A ligand-observed mass spectrometry approach integrated into the fragment based lead discovery pipeline

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 "WY" conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 μM binding affinity for CtUGGTGT24in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 μM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors.

Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes

The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.

A Liquid Chromatography-Mass Spectrometry Method to Study the Interaction between Membrane Proteins and Low-Molecular-Weight Compound Mixtures

Molecular interaction analysis is an essential technique for the study of biomolecular functions and the development of new drugs. Most current methods generally require manipulation to immobilize or label molecules, and require advance identification of at least one of the two molecules in the reaction. In this study, we succeeded in detecting the interaction of low-molecular-weight (LMW) compounds with a membrane protein mixture derived from cultured cells expressing target membrane proteins by using the size exclusion chromatography-mass spectrometry (SEC-MS) method under the condition of 0.001% lauryl maltose neopentyl glycol as detergent and atmospheric pressure chemical ionization. This method allowed us to analyze the interaction of a mixture of medicinal herbal ingredients with a mixture of membrane proteins to identify the two interacting ingredients. As it does not require specialized equipment (e.g., a two-dimensional liquid chromatography system), this SEC-MS method enables the analysis of interactions between LMW compounds and relatively high-expressed membrane proteins without immobilization or derivatization of the molecules.

Molecular docking and dynamics studies of Nicotinamide Riboside as a potential multi-target nutraceutical against SARS-CoV-2 entry, replication, and transcription: A new insight

The highly contagious Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is a newborn infectious member of the dangerous beta-coronaviruses (β-CoVs) following SARS and MERS‐CoVs, can be regarded as the most significant issue afflicting the whole world shortly after December 2019. Considering CoVs as RNA viruses with a single-stranded RNA genome (+ssRNA), the critical viral enzyme RNA dependent RNA polymerase (RdRp) is a promising therapeutic target for the potentially fatal infection COVID-19. Nicotinamide riboside (NR), which is a naturally occurring analogue of Niacin (vitamin B3), is expected to have therapeutic effects on COVID-19 due to its super close structural similarity to the proven RdRp inhibitors. Thus, at the first phase of the current molecular docking and dynamics simulation studies, we targeted SARS-CoV-2 RdRp. On the next phase, SARS-CoV RdRp, human Angiotensin-converting enzyme 2, Inosine-5’-monophosphate dehydrogenase, and the SARS-CoV-2 Structural Glycoproteins Spike, Nonstructural viral protein 3-Chymotrypsin-like protease, and Papain-like protease were targeted using the docking simulation to find other possible antiviral effects of NR serendipitously. In the current study, the resulted scores from molecular docking and dynamics simulations as the primary determinative factor as well as the observed reliable binding modes have demonstrated that Nicotinamide Riboside and its active metabolite NMN can target human ACE2 and IMPDH, along with the viral S^pro, M^pro, PL^pro, and on top of all, RdRp as a potential competitive inhibitor.

Crystal polymorphism in fragment-based lead discovery of ligands of the catalytic domain of UGGT, the glycoprotein folding quality control checkpoint

None of the current data processing pipelines for X-ray crystallography fragment-based lead discovery (FBLD) consults all the information available when deciding on the lattice and symmetry (i.e., the polymorph) of each soaked crystal. Often, X-ray crystallography FBLD pipelines either choose the polymorph based on cell volume and point-group symmetry of the X-ray diffraction data or leave polymorph attribution to manual intervention on the part of the user. Thus, when the FBLD crystals belong to more than one crystal polymorph, the discovery pipeline can be plagued by space group ambiguity, especially if the polymorphs at hand are variations of the same lattice and, therefore, difficult to tell apart from their morphology and/or their apparent crystal lattices and point groups. In the course of a fragment-based lead discovery effort aimed at finding ligands of the catalytic domain of UDP-glucose glycoprotein glucosyltransferase (UGGT), we encountered a mixture of trigonal crystals and pseudotrigonal triclinic crystals-with the two lattices closely related. In order to resolve that polymorphism ambiguity, we have written and described here a series of Unix shell scripts called CoALLA (crystal polymorph and ligand likelihood-based assignment). The CoALLA scripts are written in Unix shell and use autoPROC for data processing, CCP4-Dimple/REFMAC5 and BUSTER for refinement, and RHOFIT for ligand docking. The choice of the polymorph is effected by carrying out (in each of the known polymorphs) the tasks of diffraction data indexing, integration, scaling, and structural refinement. The most likely polymorph is then chosen as the one with the best structure refinement R_free statistic. The CoALLA scripts further implement a likelihood-based ligand assignment strategy, starting with macromolecular refinement and automated water addition, followed by removal of the water molecules that appear to be fitting ligand density, and a final round of refinement after random perturbation of the refined macromolecular model, in order to obtain unbiased difference density maps for automated ligand placement. We illustrate the use of CoALLA to discriminate between H3 and P1 crystals used for an FBLD effort to find fragments binding to the catalytic domain of Chaetomium thermophilum UGGT.

A native mass spectrometry platform identifies HOP inhibitors that modulate the HSP90-HOP protein-protein interaction

Herein we describe a native mass spectromery protein-peptide model as a competent surrogate for the HOP-HSP90 protein-protein interaction (PPI), application of which led to the qualititive identification of two new peptides capable of in vitro PPI disruption. This proof of concept study offers a viable alternative for PPI inhibitor screening.

Prediction and collection of protein-metabolite interactions

Interactions between proteins and small molecule metabolites play vital roles in regulating protein functions and controlling various cellular processes. The activities of metabolic enzymes, transcription factors, transporters and membrane receptors can all be mediated through protein-metabolite interactions (PMIs). Compared with the rich knowledge of protein-protein interactions, little is known about PMIs. To the best of our knowledge, no existing database has been developed for collecting PMIs. The recent rapid development of large-scale mass spectrometry analysis of biomolecules has led to the discovery of large amounts of PMIs. Therefore, we developed the PMI-DB to provide a comprehensive and accurate resource of PMIs. A total of 49 785 entries were manually collected in the PMI-DB, corresponding to 23 small molecule metabolites, 9631 proteins and 4 species. Unlike other databases that only provide positive samples, the PMI-DB provides non-interaction between proteins and metabolites, which not only reduces the experimental cost for biological experimenters but also facilitates the construction of more accurate algorithms for researchers using machine learning. To show the convenience of the PMI-DB, we developed a deep learning-based method to predict PMIs in the PMI-DB and compared it with several methods. The experimental results show that the area under the curve and area under the precision-recall curve of our method are 0.88 and 0.95, respectively. Overall, the PMI-DB provides a user-friendly interface for browsing the biological functions of metabolites/proteins of interest, and experimental techniques for identifying PMIs in different species, which provides important support for furthering the understanding of cellular processes. The PMI-DB is freely accessible at http://easybioai.com/PMIDB.

G protein-coupled receptors: structure- and function-based drug discovery

As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.

Releasing the technical 'shackles' on GPCR drug discovery: opportunities enabled by detergent-free polymer lipid particle (PoLiPa) purification

G-protein-coupled receptor (GPCR) drug research is presently hindered by the technical challenges associated with generating purified receptors. Consequently, the application of critical modern discovery technologies has been limited, and the vast untapped opportunity for new GPCR-directed medicines is not being realised. A simple but transformative solution is to purify receptors without removing them from their native phospholipid environment by using polymer lipid particle (PoLiPa) technology, with reagents such as styrene-maleic acid co-polymer (SMA). Compared with contemporary detergent-based and stabilising mutagenesis methods, the PoLiPa approach is simple and generic and, therefore, offers huge advantages, with the potential to revolutionise GPCR research by facilitating the availability of the purified receptors that are required for structural biology, biophysical, and panning technologies.

Emerging strategies for the identification of protein-metabolite interactions

Interactions between biological molecules enable life. The significance of a cell-wide understanding of molecular complexes is thus obvious. In comparison to protein-protein interactions, protein-metabolite interactions remain under-studied. However, this has been gradually changing due to technological progress. Here, we focus on the interactions between ligands and receptors, the triggers of signalling events. While the number of small molecules with proven or proposed signalling roles is rapidly growing, most of their protein receptors remain unknown. Conversely, there are numerous signalling proteins with predicted ligand-binding domains for which the identities of the metabolite counterparts remain elusive. Here, we discuss the current biochemical strategies for identifying protein-metabolite interactions and how they can be used to characterize known metabolite regulators and identify novel ones.

Accelerating the Throughput of Affinity Mass Spectrometry-Based Ligand Screening toward a G Protein-Coupled Receptor

Affinity mass spectrometry (MS) enables rapid screening of compound mixtures for ligands bound to a specific protein target, yet its current throughput is limited to individually assay pools of 400-2000 compounds. Typical affinity MS screens implemented in pharmaceutical industry laboratories identify putative ligands based on qualitative analysis of compound binding to the target whereas no quantitative information is acquired to discriminate high- and low-affinity ligands in the screening phase. Furthermore, these screens require purification of a stabilized form of the protein target, which poses a great challenge for membrane receptor targets. Here, we describe a new, potentially general affinity MS strategy that allows screening of 20,000 compounds in one pool for highly efficient ligand discovery toward a G protein-coupled receptor (GPCR) target. Quantitative measurement of compound binding to the receptor enables high-affinity ligand selection using both the purified receptor and receptor-embedded cell membranes. This high-throughput, label-free and quantitative affinity MS screen resulted in discovery of three new antagonists of the A2A adenosine receptor.

Efficient ligand discovery from natural herbs by integrating virtual screening, affinity mass spectrometry and targeted metabolomics

Although natural herbs have been a rich source of compounds for drug discovery, identification of bioactive components from natural herbs suffers from low efficiency and prohibitive cost of the conventional bioassay-based screening platforms. Here we develop a new strategy that integrates virtual screening, affinity mass spectrometry (MS) and targeted metabolomics for efficient discovery of herb-derived ligands towards a specific protein target site. Herb-based virtual screening conveniently selects herbs of potential bioactivity whereas affinity MS combined with targeted metabolomics readily screens candidate compounds in a high-throughput manner. This new integrated approach was benchmarked on screening chemical ligands that target the hydrophobic pocket of the nucleoprotein (NP) of Ebola viruses for which no small molecule ligands have been reported. Seven compounds identified by this approach from the crude extracts of three natural herbs were all validated to bind to the NP target in pure ligand binding assays. Among them, three compounds isolated from Piper nigrum (HJ-1, HJ-4 and HJ-6) strongly promoted the formation of large NP oligomers and reduced the protein thermal stability. In addition, cooperative binding between these chemical ligands and an endogenous peptide ligand was observed, and molecular docking was employed to propose a possible mechanism. Taken together, we established a platform integrating in silico and experimental screening approaches for efficient discovery of herb-derived bioactive ligands especially towards non-enzyme protein targets.

Aryl bis-sulfonamides bind to the active site of a homotrimeric isoprenoid biosynthesis enzyme IspF and extract the essential divalent metal cation cofactor

Characterizing the mode of action of non-covalent inhibitors in multisubunit enzymes often presents a great challenge. Most of the conventionally used methods are based on ensemble measurements of protein-ligand binding in bulk solution. They often fail to accurately describe multiple binding processes occurring in such systems. Native electrospray ionization mass spectrometry (ESI-MS) of intact protein complexes is a direct, label-free approach that can render the entire distribution of ligand-bound states in multimeric protein complexes. Here we apply native ESI-MS to comprehensively characterize the isoprenoid biosynthesis enzyme IspF from Arabidopsis thaliana, an example of a homomeric protein complex with multiple binding sites for several types of ligands, including a metal cofactor and a synthetic inhibitor. While standard biophysical techniques failed to reveal the mode of action of recently discovered aryl-sulfonamide-based inhibitors of AtIspF, direct native ESI-MS titrations of the protein with the ligands and ligand competition assays allowed us to accurately capture the solution-phase protein-ligand binding equilibria in full complexity and detail. Based on these combined with computational modeling, we propose a mechanism of AtIspF inhibition by aryl bis-sulfonamides that involves both the competition with the substrate for the ligand-binding pocket and the extraction of Zn2+ from the enzyme active site. This inhibition mode is therefore mixed competitive and non-competitive, the latter exerting a key inhibitory effect on the enzyme activity. The results of our study deliver a profound insight into the mechanisms of AtIspF action and inhibition, open new perspectives for designing inhibitors of this important drug target, and demonstrate the applicability and value of the native ESI-MS approach for deep analysis of complex biomolecular binding equilibria.

MS methods to study macromolecule-ligand interaction: Applications in drug discovery

The interaction of small compounds (i.e. ligands) with macromolecules or macromolecule assemblies (i.e. targets) is the mechanism of action of most of the drugs available today. Mass spectrometry is a popular technique for the interrogation of macromolecule-ligand interactions and therefore is also widely used in drug discovery and development. Thanks to its versatility, mass spectrometry is used for multiple purposes such as biomarker screening, identification of the mechanism of action, ligand structure optimization or toxicity assessment. The evolution and automation of the instruments now allows the development of high throughput methods with high sensitivity and a minimized false discovery rate. Herein, all these approaches are described with a focus on the methods for studying macromolecule-ligand interaction aimed at defining the structure-activity relationships of drug candidates, along with their mechanism of action, metabolism and toxicity.

Identification of natural products as novel ligands for the human 5-HT2C receptor

G protein-coupled receptors (GPCRs) constitute the largest human protein family with over 800 members, which are implicated in many important medical conditions. Serotonin receptors belong to the aminergic GPCR subfamily and play important roles in physiological and psychological activities. Structural biology studies have revealed the structures of many GPCRs in atomic details and provide the basis for the identification and investigation of the potential ligands, which interact with and modulate the receptors. Here, an integrative approach combining a focused target-specific natural compound library, a thermal-shift-based screening method, affinity mass spectrometry, molecular docking, and in vitro as well as in vivo functional assay, was applied to identify (–)-crebanine and several other aporphine alkaloids as initial hits for a human serotonin receptor subtype, the 5-HT_2C receptor. Further studies illuminated key features of their binding affinity, downstream signaling and tissue reaction, providing a molecular explanation for the interaction between (–)-crebanine and human 5-HT_2C receptor.

High-throughput identification of G protein-coupled receptor modulators through affinity mass spectrometry screening

High-throughput identification of GPCR modulators through affinity MS screening.

G protein-coupled receptors (GPCRs) represent the largest class of cell surface proteins and thus constitute an important family of therapeutic targets. Therefore, significant effort has been put towards the identification of novel ligands that can modulate the activity of a GPCR target with high efficacy and selectivity. However, due to limitations inherent to the most common techniques for GPCR ligand discovery, there is a pressing need for more efficient and effective ligand screening methods especially for the identification of potential allosteric modulators. Here we present a high-throughput, label-free and unbiased screening approach for the identification of small molecule ligands towards GPCR targets based on affinity mass spectrometry. This new approach features the usage of target-expressing cell membranes rather than purified proteins for ligand screening and allows the detection of both orthosteric and allosteric ligands targeting specific GPCRs. Screening a small compound library with this approach led to the rapid discovery of an antagonist for the 5-HT receptor and four positive allosteric modulators for GLP-1 receptor that were not previously reported.

Mass spectrometry for fragment screening

Fragment-based approaches in chemical biology and drug discovery have been widely adopted worldwide in both academia and industry. Fragment hits tend to interact weakly with their targets, necessitating the use of sensitive biophysical techniques to detect their binding. Common fragment screening techniques include differential scanning fluorimetry (DSF) and ligand-observed NMR. Validation and characterization of hits is usually performed using a combination of protein-observed NMR, isothermal titration calorimetry (ITC) and X-ray crystallography. In this context, MS is a relatively underutilized technique in fragment screening for drug discovery. MS-based techniques have the advantage of high sensitivity, low sample consumption and being label-free. This review highlights recent examples of the emerging use of MS-based techniques in fragment screening.

Current perspectives in fragment-based lead discovery (FBLD)

It is over 20 years since the first fragment-based discovery projects were disclosed. The methods are now mature for most ‘conventional’ targets in drug discovery such as enzymes (kinases and proteases) but there has also been growing success on more challenging targets, such as disruption of protein–protein interactions. The main application is to identify tractable chemical startpoints that non-covalently modulate the activity of a biological molecule. In this essay, we overview current practice in the methods and discuss how they have had an impact in lead discovery – generating a large number of fragment-derived compounds that are in clinical trials and two medicines treating patients. In addition, we discuss some of the more recent applications of the methods in chemical biology – providing chemical tools to investigate biological molecules, mechanisms and systems.

Critical Evaluation of Native Electrospray Ionization Mass Spectrometry for Fragment-Based Screening

Fragment-based screening presents a promising alternative to high-throughput screening and has gained great attention in recent years. So far, only a few studies have discussed mass spectrometry as a screening technology for fragments. Herein, we report the application of native electrospray ionization mass spectrometry (MS) for screening defined sets of fragments against four different target proteins. Fragments were selected from a primary screening conducted with a thermal shift assay (TSA) and represented different binding categories. Our data indicated that, beside specific complex formation, many fragments show extensive multiple binding and also charge-state shifts. Both of these factors complicate automated data analysis and decrease the attractiveness of native MS as a primary screening tool for fragments. A comparison of the hits identified by native MS and TSA showed good agreement for two of the proteins. Furthermore, we discuss general challenges, including the determination of an optimal fragment concentration and the question of how to rank fragment hits according to their affinity. In conclusion, we consider native MS to be a highly valuable tool for the validation and deeper investigation of promising fragment hits rather than a method for primary screening.

Novel Chemical Ligands to Ebola Virus and Marburg Virus Nucleoproteins Identified by Combining Affinity Mass Spectrometry and Metabolomics Approaches

The nucleoprotein (NP) of Ebola virus (EBOV) and Marburg virus (MARV) is an essential component of the viral ribonucleoprotein complex and significantly impacts replication and transcription of the viral RNA genome. Although NP is regarded as a promising antiviral druggable target, no chemical ligands have been reported to interact with EBOV NP or MARV NP. We identified two compounds from a traditional Chinese medicine Gancao (licorice root) that can bind both NPs by combining affinity mass spectrometry and metabolomics approaches. These two ligands, 18β-glycyrrhetinic acid and licochalcone A, were verified by defined compound mixture screens and further characterized with individual ligand binding assays. Accompanying biophysical analyses demonstrate that binding of 18β-glycyrrhetinic acid to EBOV NP significantly reduces protein thermal stability, induces formation of large NP oligomers, and disrupts the critical association of viral ssRNA with NP complexes whereas the compound showed no such activity on MARV NP. Our study has revealed the substantial potential of new analytical techniques in ligand discovery from natural herb resources. In addition, identification of a chemical ligand that influences the oligomeric state and RNA-binding function of EBOV NP sheds new light on antiviral drug development.

Native State Mass Spectrometry, Surface Plasmon Resonance, and X-ray Crystallography Correlate Strongly as a Fragment Screening Combination

Fragment-based drug discovery (FBDD) is contingent on the development of analytical methods to identify weak protein-fragment noncovalent interactions. Herein we have combined an underutilized fragment screening method, native state mass spectrometry, together with two proven and popular fragment screening methods, surface plasmon resonance and X-ray crystallography, in a fragment screening campaign against human carbonic anhydrase II (CA II). In an initial fragment screen against a 720-member fragment library (the "CSIRO Fragment Library") seven CA II binding fragments, including a selection of nonclassical CA II binding chemotypes, were identified. A further 70 compounds that comprised the initial hit chemotypes were subsequently sourced from the full CSIRO compound collection and screened. The fragment results were extremely well correlated across the three methods. Our findings demonstrate that there is a tremendous opportunity to apply native state mass spectrometry as a complementary fragment screening method to accelerate drug discovery.