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Affinity-based DNA-encoded library (DEL) selection is considered a powerful tool for small molecule drug discovery. Such selections are a multi-round process that involves incubation of a target protein with the DEL, capture of the protein and associated DEL compounds on a solid support, separation of bound molecules from the bulk DEL that is unbound, and recovery of bound DEL molecules. Each step is of great importance in order to achieve successful selections. Here we describe the selection process against a soluble target protein in both the immobilized and in-solution modes., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

Drug affinity responsive target stability (DARTS) assay is used to detect the interaction between a ligand and a protein based on the observation that some ligands can protect the target protein from degradation by proteases when mixed in a solution. To set up the assay, a ligand is first mixed with a purified candidate target protein or a total cell lysate that contains a candidate target protein. Then, different amounts of protease are added to the mixture to allow the enzyme to digest the protein in the mixture. After protease digestion, the candidate target protein is detected by assays such as western blot, silver staining, or Coomassie blue staining. In theory, the candidate protein should be protected by the ligand from protease digestion, which is reflected by higher abundance of the candidate protein in mixtures containing the ligand compared with the control treatment. There are a few significant advantages of DARTS: (a) the ligand does not need to be modified so the native ligand could be used; (b) the candidate target protein could be either purified protein or protein that is present in the total cell lysate; and (c) the assay can be used together with proteomics analysis to identify an unknown target protein. The assay is especially valuable to test the interaction between the ligand and membrane proteins that are often challenging to purify. In this chapter, we use Endosidin2 (ES2) and its target protein Arabidopsis thaliana EXO70A1 (AtEXO70A1) as an example to show the step-by-step procedure of the DARTS assay.

In silico simulations of biological systems are of the significant importance to obtain insights on specific processes that experimental protocols have difficulty to elucidate. More particularly, and to ensure that a given molecule is able to reach its cellular target, the development of computational methods able to quickly estimate the cellular permeabilities for small molecules can become an important tool in the early stages of drug development. Herein, a computational protocol for predicting permeability coefficients, concerning both membranes and proteins, is presented and discussed., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)

Microscale thermophoresis (MST) is a biophysical assay to quantify the interaction between molecules, such as proteins and small molecules. In recent years, the MST assay has been used to detect protein-protein and protein-drug interactions. The assay detects the interaction between molecules by quantifying the thermophoretic movement of fluorescent molecules in response to a temperature gradient. In practice, the fluorescent molecule is mixed with different concentrations of the nonfluorescent ligand, and the mixture of molecules in solution is loaded to capillaries. A temperature gradient is applied to samples in the capillaries, and the movement of the fluorescent molecule in the temperature gradient is detected and recorded. The effect of different concentrations of the nonfluorescent ligand on the movement of the fluorescent molecule is quantified to test for the interaction between molecules. If the fluorescent molecule interacts with the ligand, the molecular properties of the molecules, such as charge, size, and hydration shell, will influence the molecular motility. MST has the advantages of being quantitative and robust. In this chapter, we will use Endosidin2 and its target protein Arabidopsis thaliana EXO70A1 (AtEXO70A1), as an example to show the procedure of using MST to test the interaction between a GFP-tagged protein and a small molecule.

Nanopore enzymology is a powerful single-molecule technique for the label-free study of enzymes using engineered protein nanopore sensors. The technique has been applied to protein kinases, where it has enabled the full repertoire of kinase function to be observed, including: kinetics of substrate binding and dissociation, product binding and dissociation, nucleotide binding, and reversible phosphorylation. Further, minor modifications enable the screening of type I kinase inhibitors and the determination of inhibition constants in a facile and label-free manner. Here, we describe the design and production of suitably engineered protein nanopores and their use for the determination of key mechanistic parameters of kinases. We also provide procedures for the determination of inhibition constants of protein kinase inhibitors.

Apoptosis, a form of programmed cell death that is important for development and homeostasis, is regulated by the BCL-2 family of proteins. Over twenty BCL-2 family members have been classified in three groups based on structural homology and function. The multidomain antiapoptotic proteins promote survival, whereas the multidomain and the BH3-only proapoptotic members induce cell death. Because the interaction among the BCL-2 family members occurs primarily at the mitochondrial outer membrane, biochemical assays using artificial liposomes have been developed to study the functional relationship between these proteins. The liposomal permeabilization assay is a cell-free system that relies on the ability of multidomain pro-apoptotic members to promote membrane permeabilization upon activation. By encapsulating a fluorophore and a quencher into liposomes, the degree of permeabilization can be quantified by the increase in fluorescence intensity as the fluorophore and quencher dissociate. The liposomal permeabilization assay has been used to delineate interactions among BCL-2 family members as well as to characterize peptides, small molecules, and lipids that modulate the function of BCL-2 family of proteins. Here, we describe in detail the permeabilization of liposomes induced by the interaction between BAX and BH3-only activator tBID.

DNA-encoded library technology (ELT) is a cutting-edge enabling technology platform for drug discovery. Here we describe how to design and synthesize a macrocyclic DNA-encoded library; how to perform selection, sequencing, and data analysis to identify potential active peptides; and how to synthesize off-DNA peptides to confirm activity. This approach provides an effective tool for pharmaceutical research based on peptides.

Biomolecular nuclear magnetic resonance (NMR) is a powerful and versatile method for studying both protein-protein interactions (PPIs) and protein-small molecule binding. NMR has been used extensively in the investigation of BCL-2 family proteins revealing the structure of key family members, identifying binding partners and interaction sites, and screening small molecule modulators. In this chapter we discuss the application of NMR to identify interaction sites and structure determination of protein-protein and protein-small molecule complexes using two examples.

Knowing the physicochemical and general biochemical properties of a compound is critical to understanding how it behaves in different biological environments and to anticipating what is likely to happen in situations where that behavior cannot be measured directly. Quantitative structure-property relationship (QSPR) models provide a way to predict those properties even before a compound has been synthesized simply by knowing what its structure would be. This chapter describes a general workflow for compiling the data upon which a useful QSPR model is built, curating it, evaluating that model's performance, and then analyzing the predictive errors with an eye toward identifying systematic errors in the input data. The focus here is on models for the absorption, distribution, metabolism, and excretion (ADME) properties of drugs and toxins, but the considerations explored are general and applicable to any QSPR.

Capture-SELEX is an effective molecular strategy enabling the discovery of structure-switching aptamers, which might find useful application in molecular detection or separation. We here provide a protocol to perform capture-SELEX for DNA aptamers binding soluble small molecules, which includes a straightforward functional validation by SPR. The SELEX strategy here described is adaptable to any water-soluble molecular target and might foster the development of DNA aptamers binding therapeutic small molecules, at the great advantage of clinical bioanalytics.

Docking algorithms have been widely used to elucidate ligand:receptor interactions that are important in biological function. Here, we introduce an in-house developed docking-refinement protocol that combines the following innovative features. (1) The use of multiple short molecular dynamics (MD) docking simulations, with residues within the binding pocket of the receptor unconstrained, so that the binding modes of the ligand in the binding pocket may be exhaustively examined. (2) The initial positioning of the ligand within the binding pocket based on complementary shape, and the use of both harmonic and quartic spherical potentials to constrain the ligand in the binding pocket during multiple short docking simulations. (3) The selection of the most probable binding modes generated by the short docking simulations using interaction energy calculations, as well as the subsequent application of all-atom MD simulations and physical-chemistry based free energy calculations to elucidate the most favorable binding mode of the ligand in complex with the receptor. In this chapter, we provide step-by-step instructions on how to computationally investigate the binding of small-molecule ligands to protein receptors by examining as control and test cases, respectively, the binding of L-serine and R-3,4-dihydroxymandelic acid (R-DHMA) to the Escherichia coli chemoreceptor Tsr. Similar computational strategies can be used for the molecular modeling of a series of ligand:protein receptor interactions.

Protein-small molecule interaction studies provide useful insights into biological processes taking place within the living cell. A special yeast hybrid system, the yeast three-hybrid method, has been developed and used to explore proteins that bind to small molecules, by which means it may be possible to unravel biological processes and dissect function of biological systems. Here we present a protocol employing this method for identifying such binding proteins.

Ligand-receptor interactions triggering signal transduction components of many sensory pathways, remain elusive due to paucity of high-throughput screening methods. Here we describe our use of small molecule microarrays comprising of small glycans, amino and organic acids, salts, and other known chemoeffectors, for screening of ligands specific to various sensory receptors, followed by surface plasmon resonance to verify the veracity and to determine the affinity constants of the interactions. This methodology allows for rapid and identification of the direct ligand binding between the sensory receptors and their specific ligands.

The Escherichia coli chemotaxis protein CheY is a model receiver domain containing a native tryptophan residue that serves as a fluorescent probe for CheY autophosphorylation with small molecule phosphodonors. Here we describe fluorescence measurement of apparent bimolecular rate constants for reaction of wild type and mutant CheY with phosphodonors acetyl phosphate, phosphoramidate, or monophosphoimidazole. Step-by-step protocols to synthesize phosphoramidate (K + salt) and monophosphoimidazole (Na + salt), which are not commercially available, are provided. Key factors to consider in developing autophosphorylation assays for other response regulators are also discussed.

RNA aptamers can serve as valuable tools for studying and manipulating live cells. Fluorescent aptamers are the ones that bind to and turn on fluorescence of small-molecule dyes (fluorogens). Similarly to fluorescent proteins, fluorescent RNA aptamers can be used to image spatial and temporal RNA dynamics in live cells. Additionally, these aptamers can serve as a basis for engineering genetically encoded fluorescent biosensors. This chapter presents a protocol for rapid and efficient screening of RNA aptamer libraries to isolate fluorescent aptamers. The protocol describes how to design, clone, and express RNA aptamer library in bacterial cells and how to screen the bacteria to find aptamers with the desired fluorescent properties.

The over 500 human protein kinases are estimated to phosphorylate at least one-third of the proteome. This posttranslational modification is of paramount importance to intracellular signaling and its deregulation is linked to numerous diseases. Deciphering the specific cellular role of a protein kinase of interest remains challenging given their structural similarity and potentially overlapping activity. In order to exert control over the activity of user-defined kinases and allow for understanding and engineering of complex signal transduction pathways, we have designed ligand inducible split protein kinases. In this approach, protein kinases are dissected into two fragments that cannot spontaneously assemble and are thus inactive. The two kinase fragments are attached to chemical inducers of dimerization (CIDs) that allow for ligand induced heterodimerization and concomitant activation of kinase activity.

Despite many years of research into bacterial chemotaxis, the only well characterized system to date is that of E. coli. Even for E. coli, the direct ligand binding had been fully characterized only for aspartate and serene receptors Tar and Tsr. In 30 years since, no other direct receptor-ligand interaction had been described for bacteria, until the characterization of the C. jejuni aspartate and multiligand receptors (Hartley-Tassell et al. Mol Microbiol 75:710-730, 2010). While signal transduction components of many sensory pathways have now been characterized, ligand-receptor interactions remain elusive due to paucity of high-throughput screening methods. Here, we describe the use of microarray screening we developed to identify ligands, surface plasmon resonance, and saturation transfer difference nuclear magnetic resonance (STD-NMR) we used to verify the hits and to determine the affinity constants of the interactions, allowing for more targeted verification of ligands with traditional chemotaxis and in vivo assays described in Chapter 13 .

New methods to identify RNA-binding small molecules open yet unexplored opportunities for the pharmacological modulation of RNA-driven biology and disease states. One such approach is the use of small molecule microarrays (SMMs). Typically, SMMs are generated by spatially arraying and covalently linking a library of small molecules to a glass surface. Next, incubation of the arrays with a fluorescently labeled RNA reveals binding interactions that are detected upon slide imaging. The relative ease with which SMMs are manufactured enables the screening of multiple oligonucleotides in parallel against tens of thousands of small molecules, providing information about both binding and selectivity of identified RNA-small molecule interactions. This approach is useful for screening a broad variety of structurally and functionally diverse RNAs. Here, we present a general method for the preparation and use of SMMs to rapidly identify small molecules that selectively bind to an RNA of interest.

Whilst small interfering (si) RNAs have emerged as a promising therapeutic modality for treating a diversity of human diseases, delivery constitutes the most serious obstacle to siRNA drug development. As the most used delivery agents can enter all cell types, specificity must be built into the delivery agents or directly attached to the siRNA molecules. The use of antibodies, peptides, Peptide-Fc fusions, aptamers, and other targeting ligands has now enabled efficient gene silencing in the desired cell populations/tissues in vitro and in vivo. The present review summarizes these current innovations, which are important for the design of safe therapeutic siRNAs.

Fragment-based drug design has proved itself as a powerful technique for increasing the sampling and diversity of chemical space and enabling the design of novel leads and compounds. Computational techniques for identifying fragments, binding sites and particularly for linking, growing, and evolving fragments play a significant role in the process. Information from ADME studies and clustering property information in the form of toxicophores and chemotypes can play a significant role in aiding the design of novel, selective fragments with good activity profiles.

Fragment-based drug design represents a challenge for computational drug design because almost inevitably fragments will be weak binders to the biomolecular targets of a specific disease, and the performances of the scoring functions for weak binders are usually poorer than those for the stronger binders. This protocol describes how to predict the binding modes and binding affinities of fragments towards their binding partner with our refined AutoDock scoring function incorporating a quantum chemical charge model, namely, the restrained electrostatic potential (RESP) model. This scoring function was calibrated by robust regression analysis and has been demonstrated to perform well for general classes of protein-ligand interactions and for weak binders (with root-mean square of error of about 2.1 kcal/mol).

We present a new protocol aimed at the structure-based design of drug-like molecules using a fragment approach. It starts from a suitably placed and well-defined "base fragment" and then uses an incremental construction algorithm and a scoring function to grow the molecule into prioritized candidates. The selection of the most promising solutions for synthesis and validation is guided by the optimization of the calculated ligand efficiency indices known as binding efficiency index (BEI) and surface efficiency index (SEI), which allow the user to navigate proficiently in chemico-biological space. A test case for the protocol is exemplified here using published data for inhibitors of protein kinase B, aka AKT, a key enzyme in several signal transduction pathways. Our procedure was able to identify the main features responsible for the binding of inhibitors and guided the selection process towards molecules that included or resembled those shown as the most active in the original studies.

Fragment hopping is a fragment-based approach to designing biologically active small molecules. The key of this approach is the determination of the minimal pharmacophoric elements in the three-dimensional space. Based on the derived minimal pharmacophoric elements, new fragments with different chemotypes can be generated and positioned to the active site of the target protein. Herein, we detail a protocol for performing fragment hopping. This approach can not only explore a wide chemical space to produce new ligands with novel scaffolds but also characterize and utilize the delicate differences in the active sites between isofunctional proteins to produce new ligands with high target selectivity/specificity.

One of the most powerful tools for designing drug molecules is an understanding of the target protein's binding site. Identifying key amino acids and understanding the electronic, steric, and solvation properties of the site enables the design of potent ligands. Of equal importance for the success of a drug discovery program is the evaluation of binding site druggability. Determining, a priori, if a particular binding site has the appropriate character to bind drug-like ligands saves research time and money.While there are a variety of experimental and computational techniques to identify and characterize binding sites, the focus of this chapter is on Binding Site Analysis (BSA) using virtual fragment simulations. The methodology of the technique is described, along with examples of successful application to drug discovery programs. BSA both indicates if a protein is a viable target for drug discovery and provides a roadmap for designing ligands. Using a computational fragment-based method is a effective means of understanding of a binding site.

Fragment-based drug design (FBDD) involves screening low molecular weight molecules ("fragments") that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind nonoverlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy.The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is "soaked" in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called "FragMaps" can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine "Grid Free Energies (GFEs)," which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities.

The identification of proteins that interact with small bioactive molecules is a critical but often difficult and time-consuming step in understanding cellular signaling pathways or molecular mechanisms of drug action. Numerous methods for identifying small molecule-interacting proteins have been developed and utilized, including affinity-based purification followed by mass spectrometry analysis, protein microarrays, phage display, and three-hybrid approaches. Although all these methods have been used successfully, there remains a need for additional techniques for analyzing small molecule-protein interactions. A promising method for identifying small molecule-protein interactions is affinity-based selection of yeast surface-displayed human proteome libraries. Large and diverse libraries displaying human protein fragments on the surface of yeast cells have been constructed and subjected to FACS-based enrichment followed by comprehensive exon microarray-based output analysis to identify protein fragments with affinity for small molecule ligands. In a recent example, a proteome-wide search has been successfully carried out to identify cellular proteins binding to the signaling lipids PtdIns(4,5)P2 and PtdIns(3,4,5)P3. Known phosphatidylinositide-binding proteins such as pleckstrin homology domains were identified, as well as many novel interactions. Intriguingly, many novel nuclear phosphatidylinositide-binding proteins were discovered. Although the existence of an independent pool of nuclear phosphatidylinositides has been known about for some time, their functions and mechanism of action remain obscure. Thus, the identification and subsequent study of nuclear phosphatidylinositide-binding proteins is expected to bring new insights to this important biological question. Based on the success with phosphatidylinositides, it is expected that the screening of yeast surface-displayed human proteome libraries will be of general use for the discovery of novel small molecule-protein interactions, thus facilitating the study of cellular signaling pathways and mechanisms of drug action or toxicity.

Genome-wide association studies and genetic linkage studies have created a growing list of proteins related to disease. Small molecules can serve as useful probes of function for these proteins in a cellular setting or may serve as leads for therapeutic development. High-throughput and general binding assays may provide a path for discovering small molecules that target proteins for which little is known about structure or function or for which conventional functional assays have failed. One such binding assay involves small-molecule microarrays (SMMs) containing compounds that have been arrayed and immobilized onto a solid support. The SMMs can be incubated with a protein target of interest and protein-small molecule interactions may be detected using a variety of fluorescent readouts. Several suitable methods for manufacturing SMMs exist and different immobilization methods may be more or less preferable for any given application. Here, we describe protocols for covalent capture of small molecules using an isocyanate-coated glass surface and detection of binding using purified protein.

Affinity chromatography is the method of choice for biomolecule separation and isolation with highly specific target recognition; it is ideally suited to the purification of immunotherapeutic proteins (i.e., mAbs). Conventional affinity purification protocols are based on natural immunoglobulin (Ig)-binding proteins, which are expensive to produce, labile, unstable, and exhibit lot-to-lot variability. Biological ligands are now being replaced by cost-effective, synthetic ligands, derived from the concepts of rational design and combinatorial chemistry, aided by in silico approaches. In this chapter, we describe a new synthetic procedure for the development of affinity ligands for immunoglobulins based on the multicomponent Ugi reaction. The lead ligand developed herein is specific for the IgG-Fab fragment and mimics Protein L (PpL), an IgG-binding protein isolated from Peptostreptococcus magnus strains and usually used for the purification of antibodies and their fragments.

Small molecule-immobilized affinity matrices are indispensable tools in chemical genomics to screen and purify protein targets for biologically active small molecules. Usually, prior to immobilization, small -molecules have to be derivatized at a position that does not significantly abrogate the intrinsic biological activity, or chemically synthesized to have an appropriate functional group for the immobilization chemistry. Here, we describe a photo-cross-linking technique to immobilize biologically active small molecules for protein target screening, without the need for chemical derivatization.

Despite the hundreds of kinase inhibitors currently in discovery and pre-clinical phases, the number of kinase inhibitors which have been approved and are on the market remains low by comparison. This discrepancy reflects the challenges which accompany the development of kinase inhibitors which are relatively specific and less toxic. Targeting protein kinases with ATP-competitive inhibitors has been the classical approach to inhibiting kinase activity, but the highly conserved nature of the ATP-binding site contributes to poor inhibitor selectivity, issues which have particularly hampered the development of novel kinase inhibitors. We developed a high-throughput screening technology that can discriminate for inhibitors which stabilize the inactive "DFG-out" kinase conformation by binding within an allosteric pocket adjacent to the ATP-binding site. Here, we describe how to use this approach to measure the K (d) of ligands, as well as how to kinetically characterize the binding and dissociation of ligands to the kinase. We also describe how this technology can be used to rapidly screen small molecule libraries at high throughput.

In affinity-based chemoproteomics strategies, the direct immobilization of small bioactive probe molecules to a solid support may pose problems with respect to the preservation of the functional activity toward the target proteins. Typically, immobilized molecules on solid supports exhibit lower affinity for target proteins compared to the free parent molecule. This may lead to a failure to specifically capture the target proteins or to unacceptable losses during the washing steps. To circumvent these shortcomings, we have devised small molecule-peptide conjugates (SMPCs), which enable wide-ranging experimental strategies for the capturing of protein targets of small molecules from cells or tissues. With the possibilities of synthesizing peptides of tailored biochemical and biophysical properties, SMPCs enable the identification of protein targets of small molecules from cell-lysates and intact cells. Moreover, labeling of these conjugates with fluorophores can provide information on the cellular localization and distribution of the target.

Multiproperty lead optimization that satisfies multiple biological endpoints remains a challenge in the pursuit of viable drug candidates. Optimization of a given lead compound to one having a desired set of molecular attributes often involves a lengthy iterative process that utilizes existing information, tests hypotheses, and incorporates new data. Within the context of a data-rich corporate setting, computational tools and predictive models have provided the chemists a means for facilitating and streamlining this iterative design process. This chapter discloses an actual library design scenario for following up a lead compound that inhibits 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme. The application of computational tools and predictive models in the targeted library design of adamantyl amide 11β-HSD1 inhibitors is described. Specifically, the multiproperty profiling using our proprietary PGVL (Pfizer Global Virtual Library) Hub is discussed in conjunction with the structure-based component of the library design using our in-house docking tool AGDOCK. The docking simulations were based on a piecewise linear potential energy function in combination with an efficient evolutionary programming search engine. The library production protocols and results are also presented.

We present here a workflow for designing a kinase-targeted library (KTL) with the goal of capturing known kinase inhibitor chemical space. We validated our design retrospectively using recent, high-throughput screening data and found significant enrichment of kinase inhibitor hits while retaining majority of the active kinase inhibitor series. To further assist kinase projects in triaging KTL screen hits, we also developed a methodology to systematically annotate known kinase inhibitors in the KTL with regard to their binding modes.

A successful fragment-based lead discovery (FBLD) campaign largely depends on the content of the fragment collection being screened. To design a successful fragment collection, several factors must be considered, including collection size, property filters, hit follow-up considerations, and screening methods. In this chapter, we will discuss each factor and how it was applied to the design and assembly of one or more fragment collections in a major pharmaceutical company setting. We will also present examples and statistics of screening results from such collections and how subsequent collections can be improved. Lastly, we will provide a summary comparison of selected fragment collections from literature.

PGVL Hub is a Pfizer internal desktop tool for chemical library and singleton design. In this chapter, we give a short introduction to PGVL Hub, the core workflow it supports, and the rich design capabilities it provides. By re-creating two legacy targeted libraries against the human checkpoint kinase 1 (Chk1) as a showcase, we illustrate how PGVL Hub could be used to help library designers carry out the steps in library design and realize design objectives such as SAR expansion and improvement in both kinase selectivity and compound aqueous solubility. Finally we share several tips about library design and usage of PGVL Hub.

The drug discovery process mainly relies on the experimental high-throughput screening of huge compound libraries in their pursuit of new active compounds. However, spiraling research and development costs and unimpressive success rates have driven the development of more rational, efficient, and cost-effective methods. With the increasing availability of protein structural information, advancement in computational algorithms, and faster computing resources, in silico docking-based methods are increasingly used to design smaller and focused compound libraries in order to reduce screening efforts and costs and at the same time identify active compounds with a better chance of progressing through the optimization stages. This chapter is a primer on the various docking-based methods developed for the purpose of structure-based library design. Our aim is to elucidate some basic terms related to the docking technique and explain the methodology behind several docking-based library design methods. This chapter also aims to guide the novice computational practitioner by laying out the general steps involved for such an exercise. Selected successful case studies conclude this chapter.

The identification of specific interactions between small molecules and human proteins of interest is a fundamental step in chemical biology and drug development. The small molecules that bind to specific proteins can be used as tools to study the functions of proteins and biological processes in cells. We have developed an efficient method to obtain novel binding ligands of human proteins by a chemical array approach. Our method includes the use of cell lysates that express proteins of interest fused with red fluorescent protein (RFP) and high-throughput screening by merged display analysis, which removes false positive signals from array experiments. To demonstrate large-scale ligand screening for various human proteins of interest, the gene library GLORIA (Gene Library of Osada Laboratory at RIKEN for chemical array analysis) has been established. Using the systematic platform, we detected novel inhibitors of carbonic anhydrase II. We also have shown that this screening method is useful not merely for ligand screening of proteins of interest, but also for gaining insight into structure-affinity relationships (SARs) and for studies of "fragment-based approach."Traditional fragment-based ligand discoveries have been demonstrated by using several technologies, such as NMR spectroscopy and X-ray crystallography and mass spectrometry. We present initial studies of fragment-based approach to binding assay by using the chemical array format.

Prion diseases, also called transmissible spongiform encephalopathies (TSEs), are a group of neurodegenerative disorders affecting animals and humans. No effective treatments are currently available for the diseases, vCJD in particular. It is believed that the formation of protease-resistant insoluble prion protein (PrP(Sc)), which is the main component of amyloidal deposits, from the cellular prion protein (PrP(C)), is essential for the progression of the disease. Therefore, both PrP(Sc) and PrP(C) are currently being used as potential drug targets.This protocol details an optimised experimental protocol to conduct an affinity screening of compound libraries by the immobilisation of PrP(C) using an SPR-based instrument, Biacore 3000.

General binding assays involving microarrays of small molecules can be used to identify small molecule ligands for nearly any protein, even in the absence of knowledge about protein structure or function. Several suitable methods for manufacturing small molecule microarrays (SMMs) exist and different immobilization methods may be more or less preferable for any given application. Here, we describe a protocol for noncovalent and homogenous capture of small molecules using fluorous interactions between small molecules containing fluorocarbon tags and fluorocarbon-coated glass surfaces. These arrays are especially useful for applications that require display of compounds in a specific orientation such as screening biased libraries.

The promise of rapid and cost-effective drug screening assays on solid support is one that may now be realized with the advent of small molecule microarrays. Many of the initial hurdles in library design and microarray fabrication have been overcome over the last decade, allowing this platform to become more accessible to researchers across both the academic and industrial spheres. Beyond pharmaceutical screening, microarrays reveal quantitative ligand-binding signatures that in the form of protein fingerprints provide a means to discriminate between closely related proteins. The value of protein fingerprinting in drug discovery is also highlighted through the identification of ligands that not only offer good potency, but also good selectivity. Herein, we describe the method for high-throughput screening and profiling of metalloproteases on small molecule microarrays. Metalloproteases are an important class of proteins, which are implicated in the pathogenicity of certain microbes and in the progression of cancer. We have introduced a novel two-colour labelling and application approach that directly elucidates functional ligands, reducing the burden of downstream revalidation of identified hits.

Speed and throughput are vital ingredients for discovery-driven, "-omics" research. The small molecule microarray is one such platform, which delivers phenomenal screening throughput and capabilities. The concept at the heart of the technology is elegant, yet simple: by presenting large collections of molecules at a high density on a flat surface, one is able to interrogate them quickly and conveniently, evaluating all possible interactions in a single step. SMMs have, over the last decade, been established as a robust platform for screening, lead discovery, and molecular characterization. In this chapter, we describe the ways in which microarrays have been constructed and applied, focusing on the practical challenges faced when designing and performing SMM experiments. This is written as an introduction for new readers to the field, explaining the key principles and laying the foundation for the chapters that follow.

Proteomic screening with small molecule microarrays can be a powerful tool in conjunction with various forward chemical genetics screening and high-throughput phenotype assays. Small molecule microarray screening can provide high quality information from the direct binding interaction between proteins of interest and a collection of small molecules in a high-throughput fashion. To realize this potential of small molecule microarray in the postgenomic era, the immobilization of small molecules on the surface of microscope glass slides has been a critical step, to apply small molecule library in protein screening assays and dissecting the protein network. In this chapter, we would like to focus on the protocol for the systematic immobilization of synthetic drug-like small molecules containing either specific functional handles or common functional groups.

We describe herein a new method for the high-throughput identification of affinity-based probes (AfBPs) using a small molecule microarray (SMM) approach. A hydroxylethylene-based small molecule library was first generated by solid-phase combinatorial synthesis. The library was tagged with biotin to facilitate immobilization on avidin-coated slides. Preliminary screening with γ-secretase (both the recombinantly purified protein as well as cellular lysates overexpressing the enzyme) was carried out, in order to identify potential small molecule binders, which were subsequently redesigned into AfBPs. Several specific and potent probes for γ-secretase were thus identified through the binding profiles observed on the SMMs. The SMM platform was able to sensitively and conveniently report activity-based binding interactions between aspartic proteases and their small molecule inhibitors. This new approach thus provides a potentially more rapid and efficient method for developing AfBPs using SMMs.

Conditional gene expression systems are important tools to identify the function of essential genes or in terms of gene therapy approaches. Small molecule-binding aptamers can be used for efficient control of gene expression by inserting them into the 5' untranslated region of an mRNA with the ligand-bound form inhibiting gene expression by interfering with translation initiation. However, only a small fraction of in vitro selected aptamers has the potential to act as regulator of gene expression which originates the necessity to develop screening systems for the identification of regulatory active aptamers. We describe here a simple and powerful yeast-based screening system which allows the rapid identification of small molecule-binding aptamers with the potential to act as artificial riboswitches for conditional control of gene expression.

Low-throughput screening for bioactive substances often represents the only way to discover new ligands of a drug target. This limits the number of compounds that can be tested for bioactivity. In such a situation, the design of small, focused compound libraries provides an alternative to the concept of large, maximally diverse screening collections. We present the technique of "adaptive" compound library design, which implements a simulated evolutionary process. Compound assembly and determination of bioactivity can be performed using computer-based methods (virtual screening), or in the laboratory. We show that there exists an optimal combination of the size of a screening library and the number of iterative screening rounds with the aim to keep experimental efforts at a minimum.

We have comprehensively cloned genes associated with the synthesis of glycans in the human body, then translated those glycogenes into recombinant glycosyltransferases using a variety of expression systems. The library of glycans or glycopeptides having various structures can be synthesized in a test tube using various enzymes. Using the glycan library, we have recently constructed a multistage tandem mass (MS( n )) spectral library containing observed spectra. This library may be utilized as a novel tool for glycomics research, as it enables users to identify oligosaccharides very easily and quickly by spectral matching.

During the last decade, Virtual Screening (VS) has definitively established itself as an important part of the drug discovery and development process. VS involves the selection of likely drug candidates from large libraries of chemical structures by using computational methodologies, but the generic definition of VS encompasses many different methodologies. This chapter provides an introduction to the field by reviewing a variety of important aspects, including the different types of virtual screening methods, and the several steps required for a successful virtual screening campaign within a state-of-the-art approach, from target selection to postfilter application. This analysis is further complemented with a small collection important VS success stories.

The hepatitis C virus (HCV) has infected some 170 million people worldwide, and is expected to pose a significant medical problem for the foreseeable future. No vaccine is presently available, and the current antiviral therapies (pegylated interferon-alpha and ribavirin) are characterized by limited efficacy, high costs, and substantial side effects. Initiation of infection requires attachment of the HCV virus to the cell surface followed by viral entry and represents a critical determinant of tissue tropism and pathogenesis. Small molecules that inhibit the virus at the stage of viral entry, for example, by blocking the interactions between viral envelope glycoprotein and cellular receptor or coreceptor or by inhibiting the viral fusion process, would serve as attractive antiviral drugs. Recent development of HCV pseudoparticles (HCVpp), displaying unmodified and functional HCV glycoprotein on the surface of retroviral core particles, has greatly facilitated studies of HCV entry and provides an essential tool for the identification and characterization of molecules that block HCV entry. We have adapted the HCVpp infection assay with HCVpp harboring a luciferase reporter to a 96-well format and screened a small-molecule compound library to identify inhibitors of HCV entry. Such active viral entry inhibitors have the potential to be first-in-class antiviral drugs that can be incorporated into combinations of multiple drugs with different targets for the treatment of chronic HCV infection.

Peptide aptamers have primarily been used as research tools to manipulate protein function and study regulatory networks. However, they also find multiple applications in therapeutic research, from target identification and validation to drug discovery. Because of their unbiased combinatorial nature, peptide aptamers interrogate the biological significance of numerous molecular surfaces on target proteins. Their use enables the identification and validation of some of these surfaces as interesting therapeutic targets to pursue. Peptide aptamers can subsequently be used to guide the discovery of small molecule drugs specific for these molecular surfaces.Here, we present a high-throughput screening assay that identifies small molecules that displace interactions between proteins and their cognate peptide aptamers. AptaScreen is a duplex yeast two-hybrid assay featuring two luciferase reporter genes. It can be performed in 96- or 384-well plates and can be fully automated.