonzalez, Luis

2010-01-01

A new method for proving, in an immediate way, many combinatorial identities is presented. The method is based on a simple recursive combinatorial formula involving n + 1 arbitrary real parameters. Moreover, this formula enables one not only to prove, but also generate many different combinatorial identities (not being required to know them "a…

Azide–Alkyne Click Conjugation on Quantum Dots by Selective Copper Coordination

PubMed Central

Mann, Victor R.; Powers, Alexander S.; Tilley, Drew C.; Sack, Jon T.; Cohen, Bruce E.

2018-01-01

Functionalization of nanocrystals is essential for their practical application, but synthesis on nanocrystal surfaces is limited by incompatibilities with certain key reagents. The copper-catalyzed azide-alkyne cycloaddition (CuAAC) is among the most useful methods for ligating molecules to surfaces, but has been largely useless for semiconductor quantum dots (QDs) because Cu+ ions quickly and irreversibly quench QD fluorescence. To discover non-quenching synthetic conditions for Cu-catalyzed click reactions on QD surfaces, we developed a combinatorial fluorescence assay to screen >2000 reaction conditions to maximize cycloaddition efficiency while minimizing QD quenching. We identify conditions for complete coupling without significant quenching, which are compatible with common QD polymer surfaces and various azide/alkyne pairs. Based on insight from the combinatorial screen and mechanistic studies of Cu coordination and quenching, we find that superstoichiometric concentrations of Cu can promote full coupling if accompanied by ligands that selectively compete the Cu from the QD surface but allow it to remain catalytically active. Applied to the conjugation of a K+ channel-specific peptidyl toxin to CdSe/ZnS QDs, we synthesize unquenched QD conjugates and image their specific and voltage-dependent affinity for K+ channels in live cells. PMID:29608274

Programmable single-cell mammalian biocomputers.

PubMed

Ausländer, Simon; Ausländer, David; Müller, Marius; Wieland, Markus; Fussenegger, Martin

2012-07-05

Synthetic biology has advanced the design of standardized control devices that program cellular functions and metabolic activities in living organisms. Rational interconnection of these synthetic switches resulted in increasingly complex designer networks that execute input-triggered genetic instructions with precision, robustness and computational logic reminiscent of electronic circuits. Using trigger-controlled transcription factors, which independently control gene expression, and RNA-binding proteins that inhibit the translation of transcripts harbouring specific RNA target motifs, we have designed a set of synthetic transcription–translation control devices that could be rewired in a plug-and-play manner. Here we show that these combinatorial circuits integrated a two-molecule input and performed digital computations with NOT, AND, NAND and N-IMPLY expression logic in single mammalian cells. Functional interconnection of two N-IMPLY variants resulted in bitwise intracellular XOR operations, and a combinatorial arrangement of three logic gates enabled independent cells to perform programmable half-subtractor and half-adder calculations. Individual mammalian cells capable of executing basic molecular arithmetic functions isolated or coordinated to metabolic activities in a predictable, precise and robust manner may provide new treatment strategies and bio-electronic interfaces in future gene-based and cell-based therapies.

Searching for substructures in fragment spaces.

PubMed

Ehrlich, Hans-Christian; Volkamer, Andrea; Rarey, Matthias

2012-12-21

A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are composed of molecular fragments and their connection rules, made the representation of large combinatorial data sets feasible. At the same time, search algorithms face the problem of structural features spanning over multiple fragments. Due to the combinatorial nature of FSs, an enumeration of all products is impossible. In order to overcome these time and storage issues, we present a method that is able to find substructures in FSs without explicit product enumeration. This is accomplished by splitting substructures into subsubstructures and mapping them onto fragments with respect to fragment connectivity rules. The method has been evaluated on three different drug discovery scenarios considering the exploration of a molecule class, the elaboration of decoration patterns for a molecular core, and the exhaustive query for peptides in FSs. FSs can be searched in seconds, and found products contain novel compounds not present in the PubChem database which may serve as hints for new lead structures.

Phenotype-information-phenotype cycle for deconvolution of combinatorial antibody libraries selected against complex systems.

PubMed

Zhang, Hongkai; Torkamani, Ali; Jones, Teresa M; Ruiz, Diana I; Pons, Jaume; Lerner, Richard A

2011-08-16

Use of large combinatorial antibody libraries and next-generation sequencing of nucleic acids are two of the most powerful methods in modern molecular biology. The libraries are screened using the principles of evolutionary selection, albeit in real time, to enrich for members with a particular phenotype. This selective process necessarily results in the loss of information about less-fit molecules. On the other hand, sequencing of the library, by itself, gives information that is mostly unrelated to phenotype. If the two methods could be combined, the full potential of very large molecular libraries could be realized. Here we report the implementation of a phenotype-information-phenotype cycle that integrates information and gene recovery. After selection for phage-encoded antibodies that bind to targets expressed on the surface of Escherichia coli, the information content of the selected pool is obtained by pyrosequencing. Sequences that encode specific antibodies are identified by a bioinformatic analysis and recovered by a stringent affinity method that is uniquely suited for gene isolation from a highly degenerate collection of nucleic acids. This approach can be generalized for selection of antibodies against targets that are present as minor components of complex systems.

Molecular targets for small-molecule modulators of circadian clocks

PubMed Central

He, Baokun; Chen, Zheng

2016-01-01

Background Circadian clocks are endogenous timing systems that regulate various aspects of mammalian metabolism, physiology and behavior. Traditional chronotherapy refers to the administration of drugs in a defined circadian time window to achieve optimal pharmacokinetic and therapeutic efficacies. In recent years, substantial efforts have been dedicated to developing novel small-molecule modulators of circadian clocks. Methods Here, we review the recent progress in the identification of molecular targets of small-molecule clock modulators and their efficacies in clock-related disorders. Specifically, we examine the clock components and regulatory factors as possible molecular targets of small molecules, and we review several key clock-related disorders as promising venues for testing the preventive/therapeutic efficacies of these small molecules. Finally, we also discuss circadian regulation of drug metabolism. Results Small molecules can modulate the period, phase and/or amplitude of the circadian cycle. Core clock proteins, nuclear hormone receptors, and clock-related kinases and other epigenetic regulators are promising molecular targets for small molecules. Through these targets small molecules exert protective effects against clock-related disorders including the metabolic syndrome, immune disorders, sleep disorders and cancer. Small molecules can also modulate circadian drug metabolism and response to existing therapeutics. Conclusion Small-molecule clock modulators target clock components or diverse cellular pathways that functionally impinge upon the clock. Target identification of new small-molecule modulators will deepen our understanding of key regulatory nodes in the circadian network. Studies of clock modulators will facilitate their therapeutic applications, alone or in combination, for clock-related diseases. PMID:26750111

High-Throughput Genetic Analysis and Combinatorial Chiral Separations Based on Capillary Electrophoresis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, Wenwan

2003-01-01

Capillary electrophoresis (CE) offers many advantages over conventional analytical methods, such as speed, simplicity, high resolution, low cost, and small sample consumption, especially for the separation of enantiomers. However, chiral method developments still can be time consuming and tedious. They designed a comprehensive enantioseparation protocol employing neutral and sulfated cyclodextrins as chiral selectors for common basic, neutral, and acidic compounds with a 96-capillary array system. By using only four judiciously chosen separation buffers, successful enantioseparations were achieved for 49 out of 54 test compounds spanning a large variety of pKs and structures. Therefore, unknown compounds can be screened in thismore » manner to identify optimal enantioselective conditions in just one rn. In addition to superior separation efficiency for small molecules, CE is also the most powerful technique for DNA separations. Using the same multiplexed capillary system with UV absorption detection, the sequence of a short DNA template can be acquired without any dye-labels. Two internal standards were utilized to adjust the migration time variations among capillaries, so that the four electropherograms for the A, T, C, G Sanger reactions can be aligned and base calling can be completed with a high level of confidence. the CE separation of DNA can be applied to study differential gene expression as well. Combined with pattern recognition techniques, small variations among electropherograms obtained by the separation of cDNA fragments produced from the total RNA samples of different human tissues can be revealed. These variations reflect the differences in total RNA expression among tissues. Thus, this Ce-based approach can serve as an alternative to the DNA array techniques in gene expression analysis.« less

Recent advances in developing small molecules targeting RNA.

PubMed

Guan, Lirui; Disney, Matthew D

2012-01-20

RNAs are underexploited targets for small molecule drugs or chemical probes of function. This may be due, in part, to a fundamental lack of understanding of the types of small molecules that bind RNA specifically and the types of RNA motifs that specifically bind small molecules. In this review, we describe recent advances in the development and design of small molecules that bind to RNA and modulate function that aim to fill this void.

Fuel management optimization using genetic algorithms and code independence

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1994-12-31

Fuel management optimization is a hard problem for traditional optimization techniques. Loading pattern optimization is a large combinatorial problem without analytical derivative information. Therefore, methods designed for continuous functions, such as linear programming, do not always work well. Genetic algorithms (GAs) address these problems and, therefore, appear ideal for fuel management optimization. They do not require derivative information and work well with combinatorial. functions. The GAs are a stochastic method based on concepts from biological genetics. They take a group of candidate solutions, called the population, and use selection, crossover, and mutation operators to create the next generation of bettermore » solutions. The selection operator is a {open_quotes}survival-of-the-fittest{close_quotes} operation and chooses the solutions for the next generation. The crossover operator is analogous to biological mating, where children inherit a mixture of traits from their parents, and the mutation operator makes small random changes to the solutions.« less

Target-directed Dynamic Combinatorial Chemistry: A Study on Potentials and Pitfalls as Exemplified on a Bacterial Target.

PubMed

Frei, Priska; Pang, Lijuan; Silbermann, Marleen; Eriş, Deniz; Mühlethaler, Tobias; Schwardt, Oliver; Ernst, Beat

2017-08-25

Target-directed dynamic combinatorial chemistry (DCC) is an emerging technique for the efficient identification of inhibitors of pharmacologically relevant targets. In this contribution, we present an application for a bacterial target, the lectin FimH, a crucial virulence factor of uropathogenic E. coli being the main cause of urinary tract infections. A small dynamic library of acylhydrazones was formed from aldehydes and hydrazides and equilibrated at neutral pH in presence of aniline as nucleophilic catalyst. The major success factors turned out to be an accordingly adjusted ratio of scaffolds and fragments, an adequate sample preparation prior to HPLC analysis, and the data processing. Only then did the ranking of the dynamic library constituents correlate well with affinity data. Furthermore, as a support of DCC applications especially to larger libraries, a new protocol for improved hit identification was established. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort.

PubMed

Jeschek, Markus; Gerngross, Daniel; Panke, Sven

2016-03-31

Rational flux design in metabolic engineering approaches remains difficult since important pathway information is frequently not available. Therefore empirical methods are applied that randomly change absolute and relative pathway enzyme levels and subsequently screen for variants with improved performance. However, screening is often limited on the analytical side, generating a strong incentive to construct small but smart libraries. Here we introduce RedLibs (Reduced Libraries), an algorithm that allows for the rational design of smart combinatorial libraries for pathway optimization thereby minimizing the use of experimental resources. We demonstrate the utility of RedLibs for the design of ribosome-binding site libraries by in silico and in vivo screening with fluorescent proteins and perform a simple two-step optimization of the product selectivity in the branched multistep pathway for violacein biosynthesis, indicating a general applicability for the algorithm and the proposed heuristics. We expect that RedLibs will substantially simplify the refactoring of synthetic metabolic pathways.

Inhibition of CRM1-dependent nuclear export sensitizes malignant cells to cytotoxic and targeted agents

PubMed Central

Turner, Joel G.; Dawson, Jana; Cubitt, Christopher L.; Baz, Rachid; Sullivan, Daniel M.

2014-01-01

Nuclear-cytoplasmic trafficking of proteins is a significant factor in the development of cancer and drug resistance. Subcellular localization of exported proteins linked to cancer development include those involved in cell growth and proliferation, apoptosis, cell cycle regulation, transformation, angiogenesis, cell adhesion, invasion, and metastasis. Here, we examined the basic mechanisms involved in the export of proteins from the nucleus to the cytoplasm. All proteins over 40 kDa use the nuclear pore complex to gain entry or exit from the nucleus, with the primary nuclear export molecule involved in these processes being chromosome region maintenance 1 (CRM1, exportin 1 or XPO1). Proteins exported from the nucleus must possess a hydrophobic nuclear export signal (NES) peptide that binds to a hydrophobic groove containing an active-site Cys528 in the CRM1 protein. CRM1 inhibitors function largely by covalent modification of the active site Cys528 and prevent binding to the cargo protein NES. In the absence of a CRM1 inhibitor, CRM1 binds cooperatively to the NES of the cargo protein and RanGTP, forming a trimer that is actively transported out of the nucleus by facilitated diffusion. Nuclear export can be blocked by CRM1 inhibitors, NES peptide inhibitors or by preventing post-translational modification of cargo proteins. Clinical trials using the classic CRM1 inhibitor leptomycin B proved too toxic for patients; however, a new generation of less toxic small molecule inhibitors are being used in clinical trials in patients with both hematological malignancies and solid tumors. Additional trials are being initiated using small-molecule CRM1 inhibitors in combination with chemotherapeutics such as pegylated liposomal doxorubicin. In this review, we present evidence that combining the new CRM1 inhibitors with other classes of therapeutics may prove effective in the treatment of cancer. Potential combinatorial therapies discussed include the use of CRM1 inhibitors and the addition of alkylating agents (melphalan), anthracyclines (doxorubicin and daunomycin), BRAF inhibitors, platinum drugs (cisplatin and oxaliplatin), proteosome inhibitors (bortezomib and carfilzomib), or tyrosine-kinase inhibitors (imatinib). Also, the sequence of treatment may be important for combination therapy. We found that the most effective treatment regimen involved first priming the cancer cells with the CRM1 inhibitor followed by doxorubicin, bortezomib, carfilzomib, or melphalan. This order sensitized both de novo and acquired drug-resistant cancer cell lines. PMID:24631834

Exercises in molecular computing.

PubMed

Stojanovic, Milan N; Stefanovic, Darko; Rudchenko, Sergei

2014-06-17

CONSPECTUS: The successes of electronic digital logic have transformed every aspect of human life over the last half-century. The word "computer" now signifies a ubiquitous electronic device, rather than a human occupation. Yet evidently humans, large assemblies of molecules, can compute, and it has been a thrilling challenge to develop smaller, simpler, synthetic assemblies of molecules that can do useful computation. When we say that molecules compute, what we usually mean is that such molecules respond to certain inputs, for example, the presence or absence of other molecules, in a precisely defined but potentially complex fashion. The simplest way for a chemist to think about computing molecules is as sensors that can integrate the presence or absence of multiple analytes into a change in a single reporting property. Here we review several forms of molecular computing developed in our laboratories. When we began our work, combinatorial approaches to using DNA for computing were used to search for solutions to constraint satisfaction problems. We chose to work instead on logic circuits, building bottom-up from units based on catalytic nucleic acids, focusing on DNA secondary structures in the design of individual circuit elements, and reserving the combinatorial opportunities of DNA for the representation of multiple signals propagating in a large circuit. Such circuit design directly corresponds to the intuition about sensors transforming the detection of analytes into reporting properties. While this approach was unusual at the time, it has been adopted since by other groups working on biomolecular computing with different nucleic acid chemistries. We created logic gates by modularly combining deoxyribozymes (DNA-based enzymes cleaving or combining other oligonucleotides), in the role of reporting elements, with stem-loops as input detection elements. For instance, a deoxyribozyme that normally exhibits an oligonucleotide substrate recognition region is modified such that a stem-loop closes onto the substrate recognition region, making it unavailable for the substrate and thus rendering the deoxyribozyme inactive. But a conformational change can then be induced by an input oligonucleotide, complementary to the loop, to open the stem, allow the substrate to bind, and allow its cleavage to proceed, which is eventually reported via fluorescence. In this Account, several designs of this form are reviewed, along with their application in the construction of large circuits that exhibited complex logical and temporal relationships between the inputs and the outputs. Intelligent (in the sense of being capable of nontrivial information processing) theranostic (therapy + diagnostic) applications have always been the ultimate motivation for developing computing (i.e., decision-making) circuits, and we review our experiments with logic-gate elements bound to cell surfaces that evaluate the proximal presence of multiple markers on lymphocytes.

Exercises in Molecular Computing

PubMed Central

2014-01-01

Conspectus The successes of electronic digital logic have transformed every aspect of human life over the last half-century. The word “computer” now signifies a ubiquitous electronic device, rather than a human occupation. Yet evidently humans, large assemblies of molecules, can compute, and it has been a thrilling challenge to develop smaller, simpler, synthetic assemblies of molecules that can do useful computation. When we say that molecules compute, what we usually mean is that such molecules respond to certain inputs, for example, the presence or absence of other molecules, in a precisely defined but potentially complex fashion. The simplest way for a chemist to think about computing molecules is as sensors that can integrate the presence or absence of multiple analytes into a change in a single reporting property. Here we review several forms of molecular computing developed in our laboratories. When we began our work, combinatorial approaches to using DNA for computing were used to search for solutions to constraint satisfaction problems. We chose to work instead on logic circuits, building bottom-up from units based on catalytic nucleic acids, focusing on DNA secondary structures in the design of individual circuit elements, and reserving the combinatorial opportunities of DNA for the representation of multiple signals propagating in a large circuit. Such circuit design directly corresponds to the intuition about sensors transforming the detection of analytes into reporting properties. While this approach was unusual at the time, it has been adopted since by other groups working on biomolecular computing with different nucleic acid chemistries. We created logic gates by modularly combining deoxyribozymes (DNA-based enzymes cleaving or combining other oligonucleotides), in the role of reporting elements, with stem–loops as input detection elements. For instance, a deoxyribozyme that normally exhibits an oligonucleotide substrate recognition region is modified such that a stem–loop closes onto the substrate recognition region, making it unavailable for the substrate and thus rendering the deoxyribozyme inactive. But a conformational change can then be induced by an input oligonucleotide, complementary to the loop, to open the stem, allow the substrate to bind, and allow its cleavage to proceed, which is eventually reported via fluorescence. In this Account, several designs of this form are reviewed, along with their application in the construction of large circuits that exhibited complex logical and temporal relationships between the inputs and the outputs. Intelligent (in the sense of being capable of nontrivial information processing) theranostic (therapy + diagnostic) applications have always been the ultimate motivation for developing computing (i.e., decision-making) circuits, and we review our experiments with logic-gate elements bound to cell surfaces that evaluate the proximal presence of multiple markers on lymphocytes. PMID:24873234

ILP-2 modeling and virtual screening of an FDA-approved library:a possible anticancer therapy.

PubMed

Khalili, Saeed; Mohammadpour, Hemn; Shokrollahi Barough, Mahideh; Kokhaei, Parviz

2016-06-23

The members of the inhibitors of apoptosis protein (IAP) family inhibit diverse components of the caspase signaling pathway, notably caspase 3, 7, and 9. ILP-2 (BIRC-8) is the most recently identified member of the IAPs, mainly interacting with caspase 9. This interaction would eventually lead to death resistance in the case of cancerous cells. Therefore, structural modeling of ILP-2 and finding applicable inhibitors of its interaction with caspase 9 are a compelling challenge. Three main protein modeling approaches along with various model refinement measures were harnessed to achieve a reliable 3D model, using state-of-the-art software. Thereafter, the selected model was employed to perform virtual screening of an FDA approved library. A model built by a combinatorial approach (homology and ab initio approaches) was chosen as the best model. Model refinement processes successfully bolstered the model quality. Virtual screening of the compound library introduced several high affinity inhibitor candidates that interact with functional residues of ILP2. Given the 3D structure of the ILP2 molecule, we found promising inhibitory molecules. In addition to high affinity towards the ILP2 molecule, these molecules interact with residues that play pivotal rules in ILP2-caspase interaction. These molecules would inhibit ILP2-caspase interaction and consequently would lead to reactivated cell apoptosis through the caspases pathway.

Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

PubMed

Lee, M L; Schneider, G

2001-01-01

Natural products were analyzed to determine whether they contain appealing novel scaffold architectures for potential use in combinatorial chemistry. Ring systems were extracted and clustered on the basis of structural similarity. Several such potential scaffolds for combinatorial chemistry were identified that are not present in current trade drugs. For one of these scaffolds a virtual combinatorial library was generated. Pharmacophoric properties of natural products, trade drugs, and the virtual combinatorial library were assessed using a self-organizing map. Obviously, current trade drugs and natural products have several topological pharmacophore patterns in common. These features can be systematically explored with selected combinatorial libraries based on a combination of natural product-derived and synthetic molecular building blocks.

Use of combinatorial chemistry to speed drug discovery.

PubMed

Rádl, S

1998-10-01

IBC's International Conference on Integrating Combinatorial Chemistry into the Discovery Pipeline was held September 14-15, 1998. The program started with a pre-conference workshop on High-Throughput Compound Characterization and Purification. The agenda of the main conference was divided into sessions of Synthesis, Automation and Unique Chemistries; Integrating Combinatorial Chemistry, Medicinal Chemistry and Screening; Combinatorial Chemistry Applications for Drug Discovery; and Information and Data Management. This meeting was an excellent opportunity to see how big pharma, biotech and service companies are addressing the current bottlenecks in combinatorial chemistry to speed drug discovery. (c) 1998 Prous Science. All rights reserved.

Interspecies scaling and prediction of human clearance: comparison of small- and macro-molecule drugs

PubMed Central

Huh, Yeamin; Smith, David E.; Feng, Meihau Rose

2014-01-01

Human clearance prediction for small- and macro-molecule drugs was evaluated and compared using various scaling methods and statistical analysis.Human clearance is generally well predicted using single or multiple species simple allometry for macro- and small-molecule drugs excreted renally.The prediction error is higher for hepatically eliminated small-molecules using single or multiple species simple allometry scaling, and it appears that the prediction error is mainly associated with drugs with low hepatic extraction ratio (Eh). The error in human clearance prediction for hepatically eliminated small-molecules was reduced using scaling methods with a correction of maximum life span (MLP) or brain weight (BRW).Human clearance of both small- and macro-molecule drugs is well predicted using the monkey liver blood flow method. Predictions using liver blood flow from other species did not work as well, especially for the small-molecule drugs. PMID:21892879

Facilities for small-molecule crystallography at synchrotron sources.

PubMed

Barnett, Sarah A; Nowell, Harriott; Warren, Mark R; Wilcox, Andrian; Allan, David R

2016-01-01

Although macromolecular crystallography is a widely supported technique at synchrotron radiation facilities throughout the world, there are, in comparison, only very few beamlines dedicated to small-molecule crystallography. This limited provision is despite the increasing demand for beamtime from the chemical crystallography community and the ever greater overlap between systems that can be classed as either small macromolecules or large small molecules. In this article, a very brief overview of beamlines that support small-molecule single-crystal diffraction techniques will be given along with a more detailed description of beamline I19, a dedicated facility for small-molecule crystallography at Diamond Light Source.

A graph-based approach to construct target-focused libraries for virtual screening.

PubMed

Naderi, Misagh; Alvin, Chris; Ding, Yun; Mukhopadhyay, Supratik; Brylinski, Michal

2016-01-01

Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family. Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns. We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated. eSynth can successfully reconstruct chemically feasible molecules from molecular fragments. Furthermore, in a procedure mimicking the real application, where one expects to discover novel compounds based on a small set of already developed bioactives, eSynth is capable of generating diverse collections of molecules with the desired activity profiles. Thus, we are very optimistic that our effort will contribute to targeted drug discovery. eSynth is freely available to the academic community at www.brylinski.org/content/molecular-synthesis.Graphical abstractAssuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. Here, we developed eSynth, an automated method to synthesize new compounds by reconnecting these building blocks following the connectivity patterns via an exhaustive graph-based search algorithm. eSynth opens up a possibility to rapidly construct virtual screening libraries for targeted drug discovery.

Systems Based Study of the Therapeutic Potential of Small Charged Molecules for the Inhibition of IL-1 Mediated Cartilage Degradation

PubMed Central

Kar, Saptarshi; Smith, David W.; Gardiner, Bruce S.; Grodzinsky, Alan J.

2016-01-01

Inflammatory cytokines are key drivers of cartilage degradation in post-traumatic osteoarthritis. Cartilage degradation mediated by these inflammatory cytokines has been extensively investigated using in vitro experimental systems. Based on one such study, we have developed a computational model to quantitatively assess the impact of charged small molecules intended to inhibit IL-1 mediated cartilage degradation. We primarily focus on the simplest possible computational model of small molecular interaction with the IL-1 system—direct binding of the small molecule to the active site on the IL-1 molecule itself. We first use the model to explore the uptake and release kinetics of the small molecule inhibitor by cartilage tissue. Our results show that negatively charged small molecules are excluded from the negatively charged cartilage tissue and have uptake kinetics in the order of hours. In contrast, the positively charged small molecules are drawn into the cartilage with uptake and release timescales ranging from hours to days. Using our calibrated computational model, we subsequently explore the effect of small molecule charge and binding constant on the rate of cartilage degradation. The results from this analysis indicate that the small molecules are most effective in inhibiting cartilage degradation if they are either positively charged and/or bind strongly to IL-1α, or both. Furthermore, our results showed that the cartilage structural homeostasis can be restored by the small molecule if administered within six days following initial tissue exposure to IL-1α. We finally extended the scope of the computational model by simulating the competitive inhibition of cartilage degradation by the small molecule. Results from this model show that small molecules are more efficient in inhibiting cartilage degradation by binding directly to IL-1α rather than binding to IL-1α receptors. The results from this study can be used as a template for the design and development of more pharmacologically effective osteoarthritis drugs, and to investigate possible therapeutic options. PMID:27977731

Anticancer Activity of Curcumin and Its Analogues: Preclinical and Clinical Studies.

PubMed

Allegra, Alessandro; Innao, Vanessa; Russo, Sabina; Gerace, Demetrio; Alonci, Andrea; Musolino, Caterina

2017-01-02

Curcumin has been shown to have a wide variety of therapeutic effects, ranging from anti-inflammatory, chemopreventive, anti-proliferative, and anti-metastatic. This review provides an overview of the recent research conducted to overcome the problems with the bioavailability of curcumin, and of the preclinical and clinical studies that have reported success in combinatorial strategies coupling curcumin with other treatments. Research on the signaling pathways that curcumin treatment targets shows that it potently acts on major intracellular components involved in key processes such as genomic modulations, cell invasion and cell death pathways. Curcumin is a promising molecule for the prevention and treatment of cancer.

[Status of libraries and databases for natural products at abroad].

PubMed

Zhao, Li-Mei; Tan, Ning-Hua

2015-01-01

For natural products are one of the important sources for drug discovery, libraries and databases of natural products are significant for the development and research of natural products. At present, most of compound libraries at abroad are synthetic or combinatorial synthetic molecules, resulting to access natural products difficult; for information of natural products are scattered with different standards, it is difficult to construct convenient, comprehensive and large-scale databases for natural products. This paper reviewed the status of current accessing libraries and databases for natural products at abroad and provided some important information for the development of libraries and database for natural products.

Microbatteries for Combinatorial Studies of Conventional Lithium-Ion Batteries

NASA Technical Reports Server (NTRS)

West, William; Whitacre, Jay; Bugga, Ratnakumar

2003-01-01

Integrated arrays of microscopic solid-state batteries have been demonstrated in a continuing effort to develop microscopic sources of power and of voltage reference circuits to be incorporated into low-power integrated circuits. Perhaps even more importantly, arrays of microscopic batteries can be fabricated and tested in combinatorial experiments directed toward optimization and discovery of battery materials. The value of the combinatorial approach to optimization and discovery has been proven in the optoelectronic, pharmaceutical, and bioengineering industries. Depending on the specific application, the combinatorial approach can involve the investigation of hundreds or even thousands of different combinations; hence, it is time-consuming and expensive to attempt to implement the combinatorial approach by building and testing full-size, discrete cells and batteries. The conception of microbattery arrays makes it practical to bring the advantages of the combinatorial approach to the development of batteries.

Antibody-enabled small-molecule drug discovery.

PubMed

Lawson, Alastair D G

2012-06-29

Although antibody-based therapeutics have become firmly established as medicines for serious diseases, the value of antibodies as tools in the early stages of small-molecule drug discovery is only beginning to be realized. In particular, antibodies may provide information to reduce risk in small-molecule drug discovery by enabling the validation of targets and by providing insights into the design of small-molecule screening assays. Moreover, antibodies can act as guides in the quest for small molecules that have the ability to modulate protein-protein interactions, which have traditionally only been considered to be tractable targets for biological drugs. The development of small molecules that have similar therapeutic effects to current biologics has the potential to benefit a broader range of patients at earlier stages of disease.

A global view of regulatory networks in lung cancer: An approach to understand homogeneity and heterogeneity.

PubMed

Lu, Jiapei; Wang, William; Xu, Menglin; Li, Yuping; Chen, Chengshui; Wang, Xiangdong

2017-02-01

A number of new biotechnologies are used to identify potential biomarkers for the early detection of lung cancer, enabling a personalized therapy to be developed in response. The combinatorial cross-regulation of hundreds of biological function-specific transcription factors (TFs) is defined as the understanding of regulatory networks of molecules within the cell. Here we integrated global databases with 537 patients with lung adenocarcinoma (ADC), 140 with lung squamous carcinoma (SCC), 9 with lung large-cell carcinoma (LCC), 56 with small-cell lung cancer (SCLC), and 590 without cancer with the understanding of TF functions. The present review aims at the homogeneity or heterogeneity of gene expression profiles among subtypes of lung cancer. About 5, 136, 52, or 16 up-regulated or 19, 24, 122, or 97down-regulated type-special TF genes were identified in ADC, SCC, LCC or SCLC, respectively. DNA-binding and transcription regulator activity associated genes play a dominant role in the differentiation of subtypes in lung cancer. Subtype-specific TF gene regulatory networks with elements should be an alternative for diagnostic and therapeutic targets for early identification of lung cancer and can provide insightful clues to etiology and pathogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hit discovery of 4-amino-N-(4-(3-(trifluoromethyl)phenoxy)pyrimidin-5-yl)benzamide: A novel EGFR inhibitor from a designed small library.

PubMed

Elkamhawy, Ahmed; Paik, Sora; Hassan, Ahmed H E; Lee, Yong Sup; Roh, Eun Joo

2017-12-01

Searching for hit compounds within the huge chemical space resembles the attempt to find a needle in a haystack. Cheminformatics-guided selection of few representative molecules of a rationally designed virtual combinatorial library is a powerful tool to confront this challenge, speed up hit identification and cut off costs. Herein, this approach has been applied to identify hit compounds with novel scaffolds able to inhibit EGFR kinase. From a generated virtual library, six 4-aryloxy-5-aminopyrimidine scaffold-derived compounds were selected, synthesized and evaluated as hit EGFR inhibitors. 4-Aryloxy-5-benzamidopyrimidines inhibited EGFR with IC 50 1.05-5.37 μM. Cell-based assay of the most potent EGFR inhibitor hit (10ac) confirmed its cytotoxicity against different cancerous cells. In spite of no EGFR, HER2 or VEGFR1 inhibition was elicited by 4-aryloxy-5-(thio)ureidopyrimidine derivatives, cell-based evaluation suggested them as antiproliferative hits acting by other mechanism(s). Molecular docking study provided a plausible explanation of incapability of 4-aryloxy-5-(thio)ureidopyrimidines to inhibit EGFR and suggested a reasonable binding mode of 4-aryloxy-5-benzamidopyrimidines which provides a basis to develop more optimized ligands. Copyright © 2017 Elsevier Inc. All rights reserved.

Basal cell carcinoma pathogenesis and therapy involving hedgehog signaling and beyond.

PubMed

Bakshi, Anshika; Chaudhary, Sandeep C; Rana, Mehtab; Elmets, Craig A; Athar, Mohammad

2017-12-01

Basal cell carcinoma (BCC) of the skin is driven by aberrant hedgehog signaling. Thus blocking this signaling pathway by small molecules such as vismodegib inhibits tumor growth. Primary cilium in the epidermal cells plays an integral role in the processing of hedgehog signaling-related proteins. Recent genomic studies point to the involvement of additional genetic mutations that might be associated with the development of BCCs, suggesting significance of other signaling pathways, such as WNT, NOTCH, mTOR, and Hippo, aside from hedgehog in the pathogenesis of this human neoplasm. Some of these pathways could be regulated by noncoding microRNA. Altered microRNA expression profile is recognized with the progression of these lesions. Stopping treatment with Smoothened (SMO) inhibitors often leads to tumor reoccurrence in the patients with basal cell nevus syndrome, who develop 10-100 of BCCs. In addition, the initial effectiveness of these SMO inhibitors is impaired due to the onset of mutations in the drug-binding domain of SMO. These data point to a need to develop strategies to overcome tumor recurrence and resistance and to enhance efficacy by developing novel single agent-based or multiple agents-based combinatorial approaches. Immunotherapy and photodynamic therapy could be additional successful approaches particularly if developed in combination with chemotherapy for inoperable and metastatic BCCs. © 2017 Wiley Periodicals, Inc.

Basal cell carcinoma pathogenesis and therapy involving hedgehog signaling and beyond

PubMed Central

Bakshi, Anshika; Chaudhary, Sandeep C.; Rana, Mehtab; Elmets, Craig A.; Athar, Mohammad

2018-01-01

Basal cell carcinoma (BCC) of the skin is driven by aberrant hedgehog signaling. Thus blocking this signaling pathway by small molecules such as vismodegib inhibits tumor growth. Primary cilium in the epidermal cells plays an integral role in the processing of hedgehog signaling-related proteins. Recent genomic studies point to the involvement of additional genetic mutations that might be associated with the development of BCCs, suggesting significance of other signaling pathways, such as WNT, NOTCH, mTOR, and Hippo, aside from hedgehog in the pathogenesis of this human neoplasm. Some of these pathways could be regulated by noncoding microRNA. Altered microRNA expression profile is recognized with the progression of these lesions. Stopping treatment with Smoothened (SMO) inhibitors often leads to tumor reoccurrence in the patients with basal cell nevus syndrome, who develop 10–100 of BCCs. In addition, the initial effectiveness of these SMO inhibitors is impaired due to the onset of mutations in the drug-binding domain of SMO. These data point to a need to develop strategies to overcome tumor recurrence and resistance and to enhance efficacy by developing novel single agent-based or multiple agents-based combinatorial approaches. Immunotherapy and photodynamic therapy could be additional successful approaches particularly if developed in combination with chemotherapy for inoperable and metastatic BCCs. PMID:28574612

Combination therapy with PD-1/PD-L1 blockade: An overview of ongoing clinical trials.

PubMed

Johnson, C Bryce; Win, Shwe Y

2018-01-01

Monoclonal antibodies (mAbs) that block the programmed death 1 (PD-1) or programmed death-ligand 1 (PD-L1) receptors are the most clinically advanced tumor immunotherapies. Given the broad antitumor efficacy and novel mechanism of action, numerous combinatorial approaches incorporating PD-1/PD-L1 blockade have been suggested; herein we present a comprehensive analysis of these clinical trials. We queried clinicaltrials.gov for all PD-1/PD-L1 mAbs administered for cancer therapy with an end date of 4/30/2017. A total of 1,218 clinical trials met our search criteria. These trials have a planned enrollment of 227,190 patients, and approximately half (493) were initiated in 2016 alone. Of these over 1,200 trials, 916 combine PD-1/PD-L1 blockade with at least one additional therapy, ranging from traditional treatment modalities like surgery and chemoradiation to newer therapies like small molecule inhibitors and other immunotherapies. The staggering proliferation of clinical trials combining PD-1/PD-L1 blockade with disparate treatments necessitates careful accounting to maximize efficiency and highlight areas of unmet needs. We believe our analysis provides this data and expect it will facilitate the design of future clinical trials in this burgeoning area of oncology research.

CSBB-ConeExclusion, adapting structure based solution virtual screening to libraries on solid support.

PubMed

Shave, Steven; Auer, Manfred

2013-12-23

Combinatorial chemical libraries produced on solid support offer fast and cost-effective access to a large number of unique compounds. If such libraries are screened directly on-bead, the speed at which chemical space can be explored by chemists is much greater than that addressable using solution based synthesis and screening methods. Solution based screening has a large supporting body of software such as structure-based virtual screening tools which enable the prediction of protein-ligand complexes. Use of these techniques to predict the protein bound complexes of compounds synthesized on solid support neglects to take into account the conjugation site on the small molecule ligand. This may invalidate predicted binding modes, the linker may be clashing with protein atoms. We present CSBB-ConeExclusion, a methodology and computer program which provides a measure of the applicability of solution dockings to solid support. Output is given in the form of statistics for each docking pose, a unique 2D visualization method which can be used to determine applicability at a glance, and automatically generated PyMol scripts allowing visualization of protein atom incursion into a defined exclusion volume. CSBB-ConeExclusion is then exemplarically used to determine the optimum attachment point for a purine library targeting cyclin-dependent kinase 2 CDK2.

Computer-aided drug design at Boehringer Ingelheim

NASA Astrophysics Data System (ADS)

Muegge, Ingo; Bergner, Andreas; Kriegl, Jan M.

2017-03-01

Computer-Aided Drug Design (CADD) is an integral part of the drug discovery endeavor at Boehringer Ingelheim (BI). CADD contributes to the evaluation of new therapeutic concepts, identifies small molecule starting points for drug discovery, and develops strategies for optimizing hit and lead compounds. The CADD scientists at BI benefit from the global use and development of both software platforms and computational services. A number of computational techniques developed in-house have significantly changed the way early drug discovery is carried out at BI. In particular, virtual screening in vast chemical spaces, which can be accessed by combinatorial chemistry, has added a new option for the identification of hits in many projects. Recently, a new framework has been implemented allowing fast, interactive predictions of relevant on and off target endpoints and other optimization parameters. In addition to the introduction of this new framework at BI, CADD has been focusing on the enablement of medicinal chemists to independently perform an increasing amount of molecular modeling and design work. This is made possible through the deployment of MOE as a global modeling platform, allowing computational and medicinal chemists to freely share ideas and modeling results. Furthermore, a central communication layer called the computational chemistry framework provides broad access to predictive models and other computational services.

MIFT: GIFT Combinatorial Geometry Input to VCS Code

DTIC Science & Technology

1977-03-01

r-w w-^ H ^ß0318is CQ BRL °RCUMr REPORT NO. 1967 —-S: ... MIFT: GIFT COMBINATORIAL GEOMETRY INPUT TO VCS CODE Albert E...TITLE (and Subtitle) MIFT: GIFT Combinatorial Geometry Input to VCS Code S. TYPE OF REPORT & PERIOD COVERED FINAL 6. PERFORMING ORG. REPORT NUMBER...Vehicle Code System (VCS) called MORSE was modified to accept the GIFT combinatorial geometry package. GIFT , as opposed to the geometry package

Neural Meta-Memes Framework for Combinatorial Optimization

NASA Astrophysics Data System (ADS)

Song, Li Qin; Lim, Meng Hiot; Ong, Yew Soon

In this paper, we present a Neural Meta-Memes Framework (NMMF) for combinatorial optimization. NMMF is a framework which models basic optimization algorithms as memes and manages them dynamically when solving combinatorial problems. NMMF encompasses neural networks which serve as the overall planner/coordinator to balance the workload between memes. We show the efficacy of the proposed NMMF through empirical study on a class of combinatorial problem, the quadratic assignment problem (QAP).

A truncated and dimeric format of an Affibody library on bacteria enables FACS-mediated isolation of amyloid-beta aggregation inhibitors with subnanomolar affinity.

PubMed

Lindberg, Hanna; Härd, Torleif; Löfblom, John; Ståhl, Stefan

2015-09-01

The amyloid hypothesis suggests that accumulation of amyloid β (Aβ) peptides in the brain is involved in development of Alzheimer's disease. We previously generated a small dimeric affinity protein that inhibited Aβ aggregation by sequestering the aggregation prone parts of the peptide. The affinity protein is originally based on the Affibody scaffold, but is evolved to a distinct interaction mechanism involving complex structural rearrangement in both the Aβ peptide and the affinity proteins upon binding. The aim of this study was to decrease the size of the dimeric affinity protein and significantly improve its affinity for the Aβ peptide to increase its potential as a future therapeutic agent. We combined a rational design approach with combinatorial protein engineering to generate two different affinity maturation libraries. The libraries were displayed on staphylococcal cells and high-affinity Aβ-binding molecules were isolated using flow-cytometric sorting. The best performing candidate binds Aβ with a KD value of around 300 pM, corresponding to a 50-fold improvement in affinity relative to the first-generation binder. The new dimeric Affibody molecule was shown to capture Aβ1-42 peptides from spiked E. coli lysate. Altogether, our results demonstrate successful engineering of this complex binder for increased affinity to the Aβ peptide. © 2015 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial-NoDerivs Licence, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A community resource benchmarking predictions of peptide binding to MHC-I molecules.

PubMed

Peters, Bjoern; Bui, Huynh-Hoa; Frankild, Sune; Nielson, Morten; Lundegaard, Claus; Kostem, Emrah; Basch, Derek; Lamberth, Kasper; Harndahl, Mikkel; Fleri, Ward; Wilson, Stephen S; Sidney, John; Lund, Ole; Buus, Soren; Sette, Alessandro

2006-06-09

Recognition of peptides bound to major histocompatibility complex (MHC) class I molecules by T lymphocytes is an essential part of immune surveillance. Each MHC allele has a characteristic peptide binding preference, which can be captured in prediction algorithms, allowing for the rapid scan of entire pathogen proteomes for peptide likely to bind MHC. Here we make public a large set of 48,828 quantitative peptide-binding affinity measurements relating to 48 different mouse, human, macaque, and chimpanzee MHC class I alleles. We use this data to establish a set of benchmark predictions with one neural network method and two matrix-based prediction methods extensively utilized in our groups. In general, the neural network outperforms the matrix-based predictions mainly due to its ability to generalize even on a small amount of data. We also retrieved predictions from tools publicly available on the internet. While differences in the data used to generate these predictions hamper direct comparisons, we do conclude that tools based on combinatorial peptide libraries perform remarkably well. The transparent prediction evaluation on this dataset provides tool developers with a benchmark for comparison of newly developed prediction methods. In addition, to generate and evaluate our own prediction methods, we have established an easily extensible web-based prediction framework that allows automated side-by-side comparisons of prediction methods implemented by experts. This is an advance over the current practice of tool developers having to generate reference predictions themselves, which can lead to underestimating the performance of prediction methods they are not as familiar with as their own. The overall goal of this effort is to provide a transparent prediction evaluation allowing bioinformaticians to identify promising features of prediction methods and providing guidance to immunologists regarding the reliability of prediction tools.

Inhibition of Hepatitis C Virus Replication by Intracellular Delivery of Multiple siRNAs by Nanosomes

PubMed Central

Chandra, Partha K; Kundu, Anup K; Hazari, Sidhartha; Chandra, Sruti; Bao, Lili; Ooms, Tara; Morris, Gilbert F; Wu, Tong; Mandal, Tarun K; Dash, Srikanta

2012-01-01

Sustained antiviral responses of chronic hepatitis C virus (HCV) infection have improved recently by the use of direct-acting antiviral agents along with interferon (IFN)-α and ribavirin. However, the emergence of drug-resistant variants is expected to be a major problem. We describe here a novel combinatorial small interfering RNA (siRNA) nanosome-based antiviral approach to clear HCV infection. Multiple siRNAs targeted to the highly conserved 5′-untranslated region (UTR) of the HCV genome were synthesized and encapsulated into lipid nanoparticles called nanosomes. We show that siRNA can be repeatedly delivered to 100% of cells in culture using nanosomes without toxicity. Six siRNAs dramatically reduced HCV replication in both the replicon and infectious cell culture model. Repeated treatments with two siRNAs were better than a single siRNA treatment in minimizing the development of an escape mutant, resulting in rapid inhibition of viral replication. Systemic administration of combinatorial siRNA-nanosomes is well tolerated in BALB/c mice without liver injury or histological toxicity. As a proof-of-principle, we showed that systemic injections of siRNA nanosomes significantly reduced HCV replication in a liver tumor-xenotransplant mouse model of HCV. Our results indicate that systemic delivery of combinatorial siRNA nanosomes can be used to minimize the development of escape mutants and inhibition of HCV infection. PMID:22617108

Small Molecule Chemical Probes of MicroRNA Function

PubMed Central

Velagapudi, Sai Pradeep; Vummidi, Balayeshwanth R.; Disney, Matthew D.

2015-01-01

MicroRNAs (miRNAs) are small, non-coding RNAs that control protein expression. Aberrant miRNA expression has been linked to various human diseases, and thus miRNAs have been explored as diagnostic markers and therapeutic targets. Although it is challenging to target RNA with small molecules in general, there have been successful campaigns that have identified small molecule modulators of miRNA function by targeting various pathways. For example, small molecules that modulate transcription and target nuclease processing sites in miRNA precursors have been identified. Herein, we describe challenges in developing chemical probes that target miRNAs and highlight aspects of miRNA cellular biology elucidated by using small molecule chemical probes. We expect that this area will expand dramatically in the near future as strides are made to understand small molecule recognition of RNA from a fundamental perspective. PMID:25500006

Medium-Bandgap Small-Molecule Donors Compatible with Both Fullerene and Nonfullerene Acceptors.

PubMed

Huo, Yong; Yan, Cenqi; Kan, Bin; Liu, Xiao-Fei; Chen, Li-Chuan; Hu, Chen-Xia; Lau, Tsz-Ki; Lu, Xinhui; Sun, Chun-Lin; Shao, Xiangfeng; Chen, Yongsheng; Zhan, Xiaowei; Zhang, Hao-Li

2018-03-21

Much effort has been devoted to the development of new donor materials for small-molecule organic solar cells due to their inherent advantages of well-defined molecular weight, easy purification, and good reproducibility in photovoltaic performance. Herein, we report two small-molecule donors that are compatible with both fullerene and nonfullerene acceptors. Both molecules consist of an (E)-1,2-di(thiophen-2-yl)ethane-substituted (TVT-substituted) benzo[1,2-b:4,5-b']dithiophene (BDT) as the central unit, and two rhodanine units as the terminal electron-withdrawing groups. The central units are modified with either alkyl side chains (DRBDT-TVT) or alkylthio side chains (DRBDT-STVT). Both molecules exhibit a medium bandgap with complementary absorption and proper energy level offset with typical acceptors like PC 71 BM and IDIC. The optimized devices show a decent power conversion efficiency (PCE) of 6.87% for small-molecule organic solar cells and 6.63% for nonfullerene all small-molecule organic solar cells. Our results reveal that rationally designed medium-bandgap small-molecule donors can be applied in high-performance small-molecule organic solar cells with different types of acceptors.

Inforna 2.0: A Platform for the Sequence-Based Design of Small Molecules Targeting Structured RNAs.

PubMed

Disney, Matthew D; Winkelsas, Audrey M; Velagapudi, Sai Pradeep; Southern, Mark; Fallahi, Mohammad; Childs-Disney, Jessica L

2016-06-17

The development of small molecules that target RNA is challenging yet, if successful, could advance the development of chemical probes to study RNA function or precision therapeutics to treat RNA-mediated disease. Previously, we described Inforna, an approach that can mine motifs (secondary structures) within target RNAs, which is deduced from the RNA sequence, and compare them to a database of known RNA motif-small molecule binding partners. Output generated by Inforna includes the motif found in both the database and the desired RNA target, lead small molecules for that target, and other related meta-data. Lead small molecules can then be tested for binding and affecting cellular (dys)function. Herein, we describe Inforna 2.0, which incorporates all known RNA motif-small molecule binding partners reported in the scientific literature, a chemical similarity searching feature, and an improved user interface and is freely available via an online web server. By incorporation of interactions identified by other laboratories, the database has been doubled, containing 1936 RNA motif-small molecule interactions, including 244 unique small molecules and 1331 motifs. Interestingly, chemotype analysis of the compounds that bind RNA in the database reveals features in small molecule chemotypes that are privileged for binding. Further, this updated database expanded the number of cellular RNAs to which lead compounds can be identified.

Mapping the Small Molecule Interactome by Mass Spectrometry.

PubMed

Flaxman, Hope A; Woo, Christina M

2018-01-16

Mapping small molecule interactions throughout the proteome provides the critical structural basis for functional analysis of their impact on biochemistry. However, translation of mass spectrometry-based proteomics methods to directly profile the interaction between a small molecule and the whole proteome is challenging because of the substoichiometric nature of many interactions, the diversity of covalent and noncovalent interactions involved, and the subsequent computational complexity associated with their spectral assignment. Recent advances in chemical proteomics have begun fill this gap to provide a structural basis for the breadth of small molecule-protein interactions in the whole proteome. Innovations enabling direct characterization of the small molecule interactome include faster, more sensitive instrumentation coupled to chemical conjugation, enrichment, and labeling methods that facilitate detection and assignment. These methods have started to measure molecular interaction hotspots due to inherent differences in local amino acid reactivity and binding affinity throughout the proteome. Measurement of the small molecule interactome is producing structural insights and methods for probing and engineering protein biochemistry. Direct structural characterization of the small molecule interactome is a rapidly emerging area pushing new frontiers in biochemistry at the interface of small molecules and the proteome.

Utilising the EGFR interactome to identify mechanisms of drug resistance in non-small cell lung cancer - Proof of concept towards a systems pharmacology approach.

PubMed

Saafan, Hisham; Foerster, Sarah; Parra-Guillen, Zinnia P; Hammer, Elke; Michaelis, Martin; Cinatl, Jindrich; Völker, Uwe; Fröhlich, Holger; Kloft, Charlotte; Ritter, Christoph A

2016-10-30

Drug treatment of epidermal growth factor receptor (EGFR) positive non-small cell lung cancer has improved substantially by targeting activating mutations within the receptor tyrosine kinase domain. However, the development of drug resistance still limits this approach. As root causes, large heterogeneity between tumour entities but also within tumour cells have been suggested. Therefore, approaches to identify these multitude and complex mechanisms are urgently required. Affinity purification coupled with high resolution mass spectrometry was applied to isolate and characterise the EGFR interactome from HCC4006 non-small cell lung cancer cells and their variant HCC4006 r ERLO 0.5 adapted to grow in the presence of therapeutically relevant concentrations of erlotinib. Bioinformatics analyses were carried out to identify proteins and their related molecular functions that interact differentially with EGFR in the untreated state or when incubated with erlotinib prior to EGFR activation. Across all experimental conditions 375 proteins were detected to participate in the EGFR interactome, 90% of which constituted a complex protein interaction network that was bioinformatically reconstructed from literature data. Treatment of HCC4006 r ERLO 0.5 cells carrying a resistance phenotype to erlotinib was associated with an increase of protein levels of members of the clathrin-associated adaptor protein family AP2 (AP2A1, AP2A2, AP2B1), structural proteins of cytoskeleton rearrangement as well as signalling molecules such as Shc. Validation experiments confirmed activation of the Ras-Raf-Mek-Erk (MAPK)-pathway, of which Shc is an initiating adaptor molecule, in HCC4006 r ERLO 0.5 cells. Taken together, differential proteins in the EGFR interactome of HCC4006 r ERLO 0.5 cells were identified that could be related to multiple resistance mechanisms including alterations in growth factor receptor expression, cellular remodelling processes suggesting epithelial-to-mesenchymal transition as well as alterations in downstream signalling. Knowledge of these mechanisms is a pivotal step to build an integrative model of drug resistance in a systems pharmacology manner and to be able to investigate the interplay of these mechanisms and ultimately recommend combinatorial treatment strategies to overcome drug resistance. Copyright © 2016 Elsevier B.V. All rights reserved.

FOREWORD: Focus on Combinatorial Materials Science Focus on Combinatorial Materials Science

NASA Astrophysics Data System (ADS)

Chikyo, Toyohiro

2011-10-01

About 15 years have passed since the introduction of modern combinatorial synthesis and high-throughput techniques for the development of novel inorganic materials; however, similar methods existed before. The most famous was reported in 1970 by Hanak who prepared composition-spread films of metal alloys by sputtering mixed-material targets. Although this method was innovative, it was rarely used because of the large amount of data to be processed. This problem is solved in the modern combinatorial material research, which is strongly related to computer data analysis and robotics. This field is still at the developing stage and may be enriched by new methods. Nevertheless, given the progress in measurement equipment and procedures, we believe the combinatorial approach will become a major and standard tool of materials screening and development. The first article of this journal, published in 2000, was titled 'Combinatorial solid state materials science and technology', and this focus issue aims to reintroduce this topic to the Science and Technology of Advanced Materials audience. It covers recent progress in combinatorial materials research describing new results in catalysis, phosphors, polymers and metal alloys for shape memory materials. Sophisticated high-throughput characterization schemes and innovative synthesis tools are also presented, such as spray deposition using nanoparticles or ion plating. On a technical note, data handling systems are introduced to familiarize researchers with the combinatorial methodology. We hope that through this focus issue a wide audience of materials scientists can learn about recent and future trends in combinatorial materials science and high-throughput experimentation.

Small molecule chemical probes of microRNA function.

PubMed

Velagapudi, Sai Pradeep; Vummidi, Balayeshwanth R; Disney, Matthew D

2015-02-01

MicroRNAs (miRNAs) are small, non-coding RNAs that control protein expression. Aberrant miRNA expression has been linked to various human diseases, and thus miRNAs have been explored as diagnostic markers and therapeutic targets. Although it is challenging to target RNA with small molecules in general, there have been successful campaigns that have identified small molecule modulators of miRNA function by targeting various pathways. For example, small molecules that modulate transcription and target nuclease processing sites in miRNA precursors have been identified. Herein, we describe challenges in developing chemical probes that target miRNAs and highlight aspects of miRNA cellular biology elucidated by using small molecule chemical probes. We expect that this area will expand dramatically in the near future as progress is made in understanding small molecule recognition of RNA. Copyright © 2014. Published by Elsevier Ltd.

Evaluation of the Optimum Composition of Low-Temperature Fuel Cell Electrocatalysts for Methanol Oxidation by Combinatorial Screening.

PubMed

Antolini, Ermete

2017-02-13

Combinatorial chemistry and high-throughput screening represent an innovative and rapid tool to prepare and evaluate a large number of new materials, saving time and expense for research and development. Considering that the activity and selectivity of catalysts depend on complex kinetic phenomena, making their development largely empirical in practice, they are prime candidates for combinatorial discovery and optimization. This review presents an overview of recent results of combinatorial screening of low-temperature fuel cell electrocatalysts for methanol oxidation. Optimum catalyst compositions obtained by combinatorial screening were compared with those of bulk catalysts, and the effect of the library geometry on the screening of catalyst composition is highlighted.

Combinatorial Nano-Bio Interfaces.

PubMed

Cai, Pingqiang; Zhang, Xiaoqian; Wang, Ming; Wu, Yun-Long; Chen, Xiaodong

2018-06-08

Nano-bio interfaces are emerging from the convergence of engineered nanomaterials and biological entities. Despite rapid growth, clinical translation of biomedical nanomaterials is heavily compromised by the lack of comprehensive understanding of biophysicochemical interactions at nano-bio interfaces. In the past decade, a few investigations have adopted a combinatorial approach toward decoding nano-bio interfaces. Combinatorial nano-bio interfaces comprise the design of nanocombinatorial libraries and high-throughput bioevaluation. In this Perspective, we address challenges in combinatorial nano-bio interfaces and call for multiparametric nanocombinatorics (composition, morphology, mechanics, surface chemistry), multiscale bioevaluation (biomolecules, organelles, cells, tissues/organs), and the recruitment of computational modeling and artificial intelligence. Leveraging combinatorial nano-bio interfaces will shed light on precision nanomedicine and its potential applications.

Combinatorial computational chemistry approach for materials design: applications in deNOx catalysis, Fischer-Tropsch synthesis, lanthanoid complex, and lithium ion secondary battery.

PubMed

Koyama, Michihisa; Tsuboi, Hideyuki; Endou, Akira; Takaba, Hiromitsu; Kubo, Momoji; Del Carpio, Carlos A; Miyamoto, Akira

2007-02-01

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

Biological Moleculars: Have Most of Our Problems Already Been Solved?

NASA Technical Reports Server (NTRS)

Downey, James P.; Rose, M. Franklin (Technical Monitor)

2000-01-01

Evolution has resulted in biological machinery that engineers have great reason to envy and at present can only poorly mimic. This is not just a curiosity as biological systems perform many functions that are desired industrial processes. Examples include photosynthesis, chemosynthesis, energy storage, low temperature chemical conversion, reproducible manufacture of chemical compounds, etc. The bases of biological machinery are the proteins and nucleic acids that comprise living organisms. Each molecule functions as a part of a biological machine. In many cases the molecule can be properly regarded as a stand alone machine of its own. Concepts and methods for harnessing the power of biological molecules exist but are often overlooked in the industrial world. Some are old and appear crude but are quite effective, e.g. the fermentation of grains and fruits. Currently, there is a revolution in progress regarding the harnessing biological processes. These include techniques such as genetic manipulation via polymerase chain reaction, forced evolution also known as evolution in a test tube, determination of molecular structure, and combinatorial chemistry. The following is a brief discussion on how these processes are performed and how they may relate to industrial and aerospace processes.

Self-optimizing charge-transfer energy phenomena in metallosupramolecular complexes by dynamic constitutional self-sorting.

PubMed

Legrand, Yves-Marie; van der Lee, Arie; Barboiu, Mihail

2007-11-12

In this paper we report an extended series of 2,6-(iminoarene)pyridine-type ZnII complexes [(Lii)2Zn]II, which were surveyed for their ability to self-exchange both their ligands and their aromatic arms and to form different homoduplex and heteroduplex complexes in solution. The self-sorting of heteroduplex complexes is likely to be the result of geometric constraints. Whereas the imine-exchange process occurs quantitatively in 1:1 mixtures of [(Lii)2Zn]II complexes, the octahedral coordination process around the metal ion defines spatial-frustrated exchanges that involve the selective formation of heterocomplexes of two, by two different substituents; the bulkiest ones (pyrene in principle) specifically interact with the pseudoterpyridine core, sterically hindering the least bulky ones, which are intermolecularly stacked with similar ligands of neighboring molecules. Such a self-sorting process defined by the specific self-constitution of the ligands exchanging their aromatic substituents is self-optimized by a specific control over their spatial orientation around a metal center within the complex. They ultimately show an improved charge-transfer energy function by virtue of the dynamic amplification of self-optimized heteroduplex architectures. These systems therefore illustrate the convergence of the combinatorial self-sorting of the dynamic combinatorial libraries (DCLs) strategy and the constitutional self-optimized function.

Tailoring gas sensor arrays via the design of short peptides sequences as binding elements.

PubMed

Mascini, Marcello; Pizzoni, Daniel; Perez, German; Chiarappa, Emilio; Di Natale, Corrado; Pittia, Paola; Compagnone, Dario

2017-07-15

A semi-combinatorial virtual approach was used to prepare peptide-based gas sensors with binding properties towards five different chemical classes (alcohols, aldehydes, esters, hydrocarbons and ketones). Molecular docking simulations were conducted for a complete tripeptide library (8000 elements) versus 58 volatile compounds belonging to those five chemical classes. By maximizing the differences between chemical classes, a subset of 120 tripeptides was extracted and used as scaffolds for generating a combinatorial library of 7912 tetrapeptides. This library was processed in an analogous way to the former. Five tetrapeptides (IHRI, KSDS, LGFD, TGKF and WHVS) were chosen depending on their virtual affinity and cross-reactivity for the experimental step. The five peptides were covalently bound to gold nanoparticles by adding a terminal cysteine to each tetrapeptide and deposited onto 20MHz quartz crystal microbalances to construct the gas sensors. The behavior of peptides after this chemical modification was simulated at the pH range used in the immobilization step. ΔF signals analyzed by principal component analysis matched the virtually screened data. The array was able to clearly discriminate the 13 volatile compounds tested based on their hydrophobicity and hydrophilicity molecules as well as the molecular weight. Copyright © 2016 Elsevier B.V. All rights reserved.

Defining RNA-Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA.

PubMed

Velagapudi, Sai Pradeep; Luo, Yiling; Tran, Tuan; Haniff, Hafeez S; Nakai, Yoshio; Fallahi, Mohammad; Martinez, Gustavo J; Childs-Disney, Jessica L; Disney, Matthew D

2017-03-22

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif-small molecule interactions identified via selection. Named High Throughput Structure-Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif-small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule-RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs.

Natural Products as Sources of New Drugs over the 30 Years from 1981 to 2010†

PubMed Central

Newman, David J.; Cragg, Gordon M.

2013-01-01

This review is an updated and expanded version of the three prior reviews that were published in this journal in 1997, 2003 and 2007. In the case of all approved therapeutic agents, the time frame has been extended to cover the 30 years from January 1st 1981 to December 31st 2010 for all diseases world-wide, and from 1950 (earliest so far identified) to December 2010 for all approved antitumor drugs world-wide. We have continued to utilize our secondary subdivision of a “natural product mimic” or “NM” to join the original primary divisions, and have added a new designation “natural product botanical” or “NB” to cover those botanical “defined mixtures” that have now been recognized as drug entities by the FDA and similar organizations. From the data presented, the utility of natural products as sources of novel structures, but not necessarily the final drug entity, is still alive and well. Thus, in the area of cancer, over the time frame from around the 1940s to date, of the 175 small molecules, 131 or 74.8% are other than “S” (synthetic), with 85 or 48.6% actually being either natural products or directly derived there from. In other areas, the influence of natural product structures is quite marked with, as expected from prior information, the anti-infective area being dependent on natural products and their structures. Although combinatorial chemistry techniques have succeeded as methods of optimizing structures, and have been used very successfully in the optimization of many recently approved agents, we are only able to identify only one de novo combinatorial compound approved as a drug in this 30-year time frame. We wish to draw the attention of readers to the rapidly evolving recognition that a significant number of natural product drugs/leads are actually produced by microbes and/or microbial interactions with the “host from whence it was isolated”, and therefore we consider that this area of natural product research should be expanded significantly. PMID:22316239

Combinatorial In Silico Strategy towards Identifying Potential Hotspots during Inhibition of Structurally Identical HDAC1 and HDAC2 Enzymes for Effective Chemotherapy against Neurological Disorders

PubMed Central

Ganai, Shabir Ahmad; Abdullah, Ehsaan; Rashid, Romana; Altaf, Mohammad

2017-01-01

Histone deacetylases (HDACs) regulate epigenetic gene expression programs by modulating chromatin architecture and are required for neuronal development. Dysregulation of HDACs and aberrant chromatin acetylation homeostasis have been implicated in various diseases ranging from cancer to neurodegenerative disorders. Histone deacetylase inhibitors (HDACi), the small molecules interfering HDACs have shown enhanced acetylation of the genome and are gaining great attention as potent drugs for treating cancer and neurodegeneration. HDAC2 overexpression has implications in decreasing dendrite spine density, synaptic plasticity and in triggering neurodegenerative signaling. Pharmacological intervention against HDAC2 though promising also targets neuroprotective HDAC1 due to high sequence identity (94%) with former in catalytic domain, culminating in debilitating off-target effects and creating hindrance in the defined intervention. This emphasizes the need of designing HDAC2-selective inhibitors to overcome these vicious effects and for escalating the therapeutic efficacy. Here we report a top-down combinatorial in silico approach for identifying the structural variants that are substantial for interactions against HDAC1 and HDAC2 enzymes. We used extra-precision (XP)-molecular docking, Molecular Mechanics Generalized Born Surface Area (MMGBSA) for predicting affinity of inhibitors against the HDAC1 and HDAC2 enzymes. Importantly, we employed a novel in silico strategy of coupling the state-of-the-art molecular dynamics simulation (MDS) to energetically-optimized structure based pharmacophores (e-Pharmacophores) method via MDS trajectory clustering for hypothesizing the e-Pharmacophore models. Further, we performed e-Pharmacophores based virtual screening against phase database containing millions of compounds. We validated the data by performing the molecular docking and MM-GBSA studies for the selected hits among the retrieved ones. Our studies attributed inhibitor potency to the ability of forming multiple interactions and infirm potency to least interactions. Moreover, our studies delineated that a single HDAC inhibitor portrays differential features against HDAC1 and HDAC2 enzymes. The high affinity and selective HDAC2 inhibitors retrieved through e-Pharmacophores based virtual screening will play a critical role in ameliorating neurodegenerative signaling without hampering the neuroprotective isoform (HDAC1). PMID:29170627

Use of nanotechnology for improved pharmacokinetics and activity of immunogenic cell death inducers used in cancer chemotherapy.

PubMed

Janicka, Martyna; Gubernator, Jerzy

2017-09-01

Immunogenic cell death inducers (ICD inducers) are a diverse group of therapeutic molecules capable of eliciting an adaptive immune response against the antigens present on the surface of dying cancer cells. Most of these molecules suffer from low bioavailability, high toxicity and poor pharmacokinetics which limit their application. It is believed that nanotechnology, in particular nano-sized nanocarriers, can address most of the issues that limit the use of ICD inducers. Area covered: The mechanism of action of ICD inducers and their limitations is discussed. In addition, we cover the novel possibilities arising from the use of nanotechnology to improve delivery of ICD inducers to the target tissue as well as the restrictions of modern nanotechnology. Expert opinion: At present, nanocarrier formulations suffer from low bioavailability, poor pharmacokinetics and stability issues. Nonetheless, there is a tremendous future for combinatorial immune-pharmacological treatments of human tumors based on nanocarrier delivery of ICD inducers.

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

PubMed Central

Reticker-Flynn, Nathan E.; Braga Malta, David F.; Winslow, Monte M.; Lamar, John M.; Xu, Mary J.; Underhill, Gregory H.; Hynes, Richard O.; Jacks, Tyler E.; Bhatia, Sangeeta N.

2013-01-01

Extracellular matrix interactions play essential roles in normal physiology and many pathological processes. While the importance of ECM interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel screening platform capable of measuring phenotypic responses to combinations of ECM molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the ECM-dependent adhesion of tumor-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumor lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8, or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified ECM and integrin interactions that could serve as therapeutic targets. PMID:23047680

Smooth Constrained Heuristic Optimization of a Combinatorial Chemical Space

DTIC Science & Technology

2015-05-01

ARL-TR-7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...7294•MAY 2015 US Army Research Laboratory Smooth ConstrainedHeuristic Optimization of a Combinatorial Chemical Space by Berend Christopher...

Preparation of cherry-picked combinatorial libraries by string synthesis.

PubMed

Furka, Arpád; Dibó, Gábor; Gombosuren, Naran

2005-03-01

String synthesis [1-3] is an efficient and cheap manual method for preparation of combinatorial libraries by using macroscopic solid support units. Sorting the units between two synthetic steps is an important operation of the procedure. The software developed to guide sorting can be used only when complete combinatorial libraries are prepared. Since very often only selected components of the full libraries are needed, new software was constructed that guides sorting in preparation of non-complete combinatorial libraries. Application of the software is described in details.

Small Molecule Inhibitors of AI-2 Signaling in Bacteria: State-of-the-Art and Future Perspectives for Anti-Quorum Sensing Agents

PubMed Central

Guo, Min; Gamby, Sonja; Zheng, Yue; Sintim, Herman O.

2013-01-01

Bacteria respond to different small molecules that are produced by other neighboring bacteria. These molecules, called autoinducers, are classified as intraspecies (i.e., molecules produced and perceived by the same bacterial species) or interspecies (molecules that are produced and sensed between different bacterial species). AI-2 has been proposed as an interspecies autoinducer and has been shown to regulate different bacterial physiology as well as affect virulence factor production and biofilm formation in some bacteria, including bacteria of clinical relevance. Several groups have embarked on the development of small molecules that could be used to perturb AI-2 signaling in bacteria, with the ultimate goal that these molecules could be used to inhibit bacterial virulence and biofilm formation. Additionally, these molecules have the potential to be used in synthetic biology applications whereby these small molecules are used as inputs to switch on and off AI-2 receptors. In this review, we highlight the state-of-the-art in the development of small molecules that perturb AI-2 signaling in bacteria and offer our perspective on the future development and applications of these classes of molecules. PMID:23994835

Global gene expression analysis by combinatorial optimization.

PubMed

Ameur, Adam; Aurell, Erik; Carlsson, Mats; Westholm, Jakub Orzechowski

2004-01-01

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

Combinatorial neural codes from a mathematical coding theory perspective.

PubMed

Curto, Carina; Itskov, Vladimir; Morrison, Katherine; Roth, Zachary; Walker, Judy L

2013-07-01

Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes do not support accurate error correction, although the error-correcting performance of receptive field codes catches up to that of random comparison codes when a small tolerance to error is introduced. However, receptive field codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.

Generation of Affibody ligands binding interleukin-2 receptor alpha/CD25.

PubMed

Grönwall, Caroline; Snelders, Eveline; Palm, Anna Jarelöv; Eriksson, Fredrik; Herne, Nina; Ståhl, Stefan

2008-06-01

Affibody molecules specific for human IL-2Ralpha, the IL-2 (interleukin-2) receptor alpha subunit, also known as CD25, were selected by phage-display technology from a combinatorial protein library based on the 58-residue Protein A-derived Z domain. The IL-2R system plays a major role in T-cell activation and the regulation of cellular immune responses. Moreover, CD25 has been found to be overexpressed in organ rejections, a number of autoimmune diseases and T-cell malignancies. The phage-display selection using Fc-fused target protein generated 16 unique Affibody molecules targeting CD25. The two most promising binders were characterized in more detail using biosensor analysis and demonstrated strong and selective binding to CD25. Kinetic biosensor analysis revealed that the two monomeric Affibody molecules bound to CD25 with apparent affinities of 130 and 240 nM respectively. The Affibody molecules were, on biosensor analysis, found to compete for the same binding site as the natural ligand IL-2 and the IL-2 blocking monoclonal antibody 2A3. Hence the Affibody molecules were assumed to have an overlapping binding site with IL-2 and antibodies targeting the IL-2 blocking Tac epitope (for example, the monoclonal antibodies Daclizumab and Basiliximab, both of which have been approved for therapeutic use). Furthermore, immunofluorescence microscopy and flow-cytometric analysis of CD25-expressing cells demonstrated that the selected Affibody molecules bound to CD4+ CD25+ PMBCs (peripheral-blood mononuclear cells), the IL-2-dependent cell line NK92 and phytohaemagglutinin-activated PMBCs. The potential use of the CD25-binding Affibody molecules as targeting agents for medical imaging and for therapeutic applications is discussed.

Validation of an Instrument and Testing Protocol for Measuring the Combinatorial Analysis Schema.

ERIC Educational Resources Information Center

Staver, John R.; Harty, Harold

1979-01-01

Designs a testing situation to examine the presence of combinatorial analysis, to establish construct validity in the use of an instrument, Combinatorial Analysis Behavior Observation Scheme (CABOS), and to investigate the presence of the schema in young adolescents. (Author/GA)

Organic small molecule semiconducting chromophores for use in organic electronic devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Welch, Gregory C.; Hoven, Corey V.; Nguyen, Thuc-Quyen

Small organic molecule semi-conducting chromophores containing a pyridalthiadiazole, pyridaloxadiazole, or pyridaltriazole core structure are disclosed. Such compounds can be used in organic heterojunction devices, such as organic small molecule solar cells and transistors.

Structure-guided Discovery of Dual-recognition Chemibodies.

PubMed

Cheng, Alan C; Doherty, Elizabeth M; Johnstone, Sheree; DiMauro, Erin F; Dao, Jennifer; Luthra, Abhinav; Ye, Jay; Tang, Jie; Nixey, Thomas; Min, Xiaoshan; Tagari, Philip; Miranda, Les P; Wang, Zhulun

2018-05-15

Small molecules and antibodies each have advantages and limitations as therapeutics. Here, we present for the first time to our knowledge, the structure-guided design of "chemibodies" as small molecule-antibody hybrids that offer dual recognition of a single target by both a small molecule and an antibody, using DPP-IV enzyme as a proof of concept study. Biochemical characterization demonstrates that the chemibodies present superior DPP-IV inhibition compared to either small molecule or antibody component alone. We validated our design by successfully solving a co-crystal structure of a chemibody in complex with DPP-IV, confirming specific binding of the small molecule portion at the interior catalytic site and the Fab portion at the protein surface. The discovery of chemibodies presents considerable potential for novel therapeutics that harness the power of both small molecule and antibody modalities to achieve superior specificity, potency, and pharmacokinetic properties.

Rational design of chemical genetic probes of RNA function and lead therapeutics targeting repeating transcripts.

PubMed

Disney, Matthew D

2013-12-01

RNA is an important yet vastly underexploited target for small molecule chemical probes or lead therapeutics. Small molecules have been used successfully to modulate the function of the bacterial ribosome, viral RNAs and riboswitches. These RNAs are either highly expressed or can be targeted using substrate mimicry, a mainstay in the design of enzyme inhibitors. However, most cellular RNAs are neither highly expressed nor have a lead small molecule inhibitor, a significant challenge for drug discovery efforts. Herein, I describe the design of small molecules targeting expanded repeating transcripts that cause myotonic muscular dystrophy (DM). These test cases illustrate the challenges of designing small molecules that target RNA and the advantages of targeting repeating transcripts. Lastly, I discuss how small molecules might be more advantageous than oligonucleotides for targeting RNA. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advancing Biological Understanding and Therapeutics Discovery with Small Molecule Probes

PubMed Central

Schreiber, Stuart L.; Kotz, Joanne D.; Li, Min; Aubé, Jeffrey; Austin, Christopher P.; Reed, John C.; Rosen, Hugh; White, E. Lucile; Sklar, Larry A.; Lindsley, Craig W.; Alexander, Benjamin R.; Bittker, Joshua A.; Clemons, Paul A.; de Souza, Andrea; Foley, Michael A.; Palmer, Michelle; Shamji, Alykhan F.; Wawer, Mathias J.; McManus, Owen; Wu, Meng; Zou, Beiyan; Yu, Haibo; Golden, Jennifer E.; Schoenen, Frank J.; Simeonov, Anton; Jadhav, Ajit; Jackson, Michael R.; Pinkerton, Anthony B.; Chung, Thomas D.Y.; Griffin, Patrick R.; Cravatt, Benjamin F.; Hodder, Peter S.; Roush, William R.; Roberts, Edward; Chung, Dong-Hoon; Jonsson, Colleen B.; Noah, James W.; Severson, William E.; Ananthan, Subramaniam; Edwards, Bruce; Oprea, Tudor I.; Conn, P. Jeffrey; Hopkins, Corey R.; Wood, Michael R.; Stauffer, Shaun R.; Emmitte, Kyle A.

2015-01-01

Small-molecule probes can illuminate biological processes and aid in the assessment of emerging therapeutic targets by perturbing biological systems in a manner distinct from other experimental approaches. Despite the tremendous promise of chemical tools for investigating biology and disease, small-molecule probes were unavailable for most targets and pathways as recently as a decade ago. In 2005, the U.S. National Institutes of Health launched the decade-long Molecular Libraries Program with the intent of innovating in and broadening access to small-molecule science. This Perspective describes how novel small-molecule probes identified through the program are enabling the exploration of biological pathways and therapeutic hypotheses not otherwise testable. These experiences illustrate how small-molecule probes can help bridge the chasm between biological research and the development of medicines, but also highlight the need to innovate the science of therapeutic discovery. PMID:26046436

High mobility high efficiency organic films based on pure organic materials

DOEpatents

Salzman, Rhonda F [Ann Arbor, MI; Forrest, Stephen R [Ann Arbor, MI

2009-01-27

A method of purifying small molecule organic material, performed as a series of operations beginning with a first sample of the organic small molecule material. The first step is to purify the organic small molecule material by thermal gradient sublimation. The second step is to test the purity of at least one sample from the purified organic small molecule material by spectroscopy. The third step is to repeat the first through third steps on the purified small molecule material if the spectroscopic testing reveals any peaks exceeding a threshold percentage of a magnitude of a characteristic peak of a target organic small molecule. The steps are performed at least twice. The threshold percentage is at most 10%. Preferably the threshold percentage is 5% and more preferably 2%. The threshold percentage may be selected based on the spectra of past samples that achieved target performance characteristics in finished devices.

Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.

PubMed

Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi

2016-06-01

Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.

Characterizing protein domain associations by Small-molecule ligand binding

PubMed Central

Li, Qingliang; Cheng, Tiejun; Wang, Yanli; Bryant, Stephen H.

2012-01-01

Background Protein domains are evolutionarily conserved building blocks for protein structure and function, which are conventionally identified based on protein sequence or structure similarity. Small molecule binding domains are of great importance for the recognition of small molecules in biological systems and drug development. Many small molecules, including drugs, have been increasingly identified to bind to multiple targets, leading to promiscuous interactions with protein domains. Thus, a large scale characterization of the protein domains and their associations with respect to small-molecule binding is of particular interest to system biology research, drug target identification, as well as drug repurposing. Methods We compiled a collection of 13,822 physical interactions of small molecules and protein domains derived from the Protein Data Bank (PDB) structures. Based on the chemical similarity of these small molecules, we characterized pairwise associations of the protein domains and further investigated their global associations from a network point of view. Results We found that protein domains, despite lack of similarity in sequence and structure, were comprehensively associated through binding the same or similar small-molecule ligands. Moreover, we identified modules in the domain network that consisted of closely related protein domains by sharing similar biochemical mechanisms, being involved in relevant biological pathways, or being regulated by the same cognate cofactors. Conclusions A novel protein domain relationship was identified in the context of small-molecule binding, which is complementary to those identified by traditional sequence-based or structure-based approaches. The protein domain network constructed in the present study provides a novel perspective for chemogenomic study and network pharmacology, as well as target identification for drug repurposing. PMID:23745168

Proteoform-specific protein binding of small molecules in complex matrices

USDA-ARS?s Scientific Manuscript database

Characterizing the specific binding between protein targets and small molecules is critically important for drug discovery. Conventional assays require isolation and purification of small molecules from complex matrices through multistep chromatographic fractionation, which may alter their original ...

Pydna: a simulation and documentation tool for DNA assembly strategies using python.

PubMed

Pereira, Filipa; Azevedo, Flávio; Carvalho, Ângela; Ribeiro, Gabriela F; Budde, Mark W; Johansson, Björn

2015-05-02

Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool. We have developed pydna, an extensible, free and open source Python library for simulating basic molecular biology DNA unit operations such as restriction digestion, ligation, PCR, primer design, Gibson assembly and homologous recombination. A cloning strategy expressed as a pydna script provides a description that is complete, unambiguous and stable. Execution of the script automatically yields the sequence of the final molecule(s) and that of any intermediate constructs. Pydna has been designed to be understandable for biologists with limited programming skills by providing interfaces that are semantically similar to the description of molecular biology unit operations found in literature. Pydna simplifies both the planning and sharing of cloning strategies and is especially useful for complex or combinatorial DNA molecule construction. An important difference compared to existing tools with similar goals is the use of Python instead of a specifically constructed language, providing a simulation environment that is more flexible and extensible by the user.

Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules

PubMed Central

Desai, Aarti; Singh, Vivek K.; Jere, Abhay

2016-01-01

Introduction Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense) that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage. Results The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with ‘High’ reliability scoring), DEREK (accuracy = 72.73% and CCR = 71.44%) and TOPKAT (accuracy = 60.00% and CCR = 61.67%). Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%), the coverage was very low (only 10 out of 77 molecules were predicted reliably). Conclusions Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing. PMID:27271321

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

PubMed Central

Wagner, Bridget K.; Clemons, Paul A.

2009-01-01

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene-expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe- and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of “virtual” profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe and drug discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections. PMID:19825513

Small Molecule based Musculoskeletal Regenerative Engineering

PubMed Central

Lo, Kevin W.-H.; Jiang, Tao; Gagnon, Keith A.; Nelson, Clarke; Laurencin, Cato T.

2014-01-01

Clinicians and scientists working in the field of regenerative engineering are actively investigating a wide range of methods to promote musculoskeletal tissue regeneration. Small molecule-mediated tissue regeneration is emerging as a promising strategy for regenerating various musculoskeletal tissues and a large number of small molecule compounds have been recently discovered as potential bioactive molecules for musculoskeletal tissue repair and regeneration. In this review, we summarize the recent literature encompassing the past four years in the area of small bioactive molecule for promoting repair and regeneration of various musculoskeletal tissues including bone, muscle, cartilage, tendon, and nerve. PMID:24405851

Combinatorial enzyme technology for the conversion of agricultural fibers to functional properties

USDA-ARS?s Scientific Manuscript database

The concept of combinatorial chemistry has received little attention in agriculture and food research, although its applications in this area were described more than fifteen years ago (1, 2). More recently, interest in the use of combinatorial chemistry in agrochemical discovery has been revitalize...

An Investigation into Post-Secondary Students' Understanding of Combinatorial Questions

ERIC Educational Resources Information Center

Bulone, Vincent William

2017-01-01

The purpose of this dissertation was to study aspects of how post-secondary students understand combinatorial problems. Within this dissertation, I considered understanding through two different lenses: i) student connections to previous problems; and ii) common combinatorial distinctions such as ordered versus unordered and repetitive versus…

Defining RNA–Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA

PubMed Central

2017-01-01

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif–small molecule interactions identified via selection. Named High Throughput Structure–Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif–small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule–RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs. PMID:28386598

Understanding the Halogenation Effects in Diketopyrrolopyrrole-Based Small Molecule Photovoltaics.

PubMed

Sun, Shi-Xin; Huo, Yong; Li, Miao-Miao; Hu, Xiaowen; Zhang, Hai-Jun; Zhang, You-Wen; Zhang, You-Dan; Chen, Xiao-Long; Shi, Zi-Fa; Gong, Xiong; Chen, Yongsheng; Zhang, Hao-Li

2015-09-16

Two molecules containing a central diketopyrrolopyrrole and two oligothiophene units have been designed and synthesized. Comparisons between the molecules containing terminal F (FDPP) and Cl (CDPP) atoms allowed us to evaluate the effects of halogenation on the photovoltaic properties of the small molecule organic solar cells (OSCs). The OSCs devices employing FDPP:PC71BM films showed power conversion efficiencies up to 4.32%, suggesting that fluorination is an efficient method for constructing small molecules for OSCs.

ChemBank: a small-molecule screening and cheminformatics resource database.

PubMed

Seiler, Kathleen Petri; George, Gregory A; Happ, Mary Pat; Bodycombe, Nicole E; Carrinski, Hyman A; Norton, Stephanie; Brudz, Steve; Sullivan, John P; Muhlich, Jeremy; Serrano, Martin; Ferraiolo, Paul; Tolliday, Nicola J; Schreiber, Stuart L; Clemons, Paul A

2008-01-01

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets. The cGRNB web-server is free and available online at http://www.scbit.org/cgrnb.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset | Office of Cancer Genomics

Cancer.gov

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset.

A Nonfullerene Small Molecule Acceptor with 3D Interlocking Geometry Enabling Efficient Organic Solar Cells.

PubMed

Lee, Jaewon; Singh, Ranbir; Sin, Dong Hun; Kim, Heung Gyu; Song, Kyu Chan; Cho, Kilwon

2016-01-06

A new 3D nonfullerene small-molecule acceptor is reported. The 3D interlocking geometry of the small-molecule acceptor enables uniform molecular conformation and strong intermolecular connectivity, facilitating favorable nanoscale phase separation and electron charge transfer. By employing both a novel polymer donor and a nonfullerene small-molecule acceptor in the solution-processed organic solar cells, a high-power conversion efficiency of close to 6% is demonstrated. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A "roller-wheel" Pt-containing small molecule that outperforms its polymer analogs in organic solar cells

DOE PAGES

He, Wenhan; Wu, Qin; Livshits, Maksim Y.; ...

2016-05-23

A novel Pt-bisacetylide small molecule (Pt-SM) featuring “roller-wheel” geometry was synthesized and characterized. When compared with conventional Pt-containing polymers and small molecules having “dumbbell” shaped structures, Pt-SM displays enhanced crystallinity and intermolecular π–π interactions, as well as favorable panchromatic absorption behaviors. Furthermore, organic solar cells (OSCs) employing Pt-SM achieve power conversion efficiencies (PCEs) up to 5.9%, the highest reported so far for Pt-containing polymers and small molecules.

A "roller-wheel" Pt-containing small molecule that outperforms its polymer analogs in organic solar cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Wenhan; Wu, Qin; Livshits, Maksim Y.

A novel Pt-bisacetylide small molecule (Pt-SM) featuring “roller-wheel” geometry was synthesized and characterized. When compared with conventional Pt-containing polymers and small molecules having “dumbbell” shaped structures, Pt-SM displays enhanced crystallinity and intermolecular π–π interactions, as well as favorable panchromatic absorption behaviors. Furthermore, organic solar cells (OSCs) employing Pt-SM achieve power conversion efficiencies (PCEs) up to 5.9%, the highest reported so far for Pt-containing polymers and small molecules.

The construction of combinatorial manifolds with prescribed sets of links of vertices

NASA Astrophysics Data System (ADS)

Gaifullin, A. A.

2008-10-01

To every oriented closed combinatorial manifold we assign the set (with repetitions) of isomorphism classes of links of its vertices. The resulting transformation \\mathcal{L} is the main object of study in this paper. We pose an inversion problem for \\mathcal{L} and show that this problem is closely related to Steenrod's problem on the realization of cycles and to the Rokhlin-Schwartz-Thom construction of combinatorial Pontryagin classes. We obtain a necessary condition for a set of isomorphism classes of combinatorial spheres to belong to the image of \\mathcal{L}. (Sets satisfying this condition are said to be balanced.) We give an explicit construction showing that every balanced set of isomorphism classes of combinatorial spheres falls into the image of \\mathcal{L} after passing to a multiple set and adding several pairs of the form (Z,-Z), where -Z is the sphere Z with the orientation reversed. Given any singular simplicial cycle \\xi of a space X, this construction enables us to find explicitly a combinatorial manifold M and a map \\varphi\\colon M\\to X such that \\varphi_* \\lbrack M \\rbrack =r[\\xi] for some positive integer r. The construction is based on resolving singularities of \\xi. We give applications of the main construction to cobordisms of manifolds with singularities and cobordisms of simple cells. In particular, we prove that every rational additive invariant of cobordisms of manifolds with singularities admits a local formula. Another application is the construction of explicit (though inefficient) local combinatorial formulae for polynomials in the rational Pontryagin classes of combinatorial manifolds.

A-π-D-π-A Electron-Donating Small Molecules for Solution-Processed Organic Solar Cells: A Review.

PubMed

Wang, Zhen; Zhu, Lingyun; Shuai, Zhigang; Wei, Zhixiang

2017-11-01

Organic solar cells based on semiconducting polymers and small molecules have attracted considerable attention in the last two decades. Moreover, the power conversion efficiencies for solution-processed solar cells containing A-π-D-π-A-type small molecules and fullerenes have reached 11%. However, the method for designing high-performance, photovoltaic small molecules still remains unclear. In this review, recent studies on A-π-D-π-A electron-donating small molecules for organic solar cells are introduced. Moreover, the relationships between molecular properties and device performances are summarized, from which inspiration for the future design of high performance organic solar cells may be obtained. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Training and Transfer in Combinatorial Problem Solving: The Development of Formal Reasoning During Early Adolescence

ERIC Educational Resources Information Center

Barratt, Barnaby B.

1975-01-01

This study investigated the emergence of combinatorial competence in early adolescence and the effectiveness of a programmed discovery training procedure. Significant increases in combinatorial skill with age were shown; it was found that the expression of this skill was significantly facilitated if problems involved concrete material of low…

Invention as a combinatorial process: evidence from US patents

PubMed Central

Youn, Hyejin; Strumsky, Deborah; Bettencourt, Luis M. A.; Lobo, José

2015-01-01

Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here, we use US patent records dating from 1790 to 2010 to formally characterize invention as a combinatorial process. To do this, we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the United States Patent and Trademark Office to classify the technologies responsible for an invention's novelty. We find that the combinatorial inventive process exhibits an invariant rate of ‘exploitation’ (refinements of existing combinations of technologies) and ‘exploration’ (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities—the building blocks to be combined—that has significantly slowed down. We also find that, notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations. PMID:25904530

Combinatorial application of two aldehyde oxidoreductases on isobutanol production in the presence of furfural.

PubMed

Seo, Hyung-Min; Jeon, Jong-Min; Lee, Ju Hee; Song, Hun-Suk; Joo, Han-Byul; Park, Sung-Hee; Choi, Kwon-Young; Kim, Yong Hyun; Park, Kyungmoon; Ahn, Jungoh; Lee, Hongweon; Yang, Yung-Hun

2016-01-01

Furfural is a toxic by-product formulated from pretreatment processes of lignocellulosic biomass. In order to utilize the lignocellulosic biomass on isobutanol production, inhibitory effect of the furfural on isobutanol production was investigated and combinatorial application of two oxidoreductases, FucO and YqhD, was suggested as an alternative strategy. Furfural decreased cell growth and isobutanol production when only YqhD or FucO was employed as an isobutyraldehyde oxidoreductase. However, combinatorial overexpression of FucO and YqhD could overcome the inhibitory effect of furfural giving higher isobutanol production by 110% compared with overexpression of YqhD. The combinatorial oxidoreductases increased furfural detoxification rate 2.1-fold and also accelerated glucose consumption 1.4-fold. When it compares to another known system increasing furfural tolerance, membrane-bound transhydrogenase (pntAB), the combinatorial aldehyde oxidoreductases were better on cell growth and production. Thus, to control oxidoreductases is important to produce isobutanol using furfural-containing biomass and the combinatorial overexpression of FucO and YqhD can be an alternative strategy.

Combinatorial Methods for Exploring Complex Materials

NASA Astrophysics Data System (ADS)

Amis, Eric J.

2004-03-01

Combinatorial and high-throughput methods have changed the paradigm of pharmaceutical synthesis and have begun to have a similar impact on materials science research. Already there are examples of combinatorial methods used for inorganic materials, catalysts, and polymer synthesis. For many investigations the primary goal has been discovery of new material compositions that optimize properties such as phosphorescence or catalytic activity. In the midst of the excitement generated to "make things", another opportunity arises for materials science to "understand things" by using the efficiency of combinatorial methods. We have shown that combinatorial methods hold potential for rapid and systematic generation of experimental data over the multi-parameter space typical of investigations in polymer physics. We have applied the combinatorial approach to studies of polymer thin films, biomaterials, polymer blends, filled polymers, and semicrystalline polymers. By combining library fabrication, high-throughput measurements, informatics, and modeling we can demonstrate validation of the methodology, new observations, and developments toward predictive models. This talk will present some of our latest work with applications to coating stability, multi-component formulations, and nanostructure assembly.

A general electrochemical method for label-free screening of protein–small molecule interactions†

PubMed Central

Cash, Kevin J.; Ricci, Francesco

2010-01-01

Here we report a versatile method by which the interaction between a protein and a small molecule, and the disruption of that interaction by competition with other small molecules, can be monitored electrochemically directly in complex sample matrices. PMID:19826675

Toward Generalization of Iterative Small Molecule Synthesis

PubMed Central

Lehmann, Jonathan W.; Blair, Daniel J.; Burke, Martin D.

2018-01-01

Small molecules have extensive untapped potential to benefit society, but access to this potential is too often restricted by limitations inherent to the customized approach currently used to synthesize this class of chemical matter. In contrast, the “building block approach”, i.e., generalized iterative assembly of interchangeable parts, has now proven to be a highly efficient and flexible way to construct things ranging all the way from skyscrapers to macromolecules to artificial intelligence algorithms. The structural redundancy found in many small molecules suggests that they possess a similar capacity for generalized building block-based construction. It is also encouraging that many customized iterative synthesis methods have been developed that improve access to specific classes of small molecules. There has also been substantial recent progress toward the iterative assembly of many different types of small molecules, including complex natural products, pharmaceuticals, biological probes, and materials, using common building blocks and coupling chemistry. Collectively, these advances suggest that a generalized building block approach for small molecule synthesis may be within reach. PMID:29696152

Tumor-targeting peptides from combinatorial libraries*

PubMed Central

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S.

2018-01-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges infighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. PMID:27210583

Identification of combinatorial drug regimens for treatment of Huntington's disease using Drosophila

NASA Astrophysics Data System (ADS)

Agrawal, Namita; Pallos, Judit; Slepko, Natalia; Apostol, Barbara L.; Bodai, Laszlo; Chang, Ling-Wen; Chiang, Ann-Shyn; Michels Thompson, Leslie; Marsh, J. Lawrence

2005-03-01

We explore the hypothesis that pathology of Huntington's disease involves multiple cellular mechanisms whose contributions to disease are incrementally additive or synergistic. We provide evidence that the photoreceptor neuron degeneration seen in flies expressing mutant human huntingtin correlates with widespread degenerative events in the Drosophila CNS. We use a Drosophila Huntington's disease model to establish dose regimens and protocols to assess the effectiveness of drug combinations used at low threshold concentrations. These proof of principle studies identify at least two potential combinatorial treatment options and illustrate a rapid and cost-effective paradigm for testing and optimizing combinatorial drug therapies while reducing side effects for patients with neurodegenerative disease. The potential for using prescreening in Drosophila to inform combinatorial therapies that are most likely to be effective for testing in mammals is discussed. combinatorial treatments | neurodegeneration

Nonparametric Combinatorial Sequence Models

NASA Astrophysics Data System (ADS)

Wauthier, Fabian L.; Jordan, Michael I.; Jojic, Nebojsa

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This paper presents a nonparametric prior on sequences which allows combinatorial structures to emerge and which induces a posterior distribution over factorized sequence representations. We carry out experiments on three sequence datasets which indicate that combinatorial structures are indeed present and that combinatorial sequence models can more succinctly describe them than simpler mixture models. We conclude with an application to MHC binding prediction which highlights the utility of the posterior distribution induced by the prior. By integrating out the posterior our method compares favorably to leading binding predictors.

Synergistic Effect of Combinatorial Treatment with Curcumin and Mitomycin C on the Induction of Apoptosis of Breast Cancer Cells: A cDNA Microarray Analysis

PubMed Central

Zhou, Qian-Mei; Chen, Qi-Long; Du, Jia; Wang, Xiu-Feng; Lu, Yi-Yu; Zhang, Hui; Su, Shi-Bing

2014-01-01

In order to explore the synergistic mechanisms of combinatorial treatment using curcumin and mitomycin C (MMC) for breast cancer, MCF-7 breast cancer xenografts were conducted to observe the synergistic effect of combinatorial treatment using curcumin and MMC at various dosages. The synergistic mechanisms of combinatorial treatment using curcumin and MMC on the inhibition of tumor growth were explored by differential gene expression profile, gene ontology (GO), ingenuity pathway analysis (IPA) and Signal–Net network analysis. The expression levels of selected genes identified by cDNA microarray expression profiling were validated by quantitative RT-PCR (qRT-PCR) and Western blot analysis. Effect of combinatorial treatment on the inhibition of cell growth was observed by MTT assay. Apoptosis was detected by flow cytometric analysis and Hoechst 33258 staining. The combinatorial treatment of 100 mg/kg curcumin and 1.5 mg/kg MMC revealed synergistic inhibition on tumor growth. Among 1501 differentially expressed genes, the expression of 25 genes exhibited an obvious change and a significant difference in 27 signal pathways was observed (p < 0.05). In addition, Mapk1 (ERK) and Mapk14 (MAPK p38) had more cross-interactions with other genes and revealed an increase in expression by 8.14- and 11.84-fold, respectively during the combinatorial treatment by curcumin and MMC when compared with the control. Moreover, curcumin can synergistically improve tumoricidal effect of MMC in another human breast cancer MDA-MB-231 cells. Apoptosis was significantly induced by the combinatorial treatment (p < 0.05) and significantly inhibited by ERK inhibitor (PD98059) in MCF-7 cells (p < 0.05). The synergistic effect of combinatorial treatment by curcumin and MMC on the induction of apoptosis in breast cancer cells may be via the ERK pathway. PMID:25226537

Screening of Small Molecule Interactor Library by Using In-Cell NMR Spectroscopy (SMILI-NMR)

PubMed Central

Xie, Jingjing; Thapa, Rajiv; Reverdatto, Sergey; Burz, David S.; Shekhtman, Alexander

2011-01-01

We developed an in-cell NMR assay for screening small molecule interactor libraries (SMILI-NMR) for compounds capable of disrupting or enhancing specific interactions between two or more components of a biomolecular complex. The method relies on the formation of a well-defined biocomplex and utilizes in-cell NMR spectroscopy to identify the molecular surfaces involved in the interaction at atomic scale resolution. Changes in the interaction surface caused by a small molecule interfering with complex formation are used as a read-out of the assay. The in-cell nature of the experimental protocol insures that the small molecule is capable of penetrating the cell membrane and specifically engaging the target molecule(s). Utility of the method was demonstrated by screening a small dipeptide library against the FKBP–FRB protein complex involved in cell cycle arrest. The dipeptide identified by SMILI-NMR showed biological activity in a functional assay in yeast. PMID:19422228

Combinatorial theory of Macdonald polynomials I: proof of Haglund's formula.

PubMed

Haglund, J; Haiman, M; Loehr, N

2005-02-22

Haglund recently proposed a combinatorial interpretation of the modified Macdonald polynomials H(mu). We give a combinatorial proof of this conjecture, which establishes the existence and integrality of H(mu). As corollaries, we obtain the cocharge formula of Lascoux and Schutzenberger for Hall-Littlewood polynomials, a formula of Sahi and Knop for Jack's symmetric functions, a generalization of this result to the integral Macdonald polynomials J(mu), a formula for H(mu) in terms of Lascoux-Leclerc-Thibon polynomials, and combinatorial expressions for the Kostka-Macdonald coefficients K(lambda,mu) when mu is a two-column shape.

Interactions of quercetin, curcumin, epigallocatechin gallate and folic acid with gelatin.

PubMed

Yang, Tingting; Yang, Huiru; Fan, Yan; Li, Bafang; Hou, Hu

2018-06-15

Some small bioactive molecules from food show the potential health benefits, but with poor chemical stability and bioavailability. The interactions between small molecules and gelatin were investigated. Fluorescence experiments demonstrated that the bimolecular quenching constants (k q ) of complexes (gelatin-quercetin, gelatin-curcumin, gelatin-epigallocatechin gallate, gelatin-folic acid) were 3.7 × 10 12  L·mol -1 ·s -1 , 1.4 × 10 12  L·mol -1 ·s -1 , 2.7 × 10 12  L·mol -1 ·s -1 and 8.5 × 10 12  L·mol -1 ·s -1 , indicating that fluorescence quenching did not arise from a dynamical mechanism, but from gelatin-small molecules binding. Furthermore, the affinity with gelatin was ranked in the order of folic acid > quercetin > epigallocatechin gallate > curcumin. Fluorescence spectroscopy, ultraviolet and visible absorption spectroscopy, FTIR and circular dichroism showed that the interactions between small molecules and gelatin did not significantly alter the conformation and secondary structure of gelatin. Non-covalent interactions may result in the binding of gelatin with small molecules. The interactions were considered to be through two modes: (1) small molecules bound within the hydrophobic pockets of gelatin; (2) small molecules surrounded the gelatin molecule mainly through hydrogen bonds and hydrophobic interactions. Copyright © 2018 Elsevier B.V. All rights reserved.

Targeting Leishmania major parasite with peptides derived from a combinatorial phage display library.

PubMed

Rhaiem, Rafik Ben; Houimel, Mehdi

2016-07-01

Cutaneous leishmaniasis (CL) is a global problem caused by intracellular protozoan pathogens of the genus Leishmania for which there are no suitable vaccine or chemotherapy options. Thus, de novo identification of small molecules binding to the Leishmania parasites by direct screening is a promising and appropriate alternative strategy for the development of new drugs. In this study, we used a random linear hexapeptide library fused to the gene III protein of M13 filamentous bacteriophage to select binding peptides to metacyclic promastigotes from a highly virulent strain of Leishmania major (Zymodeme MON-25; MHOM/TN/94/GLC94). After four rounds of stringent selection and amplification, polyclonal and monoclonal phage-peptides directed against L. major metacyclic promastigotes were assessed by ELISA, and the optimal phage-peptides were grown individually and characterized for binding to L. major by monoclonal phage ELISA. The DNA of 42 phage-peptides clones was amplified by PCR, sequenced, and their amino acid sequences deduced. Six different peptide sequences were obtained with frequencies of occurrence ranging from 2.3% to 85.7%. The biological effect of the peptides was assessed in vitro on human monocytes infected with L. major metacyclic promastigotes, and in vivo on susceptible parasite-infected BALB/c mice. The development of cutaneous lesions in the right hind footpads of infected mice after 13 weeks post-infection showed a protection rate of 81.94% with the injected peptide P2. Moreover, Western blots revealed that the P2 peptide interacted with the major surface protease gp63, a protein of 63kDa molecular weight. Moreover, bioinformatics were used to predict the interaction between peptides and the major surface molecule of the L. major. The molecular docking showed that the P2 peptide has the minimum interaction energy and maximum shape complimentarity with the L. major gp63 active site. Our study demonstrated that the P2 peptide occurs at high frequency during the screening procedure, best inhibits L. major growth kinetics in vitro, and reduces cutaneous lesions in BALB/c mice, thus showing great promise in the development of new therapeutic molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

Small area estimation of obesity prevalence and dietary patterns: a model applied to Rio de Janeiro city, Brazil.

PubMed

Cataife, Guido

2014-03-01

We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008-9 family expenditure survey with Census 2010 socio-demographic data. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich. Male and female obesity rates are uncorrelated at the small area level. The model is an effective tool to understand the complexity of the problem and to aid in policy design. © 2013 Published by Elsevier Ltd.

To Think without Thinking: The Implications of Combinatory Play and the Creative Process for Neuroaesthetics

ERIC Educational Resources Information Center

Stevens, Victoria

2014-01-01

The author considers combinatory play as an intersection between creativity, play, and neuroaesthetics. She discusses combinatory play as vital to the creative process in art and science, particularly with regard to the incubation of new ideas. She reviews findings from current neurobiological research and outlines the way that the brain activates…

Computational approaches to screen candidate ligands with anti- Parkinson's activity using R programming.

PubMed

Jayadeepa, R M; Niveditha, M S

2012-01-01

It is estimated that by 2050 over 100 million people will be affected by the Parkinson's disease (PD). We propose various computational approaches to screen suitable candidate ligand with anti-Parkinson's activity from phytochemicals. Five different types of dopamine receptors have been identified in the brain, D1-D5. Dopamine receptor D3 was selected as the target receptor. The D3 receptor exists in areas of the brain outside the basal ganglia, such as the limbic system, and thus may play a role in the cognitive and emotional changes noted in Parkinson's disease. A ligand library of 100 molecules with anti-Parkinson's activity was collected from literature survey. Nature is the best combinatorial chemist and possibly has answers to all diseases of mankind. Failure of some synthetic drugs and its side effects have prompted many researches to go back to ancient healing methods which use herbal medicines to give relief. Hence, the candidate ligands with anti-Parkinson's were selected from herbal sources through literature survey. Lipinski rules were applied to screen the suitable molecules for the study, the resulting 88 molecules were energy minimized, and subjected to docking using Autodock Vina. The top eleven molecules were screened according to the docking score generated by Autodock Vina Commercial drug Ropinirole was computed similarly and was compared with the 11 phytochemicals score, the screened molecules were subjected to toxicity analysis and to verify toxic property of phytochemicals. R Programming was applied to remove the bias from the top eleven molecules. Using cluster analysis and Confusion Matrix two phytochemicals were computationally selected namely Rosmarinic acid and Gingkolide A for further studies on the disease Parkinson's.

Selection and Biosensor Application of Aptamers for Small Molecules

PubMed Central

Pfeiffer, Franziska; Mayer, Günter

2016-01-01

Small molecules play a major role in the human body and as drugs, toxins, and chemicals. Tools to detect and quantify them are therefore in high demand. This review will give an overview about aptamers interacting with small molecules and their selection. We discuss the current state of the field, including advantages as well as problems associated with their use and possible solutions to tackle these. We then discuss different kinds of small molecule aptamer-based sensors described in literature and their applications, ranging from detecting drinking water contaminations to RNA imaging. PMID:27379229

Methods to enable the design of bioactive small molecules targeting RNA

PubMed Central

Disney, Matthew D.; Yildirim, Ilyas; Childs-Disney, Jessica L.

2014-01-01

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including Structure-Activity Relationships Through Sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome. PMID:24357181

Methods to enable the design of bioactive small molecules targeting RNA.

PubMed

Disney, Matthew D; Yildirim, Ilyas; Childs-Disney, Jessica L

2014-02-21

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset.

PubMed

Seashore-Ludlow, Brinton; Rees, Matthew G; Cheah, Jaime H; Cokol, Murat; Price, Edmund V; Coletti, Matthew E; Jones, Victor; Bodycombe, Nicole E; Soule, Christian K; Gould, Joshua; Alexander, Benjamin; Li, Ava; Montgomery, Philip; Wawer, Mathias J; Kuru, Nurdan; Kotz, Joanne D; Hon, C Suk-Yee; Munoz, Benito; Liefeld, Ted; Dančík, Vlado; Bittker, Joshua A; Palmer, Michelle; Bradner, James E; Shamji, Alykhan F; Clemons, Paul A; Schreiber, Stuart L

2015-11-01

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2). We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses. ©2015 American Association for Cancer Research.

Mapping of Drug-like Chemical Universe with Reduced Complexity Molecular Frameworks.

PubMed

Kontijevskis, Aleksejs

2017-04-24

The emergence of the DNA-encoded chemical libraries (DEL) field in the past decade has attracted the attention of the pharmaceutical industry as a powerful mechanism for the discovery of novel drug-like hits for various biological targets. Nuevolution Chemetics technology enables DNA-encoded synthesis of billions of chemically diverse drug-like small molecule compounds, and the efficient screening and optimization of these, facilitating effective identification of drug candidates at an unprecedented speed and scale. Although many approaches have been developed by the cheminformatics community for the analysis and visualization of drug-like chemical space, most of them are restricted to the analysis of a maximum of a few millions of compounds and cannot handle collections of 10 8 -10 12 compounds typical for DELs. To address this big chemical data challenge, we developed the Reduced Complexity Molecular Frameworks (RCMF) methodology as an abstract and very general way of representing chemical structures. By further introducing RCMF descriptors, we constructed a global framework map of drug-like chemical space and demonstrated how chemical space occupied by multi-million-member drug-like Chemetics DNA-encoded libraries and virtual combinatorial libraries with >10 12 members could be analyzed and mapped without a need for library enumeration. We further validate the approach by performing RCMF-based searches in a drug-like chemical universe and mapping Chemetics library selection outputs for LSD1 targets on a global framework chemical space map.

Targeting the yin and the yang: combined inhibition of the tyrosine kinase c-Src and the tyrosine phosphatase SHP-2 disrupts pancreatic cancer signaling and biology in vitro and tumor formation in vivo.

PubMed

Gomes, Evan G; Connelly, Sarah F; Summy, Justin M

2013-07-01

Although c-Src (Src) has emerged as a potential pancreatic cancer target in preclinical studies, Src inhibitors have not demonstrated a significant therapeutic benefit in clinical trials. The objective of these studies was to examine the effects of combining Src inhibition with inhibition of the protein tyrosine phosphatase SHP-2 in pancreatic cancer cells in vitro and in vivo. SHP-2 and Src functions were inhibited by siRNA or small molecule inhibitors. The effects of dual Src/SHP-2 functional inhibition were evaluated by Western blot analysis of downstream signaling pathways; cell biology assays to examine caspase activity, viability, adhesion, migration, and invasion in vitro; and an orthotopic nude mouse model to observe pancreatic tumor formation in vivo. Dual targeting of Src and SHP-2 induces an additive or supra-additive loss of phosphorylation of Akt and ERK-1/2 and corresponding increases in expression of apoptotic markers, relative to targeting either protein individually. Combinatorial inhibition of Src and SHP-2 significantly reduces viability, adhesion, migration, and invasion of pancreatic cancer cells in vitro and tumor formation in vivo, relative to individual Src/SHP-2 inhibition. These data suggest that the antitumor effects of Src inhibition in pancreatic cancer may be enhanced through simultaneous inhibition of SHP-2.

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets.

PubMed

Trepalin, Sergey; Osadchiy, Nikolay

2005-01-01

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10(-40) in typical cases.

The centroidal algorithm in molecular similarity and diversity calculations on confidential datasets

NASA Astrophysics Data System (ADS)

Trepalin, Sergey; Osadchiy, Nikolay

2005-09-01

Chemical structure provides exhaustive description of a compound, but it is often proprietary and thus an impediment in the exchange of information. For example, structure disclosure is often needed for the selection of most similar or dissimilar compounds. Authors propose a centroidal algorithm based on structural fragments (screens) that can be efficiently used for the similarity and diversity selections without disclosing structures from the reference set. For an increased security purposes, authors recommend that such set contains at least some tens of structures. Analysis of reverse engineering feasibility showed that the problem difficulty grows with decrease of the screen's radius. The algorithm is illustrated with concrete calculations on known steroidal, quinoline, and quinazoline drugs. We also investigate a problem of scaffold identification in combinatorial library dataset. The results show that relatively small screens of radius equal to 2 bond lengths perform well in the similarity sorting, while radius 4 screens yield better results in diversity sorting. The software implementation of the algorithm taking SDF file with a reference set generates screens of various radii which are subsequently used for the similarity and diversity sorting of external SDFs. Since the reverse engineering of the reference set molecules from their screens has the same difficulty as the RSA asymmetric encryption algorithm, generated screens can be stored openly without further encryption. This approach ensures an end user transfers only a set of structural fragments and no other data. Like other algorithms of encryption, the centroid algorithm cannot give 100% guarantee of protecting a chemical structure from dataset, but probability of initial structure identification is very small-order of 10-40 in typical cases.

Overcoming Resistance to Cetuximab with Honokiol, A Small-Molecule Polyphenol.

PubMed

Pearson, Hannah E; Iida, Mari; Orbuch, Rachel A; McDaniel, Nellie K; Nickel, Kwangok P; Kimple, Randall J; Arbiser, Jack L; Wheeler, Deric L

2018-01-01

Overexpression and activation of the EGFR have been linked to poor prognosis in several human cancers. Cetuximab is a mAb against EGFR that is used for the treatment in head and neck squamous cell carcinoma (HNSCC) and metastatic colorectal cancer. Unfortunately, most tumors have intrinsic or will acquire resistance to cetuximab during the course of therapy. Honokiol is a natural compound found in the bark and leaves of the Chinese Magnolia tree and is established to have several anticancer properties without appreciable toxicity. In this study, we hypothesized that combining cetuximab and honokiol treatments could overcome acquired resistance to cetuximab. We previously developed a model of acquired resistance to cetuximab in non-small cell lung cancer H226 cell line. Treatment of cetuximab-resistant clones with honokiol and cetuximab resulted in a robust antiproliferative response. Immunoblot analysis revealed the HER family and their signaling pathways were downregulated after combination treatment, most notably the proliferation (MAPK) and survival (AKT) pathways. In addition, we found a decrease in phosphorylation of DRP1 and reactive oxygen species after combination treatment in cetuximab-resistant clones, which may signify a change in mitochondrial function. Furthermore, we utilized cetuximab-resistant HNSCC patient-derived xenografts (PDX) to test the benefit of combinatorial treatment in vivo There was significant growth delay in PDX tumors after combination treatment with a subsequent downregulation of active MAPK, AKT, and DRP1 signaling as seen in vitro Collectively, these data suggest that honokiol is a promising natural compound in overcoming acquired resistance to cetuximab. Mol Cancer Ther; 17(1); 204-14. ©2017 AACR . ©2017 American Association for Cancer Research.

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis

PubMed Central

Twarog, Nathaniel R.; Low, Jonathan A.; Currier, Duane G.; Miller, Greg; Chen, Taosheng; Shelat, Anang A.

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2’-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used. PMID:26886014

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis.

PubMed

Twarog, Nathaniel R; Low, Jonathan A; Currier, Duane G; Miller, Greg; Chen, Taosheng; Shelat, Anang A

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.

Combinatorial genetic perturbation to refine metabolic circuits for producing biofuels and biochemicals.

PubMed

Kim, Hyo Jin; Turner, Timothy Lee; Jin, Yong-Su

2013-11-01

Recent advances in metabolic engineering have enabled microbial factories to compete with conventional processes for producing fuels and chemicals. Both rational and combinatorial approaches coupled with synthetic and systematic tools play central roles in metabolic engineering to create and improve a selected microbial phenotype. Compared to knowledge-based rational approaches, combinatorial approaches exploiting biological diversity and high-throughput screening have been demonstrated as more effective tools for improving various phenotypes of interest. In particular, identification of unprecedented targets to rewire metabolic circuits for maximizing yield and productivity of a target chemical has been made possible. This review highlights general principles and the features of the combinatorial approaches using various libraries to implement desired phenotypes for strain improvement. In addition, recent applications that harnessed the combinatorial approaches to produce biofuels and biochemicals will be discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Tumor-targeting peptides from combinatorial libraries.

PubMed

Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S

2017-02-01

Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges in fighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. Copyright © 2017. Published by Elsevier B.V.

Identification of a Broad-Spectrum Antiviral Small Molecule against Severe Acute Respiratory Syndrome Coronavirus and Ebola, Hendra, and Nipah Viruses by Using a Novel High-Throughput Screening Assay

PubMed Central

Elshabrawy, Hatem A.; Fan, Jilao; Haddad, Christine S.; Ratia, Kiira; Broder, Christopher C.; Caffrey, Michael

2014-01-01

ABSTRACT Severe acute respiratory syndrome coronavirus (SARS-CoV) and Ebola, Hendra, and Nipah viruses are members of different viral families and are known causative agents of fatal viral diseases. These viruses depend on cathepsin L for entry into their target cells. The viral glycoproteins need to be primed by protease cleavage, rendering them active for fusion with the host cell membrane. In this study, we developed a novel high-throughput screening assay based on peptides, derived from the glycoproteins of the aforementioned viruses, which contain the cathepsin L cleavage site. We screened a library of 5,000 small molecules and discovered a small molecule that can inhibit the cathepsin L cleavage of all viral peptides with minimal inhibition of cleavage of a host protein-derived peptide (pro-neuropeptide Y). The small molecule inhibited the entry of all pseudotyped viruses in vitro and the cleavage of SARS-CoV spike glycoprotein in an in vitro cleavage assay. In addition, the Hendra and Nipah virus fusion glycoproteins were not cleaved in the presence of the small molecule in a cell-based cleavage assay. Furthermore, we demonstrate that the small molecule is a mixed inhibitor of cathepsin L. Our broad-spectrum antiviral small molecule appears to be an ideal candidate for future optimization and development into a potent antiviral against SARS-CoV and Ebola, Hendra, and Nipah viruses. IMPORTANCE We developed a novel high-throughput screening assay to identify small molecules that can prevent cathepsin L cleavage of viral glycoproteins derived from SARS-CoV and Ebola, Hendra, and Nipah viruses that are required for their entry into the host cell. We identified a novel broad-spectrum small molecule that could block cathepsin L-mediated cleavage and thus inhibit the entry of pseudotypes bearing the glycoprotein derived from SARS-CoV or Ebola, Hendra, or Nipah virus. The small molecule can be further optimized and developed into a potent broad-spectrum antiviral drug. PMID:24501399

Identification of a broad-spectrum antiviral small molecule against severe acute respiratory syndrome coronavirus and Ebola, Hendra, and Nipah viruses by using a novel high-throughput screening assay.

PubMed

Elshabrawy, Hatem A; Fan, Jilao; Haddad, Christine S; Ratia, Kiira; Broder, Christopher C; Caffrey, Michael; Prabhakar, Bellur S

2014-04-01

Severe acute respiratory syndrome coronavirus (SARS-CoV) and Ebola, Hendra, and Nipah viruses are members of different viral families and are known causative agents of fatal viral diseases. These viruses depend on cathepsin L for entry into their target cells. The viral glycoproteins need to be primed by protease cleavage, rendering them active for fusion with the host cell membrane. In this study, we developed a novel high-throughput screening assay based on peptides, derived from the glycoproteins of the aforementioned viruses, which contain the cathepsin L cleavage site. We screened a library of 5,000 small molecules and discovered a small molecule that can inhibit the cathepsin L cleavage of all viral peptides with minimal inhibition of cleavage of a host protein-derived peptide (pro-neuropeptide Y). The small molecule inhibited the entry of all pseudotyped viruses in vitro and the cleavage of SARS-CoV spike glycoprotein in an in vitro cleavage assay. In addition, the Hendra and Nipah virus fusion glycoproteins were not cleaved in the presence of the small molecule in a cell-based cleavage assay. Furthermore, we demonstrate that the small molecule is a mixed inhibitor of cathepsin L. Our broad-spectrum antiviral small molecule appears to be an ideal candidate for future optimization and development into a potent antiviral against SARS-CoV and Ebola, Hendra, and Nipah viruses. We developed a novel high-throughput screening assay to identify small molecules that can prevent cathepsin L cleavage of viral glycoproteins derived from SARS-CoV and Ebola, Hendra, and Nipah viruses that are required for their entry into the host cell. We identified a novel broad-spectrum small molecule that could block cathepsin L-mediated cleavage and thus inhibit the entry of pseudotypes bearing the glycoprotein derived from SARS-CoV or Ebola, Hendra, or Nipah virus. The small molecule can be further optimized and developed into a potent broad-spectrum antiviral drug.

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read-Write Genome Evolution as an Active Biological Process.

PubMed

Shapiro, James A

2016-06-08

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess "Read-Write Genomes" they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification.

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read–Write Genome Evolution as an Active Biological Process

PubMed Central

Shapiro, James A.

2016-01-01

The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess “Read–Write Genomes” they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification. PMID:27338490

HDAC Inhibitors as Novel Anti-Cancer Therapeutics.

PubMed

De Souza, Cristabelle; Chatterji, Biswa Prasun

2015-01-01

Malignant growth of cells is a condition characterized by unchecked cellular proliferation, genetic instability and epigenetic dysregulation. Up-regulated HDAC (Histone Deacetylase) enzyme activity is associated with a closed chromatin assembly and subsequent gene repression, forming a characteristic feature of malignantly transformed cells. Novel therapeutics are now targeting the zinc containing HDAC enzymes for treating various types of cancers. Recently, a spate of drugs acting via HDAC inhibition have been undergoing clinical trials and several patents present exciting molecules like PCI-24781 (Abexinostat), ITF- 2357 (Givinostat); MS-275 (Entinostat), MGCD 0103 (Mocetinostat), LBH-589 (Panobinostat), FK228 (Romidepsin), PXD-101 (Belinostat) and Valproic Acid to be used as alternatives or adjuvants to traditional chemotherapeutics. However, only three HDAC inhibitors have acquired FDA approval till date. Recently, PXD-101 obtained FDA approval for the treatment of Refractory or Relapsed Peripheral T cell lymphoma. The current article reviews patents that have introduced novel molecules that are HDAC isoform specific, superior to first generation HDAC inhibitors like SAHA (Suberoylanilide Hydroxamic Acid) and TSA (Trichostatin A) and can be modified structurally to reduce toxic side effects and increase specificity. These molecules can combine the best characteristics of an ideal HDAC inhibiting drug either as monotherapy or in combinatorial therapy for cancer treatment thus, indicating promise to be included in the next generation of target specific HDAC inhibiting drugs.

Ribosome Display of Combinatorial Antibody Libraries Derived from Mice Immunized with Heat-Killed Xylella fastidiosa and the Selection of MopB-Specific Single-Chain Antibodies

PubMed Central

Azizi, Armaghan; Arora, Arinder; Markiv, Anatoliy; Lampe, David J.; Miller, Thomas A.

2012-01-01

Pierce's disease is a devastating lethal disease of Vitus vinifera grapevines caused by the bacterium Xylella fastidiosa. There is no cure for Pierce's disease, and control is achieved predominantly by suppressing transmission of the glassy-winged sharpshooter insect vector. We present a simple robust approach for the generation of panels of recombinant single-chain antibodies against the surface-exposed elements of X. fastidiosa that may have potential use in diagnosis and/or disease transmission blocking studies. In vitro combinatorial antibody ribosome display libraries were assembled from immunoglobulin transcripts rescued from the spleens of mice immunized with heat-killed X. fastidiosa. The libraries were used in a single round of selection against an outer membrane protein, MopB, resulting in the isolation of a panel of recombinant antibodies. The potential use of selected anti-MopB antibodies was demonstrated by the successful application of the 4XfMopB3 antibody in an enzyme-linked immunosorbent assay (ELISA), a Western blot assay, and an immunofluorescence assay (IFA). These immortalized in vitro recombinant single-chain antibody libraries generated against heat-killed X. fastidiosa are a resource for the Pierce's disease research community that may be readily accessed for the isolation of antibodies against a plethora of X. fastidiosa surface-exposed antigenic molecules. PMID:22327580

Distributed Drug Discovery, Part 2: Global Rehearsal of Alkylating Agents for the Synthesis of Resin-Bound Unnatural Amino Acids and Virtual D3 Catalog Construction

PubMed Central

2008-01-01

Distributed Drug Discovery (D3) proposes solving large drug discovery problems by breaking them into smaller units for processing at multiple sites. A key component of the synthetic and computational stages of D3 is the global rehearsal of prospective reagents and their subsequent use in the creation of virtual catalogs of molecules accessible by simple, inexpensive combinatorial chemistry. The first section of this article documents the feasibility of the synthetic component of Distributed Drug Discovery. Twenty-four alkylating agents were rehearsed in the United States, Poland, Russia, and Spain, for their utility in the synthesis of resin-bound unnatural amino acids 1, key intermediates in many combinatorial chemistry procedures. This global reagent rehearsal, coupled to virtual library generation, increases the likelihood that any member of that virtual library can be made. It facilitates the realistic integration of worldwide virtual D3 catalog computational analysis with synthesis. The second part of this article describes the creation of the first virtual D3 catalog. It reports the enumeration of 24 416 acylated unnatural amino acids 5, assembled from lists of either rehearsed or well-precedented alkylating and acylating reagents, and describes how the resulting catalog can be freely accessed, searched, and downloaded by the scientific community. PMID:19105725

Morphological Constraints on Cerebellar Granule Cell Combinatorial Diversity.

PubMed

Gilmer, Jesse I; Person, Abigail L

2017-12-13

Combinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Granule cells (GrCs) sample approximately four mossy fiber inputs and are thought to form a combinatorial code useful for pattern separation and learning. We constructed a spatially realistic model of the cerebellar GCL and examined how GCL architecture contributes to GrC combinatorial diversity. We found that GrC combinatorial diversity saturates quickly as mossy fiber input diversity increases, and that this saturation is in part a consequence of short dendrites, which limit access to diverse inputs and favor dense sampling of local inputs. This local sampling also produced GrCs that were combinatorially redundant, even when input diversity was extremely high. In addition, we found that mossy fiber clustering, which is a common anatomical pattern, also led to increased redundancy of GrC input combinations. We related this redundancy to hypothesized roles of temporal expansion of GrC information encoding in service of learned timing, and we show that GCL architecture produces GrC populations that support both temporal and combinatorial expansion. Finally, we used novel anatomical measurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, finding that these circuit features uniquely contribute to enhancing GrC diversification and redundancy. Our results complement information theoretic studies of granule layer structure and provide insight into the contributions of granule layer anatomical features to afferent mixing. SIGNIFICANCE STATEMENT Cerebellar granule cells are among the simplest neurons, with tiny somata and, on average, just four dendrites. These characteristics, along with their dense organization, inspired influential theoretical work on the granule cell layer as a combinatorial expander, where each granule cell represents a unique combination of inputs. Despite the centrality of these theories to cerebellar physiology, the degree of expansion supported by anatomically realistic patterns of inputs is unknown. Using modeling and anatomy, we show that realistic input patterns constrain combinatorial diversity by producing redundant combinations, which nevertheless could support temporal diversification of like combinations, suitable for learned timing. Our study suggests a neural substrate for producing high levels of both combinatorial and temporal diversity in the granule cell layer. Copyright © 2017 the authors 0270-6474/17/3712153-14$15.00/0.

Recent Developments in β-Cell Differentiation of Pluripotent Stem Cells Induced by Small and Large Molecules

PubMed Central

Kumar, S. Suresh; Alarfaj, Abdullah A.; Munusamy, Murugan A.; Singh, A. J. A. Ranjith; Peng, I-Chia; Priya, Sivan Padma; Hamat, Rukman Awang; Higuchi, Akon

2014-01-01

Human pluripotent stem cells, including human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs), hold promise as novel therapeutic tools for diabetes treatment because of their self-renewal capacity and ability to differentiate into beta (β)-cells. Small and large molecules play important roles in each stage of β-cell differentiation from both hESCs and hiPSCs. The small and large molecules that are described in this review have significantly advanced efforts to cure diabetic disease. Lately, effective protocols have been implemented to induce hESCs and human mesenchymal stem cells (hMSCs) to differentiate into functional β-cells. Several small molecules, proteins, and growth factors promote pancreatic differentiation from hESCs and hMSCs. These small molecules (e.g., cyclopamine, wortmannin, retinoic acid, and sodium butyrate) and large molecules (e.g. activin A, betacellulin, bone morphogentic protein (BMP4), epidermal growth factor (EGF), fibroblast growth factor (FGF), keratinocyte growth factor (KGF), hepatocyte growth factor (HGF), noggin, transforming growth factor (TGF-α), and WNT3A) are thought to contribute from the initial stages of definitive endoderm formation to the final stages of maturation of functional endocrine cells. We discuss the importance of such small and large molecules in uniquely optimized protocols of β-cell differentiation from stem cells. A global understanding of various small and large molecules and their functions will help to establish an efficient protocol for β-cell differentiation. PMID:25526563

High Throughput, Label-free Screening Small Molecule Compound Libraries for Protein-Ligands using Combination of Small Molecule Microarrays and a Special Ellipsometry-based Optical Scanner.

PubMed

Landry, James P; Fei, Yiyan; Zhu, X D

2011-12-01

Small-molecule compounds remain the major source of therapeutic and preventative drugs. Developing new drugs against a protein target often requires screening large collections of compounds with diverse structures for ligands or ligand fragments that exhibit sufficiently affinity and desirable inhibition effect on the target before further optimization and development. Since the number of small molecule compounds is large, high-throughput screening (HTS) methods are needed. Small-molecule microarrays (SMM) on a solid support in combination with a suitable binding assay form a viable HTS platform. We demonstrate that by combining an oblique-incidence reflectivity difference optical scanner with SMM we can screen 10,000 small-molecule compounds on a single glass slide for protein ligands without fluorescence labeling. Furthermore using such a label-free assay platform we can simultaneously acquire binding curves of a solution-phase protein to over 10,000 immobilized compounds, thus enabling full characterization of protein-ligand interactions over a wide range of affinity constants.

Delivery of small molecules for bone regenerative engineering: preclinical studies and potential clinical applications.

PubMed

Laurencin, Cato T; Ashe, Keshia M; Henry, Nicole; Kan, Ho Man; Lo, Kevin W-H

2014-06-01

Stimulation of bone regeneration using growth factors is a promising approach for musculoskeletal regenerative engineering. However, common limitations with protein growth factors, such as high manufacturing costs, protein instability, contamination issues, and unwanted immunogenic responses of the host reduce potential clinical applications. New strategies for bone regeneration that involve inexpensive and stable small molecules can obviate these problems and have a significant impact on the treatment of skeletal injury and diseases. Over the past decade, a large number of small molecules with the potential of regenerating skeletal tissue have been reported in the literature. Here, we review this literature, paying specific attention to the prospects for small molecule-based bone-regenerative engineering. We also review the preclinical study of small molecules associated with bone regeneration. Copyright © 2014 Elsevier Ltd. All rights reserved.

Small molecule annotation for the Protein Data Bank

PubMed Central

Sen, Sanchayita; Young, Jasmine; Berrisford, John M.; Chen, Minyu; Conroy, Matthew J.; Dutta, Shuchismita; Di Costanzo, Luigi; Gao, Guanghua; Ghosh, Sutapa; Hudson, Brian P.; Igarashi, Reiko; Kengaku, Yumiko; Liang, Yuhe; Peisach, Ezra; Persikova, Irina; Mukhopadhyay, Abhik; Narayanan, Buvaneswari Coimbatore; Sahni, Gaurav; Sato, Junko; Sekharan, Monica; Shao, Chenghua; Tan, Lihua; Zhuravleva, Marina A.

2014-01-01

The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100 000 structures contain more than 20 000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors. PMID:25425036

Small molecule annotation for the Protein Data Bank.

PubMed

Sen, Sanchayita; Young, Jasmine; Berrisford, John M; Chen, Minyu; Conroy, Matthew J; Dutta, Shuchismita; Di Costanzo, Luigi; Gao, Guanghua; Ghosh, Sutapa; Hudson, Brian P; Igarashi, Reiko; Kengaku, Yumiko; Liang, Yuhe; Peisach, Ezra; Persikova, Irina; Mukhopadhyay, Abhik; Narayanan, Buvaneswari Coimbatore; Sahni, Gaurav; Sato, Junko; Sekharan, Monica; Shao, Chenghua; Tan, Lihua; Zhuravleva, Marina A

2014-01-01

The Protein Data Bank (PDB) is the single global repository for three-dimensional structures of biological macromolecules and their complexes, and its more than 100,000 structures contain more than 20,000 distinct ligands or small molecules bound to proteins and nucleic acids. Information about these small molecules and their interactions with proteins and nucleic acids is crucial for our understanding of biochemical processes and vital for structure-based drug design. Small molecules present in a deposited structure may be attached to a polymer or may occur as a separate, non-covalently linked ligand. During curation of a newly deposited structure by wwPDB annotation staff, each molecule is cross-referenced to the PDB Chemical Component Dictionary (CCD). If the molecule is new to the PDB, a dictionary description is created for it. The information about all small molecule components found in the PDB is distributed via the ftp archive as an external reference file. Small molecule annotation in the PDB also includes information about ligand-binding sites and about covalent and other linkages between ligands and macromolecules. During the remediation of the peptide-like antibiotics and inhibitors present in the PDB archive in 2011, it became clear that additional annotation was required for consistent representation of these molecules, which are quite often composed of several sequential subcomponents including modified amino acids and other chemical groups. The connectivity information of the modified amino acids is necessary for correct representation of these biologically interesting molecules. The combined information is made available via a new resource called the Biologically Interesting molecules Reference Dictionary, which is complementary to the CCD and is now routinely used for annotation of peptide-like antibiotics and inhibitors. © The Author(s) 2014. Published by Oxford University Press.

Developing an Efficient and General Strategy for Immobilization of Small Molecules onto Microarrays Using Isocyanate Chemistry.

PubMed

Zhu, Chenggang; Zhu, Xiangdong; Landry, James P; Cui, Zhaomeng; Li, Quanfu; Dang, Yongjun; Mi, Lan; Zheng, Fengyun; Fei, Yiyan

2016-03-16

Small-molecule microarray (SMM) is an effective platform for identifying lead compounds from large collections of small molecules in drug discovery, and efficient immobilization of molecular compounds is a pre-requisite for the success of such a platform. On an isocyanate functionalized surface, we studied the dependence of immobilization efficiency on chemical residues on molecular compounds, terminal residues on isocyanate functionalized surface, lengths of spacer molecules, and post-printing treatment conditions, and we identified a set of optimized conditions that enable us to immobilize small molecules with significantly improved efficiencies, particularly for those molecules with carboxylic acid residues that are known to have low isocyanate reactivity. We fabricated microarrays of 3375 bioactive compounds on isocyanate functionalized glass slides under these optimized conditions and confirmed that immobilization percentage is over 73%.

Cell-targetable DNA nanocapsules for spatiotemporal release of caged bioactive small molecules

NASA Astrophysics Data System (ADS)

Veetil, Aneesh T.; Chakraborty, Kasturi; Xiao, Kangni; Minter, Myles R.; Sisodia, Sangram S.; Krishnan, Yamuna

2017-12-01

Achieving triggered release of small molecules with spatial and temporal precision at designated cells within an organism remains a challenge. By combining a cell-targetable, icosahedral DNA-nanocapsule loaded with photoresponsive polymers, we show cytosolic delivery of small molecules with the spatial resolution of single endosomes in specific cells in Caenorhabditis elegans. Our technology can report on the extent of small molecules released after photoactivation as well as pinpoint the location at which uncaging of the molecules occurred. We apply this technology to release dehydroepiandrosterone (DHEA), a neurosteroid that promotes neurogenesis and neuron survival, and determined the timescale of neuronal activation by DHEA, using light-induced release of DHEA from targeted DNA nanocapsules. Importantly, sequestration inside the DNA capsule prevents photocaged DHEA from activating neurons prematurely. Our methodology can in principle be generalized to diverse neurostimulatory molecules.

Molecular computation: RNA solutions to chess problems.

PubMed

Faulhammer, D; Cukras, A R; Lipton, R J; Landweber, L F

2000-02-15

We have expanded the field of "DNA computers" to RNA and present a general approach for the solution of satisfiability problems. As an example, we consider a variant of the "Knight problem," which asks generally what configurations of knights can one place on an n x n chess board such that no knight is attacking any other knight on the board. Using specific ribonuclease digestion to manipulate strands of a 10-bit binary RNA library, we developed a molecular algorithm and applied it to a 3 x 3 chessboard as a 9-bit instance of this problem. Here, the nine spaces on the board correspond to nine "bits" or placeholders in a combinatorial RNA library. We recovered a set of "winning" molecules that describe solutions to this problem.

DNA-Encoded Chemical Libraries: A Selection System Based on Endowing Organic Compounds with Amplifiable Information.

PubMed

Neri, Dario; Lerner, Richard A

2018-06-20

The discovery of organic ligands that bind specifically to proteins is a central problem in chemistry, biology, and the biomedical sciences. The encoding of individual organic molecules with distinctive DNA tags, serving as amplifiable identification bar codes, allows the construction and screening of combinatorial libraries of unprecedented size, thus facilitating the discovery of ligands to many different protein targets. Fundamentally, one links powers of genetics and chemical synthesis. After the initial description of DNA-encoded chemical libraries in 1992, several experimental embodiments of the technology have been reduced to practice. This review provides a historical account of important milestones in the development of DNA-encoded chemical libraries, a survey of relevant ongoing research activities, and a glimpse into the future.

Chemical Space of DNA-Encoded Libraries.

PubMed

Franzini, Raphael M; Randolph, Cassie

2016-07-28

In recent years, DNA-encoded chemical libraries (DECLs) have attracted considerable attention as a potential discovery tool in drug development. Screening encoded libraries may offer advantages over conventional hit discovery approaches and has the potential to complement such methods in pharmaceutical research. As a result of the increased application of encoded libraries in drug discovery, a growing number of hit compounds are emerging in scientific literature. In this review we evaluate reported encoded library-derived structures and identify general trends of these compounds in relation to library design parameters. We in particular emphasize the combinatorial nature of these libraries. Generally, the reported molecules demonstrate the ability of this technology to afford hits suitable for further lead development, and on the basis of them, we derive guidelines for DECL design.

Exploring biology with small organic molecules

PubMed Central

Stockwell, Brent R.

2011-01-01

Small organic molecules have proven to be invaluable tools for investigating biological systems, but there is still much to learn from their use. To discover and to use more effectively new chemical tools to understand biology, strategies are needed that allow us to systematically explore ‘biological-activity space’. Such strategies involve analysing both protein binding of, and phenotypic responses to, small organic molecules. The mapping of biological-activity space using small molecules is akin to mapping the stars — uncharted territory is explored using a system of coordinates that describes where each new feature lies. PMID:15602550

Inference of combinatorial Boolean rules of synergistic gene sets from cancer microarray datasets.

PubMed

Park, Inho; Lee, Kwang H; Lee, Doheon

2010-06-15

Gene set analysis has become an important tool for the functional interpretation of high-throughput gene expression datasets. Moreover, pattern analyses based on inferred gene set activities of individual samples have shown the ability to identify more robust disease signatures than individual gene-based pattern analyses. Although a number of approaches have been proposed for gene set-based pattern analysis, the combinatorial influence of deregulated gene sets on disease phenotype classification has not been studied sufficiently. We propose a new approach for inferring combinatorial Boolean rules of gene sets for a better understanding of cancer transcriptome and cancer classification. To reduce the search space of the possible Boolean rules, we identify small groups of gene sets that synergistically contribute to the classification of samples into their corresponding phenotypic groups (such as normal and cancer). We then measure the significance of the candidate Boolean rules derived from each group of gene sets; the level of significance is based on the class entropy of the samples selected in accordance with the rules. By applying the present approach to publicly available prostate cancer datasets, we identified 72 significant Boolean rules. Finally, we discuss several identified Boolean rules, such as the rule of glutathione metabolism (down) and prostaglandin synthesis regulation (down), which are consistent with known prostate cancer biology. Scripts written in Python and R are available at http://biosoft.kaist.ac.kr/~ihpark/. The refined gene sets and the full list of the identified Boolean rules are provided in the Supplementary Material. Supplementary data are available at Bioinformatics online.

Viral morphogenesis is the dominant source of sequence censorship in M13 combinatorial peptide phage display.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodi, D. J.; Soares, A. S.; Makowski, L.

Novel statistical methods have been developed and used to quantitate and annotate the sequence diversity within combinatorial peptide libraries on the basis of small numbers (1-200) of sequences selected at random from commercially available M13 p3-based phage display libraries. These libraries behave statistically as though they correspond to populations containing roughly 4.0{+-}1.6% of the random dodecapeptides and 7.9{+-}2.6% of the random constrained heptapeptides that are theoretically possible within the phage populations. Analysis of amino acid residue occurrence patterns shows no demonstrable influence on sequence censorship by Escherichia coli tRNA isoacceptor profiles or either overall codon or Class II codon usagemore » patterns, suggesting no metabolic constraints on recombinant p3 synthesis. There is an overall depression in the occurrence of cysteine, arginine and glycine residues and an overabundance of proline, threonine and histidine residues. The majority of position-dependent amino acid sequence bias is clustered at three positions within the inserted peptides of the dodecapeptide library, +1, +3 and +12 downstream from the signal peptidase cleavage site. Conformational tendency measures of the peptides indicate a significant preference for inserts favoring a {beta}-turn conformation. The observed protein sequence limitations can primarily be attributed to genetic codon degeneracy and signal peptidase cleavage preferences. These data suggest that for applications in which maximal sequence diversity is essential, such as epitope mapping or novel receptor identification, combinatorial peptide libraries should be constructed using codon-corrected trinucleotide cassettes within vector-host systems designed to minimize morphogenesis-related censorship.« less

Morphological study on small molecule acceptor-based organic solar cells with efficiencies beyond 7% (Presentation Recording)

NASA Astrophysics Data System (ADS)

Ma, Wei; Yan, He

2015-10-01

Despite the essential role of fullerenes in achieving best-performance organic solar cells (OSCs), fullerene acceptors have several drawbacks including poor light absorption, high-cost production and purification. For this reason, small molecule acceptor (SMA)-based OSCs have attracted much attention due to the easy tunability of electronic and optical properties of SMA materials. In this study, polymers with temperature dependent aggregation behaviors are combined with various small molecule acceptor materials, which lead to impressive power conversion efficiencies of up to 7.3%. The morphological and aggregation properties of the polymer:small molecule blends are studied in details. It is found that the temperature-dependent aggregation behavior of polymers allows for the processing of the polymer solutions at moderately elevated temperature, and more importantly, controlled aggregation and strong crystallization of the polymer during the film cooling and drying process. This results in a well-controlled and near-ideal polymer:small molecule morphology that is controlled by polymer aggregation during warm casting and thus insensitive to the choice of small molecules. As a result, several cases of highly efficient (PCE between 6-7.3%) SMA OSCs are achieved. The second part of this presentation will describe the morphology of a new small molecule acceptor with a unique 3D structure. The relationship between molecular structure and morphology is revealed.

Identification of small molecule inhibitors of cytokinesis and single cell wound repair

PubMed Central

Clark, Andrew G.; Sider, Jenny R.; Verbrugghe, Koen; Fenteany, Gabriel; von Dassow, George; Bement, William M.

2013-01-01

Screening of small molecule libraries offers the potential to identify compounds that inhibit specific biological processes and, ultimately, to identify macromolecules that are important players in such processes. To date, however, most screens of small molecule libraries have focused on identification of compounds that inhibit known proteins or particular steps in a given process, and have emphasized automated primary screens. Here we have used “low tech” in vivo primary screens to identify small molecules that inhibit both cytokinesis and single cell wound repair, two complex cellular processes that possess many common features. The “diversity set”, an ordered array of 1990 compounds available from the National Cancer Institute, was screened in parallel to identify compounds that inhibit cytokinesis in D. excentricus (sand dollar) embryos and single cell wound repair in X. laevis (frog) oocytes. Two small molecules were thus identified: Sph1 and Sph2. Sph1 reduces Rho activation in wound repair and suppresses formation of the spindle midzone during cytokinesis. Sph2 also reduces Rho activation in wound repair and may inhibit cytokinesis by blocking membrane fusion. The results identify two small molecules of interest for analysis of wound repair and cytokinesis, reveal that these processes are more similar than often realized and reveal the potential power of low tech screens of small molecule libraries for analysis of complex cellular processes. PMID:23125193

Finding the Right Candidate for the Right Position: A Fast NMR-Assisted Combinatorial Method for Optimizing Nucleic Acids Binders.

PubMed

Jiménez-Moreno, Ester; Montalvillo-Jiménez, Laura; Santana, Andrés G; Gómez, Ana M; Jiménez-Osés, Gonzalo; Corzana, Francisco; Bastida, Agatha; Jiménez-Barbero, Jesús; Cañada, Francisco Javier; Gómez-Pinto, Irene; González, Carlos; Asensio, Juan Luis

2016-05-25

Development of strong and selective binders from promiscuous lead compounds represents one of the most expensive and time-consuming tasks in drug discovery. We herein present a novel fragment-based combinatorial strategy for the optimization of multivalent polyamine scaffolds as DNA/RNA ligands. Our protocol provides a quick access to a large variety of regioisomer libraries that can be tested for selective recognition by combining microdialysis assays with simple isotope labeling and NMR experiments. To illustrate our approach, 20 small libraries comprising 100 novel kanamycin-B derivatives have been prepared and evaluated for selective binding to the ribosomal decoding A-Site sequence. Contrary to the common view of NMR as a low-throughput technique, we demonstrate that our NMR methodology represents a valuable alternative for the detection and quantification of complex mixtures, even integrated by highly similar or structurally related derivatives, a common situation in the context of a lead optimization process. Furthermore, this study provides valuable clues about the structural requirements for selective A-site recognition.

Design of focused and restrained subsets from extremely large virtual libraries.

PubMed

Jamois, Eric A; Lin, Chien T; Waldman, Marvin

2003-11-01

With the current and ever-growing offering of reagents along with the vast palette of organic reactions, virtual libraries accessible to combinatorial chemists can reach sizes of billions of compounds or more. Extracting practical size subsets for experimentation has remained an essential step in the design of combinatorial libraries. A typical approach to computational library design involves enumeration of structures and properties for the entire virtual library, which may be unpractical for such large libraries. This study describes a new approach termed as on the fly optimization (OTFO) where descriptors are computed as needed within the subset optimization cycle and without intermediate enumeration of structures. Results reported herein highlight the advantages of coupling an ultra-fast descriptor calculation engine to subset optimization capabilities. We also show that enumeration of properties for the entire virtual library may not only be unpractical but also wasteful. Successful design of focused and restrained subsets can be achieved while sampling only a small fraction of the virtual library. We also investigate the stability of the method and compare results obtained from simulated annealing (SA) and genetic algorithms (GA).

Development of non-natural flavanones as antimicrobial agents.

PubMed

Fowler, Zachary L; Shah, Karan; Panepinto, John C; Jacobs, Amy; Koffas, Mattheos A G

2011-01-01

With growing concerns over multidrug resistance microorganisms, particularly strains of bacteria and fungi, evolving to become resistant to the antimicrobial agents used against them, the identification of new molecular targets becomes paramount for novel treatment options. Recently, the use of new treatments containing multiple active ingredients has been shown to increase the effectiveness of existing molecules for some infections, often with these added compounds enabling the transport of a toxic molecule into the infecting species. Flavonoids are among the most abundant plant secondary metabolites and have been shown to have natural abilities as microbial deterrents and anti-infection agents in plants. Combining these ideas we first sought to investigate the potency of natural flavonoids in the presence of efflux pump inhibitors to limit Escherichia coli growth. Then we used the natural flavonoid scaffold to synthesize non-natural flavanone molecules and further evaluate their antimicrobial efficacy on Escherichia coli, Bacillus subtilis and the fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus. Of those screened, we identified the synthetic molecule 4-chloro-flavanone as the most potent antimicrobial compound with a MIC value of 70 µg/mL in E. coli when combined with the inhibitor Phe-Arg-ß-naphthylamide, and MICs of 30 µg/mL in S. cerevesiae and 30 µg/mL in C. neoformans when used alone. Through this study we have demonstrated that combinatorial synthesis of non-natural flavonones can identify novel antimicrobial agents with activity against bacteria and fungi but with minimal toxicity to human cells.

Development of Non-Natural Flavanones as Antimicrobial Agents

PubMed Central

Fowler, Zachary L.; Shah, Karan; Panepinto, John C.; Jacobs, Amy; Koffas, Mattheos A. G.

2011-01-01

With growing concerns over multidrug resistance microorganisms, particularly strains of bacteria and fungi, evolving to become resistant to the antimicrobial agents used against them, the identification of new molecular targets becomes paramount for novel treatment options. Recently, the use of new treatments containing multiple active ingredients has been shown to increase the effectiveness of existing molecules for some infections, often with these added compounds enabling the transport of a toxic molecule into the infecting species. Flavonoids are among the most abundant plant secondary metabolites and have been shown to have natural abilities as microbial deterrents and anti-infection agents in plants. Combining these ideas we first sought to investigate the potency of natural flavonoids in the presence of efflux pump inhibitors to limit Escherichia coli growth. Then we used the natural flavonoid scaffold to synthesize non-natural flavanone molecules and further evaluate their antimicrobial efficacy on Escherichia coli, Bacillus subtilis and the fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus. Of those screened, we identified the synthetic molecule 4-chloro-flavanone as the most potent antimicrobial compound with a MIC value of 70 µg/mL in E. coli when combined with the inhibitor Phe-Arg-ß-naphthylamide, and MICs of 30 µg/mL in S. cerevesiae and 30 µg/mL in C. neoformans when used alone. Through this study we have demonstrated that combinatorial synthesis of non-natural flavonones can identify novel antimicrobial agents with activity against bacteria and fungi but with minimal toxicity to human cells. PMID:22039419

Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening

PubMed Central

Harini, K.; Sowdhamini, Ramanathan

2015-01-01

Olfactory receptors (ORs) belong to the class A G-Protein Coupled Receptor superfamily of proteins. Unlike G-Protein Coupled Receptors, ORs exhibit a combinatorial response to odors/ligands. ORs display an affinity towards a range of odor molecules rather than binding to a specific set of ligands and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities. The diversity in odor recognition is linked to the highly variable transmembrane domains of these receptors. The purpose of this study is to decode the odor-olfactory receptor interactions using in silico docking studies. In this study, a ligand (odor molecules) dataset of 125 molecules was used to carry out in silico docking using the GLIDE docking tool (SCHRODINGER Inc Pvt LTD). Previous studies, with smaller datasets of ligands, have shown that orthologous olfactory receptors respond to similarly-tuned ligands, but are dramatically different in their efficacy and potency. Ligand docking results were applied on homologous pairs (with varying sequence identity) of ORs from human and mouse genomes and ligand binding residues and the ligand profile differed among such related olfactory receptor sequences. This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity. A ligand profile has been obtained for each of the 20 receptors in this analysis which will be useful for expression and mutation studies on these receptors. PMID:26221959

High-throughput identification and rational design of synergistic small-molecule pairs for combating and bypassing antibiotic resistance.

PubMed

Wambaugh, Morgan A; Shakya, Viplendra P S; Lewis, Adam J; Mulvey, Matthew A; Brown, Jessica C S

2017-06-01

Antibiotic-resistant infections kill approximately 23,000 people and cost $20,000,000,000 each year in the United States alone despite the widespread use of small-molecule antimicrobial combination therapy. Antibiotic combinations typically have an additive effect: the efficacy of the combination matches the sum of the efficacies of each antibiotic when used alone. Small molecules can also act synergistically when the efficacy of the combination is greater than the additive efficacy. However, synergistic combinations are rare and have been historically difficult to identify. High-throughput identification of synergistic pairs is limited by the scale of potential combinations: a modest collection of 1,000 small molecules involves 1 million pairwise combinations. Here, we describe a high-throughput method for rapid identification of synergistic small-molecule pairs, the overlap2 method (O2M). O2M extracts patterns from chemical-genetic datasets, which are created when a collection of mutants is grown in the presence of hundreds of different small molecules, producing a precise set of phenotypes induced by each small molecule across the mutant set. The identification of mutants that show the same phenotype when treated with known synergistic molecules allows us to pinpoint additional molecule combinations that also act synergistically. As a proof of concept, we focus on combinations with the antibiotics trimethoprim and sulfamethizole, which had been standard treatment against urinary tract infections until widespread resistance decreased efficacy. Using O2M, we screened a library of 2,000 small molecules and identified several that synergize with the antibiotic trimethoprim and/or sulfamethizole. The most potent of these synergistic interactions is with the antiviral drug azidothymidine (AZT). We then demonstrate that understanding the molecular mechanism underlying small-molecule synergistic interactions allows the rational design of additional combinations that bypass drug resistance. Trimethoprim and sulfamethizole are both folate biosynthesis inhibitors. We find that this activity disrupts nucleotide homeostasis, which blocks DNA replication in the presence of AZT. Building on these data, we show that other small molecules that disrupt nucleotide homeostasis through other mechanisms (hydroxyurea and floxuridine) also act synergistically with AZT. These novel combinations inhibit the growth and virulence of trimethoprim-resistant clinical Escherichia coli and Klebsiella pneumoniae isolates, suggesting that they may be able to be rapidly advanced into clinical use. In sum, we present a generalizable method to screen for novel synergistic combinations, to identify particular mechanisms resulting in synergy, and to use the mechanistic knowledge to rationally design new combinations that bypass drug resistance.

High-throughput identification and rational design of synergistic small-molecule pairs for combating and bypassing antibiotic resistance

PubMed Central

Lewis, Adam J.; Mulvey, Matthew A.

2017-01-01

Antibiotic-resistant infections kill approximately 23,000 people and cost $20,000,000,000 each year in the United States alone despite the widespread use of small-molecule antimicrobial combination therapy. Antibiotic combinations typically have an additive effect: the efficacy of the combination matches the sum of the efficacies of each antibiotic when used alone. Small molecules can also act synergistically when the efficacy of the combination is greater than the additive efficacy. However, synergistic combinations are rare and have been historically difficult to identify. High-throughput identification of synergistic pairs is limited by the scale of potential combinations: a modest collection of 1,000 small molecules involves 1 million pairwise combinations. Here, we describe a high-throughput method for rapid identification of synergistic small-molecule pairs, the overlap2 method (O2M). O2M extracts patterns from chemical-genetic datasets, which are created when a collection of mutants is grown in the presence of hundreds of different small molecules, producing a precise set of phenotypes induced by each small molecule across the mutant set. The identification of mutants that show the same phenotype when treated with known synergistic molecules allows us to pinpoint additional molecule combinations that also act synergistically. As a proof of concept, we focus on combinations with the antibiotics trimethoprim and sulfamethizole, which had been standard treatment against urinary tract infections until widespread resistance decreased efficacy. Using O2M, we screened a library of 2,000 small molecules and identified several that synergize with the antibiotic trimethoprim and/or sulfamethizole. The most potent of these synergistic interactions is with the antiviral drug azidothymidine (AZT). We then demonstrate that understanding the molecular mechanism underlying small-molecule synergistic interactions allows the rational design of additional combinations that bypass drug resistance. Trimethoprim and sulfamethizole are both folate biosynthesis inhibitors. We find that this activity disrupts nucleotide homeostasis, which blocks DNA replication in the presence of AZT. Building on these data, we show that other small molecules that disrupt nucleotide homeostasis through other mechanisms (hydroxyurea and floxuridine) also act synergistically with AZT. These novel combinations inhibit the growth and virulence of trimethoprim-resistant clinical Escherichia coli and Klebsiella pneumoniae isolates, suggesting that they may be able to be rapidly advanced into clinical use. In sum, we present a generalizable method to screen for novel synergistic combinations, to identify particular mechanisms resulting in synergy, and to use the mechanistic knowledge to rationally design new combinations that bypass drug resistance. PMID:28632788

X-ray characterization of solid small molecule organic materials

DOEpatents

Billinge, Simon; Shankland, Kenneth; Shankland, Norman; Florence, Alastair

2014-06-10

The present invention provides, inter alia, methods of characterizing a small molecule organic material, e.g., a drug or a drug product. This method includes subjecting the solid small molecule organic material to x-ray total scattering analysis at a short wavelength, collecting data generated thereby, and mathematically transforming the data to provide a refined set of data.

Group specific internal standard technology (GSIST) for simultaneous identification and quantification of small molecules

DOEpatents

Adamec, Jiri; Yang, Wen-Chu; Regnier, Fred E

2014-01-14

Reagents and methods are provided that permit simultaneous analysis of multiple diverse small molecule analytes present in a complex mixture. Samples are labeled with chemically identical but isotopically distince forms of the labeling reagent, and analyzed using mass spectrometry. A single reagent simultaneously derivatizes multiple small molecule analytes having different reactive functional groups.

Crossing borders to bind proteins--a new concept in protein recognition based on the conjugation of small organic molecules or short peptides to polypeptides from a designed set.

PubMed

Baltzer, Lars

2011-06-01

A new concept for protein recognition and binding is highlighted. The conjugation of small organic molecules or short peptides to polypeptides from a designed set provides binder molecules that bind proteins with high affinities, and with selectivities that are equal to those of antibodies. The small organic molecules or peptides need to bind the protein targets but only with modest affinities and selectivities, because conjugation to the polypeptides results in molecules with dramatically improved binder performance. The polypeptides are selected from a set of only sixteen sequences designed to bind, in principle, any protein. The small number of polypeptides used to prepare high-affinity binders contrasts sharply with the huge libraries used in binder technologies based on selection or immunization. Also, unlike antibodies and engineered proteins, the polypeptides have unordered three-dimensional structures and adapt to the proteins to which they bind. Binder molecules for the C-reactive protein, human carbonic anhydrase II, acetylcholine esterase, thymidine kinase 1, phosphorylated proteins, the D-dimer, and a number of antibodies are used as examples to demonstrate that affinities are achieved that are higher than those of the small molecules or peptides by as much as four orders of magnitude. Evaluation by pull-down experiments and ELISA-based tests in human serum show selectivities to be equal to those of antibodies. Small organic molecules and peptides are readily available from pools of endogenous ligands, enzyme substrates, inhibitors or products, from screened small molecule libraries, from phage display, and from mRNA display. The technology is an alternative to established binder concepts for applications in drug development, diagnostics, medical imaging, and protein separation.

Membrane Fusion Induced by Small Molecules and Ions

PubMed Central

Mondal Roy, Sutapa; Sarkar, Munna

2011-01-01

Membrane fusion is a key event in many biological processes. These processes are controlled by various fusogenic agents of which proteins and peptides from the principal group. The fusion process is characterized by three major steps, namely, inter membrane contact, lipid mixing forming the intermediate step, pore opening and finally mixing of inner contents of the cells/vesicles. These steps are governed by energy barriers, which need to be overcome to complete fusion. Structural reorganization of big molecules like proteins/peptides, supplies the required driving force to overcome the energy barrier of the different intermediate steps. Small molecules/ions do not share this advantage. Hence fusion induced by small molecules/ions is expected to be different from that induced by proteins/peptides. Although several reviews exist on membrane fusion, no recent review is devoted solely to small moleculs/ions induced membrane fusion. Here we intend to present, how a variety of small molecules/ions act as independent fusogens. The detailed mechanism of some are well understood but for many it is still an unanswered question. Clearer understanding of how a particular small molecule can control fusion will open up a vista to use these moleucles instead of proteins/peptides to induce fusion both in vivo and in vitro fusion processes. PMID:21660306

Perylene-Diimide Based Donor-Acceptor-Donor Type Small-Molecule Acceptors for Solution-Processable Organic Solar Cells

NASA Astrophysics Data System (ADS)

Ganesamoorthy, Ramasamy; Vijayaraghavan, Rajagopalan; Sakthivel, Pachagounder

2017-12-01

Development of nonfullerene acceptors plays an important role in the commercial availability of plastic solar cells. We report herein synthesis of bay-substituted donor-acceptor-donor (D-A-D)-type perylene diimide (PDI)-based small molecules (SM-1 to SM-4) by Suzuki coupling method and their use as acceptors in bulk heterojunction organic solar cells (BHJ-OSCs) with poly(3-hexylthiophene) (P3HT) polymer donor. We varied the number of electron-rich thiophene units and the solubilizing side chains and also evaluated the optical and electrochemical properties of the small molecules. The synthesized small molecules were confirmed by Fourier-transform infrared (FT-IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and high-resolution mass spectroscopy (HR-MS). The small molecules showed extensive and strong absorption in the ultraviolet-visible (UV-Vis) region up to 750 nm, with bandgap (E_{{g}}^{{opt}} ) reduced below <2 eV. The energy levels of small molecules SM-1 to SM-4 were suitable for use as electron-accepting materials. The small molecules showed good thermal stability up to 300°C. BHJ-OSCs with SM-1 and P3HT polymer donor showed maximum power conversion efficiency (PCE) of 0.19% with V oc of 0.30 V, J sc of 1.72 mA cm-2, and fill factor (FF) of 37%. The PCE decreased with the number of thiophene units. The PCE of SM-2 was lower than that of SM-1. This difference in PCE can be explained by the higher aggregation tendency of the bithiophene compared with the thiophene unit. Introduction of the solubilizing group in the bay position increased the aggregation property, leading to much lower PCE than for the small molecules without solubilizing group.

Hierarchical virtual screening approaches in small molecule drug discovery.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Combinatorial chemistry has matured in the last three decades: dedicated to Professor Árpád Furka on the occasion of his 80th birthday.

PubMed

Dibó, Gábor

2012-02-01

Combinatorial chemistry was introduced in the 1980s. It provided the possibility to produce new compounds in practically unlimited number. New strategies and technologies have also been developed that made it possible to screen very large number of compounds and to identify useful components in mixtures containing millions of different substances. This dramatically changed the drug discovery process and the way of thinking of synthetic chemists. In addition, combinatorial strategies became useful in areas such as pharmaceutical research, agrochemistry, catalyst design, and materials research. Prof. Árpád Furka is one of the pioneers of combinatorial chemistry.

Construction of a virtual combinatorial library using SMILES strings to discover potential structure-diverse PPAR modulators.

PubMed

Liao, Chenzhong; Liu, Bing; Shi, Leming; Zhou, Jiaju; Lu, Xian-Ping

2005-07-01

Based on the structural characters of PPAR modulators, a virtual combinatorial library containing 1226,625 compounds was constructed using SMILES strings. Selected ADME filters were employed to compel compounds having poor drug-like properties from this library. This library was converted to sdf and mol2 files by CONCORD 4.0, and was then docked to PPARgamma by DOCK 4.0 to identify new chemical entities that may be potential drug leads against type 2 diabetes and other metabolic diseases. The method to construct virtual combinatorial library using SMILES strings was further visualized by Visual Basic.net that can facilitate the needs of generating other type virtual combinatorial libraries.

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer's disease.

PubMed

Habchi, Johnny; Chia, Sean; Limbocker, Ryan; Mannini, Benedetta; Ahn, Minkoo; Perni, Michele; Hansson, Oskar; Arosio, Paolo; Kumita, Janet R; Challa, Pavan Kumar; Cohen, Samuel I A; Linse, Sara; Dobson, Christopher M; Knowles, Tuomas P J; Vendruscolo, Michele

2017-01-10

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer's disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery.

Synthesis of many different types of organic small molecules using one automated process.

PubMed

Li, Junqi; Ballmer, Steven G; Gillis, Eric P; Fujii, Seiko; Schmidt, Michael J; Palazzolo, Andrea M E; Lehmann, Jonathan W; Morehouse, Greg F; Burke, Martin D

2015-03-13

Small-molecule synthesis usually relies on procedures that are highly customized for each target. A broadly applicable automated process could greatly increase the accessibility of this class of compounds to enable investigations of their practical potential. Here we report the synthesis of 14 distinct classes of small molecules using the same fully automated process. This was achieved by strategically expanding the scope of a building block-based synthesis platform to include even C(sp3)-rich polycyclic natural product frameworks and discovering a catch-and-release chromatographic purification protocol applicable to all of the corresponding intermediates. With thousands of compatible building blocks already commercially available, many small molecules are now accessible with this platform. More broadly, these findings illuminate an actionable roadmap to a more general and automated approach for small-molecule synthesis. Copyright © 2015, American Association for the Advancement of Science.

Antibody-Mediated Small Molecule Detection Using Programmable DNA-Switches.

PubMed

Rossetti, Marianna; Ippodrino, Rudy; Marini, Bruna; Palleschi, Giuseppe; Porchetta, Alessandro

2018-06-13

The development of rapid, cost-effective, and single-step methods for the detection of small molecules is crucial for improving the quality and efficiency of many applications ranging from life science to environmental analysis. Unfortunately, current methodologies still require multiple complex, time-consuming washing and incubation steps, which limit their applicability. In this work we present a competitive DNA-based platform that makes use of both programmable DNA-switches and antibodies to detect small target molecules. The strategy exploits both the advantages of proximity-based methods and structure-switching DNA-probes. The platform is modular and versatile and it can potentially be applied for the detection of any small target molecule that can be conjugated to a nucleic acid sequence. Here the rational design of programmable DNA-switches is discussed, and the sensitive, rapid, and single-step detection of different environmentally relevant small target molecules is demonstrated.

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE PAGES

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.; ...

2016-08-30

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Large scale nanoparticle screening for small molecule analysis in laser desorption ionization mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yagnik, Gargey B.; Hansen, Rebecca L.; Korte, Andrew R.

Nanoparticles (NPs) have been suggested as efficient matrixes for small molecule profiling and imaging by laser-desorption ionization mass spectrometry (LDI-MS), but so far there has been no systematic study comparing different NPs in the analysis of various classes of small molecules. Here, we present a large scale screening of 13 NPs for the analysis of two dozen small metabolite molecules. Many NPs showed much higher LDI efficiency than organic matrixes in positive mode and some NPs showed comparable efficiencies for selected analytes in negative mode. Our results suggest that a thermally driven desorption process is a key factor for metalmore » oxide NPs, but chemical interactions are also very important, especially for other NPs. Furthermore, the screening results provide a useful guideline for the selection of NPs in the LDI-MS analysis of small molecules.« less

Small Molecule Signaling Agents: The Integrated Chemistry and Biochemistry of Nitrogen Oxides, Oxides of Carbon, Dioxygen, Hydrogen Sulfide, and Their Derived Species

PubMed Central

Fukuto, Jon M.; Carrington, Samantha J.; Tantillo, Dean J.; Harrison, Jason G.; Ignarro, Louis J.; Freeman, Bruce A.; Chen, Andrew; Wink, David A.

2014-01-01

Several small molecule species formally known primarily as toxic gases have, over the past 20 years, been shown to be endogenously generated signaling molecules. The biological signaling associated with the small molecules NO, CO, H2S (and the nonendogenously generated O2), and their derived species have become a topic of extreme interest. It has become increasingly clear that these small molecule signaling agents form an integrated signaling web that affects/regulates numerous physiological processes. The chemical interactions between these species and each other or biological targets is an important factor in their roles as signaling agents. Thus, a fundamental understanding of the chemistry of these molecules is essential to understanding their biological/physiological utility. This review focuses on this chemistry and attempts to establish the chemical basis for their signaling functions. PMID:22263838

Fluorination-enabled optimal morphology leads to over 11% efficiency for inverted small-molecule organic solar cells

PubMed Central

Deng, Dan; Zhang, Yajie; Zhang, Jianqi; Wang, Zaiyu; Zhu, Lingyun; Fang, Jin; Xia, Benzheng; Wang, Zhen; Lu, Kun; Ma, Wei; Wei, Zhixiang

2016-01-01

Solution-processable small molecules for organic solar cells have attracted intense attention for their advantages of definite molecular structures compared with their polymer counterparts. However, the device efficiencies based on small molecules are still lower than those of polymers, especially for inverted devices, the highest efficiency of which is <9%. Here we report three novel solution-processable small molecules, which contain π-bridges with gradient-decreased electron density and end acceptors substituted with various fluorine atoms (0F, 1F and 2F, respectively). Fluorination leads to an optimal active layer morphology, including an enhanced domain purity, the formation of hierarchical domain size and a directional vertical phase gradation. The optimal morphology balances charge separation and transfer, and facilitates charge collection. As a consequence, fluorinated molecules exhibit excellent inverted device performance, and an average power conversion efficiency of 11.08% is achieved for a two-fluorine atom substituted molecule. PMID:27991486

[Effect of annealing temperature on the crystallization and spectroscopic response of a small-molecule semiconductor doped in polymer film].

PubMed

Yin, Ming; Zhang, Xin-Ping; Liu, Hong-Mei

2012-11-01

The crystallization properties of the perylene (EPPTC) molecules doped in the solid film of the derivative of polyfluorene (F8BT) at different annealing temperatures, as well as the consequently induced spectroscopic response of the exciplex emission in the heterojunction structures, were studied in the present paper. Experimental results showed that the phase separation between the small and the polymer molecules in the blend film is enhanced with increasing the annealing temperature, which leads to the crystallization of the EPPTC molecules due to the strong pi-pi stacking. The size of the crystal phase increases with increasing the annealing temperature. However, this process weakens the mechanisms of the heterojunction configuration, thus, the total interfacial area between the small and the polymer molecules and the amount of exciplex are reduced significantly in the blend film. Meanwhile, the energy transfer from the polymer to the small molecules is also reduced. As a result, the emission from the exciplex becomes weaker with increasing the annealing temperature, whereas the stronger emission from the polymer molecules and from the crystal phase of the small molecules can be observed. These experimental results are very important for understanding and tailoring the organic heterojunction structures. Furthermore, this provides photophysics for improving the performance of photovoltaic or solar cell devices.

Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

PubMed Central

Tabchy, Adel; Eltonsy, Nevine; Housman, David E.; Mills, Gordon B.

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance. PMID:23577104

Systematic identification of combinatorial drivers and targets in cancer cell lines.

PubMed

Tabchy, Adel; Eltonsy, Nevine; Housman, David E; Mills, Gordon B

2013-01-01

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.

An evaluation of methods for estimating the number of local optima in combinatorial optimization problems.

PubMed

Hernando, Leticia; Mendiburu, Alexander; Lozano, Jose A

2013-01-01

The solution of many combinatorial optimization problems is carried out by metaheuristics, which generally make use of local search algorithms. These algorithms use some kind of neighborhood structure over the search space. The performance of the algorithms strongly depends on the properties that the neighborhood imposes on the search space. One of these properties is the number of local optima. Given an instance of a combinatorial optimization problem and a neighborhood, the estimation of the number of local optima can help not only to measure the complexity of the instance, but also to choose the most convenient neighborhood to solve it. In this paper we review and evaluate several methods to estimate the number of local optima in combinatorial optimization problems. The methods reviewed not only come from the combinatorial optimization literature, but also from the statistical literature. A thorough evaluation in synthetic as well as real problems is given. We conclude by providing recommendations of methods for several scenarios.

Combinatorial materials approach to accelerate materials discovery for transportation (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tong, Wei

2017-04-01

Combinatorial material research offers fast and efficient solutions to identify promising and advanced materials. It has revolutionized the pharmaceutical industry and now is being applied to accelerate the discovery of other new compounds, e.g. superconductors, luminescent materials, catalysts etc. Differing from the traditional trial-and-error process, this approach allows for the synthesis of a large number of compositionally diverse compounds by varying the combinations of the components and adjusting the ratios. It largely reduces the cost of single-sample synthesis/characterization, along with the turnaround time in the material discovery process, therefore, could dramatically change the existing paradigm for discovering and commercializing new materials. This talk outlines the use of combinatorial materials approach in the material discovery in transportation sector. It covers the general introduction to the combinatorial material concept, state of art for its application in energy-related research. At the end, LBNL capabilities in combinatorial materials synthesis and high throughput characterization that are applicable for material discovery research will be highlighted.

Peptide ligands targeting integrin alpha3beta1 in non-small cell lung cancer.

PubMed

Lau, Derick; Guo, Linlang; Liu, Ruiwu; Marik, Jan; Lam, Kit

2006-06-01

Lung cancer is one of the most common cancers and is the leading cause of cancer death. We wish to identify peptide ligands for unique cell surface receptors of non-small lung cancer with the hope of developing these ligands as diagnostic and therapeutic agents. Using the method of 'one-bead one-peptide' combinatorial chemistry, a library of random cyclic octapeptides was synthesized on polystyrene beads. This library was used to screen for peptides that promoted attachment of lung adenocarcinoma cells employing a 'cell-growth-on-bead' assay. Consensus peptide sequences of cNGXGXXc were identified. These peptides promoted cell adhesion by targeting integrin alpha3beta1 over-expressed in non-small lung cancer cells. These peptide beads can be applied to capture cancer cells in malignant pleural fluid for purpose of diagnosis of lung cancer.

Discovery of the leinamycin family of natural products by mining actinobacterial genomes

PubMed Central

Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen

2017-01-01

Nature’s ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF–SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF–SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm-type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature’s rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature’s biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity. PMID:29229819

Discovery of the leinamycin family of natural products by mining actinobacterial genomes.

PubMed

Pan, Guohui; Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Yang, Dong; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen; Shen, Ben

2017-12-26

Nature's ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF-SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF-SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm -type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature's rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature's biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

Hippocampal and cortical neuronal growth mediated by the small molecule natural product clovanemagnolol.

PubMed

Khaing, Zin; Kang, Danby; Camelio, Andrew M; Schmidt, Christine E; Siegel, Dionicio

2011-08-15

The use of small molecule surrogates of growth factors that directly or indirectly promote growth represents an attractive approach to regenerative medicine. With synthetic access to clovanemagnolol, a small molecule initially isolated from the bark of the Bigleaf Magnolia tree, we have examined the small molecule's ability to promote growth of embryonic hippocampal and cortical neurons in serum-free medium. Comparisons with magnolol, a known promoter of growth, reveals that clovanmagnolol is a potent neurotrophic agent, promoting neuronal growth at concentrations of 10 nM. In addition, both clovanemagnolol and magnolol promote growth through a biphasic dose response. Copyright © 2011 Elsevier Ltd. All rights reserved.

Second-generation DNA-templated macrocycle libraries for the discovery of bioactive small molecules.

PubMed

Usanov, Dmitry L; Chan, Alix I; Maianti, Juan Pablo; Liu, David R

2018-07-01

DNA-encoded libraries have emerged as a widely used resource for the discovery of bioactive small molecules, and offer substantial advantages compared with conventional small-molecule libraries. Here, we have developed and streamlined multiple fundamental aspects of DNA-encoded and DNA-templated library synthesis methodology, including computational identification and experimental validation of a 20 × 20 × 20 × 80 set of orthogonal codons, chemical and computational tools for enhancing the structural diversity and drug-likeness of library members, a highly efficient polymerase-mediated template library assembly strategy, and library isolation and purification methods. We have integrated these improved methods to produce a second-generation DNA-templated library of 256,000 small-molecule macrocycles with improved drug-like physical properties. In vitro selection of this library for insulin-degrading enzyme affinity resulted in novel insulin-degrading enzyme inhibitors, including one of unusual potency and novel macrocycle stereochemistry (IC 50  = 40 nM). Collectively, these developments enable DNA-templated small-molecule libraries to serve as more powerful, accessible, streamlined and cost-effective tools for bioactive small-molecule discovery.

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy

PubMed Central

Adams, Christopher M.; Ebert, Scott M.; Dyle, Michael C.

2017-01-01

Purpose of review Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Recent findings Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Summary Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function. PMID:25807353

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy.

PubMed

Adams, Christopher M; Ebert, Scott M; Dyle, Michael C

2015-05-01

Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function.

Combinatorial pretreatment and fermentation optimization enabled a record yield on lignin bioconversion.

PubMed

Liu, Zhi-Hua; Xie, Shangxian; Lin, Furong; Jin, Mingjie; Yuan, Joshua S

2018-01-01

Lignin valorization has recently been considered to be an essential process for sustainable and cost-effective biorefineries. Lignin represents a potential new feedstock for value-added products. Oleaginous bacteria such as Rhodococcus opacus can produce intracellular lipids from biodegradation of aromatic substrates. These lipids can be used for biofuel production, which can potentially replace petroleum-derived chemicals. However, the low reactivity of lignin produced from pretreatment and the underdeveloped fermentation technology hindered lignin bioconversion to lipids. In this study, combinatorial pretreatment with an optimized fermentation strategy was evaluated to improve lignin valorization into lipids using R. opacus PD630. As opposed to single pretreatment, combinatorial pretreatment produced a 12.8-75.6% higher lipid concentration in fermentation using lignin as the carbon source. Gas chromatography-mass spectrometry analysis showed that combinatorial pretreatment released more aromatic monomers, which could be more readily utilized by lignin-degrading strains. Three detoxification strategies were used to remove potential inhibitors produced from pretreatment. After heating detoxification of the lignin stream, the lipid concentration further increased by 2.9-9.7%. Different fermentation strategies were evaluated in scale-up lipid fermentation using a 2.0-l fermenter. With laccase treatment of the lignin stream produced from combinatorial pretreatment, the highest cell dry weight and lipid concentration were 10.1 and 1.83 g/l, respectively, in fed-batch fermentation, with a total soluble substrate concentration of 40 g/l. The improvement of the lipid fermentation performance may have resulted from lignin depolymerization by the combinatorial pretreatment and laccase treatment, reduced inhibition effects by fed-batch fermentation, adequate oxygen supply, and an accurate pH control in the fermenter. Overall, these results demonstrate that combinatorial pretreatment, together with fermentation optimization, favorably improves lipid production using lignin as the carbon source. Combinatorial pretreatment integrated with fed-batch fermentation was an effective strategy to improve the bioconversion of lignin into lipids, thus facilitating lignin valorization in biorefineries.

Mass amplifying probe for sensitive fluorescence anisotropy detection of small molecules in complex biological samples.

PubMed

Cui, Liang; Zou, Yuan; Lin, Ninghang; Zhu, Zhi; Jenkins, Gareth; Yang, Chaoyong James

2012-07-03

Fluorescence anisotropy (FA) is a reliable and excellent choice for fluorescence sensing. One of the key factors influencing the FA value for any molecule is the molar mass of the molecule being measured. As a result, the FA method with functional nucleic acid aptamers has been limited to macromolecules such as proteins and is generally not applicable for the analysis of small molecules because their molecular masses are relatively too small to produce observable FA value changes. We report here a molecular mass amplifying strategy to construct anisotropy aptamer probes for small molecules. The probe is designed in such a way that only when a target molecule binds to the probe does it activate its binding ability to an anisotropy amplifier (a high molecular mass molecule such as protein), thus significantly increasing the molecular mass and FA value of the probe/target complex. Specifically, a mass amplifying probe (MAP) consists of a targeting aptamer domain against a target molecule and molecular mass amplifying aptamer domain for the amplifier protein. The probe is initially rendered inactive by a small blocking strand partially complementary to both target aptamer and amplifier protein aptamer so that the mass amplifying aptamer domain would not bind to the amplifier protein unless the probe has been activated by the target. In this way, we prepared two probes that constitute a target (ATP and cocaine respectively) aptamer, a thrombin (as the mass amplifier) aptamer, and a fluorophore. Both probes worked well against their corresponding small molecule targets, and the detection limits for ATP and cocaine were 0.5 μM and 0.8 μM, respectively. More importantly, because FA is less affected by environmental interferences, ATP in cell media and cocaine in urine were directly detected without any tedious sample pretreatment. Our results established that our molecular mass amplifying strategy can be used to design aptamer probes for rapid, sensitive, and selective detection of small molecules by means of FA in complex biological samples.

Single-molecule techniques in biophysics: a review of the progress in methods and applications.

PubMed

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J M; Leake, Mark C

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Single-molecule techniques in biophysics: a review of the progress in methods and applications

NASA Astrophysics Data System (ADS)

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J. M.; Leake, Mark C.

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in ‘force spectroscopy’ techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Heightening energetic stress selectively targets LKB1-deficient non-small cell lung cancers

PubMed Central

Momcilovic, Milica; McMickle, Robert; Abt, Evan; Seki, Atsuko; Simko, Sarah A.; Magyar, Clara; Stout, David B.; Fishbein, Michael C.; Walser, Tonya C.; Dubinett, Steven M.; Shackelford, David B.

2015-01-01

Inactivation of the LKB1 tumor suppressor is a frequent event in non-small cell lung carcinoma (NSCLC) leading to the activation of mammalian target of rapamycin complex 1 (mTORC1) and sensitivity to the metabolic stress inducer phenformin. In this study, we explored the combinatorial use of phenformin with the mTOR catalytic kinase inhibitor MLN0128 as a treatment strategy for NSCLC bearing co-mutations in the LKB1 and KRAS genes. NSCLC is a genetically and pathologically heterogeneous disease, giving rise to lung tumors of varying histologies that include adenocarcinomas (ADCs) and squamous cell carcinomas (SCCs). We demonstrate that phenformin in combination with MLN0128 induced a significant therapeutic response in KRAS/LKB1 mutant human cell lines and genetically engineered mouse models of NSCLC that develop both ADCs and SCCs. Specifically, we found that KRAS/LKB1 mutant lung ADCs responded strongly to phenformin + MLN0128 treatment, but the response of SCCs to single or combined treatment with MLN0128 was more attenuated due to acquired resistance to mTOR inhibition through modulation of the AKT-GSK signaling axis. Combinatorial use of the mTOR inhibitor and AKT inhibitor MK2206 robustly inhibited the growth and viability of squamous lung tumors thus providing an effective strategy to overcome resistance. Taken together, our findings define new personalized therapeutic strategies that may be rapidly translated into clinical use for the treatment of KRAS/LKB1 mutant adenocarcinomas and squamous cell tumors. PMID:26574479

Heightening Energetic Stress Selectively Targets LKB1-Deficient Non-Small Cell Lung Cancers.

PubMed

Momcilovic, Milica; McMickle, Robert; Abt, Evan; Seki, Atsuko; Simko, Sarah A; Magyar, Clara; Stout, David B; Fishbein, Michael C; Walser, Tonya C; Dubinett, Steven M; Shackelford, David B

2015-11-15

Inactivation of the LKB1 tumor suppressor is a frequent event in non-small cell lung carcinoma (NSCLC) leading to the activation of mTOR complex 1 (mTORC1) and sensitivity to the metabolic stress inducer phenformin. In this study, we explored the combinatorial use of phenformin with the mTOR catalytic kinase inhibitor MLN0128 as a treatment strategy for NSCLC bearing comutations in the LKB1 and KRAS genes. NSCLC is a genetically and pathologically heterogeneous disease, giving rise to lung tumors of varying histologies that include adenocarcinomas and squamous cell carcinomas (SCC). We demonstrate that phenformin in combination with MLN0128 induced a significant therapeutic response in KRAS/LKB1-mutant human cell lines and genetically engineered mouse models of NSCLC that develop both adenocarcinomas and SCCs. Specifically, we found that KRAS/LKB1-mutant lung adenocarcinomas responded strongly to phenformin + MLN0128 treatment, but the response of SCCs to single or combined treatment with MLN0128 was more attenuated due to acquired resistance to mTOR inhibition through modulation of the AKT-GSK signaling axis. Combinatorial use of the mTOR inhibitor and AKT inhibitor MK2206 robustly inhibited the growth and viability of squamous lung tumors, thus providing an effective strategy to overcome resistance. Taken together, our findings define new personalized therapeutic strategies that may be rapidly translated into clinical use for the treatment of KRAS/LKB1-mutant adenocarcinomas and squamous cell tumors. ©2015 American Association for Cancer Research.

Influence of thermocleavable functionality on organic field-effect transistor performance of small molecules

NASA Astrophysics Data System (ADS)

Mahale, Rajashree Y.; Dharmapurikar, Satej S.; Chini, Mrinmoy Kumar; Venugopalan, Vijay

2017-06-01

Diketopyrrolopyrrole based donor-acceptor-donor conjugated small molecules using ethylene dioxythiophene as a donor was synthesized. Electron deficient diketopyrrolopyrrole unit was substituted with thermocleavable (tert-butyl acetate) side chains. The thermal treatment of the molecules at 160 °C eliminated the tert-butyl ester group results in the formation of corresponding acid. Optical and theoretical studies revealed that the molecules adopted a change in molecular arrangement after thermolysis. The conjugated small molecules possessed p-channel charge transport characteristics in organic field effect transistors. The charge carrier mobility was increased after thermolysis of tert-butyl ester group to 5.07 × 10-5 cm2/V s.

Discovery of Small Molecules that Inhibit the Disordered Protein, p27Kip1

PubMed Central

Iconaru, Luigi I.; Ban, David; Bharatham, Kavitha; Ramanathan, Arvind; Zhang, Weixing; Shelat, Anang A.; Zuo, Jian; Kriwacki, Richard W.

2015-01-01

Disordered proteins are highly prevalent in biological systems, they control myriad signaling and regulatory processes, and their levels and/or cellular localization are often altered in human disease. In contrast to folded proteins, disordered proteins, due to conformational heterogeneity and dynamics, are not considered viable drug targets. We challenged this paradigm by identifying through NMR-based screening small molecules that bound specifically, albeit weakly, to the disordered cell cycle regulator, p27Kip1 (p27). Two groups of molecules bound to sites created by transient clusters of aromatic residues within p27. Conserved chemical features within these two groups of small molecules exhibited complementarity to their binding sites within p27, establishing structure-activity relationships for small molecule:disordered protein interactions. Finally, one compound counteracted the Cdk2/cyclin A inhibitory function of p27 in vitro, providing proof-of-principle that small molecules can inhibit the function of a disordered protein (p27) through sequestration in a conformation incapable of folding and binding to a natural regulatory target (Cdk2/cyclin A). PMID:26507530

Discovery of Small Molecules that Inhibit the Disordered Protein, p27 Kip1

DOE PAGES

Iconaru, Luigi I.; Ban, David; Bharatham, Kavitha; ...

2015-10-28

In disordered proteins we see that they are highly prevalent in biological systems. They control myriad signaling and regulatory processes, and their levels and/or cellular localization are often altered in human disease. In contrast to folded proteins, disordered proteins, due to conformational heterogeneity and dynamics, are not considered viable drug targets. We challenged this paradigm by identifying through NMR-based screening small molecules that bound specifically, albeit weakly, to the disordered cell cycle regulator, p27 Kip1 (p27). Moreover, two groups of molecules bound to sites created by transient clusters of aromatic residues within p27. Conserved chemical features within these two groupsmore » of small molecules exhibited complementarity to their binding sites within p27, establishing structure-activity relationships for small molecule: disordered protein interactions. Finally, one compound counteracted the Cdk2/cyclin A inhibitory function of p27 in vitro, providing proof-of- principle that small molecules can inhibit the function of a disordered protein (p27) through sequestration in a conformation incapable of folding and binding to a natural regulatory target (Cdk2/cyclin A).« less

Strategy to discover diverse optimal molecules in the small molecule universe.

PubMed

Rupakheti, Chetan; Virshup, Aaron; Yang, Weitao; Beratan, David N

2015-03-23

The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework ( Virshup et al. J. Am. Chem. Soc. 2013 , 135 , 7296 - 7303 ) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 10(5) molecules.

Strategy To Discover Diverse Optimal Molecules in the Small Molecule Universe

PubMed Central

2015-01-01

The small molecule universe (SMU) is defined as a set of over 1060 synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework (Virshup et al. J. Am. Chem. Soc.2013, 135, 7296–730323548177) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 105 molecules. PMID:25594586

An Indexed Combinatorial Library: The Synthesis and Testing of Insect Repellents

NASA Astrophysics Data System (ADS)

Miles, William H.; Gelato, Kathy A.; Pompizzi, Kristen M.; Scarbinsky, Aislinn M.; Albrecht, Brian K.; Reynolds, Elaine R.

2001-04-01

An indexed combinatorial library of amides was prepared by the reaction of amines and acid chlorides. A simple test for insect repellency using fruit flies (Drosophila melanogaster) allowed the determination of the most repellent sublibraries. The student-generated data were collected and analyzed to determine the most active amide(s) in the library. This experiment illustrates the fundamentals of combinatorial chemistry, a field that has undergone explosive growth in the last decade.

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Stein, Martin; Jackson, David; Eils, Roland

2009-12-01

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.

Small Molecule Protection of Bone Marrow Hematopoietic Stem Cells

DTIC Science & Technology

2015-10-01

several recently identified small molecules can protect hematopoietic stem cells (HSCs) from damage or killing by endogenous aldehydes . Proof-of-concept...anemia bone marrow failure CD34+ hematopoietic stem cells aldehydes formaldehyde DNA damage DNA base adduct DNA-protein crosslink mass...below. Revised Specific Aim 1: Small molecule protection of human cells from aldehyde - induced killing (in vitro studies - no mice or human subjects

High-throughput screening approaches and combinatorial development of biomaterials using microfluidics.

PubMed

Barata, David; van Blitterswijk, Clemens; Habibovic, Pamela

2016-04-01

From the first microfluidic devices used for analysis of single metabolic by-products to highly complex multicompartmental co-culture organ-on-chip platforms, efforts of many multidisciplinary teams around the world have been invested in overcoming the limitations of conventional research methods in the biomedical field. Close spatial and temporal control over fluids and physical parameters, integration of sensors for direct read-out as well as the possibility to increase throughput of screening through parallelization, multiplexing and automation are some of the advantages of microfluidic over conventional, 2D tissue culture in vitro systems. Moreover, small volumes and relatively small cell numbers used in experimental set-ups involving microfluidics, can potentially decrease research cost. On the other hand, these small volumes and numbers of cells also mean that many of the conventional molecular biology or biochemistry assays cannot be directly applied to experiments that are performed in microfluidic platforms. Development of different types of assays and evidence that such assays are indeed a suitable alternative to conventional ones is a step that needs to be taken in order to have microfluidics-based platforms fully adopted in biomedical research. In this review, rather than providing a comprehensive overview of the literature on microfluidics, we aim to discuss developments in the field of microfluidics that can aid advancement of biomedical research, with emphasis on the field of biomaterials. Three important topics will be discussed, being: screening, in particular high-throughput and combinatorial screening; mimicking of natural microenvironment ranging from 3D hydrogel-based cellular niches to organ-on-chip devices; and production of biomaterials with closely controlled properties. While important technical aspects of various platforms will be discussed, the focus is mainly on their applications, including the state-of-the-art, future perspectives and challenges. Microfluidics, being a technology characterized by the engineered manipulation of fluids at the submillimeter scale, offers some interesting tools that can advance biomedical research and development. Screening platforms based on microfluidic technologies that allow high-throughput and combinatorial screening may lead to breakthrough discoveries not only in basic research but also relevant to clinical application. This is further strengthened by the fact that reliability of such screens may improve, since microfluidic systems allow close mimicking of physiological conditions. Finally, microfluidic systems are also very promising as micro factories of a new generation of natural or synthetic biomaterials and constructs, with finely controlled properties. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL).

PubMed

Melagraki, Georgia; Ntougkos, Evangelos; Rinotas, Vagelis; Papaneophytou, Christos; Leonis, Georgios; Mavromoustakos, Thomas; Kontopidis, George; Douni, Eleni; Afantitis, Antreas; Kollias, George

2017-04-01

We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure-based with ligand-based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.

A dual-targeting PDGFRbeta/VEGF-A molecule assembled from stable antibody fragments demonstrates anti-angiogenic activity in vitro and in vivo.

PubMed

Mabry, Robert; Gilbertson, Debra G; Frank, Amanda; Vu, Tuyen; Ardourel, Dan; Ostrander, Craig; Stevens, Brenda; Julien, Susan; Franke, Secil; Meengs, Brent; Brody, Jennifer; Presnell, Scott; Hamacher, Nels B; Lantry, Megan; Wolf, Anitra; Bukowski, Tom; Rosler, Robert; Yen, Cindy; Anderson-Haley, Monica; Brasel, Kenneth; Pan, Qi; Franklin, Hank; Thompson, Penny; Dodds, Mike; Underwood, Sara; Peterson, Scott; Sivakumar, Pallavur V; Snavely, Mark

2010-01-01

Targeting angiogenesis is a promising approach to the treatment of solid tumors and age-related macular degeneration (AMD). Inhibition of vascularization has been validated by the successful marketing of monoclonal antibodies (mAbs) that target specific growth factors or their receptors, but there is considerable room for improvement in existing therapies. Combination of mAbs targeting both the VEGF and PDGF pathways has the potential to increase the efficacy of anti-angiogenic therapy without the accompanying toxicities of tyrosine kinase inhibitors and the inability to combine efficiently with traditional chemotherapeutics. However, development costs and regulatory issues have limited the use of combinatorial approaches for the generation of more efficacious treatments. The concept of mediating disease pathology by targeting two antigens with one therapeutic was proposed over two decades ago. While mAbs are particularly suitable candidates for a dual-targeting approach, engineering bispecificity into one molecule can be difficult due to issues with expression and stability, which play a significant role in manufacturability. Here, we address these issues upstream in the process of developing a bispecific antibody (bsAb). Single-chain antibody fragments (scFvs) targeting PDGFRbeta and VEGF-A were selected for superior stability. The scFvs were fused to both termini of human Fc to generate a bispecific, tetravalent molecule. The resulting molecule displays potent activity, binds both targets simultaneously, and is stable in serum. The assembly of a bsAb using stable monomeric units allowed development of an anti-PDGFRB/VEGF-A antibody capable of attenuating angiogenesis through two distinct pathways and represents an efficient method for rapid engineering of dual-targeting molecules.

Beyond directed evolution - semi-rational protein engineering and design

PubMed Central

Lutz, Stefan

2010-01-01

Over the last two decades, directed evolution has transformed the field of protein engineering. The advances in understanding protein structure and function, in no insignificant part a result of directed evolution studies, are increasingly empowering scientists and engineers to device more effective methods for manipulating and tailoring biocatalysts. Abandoning large combinatorial libraries, the focus has shifted to small, functionally-rich libraries and rational design. A critical component to the success of these emerging engineering strategies are computational tools for the evaluation of protein sequence datasets and the analysis of conformational variations of amino acids in proteins. Highlighting the opportunities and limitations of such approaches, this review focuses on recent engineering and design examples that require screening or selection of small libraries. PMID:20869867

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

Free-standing few-layered graphene oxide films: selective, steady and lasting permeation of organic molecules with adjustable speeds

NASA Astrophysics Data System (ADS)

Huang, Tao; An, Qi; Luan, Xinglong; Zhang, Qian; Zhang, Yihe

2016-01-01

A variety of small molecules with diameters around 1 nm possess a range of functions, such as antibiotic, antimicrobic, anticoagulant, pesticidal and chemotherapy effects, making these molecules especially useful in various applications ranging from medical treatment to environmental microbiological control. However, the long-term steady delivery (release or permeation) of these small molecules with adjustable and controllable speeds has remained an especially challenging task. In this study, we prepared covalently cross-linked free-standing few-layered GO films using a layer-by-layer technique in combination with photochemical cross-linkages, and achieved a controlled release of positively charged, negatively charged, and zwitterionic small molecules with adjustable and controllable speeds. The steady delivery of the small molecule lasted up to 9 days. Other functionalities, such as graphene-enhanced Raman spectra and electrochemical properties that could also be integrated or employed in delivery systems, were also studied for our films. We expect the special molecular delivery properties of our films to lead to new possibilities in drug/fertilizer delivery and environmental microbiological control applications.A variety of small molecules with diameters around 1 nm possess a range of functions, such as antibiotic, antimicrobic, anticoagulant, pesticidal and chemotherapy effects, making these molecules especially useful in various applications ranging from medical treatment to environmental microbiological control. However, the long-term steady delivery (release or permeation) of these small molecules with adjustable and controllable speeds has remained an especially challenging task. In this study, we prepared covalently cross-linked free-standing few-layered GO films using a layer-by-layer technique in combination with photochemical cross-linkages, and achieved a controlled release of positively charged, negatively charged, and zwitterionic small molecules with adjustable and controllable speeds. The steady delivery of the small molecule lasted up to 9 days. Other functionalities, such as graphene-enhanced Raman spectra and electrochemical properties that could also be integrated or employed in delivery systems, were also studied for our films. We expect the special molecular delivery properties of our films to lead to new possibilities in drug/fertilizer delivery and environmental microbiological control applications. Electronic supplementary information (ESI) available: AFM images of GO and GO films, UV-vis spectra of delayed release, and permeation fidelities. See DOI: 10.1039/c5nr08129g

A Novel Protocol for Directed Differentiation of C9orf72-Associated Human Induced Pluripotent Stem Cells Into Contractile Skeletal Myotubes.

PubMed

Swartz, Elliot W; Baek, Jaeyun; Pribadi, Mochtar; Wojta, Kevin J; Almeida, Sandra; Karydas, Anna; Gao, Fen-Biao; Miller, Bruce L; Coppola, Giovanni

2016-11-01

: Induced pluripotent stem cells (iPSCs) offer an unlimited resource of cells to be used for the study of underlying molecular biology of disease, therapeutic drug screening, and transplant-based regenerative medicine. However, methods for the directed differentiation of skeletal muscle for these purposes remain scarce and incomplete. Here, we present a novel, small molecule-based protocol for the generation of multinucleated skeletal myotubes using eight independent iPSC lines. Through combinatorial inhibition of phosphoinositide 3-kinase (PI3K) and glycogen synthase kinase 3β (GSK3β) with addition of bone morphogenic protein 4 (BMP4) and fibroblast growth factor 2 (FGF2), we report up to 64% conversion of iPSCs into the myogenic program by day 36 as indicated by MYOG + cell populations. These cells began to exhibit spontaneous contractions as early as 34 days in vitro in the presence of a serum-free medium formulation. We used this protocol to obtain iPSC-derived muscle cells from frontotemporal dementia (FTD) patients harboring C9orf72 hexanucleotide repeat expansions (rGGGGCC), sporadic FTD, and unaffected controls. iPSCs derived from rGGGGCC carriers contained RNA foci but did not vary in differentiation efficiency when compared to unaffected controls nor display mislocalized TDP-43 after as many as 120 days in vitro. This study presents a rapid, efficient, and transgene-free method for generating multinucleated skeletal myotubes from iPSCs and a resource for further modeling the role of skeletal muscle in amyotrophic lateral sclerosis and other motor neuron diseases. Protocols to produce skeletal myotubes for disease modeling or therapy are scarce and incomplete. The present study efficiently generates functional skeletal myotubes from human induced pluripotent stem cells using a small molecule-based approach. Using this strategy, terminal myogenic induction of up to 64% in 36 days and spontaneously contractile myotubes within 34 days were achieved. Myotubes derived from patients carrying the C9orf72 repeat expansion show no change in differentiation efficiency and normal TDP-43 localization after as many as 120 days in vitro when compared to unaffected controls. This study provides an efficient, novel protocol for the generation of skeletal myotubes from human induced pluripotent stem cells that may serve as a valuable tool in drug discovery and modeling of musculoskeletal and neuromuscular diseases. ©AlphaMed Press.

Combinatorial Dyson-Schwinger equations and inductive data types

NASA Astrophysics Data System (ADS)

Kock, Joachim

2016-06-01

The goal of this contribution is to explain the analogy between combinatorial Dyson-Schwinger equations and inductive data types to a readership of mathematical physicists. The connection relies on an interpretation of combinatorial Dyson-Schwinger equations as fixpoint equations for polynomial functors (established elsewhere by the author, and summarised here), combined with the now-classical fact that polynomial functors provide semantics for inductive types. The paper is expository, and comprises also a brief introduction to type theory.

Combinatorial stresses kill pathogenic Candida species

PubMed Central

Kaloriti, Despoina; Tillmann, Anna; Cook, Emily; Jacobsen, Mette; You, Tao; Lenardon, Megan; Ames, Lauren; Barahona, Mauricio; Chandrasekaran, Komelapriya; Coghill, George; Goodman, Daniel; Gow, Neil A. R.; Grebogi, Celso; Ho, Hsueh-Lui; Ingram, Piers; McDonagh, Andrew; De Moura, Alessandro P. S.; Pang, Wei; Puttnam, Melanie; Radmaneshfar, Elahe; Romano, Maria Carmen; Silk, Daniel; Stark, Jaroslav; Stumpf, Michael; Thiel, Marco; Thorne, Thomas; Usher, Jane; Yin, Zhikang; Haynes, Ken; Brown, Alistair J. P.

2012-01-01

Pathogenic microbes exist in dynamic niches and have evolved robust adaptive responses to promote survival in their hosts. The major fungal pathogens of humans, Candida albicans and Candida glabrata, are exposed to a range of environmental stresses in their hosts including osmotic, oxidative and nitrosative stresses. Significant efforts have been devoted to the characterization of the adaptive responses to each of these stresses. In the wild, cells are frequently exposed simultaneously to combinations of these stresses and yet the effects of such combinatorial stresses have not been explored. We have developed a common experimental platform to facilitate the comparison of combinatorial stress responses in C. glabrata and C. albicans. This platform is based on the growth of cells in buffered rich medium at 30°C, and was used to define relatively low, medium and high doses of osmotic (NaCl), oxidative (H 2O2) and nitrosative stresses (e.g., dipropylenetriamine (DPTA)-NONOate). The effects of combinatorial stresses were compared with the corresponding individual stresses under these growth conditions. We show for the first time that certain combinations of combinatorial stress are especially potent in terms of their ability to kill C. albicans and C. glabrata and/or inhibit their growth. This was the case for combinations of osmotic plus oxidative stress and for oxidative plus nitrosative stress. We predict that combinatorial stresses may be highly signif cant in host defences against these pathogenic yeasts. PMID:22463109

Steam explosion and its combinatorial pretreatment refining technology of plant biomass to bio-based products.

PubMed

Chen, Hong-Zhang; Liu, Zhi-Hua

2015-06-01

Pretreatment is a key unit operation affecting the refinery efficiency of plant biomass. However, the poor efficiency of pretreatment and the lack of basic theory are the main challenges to the industrial implementation of the plant biomass refinery. The purpose of this work is to review steam explosion and its combinatorial pretreatment as a means of overcoming the intrinsic characteristics of plant biomass, including recalcitrance, heterogeneity, multi-composition, and diversity. The main advantages of the selective use of steam explosion and other combinatorial pretreatments across the diversity of raw materials are introduced. Combinatorial pretreatment integrated with other unit operations is proposed as a means to exploit the high-efficiency production of bio-based products from plant biomass. Finally, several pilot- and demonstration-scale operations of the plant biomass refinery are described. Based on the principle of selective function and structure fractionation, and multi-level and directional composition conversion, an integrated process with the combinatorial pretreatments of steam explosion and other pretreatments as the core should be feasible and conform to the plant biomass refinery concept. Combinatorial pretreatments of steam explosion and other pretreatments should be further exploited based on the type and intrinsic characteristics of the plant biomass used, the bio-based products to be made, and the complementarity of the processes. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Fragment-Based Method of Creating Small-Molecule Libraries to Target the Aggregation of Intrinsically Disordered Proteins.

PubMed

Joshi, Priyanka; Chia, Sean; Habchi, Johnny; Knowles, Tuomas P J; Dobson, Christopher M; Vendruscolo, Michele

2016-03-14

The aggregation process of intrinsically disordered proteins (IDPs) has been associated with a wide range of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Currently, however, no drug in clinical use targets IDP aggregation. To facilitate drug discovery programs in this important and challenging area, we describe a fragment-based approach of generating small-molecule libraries that target specific IDPs. The method is based on the use of molecular fragments extracted from compounds reported in the literature to inhibit of the aggregation of IDPs. These fragments are used to screen existing large generic libraries of small molecules to form smaller libraries specific for given IDPs. We illustrate this approach by describing three distinct small-molecule libraries to target, Aβ, tau, and α-synuclein, which are three IDPs implicated in Alzheimer's and Parkinson's diseases. The strategy described here offers novel opportunities for the identification of effective molecular scaffolds for drug discovery for neurodegenerative disorders and to provide insights into the mechanism of small-molecule binding to IDPs.

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer’s disease

PubMed Central

Habchi, Johnny; Chia, Sean; Limbocker, Ryan; Mannini, Benedetta; Ahn, Minkoo; Perni, Michele; Hansson, Oskar; Arosio, Paolo; Kumita, Janet R.; Challa, Pavan Kumar; Cohen, Samuel I. A.; Dobson, Christopher M.; Knowles, Tuomas P. J.; Vendruscolo, Michele

2017-01-01

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer’s disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery. PMID:28011763

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reznik, Ed; Christodoulou, Dimitris; Goldford, Joshua E.

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurementsmore » and the SMRN to make inferences on the sensitivity of enzymes to their regulators. By generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.« less

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

Design of a bioactive small molecule that targets r(AUUCU) repeats in spinocerebellar ataxia 10.

PubMed

Yang, Wang-Yong; Gao, Rui; Southern, Mark; Sarkar, Partha S; Disney, Matthew D

2016-06-01

RNA is an important target for chemical probes of function and lead therapeutics; however, it is difficult to target with small molecules. One approach to tackle this problem is to identify compounds that target RNA structures and utilize them to multivalently target RNA. Here we show that small molecules can be identified to selectively bind RNA base pairs by probing a library of RNA-focused small molecules. A small molecule that selectively binds AU base pairs informed design of a dimeric compound (2AU-2) that targets the pathogenic RNA, expanded r(AUUCU) repeats, that causes spinocerebellar ataxia type 10 (SCA10) in patient-derived cells. Indeed, 2AU-2 (50 nM) ameliorates various aspects of SCA10 pathology including improvement of mitochondrial dysfunction, reduced activation of caspase 3, and reduction of nuclear foci. These studies provide a first-in-class chemical probe to study SCA10 RNA toxicity and potentially define broadly applicable compounds targeting RNA AU base pairs in cells.

Small-Molecule-Directed Hepatocyte-Like Cell Differentiation of Human Pluripotent Stem Cells.

PubMed

Mathapati, Santosh; Siller, Richard; Impellizzeri, Agata A R; Lycke, Max; Vegheim, Karianne; Almaas, Runar; Sullivan, Gareth J

2016-08-17

Hepatocyte-like cells (HLCs) generated in vitro from human pluripotent stem cells (hPSCs) provide an invaluable resource for basic research, regenerative medicine, drug screening, toxicology, and modeling of liver disease and development. This unit describes a small-molecule-driven protocol for in vitro differentiation of hPSCs into HLCs without the use of growth factors. hPSCs are coaxed through a developmentally relevant route via the primitive streak to definitive endoderm (DE) using the small molecule CHIR99021 (a Wnt agonist), replacing the conventional growth factors Wnt3A and activin A. The small-molecule-derived DE is then differentiated to hepatoblast-like cells in the presence of dimethyl sulfoxide. The resulting hepatoblasts are then differentiated to HLCs with N-hexanoic-Tyr, Ile-6 aminohexanoic amide (Dihexa, a hepatocyte growth factor agonist) and dexamethasone. The protocol provides an efficient and reproducible procedure for differentiation of hPSCs into HLCs utilizing small molecules. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Bioorthogonal cyclization-mediated in situ self-assembly of small-molecule probes for imaging caspase activity in vivo

NASA Astrophysics Data System (ADS)

Ye, Deju; Shuhendler, Adam J.; Cui, Lina; Tong, Ling; Tee, Sui Seng; Tikhomirov, Grigory; Felsher, Dean W.; Rao, Jianghong

2014-06-01

Directed self-assembly of small molecules in living systems could enable a myriad of applications in biology and medicine, and already this has been used widely to synthesize supramolecules and nano/microstructures in solution and in living cells. However, controlling the self-assembly of synthetic small molecules in living animals is challenging because of the complex and dynamic in vivo physiological environment. Here we employ an optimized first-order bioorthogonal cyclization reaction to control the self-assembly of a fluorescent small molecule, and demonstrate its in vivo applicability by imaging caspase-3/7 activity in human tumour xenograft mouse models of chemotherapy. The fluorescent nanoparticles assembled in situ were imaged successfully in both apoptotic cells and tumour tissues using three-dimensional structured illumination microscopy. This strategy combines the advantages offered by small molecules with those of nanomaterials and should find widespread use for non-invasive imaging of enzyme activity in vivo.

9,10-Azaboraphenanthrene-containing small molecules and conjugated polymers: synthesis and their application in chemodosimeters for the ratiometric detection of fluoride ions.

PubMed

Zhang, Weidong; Li, Guoping; Xu, Letian; Zhuo, Yue; Wan, Wenming; Yan, Ni; He, Gang

2018-05-21

The introduction of main group elements into conjugated scaffolds is emerging as a key route to novel optoelectronic materials. Herein, an efficient and versatile way to synthesize polymerizable 9,10-azaboraphenanthrene ( BNP )-containing monomers by aromaticity-driven ring expansion reactions between highly antiaromatic borafluorene and azides is reported, and the corresponding conjugated small molecules and polymers are developed as well. The BNP -containing small molecules and conjugated polymers showed good air/moisture stability and notable fluorescence properties. Addition of fluoride ions to the BNP -based small molecules and polymers induced a rapid change in the emission color from blue to green/yellow, respectively, accompanied by strong intensity changes. The conjugated polymers showed better ratiometric sensing performance than small molecules due to the exciton migration along the conjugated chains. Further experiments showed that the sensing process is fully reversible. The films prepared by solution-deposition of BNP -based compounds in the presence of polycaprolactone also showed good ratiometric sensing for fluoride ions.

Small molecules enhance CRISPR genome editing in pluripotent stem cells.

PubMed

Yu, Chen; Liu, Yanxia; Ma, Tianhua; Liu, Kai; Xu, Shaohua; Zhang, Yu; Liu, Honglei; La Russa, Marie; Xie, Min; Ding, Sheng; Qi, Lei S

2015-02-05

The bacterial CRISPR-Cas9 system has emerged as an effective tool for sequence-specific gene knockout through non-homologous end joining (NHEJ), but it remains inefficient for precise editing of genome sequences. Here we develop a reporter-based screening approach for high-throughput identification of chemical compounds that can modulate precise genome editing through homology-directed repair (HDR). Using our screening method, we have identified small molecules that can enhance CRISPR-mediated HDR efficiency, 3-fold for large fragment insertions and 9-fold for point mutations. Interestingly, we have also observed that a small molecule that inhibits HDR can enhance frame shift insertion and deletion (indel) mutations mediated by NHEJ. The identified small molecules function robustly in diverse cell types with minimal toxicity. The use of small molecules provides a simple and effective strategy to enhance precise genome engineering applications and facilitates the study of DNA repair mechanisms in mammalian cells. Copyright © 2015 Elsevier Inc. All rights reserved.

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

DOE PAGES

Reznik, Ed; Christodoulou, Dimitris; Goldford, Joshua E.; ...

2017-09-12

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurementsmore » and the SMRN to make inferences on the sensitivity of enzymes to their regulators. By generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Yung-Ting; Department of Electrical Engineering, Graduate Institute of Photonics and Optoelectronics, National Taiwan University, Taipei, Taiwan 10617, Taiwan; Liu, Shun-Wei

Single-layer blue phosphorescence organic light emitting diodes (OLEDs) with either small-molecule or polymer hosts are fabricated using solution process and the performances of devices with different hosts are investigated. The small-molecule device exhibits luminous efficiency of 14.7 cd/A and maximum power efficiency of 8.39 lm/W, which is the highest among blue phosphorescence OLEDs with single-layer solution process and small molecular hosts. Using the same solution process for all devices, comparison of light out-coupling enhancement, with brightness enhancement film (BEF), between small-molecule and polymer based OLEDs is realized. Due to different dipole orientation and anisotropic refractive index, polymer-based OLEDs would trap less lightmore » than small molecule-based OLEDs internally, about 37% better based simulation results. In spite of better electrical and spectroscopic characteristics, including ambipolar characteristics, higher carrier mobility, higher photoluminescence quantum yield, and larger triplet state energy, the overall light out-coupling efficiency of small molecule-based devices is worse than that of polymer-based devices without BEF. However, with BEF for light out-coupling enhancement, the improved ratio in luminous flux and luminous efficiency for small molecule based device is 1.64 and 1.57, respectively, which are significantly better than those of PVK (poly-9-vinylcarbazole) devices. In addition to the theoretical optical simulation, the experimental data also confirm the origins of differential light-outcoupling enhancement. The maximum luminous efficiency and power efficiency are enhanced from 14.7 cd/A and 8.39 lm/W to 23 cd/A and 13.2 lm/W, respectively, with laminated BEF, which are both the highest so far for single-layer solution-process blue phosphorescence OLEDs with small molecule hosts.« less

Plasmonic Aptamer-Gold Nanoparticle Sensors for Small Molecule Fingerprint Identification

DTIC Science & Technology

2014-08-01

AFRL-RH-WP-TR-2014-0107 PLASMONIC APTAMER -GOLD NANOPARTICLE SENSORS FOR SMALL MOLECULE FINGERPRINT IDENTIFICATION Jorge Chávez Grant Slusher...Plasmonic Aptamer -Gold Nanoparticle Sensors for Small Molecule Fingerprint Identification 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER 5c. PROGRAM...The utilization of the plasmonic response of aptamer -gold nanoparticle conjugates (Apt-AuNPs) to design cross- reactive arrays for fingerprint

Covalent small-molecule-RNA complex formation enables cellular profiling of small-molecule-RNA interactions.

PubMed

Guan, Lirui; Disney, Matthew D

2013-09-16

Won't let you go! A strategy is described to design small molecules that react with their cellular RNA targets. This approach not only improves the activity of compounds targeting RNA in cell culture by a factor of about 2500 but also enables cell-wide profiling of its RNA targets. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Re-education begins at home: an overview of the discovery of in vivo-active small molecule modulators of endogenous stem cells.

PubMed

Um, JungIn; Lee, Ji-Hyung; Jung, Da-Woon; Williams, Darren R

2018-04-01

Degenerative diseases, such as Alzheimer's disease, heart disease and arthritis cause great suffering and are major socioeconomic burdens. An attractive treatment approach is stem cell transplantation to regenerate damaged or destroyed tissues. However, this can be problematic. For example, donor cells may not functionally integrate into the host tissue. An alternative methodology is to deliver bioactive agents, such as small molecules, directly into the diseased tissue to enhance the regenerative potential of endogenous stem cells. Areas covered: In this review, the authors discuss the necessity of developing these small molecules to treat degenerative diseases and survey progress in their application as therapeutics. They describe both the successes and caveats of developing small molecules that target endogenous stem cells to induce tissue regeneration. This article is based on literature searches which encompass databases for biomedical research and clinical trials. These small molecules are also categorized per their target disease and mechanism of action. Expert opinion: The development of small molecules targeting endogenous stem cells is a high-profile research area. Some compounds have made the successful transition to the clinic. Novel approaches, such as modulating the stem cell niche or targeted delivery to disease sites, should increase the likelihood of future successes in this field.

Bottom-up design of small molecules that stimulate exon 10 skipping in mutant MAPT pre-mRNA.

PubMed

Luo, Yiling; Disney, Matthew D

2014-09-22

One challenge in chemical biology is to develop small molecules that control cellular protein content. The amount and identity of proteins are influenced by the RNAs that encode them; thus, protein content in a cell could be affected by targeting mRNA. However, RNA has been traditionally difficult to target with small molecules. In this report, we describe controlling the protein products of the mutated microtubule-associated protein tau (MAPT) mature mRNA with a small molecule. MAPT mutations in exon 10 are associated with inherited frontotemporal dementia and Parkinsonism linked to chromosome 17 (FTDP-17), an incurable disease that is directly caused by increased inclusion of exon 10 in MAPT mRNA. Recent studies have shown that mutations within a hairpin at the MAPT exon 10-intron junction decrease the thermodynamic stability of the RNA, increasing binding to U1 snRNP and thus exon 10 inclusion. Therefore, we designed small molecules that bind and stabilize a mutant MAPT by using Inforna, a computational approach based on information about RNA-small-molecule interactions. The optimal compound selectively bound the mutant MAPT hairpin and thermodynamically stabilized its folding, facilitating exon 10 exclusion. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Small Molecule Supplements Improve Cultured Megakaryocyte Polyploidization by Modulating Multiple Cell Cycle Regulators.

PubMed

Zou, Xiaojing; Qu, Mingyi; Fang, Fang; Fan, Zeng; Chen, Lin; Yue, Wen; Xie, Xiaoyan; Pei, Xuetao

2017-01-01

Platelets (PLTs) are produced by megakaryocytes (MKs) that completed differentiation and endomitosis. Endomitosis is an important process in which the cell replicates its DNA without cytokinesis and develops highly polyploid MK. In this study, to gain a better PLTs production, four small molecules (Rho-Rock inhibitor (RRI), nicotinamide (NIC), Src inhibitor (SI), and Aurora B inhibitor (ABI)) and their combinations were surveyed as MK culture supplements for promoting polyploidization. Three leukemia cell lines as well as primary mononuclear cells were chosen in the function and mechanism studies of the small molecules. In an optimal culture method, cells were treated with different small molecules and their combinations. The impact of the small molecules on megakaryocytic surface marker expression, polyploidy, proliferation, and apoptosis was examined for the best MK polyploidization supplement. The elaborate analysis confirmed that the combination of SI and RRI together with our MK induction system might result in efficient ploidy promotion. Our experiments demonstrated that, besides direct downregulation on the expression of cytoskeleton protein actin, SI and RRI could significantly enhance the level of cyclins through the suppression of p53 and p21. The verified small molecule combination might be further used in the in vitro PLT manufacture and clinical applications.

Small Molecule Supplements Improve Cultured Megakaryocyte Polyploidization by Modulating Multiple Cell Cycle Regulators

PubMed Central

Fang, Fang; Chen, Lin; Yue, Wen

2017-01-01

Platelets (PLTs) are produced by megakaryocytes (MKs) that completed differentiation and endomitosis. Endomitosis is an important process in which the cell replicates its DNA without cytokinesis and develops highly polyploid MK. In this study, to gain a better PLTs production, four small molecules (Rho-Rock inhibitor (RRI), nicotinamide (NIC), Src inhibitor (SI), and Aurora B inhibitor (ABI)) and their combinations were surveyed as MK culture supplements for promoting polyploidization. Three leukemia cell lines as well as primary mononuclear cells were chosen in the function and mechanism studies of the small molecules. In an optimal culture method, cells were treated with different small molecules and their combinations. The impact of the small molecules on megakaryocytic surface marker expression, polyploidy, proliferation, and apoptosis was examined for the best MK polyploidization supplement. The elaborate analysis confirmed that the combination of SI and RRI together with our MK induction system might result in efficient ploidy promotion. Our experiments demonstrated that, besides direct downregulation on the expression of cytoskeleton protein actin, SI and RRI could significantly enhance the level of cyclins through the suppression of p53 and p21. The verified small molecule combination might be further used in the in vitro PLT manufacture and clinical applications. PMID:29201898

Small Molecules Affect Human Dental Pulp Stem Cell Properties Via Multiple Signaling Pathways

PubMed Central

Al-Habib, Mey; Yu, Zongdong

2013-01-01

One fundamental issue regarding stem cells for regenerative medicine is the maintenance of stem cell stemness. The purpose of the study was to test whether small molecules can enhance stem cell properties of mesenchymal stem cells (MSCs) derived from human dental pulp (hDPSCs), which have potential for multiple clinical applications. We identified the effects of small molecules (Pluripotin (SC1), 6-bromoindirubin-3-oxime and rapamycin) on the maintenance of hDPSC properties in vitro and the mechanisms involved in exerting the effects. Primary cultures of hDPSCs were exposed to optimal concentrations of these small molecules. Treated hDPSCs were analyzed for their proliferation, the expression levels of pluripotent and MSC markers, differentiation capacities, and intracellular signaling activations. We found that small molecule treatments decreased cell proliferation and increased the expression of STRO-1, NANOG, OCT4, and SOX2, while diminishing cell differentiation into odonto/osteogenic, adipogenic, and neurogenic lineages in vitro. These effects involved Ras-GAP-, ERK1/2-, and mTOR-signaling pathways, which may preserve the cell self-renewal capacity, while suppressing differentiation. We conclude that small molecules appear to enhance the immature state of hDPSCs in culture, which may be used as a strategy for adult stem cell maintenance and extend their capacity for regenerative applications. PMID:23573877

Methodologies for Studying B. subtilis Biofilms as a Model for Characterizing Small Molecule Biofilm Inhibitors.

PubMed

Bucher, Tabitha; Kartvelishvily, Elena; Kolodkin-Gal, Ilana

2016-10-09

This work assesses different methodologies to study the impact of small molecule biofilm inhibitors, such as D-amino acids, on the development and resilience of Bacillus subtilis biofilms. First, methods are presented that select for small molecule inhibitors with biofilm-specific targets in order to separate the effect of the small molecule inhibitors on planktonic growth from their effect on biofilm formation. Next, we focus on how inoculation conditions affect the sensitivity of multicellular, floating B. subtilis cultures to small molecule inhibitors. The results suggest that discrepancies in the reported effects of such inhibitors such as D-amino acids are due to inconsistent pre-culture conditions. Furthermore, a recently developed protocol is described for evaluating the contribution of small molecule treatments towards biofilm resistance to antibacterial substances. Lastly, scanning electron microscopy (SEM) techniques are presented to analyze the three-dimensional spatial arrangement of cells and their surrounding extracellular matrix in a B. subtilis biofilm. SEM facilitates insight into the three-dimensional biofilm architecture and the matrix texture. A combination of the methods described here can greatly assist the study of biofilm development in the presence and absence of biofilm inhibitors, and shed light on the mechanism of action of these inhibitors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Jinhua; Pan, Baofei; Duan, Wentao

In advanced electrical grids of the future, electrochemically rechargeable fluids of high energy density will capture the power generated from intermittent sources like solar and wind. To meet this outstanding technological demand there is a need to understand the fundamental limits and interplay of electrochemical potential, stability, and solubility in low-weight redox-active molecules. By generating a combinatorial set of 1,4-dimethoxybenzene derivatives with different arrangements of substituents, we discovered a mini-malistic structure that combines exceptional long-term stability in its oxidized form and a record-breaking intrinsic capacity of 161 mAh/g. The nonaqueous redox flow battery has been demonstrated that uses this moleculemore » as a catholyte material and operated stably for 100 charge/discharge cycles. Furthermore, the observed stability trends are rationalized by mechanistic considerations of the reaction pathways.« less

Mutations in IRX5 impair craniofacial development and germ cell migration via SDF1.

PubMed

Bonnard, Carine; Strobl, Anna C; Shboul, Mohammad; Lee, Hane; Merriman, Barry; Nelson, Stanley F; Ababneh, Osama H; Uz, Elif; Güran, Tülay; Kayserili, Hülya; Hamamy, Hanan; Reversade, Bruno

2012-05-13

Using homozygosity mapping and locus resequencing, we found that alterations in the homeodomain of the IRX5 transcription factor cause a recessive congenital disorder affecting face, brain, blood, heart, bone and gonad development. We found through in vivo modeling in Xenopus laevis embryos that Irx5 modulates the migration of progenitor cell populations in branchial arches and gonads by repressing Sdf1. We further found that transcriptional control by Irx5 is modulated by direct protein-protein interaction with two GATA zinc-finger proteins, GATA3 and TRPS1; disruptions of these proteins also cause craniofacial dysmorphisms. Our findings suggest that IRX proteins integrate combinatorial transcriptional inputs to regulate key signaling molecules involved in the ontogeny of multiple organs during embryogenesis and homeostasis.

Molecular computation: RNA solutions to chess problems

PubMed Central

Faulhammer, Dirk; Cukras, Anthony R.; Lipton, Richard J.; Landweber, Laura F.

2000-01-01

We have expanded the field of “DNA computers” to RNA and present a general approach for the solution of satisfiability problems. As an example, we consider a variant of the “Knight problem,” which asks generally what configurations of knights can one place on an n × n chess board such that no knight is attacking any other knight on the board. Using specific ribonuclease digestion to manipulate strands of a 10-bit binary RNA library, we developed a molecular algorithm and applied it to a 3 × 3 chessboard as a 9-bit instance of this problem. Here, the nine spaces on the board correspond to nine “bits” or placeholders in a combinatorial RNA library. We recovered a set of “winning” molecules that describe solutions to this problem. PMID:10677471

Phage selection of peptide "microantibodies".

PubMed

Fujiwara, Daisuke; Fujii, Ikuo

2013-01-01

A bioactive peptide capable of inhibiting protein-protein interactions has the potential to be a molecular tool for biological studies and a therapeutic by disrupting aberrant interactions involved in diseases. We have developed combinatorial libraries of peptides with helix-loop-helix structure, from which the isolated peptides have the constrained structure to reduce entropy costs in binding, resulting in high binding affinities for target molecules. Previously, we designed a de novo peptide of helix-loop-helix structure that we termed a "microantibody." Using the microantibody as a library scaffold, we have constructed a phage-display library to successfully isolate molecular-targeting peptides against a cytokine receptor (granulocyte colony-stimulating factor receptor), a protein kinase (Aurora-A), and a ganglioside (GM1). Protocols in this article describe a general procedure for the library construction and the library screening.

New Catalytic DNA Biosensors for Radionuclides and Metal ion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yi Lu

2008-03-01

We aim to develop new DNA biosensors for simultaneous detection and quantification of bioavailable radionuclides, such as uranium, technetium, and plutonium, and metal contaminants, such as lead, chromium, and mercury. The sensors will be highly sensitive and selective. They will be applied to on-site, real-time assessment of concentration, speciation, and stability of the individual contaminants before and during bioremediation, and for long-term monitoring of DOE contaminated sites. To achieve this goal, we have employed a combinatorial method called “in vitro selection” to search from a large DNA library (~ 1015 different molecules) for catalytic DNA molecules that are highly specificmore » for radionuclides or other metal ions through intricate 3-dimensional interactions as in metalloproteins. Comprehensive biochemical and biophysical studies have been performed on the selected DNA molecules. The findings from these studies have helped to elucidate fundamental principles for designing effective sensors for radionuclides and metal ions. Based on the study, the DNA have been converted to fluorescent or colorimetric sensors by attaching to it fluorescent donor/acceptor pairs or gold nanoparticles, with 11 part-per-trillion detection limit (for uranium) and over million fold selectivity (over other radionuclides and metal ions tested). Practical application of the biosensors for samples from the Environmental Remediation Sciences Program (ERSP) Field Research Center (FRC) at Oak Ridge has also been demonstrated.« less

Using Hierarchical Virtual Screening To Combat Drug Resistance of the HIV-1 Protease.

PubMed

Li, Nan; Ainsworth, Richard I; Ding, Bo; Hou, Tingjun; Wang, Wei

2015-07-27

Human immunodeficiency virus (HIV) protease inhibitors (PIs) are important components of highly active anti-retroviral therapy (HAART) that block the catalytic site of HIV protease, thus preventing maturation of the HIV virion. However, with two decades of PI prescriptions in clinical practice, drug-resistant HIV mutants have now been found for all of the PI drugs. Therefore, the continuous development of new PI drugs is crucial both to combat the existing drug-resistant HIV strains and to provide treatments for future patients. Here we purpose an HIV PI drug design strategy to select candidate PIs with binding energy distributions dominated by interactions with conserved protease residues in both wild-type and various drug-resistant mutants. On the basis of this strategy, we have constructed a virtual screening pipeline including combinatorial library construction, combinatorial docking, MM/GBSA-based rescoring, and reranking on the basis of the binding energy distribution. We have tested our strategy on lopinavir by modifying its two functional groups. From an initial 751 689 candidate molecules, 18 candidate inhibitors were selected using the pipeline for experimental validation. IC50 measurements and drug resistance predictions successfully identified two ligands with both HIV protease inhibitor activity and an improved drug resistance profile on 2382 HIV mutants. This study provides a proof of concept for the integration of MM/GBSA energy analysis and drug resistance information at the stage of virtual screening and sheds light on future HIV drug design and the use of virtual screening to combat drug resistance.

High-Throughput Identification of Combinatorial Ligands for DNA Delivery in Cell Culture

NASA Astrophysics Data System (ADS)

Svahn, Mathias G.; Rabe, Kersten S.; Barger, Geoffrey; EL-Andaloussi, Samir; Simonson, Oscar E.; Didier, Boturyn; Olivier, Renaudet; Dumy, Pascal; Brandén, Lars J.; Niemeyer, Christof M.; Smith, C. I. Edvard

2008-10-01

Finding the optimal combinations of ligands for tissue-specific delivery is tedious even if only a few well-established compounds are tested. The cargo affects the receptor-ligand interaction, especially when it is charged like DNA. The ligand should therefore be evaluated together with its cargo. Several viruses have been shown to interact with more than one receptor, for efficient internalization. We here present a DNA oligonucleotide-based method for inexpensive and rapid screening of biotin labeled ligands for combinatorial effects on cellular binding and uptake. The oligonucleotide complex was designed as a 44 bp double-stranded DNA oligonucleotide with one central streptavidin molecule and a second streptavidin at the terminus. The use of a highly advanced robotic platform ensured stringent processing and execution of the experiments. The oligonucleotides were fluorescently labeled and used for detection and analysis of cell-bound, internalized and intra-cellular compartmentalized constructs by an automated line-scanning confocal microscope, IN Cell Analyzer 3000. All possible combinations of 22 ligands were explored in sets of 2 and tested on 6 different human cell lines in triplicates. In total, 10 000 transfections were performed on the automation platform. Cell-specific combinations of ligands were identified and their relative position on the scaffold oligonucleotide was found to be of importance. The ligands were found to be cargo dependent, carbohydrates were more potent for DNA delivery whereas cell penetrating peptides were more potent for delivery of less charged particles.

Precursor-Directed Combinatorial Biosynthesis of Cinnamoyl, Dihydrocinnamoyl, and Benzoyl Anthranilates in Saccharomyces cerevisiae

DOE PAGES

Eudes, Aymerick; Teixeira Benites, Veronica; Wang, George; ...

2015-10-02

Biological synthesis of pharmaceuticals and biochemicals offers an environmentally friendly alternative to conventional chemical synthesis. These alternative methods require the design of metabolic pathways and the identification of enzymes exhibiting adequate activities. Cinnamoyl, dihydrocinnamoyl, and benzoyl anthranilates are natural metabolites which possess beneficial activities for human health, and the search is expanding for novel derivatives that might have enhanced biological activity. For example, biosynthesis in Dianthus caryophyllus is catalyzed by hydroxycinnamoyl/benzoyl-CoA:anthranilate N-hydroxycinnamoyl/ benzoyltransferase (HCBT), which couples hydroxycinnamoyl-CoAs and benzoyl-CoAs to anthranilate. We recently demonstrated the potential of using yeast (Saccharomyces cerevisiae) for the biological production of a few cinnamoyl anthranilatesmore » by heterologous co-expression of 4-coumaroyl:CoA ligase from Arabidopsis thaliana (4CL5) and HCBT. Here we report that, by exploiting the substrate flexibility of both 4CL5 and HCBT, we achieved rapid biosynthesis of more than 160 cinnamoyl, dihydrocinnamoyl, and benzoyl anthranilates in yeast upon feeding with both natural and non-natural cinnamates, dihydrocinnamates, benzoates, and anthranilates. Our results demonstrate the use of enzyme promiscuity in biological synthesis to achieve high chemical diversity within a defined class of molecules. Finally, this work also points to the potential for the combinatorial biosynthesis of diverse and valuable cinnamoylated, dihydrocinnamoylated, and benzoylated products by using the versatile biological enzyme 4CL5 along with characterized cinnamoyl-CoA- and benzoyl-CoA-utilizing transferases.« less

Leveraging Modeling Approaches: Reaction Networks and Rules

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349

Leveraging modeling approaches: reaction networks and rules.

PubMed

Blinov, Michael L; Moraru, Ion I

2012-01-01

We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.

Synergistic Effect of Auto-Activation and Small RNA Regulation on Gene Expression

NASA Astrophysics Data System (ADS)

Xiong, Li-Ping; Ma, Yu-Qiang; Tang, Lei-Han

2010-09-01

Auto-activation and small ribonucleic acid (RNA)-mediated regulation are two important mechanisms in controlling gene expression. We study the synergistic effect of these two regulations on gene expression. It is found that under this combinatorial regulation, gene expression exhibits bistable behaviors at the transition regime, while each of these two regulations, if working solely, only leads to monostability. Within the stochastic framework, the base pairing strength between sRNA and mRNA plays an important role in controlling the transition time between on and off states. The noise strength of protein number in the off state approaches 1 and is smaller than that in the on state. The noise strength also depends on which parameters, the feedback strength or the synthesis rate of small RNA, are tuned in switching the gene expression on and off. Our findings may provide a new insight into gene-regulation mechanism and can be applied in synthetic biology.

Electronic Structure of Small Lanthanide Containing Molecules

NASA Astrophysics Data System (ADS)

Kafader, Jared O.; Ray, Manisha; Topolski, Josey E.; Chick Jarrold, Caroline

2016-06-01

Lanthanide-based materials have unusual electronic properties because of the high number of electronic degrees of freedom arising from partial occupation of 4f orbitals, which make these materials optimal for their utilization in many applications including electronics and catalysis. Electronic spectroscopy of small lanthanide molecules helps us understand the role of these 4f electrons, which are generally considered core-like because of orbital contraction, but are energetically similar to valence electrons. The spectroscopy of small lanthanide-containing molecules is relatively unexplored and to broaden this understanding we have completed the characterization of small cerium, praseodymium, and europium molecules using photoelectron spectroscopy coupled with DFT calculations. The characterization of PrO, EuH, EuO/EuOH, and CexOy molecules have allowed for the determination of their electron affinity, the assignment of numerous anion to neutral state transitions, modeling of anion/neutral structures and electron orbital occupation.

Evaluation of the Current Status of the Combinatorial Approach for the Study of Phase Diagrams

PubMed Central

Wong-Ng, W.

2012-01-01

This paper provides an evaluation of the effectiveness of using the high throughput combinatorial approach for preparing phase diagrams of thin film and bulk materials. Our evaluation is based primarily on examples of combinatorial phase diagrams that have been reported in the literature as well as based on our own laboratory experiments. Various factors that affect the construction of these phase diagrams are examined. Instrumentation and analytical approaches needed to improve data acquisition and data analysis are summarized. PMID:26900530

Research on thermal protection mechanism of forward-facing cavity and opposing jet combinatorial thermal protection system

NASA Astrophysics Data System (ADS)

Lu, Hai-Bo; Liu, Wei-Qiang

2014-04-01

Validated by the correlated experiments, a nose-tip with forward-facing cavity/opposing jet/the combinatorial configuration of forward-facing cavity and opposing jet thermal protection system (TPS) are investigated numerically. The physical mechanism of these TPS is discussed, and the cooling efficiency of them is compared. The combinatorial system is more suitable to be the TPS for the high speed vehicles which need fly under various flow conditions with long-range and long time.

Combinatorial approach to the representation of the Schur-Weyl duality in one-dimensional spin systems

NASA Astrophysics Data System (ADS)

Jakubczyk, Dorota; Jakubczyk, Paweł

2018-02-01

We propose combinatorial approach to the representation of Schur-Weyl duality in physical systems on the example of one-dimensional spin chains. Exploiting the Robinson-Schensted-Knuth algorithm, we perform decomposition of the dual group representations into irreducible representations in a fully combinatorial way. As representation space, we choose the Hilbert space of the spin chains, but this approach can be easily generalized to an arbitrary physical system where the Schur-Weyl duality works.

Massively multiplex single-cell Hi-C

PubMed Central

Ramani, Vijay; Deng, Xinxian; Qiu, Ruolan; Gunderson, Kevin L; Steemers, Frank J; Disteche, Christine M; Noble, William S; Duan, Zhijun; Shendure, Jay

2016-01-01

We present single-cell combinatorial indexed Hi-C (sciHi-C), which applies the concept of combinatorial cellular indexing to chromosome conformation capture. In this proof-of-concept, we generate and sequence six sciHi-C libraries comprising a total of 10,696 single cells. We use sciHi-C data to separate cells by karytoypic and cell-cycle state differences and identify cell-to-cell heterogeneity in mammalian chromosomal conformation. Our results demonstrate that combinatorial indexing is a generalizable strategy for single-cell genomics. PMID:28135255

Unravelling the complex venom landscapes of lethal Australian funnel-web spiders (Hexathelidae: Atracinae) using LC-MALDI-TOF mass spectrometry.

PubMed

Palagi, Alexandre; Koh, Jennifer M S; Leblanc, Mathieu; Wilson, David; Dutertre, Sébastien; King, Glenn F; Nicholson, Graham M; Escoubas, Pierre

2013-03-27

Spider venoms represent vast sources of bioactive molecules whose diversity remains largely unknown. Indeed, only a small subset of species have been studied out of the ~43,000 extant spider species. The present study investigated inter- and intra-species venom complexity in 18 samples collected from a variety of lethal Australian funnel-web spiders (Mygalomorphae: Hexathelidae: Atracinae) using C4 reversed-phase separation coupled to offline MALDI-TOF mass spectrometry (LC-MALDI-TOF MS). An in-depth investigation focusing on four atracine venoms (male Illawarra wisharti, male and female Hadronyche cerberea, and female Hadronyche infensa Toowoomba) revealed, on average, ~800 peptides in female venoms while male venoms contained ~400 peptides, distributed across most HPLC fractions. This is significantly higher than previous estimates of peptide expression in mygalomorph venoms. These venoms also showed distinct intersexual as well as intra- and inter-species variation in peptide masses. Construction of both 3D and 2D contour plots revealed that peptide mass distributions in all 18 venoms were centered around the 3200-5400m/z range and to a lesser extent the 6600-8200m/z range, consistent with previously described hexatoxins. These findings highlight the extensive diversity of peptide toxins in Australian funnel-web spider venoms that that can be exploited as novel therapeutic and biopesticide lead molecules. In the present study we describe the complexity of 18 venoms from lethal Australian funnel-web spiders using LC-MALDI-TOF MS. The study includes an in-depth investigation, focusing on four venoms, that revealed the presence of ~800 peptides in female venoms and ~400 peptides in male venoms. This is significantly higher than previous estimates of peptide expression in spider venoms. By constructing both 3D and 2D contour plots we were also able to reveal the distinct intersexual as well as intra- and inter-species variation in venom peptide masses. We show that peptide mass distributions in all 18 venoms were centered around the 3200-5400 m/z range and to a lesser extent the 6600-8200 m/z range, consistent with the small number of previously described hexatoxins from these spiders. These findings highlight the extensive diversity of peptide toxins in Australian funnel-web spider venoms that that can be exploited as novel therapeutic and biopesticide lead molecules. The present study has greatly expanded our understanding of peptide variety and complexity in these lethal mygalomorph spiders. Specifically it highlights both the utility of LC-MALDI-TOF in spider taxonomy and the massive combinatorial peptide libraries that spider venoms offer the pharmaceutical and agrochemical industry. Copyright © 2013 Elsevier B.V. All rights reserved.

Activation of Polymine Catabolism as a Novel Strategy for Treating and/or Preventing Human Prostate Cancer

DTIC Science & Technology

2006-03-01

strategy against prostate cancer and thus, worthy of small molecule discovery and development. On the basis of findings obtained over the past 3...support for the discovery and development of specific small molecule inducers of SSAT as a novel therapeutic strategy targeting prostate cancer. This...D. Unscheduled Findings. Findings under Tasks 1 and 3 provided genetic evidence for the discovery and development of small molecule inducers of

A-D-A small molecules for solution-processed organic photovoltaic cells.

PubMed

Ni, Wang; Wan, Xiangjian; Li, Miaomiao; Wang, Yunchuang; Chen, Yongsheng

2015-03-25

A-D-A small molecules have drawn more and more attention in solution-processed organic solar cells due to the advantages of a diversity of structures, easy control of energy levels, etc. Recently, a power conversion efficiency of nearly 10% has been achieved through careful material design and device optimization. This feature article reviews recent representative progress in the design and application of A-D-A small molecules in organic photovoltaic cells.

Delivery of small molecules for bone regenerative engineering: preclinical studies and potential clinical applications

PubMed Central

Laurencin, Cato T.; Ashe, Keshia M.; Henry, Nicole; Kan, Ho Man; Lo, Kevin W-H.

2014-01-01

Stimulation of bone regeneration using growth factors is a promising approach for musculoskeletal regenerative engineering. Common limitations with protein growth factors are high manufacturing costs, protein instability, contamination issues, and unwanted immunogenic responses of the host. New strategies for bone regeneration that obviate these problems can have a significant impact on the treatment of skeletal injury and diseases. Over the past decade, a large number of small molecules with the potential of regenerating skeletal tissue have been reported in the literature. Here, we review this literature, paying specific attention to the prospects for small molecule-based bone-regenerative engineering. We also review the preclinical study of small molecules associated with bone regeneration. PMID:24508820

Cobalt coated substrate for matrix-free analysis of small molecules by laser desorption/ionization mass spectrometry

NASA Astrophysics Data System (ADS)

Yalcin, Talat; Li, Liang

2009-12-01

Small molecule analysis is one of the most challenging issues in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. We have developed a cobalt coated substrate as a target for matrix-free analysis of small molecules in laser desorption/ionization mass spectrometry. Cobalt coating of 60-70 nm thickness has been characterized by scanning electron microscopy, energy dispersive X-ray analysis, X-ray diffraction, and laser induced breakdown spectroscopy. This target facilitates hundreds of samples to be spotted and analyzed without mixing any matrices, in a very short time. This can save a lot of time and money and can be a very practical approach for the analysis of small molecules by laser desorption/ionization mass spectrometry.

Combinatorial Interdependence in Lottery

ERIC Educational Resources Information Center

Helman, Danny

2005-01-01

This paper examines a real life question of gamble facing lottery players. Combinatorial dependence plays a central role in shaping the game probabilistic structure, but might not carry the merited weight in punters' considerations.

Update: the status of clinical trials with kinase inhibitors in thyroid cancer.

PubMed

Wells, Samuel A; Santoro, Massimo

2014-05-01

Thyroid cancer is usually cured by timely thyroidectomy; however, the treatment of patients with advanced disease is challenging because their tumors are mostly unresponsive to conventional therapies. Recently, the malignancy has attracted much interest for two reasons: the dramatic increase in its incidence over the last three decades, and the discovery of the genetic mutations or chromosomal rearrangements causing most histological types of thyroid cancer. This update reviews the molecular genetics of thyroid cancer and the clinical trials evaluating kinase inhibitors (KIs) in patients with locally advanced or metastatic disease. The update also reviews studies in other malignancies, which have identified mechanisms of efficacy, and also resistance, to specific KIs. This information has been critical both to the development of effective second-generation drugs and to the design of combinatorial therapeutic regimens. Finally, the update addresses the major challenges facing clinicians who seek to develop more effective therapy for patients with thyroid cancer. PubMed was searched from January 2000 to November 2013 using the following terms: thyroid cancer, treatment of thyroid cancer, clinical trials in thyroid cancer, small molecule therapeutics, kinase inhibitors, and next generation sequencing. A new era in cancer therapy has emerged based on the introduction of KIs for the treatment of patients with liquid and solid organ malignancies. Patients with thyroid cancer have benefited from this advance and will continue to do so with the development of drugs having greater specificity and with the implementation of clinical trials of combined therapeutics to overcome drug resistance.

Evaluation of an Inverse Molecular Design Algorithm in a Model Binding Site

PubMed Central

Huggins, David J.; Altman, Michael D.; Tidor, Bruce

2008-01-01

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors [M. D. Altman et al. J. Am. Chem. Soc. 130: 6099–6013, 2008]. Here we have evaluated the new method using the well studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from non-binders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the non-binders. PMID:18831031

Evaluation of an inverse molecular design algorithm in a model binding site.

PubMed

Huggins, David J; Altman, Michael D; Tidor, Bruce

2009-04-01

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors (Altman et al., J Am Chem Soc 2008;130:6099-6013). Here we have evaluated the new method using the well-studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from nonbinders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions, and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the nonbinders. (c) 2008 Wiley-Liss, Inc.

Engineering and Two-Stage Evolution of a Lignocellulosic Hydrolysate-Tolerant Saccharomyces cerevisiae Strain for Anaerobic Fermentation of Xylose from AFEX Pretreated Corn Stover

PubMed Central

Parreiras, Lucas S.; Breuer, Rebecca J.; Avanasi Narasimhan, Ragothaman; Higbee, Alan J.; La Reau, Alex; Tremaine, Mary; Qin, Li; Willis, Laura B.; Bice, Benjamin D.; Bonfert, Brandi L.; Pinhancos, Rebeca C.; Balloon, Allison J.; Uppugundla, Nirmal; Liu, Tongjun; Li, Chenlin; Tanjore, Deepti; Ong, Irene M.; Li, Haibo; Pohlmann, Edward L.; Serate, Jose; Withers, Sydnor T.; Simmons, Blake A.; Hodge, David B.; Westphall, Michael S.; Coon, Joshua J.; Dale, Bruce E.; Balan, Venkatesh; Keating, David H.; Zhang, Yaoping; Landick, Robert; Gasch, Audrey P.; Sato, Trey K.

2014-01-01

The inability of the yeast Saccharomyces cerevisiae to ferment xylose effectively under anaerobic conditions is a major barrier to economical production of lignocellulosic biofuels. Although genetic approaches have enabled engineering of S. cerevisiae to convert xylose efficiently into ethanol in defined lab medium, few strains are able to ferment xylose from lignocellulosic hydrolysates in the absence of oxygen. This limited xylose conversion is believed to result from small molecules generated during biomass pretreatment and hydrolysis, which induce cellular stress and impair metabolism. Here, we describe the development of a xylose-fermenting S. cerevisiae strain with tolerance to a range of pretreated and hydrolyzed lignocellulose, including Ammonia Fiber Expansion (AFEX)-pretreated corn stover hydrolysate (ACSH). We genetically engineered a hydrolysate-resistant yeast strain with bacterial xylose isomerase and then applied two separate stages of aerobic and anaerobic directed evolution. The emergent S. cerevisiae strain rapidly converted xylose from lab medium and ACSH to ethanol under strict anaerobic conditions. Metabolomic, genetic and biochemical analyses suggested that a missense mutation in GRE3, which was acquired during the anaerobic evolution, contributed toward improved xylose conversion by reducing intracellular production of xylitol, an inhibitor of xylose isomerase. These results validate our combinatorial approach, which utilized phenotypic strain selection, rational engineering and directed evolution for the generation of a robust S. cerevisiae strain with the ability to ferment xylose anaerobically from ACSH. PMID:25222864

Combinatorics of feedback in cellular uptake and metabolism of small molecules.

PubMed

Krishna, Sandeep; Semsey, Szabolcs; Sneppen, Kim

2007-12-26

We analyze the connection between structure and function for regulatory motifs associated with cellular uptake and usage of small molecules. Based on the boolean logic of the feedback we suggest four classes: the socialist, consumer, fashion, and collector motifs. We find that the socialist motif is good for homeostasis of a useful but potentially poisonous molecule, whereas the consumer motif is optimal for nutrition molecules. Accordingly, examples of these motifs are found in, respectively, the iron homeostasis system in various organisms and in the uptake of sugar molecules in bacteria. The remaining two motifs have no obvious analogs in small molecule regulation, but we illustrate their behavior using analogies to fashion and obesity. These extreme motifs could inspire construction of synthetic systems that exhibit bistable, history-dependent states, and homeostasis of flux (rather than concentration).

A Systematic Study of Simple Combinatorial Configurations.

ERIC Educational Resources Information Center

Dubois, Jean-Guy

1984-01-01

A classification of the simple combinatorial configurations which correspond to various cases of distribution and ordering of objects into boxes is given (in French). Concrete descriptions, structured relations, translations, and formalizations are discussed. (MNS)

Combinatorial Mathematics: Research into Practice

ERIC Educational Resources Information Center

Sriraman, Bharath; English, Lyn D.

2004-01-01

Implications and suggestions for using combinatorial mathematics in the classroom through a survey and synthesis of numerous research studies are presented. The implications revolve around five major themes that emerge from analysis of these studies.

Enabling techniques in the search for new antibiotics: Combinatorial biosynthesis of sugar-containing antibiotics.

PubMed

Park, Je Won; Nam, Sang-Jip; Yoon, Yeo Joon

2017-06-15

Nature has a talent for inventing a vast number of natural products, including hybrids generated by blending different scaffolds, resulting in a myriad of bioactive chemical entities. Herein, we review the highlights and recent trends (2010-2016) in the combinatorial biosynthesis of sugar-containing antibiotics where nature's structural diversification capabilities are exploited to enable the creation of new anti-infective and anti-proliferative drugs. In this review, we describe the modern combinatorial biosynthetic approaches for polyketide synthase-derived complex and aromatic polyketides, non-ribosomal peptide synthetase-directed lipo-/glycopeptides, aminoglycosides, nucleoside antibiotics, and alkaloids, along with their therapeutic potential. Finally, we present the feasible nexus between combinatorial biosynthesis, systems biology, and synthetic biology as a toolbox to provide new antibiotics that will be indispensable in the post-antibiotic era. Copyright © 2016 Elsevier Inc. All rights reserved.

Combinatorial vector fields and the valley structure of fitness landscapes.

PubMed

Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

Measuring and Specifying Combinatorial Coverage of Test Input Configurations

PubMed Central

Kuhn, D. Richard; Kacker, Raghu N.; Lei, Yu

2015-01-01

A key issue in testing is how many tests are needed for a required level of coverage or fault detection. Estimates are often based on error rates in initial testing, or on code coverage. For example, tests may be run until a desired level of statement or branch coverage is achieved. Combinatorial methods present an opportunity for a different approach to estimating required test set size, using characteristics of the test set. This paper describes methods for estimating the coverage of, and ability to detect, t-way interaction faults of a test set based on a covering array. We also develop a connection between (static) combinatorial coverage and (dynamic) code coverage, such that if a specific condition is satisfied, 100% branch coverage is assured. Using these results, we propose practical recommendations for using combinatorial coverage in specifying test requirements. PMID:28133442

Combinatorial chemical bath deposition of CdS contacts for chalcogenide photovoltaics

DOE PAGES

Mokurala, Krishnaiah; Baranowski, Lauryn L.; de Souza Lucas, Francisco W.; ...

2016-08-01

Contact layers play an important role in thin film solar cells, but new material development and optimization of its thickness is usually a long and tedious process. A high-throughput experimental approach has been used to accelerate the rate of research in photovoltaic (PV) light absorbers and transparent conductive electrodes, however the combinatorial research on contact layers is less common. Here, we report on the chemical bath deposition (CBD) of CdS thin films by combinatorial dip coating technique and apply these contact layers to Cu(In,Ga)Se 2 (CIGSe) and Cu 2ZnSnSe 4 (CZTSe) light absorbers in PV devices. Combinatorial thickness steps ofmore » CdS thin films were achieved by removal of the substrate from the chemical bath, at regular intervals of time, and in equal distance increments. The trends in the photoconversion efficiency and in the spectral response of the PV devices as a function of thickness of CdS contacts were explained with the help of optical and morphological characterization of the CdS thin films. The maximum PV efficiency achieved for the combinatorial dip-coating CBD was similar to that for the PV devices processed using conventional CBD. Finally, the results of this study lead to the conclusion that combinatorial dip-coating can be used to accelerate the optimization of PV device performance of CdS and other candidate contact layers for a wide range of emerging absorbers.« less

Polynomial functors and combinatorial Dyson-Schwinger equations

NASA Astrophysics Data System (ADS)

Kock, Joachim

2017-04-01

We present a general abstract framework for combinatorial Dyson-Schwinger equations, in which combinatorial identities are lifted to explicit bijections of sets, and more generally equivalences of groupoids. Key features of combinatorial Dyson-Schwinger equations are revealed to follow from general categorical constructions and universal properties. Rather than beginning with an equation inside a given Hopf algebra and referring to given Hochschild 1-cocycles, our starting point is an abstract fixpoint equation in groupoids, shown canonically to generate all the algebraic structures. Precisely, for any finitary polynomial endofunctor P defined over groupoids, the system of combinatorial Dyson-Schwinger equations X = 1 + P(X) has a universal solution, namely the groupoid of P-trees. The isoclasses of P-trees generate naturally a Connes-Kreimer-like bialgebra, in which the abstract Dyson-Schwinger equation can be internalised in terms of canonical B+-operators. The solution to this equation is a series (the Green function), which always enjoys a Faà di Bruno formula, and hence generates a sub-bialgebra isomorphic to the Faà di Bruno bialgebra. Varying P yields different bialgebras, and cartesian natural transformations between various P yield bialgebra homomorphisms and sub-bialgebras, corresponding for example to truncation of Dyson-Schwinger equations. Finally, all constructions can be pushed inside the classical Connes-Kreimer Hopf algebra of trees by the operation of taking core of P-trees. A byproduct of the theory is an interpretation of combinatorial Green functions as inductive data types in the sense of Martin-Löf type theory (expounded elsewhere).

Parallel computation with molecular-motor-propelled agents in nanofabricated networks.

PubMed

Nicolau, Dan V; Lard, Mercy; Korten, Till; van Delft, Falco C M J M; Persson, Malin; Bengtsson, Elina; Månsson, Alf; Diez, Stefan; Linke, Heiner; Nicolau, Dan V

2016-03-08

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecular-motor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NP-complete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.

Chemical correction of pre-mRNA splicing defects associated with sequestration of muscleblind-like 1 protein by expanded r(CAG)-containing transcripts.

PubMed

Kumar, Amit; Parkesh, Raman; Sznajder, Lukasz J; Childs-Disney, Jessica L; Sobczak, Krzysztof; Disney, Matthew D

2012-03-16

Recently, it was reported that expanded r(CAG) triplet repeats (r(CAG)(exp)) associated with untreatable neurological diseases cause pre-mRNA mis-splicing likely due to sequestration of muscleblind-like 1 (MBNL1) splicing factor. Bioactive small molecules that bind the 5'CAG/3'GAC motif found in r(CAG)(exp) hairpin structure were identified by using RNA binding studies and virtual screening/chemical similarity searching. Specifically, a benzylguanidine-containing small molecule was found to improve pre-mRNA alternative splicing of MBNL1-sensitive exons in cells expressing the toxic r(CAG)(exp). The compound was identified by first studying the binding of RNA 1 × 1 nucleotide internal loops to small molecules known to have affinity for nucleic acids. Those studies identified 4',6-diamidino-2-phenylindole (DAPI) as a specific binder to RNAs with the 5'CAG/3'GAC motif. DAPI was then used as a query molecule in a shape- and chemistry alignment-based virtual screen to identify compounds with improved properties, which identified 4-guanidinophenyl 4-guanidinobenzoate, a small molecule that improves pre-mRNA splicing defects associated with the r(CAG)(exp)-MBNL1 complex. This compound may facilitate the development of therapeutics to treat diseases caused by r(CAG)(exp) and could serve as a useful chemical tool to dissect the mechanisms of r(CAG)(exp) toxicity. The approach used in these studies, defining the small RNA motifs that bind small molecules with known affinity for nucleic acids and then using virtual screening to optimize them for bioactivity, may be generally applicable for designing small molecules that target other RNAs in the human genomic sequence.

A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces.

PubMed

Xu, David; Si, Yubing; Meroueh, Samy O

2017-09-25

The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.

Cancer Theranostic Nanoparticles Self-Assembled from Amphiphilic Small Molecules with Equilibrium Shift-Induced Renal Clearance

PubMed Central

Ma, Yuan; Mou, Quanbing; Sun, Mo; Yu, Chunyang; Li, Jianqi; Huang, Xiaohua; Zhu, Xinyuan; Yan, Deyue; Shen, Jian

2016-01-01

Nano drug delivery systems have emerged as promising candidates for cancer therapy, whereas their uncertainly complete elimination from the body within specific timescales restricts their clinical translation. Compared with hepatic clearance of nanoparticles, renal excretion of small molecules is preferred to minimize the agent-induced toxicity. Herein, we construct in vivo renal-clearable nanoparticles, which are self-assembled from amphiphilic small molecules holding the capabilities of magnetic resonance imaging (MRI) and chemotherapy. The assembled nanoparticles can accumulate in tumor tissues for their nano-characteristics, while the small molecules dismantled from the nanoparticles can be efficiently cleared by kidneys. The renal-clearable nanoparticles exhibit excellent tumor-inhibition performance as well as low side effects and negligible chronic toxicity. These results demonstrate a potential strategy for small molecular nano drug delivery systems with obvious anticancer effect and low-toxic metabolism pathway for clinical applications. PMID:27446502

Effects of endogenous small molecular compounds on the rheological properties, texture and microstructure of soymilk coagulum: Removal of phytate using ultrafiltration.

PubMed

Wang, Ruican; Guo, Shuntang

2016-11-15

This study aims to clarify the roles played by endogenous small molecular components in soymilk coagulation process and the properties of gels. Soymilk samples with decreasing levels of small molecules were prepared by ultrafiltration, to reduce the amount of phytate and salts. CaSO4-induced coagulation process was analyzed using rheological methods. Results showed that removal of free small molecules decreased the activation energy of protein coagulation, resulting in accelerated reaction and increased gel strength. However, too fast a reaction led to the drop in storage modulus (G'). Microscopic observation suggested that accelerated coagulation generated a coarse and non-uniform gel network with large pores. This network could not hold much water, leading to serious syneresis. Endogenous small molecules in soymilk were vital in the fine gel structure. Coagulation rate could be controlled by adjusting the amount of small molecules to obtain tofu products with the optimal texture. Copyright © 2016 Elsevier Ltd. All rights reserved.

Induction and reversal of myotonic dystrophy type 1 pre-mRNA splicing defects by small molecules.

PubMed

Childs-Disney, Jessica L; Stepniak-Konieczna, Ewa; Tran, Tuan; Yildirim, Ilyas; Park, HaJeung; Chen, Catherine Z; Hoskins, Jason; Southall, Noel; Marugan, Juan J; Patnaik, Samarjit; Zheng, Wei; Austin, Chris P; Schatz, George C; Sobczak, Krzysztof; Thornton, Charles A; Disney, Matthew D

2013-01-01

The ability to control pre-mRNA splicing with small molecules could facilitate the development of therapeutics or cell-based circuits that control gene function. Myotonic dystrophy type 1 is caused by the dysregulation of alternative pre-mRNA splicing due to sequestration of muscleblind-like 1 protein (MBNL1) by expanded, non-coding r(CUG) repeats (r(CUG)(exp)). Here we report two small molecules that induce or ameliorate alternative splicing dysregulation. A thiophene-containing small molecule (1) inhibits the interaction of MBNL1 with its natural pre-mRNA substrates. Compound (2), a substituted naphthyridine, binds r(CUG)(exp) and displaces MBNL1. Structural models show that 1 binds MBNL1 in the Zn-finger domain and that 2 interacts with UU loops in r(CUG)(exp). This study provides a structural framework for small molecules that target MBNL1 by mimicking r(CUG)(exp) and shows that targeting MBNL1 causes dysregulation of alternative splicing, suggesting that MBNL1 is thus not a suitable therapeutic target for the treatment of myotonic dystrophy type 1.

Induction and Reversal of Myotonic Dystrophy Type 1 Pre-mRNA Splicing Defects by Small Molecules

PubMed Central

Childs-Disney, Jessica L.; Stepniak-Konieczna, Ewa; Tran, Tuan; Yildirim, Ilyas; Park, HaJeung; Chen, Catherine Z.; Hoskins, Jason; Southall, Noel; Marugan, Juan J.; Patnaik, Samarjit; Zheng, Wei; Austin, Chris P.; Schatz, George C.; Sobczak, Krzysztof; Thornton, Charles A.; Disney, Matthew D.

2013-01-01

The ability to control pre-mRNA splicing with small molecules could facilitate the development of therapeutics or cell-based circuits that control gene function. Myotonic dystrophy type 1 (DM1) is caused by the dysregulation of alternative pre-mRNA splicing due to sequestration of muscleblind-like 1 protein (MBNL1) by expanded, non-coding r(CUG) repeats (r(CUG)exp). Here we report two small molecules that induce or ameliorate alternative splicing dysregulation. The thiophene-containing small molecule (1) inhibits the interaction of MBNL1 with its natural pre-mRNA substrates. Compound (2), a substituted naphthyridine, binds r(CUG)exp and displaces MBNL1. Structural models show that 1 binds MBNL1 in the Zn-finger domain and that 2 interacts with UU loops in r(CUG)exp. This study provides a structural framework for small molecules that target MBNL1 by mimicking r(CUG)exp and shows that targeting MBNL1 causes dysregulation of alternative splicing, suggesting that MBNL1 is thus not a suitable therapeutic target for the treatment of DM1. PMID:23806903

Selecting, Acquiring, and Using Small Molecule Libraries for High-Throughput Screening

PubMed Central

Dandapani, Sivaraman; Rosse, Gerard; Southall, Noel; Salvino, Joseph M.; Thomas, Craig J.

2015-01-01

The selection, acquisition and use of high quality small molecule libraries for screening is an essential aspect of drug discovery and chemical biology programs. Screening libraries continue to evolve as researchers gain a greater appreciation of the suitability of small molecules for specific biological targets, processes and environments. The decisions surrounding the make-up of any given small molecule library is informed by a multitude of variables and opinions vary on best-practices. The fitness of any collection relies upon upfront filtering to avoiding problematic compounds, assess appropriate physicochemical properties, install the ideal level of structural uniqueness and determine the desired extent of molecular complexity. These criteria are under constant evaluation and revision as academic and industrial organizations seek out collections that yield ever improving results from their screening portfolios. Practical questions including cost, compound management, screening sophistication and assay objective also play a significant role in the choice of library composition. This overview attempts to offer advice to all organizations engaged in small molecule screening based upon current best practices and theoretical considerations in library selection and acquisition. PMID:26705509

Selecting, Acquiring, and Using Small Molecule Libraries for High-Throughput Screening.

PubMed

Dandapani, Sivaraman; Rosse, Gerard; Southall, Noel; Salvino, Joseph M; Thomas, Craig J

The selection, acquisition and use of high quality small molecule libraries for screening is an essential aspect of drug discovery and chemical biology programs. Screening libraries continue to evolve as researchers gain a greater appreciation of the suitability of small molecules for specific biological targets, processes and environments. The decisions surrounding the make-up of any given small molecule library is informed by a multitude of variables and opinions vary on best-practices. The fitness of any collection relies upon upfront filtering to avoiding problematic compounds, assess appropriate physicochemical properties, install the ideal level of structural uniqueness and determine the desired extent of molecular complexity. These criteria are under constant evaluation and revision as academic and industrial organizations seek out collections that yield ever improving results from their screening portfolios. Practical questions including cost, compound management, screening sophistication and assay objective also play a significant role in the choice of library composition. This overview attempts to offer advice to all organizations engaged in small molecule screening based upon current best practices and theoretical considerations in library selection and acquisition.

Simulation-based cheminformatic analysis of organelle-targeted molecules: lysosomotropic monobasic amines.

PubMed

Zhang, Xinyuan; Zheng, Nan; Rosania, Gus R

2008-09-01

Cell-based molecular transport simulations are being developed to facilitate exploratory cheminformatic analysis of virtual libraries of small drug-like molecules. For this purpose, mathematical models of single cells are built from equations capturing the transport of small molecules across membranes. In turn, physicochemical properties of small molecules can be used as input to simulate intracellular drug distribution, through time. Here, with mathematical equations and biological parameters adjusted so as to mimic a leukocyte in the blood, simulations were performed to analyze steady state, relative accumulation of small molecules in lysosomes, mitochondria, and cytosol of this target cell, in the presence of a homogenous extracellular drug concentration. Similarly, with equations and parameters set to mimic an intestinal epithelial cell, simulations were also performed to analyze steady state, relative distribution and transcellular permeability in this non-target cell, in the presence of an apical-to-basolateral concentration gradient. With a test set of ninety-nine monobasic amines gathered from the scientific literature, simulation results helped analyze relationships between the chemical diversity of these molecules and their intracellular distributions.

Thermal Degradation of Small Molecules: A Global Metabolomic Investigation.

PubMed

Fang, Mingliang; Ivanisevic, Julijana; Benton, H Paul; Johnson, Caroline H; Patti, Gary J; Hoang, Linh T; Uritboonthai, Winnie; Kurczy, Michael E; Siuzdak, Gary

2015-11-03

Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). In this study the effect of heating was examined on a set of 64 small molecule standards and, separately, on human plasma metabolite extracts. The samples, either derivatized or underivatized, were heated at three different temperatures (60, 100, and 250 °C) at different exposure times (30 s, 60 s, and 300 s). All the samples were analyzed by liquid chromatography coupled to electrospray ionization mass spectrometry (LC/MS) and the data processed by XCMS Online ( xcmsonline.scripps.edu ). The results showed that heating at an elevated temperature of 100 °C had an appreciable effect on both the underivatized and derivatized molecules, and heating at 250 °C created substantial changes in the profile. For example, over 40% of the molecular peaks were altered in the plasma metabolite analysis after heating (250 °C, 300s) with a significant formation of degradation and transformation products. The analysis of 64 small molecule standards validated the temperature-induced changes observed on the plasma metabolites, where most of the small molecules degraded at elevated temperatures even after minimal exposure times (30 s). For example, tri- and diorganophosphates (e.g., adenosine triphosphate and adenosine diphosphate) were readily degraded into a mono-organophosphate (e.g., adenosine monophosphate) during heating. Nucleosides and nucleotides (e.g., inosine and inosine monophosphate) were also found to be transformed into purine derivatives (e.g., hypoxanthine). A newly formed transformation product, oleoyl ethyl amide, was identified in both the underivatized and derivatized forms of the plasma extracts and small molecule standard mixture, and was likely generated from oleic acid. Overall these analyses show that small molecules and metabolites undergo significant time-sensitive alterations when exposed to elevated temperatures, especially those conditions that mimic sample preparation and analysis in GC/MS experiments.

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Lexicographic goal programming and assessment tools for a combinatorial production problem.

DOT National Transportation Integrated Search

2008-01-01

NP-complete combinatorial problems often necessitate the use of near-optimal solution techniques including : heuristics and metaheuristics. The addition of multiple optimization criteria can further complicate : comparison of these solution technique...