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.     

Structure-based design and combinatorial chemistry yield low nanomolar inhibitors of cathepsin D

Background: The identification of potent small molecule ligands to receptors and enzymes is one of the major goals of chemical and biological research. Two powerful new tools that can be used in these efforts are combinatorial chemistry and structure-based design. Here we address how to join these methods in a design protocol that produces libraries of compounds that are directed against specific macromolecular targets. The aspartyl class of proteases, which is involved in numerous biological processes, was chosen to demonstrate this effective procedure.Results: Using cathepsin D, a prototypical aspartyl protease, a number of low nanomolar inhibitors were rapidly identified. Although cathepsin D is implicated in a number of therapeutically relevant processes, potent nonpeptide inhibitors have not been reported previously. The libraries, synthesized on solid support, displayed nonpeptide functionality about the (hydroxyethyl)amine isostere. The (hydroxyethyl)amine isostere, which targets the aspartyl protease class, is a stable mimetic of the tetrahedral intermediate of amide hydrolysis. Structure-based design, using the crystal structure of cathepsin D complexed with the peptide-based natural product pepstatin, was used to select the building blocks for the library synthesis. The library yielded a ‘hit rate’ of 6–7% at 1 μM inhibitor concentrations, with the most potent compound having a K_i value of 73 nM. More potent, nonpeptide inhibitors (K_i = 9–15 nM) of cathepsin D were rapidly identified by synthesizing and screening a small second generation library.Conclusions: The success of these studies clearly demonstrates the power of coupling the complementary methods of combinatorial chemistry and structure-based design. We anticipate that the general approaches described here will be successful for other members of the aspartyl protease class and for many other enzyme classes.     

Structure‐Based Design of Inhibitors of the Aspartic Protease Endothiapepsin by Exploiting Dynamic Combinatorial Chemistry

Structure‐based design (SBD) can be used for the design and/or optimization of new inhibitors for a biological target. Whereas de novo SBD is rarely used, most reports on SBD are dealing with the optimization of an initial hit. Dynamic combinatorial chemistry (DCC) has emerged as a powerful strategy to identify bioactive ligands given that it enables the target to direct the synthesis of its strongest binder. We have designed a library of potential inhibitors (acylhydrazones) generated from five aldehydes and five hydrazides and used DCC to identify the best binder(s). After addition of the aspartic protease endothiapepsin, we characterized the protein‐bound library member(s) by saturation‐transfer difference NMR spectroscopy. Cocrystallization experiments validated the predicted binding mode of the two most potent inhibitors, thus demonstrating that the combination of de novo SBD and DCC constitutes an efficient starting point for hit identification and optimization.     

Solid-phase combinatorial library of norstatine-type isosters by the nitroaldol reaction

A combinatorial library of norstatine-type peptide isosters as putative inhibitors of aspartic proteases is presented. The library was synthesized using a split-and-mix strategy designed to afford a one-bead-two-compounds library with the isosteric elements positioned centrally in peptide chains. Application of ladder synthesis during library generation enabled structure identification by MALDI-TOF mass spectroscopy. The library was screened against aspartic protease renin, and two types of inhibitors were identified, that is, XXX-psi[CHRCHOH)-XXX and an aldehyde arising from unreacted starting material. Selected hits were resynthesized and assayed in solution, revealing inhibitors of nanomolar potency.     

Synthesis of novel bridged dinitrogen heterocycles and their evaluation as potential fragments for the design of biologically active compounds

A library of saturated bridged heterocycles based on 3,6-diazabicyclo[3.2.1]octane-2,4-dione and bispidine scaffolds (mean compound molecular weight is approximately 300 Da) with up to three stereocenters and four diversity points has been synthesized. Synthetic scaffold modifications leading to an increase in molecular complexity were studied. Well-defined stereochemical structures of both compound sets was confirmed by X-ray studies and halogenoaryl substituents were inserted appropriately for the design of novel non-basic serine protease inhibitors. Comprehensive molecular modeling has been performed for all synthesized compounds giving rationales of ligand–enzyme interactions with thrombin and trypsin. Biological testing confirmed moderate inhibitory activity of halogen-substituted saturated diazabicyclic small molecules towards thrombin.     

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment‐Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC₅₀ value of 54 nm , which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization.     

Analysis and prediction of combinatorial chemistry synthesis and screening data

The goal of combinatorial chemistry is to simultaneously synthesize sets of compounds possessing properties that are then distinguished through screening. As the size of a compound set increases, data analysis becomes more challenging. Analysis of Variance (ANOVA) is an accepted statistical method that offers a straightforward solution to this problem. Two steps encountered by combinatorial scientists appear well suited to ANOVA: the prediction of synthetic outcomes (purity and yield) of set members and the analysis of screening data to identify combinations of reagent inputs that result in molecules with a desired property. To illustrate, a subset of a combinatorial array, referred to as a reaction rehearsal set, is evaluated to create a model predictive of the individual synthetic outcomes of the full matrix. In a second exercise, the biochemical screening data obtained from a combinatorial library is analyzed to identify reagent interactions that result in molecules possessing the sought activity.     

Parallel screening and activity profiling with HIV protease inhibitor pharmacophore models

Parallel Screening has been introduced as an in silico method to predict the potential biological activities of compounds by screening them with a multitude of pharmacophore models. This study presents an early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling. An extensive set of HIV protease inhibitor pharmacophore models was used to screen a selection of active and inactive compounds. Furthermore, we aimed to address the usually critically eyed point, whether it is possible in a parallel screening system to differentiate between similar molecules/molecules acting on closely related proteins, and therefore we incorporated a collection of other protease inhibitors including aspartic protease inhibitors. The results of the screening experiments show a clear trend toward most extensive retrieval of known active ligands, followed by the general protease inhibitors and lowest recovery of inactive compounds.     

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.     

Virtual darwinian drug design: QSAR inverse problem, virtual combinatorial chemistry, and computational screening

The generation of diversity and its further selection by an external system is a common mechanism for the evolution of the living species and for the current drug design methods. This assumption allows us to label the methods based on generation and selection of molecular diversity as "Darwinian" ones, and to distinguish them from the structure-based, structure-modulation approaches. An example of a Darwinian method is the inverse QSAR. It consists of the computational generation of candidate chemical structures and their selection according to a previously established QSAR model. New trends in the field of combinatorial chemical syntheses comprise the concepts of virtual combinatorial synthesis and virtual or computational screening. Virtual combinatorial synthesis, closely related to inverse QSAR, can be defined as the computational simulation of the generation of new chemical structures by using a combinatorial strategy to generate a virtual library. Virtual screening is the selection of chemical structures having potential desirable properties from a database or virtual library in order to be synthesized and assayed. This review is mainly focused on graph theoretical drug design approaches, but a survey with key references is provided that covers other simulation methods.     

Multiobjective optimization of combinatorial libraries

Combinatorial chemistry and high-throughput screening have caused a fundamental shift in the way chemists contemplate experiments. Designing a combinatorial library is a controversial art that involves a heterogeneous mix of chemistry, mathematics, economics, experience, and intuition. Although there seems to be little agreement as to what constitutes an ideal library, one thing is certain: only one property or measure seldom defines the quality of the design. In most real-world applications, a good experiment requires the simultaneous optimization of several, often conflicting, design objectives, some of which may be vague and uncertain. In this paper, we discuss a class of algorithms for subset selection rooted in the principles of multiobjective optimization. Our approach is to employ an objective function that encodes all of the desired selection criteria, and then use a simulated annealing or evolutionary approach to identify the optimal (or a nearly optimal) subset from among the vast number of possibilities. Many design criteria can be accommodated, including diversity, similarity to known actives, predicted activity and/or selectivity determined by quantitative structure-activity relationship (QSAR) models or receptor binding models, enforcement of certain property distributions, reagent cost and availability, and many others. The method is robust, convergent, and extensible, offers the user full control over the relative significance of the various objectives in the final design, and permits the simultaneous selection of compounds from multiple libraries in full- or sparse-array format.     

Redesign of protein domains using one-bead-one-compound combinatorial chemistry

A novel combinatorial strategy for the redesign of proteins based on the strength and specificity of intra- and interprotein interactions is described. The strategy has been used to redesign the hydrophobic core of the B domain of protein A. Using one-bead-one-compound combinatorial chemistry, 300 analogues of the C-terminal alpha-helix of the B domain, H3x, have been synthesized using a biocompatible resin and the HMFS linker, allowing the screening to occur while the peptides were bound to the resin. The screening was based on the ability of the H3x analogues to interact with the N-terminal helices of the B domain, H1-H2, and retain the native B domain activity, that is binding to IgG. Eight different analogues containing some nonconservative mutations were obtained from the library, the two most frequent of which, H3P1 and H3P2, were studied in detail. CD analysis revealed that the active analogues interact with H1-H2. To validate the redesign strategy the covalent modified domains H1-H2-H3P1 and H1-H2-H3P2 were synthesized and characterized. CD and NMR analysis revealed that they had a unique, stable, and well-defined three-dimensional structure similar to that for the wild-type B domain. This combinatorial strategy allows us to select for redesigned proteins with the desired activity or the desired physicochemical properties provided the right screening test is used. Furthermore, it is rich in potential for the chemical modification of proteins overcoming the drawbacks associated with the total synthesis of large protein domains.     

Strategy for discovering chemical inhibitors of human cyclophilin a: focused library design, virtual screening, chemical synthesis and bioassay

The discovery of cyclophilin A (CypA) inhibitor is now of special interest in the treatment of immunological disorders. In this work, using a strategy integrating focused combinatorial library design, virtual screening, chemical synthesis, and bioassay, a series of novel small molecular CypA inhibitors have been discovered. First, using the fragments taken from our previously discovered CypA inhibitors (Bioorg. Med. Chem. 2006, 14, 2209-2224) as building blocks, we designed a focused combinatorial library containing 255 molecules employing the LD1.0 program (J. Comb. Chem. 2005, 7, 398-406) developed by us. Sixteen compounds (1a-e, 2a-b, 3a-b, and 4a-g) were selected by using virtual screening against the X-ray crystal structure of CypA as well as druglike analysis for further synthesis and bioassay. All these sixteen molecules are CypA binders with binding affinities (K(D) values) ranging from 0.076 to 41.0 microM, and five of them (4a, 4c, and 4e-g) are potent CypA inhibitors with PPIase inhibitory activities (IC(50) values) of 0.25-6.43 microM. The hit rates for binders and inhibitors are as high as 100% and 31.25%, respectively. Remarkably, both the binding affinity and inhibitory activity of the most potent compound increase approximately 10 times than that of the most active compound discovered previously. The high hit rate and the high potency of the new CypA inhibitors demonstrated the efficiency of the strategy for focused library design and screening. In addition, the novel chemical entities reported in this study could be leads for discovering new therapies against the CypA pathway.     

Focused combinatorial library design based on structural diversity, druglikeness and binding affinity score

The advent of focused library and virtual screening has reduced the disadvantage of combinatorial chemistry and changed it to a realizable and cost-effective tool in drug discovery. Usually, genetic algorithms (GAs) are used to quickly finding high-scoring molecules by sampling a small subset of the total combinatorial space. Therefore, scoring functions play essential roles in focused library design. Reported here is our initial attempt to establish a new approach for generating a target-focused library using the combination of the scores of structural diversity and binding affinity with our newly improved drug-likeness scoring functions. Meanwhile, a software package, named LD1.0, was developed on the basis of the new approach. One test on a cyclooxygenase (COX)2-focused library successfully reproduced the structures that have been experimentally studied as COX2-selective inhibitors. Another test is on a peroxisome proliferator-activated receptors gamma-focused library design, which not only reproduces the key fragments in the approved (thiazolidinedione) TZD drugs, but also generates some new structures that are more active than the approved drugs or published ligands. Both of the two tests took approximately 15% of the running time of the ordinary molecular docking method. Thus, our new approach is an effective, reliable, and practical way for building up a properly sized focused library with a high hit rate, novel structure, and good ADME/T profile.     

Solid-phase assembly and in situ screening of protein tyrosine phosphatase inhibitors

A highly efficient solid-phase strategy for assembly of small molecule inhibitors against protein tyrosine phosphatase 1B (PTP1B) is described. The method is highlighted by its simplicity and product purity. A 70-member combinatorial library of analogues of a known PTP1B inhibitor has been synthesized, which upon direct in situ screening revealed a potent inhibitor ( Ki = 7.0 microM) against PTP1B.     

High-speed optimization of inhibitors of the malarial proteases plasmepsin I and II

Four focused libraries targeted for inhibition of the malarial proteases plasmepsin I and II were designed, synthesized, purified, and screened. Selected carboxylic acids and organometallic reactants with diverse physical properties were attached to the hydroxylethylamine scaffold in the P3 and P1' positions to furnish inhibitors with highly improved activity. The concept of controlled and sequential microwave heating was employed for rapid library generation. This combinatorial optimization protocol afforded plasmepsin inhibitors not only with K(i) values in the low nanomolar range, but also with high selectivity versus the human protease cathepsin D. With this class of inhibitory agents, modifications of the P1' substituents resulted in the largest impact on the plasmepsin/cathepsin D selectivity.     

Combinatorics of combinatorial chemistry

The hot topic among medicinal chemists today is a novel technique for chemical synthesis in drug research called combinatorial chemistry, where usually a core structure and some building‐block molecules are given and all combinatorially possible combinations are produced. The resulting set of compounds (called a library) can afterwards be systematically screened for a desired biological activity. In this paper we discuss the applications of the mathematical discipline of combinatorics to this process, especially an algorithm for the exhaustive and redundancy‐free generation of a combinatorial library as well as equations for the enumeration of library sizes. This revised version was published online in July 2006 with corrections to the Cover Date.     

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.     

Rapid identification of substrates for novel proteases using a combinatorial peptide library

Fluorogenic substrates for assaying novel proteolytic enzymes could be rapidly identified using an easy, solid-phase combinatorial assay technology. The methodology was validated with leader peptidase of Escherichia coli using a subset of an intramolecularly quenched fluorogenic peptide library. The technique was extended toward the discovery of substrates for a new aspartic protease of pharmaceutical relevance (human napsin A). We demonstrated for the first time known to us that potent fluorogenic substrates can be discovered using extracts of cells expressing recombinant enzyme to screen the peptide library. The straightforward and rapid optimization of protease substrates greatly facilitates the drug discovery process by speeding up the development of high throughput screening assays and thus helps more effective exploitation of the enormous body of information and chemical structures emerging from genomics and combinatorial chemistry technologies.     

Immunoassays: biological tools for high throughput screening and characterisation of combinatorial libraries

In the demanding field of proteomics, there is an urgent need for affinity-catcher molecules to implement effective and high throughput methods for analysing the human proteome or parts of it. Antibodies have an essential role in this endeavour, and selection, isolation and characterisation of specific antibodies represent a key issue to meet success. Alternatively, it is expected that new, well-characterised affinity reagents generated in rapid and cost-effective manners will also be used to facilitate the deciphering of the function, location and interactions of the high number of encoded protein products. Combinatorial approaches combined with high throughput screening (HTS) technologies have become essential for the generation and identification of robust affinity reagents from biological combinatorial libraries and the lead discovery of active/mimic molecules in large chemical libraries. Phage and yeast display provide the means for engineering a multitude of antibody-like molecules against any desired antigen. The construction of peptide libraries is commonly used for the identification and characterisation of ligand-receptor specific interactions, and the search for novel ligands for protein purification. Further improvement of chemical and biological resistance of affinity ligands encouraged the "intelligent" design and synthesis of chemical libraries of low-molecular-weight bio-inspired mimic compounds. No matter what the ligand source, selection and characterisation of leads is a most relevant task. Immunological assays, in microtiter plates, biosensors or microarrays, are a biological tool of inestimable value for the iterative screening of combinatorial ligand libraries for tailored specificities, and improved affinities. Particularly, enzyme-linked immunosorbent assays are frequently the method of choice in a large number of screening strategies, for both biological and chemical libraries.