Controlling the Biological Effects of Spermine Using a Synthetic Receptor

Polyamines play an important role in biology, yet their exact function in many processes is poorly understood. Artificial host molecules capable of sequestering polyamines could be useful tools for studying their cellular function. However, designing synthetic receptors with affinities sufficient to compete with biological polyamine receptors remains a huge challenge. Binding affinities of synthetic hosts are typically separated by a gap of several orders of magnitude from those of biomolecules. We now report that a dynamic combinatorial selection approach can deliver a synthetic receptor that bridges this gap. The selected receptor binds spermine with a dissociation constant of 22 nM, sufficient to remove it from its natural host DNA and reverse some of the biological effects of spermine on the nucleic acid. In low concentrations, spermine induces the formation of left-handed DNA, but upon addition of our receptor, the DNA reverts back to its right-handed form. NMR studies and computer simulations suggest that the spermine complex has the form of a pseudo-rotaxane. The spermine receptor is a promising lead for the development of therapeutics or molecular probes for elucidating spermine’s role in cell biology.

Systems chemistry: using thermodynamically controlled networks to assess molecular similarity

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background The assessment of molecular similarity is a key step in the drug discovery process that has thus far relied almost exclusively on computational approaches. We now report an experimental method for similarity assessment based on dynamic combinatorial chemistry. Results In order to assess molecular similarity directly in solution, a dynamic molecular network was used in a two-step process. First, a clustering analysis was employed to determine the network’s innate discriminatory ability. A classification algorithm was then trained to enable the classification of unknowns. The dynamic molecular network used in this work was able to identify thin amines and ammonium ions in a set of 25 different, closely related molecules. After training, it was also able to classify unknown molecules based on the presence or absence of an ethylamine group. Conclusions This is the first step in the development of molecular networks capable of predicting bioactivity based on an assessment of molecular similarity. </jats:sec

Affinity chromatography in dynamic combinatorial libraries: one-pot amplification and isolation of a strongly binding receptor

We report the one-pot amplification and isolation of a nanomolar receptor in a multibuilding block aqueous dynamic combinatorial library using a polymer-bound template. By appropriate choice of a poly(N,N-dimethylacrylamide)-based support, unselective ion-exchange type behaviour between the oppositely charged cationic guest and polyanionic hosts was overcome, such that the selective molecular recognition arising in aqueous solution reactions is manifest also in the analogous templated solid phase DCL syntheses. The ability of a polymer bound template to identify and isolate a synthetic receptor via dynamic combinatorial chemistry was not compromised by the large size of the library, consisting of well over 140 theoretical members, demonstrating the practical advantages of a polymer-supported DCL methodology

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Two-Vial, LC-MS Identification of Ephedrine Receptors from a Solution-Phase Dynamic Combinatorial Library of over 9000 Components

Reports on dynamic combinatorial chemistry have almost exclusively involved small libraries of 10-100 compounds. We now show how more than 9000 compounds can be screened in a single LC-MS analysis to reveal a series of new receptors that bind ephedrine in water. These results demonstrate the feasibility of screening DCLs that are substantially larger than the solution-phase libraries reported thus far

The Impact of the Size of Dynamic Combinatorial Libraries on the Detectability of Molecular Recognition Induced Amplification

Despite well over a decade of research on dynamic combinatorial chemistry it is still unclear whether large libraries are more or less likely to yield strong binders than small libraries. We have now addressed this question by simulating a set of libraries containing from 65 to 4828 compounds under a range of different building block and template concentrations. We investigated the effect of library size on (i) the probability of detecting any amplification; (ii) the probability of detecting the strongest binding library member present; and (iii) the binding affinity of the most amplified detectable library member. The results indicate bigger libraries are more likely to produce better binders and that the affinity of the best binders identified rises more rapidly than expected statistically on the basis of the number of screened library members. This implies that it should be advantageous to work with DCLs that are much larger than the vast majority reported thus far.

Systems chemistry

The study of complex mixtures of interacting synthetic molecules has historically not received much attention from chemists, even though research into complexity is well established in the neighbouring fields. However, with the huge recent interest in systems biology and the availability of modern analytical techniques this situation is likely to change. In this tutorial review we discuss some of the incentives for developing systems chemistry and we highlight the pioneering work in which molecular networks are making a splash. A distinction is made between networks under thermodynamic and kinetic control. The former include dynamic combinatorial libraries while the latter involve pseudo-dynamic combinatorial libraries, oscillating reactions and networks of autocatalytic and replicating compounds. These studies provide fundamental insights into the organisational principles of molecular networks and how these give rise to emergent properties such as amplification and feedback loops, and may eventually shed light on the origin of life. The knowledge obtained from the study of molecular networks should ultimately enable us to engineer new systems with properties and functions unlike any conventional materials.

Estimating Equilibrium Constants for Aggregation from the Product Distribution of a Dynamic Combinatorial Library

Multicomponent chemical systems that exhibit a network of covalent and intermolecular interactions may produce interesting and often unexpected chemical or physical behavior. The formation of aggregates is a well-recognized example and presents a particular analytical challenge. We now report the development of a numerical fitting method capable of estimating equilibrium constants for the formation of aggregates from the product distribution of a dynamic combinatorial library containing self-recognizing library members.

A Synthetic Receptor for Nicotine from a Dynamic Combinatorial Library

Designing synthetic receptors that bind biologically relevant guests in an aqueous solution remains a considerable challenge. We now report a new synthetic receptor for nicotine, selected from a dynamic combinatorial library, that binds this guest in water at neutral pH through a combination of hydrophobic and π–π interactions.