Robust and Systematic Drug Screening Method Using Chemical Arrays and the Protein Library: Identification of Novel Inhibitors of Carbonic Anhydrase II

The identification of specific interactions between small molecules and human proteins of interest is a fundamental step in chemical biology and drug development. Here we describe an efficient method to obtain novel binding ligands of human proteins by a chemical array approach. Our method includes large-scale ligand screening with two libraries, proteins and chemicals, the use of cell lysates that express proteins of interest fused with red fluorescent protein, and high-throughput screening by merged display analysis, which removes false positive signals from array experiments. Using our systematic platform, we detected novel inhibitors of carbonic anhydrase II. It is suggested that our systematic platform is a rapid and robust approach to screen novel ligands for human proteins of interest.     

A novel and efficient ligand-based virtual screening approach using the HWZ scoring function and an enhanced shape-density model

In this work, we extend our previous ligand shape-based virtual screening approach by using the scoring function Hamza–Wei–Zhan (HWZ) score and an enhanced molecular shape-density model for the ligands. The performance of the method has been tested against the 40 targets in the Database of Useful Decoys and compared with the performance of our previous HWZ score method. The virtual screening results using the novel ligand shape-based approach demonstrated a favorable improvement (area under the receiver operator characteristics curve AUC?=?.89?±?.02) and effectiveness (hit rate HR^1%?=?53.0%?±?6.3 and HR^10%?=?71.1%?±?4.9). The comparison of the overall performance of our ligand shape-based method with the highest ligand shape-based virtual screening approach using the data fusion of multi queries showed that our strategy takes into account deeper the chemical information of the set of active ligands. Furthermore, the results indicated that our method are suitable for virtual screening and yields superior prediction accuracy than the other study derived from the data fusion using five queries. Therefore, our novel ligand shape-based screening method constitutes a robust and efficient approach to the 3D similarity screening of small compounds and open the door to a whole new approach to drug design by implementing the method in the structure-based virtual screening.     

Computational design of auxotrophy-dependent microbial biosensors for combinatorial metabolic engineering experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools).     

Discovery of novel drug targets and their functions using phenotypic screening of natural products

Natural products are valuable resources that provide a variety of bioactive compounds and natural pharmacophores in modern drug discovery. Discovery of biologically active natural products and unraveling their target proteins to understand their mode of action have always been critical hurdles for their development into clinical drugs. For effective discovery and development of bioactive natural products into novel therapeutic drugs, comprehensive screening and identification of target proteins are indispensable. In this review, a systematic approach to understanding the mode of action of natural products isolated using phenotypic screening involving chemical proteomics-based target identification is introduced. This review highlights three natural products recently discovered via phenotypic screening, namely glucopiericidin A, ecumicin, and terpestacin, as representative case studies to revisit the pivotal role of natural products as powerful tools in discovering the novel functions and druggability of targets in biological systems and pathological diseases of interest.     

Development and application of a DNA microarray-based yeast two-hybrid system

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms.     

Systematic identification of SH3 domain-mediated human protein-protein interactions by peptide array target screening

Systematic identification of direct protein-protein interactions is often hampered by difficulties in expressing and purifying the corresponding full-length proteins. By taking advantage of the modular nature of many regulatory proteins, we attempted to simplify protein-protein interactions to the corresponding domain-ligand recognition and employed peptide arrays to identify such binding events. A group of 12 Src homology (SH) 3 domains from eight human proteins (Swiss-Prot ID: SRC, PLCG1, P85A, NCK1, GRB2, FYN, CRK) were used to screen a peptide target array composed of 1536 potential ligands, which led to the identification of 921 binary interactions between these proteins and 284 targets. To assess the efficiency of the peptide array target screening (PATS) method in identifying authentic protein-protein interactions, we examined a set of interactions mediated by the PLCgamma1 SH3 domain by coimmunoprecipitation and/or affinity pull-downs using full-length proteins and achieved a 75% success rate. Furthermore, we characterized a novel interaction between PLCgamma1 and hematopoietic progenitor kinase 1 (HPK1) identified by PATS and demonstrated that the PLCgamma1 SH3 domain negatively regulated HPK1 kinase activity. Compared to protein interactions listed in the online predicted human interaction protein database (OPHID), the majority of interactions identified by PATS are novel, suggesting that, when extended to the large number of peptide interaction domains encoded by the human genome, PATS should aid in the mapping of the human interactome.     

Discovery of novel triple helical DNA intercalators by an integrated virtual and actual screening platform

Virtual Screening is an increasingly attractive way to discover new small molecules with potential medicinal value. We introduce a novel strategy that integrates use of the molecular docking software Surflex with experimental validation by the method of competition dialysis. This integrated approach was used to identify ligands that selectively bind to the triplex DNA poly(dA)-[poly(dT)]₂. A library containing ~2 million ligands was virtually screened to identify compounds with chemical and structural similarity to a known triplex intercalator, the napthylquinoline MHQ-12. Further molecular docking studies using compounds with high structural similarity resulted in two compounds that were then demonstrated by competition dialysis to have a superior affinity and selectivity for the triplex nucleic acid than MHQ-12. One of the compounds has a different chemical backbone than MHQ-12, which demonstrates the ability of this strategy to ‘scaffold hop’ and to identify small molecules with novel binding properties. Biophysical characterization of these compounds by circular dichroism and thermal denaturation studies confirmed their binding mode and selectivity. These studies provide a proof-of-principle for our integrated screening strategy, and suggest that this platform may be extended to discover new compounds that target therapeutically relevant nucleic acid morphologies.     

Harnessing Single Cell Sorting to Identify Cell Division Genes and Regulators in Bacteria

Cell division is an essential cellular process that requires an array of known and unknown proteins for its spatial and temporal regulation. Here we develop a novel, high-throughput screening method for the identification of bacterial cell division genes and regulators. The method combines the over-expression of a shotgun genomic expression library to perturb the cell division process with high-throughput flow cytometry sorting to screen many thousands of clones. Using this approach, we recovered clones with a filamentous morphology for the model bacterium, Escherichia coli. Genetic analysis revealed that our screen identified both known cell division genes, and genes that have not previously been identified to be involved in cell division. This novel screening strategy is applicable to a wide range of organisms, including pathogenic bacteria, where cell division genes and regulators are attractive drug targets for antibiotic development.     

Dynamic combinatorial libraries of artificial repeat proteins

Repeat proteins are found in almost all cellular systems, where they are involved in diverse molecular recognition processes. Recent studies have suggested that de novo designed repeat proteins may serve as universal binders, and might potentially be used as practical alternative to antibodies. We describe here a novel chemical methodology for producing small libraries of repeat proteins, and screening in parallel the ligand binding of library members. The first stage of this research involved the total synthesis of a consensus-based three-repeat tetratricopeptide (TPR) protein (～14 kDa), via sequential attachment of the respective peptides. Despite the effectiveness of the synthesis and ligation steps, this method was found to be too demanding for the production of proteins containing variable number of repeats. Additionally, the analysis of binding of the individual proteins was time consuming. Therefore, we designed and prepared novel dynamic combinatorial libraries (DCLs), and show that their equilibration can facilitate the formation of TPR proteins containing up to eight repeating units. Interestingly, equilibration of the library building blocks in the presence of the biologically relevant ligands, Hsp90 and Hsp70, induced their oligomerization into forming more of the proteins with large recognition surfaces. We suggest that this work presents a novel simple and rapid tool for the simultaneous screening of protein mixtures with variable binding surfaces, and for identifying new binders for ligands of interest.     

Combinatorial chemical reengineering of the alpha class glutathione transferases

Previously, we discovered that human glutathione transferases (hGSTs) from the alpha class can be rapidly and quantitatively modified on a single tyrosine residue (Y9) using thioesters of glutathione (GS-thioesters) as acylating reagents. The current work was aimed at exploring the potential of this site-directed acylation using a combinatorial approach, and for this purpose a panel of 17 GS-thioesters were synthesized in parallel and used in screening experiments with the isoforms hGSTs A1-1, A2-2, A3-3, and A4-4. Through analytical HPLC and MALDI-MS experiments, we found that between 70 and 80% of the reagents are accepted and this is thus a very versatile reaction. The range of ligands that can be used to covalently reprogram these proteins is now expanded to include functionalities such as fluorescent groups, a photochemical probe, and an aldehyde as a handle for further chemical derivatization. This site-specific modification reaction thus allows us to create novel functional proteins with a great variety of artificial chemical groups in order to, for example, specifically tag GSTs in biological samples or create novel enzymatic function using appropriate GS-thioesters.     

RTP family members induce functional expression of mammalian odorant receptors

Transport of G protein-coupled receptors (GPCRs) to the cell surface membrane is critical in order for the receptors to recognize their ligands. However, mammalian GPCR odorant receptors (ORs), when heterologously expressed in cells, are poorly expressed on the cell surface. Here we show that the transmembrane proteins RTP1 and RTP2 promote functional cell surface expression of ORs expressed in HEK293T cells. Genes encoding these proteins are expressed specifically in olfactory neurons. These proteins are associated with OR proteins and enhance the OR responses to odorants. Similar although weaker effects were seen with a third protein, REEP1. These findings suggest that RTP1 and RTP2 in particular play significant roles in the translocation of ORs to the plasma membrane as well as in the functioning of ORs. We have used this approach to identify active odorant ligands for ORs, providing a platform for screening the chemical selectivity of the large OR family.     

Identification of the ligands of protein interaction domains through a functional approach

The identification of protein-protein interaction networks has often given important information about the functions of specific proteins and on the cross-talk among metabolic and regulatory pathways. The availability of entire genome sequences has rendered feasible the systematic screening of collections of proteins, often of unknown function, aimed to find the cognate ligands. Once identified by genetic and/or biochemical approaches, the interaction between two proteins should be validated in the physiologic environment. Herein we describe an experimental strategy to screen collections of protein-protein interaction domains to find and validate candidate interactors. The approach is based on the assumption that the overexpression in cultured cells of protein-protein interaction domains, isolated from the context of the whole protein, could titrate the endogenous ligand and, in turn, exert a dominant negative effect. The identification of the ligand could provide us with a tool to check the relevance of the interaction because the contemporary overexpression of the isolated domain and of its ligand could rescue the dominant negative phenotype. We explored this approach by analyzing the possible dominant negative effects on the cell cycle progression of a collection of phosphotyrosine binding (PTB) domains of human proteins. Of 47 PTB domains, we found that the overexpression of 10 of them significantly interfered with the cell cycle progression of NIH3T3 cells. Four of them were used as baits to identify the cognate interactors. Among these proteins, CARM1, interacting with the PTB domain of RabGAP1, and EF1alpha, interacting with RGS12, were able to rescue the block of the cell cycle induced by the isolated PTB domain of the partner protein, thus confirming in vivo the relevance of the interaction. These results suggest that the described approach can be used for the systematic screening of the ligands of various protein-protein interaction domains also by using different biological assays.     

Identification of VCP/p97, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners using membrane-based human proteome arrays

Proteins mediate their biological function through interactions with other proteins. Therefore, the systematic identification and characterization of protein-protein interactions have become a powerful proteomic strategy to understand protein function and comprehensive cellular regulatory networks. For the screening of valosin-containing protein, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners, we utilized a membrane-based array technology that allows the identification of human protein-protein interactions with crude bacterial cell extracts. Many novel interaction pairs such as valosin-containing protein/autocrine motility factor receptor, CHIP/caytaxin, or amphiphysin II/DLP4 were identified and subsequently confirmed by pull-down, two-hybrid and co-immunoprecipitation experiments. In addition, assays were performed to validate the interactions functionally. CHIP e.g. was found to efficiently polyubiquitinate caytaxin in vitro, suggesting that it might influence caytaxin degradation in vivo. Using peptide arrays, we also identified the binding motifs in the proteins DLP4, XRCC4, and fructose-1,6-bisphosphatase, which are crucial for the association with the Src homology 3 domain of amphiphysin II. Together these studies indicate that our human proteome array technology permits the identification of protein-protein interactions that are functionally involved in neurodegenerative disease processes, the degradation of protein substrates, and the transport of membrane vesicles.     

Identification of specific reachable molecular targets in human breast cancer using a versatile ex vivo proteomic method

Targeting of tumoral tissues is one of the most promising approaches to improve both the efficacy and safety of anticancer treatments. The identification of valid targets, including proteins specifically and abundantly expressed in cancer lesions, is of utmost importance. Despite state-of-the-art technologies, the discovery of cancer-associated target proteins still faces the limitation, in human tissues, of antigen accessibility to suitable high-affinity ligands such as human mAb bound to bioactive molecules. Terminal perfusion of tumor-bearing mice or ex vivo perfusion of human cancer-bearing organs with a reactive biotin ester solution has successfully led to the identification of novel accessible biomarkers. This methodology is however restricted to perfusable organs, and excludes most of the tissues of interest to targeted therapies, e.g. primary breast cancer and metastases. Herein, we report on the development of a new chemical proteomic method that bypasses the perfusion step and thus offers the potential to identify accessible molecular targets in virtually all types of animal and human tissues. We have validated our new procedure by identifying biomarkers selectively expressed in human breast carcinoma. Overall, this powerful technology may lay the ground not only for custom-made therapies in cancer, but also for the development of therapies that need to be selectively delivered in a specific tissue.     

Identification of novel proteins in Neospora caninum using an organelle purification and monoclonal antibody approach

Neospora caninum is an important veterinary pathogen that causes abortion in cattle and neuromuscular disease in dogs. Neospora has also generated substantial interest because it is an extremely close relative of the human pathogen Toxoplasma gondii, yet does not appear to infect humans. While for Toxoplasma there are a wide array of molecular tools and reagents available for experimental investigation, relatively few reagents exist for Neospora. To investigate the unique biological features of this parasite and exploit the recent sequencing of its genome, we have used an organelle isolation and monoclonal antibody approach to identify novel organellar proteins and develop a wide array of probes for subcellular localization. We raised a panel of forty-six monoclonal antibodies that detect proteins from the rhoptries, micronemes, dense granules, inner membrane complex, apicoplast, mitochondrion and parasite surface. A subset of the proteins was identified by immunoprecipitation and mass spectrometry and reveal that we have identified and localized many of the key proteins involved in invasion and host interaction in Neospora. In addition, we identified novel secretory proteins not previously studied in any apicomplexan parasite. Thus, this organellar monoclonal antibody approach not only greatly enhances the tools available for Neospora cell biology, but also identifies novel components of the unique biological characteristics of this important veterinary pathogen.     

In silico directed chemical probing of the adenosine receptor family

One of the grand challenges in chemical biology is identifying a small-molecule modulator for each individual function of all human proteins. Instead of targeting one protein at a time, an efficient approach to address this challenge is to target entire protein families by taking advantage of the relatively high levels of chemical promiscuity observed within certain boundaries of sequence phylogeny. We recently developed a computational approach to identifying the potential protein targets of compounds based on their similarity to known bioactive molecules for almost 700 targets. Here, we describe the direct identification of novel antagonists for all four adenosine receptor subtypes by applying our virtual profiling approach to a unique synthesis-driven chemical collection composed of 482 biologically-orphan molecules. These results illustrate the potential role of in silico target profiling to guide efficiently screening campaigns directed to discover new chemical probes for all members of a protein family.     

Docking and scoring with alternative side-chain conformations

We describe a scoring and modeling procedure for docking ligands into protein models that have either modeled or flexible side-chain conformations. Our methodical contribution comprises a procedure for generating new potentials of mean force for the ROTA scoring function which we have introduced previously for optimizing side-chain conformations with the tool IRECS. The ROTA potentials are specially trained to tolerate small-scale positional errors of atoms that are characteristic of (i) side-chain conformations that are modeled using a sparse rotamer library and (ii) ligand conformations that are generated using a docking program. We generated both rigid and flexible protein models with our side-chain prediction tool IRECS and docked ligands to proteins using the scoring function ROTA and the docking programs FlexX (for rigid side chains) and FlexE (for flexible side chains). We validated our approach on the forty screening targets of the DUD database. The validation shows that the ROTA potentials are especially well suited for estimating the binding affinity of ligands to proteins. The results also show that our procedure can compensate for the performance decrease in screening that occurs when using protein models with side chains modeled with a rotamer library instead of using X-ray structures. The average runtime per ligand of our method is 168 seconds on an Opteron V20z, which is fast enough to allow virtual screening of compound libraries for drug candidates.     

Obtaining and screening compound collections: a user's guide and a call to chemists

Advances in genetics, proteomics and cell biology over the past 20 years have unearthed a multitude of potential macromolecular targets for the selective treatment of disease. The challenge remains to find appropriate small molecule ligands for these proteins (or nucleic acids), and to use these ligands to validate novel disease targets. The advent of low-cost instrumentation has made industrial-style high-throughput screening possible in academic settings. Unfortunately for many, access to large collections of compounds is still limited and limiting. This article is aimed at the user who has an interest in compound screening but does not have ready access to large collections of small molecules. High-throughput screening need not be the exclusive domain of institutions and centers with vast resources and NIH Roadmap-funded compound repositories. As it turns out, many of the most interesting compounds are probably within arm's reach, in our laboratory freezers and in those of our colleagues.     

Enabling large-scale design, synthesis and validation of small molecule protein-protein antagonists

Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure.     

Chemical genomics: a systematic approach in biological research and drug discovery

The knowledge of complete sequences of different organisms is dramatically changing the landscape of biological research and pharmaceutical development. We are experiencing a transition from a trial-and-error approach in traditional biological research and natural product drug discovery to a systematic operation in genomics and target-specific drug design and selection. Small, cell-permeable and target-specific chemical ligands are particularly useful in systematic genomic approaches to study biological questions. On the other hand, genomic sequence information, comparative and structural genomics, when combined with the cutting edge technologies in synthetic chemistry and ligand screening/identification, provide a powerful way to produce target-specific and/or function-specific chemical ligands and drugs. Chemical genomics or chemogenomics is a new term that describes the development of target-specific chemical ligands and the use of such chemical ligands to globally study gene and protein functions. We anticipate that chemical genomics plays a critical role in the genomic age of biological research and drug discovery.