NMR techniques for characterization of ligand binding: utility for lead generation and optimization in drug discovery.

Over the last ten years, nmr spectroscopy has evolved into an important discipline in drug discovery. Initially, nmr was most useful as a technique to provide structural information regarding protein drug targets and target-ligand interactions. More recently, it has been shown that nmr may be used as an alternative method for identification of small molecule ligands that bind to protein drug targets. High throughput implementation of these experiments to screen small molecule libraries may lead to identification of potent and novel lead compounds. In this review, we will use examples from our own research to illustrate how nmr experiments to characterize ligand binding may be used to both screen for novel compounds during the process of lead generation, as well as provide structural information useful for lead optimization during the latter stages of a discovery program.     

Solid-phase assays for small molecule screening using sol-gel entrapped proteins.

With compound libraries exceeding one million compounds, the ability to quickly and effectively screen these compounds against relevant pharmaceutical targets has become crucial. Solid-phase assays present several advantages over solution-based methods. For example, a higher degree of miniaturization can be achieved, functional- and affinity-based studies are possible, and a variety of detection methods can be used. Unfortunately, most protein immobilization methods are either too harsh or require recombinant proteins and thus are not amenable to delicate proteins such as kinases and membrane-bound receptors. Sol-gel encapsulation of proteins in an inorganic silica matrix has emerged as a novel solid-phase assay platform. In this minireview, we discuss the development of sol-gel derived protein microarrays and sol-gel based monolithic bioaffinity columns for the high-throughput screening of small molecule libraries and mixtures.     

Biosensor analysis of drug-target interactions: direct and competitive binding assays for investigation of interactions between thrombin and thrombin inhibitors

The sensitivity of BIACORE technology is sufficient for detection and characterization of binding events involving low-molecular-weight compounds and their immobilized protein targets. The technology requires no labeling and provides information on the stability of the compound/target complex with a single injection of the compound. This is useful for qualifying hits obtained in a primary screen and in lead optimization. Although immobilized targets can be reused, the surface may slowly deteriorate, solvent effects can distort binding levels during injection of compounds, and some compounds may exhibit broad protein selectivity rather than target specificity. A reliable direct binding assay for compounds binding to immobilized thrombin using a combination of two reference surfaces, a dextran surface for subtraction and calibration of solvent effects and a protein surface for identification of compounds that tend to bind proteins, has been developed. Eleven compounds with known binding specificity to thrombin and 159 additional compounds were investigated. All compounds with known binding specificity were identified at 1 and 10 microM concentration. One additional compound was scored as positive. The direct binding assay compared favorably with two competitive assay formats, a surface competitive assay and a inhibitor in solution assay, that were examined in parallel.     

Protein affinity map of chemical space

Affinity fingerprinting is a quantitative method for mapping chemical space based on binding preferences of compounds for a reference panel of proteins. An effective reference panel of <20 proteins can be empirically selected which shows differential interaction with nearly all compounds. By using this map to iteratively sample the chemical space, identification of active ligands from a library of 30 000 candidate compounds has been accomplished for a wide spectrum of specific protein targets. In each case, <200 compounds were directly assayed against the target. Further, analysis of the fingerprint database suggests a strategy for effective selection of affinity chromatography ligands and scaffolds for combinatorial chemistry. With such a system, the large numbers of potential therapeutic targets emerging from genome research can be categorized according to ligand binding properties, complementing sequence based classification.     

Blind docking of drug-sized compounds to proteins with up to a thousand residues

Blind docking was introduced for the detection of possible binding sites and modes of peptide ligands by scanning the entire surface of protein targets. In the present study, the method is tested on a group of drug-sized compounds and proteins with up to a thousand amino acid residues. Both proteins from complex structures and ligand-free proteins were used as targets. Robustness, limitations and future perspectives of the method are discussed. It is concluded that blind docking can be used for unbiased mapping of the binding patterns of drug candidates.     

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.     

Chemical genetics strategies for identification of molecular targets

Chemical genetics is an emerging field that can be used to study the interactions of chemical compounds, including natural products, with proteins. Usually, the identification of molecular targets is the starting point for studying a drug’s mechanism of action and this has been a crucial step in understanding many biological processes. While a great variety of target identification methods have been developed over the last several years, there are still many bioactive compounds whose target proteins have not yet been revealed because no routine protocols can be adopted. This review contains information concerning the most relevant principles of chemical genetics with special emphasis on the different genomic and proteomic approaches used in forward chemical genetics to identify the molecular targets of the bioactive compounds, the advantages and disadvantages of each and a detailed list of successful examples of molecular targets identified with these approaches.     

Target identification of bioactive compounds

To fully understand the regulation of cellular events, functional analysis of each protein involved in the regulatory systems is required. Among a variety of methods to uncover protein function, chemical genetics is a remarkable approach in which small molecular compounds are used as probes to elucidate protein functions within signaling pathways. However, identifying the target of small molecular bioactive compounds isolated by cell-based assays represents a crucial hurdle that must be overcome before chemical genetic studies can commence. A variety of methods and technologies for identifying target proteins have been reported. This review therefore aims to describe approaches for identifying these molecular targets.     

Molecular glues to stabilise protein–protein interactions

Targeting protein–protein interactions (PPIs) has become a common approach to tackle various diseases whose pathobiology is driven by their mis-regulation in important signalling pathways. Modulating PPIs has tremendous untapped therapeutic potential and different approaches can be used to modulate PPIs. Initially, therapeutic effects were mostly sought by inhibiting PPIs. However, by gaining insight in the mode of action of certain therapeutic compounds, it became clear that stabilising (i.e. enhancing) PPIs can also be useful. The latter strategy is recently gaining a lot of attention, as stabilising physiologic, or even inducing novel interactions of a target protein with E3 ubiquitin ligases forms the basis of the targeted protein degradation (TPD) approach. An emerging additional example for drug discovery based on PPI stabilisation are the 14-3-3 proteins, a family of regulatory proteins, which engages in many protein–protein interactions, some of which might become therapeutical targets.     

An integrated platform of genomic assays reveals small-molecule bioactivities

Bioactive compounds are widely used to modulate protein function and can serve as important leads for drug development. Identifying the in vivo targets of these compounds remains a challenge. Using yeast, we integrated three genome-wide gene-dosage assays to measure the effect of small molecules in vivo. A single TAG microarray was used to resolve the fitness of strains derived from pools of (i) homozygous deletion mutants, (ii) heterozygous deletion mutants and (iii) genomic library transformants. We demonstrated, with eight diverse reference compounds, that integration of these three chemogenomic profiles improves the sensitivity and specificity of small-molecule target identification. We further dissected the mechanism of action of two protein phosphatase inhibitors and in the process developed a framework for the rational design of multidrug combinations to sensitize cells with specific genotypes more effectively. Finally, we applied this platform to 188 novel synthetic chemical compounds and identified both potential targets and structure-activity relationships.     

From in silico target prediction to multi-target drug design: current databases, methods and applications

Given the tremendous growth of bioactivity databases, the use of computational tools to predict protein targets of small molecules has been gaining importance in recent years. Applications span a wide range, from the 'designed polypharmacology' of compounds to mode-of-action analysis. In this review, we firstly survey databases that can be used for ligand-based target prediction and which have grown tremendously in size in the past. We furthermore outline methods for target prediction that exist, both based on the knowledge of bioactivities from the ligand side and methods that can be applied in situations when a protein structure is known. Applications of successful in silico target identification attempts are discussed in detail, which were based partly or in whole on computational target predictions in the first instance. This includes the authors' own experience using target prediction tools, in this case considering phenotypic antibacterial screens and the analysis of high-throughput screening data. Finally, we will conclude with the prospective application of databases to not only predict, retrospectively, the protein targets of a small molecule, but also how to design ligands with desired polypharmacology in a prospective manner.     

High-throughput kinase assays with protein substrates using fluorescent polymer superquenching

Background  

High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform.     

Classification of proteins based on the properties of the ligand-binding site: the case of adenine-binding proteins

Comparative analysis of protein binding sites for similar ligands yields information about conserved interactions, relevant for ligand affinity, and variable interactions, which are important for specificity. The pattern of variability can indicate new targets for a pharmacologically validated class of compounds binding to a similar site. A particularly vast group of therapeutically interesting proteins using the same or similar substrates are those that bind adenine-containing ligands. Drug development is focusing on compounds occupying the adenine-binding site and their specificity is an issue of paramount importance. We use a simple scheme to characterize and classify the adenine-binding sites in terms of their intermolecular interactions, and show that this classification does not necessarily correspond to protein classifications based on either sequence or structural similarity. We find that only a limited number of the different hydrogen bond patterns possible for adenine-binding is used, which can be utilized as an effective classification scheme. Closely related protein families usually share similar hydrogen patterns, whereas non-polar interactions are less well conserved. Our classification scheme can be used to select groups of proteins with a similar ligand-binding site, thus facilitating the definition of the properties that can be exploited to design specific inhibitors.     

AlphaFold2 protein structure prediction: Implications for drug discovery

The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificial intelligence methods compile the three-dimensional structure of proteins has made protein targets more accessible to the drug design process. Here, we present our perspective of the significance of accurate protein structure prediction on various stages of the small molecule drug discovery life cycle focusing on current capabilities and assessing how further evolution of such predictive procedures can have a more decisive impact in the discovery of new medicines.     

A strategy for high-throughput assay development using leads derived from nuclear magnetic resonance-based screening

A strategy is described for the development of high-throughput screening assays against targets of unknown function that involves the use of nuclear magnetic resonance (NMR) spectroscopy. Using this approach, molecules that bind to the protein target are identified from an NMR-based screen of a library of substrates, cofactors, and other compounds that are known to bind to many proteins and enzymes. Once a ligand has been discovered, a fluorescent or radiolabeled analog of the ligand is synthesized that can be used in a high-throughput screen. The approach is illustrated in the development of a high-throughput screening assay against HI-0033, a conserved protein from Haemophilus influenzae whose function is currently unknown. Adenosine was found to bind to HI-0033 by NMR, and fluorescent analogs were rapidly identified that bound to HI-0033 in the submicromolar range. Using these fluorescent compounds, a fluorescence polarization assay was developed that is suitable for high-throughput screening and obtaining detailed structure-activity relationships for lead optimization.     

A fluorescence-based high-throughput assay for antimicrotubule drugs

With the advent of combinatorial chemistry and the extensive libraries of potential drugs produced from it, there is a growing need for rapid sensitive, high-throughput screening for drug potency. Microtubules are important targets for anticancer agents, and new antimicrotubule compounds are of continued interest in drug development. The in vitro potency of antimicrotubule drugs may be evaluated by measuring the extent of tubulin assembly. The extent of polymerization is proportional to the turbidity of the solution, which usually has been measured as apparent absorption. The turbidity method has inherent problems that hinder its adaptation to a high-throughput format, such as a requirement for high protein concentrations and a high coefficient of variation. We present here a high-throughput assay for antimicrotubule activity in which fluorescence is used to monitor microtubule assembly. Both assembly-inhibiting and assembly-promoting compounds can be evaluated. The assay is rapid and easy to perform, and the data are reliable, with good accuracy and reproducibility.     

Revealing Potential Bioactive Compounds and Mechanisms of Lithospermum erythrorhizon against COVID-19 via Network Pharmacology Study

Lithospermum erythrorhizon (LE) is known in Korean traditional medicine for its potent therapeutic effect and antiviral activity. Currently, coronavirus (COVID-19) disease is a developing global pandemic that can cause pneumonia. A precise study of the infection and molecular pathway of COVID-19 is therefore obviously important. The compounds of LE were identified from the Natural Product Activity and Species Source (NPASS) database and screened by SwissADME. The targets interacted with the compounds and were selected using the Similarity Ensemble Approach (SEA) and Swiss Target Prediction (STP) methods. PubChem was used to classify targets linked to COVID-19. The protein–protein interaction (PPI) networks and signaling pathways–targets–bioactive compounds (STB) networks were constructed by RPackage. Lastly, we performed the molecular docking test (MDT) to verify the binding affinity between significant complexes through AutoDock 1.5.6. The Natural Product Activity and Species Source (NPASS) revealed a total of 82 compounds from LE, which interacted with 1262 targets (SEA and STP), and 249 overlapping targets were identified. The 19 final overlapping targets from the 249 targets and 356 COVID-19 targets were ultimately selected. A bubble chart exhibited that inhibition of the MAPK signaling pathway could be a key mechanism of LE on COVID-19. The three key targets (RELA, TNF, and VEGFA) directly related to the MAPK signaling pathway, and methyl 4-prenyloxycinnamate, tormentic acid, and eugenol were related to each target and had the most stable binding affinity. The three bioactive effects on the three key targets might be synergistic effects to alleviate symptoms of COVID-19 infection. Overall, this study shows that LE can play a role in alleviating COVID-19 symptoms, revealing that the three components (bioactive compounds, targets, and mechanism) are the most significant elements of LE against COVID-19. However, the promising mechanism of LE on COVID-19 is only predicted on the basis of mining data; the efficacy of the chemical compounds and the affinity between compounds and the targets in experiment was ignored, which should be further substantiated through clinical trials.     

Experimental validation of a fragment library for lead discovery using SPR biosensor technology

A new fragment library for lead discovery has been designed and experimentally validated for use in surface plasmon resonance (SPR) biosensor-based screening. The 930 compounds in the library were selected from 4.6 million commercially available compounds using a series of physicochemical and medicinal chemistry filters. They were screened against 3 prototypical drug targets: HIV-1 protease, thrombin and carbonic anhydrase, and a nontarget: human serum albumin. Compound solubility was not a problem under the conditions used for screening. The high sensitivity of the sensor surfaces allowed the detection of interactions for 35% to 97% of the fragments, depending on the target protein. None of the fragments was promiscuous (i.e., interacted with a stoichiometry ≥5:1 with all 4 proteins), and only 2 compounds dissociated slowly from all 4 proteins. The use of several targets proved valuable since several compounds would have been disqualified from the library on the grounds of promiscuity if fewer target proteins had been used. The experimental procedure allowed an efficient evaluation and exploration of the new fragment library and confirmed that the new library is suitable for SPR biosensor-based screening.     

Case studies of minimizing nonspecific inhibitors in HTS campaigns that use assay-ready plates

Identifying chemical lead matter by high-throughput screening (HTS) has been a common practice in early stage drug discovery. Evolution of small-molecule library composition to include more drug-like molecules with desirable physical chemical properties combined with improving assay technologies has vastly enhanced the capability of HTS. However, HTS campaigns can still be plagued by false positives arising from nonspecific inhibitors. The generation of assay-ready plates has permitted an incremental advancement to the speed and efficiency of HTS but has the potential to enhance the occurrence of nonspecific inhibitors. A subtle change in the order of reagent addition to the assay-ready plates can greatly alleviate false-positive inhibition. Our case studies with six different kinase and protease targets reveal that this type of inhibition affects targets regardless of enzyme class and is unpredictable based on protein construct or inhibitor chemical scaffold. These case studies support a model where a diversity set of compounds should be tested first for hit rates as a function of order of addition, carrier protein, and relevant mechanistic studies prior to launch of the HTS campaign.     

橘小实蝇化学通讯机制与引诱剂开发策略

实蝇是全球重大的果蔬虫害,对世界年均造成的经济损失高达20亿美元。橘小实蝇Bactrocera dorsalis是该类害虫的代表之一,每年对我国柑橘产业造成严重损失。以雄性引诱剂和蛋白饵剂为核心的诱杀技术已用于害虫监测和绿色防控,但是田间防控效果有待进一步提高。随着高通量测序技术成本的降低以及现代分子生物学技术的发展,科学家们提出先解析害虫化学感受的分子机制,鉴定关键的化学感受分子靶标,并以鉴定的新靶标设计和筛选更为稳定和高效引诱剂和食诱剂。为促进以关键化学感受分子为靶标的橘小实蝇行为调控技术的发展,本文综述了调控橘小实蝇行为的重要化学物质及其化学感受识别机制的研究现状。调控橘小实蝇行为的重要挥发物主要包括性信息素、植物挥发物和食物源蛋白气味。前两者中鉴定获得的特异性化合物质与橘小实蝇成虫的行为关系较为明确,例如性信息素中得到吡嗪类物质能够引诱雌虫,植物挥发物中的甲基丁香酚引诱雄虫,γ-辛内酯能够诱发雌虫产卵等;而后者食物源蛋白气味则由于成分复杂,在田间虽有一定效果,但缺乏特定化合物在雌雄虫具体行为中的功能验证。嗅觉感受机制中,外周神经感器与中枢触角叶仅有形态描述,不同类型嗅觉神经元的...