Design Of Compound Libraries Research Articles

Characterization of Small Molecules Inhibiting the Pro-Angiogenic Activity of the Zinc Finger Transcription Factor Vezf1.

Discovery of inhibitors for endothelial-related transcription factors can contribute to the development of anti-angiogenic therapies that treat various diseases, including cancer. The role of transcription factor Vezf1 in vascular development and regulation of angiogenesis has been defined by several earlier studies. Through construction of a computational model for Vezf1, work here has identified a novel small molecule drug capable of inhibiting Vezf1 from binding to its cognate DNA binding site. Using structure-based design and virtual screening of the NCI Diversity Compound Library, 12 shortlisted compounds were tested for their ability to interfere with the binding of Vezf1 to DNA using electrophoretic gel mobility shift assays. We identified one compound, T4, which has an IC50 of 20 μM. Using murine endothelial cells, MSS31, we tested the effect of T4 on endothelial cell viability and angiogenesis by using tube formation assay. Our data show that addition of T4 in cell culture medium does not affect cell viability at concentrations lower or equal to its IC 50 but strongly inhibits the network formation by MSS31 in the tube formation assays. Given its potential efficacy, this inhibitor has significant therapeutic potential in several human diseases.

DNA-encoded libraries - an efficient small molecule discovery technology for the biomedical sciences.

DNA-encoded compound libraries are a highly attractive technology for the discovery of small molecule protein ligands. These compound collections consist of small molecules covalently connected to individual DNA sequences carrying readable information about the compound structure. DNA-tagging allows for efficient synthesis, handling and interrogation of vast numbers of chemically synthesized, drug-like compounds. They are screened on proteins by an efficient, generic assay based on Darwinian principles of selection. To date, selection of DNA-encoded libraries allowed for the identification of numerous bioactive compounds. Some of these compounds uncovered hitherto unknown allosteric binding sites on target proteins; several compounds proved their value as chemical biology probes unraveling complex biology; and the first examples of clinical candidates that trace their ancestry to a DNA-encoded library were reported. Thus, DNA-encoded libraries proved their value for the biomedical sciences as a generic technology for the identification of bioactive drug-like molecules numerous times. However, large scale experiments showed that even the selection of billions of compounds failed to deliver bioactive compounds for the majority of proteins in an unbiased panel of target proteins. This raises the question of compound library design.

Realisation of small molecule libraries based on frameworks distantly related to natural products

The availability of high-quality screening compounds is of paramount importance for the discovery of innovative new medicines. Natural product (NP) frameworks can inspire the design of productive compound libraries. Here, we describe the design and synthesis of four compound libraries based on scaffolds that have broad NP-like features, but that are only distantly related to specific NPs. The optimisation of syntheses of the scaffolds using [5 + 2] cycloaddition chemistry is detailed, together with methods to yield exemplar decorated screening compounds. In each case, a library was nominated for production, leading to a total of >2900 screening compounds that augmented the Joint European Compound Library of the European Lead Factory.

The Future of Computational Chemogenomics.

Following the elucidation of the human genome, chemogenomics emerged in the beginning of the twenty-first century as an interdisciplinary research field with the aim to accelerate target and drug discovery by making best usage of the genomic data and the data linkable to it. What started as a systematization approach within protein target families now encompasses all types of chemical compounds and gene products. A key objective of chemogenomics is the establishment, extension, analysis, and prediction of a comprehensive SAR matrix which by application will enable further systematization in drug discovery. Herein we outline future perspectives of chemogenomics including the extension to new molecular modalities, or the potential extension beyond the pharma to the agro and nutrition sectors, and the importance for environmental protection. The focus is on computational sciences with potential applications for compound library design, virtual screening, hit assessment, analysis of phenotypic screens, lead finding and optimization, and systems biology-based prediction of toxicology and translational research.

Protocols for the Design of Kinase-focused Compound Libraries.

Protocols for the design of kinase-focused compound libraries are presented. Kinase-focused compound libraries can be differentiated based on the design goal. Depending on whether the library should be a discovery library specific for one particular kinase, a general discovery library for multiple distinct kinase projects, or even phenotypic screening, there exists today a variety of in silico methods to design candidate compound libraries. We address the following scenarios: 1) Datamining of SAR databases and kinase focused vendor catalogues; 2) Predictions and virtual screening; 3) Structure-based design of combinatorial kinase inhibitors; 4) Design of covalent kinase inhibitors; 5) Design of macrocyclic kinase inhibitors; and 6) Design of allosteric kinase inhibitors and activators.

Molecular Connectivity Predefines Polypharmacology: Aliphatic Rings, Chirality, and sp3 Centers Enhance Target Selectivity.

Dark chemical matter compounds are small molecules that have been recently identified as highly potent and selective hits. For this reason, they constitute a promising class of possible candidates in the process of drug discovery and raise the interest of the scientific community. To this purpose, Wassermann et al. (2015) have described the application of 2D descriptors to characterize dark chemical matter. However, their definition was based on the number of reported positive assays rather than the number of known targets. As there might be multiple assays for one single target, the number of assays does not fully describe target selectivity. Here, we propose an alternative classification of active molecules that is based on the number of known targets. We cluster molecules in four classes: black, gray, and white compounds are active on one, two to four, and more than four targets respectively, whilst inactive compounds are found to be inactive in the considered assays. In this study, black and inactive compounds are found to have not only higher solubility, but also a higher number of chiral centers, sp3 carbon atoms and aliphatic rings. On the contrary, white compounds contain a higher number of double bonds and fused aromatic rings. Therefore, the design of a screening compound library should consider these molecular properties in order to achieve target selectivity or polypharmacology. Furthermore, analysis of four main target classes (GPCRs, kinases, proteases, and ion channels) shows that GPCR ligands are more selective than the other classes, as the number of black compounds is higher in this target superfamily. On the other side, ligands that hit kinases, proteases, and ion channels bind to GPCRs more likely than to other target classes. Consequently, depending on the target protein family, appropriate screening libraries can be designed in order to minimize the likelihood of unwanted side effects early in the drug discovery process. Additionally, synergistic effects may be obtained by library design toward polypharmacology.

Privileged Structures Revisited.

Privileged structures inspire compound library design in medicinal chemistry. We performed a comprehensive analysis of 1.4 million bioactive compounds, with the aim of assessing the prevalence of certain molecular frameworks. We used the Shannon entropy formalism to quantify the promiscuity of the most frequently observed atom scaffolds across the annotated target families. This analysis revealed an apparent inverse relationship between hydrogen‐bond‐acceptor count of a scaffold and its potential promiscuity. The results further suggest that chemically easily accessible scaffolds can serve as templates for the generation of bespoke compound libraries with differing degrees of multiple target engagement, and heterocyclic, sp3‐rich frameworks are particularly suited for target‐focused library design. The outcome of our study enables us to place some of the many narratives surrounding the concept of privileged structures into a critical context.

Design of high-quality compound library and open innovation.

多くの製薬企業では，過去の創薬研究で合成した化合物や外部から入手した化合物をデータベース化し，各種試験に素早く使用できるよう保管庫に管理している．このような化合物コレクションを「化合物ライブラリー」と呼ぶ．化合物ライブラリーのスクリーニング試験から見出されたヒット化合物は，薬理活性・物性・薬物動態・安全性の観点から最適化され，膨大な試験を繰り返しながら前臨床候補化合物となる．当然，ヒット化合物に物性・薬物動態・安全性の問題があれば，その克服には多くの試験や期間が費やされてしまう．このため化合物ライブラリーには，創薬の出発点として相応しい物性・薬物動態・安全性の懸念の少ない化合物が求められる．本稿では，このような要求に応える高質な化合物ライブラリーを設計するための考え方や技術を解説し，最後に化合物ライブラリーを取り巻く最新動向を紹介する．

Structure-performance relationships of phenyl cinnamic acid derivatives as MALDI-MS matrices for sulfatide detection.

A key aspect for the further development of matrix-assisted laser desorption ionization (MALDI)-mass spectrometry (MS) is a better understanding of the working principles of MALDI matrices. To address this issue, a chemical compound library of 59 structurally related cinnamic acid derivatives was synthesized. Potential MALDI matrices were evaluated with sulfatides, a class of anionic lipids which are abundant in complex brain lipid mixtures. For each matrix relative mean S/N ratios of sulfatides were determined against 9-aminoacridine as a reference matrix using negative ion mass spectrometry with 355 and 337nm laser systems. The comparison of matrix features with their corresponding relative mean S/N ratios for sulfatide detection identified correlations between matrix substitution patterns, their chemical functionality, and their MALDI-MS performance. Crystal structures of six selected matrices provided structural insight in hydrogen bond interactions in the solid state. Principal component analysis allowed the additional identification of correlation trends between structural and physical matrix properties like number of exchangeable protons at the head group, MW, logP, UV-Vis, and sulfatide detection sensitivity. Graphical abstract Design, synthesis and mass spectrometric evaluation of MALDI-MS matrix compound libraries allows the identification of matrix structure - MALDI-MS performance relationships using multivariate statistics as a tool.

Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening.

High-throughput screening (HTS) campaigns are routinely performed in pharmaceutical companies to explore activity profiles of chemical libraries for the identification of promising candidates for further investigation. With the aim of improving hit rates in these campaigns, data-driven approaches have been used to design relevant compound screening collections, enable effective hit triage and perform activity modeling for compound prioritization. Remarkable progress has been made in the activity modeling area since the recent introduction of large-scale bioactivity-based compound similarity metrics. This is evidenced by increased hit rates in iterative screening strategies and novel insights into compound mode of action obtained through activity modeling. Here, we provide an overview of the developments in data-driven approaches, elaborate on novel activity modeling techniques and screening paradigms explored and outline their significance in HTS.

Chromones: A Promising Ring System for New Anti-inflammatory Drugs.

The quest for safer anti-inflammatory drugs is still the focus of several medicinal chemistry programs. Chromones (4H-chromen-4-ones) are a group of naturally occurring compounds ubiquitous in plants, and the chromone core has proven to be a privileged scaffold in medicinal chemistry. Herein we provide an overview of the relevance of chromones as anti-inflammatory agents, specifically as inhibitors of cyclooxygenase (COX), 5-lipoxygenase (5-LOX), interleukin-5 (IL-5), and nitric oxide (. NO) production. Numerous structure-activity relationships and mechanisms of action are discussed. This review is therefore intended to provide a foundation for the design and synthesis of novel chromone-based compound libraries for further development into safer and more efficient anti-inflammatory agents.

Designing Multi-target Compound Libraries with Gaussian Process Models.

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design.

Synthesis of two chiral octahydroindole scaffolds for drug discovery

There are over one thousand natural products that contain the octahydroindole scaffold, which can be considered a biologically validated starting point for the design of compound libraries. Two chiral octahydroindole scaffolds have been synthesized in multigram quantities in two steps from a readily available indoline. They contain either one or two amino groups (one Boc-protected) and a protected carboxylic acid group, and have been designed for ease of conversion to a lead generation library. The structures of both scaffolds have been established unequivocally by single crystal X-ray structure determination.

The twin drug approach for novel nicotinic acetylcholine receptor ligands

The association of two pharmacophoric entities generates so-called ‘twin drugs’ or dimer derivatives. We applied this approach for the design of a small compound library for the interaction with α4β2∗ nicotinic acetylcholine receptors (nAChRs). In this compound series, the nAChR ligand N,N-dimethyl-2-(pyridin-3-yloxy)ethan-1-amine 9 served as one pharmacological entity and it was initially kept constant as one part of the ‘twin’ compound. ‘Twin’ compounds with identical or non-identical entities using the ‘no linker mode’ or ‘overlap’ mode were synthesized and evaluated for their nAChR affinities. Compound 17a showed the highest affinity for the α4β2∗ nAChR subtype (Ki=0.188nM) and its (di)fluoro analogs could retain nanomolar affinities, when replacing pyridine as the hydrogen bond acceptor system by mono- or difluoro-phenyls. The ‘twin drug’ approach proved to provide compounds with high affinity and subtype selectivity for α4β2∗ nAChRs.

Facile Pd-catalyzed amination of imidazolin-1-yl chloroazines under microwave irradiation: toward a new kinase-inhibitory chemotype

The imidazolin-1-yl azine moiety, constructed using a recently developed Buchwald–Hartwig-type arylation methodology, displays excellent chemical stability under subsequent microwave-assisted Pd-catalyzed amination with a range of N-nucleophiles. This finding extends the usage of imidazolin-1-yl azines for bioactive compound library design. The latter is exemplified herein by the discovery of micromolar kinase inhibitors.

Naturally occurring scaffolds for compound library design: convenient access to bis-aryl 1-azaadamantanes carrying a vicinal amino alcohol motif

The vast majority of scaffolds found in natural products are absent from the currently available compound collections for biological screening. At the same time, scaffolds derived from natural products may have a distinct advantage over non-natural cores in terms of providing compounds endowed with biological activities and should be used extensively in screening library design. We have developed a synthetic approach to merging a naturally occurring 1-azaadamantane core with a vicinal amino alcohol moiety that is also common in natural product chemical space. The synthesis features diastereoselective epoxidation of racemic chiral 2,6-diaryl-4-methylene 1-azaadamantanes with subsequent SN2-type epoxide opening in aqueous isopropanol.

Optimization of Molecular Representativeness

Representative subsets selected from within larger data sets are useful in many chemoinformatics applications including the design of information-rich compound libraries, the selection of compounds for biological evaluation, and the development of reliable quantitative structure-activity relationship (QSAR) models. Such subsets can overcome many of the problems typical of diverse subsets, most notably the tendency of the latter to focus on outliers. Yet only a few algorithms for the selection of representative subsets have been reported in the literature. Here we report on the development of two algorithms for the selection of representative subsets from within parent data sets based on the optimization of a newly devised representativeness function either alone or simultaneously with the MaxMin function. The performances of the new algorithms were evaluated using several measures representing their ability to produce (1) subsets which are, on average, close to data set compounds; (2) subsets which, on average, span the same space as spanned by the entire data set; (3) subsets mirroring the distribution of biological indications in a parent data set; and (4) test sets which are well predicted by qualitative QSAR models built on data set compounds. We demonstrate that for three data sets (containing biological indication data, logBBB permeation data, and Plasmodium falciparum inhibition data), subsets obtained using the new algorithms are more representative than subsets obtained by hierarchical clustering, k-means clustering, or the MaxMin optimization at least in three of these measures.

Toward Lead-Oriented Synthesis: One-Pot Version of Castagnoli Condensation with Nonactivated Alicyclic Anhydrides

One-pot variation of Castagnoli condensation, that is, reaction of cyclic anhydrides, amines, and aldehydes, has been developed as a combinatorial approach to 1,2-disubstituted 5-oxopyrrolidine- and 6-oxopiperidine-3-carboxylic acids, as well as their benzo-analogues. Utility of the method to multigram preparation of building blocks and synthetic intermediates was also demonstrated. The final products are obtained in high yields and diastereoselectivity. The method fits well in the concept of lead-oriented synthesis; in particular, it can be used for the design of lead-like compound libraries, even if the strictest cut-offs are applied to the physicochemical properties of their members.

Discovery of novel small-molecule Src kinase inhibitors via a kinase-focused druglikeness rule and structure-based virtual screening

Overexpression of the non-receptor tyrosine kinase Src is implicated in the development and progression of various human cancers. Blocking signalling pathways mediated by Src is believed to be a promising anticancer strategy. We report herein the discovery of novel small-molecule Src inhibitors by crystal structure-based virtual screening. A kinase-focused druglikeness rule was proposed and used in the design of compound library. Combination of large-scale docking with DOCK and rescoring with GOLD resulted in 6 hits with moderate to potent inhibitory activity against Src. Among them, compound 1 with an IC50 of 1.2 μM shows the most potent inhibitory activity. By using molecular docking, binding models of the top 3 hits (ranked by potency and ligand efficiency) with Src were constructed to provide a rational strategy that simultaneously exploits hydrogen bonding interaction in the hinge region and hydrophobic stacking in the back pocket. This approach is instructive and meaningful to further structure-based drug design of Src inhibitors.

Parallel Chemistry in the 21st Century

The tool chest of techniques, methodologies, and equipment for conducting parallel chemistry is larger than ever before. Improvements in the laboratory and developments in computational chemistry have enabled compound library design at the desks of medicinal chemists. This unit includes a brief background in combinatorial/parallel synthesis chemistry, along with a discussion of evolving technologies for both solid- and solution-phase chemistry. In addition, there are discussions on designing compound libraries, acquisition/procurement of compounds and/or reagents, the chemistry and equipment used for chemical production, purification, sample handling, and data analysis.