Combinatorial–computational–chemoinformatics (C3) approach to finding and analyzing low-energy tautomers

Finding the most stable tautomer or a set of low-energy tautomers of molecules is critical in many aspects of molecular modelling or virtual screening experiments. Enumeration of low-energy tautomers of neutral molecules in the gas-phase or typical solvents can be performed by applying available organic chemistry knowledge. This kind of enumeration is implemented in a number of software packages and it is relatively reliable. However, in esoteric cases such as charged molecules in uncommon, non-aqueous solvents there is simply not enough available knowledge to make reliable predictions of low energy tautomers. Over the last few years we have been developing an approach to address the latter problem and we successfully applied it to discover the most stable anionic tautomers of nucleic acid bases that might be involved in the process of DNA damage by low-energy electrons and in charge transfer through DNA. The approach involves three steps: (1) combinatorial generation of a library of tautomers, (2) energy-based screening of the library using electronic structure methods, and (3) analysis of the information generated in step (2). In steps 1–3 we employ combinatorial, computational and chemoinformatics techniques, respectively. Therefore, this hybrid approach is named “Combinatorial*Computational*Chemoinformatics”, or just abbreviated as C³ (or C-cube) approach. This article summarizes our developments and most interesting methodological aspects of the C³ approach. It can serve as an example how to identify the most stable tautomers of molecular systems for which common chemical knowledge had not been sufficient to make definite predictions.     

Microfluidic platform for combinatorial synthesis in picolitre droplets

This paper presents a droplet-based microfluidic platform for miniaturized combinatorial synthesis. As a proof of concept, a library of small molecules for early stage drug screening was produced. We present an efficient strategy for producing a 7 × 3 library of potential thrombin inhibitors that can be utilized for other combinatorial synthesis applications. Picolitre droplets containing the first type of reagent (reagents A(1), A(2), …, A(m)) were formed individually in identical microfluidic chips and then stored off chip with the aid of stabilizing surfactants. These droplets were then mixed to form a library of droplets containing reagents A(1-m), each individually compartmentalized, which was reinjected into a second microfluidic chip and combinatorially fused with picolitre droplets containing the second reagent (reagents B(1), B(2), …, B(n)) that were formed on chip. The concept was demonstrated with a three-component Ugi-type reaction involving an amine (reagents A(1-3)), an aldehyde (reagents B(1-7)), and an isocyanide (held constant), to synthesize a library of small molecules with potential thrombin inhibitory activity. Our technique produced 10(6) droplets of each reaction at a rate of 2.3 kHz. Each droplet had a reaction volume of 3.1 pL, at least six orders of magnitude lower than conventional techniques. The droplets can then be divided into aliquots for different downstream screening applications. In addition to medicinal chemistry applications, this combinatorial droplet-based approach holds great potential for other applications that involve sampling large areas of chemical parameter space with minimal reagent consumption; such an approach could be beneficial when optimizing reaction conditions or performing combinatorial reactions aimed at producing novel materials.     

The measurement of molecular diversity: A three-dimensional approach

Summary This paper describes a method for selecting a small, highly diverse subset from a large pool of molecules. The method has been employed in the design of combinatorial synthetic libraries for use in high-throughput screening for pharmaceutical lead generation. It computes diversity in terms of the main factors relevant to ligand-protein binding, namely the three-dimensional arrangement of steric bulk and of polar functionalities and molecular entropy. The method was used to select a set of 20 carboxylates suitable for use as side-chain precursors in a polyamine-based library. The method depends on estimates of various physical-chemical parameters involved in ligand-protein binding; experiments examined the sensitivity of the method to these parameters. This paper compares the diversity of randomly and rationally selected side-chain sets; the results suggest that careful design of synthetic combinatorial libraries may increase their effectiveness several-fold.     

Ligand-based combinatorial design of selective purinergic receptor (A2A) antagonists using self-organizing maps

A virtual screening procedure based on a topological pharmacophore similarity metric and self-organizing maps (SOM) was developed and applied to optimizing combinatorial products functioning as P(1) purinergic receptor antagonists. The target was the human A(2A) receptor. A SOM was developed using a set of biologically tested molecules to establish a preliminary structure-activity relationship. A combinatorial library design was performed by projecting virtually assembled new molecules onto the SOM. A small focused library of 17 selected combinatorial products was synthesized and tested. On average, the designed structures yielded a 3-fold smaller binding constant ( approximately 33 vs approximately 100 nM) and 3.5-fold higher selectivity (50 vs 14) than the initial library. The most selective compound obtained revealed a 121-fold relative selectivity for A(2A) with K(i) (A(2A)) = 2.4 nM, and K(i) (A(1)) = 292 nM. This result demonstrates that it was possible to design a small, activity-enriched focused library with an improved property profile using the SOM virtual screening approach. The strategy might be particularly useful in projects in which structure-based design cannot be applied because of a lack of receptor structure information, for example, in the many projects aiming at finding new GPCR modulators.     

Cheminformatics analysis of organic substituents: identification of the most common substituents,calculation of substituent properties,and automatic identification of drug-like bioisosteric groups

A large set of more than 3 million molecules was processed to find all the organic substituents contained in the set and to identify the most common ones. During the analysis, 849 574 unique substituents were found. Extrapolated to the number of known organic molecules, this result suggests that about 3.1 million substituents are known. Based on these findings the size of virtual organic chemistry space accessible using currently known synthetic methods is estimated to be between 10(20) and 10(24) molecules. The extracted substituents were characterized by calculated electronic, hydrophobic, steric, and hydrogen bonding properties as well as by the drug-likeness index. Various possible applications of such a large database of drug-like substituents characterized by calculated properties are discussed and illustrated by reference to a Web-based tool for automatic identification of bioisosteric groups.     

Analysing the output from primary screening

From a perspective of process knowledge and enhancement, the analysis of the results of biological screening should not be limited to the outcome of specific projects, but additionally encompass a process centric view. Summarising outcomes across multiple projects is a powerful tool to gain a greater understanding of biological screening that will also enable optimisation of the strategy for specific projects or target classes. We have analysed a set of 73,651 compounds with reproducible (confirmed) results from 63 high-throughput screening (HTS) campaigns to reveal the underlying trends in the population of active compounds. We have focused on the overall physico-chemical profile of compound populations derived from biological screening since the in vivo activity of drug molecules is the result of physico-chemical and structural properties of the compound.     

Pharmacophore features of potential drugs

Drug discovery efforts rely increasingly on the identification of quality lead compounds through high-throughput synthesis and screening. However, large-scale random libraries have yielded only a low number of quality lead molecules. To address this shortcoming researchers have paid more attention to the concept of "drug-likeness" of molecules in combinatorial and screening libraries. Database profiling and analysis methods have been employed to identify the structural features of known drug molecules. Neural networks and machine learning methods help to distinguish between drugs and nondrugs. More recently, database-independent pharmacophore filters have been introduced that provide simple intuitive rules to classify potential drugs.     

Successful screening of large encoded combinatorial libraries leading to the discovery of novel p38 MAP kinase inhibitors

Screening of more than 2 million compounds comprising 41 distinct encoded combinatorial libraries revealed a novel structural class of p38 mitogen-activated protein (MAP) kinase inhibitors. The methodology used for screening large encoded combinatorial libraries combined with the statistical interpretation of screening results is described. A strong preference for a particular triaminotriazine aniline amide was discovered based on biological activity observed in the screening campaign. Additional screening of a focused follow-up combinatorial library yielded data expanding the unique combinatorial SAR and emphasizing an extraordinary preference for this particular building block and structural class. The preference is further highlighted when the p38 inhibitor data set is compared to data obtained for a panel of other kinases.     

Guidelines for the Routine Application of the Peptide Hits Technique

A set of guidelines has been developed for using the peptide hits technique (PHT) as a semi-quantitative screening tool for the identification of proteins that change in abundance in a complex mixture. The dataset that formed the basis for these experiments was created using a cell lysate derived from the yeast Saccharomyces cerevisiae, spiked at various levels with serum albumin (BSA), and analyzed by LC/MS/MS and SEQUEST. Knowing that the level of only one protein (BSA) actually changed in the mixture allowed for the development and refinement of the necessary bioinformatics and statistical analyses, e.g., principal component analysis (PCA), normalization, and analysis of variation (ANOVA). As expected, the number of BSA peptide hits changed in proportion to the amount of BSA added to the sample. PCA was able to clearly distinguish between the spiked samples and the untreated sample, indicating that PCA may be able to classify samples, e.g., healthy versus diseased, in future experiments. The use of an endogenous "housekeeping" protein was found to be superior to the use of total hits for data normalization prior to analysis. An ANOVA based model readily identified BSA as a protein of interest, that is, one likely to be changing from amongst the background proteins, indicating that an ANOVA model may be able to identify individual proteins in target or biomarker discovery experiments. General guidelines based on these combined observations are set forth for future analyses and the rapid screening for candidate proteins of interest.     

Pharmacophore features distributions in different classes of compounds

A pharmacophore analysis approach was used to investigate and compare different classes of compounds relevant to the drug discovery process (specifically, drug molecules, compounds in high throughput screening libraries, combinatorial chemistry building blocks and nondrug molecules). The distributions for a set of pharmacophore features including hydrogen bond acceptors, hydrogen bond donors, negatively ionizable centers, positively ionizable centers and hydrophobic points, were generated and examined. Significant differences were observed between the pharmacophore profiles obtained for the drug molecules and those obtained for the high-throughput screening compounds, which appear to be closely related to the nondrug pharmacophore distribution. It is suggested that the analysis of pharmacophore profiles could be used as an additional tool for the property-based optimization of compound selection and library design processes, thus improving the odds of success in lead discovery projects.     

A novel frequency distribution selection method for efficient plate layout of a diverse combinatorial library.

A deterministic method (frequency distribution method) for selecting compounds from a partitioned virtual combinatorial library for efficient synthesis is presented here. The method is based on reagent frequency analysis and can be applied to any library of molecules distributed in any given partitioned chemical space (cluster, cell-based, etc.). Compound selection by reagent frequency distribution can produce a unique, diverse set of molecules that adequately represents the library while requiring the least amount of compounds to be synthesized and minimizing the number of different reagents that must be used. This method also provides a practical solution to the configuration of plate layout. Because the method essentially identifies "expensive" regions in the chemical space to synthesize for a desired diversity or similarity coverage, decisions concerning the necessity to synthesize these compounds can be addressed. Minimum compound generation and efficient plate layout results in savings both in time of synthesis and cost of materials. This method always results in a discrete solution, which can be used for any given library size as well as any combination of reagents and is also readily adaptable to robotic automation.     

Compound set enrichment: a novel approach to analysis of primary HTS data

The main goal of high-throughput screening (HTS) is to identify active chemical series rather than just individual active compounds. In light of this goal, a new method (called compound set enrichment) to identify active chemical series from primary screening data is proposed. The method employs the scaffold tree compound classification in conjunction with the Kolmogorov-Smirnov statistic to assess the overall activity of a compound scaffold. The application of this method to seven PubChem data sets (containing between 9389 and 263679 molecules) is presented, and the ability of this method to identify compound classes with only weakly active compounds (potentially latent hits) is demonstrated. The analysis presented here shows how methods based on an activity cutoff can distort activity information, leading to the incorrect activity assignment of compound series. These results suggest that this method might have utility in the rational selection of active classes of compounds (and not just individual active compounds) for followup and validation.     

Retrospective analysis of an experimental high-throughput screening data set by recursive partitioning

With the emergence of combinatorial chemistry, whether based on parallel, mixture, solution, or solid phase chemistry, it is now possible to generate large numbers of diverse or focused compound libraries. In this paper we aim to demonstrate that it is possible to design targeted libraries by applying nonparametric statistical methods, recursive partitioning in particular, to large data sets containing thousands of compounds and their associated biological data. Moreover, when applied to an experimental high-throughput screening (HTS) data set, our data strongly suggest that this method can improve the hit rate of our primary screens (about 4- to 5-fold) while increasing screening efficiency: less than one-fifth of the complete selection needs to be screened in order to identify about 75% of all actives present.     

Mass spectrometry and combinatorial chemistry: a short outline.

The rapid evolution of combinatorial chemistry in recent years has led to a dramatic improvement in synthetic capabilities. The goal is to accelerate the discovery of molecules showing affinity against a target, such as an enzyme or a receptor, through the simultaneous synthesis of a great number of structurally diverse compounds. This is done by generating combinatorial libraries containing as many as hundreds or thousands of compounds. The need to test all these compounds led to the development of high-throughput screening (HTS) techniques, and also high-throughput analytical techniques capable of assessing the occurrence, structure and purity of the products. In order to be applied effectively to the characterization of combinatorial libraries, an analytical technique must be adequately sensitive (to analyse samples which are typically produced in nanomole amounts or less), fast, affordable and easy to automate (to minimize analysis time and operator intervention). Although no method alone can meet all the analytical challenges underlying this task, the recent progress in mass spectrometric (MS) instrumentation renders this technique an essential tool for scientists working in this area. We describe here relevant aspects of the use of MS in combinatorial technologies, such as current methods of characterization, purification and screening of libraries. Some examples from our laboratory deal with the analysis of pooled oligomeric libraries containing n x 324(n = 1, 2) compounds, using both on-line high-performance liquid chromatography/MS with an ion trap mass spectrometer, and direct infusion into a triple quadrupole instrument. In the first approach, MS and product ion MS/MS with automatic selection of the precursor were performed in one run, allowing library confirmation and structural elucidation of unexpected by-products. The second approach used MS scans to characterize the entire library and also precursor ion and neutral loss scans to detect selectively components with given structural characteristics.     

Molecular forceps from combinatorial libraries prevent the farnesylation of Ras by binding to its carboxyl terminus

INTRODUCTION: Ras is one of the major oncogenes. In order to function properly it has to undergo post-translational processing at its carboxyl terminus. It has been shown that inhibitors of farnesyl transferase, the first enzyme in the processing chain, can suppress the transforming activity of oncogenic Ras. RESULTS: We have identified molecular forceps, branched peptidic molecules, from combinatorial libraries that bind to the carboxyl terminus of Ras and interfere with its farnesylation without inhibiting the farnesyl transferase. The active molecules were selected by a screening against the carboxy-terminal octapeptide of Ras. CONCLUSIONS: The implications of our findings are twofold. First, we demonstrate that it is possible to prevent enzymatic transformations by blocking the enzyme's access to its substrate using a synthetic small molecule to mask the substrate. Second, we show that it is feasible to derive molecules from combinatorial libraries that bind a specific epitope on a protein by selecting these molecules with the isolated peptide epitope.     

Creation of hoop- and bowl-shaped benzenoid systems by selective detraction of [60]fullerene conjugation. [10]cyclophenacene and fused corannulene derivatives

Selective penta-addition of a methylcopper reagent followed by addition of a phenylcopper reagent to a suitably modified synthetic intermediate results in creation of 40pi-electron systems-hoop- and bowl-shaped cyclic benzenoid compounds, [10]cyclophenacene, and dibenzo-fused corannulene derivatives. The 40pi-electron cyclophenacene derivatives have been found to be chemically stable, yellow-colored, luminescent (560 nm), and EPR-silent. X-ray crystallographic analysis provided precision structural data sets. The dibenzo-fused corannulene derivatives exhibit blue-green (460 nm) to red (649 nm) fluorescence.     

High Throughput Strategies for the Discovery and Optimization of Catalytic Reactions

Homogeneous catalysis has provided chemists with numerous transformations to enable rapid construction of organic molecules. However, these reactions are complex, requiring multiple substrate‐dependent mechanistic steps to operate in harmony under a single set of experimental conditions. As a consequence, synthetic chemists often carry out laborious, empirical screening to identify suitable catalysts, solvents, and additives to achieve high yields and selectivity. In this Minireview, recently developed tools, technologies, and strategies will be described that improve this development process. In particular, the application of high throughput techniques to run more experiments, experimental design principles to access better data, and statistical tools to provide predictive models will be discussed.     

Aptasensors – the future of biosensing?

Aptamers are artificial nucleic acid ligands that can be generated against amino acids, drugs, proteins and other molecules. They are isolated from combinatorial libraries of synthetic nucleic acid by an iterative process of adsorption, recovery and reamplification. Aptamers, first reported in 1990, are attracting interest in the areas of therapeutics and diagnostics and offer themselves as ideal candidates for use as biocomponents in biosensors (aptasensors), possessing many advantages over state of the art affinity sensors. The properties of aptamers, their applicability to biosensor technology, current research and future prospects are addressed in this short review.     

Direct screening of a dynamic combinatorial library using mass spectrometry

A dynamic combinatorial library (DCL) screening approach is described that permits direct identification of the effective (from ineffective) combination of building blocks in the equilibrating DCL. The approach uses Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) together with sustained off-resonance irradiation collision activated dissociation (SORI-CAD) to detect noncovalent protein-DCL ligand complexes under native conditions. It was shown that in a single, rapid experiment one could concurrently identify all the ligands of interest from the DCL against a background of inactive DCL ligands while still in the presence of the target protein. This result has demonstrated that mass spectrometry may provide a fast preliminary screening approach to identify DCL candidates for later verification with more traditional but time-consuming analysis. The MS/MS enables DCL mixtures to be effectively deconvoluted without the need for either chromatography, synthesis of DCL sub-libraries, conversion of the DCL to a static library, or disruption of the protein-ligand complexes before analysis--all typically necessary for the current screening method for DCLs.