Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library

Peptidomimetics are great sources of protein ligands. The oligomeric nature of these compounds enables us to access large synthetic libraries on solid phase by using combinatorial chemistry. One of the most well studied classes of peptidomimetics is peptoids. Peptoids are easy to synthesize and have been shown to be proteolysis-resistant and cell-permeable. Over the past decade, many useful protein ligands have been identified through screening of peptoid libraries. However, most of the ligands identified from peptoid libraries do not display high affinity, with rare exceptions. This may be due, in part, to the lack of chiral centers and conformational constraints in peptoid molecules. Recently, we described a new synthetic route to access peptide tertiary amides (PTAs). PTAs are a superfamily of peptidomimetics that include but are not limited to peptides, peptoids and N-methylated peptides. With side chains on both α-carbon and main chain nitrogen atoms, the conformation of these molecules are greatly constrained by sterical hindrance and allylic 1,3 strain. (Figure 1) Our study suggests that these PTA molecules are highly structured in solution and can be used to identify protein ligands. We believe that these molecules can be a future source of high-affinity protein ligands. Here we describe the synthetic method combining the power of both split-and-pool and sub-monomer strategies to synthesize a sample one-bead one-compound (OBOC) library of PTAs.     

A structure-based strategy to identify new molecular scaffolds targeting the bacterial ribosomal A-site

The need for novel antibiotics is widely recognized. A well validated target of antibiotics is the bacterial ribosome. Recent X-ray structures of the ribosome bound to antibiotics have shed new light on the binding sites of these antibiotics, providing fresh impetus for structure-based strategies aiming at identifying new ribosomal ligands. In that respect, the ribosomal decoding region of the aminoacyl-tRNA acceptor site (A-site) is of particular interest because oligonucleotide model systems of this site are available for crystallography, NMR and compound binding assays. This work presents how these different resources can be combined in a hierarchical screening strategy which has led to the identification of new A-site ligands. The approach exploits an X-ray structure of the A-site against which large and diverse libraries of compounds were computationally docked. The complementarity of the compounds to the A-site was assessed using a scoring function specifically calibrated for RNA targets. Starting from approximately 1 million compounds, the computational selection of candidate ligands allowed us to focus the experimental work on 129 compounds, 34 of which showed affinity for the A-site in a FRET-based binding assay. NMR experiments confirmed binding to the A-site for some compounds. For the most potent compound in the FRET assay, a tentative binding mode is suggested, which is compatible with the NMR data and the limited SAR in this series. Overall, the results validate the screening strategy.     

In silico investigation of ACE2 and the main protease of SARS-CoV-2 with phytochemicals from Myristica fragrans (Houtt.) for the discovery of a novel COVID-19 drug

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), is a new coronavirus strain that was first reported in December 2019 in Wuhan, China. A specific treatment for COVID-19 has yet to be identified. Potential therapeutic targets include SARS-CoV-2 main protease (Mpro) and the SARS-CoV-2 spike-ACE2 interaction. Molecular docking, molecular dynamics (MD), solvent screening for the extraction of the specified compounds, and prediction of the drug properties of certain molecules were the methods used in this study to investigate compounds from the medicinal plant Myristica fragrans, which is one of twelve herbs in Prasachandaeng remedy (PSD). ArgusLab, AutoDock Vina, and AutoDock were used to perform docking tasks. The examined ligands were compared with panduratin A as a standard (Kanjanasirirat et al., 2020), which is a promising medicinal plant molecule for the treatment of COVID-19. Molecular docking revealed that malabaricones B and C and licarins A, B and C bound to SARS-CoV-2/ACE2 and SARS-CoV-2 Mpro with low binding energies compared to that of the standard ligand. Furthermore, appropriate solvent usage is important. Acetone was selected by COSMOquick software for compound extraction in this investigation because it can extract large amounts of all five of the abovementioned M. fragrans compounds. Furthermore, the drug-like properties of these compounds were studied utilizing the Lipinski, Veber, and Ghose criteria. The results revealed that these M. fragrans compounds have potential as effective medicines to combat the COVID-19 pandemic. However, to assess the therapeutic potential of these ligands, additional research is needed, which will use our findings as a foundation.     

Efficient hit-finding approaches for histone methyltransferases: the key parameters

For many novel epigenetics targets the chemical ligand space and structural information were limited until recently and are still largely unknown for some targets. Hit-finding campaigns are therefore dependent on large and chemically diverse libraries. In the specific case of the histone methyltransferase G9a, the authors have been able to apply an efficient process of intelligent selection of compounds for primary screening, rather than screening the full diverse deck of 900 000 compounds to identify hit compounds. A number of different virtual screening methods have been applied for the compound selection, and the results have been analyzed in the context of their individual success rates. For the primary screening of 2112 compounds, a FlashPlate assay format and full-length histone H3.1 substrate were employed. Validation of hit compounds was performed using the orthogonal fluorescence lifetime technology. Rated by purity and IC(50) value, 18 compounds (0.9% of compound screening deck) were finally considered validated primary G9a hits. The hit-finding approach has led to novel chemotypes being identified, which can facilitate hit-to-lead projects. This study demonstrates the power of virtual screening technologies for novel, therapeutically relevant epigenetics protein targets.     

Identification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening,ADMET prediction and molecular dynamics simulation assay

Histone deacetylases (HDACs) have gained increased attention as targets for anticancer drug design and development. HDAC inhibitors have proven to be effective for reversing the malignant phenotype in HDAC-dependent cancer cases. However, lack of selectivity of the many HDAC inhibitors in clinical use and trials contributes to toxicities to healthy cells. It is believed that, the continued identification of isoform-selective inhibitors will eliminate these undesirable adverse effects – a task that remains a major challenge to HDAC inhibitor designs. Here, in an attempt to identify isoform-selective inhibitors, a large compound library containing 2,703,000 compounds retrieved from Otava database was screened against class I HDACs by exhaustive approach of structure-based virtual screening using rDOCK and Autodock Vina. A total of 41 compounds were found to show high-isoform selectivity and were further redocked into their respective targets using Autodock4. Thirty-six compounds showed remarkable isoform selectivity and passed drug-likeness and absorption, distribution, metabolism, elimination and toxicity prediction tests using ADMET Predictor? and admetSAR. Furthermore, to study the stability of ligand binding modes, 10 ns-molecular dynamics (MD) simulations of the free HDAC isoforms and their complexes with respective best-ranked ligands were performed using nanoscale MD software. The inhibitors remained bound to their respective targets over time of the simulation and the overall potential energy, root-mean-square deviation, root-mean-square fluctuation profiles suggested that the detected compounds may be potential isoform-selective HDAC inhibitors or serve as promising scaffolds for further optimization towards the design of selective inhibitors for cancer therapy.     

Identification of potential inhibitors for HCV NS3 genotype 4a by combining protein–ligand interaction fingerprint, 3D pharmacophore,docking, and dynamic simulation

HCV NS3 protease domain has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting HCV genotype 1 infection. HCV genotype 4a dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS3 of genotype 4a using homology modeling, PLIF (protein–ligand interaction fingerprint), docking, pharmacophore, and dynamic simulation. A high-quality 3D model of HCV NS3 protease of genotype 4a was constructed using crystal structure of HCV NS3 protease of genotype 1b (PDB ID: 4u01) as a template. PLIF was generated using five crystal structures of HCV NS3 (PDB ID: 4u01, 3kee, 4ktc, 4i33, and 5epn) which revealed the most important residues and their interactions with the co-crystalized ligands. A 3D pharmacophore model consisting of six features was developed from the generated PLIF data and then used as a screening filter for 11,244 compounds. Only 423 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. The highest ranked five hits from docking result (compound (C1–C5)) were selected for further analysis. They exhibited stronger interaction and higher binding affinity than HCV NS3 protease ligands. Dynamic simulation of the protein–best lead complex was performed to validate and augment the virtual screening results and it showed that these compounds have a strong binding affinity and could be very effective in treating HCV genotype 4a infections.     

Tracking 20 Years of Compound-to-Target Output from Literature and Patents

The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates.     

Novel small molecule activators of the Trk family of receptor tyrosine kinases

The Tropomyosin-related kinase (Trk) receptors are a subset of the receptor tyrosine kinase family with an important functionality in the regulation of neurotrophic signaling in the peripheral and central nervous system. As the receptors are able to mediate neuronal survival by associating with their respective neurotrophin ligands, many studies have focused on the therapeutic potential of generating small-molecule mimetic compounds that elicit agonistic effects similar to those of the natural protein ligands. To this end, various structure-based studies have led to the generation of bivalent peptide-based agonists and antibodies that selectively initiate Trk receptor signaling; however, these compounds do not possess the ideal characteristics of a potential drug. Additionally, the reliance of structure-based data to generate the compound libraries, limits the potential identification of novel chemical structures with desirable activity. Therefore, subsequent investigations utilized a cell-based apoptotic screen to facilitate the analysis of large, diverse chemical libraries of small molecules and quickly identify compounds with Trk-dependent anti-apoptotic activity. Herein, we describe the Trk agonists that have been identified by this screening methodology and summarize their in vitro and in vivo neurotrophic activity as well as their efficacy in various neurological disease models, implicating their future utility as therapeutic compounds. This article is part of a Special Issue entitled: Emerging recognition and activation mechanisms of receptor tyrosine kinases.     

SELEX技术在神经系统疾病研究中的应用

配体指数级富集系统进化（systematic evolution of ligands by exponential enrichment,SELEX）技术是一种组合化学技术,可经过反复筛选扩增得到针对靶分子的高亲和力和高特异性的适配子.适配子通过识别、结合特定靶分子并对其进行功能调控从而达到对疾病诊断和治疗的目的 .近年来SELEX技术在神经系统功能和疾病研究中的应用越来越多.现已经筛选出针对朊蛋白、肌腱蛋白-C、β-淀粉样肽、乙酰胆碱受体的自身抗体等靶标的适配子,促进了对朊病毒病、脑肿瘤、阿茨海默病、重症肌无力等神经系统疾病的诊断和治疗研究,为这些疾病的诊治提供了新的研究工具.     

Discovering ligands for a microRNA precursor with peptoid microarrays

We have screened peptoid microarrays to identify specific ligands for the RNA hairpin precursor of miR-21, a microRNA involved in cancer and heart disease. Microarrays were printed by spotting a library of 7680 N-substituted oligoglycines (peptoids) onto glass slides. Two compounds on the array specifically bind RNA having the sequence and predicted secondary structure of the miR-21 precursor hairpin and have specific affinity for the target in solution. Their binding induces a conformational change around the hairpin loop, and the most specific compound recognizes the loop sequence and a bulged uridine in the proximal duplex. Functional groups contributing affinity and specificity were identified, and by varying a critical methylpyridine group, a compound with a dissociation constant of 1.9 μM for the miR-21 precursor hairpin and a 20-fold discrimination against a closely-related hairpin was created. This work describes a systematic approach to discovery of ligands for specific pre-defined novel RNA structures. It demonstrates discovery of new ligands for an RNA for which no specific lead compounds were previously known by screening a microarray of small molecules.     

Inhibitors of protein synthesis identified by a high throughput multiplexed translation screen

The use of small molecule inhibitors of cellular processes is a powerful approach to understanding gene function that complements the genetic approach. We have designed a high throughput screen to identify new inhibitors of eukaryotic protein synthesis. We used a bicistronic mRNA reporter to multiplex our assay and simultaneously screen for inhibitors of cap-dependent initiation, internal initiation and translation elongation/termination. Functional screening of >90 000 compounds in an in vitro translation reaction identified 36 inhibitors, 14 of which are known inhibitors of translation and 18 of which are nucleic acid-binding ligands. Our results indicate that intercalators constitute a large class of protein synthesis inhibitors. Four non-intercalating compounds were identified, three of which block elongation and one of which inhibits initiation. The novel inhibitor of initiation affects 5' end-mediated initiation, as well as translation initiated from picornaviral IRESs, but does not significantly affect internal initiation from the hepatitis C virus 5'-untranslated region. This compound should be useful for delineating differences in mechanism of initiation among IRESs.     

A Static-Cidal Assay for Trypanosoma brucei to Aid Hit Prioritisation for Progression into Drug Discovery Programmes

Human African Trypanosomiasis is a vector-borne disease of sub-Saharan Africa that causes significant morbidity and mortality. Current therapies have many drawbacks, and there is an urgent need for new, better medicines. Ideally such new treatments should be fast-acting cidal agents that cure the disease in as few doses as possible. Screening assays used for hit-discovery campaigns often do not distinguish cytocidal from cytostatic compounds and further detailed follow-up experiments are required. Such studies usually do not have the throughput required to test the large numbers of hits produced in a primary high-throughput screen. Here, we present a 384-well assay that is compatible with high-throughput screening and provides an initial indication of the cidal nature of a compound. The assay produces growth curves at ten compound concentrations by assessing trypanosome counts at 4, 24 and 48 hours after compound addition. A reduction in trypanosome counts over time is used as a marker for cidal activity. The lowest concentration at which cell killing is seen is a quantitative measure for the cidal activity of the compound. We show that the assay can identify compounds that have trypanostatic activity rather than cidal activity, and importantly, that results from primary high-throughput assays can overestimate the potency of compounds significantly. This is due to biphasic growth inhibition, which remains hidden at low starting cell densities and is revealed in our static-cidal assay. The assay presented here provides an important tool to follow-up hits from high-throughput screening campaigns and avoid progression of compounds that have poor prospects due to lack of cidal activity or overestimated potency.     

Multimeric receptors, new targets for the pharmaceutical industry

Cytokines and growth factors are reported to play a pivotal role in many pathologic conditions. Some recombinant proteins have demonstrated powerful therapeutic activities for example in arthritis for anti-TNF (antibody and soluble receptor) or in cancer for interleukin2 and are now available for clinical use. However limitation in production, treatment condition for use and final high costs have encouraged pharmaceutical industry to develop research of small synthetic compounds which can replace or inhibit natural ligands. During the last 5 years a series of publication have demonstrated that small peptides (up to 20 amino-acids) and non-peptide synthetic compounds may replace in vitro as well as in vivo some cytokine and cell growth factors. Selection of these compounds have used new technique of screening including phage display and gene reporter assays. Currently selected compounds mainly act as agonist and stimulate transduction signals in the target cell as do natural ligands. These results have demonstrated that at least for some cytokine and cell growth factor protein biological action may be mimicked by small molecular weight synthetic compound. Next steps will deal with selection of drug candidates able to be studied at the clinical level.     

Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

Development and Validation of a Novel Leishmania donovani Screening Cascade for High-Throughput Screening Using a Novel Axenic Assay with High Predictivity of Leishmanicidal Intracellular Activity

Visceral leishmaniasis is an important parasitic disease of the developing world with a limited arsenal of drugs available for treatment. The existing drugs have significant deficiencies so there is an urgent need for new and improved drugs. In the human host, Leishmania are obligate intracellular parasites which poses particular challenges in terms of drug discovery. To achieve sufficient throughput and robustness, free-living parasites are often used in primary screening assays as a surrogate for the more complex intracellular assays. We and others have found that such axenic assays have a high false positive rate relative to the intracellular assays, and that this limits their usefulness as a primary platform for screening of large compound collections. While many different reasons could lie behind the poor translation from axenic parasite to intracellular parasite, we show here that a key factor is the identification of growth slowing and cytostatic compounds by axenic assays in addition to the more desirable cytocidal compounds. We present a screening cascade based on a novel cytocidal-only axenic amastigote assay, developed by increasing starting density of cells and lowering the limit of detection, and show that it has a much improved translation to the intracellular assay. We propose that this assay is an improved primary platform in a new Leishmania screening cascade designed for the screening of large compound collections. This cascade was employed to screen a diversity-oriented-synthesis library, and yielded two novel antileishmanial chemotypes. The approach we have taken may have broad relevance to anti-infective and anti-parasitic drug discovery.     

The 2-deoxyglucose uptake method as a first screen for neurotoxic compounds

Our primary goal is to develop a screening procedure to detect and partially characterize neurotoxic compounds. There is a great need for a new approach to screening for neurotoxicants because our industrialized world abounds with untested and potentially neurotoxic compounds. A large number of new compounds are introduced each year. Although a number of testing approaches to the screening for neurotoxicants have been proposed in the recent years, a consensus on the most adequate approach is yet to emerge. The existing methods share a number of shortcomings. Thus, most methods only detect a fraction of the tested neurotoxicants. Other methods lack the necessary resolution to detect the neurotoxic damage reproducibly and reliably. Furthermore, many screening approaches are too time consuming and costly to be used for the large-scale screening of neurotoxicants. It is, therefore, imperative to develop reliable and efficient screening methods applicable in regulatory toxicology. In this report, we describe two versions of the same method that we feel may be very beneficial for the large-scale screening of neurotoxicants. The 2-deoxyglucose (2-DG) uptake method provides an indirect measure of neuronal activity in different areas of the brain. The ability of the method to detect most, if not all, neuroactive substances is reviewed in this report. In the context of this report, a neuroactive substance is defined as a substance acting directly on the central or peripheral nervous system neurons and (or) glia. The 2-DG method equals the sensitivity of the most sensitive alternative methods which were selectively designed to detect the effects of specific groups of compounds. The generality and sensitivity of the 2-DG method are of major importance. Thus, if a tested compound does not affect the uptake of 2-DG into the brain, it is not likely to be neuroactive. Since neurotoxic compounds are a subset of neuroactive compounds, a compound that is not neuroactive is also not neurotoxic. Thus, a single test may, in some instances, determine if a tested compound is nontoxic. In addition, it appears that each compound or, at least, each family of compounds produces a characteristic profile ("pattern") of the sites of altered 2-DG uptake. This pattern can be exploited to characterize the tested compound and help us decide whether it is neurotoxic or neuroactive. Preliminary results from our laboratory indicate classical neurotoxic agents such as acrylamide, triethyltin, and 2,5-hexanedione induce a generalized depression of the 2-DG uptake throughout the brain.(ABSTRACT TRUNCATED AT 400 WORDS)     

Non-Traditional Antibacterial Screening Approaches for the Identification of Novel Inhibitors of the Glyoxylate Shunt in Gram-Negative Pathogens

Antibacterial compounds that affect bacterial viability have traditionally been identified, confirmed, and characterized in standard laboratory media. The historical success of identifying new antibiotics via this route has justifiably established a traditional means of screening for new antimicrobials. The emergence of multi-drug-resistant (MDR) bacterial pathogens has expedited the need for new antibiotics, though many in the industry have questioned the source(s) of these new compounds. As many pharmaceutical companies'' chemical libraries have been exhaustively screened via the traditional route, we have concluded that all compounds with any antibacterial potential have been identified. While new compound libraries and platforms are being pursued, it also seems prudent to screen the libraries we currently have in hand using alternative screening approaches. One strategy involves screening under conditions that better reflect the environment pathogens experience during an infection, and identifying in vivo essential targets and pathways that are dispensable for growth in standard laboratory media in vitro. Here we describe a novel screening strategy for identifying compounds that inhibit the glyoxylate shunt in Pseudomonas aeruginosa, a pathway that is required for bacterial survival in the pulmonary environment. We demonstrate that these compounds, which were not previously identified using traditional screening approaches, have broad-spectrum antibacterial activity when they are tested under in vivo-relevant conditions. We also show that these compounds have potent activity on both enzymes that comprise the glyoxylate shunt, a feature that was supported by computational homology modeling. By dual-targeting both enzymes in this pathway, we would expect to see a reduced propensity for resistance development to these compounds. Taken together, these data suggest that understanding the in vivo environment that bacterial pathogens must tolerate, and adjusting the antibacterial screening paradigm to reflect those conditions, could identify novel antibiotics for the treatment of serious MDR pathogens.     

Knowledge-based Fragment Binding Prediction

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE''s ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.     

The purines: potent and versatile small molecule inhibitors and modulators of key biological targets

The goal of this review is to highlight the wide range of biological activities displayed by purines, with particular emphasis on new purine-based agents which find potential application as chemical-biology tools and/or therapeutic agents. The expanding interest in the biological properties of polyfunctionalized purine derivatives issues, in large part, from the development of rapid high-throughput screening essays for new protein targets, and the corresponding development of efficient synthetic methodology adapted to the construction of highly diverse purine libraries. Purine-based compounds have found new applications as inducers of interferon and lineage-committed cell dedifferentiation, agonists and antagonists of adenosine receptors, ligands of corticotropin-releasing hormone receptors, and as inhibitors of HSP90, Src kinase, p38alpha MAP kinase, sulfotransferases, phosphodiesterases, and Cdks. The scope of application of purines in biology is most certainly far from being exhausted. Testing purine derivatives against the multitude of biological targets for which small molecule probes have not yet been found should thus be a natural reflex.     

Design and implementation of cell-based assays to model human disease.

Cell-based assays, if appropriately designed, can be used to rapidly identify molecular mechanisms of human disease and develop novel therapeutics. In the last 20 years, many genes that cause or contribute to diverse disorders, including cancer and neurodegenerative disease, have been identified. With such genes in hand, scientists have created numerous model systems to dissect the molecular mechanisms of basic cellular and developmental biology. Meanwhile, techniques for high-throughput screening that use large chemical libraries have been developed, as have cDNA and RNA interference libraries that cover the entire human genome. By combining cell-based assays with chemical and genetic screens, we now have vastly improved our ability to dissect molecular mechanisms of disease and to identify therapeutic targets and therapeutic lead compounds. However, cell-based screening systems have yet to yield many fundamental insights into disease pathogenesis, and the development of therapeutic leads is frustratingly slow. This may be due to a failure of such assays to accurately reflect key aspects of pathogenesis. This Review attempts to guide the design of productive cellular models of human disease that may be used in high-throughput chemical and genetic screens. We emphasize two points: (i) model systems should use quantifiable molecular indicators of a pathogenic process, and (ii) small chemical libraries that include molecules with known biological activity and/or acceptable safety profiles are very useful.