Assessing the scaffold diversity of screening libraries

Medicinal chemists have traditionally realized assessments of chemical diversity and subsequent compound acquisition, although a recent study suggests that experts are usually inconsistent in reviewing large data sets. To analyze the scaffold diversity of commercially available screening collections, we have developed a general workflow aimed at (1) identifying druglike compounds, (2) clustering them by maximum common substructures (scaffolds), (3) measuring the scaffold diversity encoded by each screening collection independently of its size, and finally (4) merging all common substructures in a nonredundant scaffold library that can easily be browsed by structural and topological queries. Starting from 2.4 million compounds out of 12 commercial sources, four categories of libraries could be identified: large- and medium-sized combinatorial libraries (low scaffold diversity), diverse libraries (medium diversity, medium size), and highly diverse libraries (high diversity, low size). The chemical space covered by the scaffold library can be searched to prioritize scaffold-focused libraries.     

Application of Shannon-like diversity measures to cell-based chemistry spaces

The use of multi-dimensional “chemistry spaces” to represent large compound collections has become widespread in pharmaceutical research. In such spaces compounds are treated as points. Points in close proximity represent similar compounds, while distant points represent dissimilar compounds. Assessing the diversity of a compound collection, thus, is tantamount to characterizing the distribution of points in chemistry space. To facilitate many procedures such as selecting subsets of compounds for screening, for compound acquisition and designing combinatorial libraries, chemistry spaces have been partitioned into sets of non-overlapping, multi-dimensional cells, which are generated by dividing each axis into a number of equal-sized bins. This leads to a lattice of (N_bins)^N_dim{(N_{bins})^{N_{\rm dim}}} cells, where N _bins is the number of bins on each axis and N _dim is the dimensionality of the space. One diversity measure that is typically used in cell-based chemistry spaces is identical in form to Shannon entropy, D_Ncpd^cpd{D_{N_{cpd}}^{cpd}} A normalized measure of this Shannon entropy given by, D_rel^cpd{D_{rel}^{cpd}} enables comparison between compound collections that occupy different number of occupied cells. Although D_rel^cpd{D_{rel}^{cpd}} characterizes the uniformity and “spreadout” of the corresponding compound collection, it treats cells as positionally independent. Some of the positional information lost can be recaptured by another diversity measure, which is also related in form to Shannon entropy. This new measure D_Nbin^cell (l){D_{N_{bin}}^{cell} (\lambda)} characterizes the distribution of occupied cells along each axis of chemistry space. The normalized measure á D_rel^cell ñ{\left\langle {D_{rel}^{cell}}\right\rangle} over all axes is given then by the average. Examples illustrating the applicability of these two Shannon-like measures to compound collections are presented.     

Library fingerprints: a novel approach to the screening of virtual libraries

We propose a novel method to prioritize libraries for combinatorial synthesis and high-throughput screening that assesses the viability of a particular library on the basis of the aggregate physical-chemical properties of the compounds using a na?ve Bayesian classifier. This approach prioritizes collections of related compounds according to the aggregate values of their physical-chemical parameters in contrast to single-compound screening. The method is also shown to be useful in screening existing noncombinatorial libraries when the compounds in these libraries have been previously clustered according to their molecular graphs. We show that the method used here is comparable or superior to the single-compound virtual screening of combinatorial libraries and noncombinatorial libraries and is superior to the pairwise Tanimoto similarity searching of a collection of combinatorial libraries.     

Domino Transformations of Ene/Yne Tethered Salicylaldehyde Derivatives: Pluripotent Platforms for the Construction of High sp3 Content and Privileged Architectures

Diversity-oriented synthesis (DOS) has become a powerful synthetic tool that facilitates the construction of nature-inspired and privileged chemical space, particularly for sp³-rich non-flat scaffolds, which are needed for phenotypic screening campaigns. These diverse compound collections led to the discovery of novel chemotypes that can modulate the protein function in underrepresented biological space. In this context, starting material-driven DOS is one of the most important tools used to build diverse compound libraries with rich stereochemical and scaffold diversity. To this end, ene/yne tethered salicylaldehyde derivatives have emerged as a pluripotent chemical platform, the products of which led to the construction of a privileged chemical space with significant biological activities. In this review, various domino transformations employing o-alkene/alkyne tethered aryl aldehyde/ketone platforms are described and discussed, with emphasis on the period from 2011 to date.     

Past and future perspectives of synthetic peptide libraries

Combinatorial preparation and HTS of arrays of compounds have increased the speed of drug discovery. A strong impulse in this field has come by the introduction of the solid phase synthesis method that, through automation and miniaturization, has paved the way to the preparation of large collections of compounds in compact and trackable formats. Due to the well established synthetic procedures, peptides have been largely used to develop the basic concepts of combinatorial chemistry and peptide libraries are still successfully employed in screening programs. However, peptides generally do not fulfil the requirements of low conformational flexibility, stability and bioavailability needed for good drug candidates and peptide leads with high potency and selectivity are often made "druggable" by conversion to more stable structures with improved pharmacological profiles. Such an approach makes the screening of peptide libraries still a valuable tool for drug discovery. We propose here a panoramic review of the most common methods for the preparation and screening of peptide libraries and the most interesting findings of the last decade. We also report on a new approach we follow in our laboratory that is based on the use of "simplified" libraries composed by a minimum number of non-redundant amino acids for the assembly of short peptides. The choice of amino acids is dictated by diversity in lipophilicity, MW, charge and polarity. Newly identified active sequences are then modified by preparing new variants containing analogous amino acids, so that the chemical space occupied by the excluded residues can be explored. This approach offers the advantage of simplifying the synthesis and deconvolution of libraries and provides new active compounds with a molecular size similar to that of small molecules, to which they can be easily converted.     

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.     

Functionality‐Independent DNA Encoding of Complex Natural Products

DNA encoded chemical libraries (DELs) link the powers of genetics and chemical synthesis via combinatorial optimization. Through combinatorial chemistry, DELs can grow to the unprecedented size of billions to trillions. To take full advantage of the DEL approach, linking the power of genetics directly to chemical structures would offer even greater diversity in a finite chemical world. Natural products have evolved an incredible structural diversity along with their biological evolution. Herein, we used traditional Chinese medicines (TCMs) as examples in a late‐stage modification toolbox approach to annotate these complex organic compounds with amplifiable DNA barcodes, which could be easily incorporated into a DEL. The method of end‐products labeling also generates a cluster of isomers with a single DNA tag at different sites. These isomers provide an additional spatial diversity for multiple accessible pockets of targeted proteins. Notably, a novel PARP1 inhibitor from TCM has been identified from the natural products enriched DEL (nDEL).     

Combinatorial library design using a multiobjective genetic algorithm

Early results from screening combinatorial libraries have been disappointing with libraries either failing to deliver the improved hit rates that were expected or resulting in hits with characteristics that make them undesirable as lead compounds. Consequently, the focus in library design has shifted toward designing libraries that are optimized on multiple properties simultaneously, for example, diversity and "druglike" physicochemical properties. Here we describe the program MoSELECT that is based on a multiobjective genetic algorithm and which is able to suggest a family of solutions to multiobjective library design where all the solutions are equally valid and each represents a different compromise between the objectives. MoSELECT also allows the relationships between the different objectives to be explored with competing objectives easily identified. The library designer can then make an informed choice on which solution(s) to explore. Various performance characteristics of MoSELECT are reported based on a number of different combinatorial libraries.     

MS-Pep: a computer program for the interpretation of mass spectra of peptide libraries

Electrospray mass spectrometry (ESI-MS) is an established method for the qualitative analysis of synthetic peptide libraries and combinatorial mixtures or collections of small organic compounds. However, the calculation of the mass distribution of even small peptide mixtures is a time-consuming and error-proned task. Therefore, the computer program MS-Pep has been developed, which calculates the masses of expected peptides, byproducts and the mass distributions of peptide libraries.     

MS-Pep: a computer program for the interpretation of mass spectra of peptide libraries

Electrospray mass spectrometry (ESI-MS) is an established method for the qualitative analysis of synthetic peptide libraries and combinatorial mixtures or collections of small organic compounds. However, the calculation of the mass distribution of even small peptide mixtures is a time-consuming and error-proned task. Therefore, the computer program MS-Pep has been developed, which calculates the masses of expected peptides, byproducts and the mass distributions of peptide libraries. Received: 2 December 1996 / Revised: 17 April 1997 / Accepted: 21 April 1997     

Combinatorial Chemistry—Challenge and Chance for the Development of New Catalysts and Materials

One should not underestimate the capability of the combinatorial method in solid-state chemistry; this is the opinion of the author. Combinatorial chemistry can provide a large number of new compounds, but once the components that are interesting for a certain application have been successfully selected, the techniques of conventional catalysis and materials research are required. The strengths of conventional chemistry lie in the optimization, systematic modification, and improvement of new lead structures. In contrast, discovery is the potential strength of combinatorial chemistry. Careful design is most important for the synthesis of useful libraries, since the diversity of the periodic table is much too large to be accessed comprehensively or systematically by such large libraries.     

From protein domains to drug candidates-natural products as guiding principles in the design and synthesis of compound libraries

In the continuing effort to find small molecules that alter protein function and ultimately might lead to new drugs, combinatorial chemistry has emerged as a very powerful tool. Contrary to original expectations that large libraries would result in the discovery of many hit and lead structures, it has been recognized that the biological relevance, design, and diversity of the library are more important. As the universe of conceivable compounds is almost infinite, the question arises: where is a biologically validated starting point from which to build a combinatorial library? Nature itself might provide an answer: natural products have been evolved to bind to proteins. Recent results in structural biology and bioinformatics indicate that the number of distinct protein families and folds is fairly limited. Often the same structural domain is used by many proteins in a more or less modified form created by divergent evolution. Recent progress in solid-phase organic synthesis has enabled the synthesis of combinatorial libraries based on the structure of complex natural products. It can be envisioned that natural-product-based combinatorial synthesis may permit hit or lead compounds to be found with enhanced probability and quality.     

Synthesis of combinatorial libraries based on terpenoid scaffolds

Triterpenoid-based scaffolds betulinic acid (1a) and ursolic acid (1b), have been used for the generation of combinatorial libraries in parallel format using solid phase organic synthesis method. These templates have the potential for the synthesis and amplification of triterpenoid-based compounds with one and two-point diversity. This has been demonstrated by the synthesis of two small libraries comprising 18 derivatives each of betulinic acid and ursolic acid with structural diversity at C-3 and C-28 positions. The primary screening of antimalarial activity of these libraries against P. falciparum in vitro led to the identification of four compounds with 5 fold increase in the activity compared to betulinic and ursolic acids.     

Surrogate docking: structure-based virtual screening at high throughput speed

Summary Structure-based screening using fully flexible docking is still too slow for large molecular libraries. High quality docking of a million molecule library can take days even on a cluster with hundreds of CPUs. This performance issue prohibits the use of fully flexible docking in the design of large combinatorial libraries. We have developed a fast structure-based screening method, which utilizes docking of a limited number of compounds to build a 2D QSAR model used to rapidly score the rest of the database. We compare here a model based on radial basis functions and a Bayesian categorization model. The number of compounds that need to be actually docked depends on the number of docking hits found. In our case studies reasonable quality models are built after docking of the number of molecules containing 50 docking hits. The rest of the library is screened by the QSAR model. Optionally a fraction of the QSAR-prioritized library can be docked in order to find the true docking hits. The quality of the model only depends on the training set size – not on the size of the library to be screened. Therefore, for larger libraries the method yields higher gain in speed no change in performance. Prioritizing a large library with these models provides a significant enrichment with docking hits: it attains the values of 13 and 35 at the beginning of the score-sorted libraries in our two case studies: screening of the NCI collection and a combinatorial libraries on CDK2 kinase structure. With such enrichments, only a fraction of the database must actually be docked to find many of the true hits. The throughput of the method allows its use in screening of large compound collections and in the design of large combinatorial libraries. The strategy proposed has an important effect on efficiency but does not affect retrieval of actives, the latter being determined by the quality of the docking method itself. Electronic supplementary material is available at http://dx.doi.org/10.1007/s10822-005-9002-6.     

Library Design Guided by In-house Developed Computer Tools

In recent years, combinatorial library synthesis for drug discovery begins to migrate from library synthesis solely dictated by chemistry availability to design and synthesis of libraries with more drug-like properties. Lipinski's rule of five has been used to evaluate drug-like properties of individual compound; recently LibProTM, a new computation program has been developed at Pharmacopeia to evaluate durg-like properties of libraries. By using LibPrpTM, chemists at Pharmacopeia are able to obtain information of molecular weight and ClogP distribution of a library, and percentage of library members that violate Lipinski's rule after input structures of synthons for each combinatorial step. Currently, a "virtual library design” approach that is to calculate properties of a library at conceptual phase of the library design has been used to predetermine the value of the library. Also a new computer program used to predict "Absorption” of compounds will also be discussed.