PEG based resins for protease drug discovery synthesis, screening and analysis of combinatorial on-bead libraries

This review will cover the entire hit identification process performed with biocompatible, aqueous solvated, poly[ethylene glycol] (PEG) based resins - from synthesis, through screening, to analysis. The different types of resins (including their preparation) will be discussed and compared individually. Examples of one-bead-one-compound substrate libraries will be presented, as will one-bead-two-compounds libraries used for the discovery of enzyme inhibitors. The review includes a section covering organic and bio-organic reactions performed on all-PEG resins and discusses on-bead screening of the libraries with biomolecules. Finally, analysis of compounds on single beads, either via investigation by on-bead NMR or by ladder-coding of the combinatorial compound is covered. In general, the review will focus on chemistry, libraries, synthesis, screening, and analysis, using all-PEG based resins.     

Glycosamino acids: building blocks for combinatorial synthesis-implications for drug discovery

The unique functions of carbohydrates, including energy storage, transport, modulation of protein function, intercellular adhesion, signal transduction, malignant transformation, and viral and bacterial cell-surface recognition, underlie a significant pharmaceutical potential. The development of combinatorial carbohydrate libraries in this important arena has been slow, in contrast to the rapid development of combinatorial synthesis in the area of small-molecule libraries and biopolymers. This is largely as a result of the inherent difficulties presented by this class of polyfunctional compounds. Nevertheless, strategies to cope with these problems have been devised over the past seven years, and combinatorial carbohydrate libraries have appeared. The incorporation of an amino acid moiety into the carbohydrate scaffold generates glycosamino acids, which are attractive building blocks for the preparation of carbohydrate-based libraries because of the well-established automated peptide synthesis. Derivatization as well as homo- and heterooligomerization of glycosamino acids can be used to create novel structures with unique properties. Glycosamino acids are hybrid structures of carbohydrates and amino acids which can be utilized to generate potential glycomimetics and peptidomimetics. The incorporation of glycosamino acids into peptides allows the engineering of carbohydrate-binding sites into synthetic polypeptides, which may also influence the pharmacokinetic and dynamic properties of the peptides. Furthermore, sugar-amino acid hybrids offer a tremendous structural and functional diversity, which is largely unexplored and requires combinatorial strategies for efficient exploitation. This article provides an overview of previous work on glycosamino acids and discusses their use in combinatorial synthesis and drug discovery. Supporting information for this article is available on the WWW under http://www.angewandte.com or from the author.     

Molecular shape diversity of combinatorial libraries: a prerequisite for broad bioactivity

A computational method to rapidly assess and visualize the diversity in molecular shape associated with a given compound set has been developed. Normalized ratios of principal moments of inertia are plotted into two-dimensional triangular graphs and then used to compare the shape space covered by different compound sets, such as combinatorial libraries of varying size and composition. We have further developed a computational method to analyze interset similarity in terms of shape space coverage, which allows the shape redundancy between the different subsets of a given compound collection to be analyzed in a quantitative way. The shape space coverage has been found to originate mainly from the nature and the 3D-geometry (but not the size) of the central scaffold, while the number and nature of the peripheral substituents and conformational aspects were shown to be of minor importance. Substantial shape space coverage has been correlated with broad biological activity by applying the same shape analysis to collections of known bioactive compounds, such as MDDR and the GOLD-set. The aggregate of our results corroborates the intuitive notion that molecular shape is intimately linked to biological activity and that a high degree of shape (hence scaffold) diversity in screening collections will increase the odds of addressing a broad range of biological targets.     

Fractionated marine invertebrate extract libraries for drug discovery

The high-throughput screening and drug discovery paradigm has necessitated a change in preparation of natural product samples for screening programs. In an attempt to improve the quality of marine natural products samples for screening, several fractionation strategies were investigated. The final method used HP20SS as a solid support to effectively desalt extracts and fractionate the organic components. Additionally, methods to integrate an automated LCMS fractionation approach to shorten discovery time lines have been implemented.     

Cross-referenced combinatorial libraries for the discovery of metal-complexing ligands: library deconvolution by LC-MS

N-Acylthioureas are excellent ligands for a variety of heavy metals, but their metal selectivity is highly dependent on the precise nature of the substituents present. In this paper we show how combinatorial chemistry techniques can be used to establish relative affinities for copper within a mixture of 100 such thioureas. Following a straightforward synthesis, and copper extraction using standard liquid-liquid extraction techniques, LC-MS was used to identify the ligands which bind most strongly to the copper ions. Among the 100 ligands XC(O)N(Z)C(S)NHY, the most important substituent is the Y group bound to the NH: only aromatic Y substituents give strong binding to copper. The acyl X substituents are invariably aromatic, and an electron-rich X group is best; the affinity for copper seems to be less dependent on the Z substituent, although a large group such as benzyl disfavours copper binding. The five ligands from the library which bind copper most strongly have been clearly identified by a series of experiments: they all have aromatic groups in the Y position, but the X and Z substituents can be more varied. This is a very convincing demonstration of the power of combinatorial methods: to have found the same information by conventional methods would have required a lengthy and repetitive series of syntheses and investigations. In addition, our results give some preliminary evidence for synergistic binding of two different ligands, but this requires further investigation.     

Maximum-score diversity selection for early drug discovery

Diversity selection is a common task in early drug discovery. One drawback of current approaches is that usually only the structural diversity is taken into account, therefore, activity information is ignored. In this article, we present a modified version of diversity selection, which we term Maximum-Score Diversity Selection, that additionally takes the estimated or predicted activities of the molecules into account. We show that finding an optimal solution to this problem is computationally very expensive (it is NP-hard), and therefore, heuristic approaches are needed. After a discussion of existing approaches, we present our new method, which is computationally far more efficient but at the same time produces comparable results. We conclude by validating these theoretical differences on several data sets.     

Integrating virtual screening and combinatorial chemistry for accelerated drug discovery

Virtual screening is increasingly being used in drug discovery programs with a growing number of successful applications. Experimental methodologies developed to speed up the drug discovery processes include high-throughput screening and combinatorial chemistry. The complementarities between computational and experimental screenings have been recognized and reviewed in the literature. Computational methods have also been used in the combinatorial chemistry field, in particular in library design. However, the integration of computational and combinatorial chemistry screenings has been attempted only recently. Combinatorial libraries (experimental or virtual) represent a notable source of chemically related compounds. Advances in combinatorial chemistry and deconvolution strategies, have enabled the rapid exploration of novel and dense regions in the chemical space. The present review is focused on the integration of virtual and experimental screening of combinatorial libraries. Applications of virtual screening to discover novel anticancer agents and our ongoing efforts towards the integration of virtual screening and combinatorial chemistry are also discussed.     

Receptor-assisted combinatorial chemistry: thermodynamics and kinetics in drug discovery

Current drug discovery using combinatorial chemistry involves synthesis followed by screening, but emerging methods involve receptor-assistance to combine these steps. Adding stoichiometric amounts of receptor during library synthesis alters the kinetics or thermodynamics of the synthesis in a way that identifies the best-binding library members. Three main methods have emerged thus far in receptor-assisted combinatorial chemistry: dynamic combinatorial libraries, receptor-accelerated synthesis, and a new method, pseudo-dynamic libraries. Pseudo-dynamic libraries apply both thermodynamics and kinetics to amplify library members to easily observable levels, and attain selectivity heretofore unseen in receptor-assisted systems.     

A scalable approach to combinatorial library design for drug discovery

In this paper, we propose an algorithm for the design of lead generation libraries required in combinatorial drug discovery. This algorithm addresses simultaneously the two key criteria of diversity and representativeness of compounds in the resulting library and is computationally efficient when applied to a large class of lead generation design problems. At the same time, additional constraints on experimental resources are also incorporated in the framework presented in this paper. A computationally efficient scalable algorithm is developed, where the ability of the deterministic annealing algorithm to identify clusters is exploited to truncate computations over the entire data set to computations over individual clusters. An analysis of this algorithm quantifies the tradeoff between the error due to truncation and computational effort. Results applied on test data sets corroborate the analysis and show improvement by factors as large as 10 or more, depending on the data sets.     

Survey of the diversity space coverage of reported combinatorial libraries

Courtesy of the annual collections reported by Roland E. Dolle in the Journal of Combinatorial Chemistry, all three-point diverse libraries reported in the literature since 1992 have been evaluated according to their similarity at the library level (the Diversity Space approach).1 This comparison enabled the identification of several particularly promising scaffold hopping opportunities and highlighted a number of optimal libraries (surrogates) expected to reveal binding information characteristic of an entire area of chemical space. As highlighted herein, future library design pursuits would benefit from a methodology such as the Diversity Space approach to ensure access to novel areas within the chemical landscape, thereby avoiding the expenditure of additional resources to cover a previously explored region.     

Solid-phase extraction for combinatorial libraries

Solid-phase extraction (SPE) has during the last three years emerged as a convenient method for the purification of compound libraries prepared by solution synthesis. The widespread use of SPE in combinatorial chemistry can be explained by straightforward SPE method development facilitated by the availability of numerous commercial SPE resins. High-speed automated SPE is readily accomplished by taking advantage of commercial laboratory robot systems. The present review summarizes and discusses advancements made in the use of different SPE resins and molecule tagging techniques for optimization of ion-exchange, reversed-phase, normal-phase and fluorous-phase SPE in combinatorial chemistry.     

A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases

The discovery of various protein/receptor targets from genomic research is expanding rapidly. Along with the automation of organic synthesis and biochemical screening, this is bringing a major change in the whole field of drug discovery research. In the traditional drug discovery process, the industry tests compounds in the thousands. With automated synthesis, the number of compounds to be tested could be in the millions. This two-dimensional expansion will lead to a major demand for resources, unless the chemical libraries are made wisely. The objective of this work is to provide both quantitative and qualitative characterization of known drugs which will help to generate "drug-like" libraries. In this work we analyzed the Comprehensive Medicinal Chemistry (CMC) database and seven different subsets belonging to different classes of drug molecules. These include some central nervous system active drugs and cardiovascular, cancer, inflammation, and infection disease states. A quantitative characterization based on computed physicochemical property profiles such as log P, molar refractivity, molecular weight, and number of atoms as well as a qualitative characterization based on the occurrence of functional groups and important substructures are developed here. For the CMC database, the qualifying range (covering more than 80% of the compounds) of the calculated log P is between -0.4 and 5.6, with an average value of 2.52. For molecular weight, the qualifying range is between 160 and 480, with an average value of 357. For molar refractivity, the qualifying range is between 40 and 130, with an average value of 97. For the total number of atoms, the qualifying range is between 20 and 70, with an average value of 48. Benzene is by far the most abundant substructure in this drug database, slightly more abundant than all the heterocyclic rings combined. Nonaromatic heterocyclic rings are twice as abundant as the aromatic heterocycles. Tertiary aliphatic amines, alcoholic OH and carboxamides are the most abundant functional groups in the drug database. The effective range of physicochemical properties presented here can be used in the design of drug-like combinatorial libraries as well as in developing a more efficient corporate medicinal chemistry library.     

(19)F-encoded combinatorial libraries: discovery of selective metal binding and catalytic peptoids

A (19)F NMR method for encoding of combinatorial libraries has been developed. Aryl fluorides whose chemical shifts are modified by aromatic substituents were prepared and attached to resin support beads that were used in the split-pool synthesis of peptoids. The detection of the (19)F NMR signal of tags derived from a single "big bead" was demonstrated. The library diversity arises from peptoid amines and the cyclic anhydrides used in their acylation. The resulting 90-compound library was examined for metal ion binding, and novel ligands for iron and copper were discovered. Their binding constants were determined to be in the low micromolar range using conventional methods. The library was also examined for autocatalysis of acylation, and a molecule possessing the catalytic triad of serine proteases was deduced.     

Expanding diversity in dynamic combinatorial libraries: simultaneous exchange of disulfide and thioester linkages

Dynamic combinatorial libraries have been prepared which feature two simultaneous covalent exchange reactions in aqueous solution at neutral pH. This allows for diversity, not only of the subunits that are linked, but also of the linkage itself.     

Structure-guided design of CPPC-paired disulfide-rich peptide libraries for ligand and drug discovery

Peptides constrained through multiple disulfides (or disulfide-rich peptides, DRPs) have been an emerging frontier for ligand and drug discovery. Such peptides have the potential to combine the binding capability of biologics with the stability and bioavailability of smaller molecules. However, DRPs with stable three-dimensional (3D) structures are usually of natural origin or engineered from natural ones. Here, we report the discovery and identification of CPPC (cysteine–proline–proline–cysteine) motif-directed DRPs with stable 3D structures (i.e., CPPC–DRPs). A range of new CPPC–DRPs were designed or selected from either random or structure–convergent peptide libraries. Thus, for the first time we revealed that the CPPC–DRPs can maintain diverse 3D structures by taking advantage of constraints from unique dimeric CPPC mini-loops, including irregular structures and regular α-helix and β-sheet folds. New CPPC–DRPs that can specifically bind the receptors (CD28) on the cell surface were also successfully discovered and identified using our DRP-discovery platform. Overall, this study provides the basis for accessing an unconventional peptide structure space previously inaccessible by natural DRPs and computational designs, inspiring the development of new peptide ligands and therapeutics.

CPPC-paired disulfide-rich peptides with stable 3D structures have been discovered through rational library design and screening, providing unconventional peptide scaffolds for the development of new peptide therapeutics.