Ligand-receptor interaction platforms and their applications for drug discovery

Computational approach for drug discovery against Gardnerella vaginalis in quest for safer and effective treatments for bacterial vaginosis

Bacterial vaginosis (BV), primarily attributed to Gardnerella vaginalis, poses significant challenges due to antibiotic resistance and suboptimal treatment outcomes. This study presents an integrated approach to identify potential drug targets and screen compounds against this bacterium by leveraging a computational methodology. Subtractive proteomics of the reference strain ASM286196v1/UMB0386 (assembly accession: GCA_002861965.1) facilitated the prioritization of proteins with essential bacterial functions and pathways as potential drug targets. We selected 3-deoxy-7-phosphoheptulonate synthase (aroG gene product; also known as DAHP synthase) for downstream analysis. Molecular docking was employed in PyRx (AutoDock Vina) to predict binding affinities between aroG inhibitors from the ZINC database and 3-deoxy-7-phosphoheptulonate synthase. Molecular dynamics simulations of 100 ns, using GROMACS, validated the stability of drug-target interactions. Additionally, ADMET profiling aided in the selection of compounds with favorable pharmacokinetic properties and safety profile for human hosts. PBPK profiling showed that ZINC98088375 had the highest bioavailability and efficient systemic circulation. Conversely, ZINC5113880 demonstrated the lowest absorption rate (39.661%). Moreover, cirrhosis, steatosis, and renal impairment appeared to influence blood concentration of the drug, impacting bioavailability. The integrative -omics approach utilized in this study underscores the potential of computer-aided drug design and offers a rational strategy for targeted inhibitor discovery against G. vaginalis. The strategy is an attempt to address the limitations of current BV treatments, including antibiotic resistance, and pave way for the development of safer and more effective therapeutics.

Protein aggregation and therapeutic strategies in SOD1- and TDP-43- linked ALS

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with severe socio-economic impact. A hallmark of ALS pathology is the presence of aberrant cytoplasmic inclusions composed of misfolded and aggregated proteins, including both wild-type and mutant forms. This review highlights the critical role of misfolded protein species in ALS pathogenesis, particularly focusing on Cu/Zn superoxide dismutase (SOD1) and TAR DNA-binding protein 43 (TDP-43), and emphasizes the urgent need for innovative therapeutic strategies targeting these misfolded proteins directly. Despite significant advancements in understanding ALS mechanisms, the disease remains incurable, with current treatments offering limited clinical benefits. Through a comprehensive analysis, the review focuses on the direct modulation of the misfolded proteins and presents recent discoveries in small molecules and peptides that inhibit SOD1 and TDP-43 aggregation, underscoring their potential as effective treatments to modify disease progression and improve clinical outcomes.

Cell-mediated nanoparticle delivery systems: towards precision nanomedicine

Cell-mediated nanoparticle delivery systems (CMNDDs) utilize cells as carriers to deliver the drug-loaded nanoparticles. Unlike the traditional nanoparticle drug delivery approaches, CMNDDs take the advantages of cell characteristics, such as the homing capabilities of stem cells, inflammatory chemotaxis of neutrophils, prolonged blood circulation of red blood cells, and internalization of macrophages. Subsequently, CMNDDs can easily prolong the blood circulation, cross biological barriers, such as the blood-brain barrier and the bone marrow-blood barrier, and rapidly arrive at the diseased areas. Such advantageous properties make CMNDDs promising delivery candidates for precision targeting. In this review, we summarize the recent advances in CMNDDs fabrication and biomedical applications. Specifically, ligand-receptor interactions, non-covalent interactions, covalent interactions, and internalization are commonly applied in constructing CMNDDs in vitro. By hitchhiking cells, such as macrophages, red blood cells, monocytes, neutrophils, and platelets, nanoparticles can be internalized or attached to cells to construct CMNDDs in vivo. Then we highlight the recent application of CMNDDs in treating different diseases, such as cancer, central nervous system disorders, lung diseases, and cardiovascular diseases, with a brief discussion about challenges and future perspectives in the end.

Dearomatization drives complexity generation in freshwater organic matter

Dissolved organic matter (DOM) is one of the most complex, dynamic and abundant sources of organic carbon, but its chemical reactivity remains uncertain1-3. Greater insights into DOM structural features could facilitate understanding its synthesis, turnover and processing in the global carbon cycle4,5. Here we use complementary multiplicity-edited 13C nuclear magnetic resonance (NMR) spectra to quantify key substructures assembling the carbon skeletons of DOM from four main Amazon rivers and two mid-size Swedish boreal lakes. We find that one type of reaction mechanism, oxidative dearomatization (ODA), widely used in organic synthetic chemistry to create natural product scaffolds6-10, is probably a key driver for generating structural diversity during processing of DOM that are rich in suitable polyphenolic precursor molecules. Our data suggest a high abundance of tetrahedral quaternary carbons bound to one oxygen and three carbon atoms (OCqC3 units). These units are rare in common biomolecules but could be readily produced by ODA of lignin-derived and tannin-derived polyphenols. Tautomerization of (poly)phenols by ODA creates non-planar cyclohexadienones, which are subject to immediate and parallel cycloadditions. This combination leads to a proliferation of structural diversity of DOM compounds from early stages of DOM processing, with an increase in oxygenated aliphatic structures. Overall, we propose that ODA is a key reaction mechanism for complexity acceleration in the processing of DOM molecules, creation of new oxygenated aliphatic molecules and that it could be prevalent in nature.

ThermoBRET: A Ligand-Engagement Nanoscale Thermostability Assay Applied to GPCRs

Measurements of membrane protein thermostability reflect ligand binding. Current thermostability assays often require protein purification or rely on pre-existing radiolabelled or fluorescent ligands, limiting their application to established targets. Alternative methods, such as fluorescence-detection size exclusion chromatography thermal shift, detect protein aggregation but are not amenable to high-throughput screening. Here, we present a ThermoBRET method to quantify the relative thermostability of G protein coupled receptors (GPCRs), using cannabinoid receptors (CB1 and CB2 ) and the β2 -adrenoceptor (β2 AR) as model systems. ThermoBRET reports receptor unfolding, does not need labelled ligands and can be used with non-purified proteins. It uses Bioluminescence Resonance Energy Transfer (BRET) between Nanoluciferase (Nluc) and a thiol-reactive fluorescent dye that binds cysteines exposed by unfolding. We demonstrate that the melting point (Tm ) of Nluc-fused GPCRs can be determined in non-purified detergent solubilised membrane preparations or solubilised whole cells, revealing differences in thermostability for different solubilising conditions and in the presence of stabilising ligands. We extended the range of the assay by developing the thermostable tsNLuc by incorporating mutations from the fragments of split-Nluc (Tm of 87 °C versus 59 °C). ThermoBRET allows the determination of GPCR thermostability, which is useful for protein purification optimisation and drug discovery screening.

Discovery of ICOS-Targeted Small Molecules Using Pharmacophore-Based Screening

There are currently no small molecules clinically approved as immune checkpoint modulators. Besides possessing oral bioavailability, cell-penetrating capabilities and enhanced tumor penetration compared to monoclonal antibodies (mAbs), small molecules are amenable to pharmacokinetic optimization, which allows adopting flexible dosage regimens that may avoid immune-related adverse events associated with mAbs. The interaction of inducible co-stimulator (ICOS) with its ligand (ICOS-L) plays key roles in T-cell differentiation and activation of T-cell to B-cell functions. This study represents the development and validation of a virtual screening strategy to identify small molecules that bind a novel druggable binding pocket in human ICOS. We used a lipophilic canyon in the apo-structure of ICOS and the ICOS/ICOS-L interface individually as templates for molecular dynamics simulation to generate 3D pharmacophores subsequently used for virtual screening campaigns. Our strategy was successful finding a first-in-class small molecule ICOS binder (5P, KD value=108.08±26.76 μM) and validating biophysical screening platforms for ICOS-targeted small molecules. We anticipate that future structural optimization of 5P will result in the discovery of high affinity chemical ligands for ICOS.

QMrebind: incorporating quantum mechanical force field reparameterization at the ligand binding site for improved drug-target kinetics through milestoning simulations

Understanding the interaction of ligands with biomolecules is an integral component of drug discovery and development. Challenges for computing thermodynamic and kinetic quantities for pharmaceutically relevant receptor-ligand complexes include the size and flexibility of the ligands, large-scale conformational rearrangements of the receptor, accurate force field parameters, simulation efficiency, and sufficient sampling associated with rare events. Our recently developed multiscale milestoning simulation approach, SEEKR2 (Simulation Enabled Estimation of Kinetic Rates v.2), has demonstrated success in predicting unbinding (koff) kinetics by employing molecular dynamics (MD) simulations in regions closer to the binding site. The MD region is further subdivided into smaller Voronoi tessellations to improve the simulation efficiency and parallelization. To date, all MD simulations are run using general molecular mechanics (MM) force fields. The accuracy of calculations can be further improved by incorporating quantum mechanical (QM) methods into generating system-specific force fields through reparameterizing ligand partial charges in the bound state. The force field reparameterization process modifies the potential energy landscape of the bimolecular complex, enabling a more accurate representation of the intermolecular interactions and polarization effects at the bound state. We present QMrebind (Quantum Mechanical force field reparameterization at the receptor-ligand binding site), an ORCA-based software that facilitates reparameterizing the potential energy function within the phase space representing the bound state in a receptor-ligand complex. With SEEKR2 koff estimates and experimentally determined kinetic rates, we compare and interpret the receptor-ligand unbinding kinetics obtained using the newly reparameterized force fields for model host-guest systems and HSP90-inhibitor complexes. This method provides an opportunity to achieve higher accuracy in predicting receptor-ligand koff rate constants.

Structure-affinity and structure-residence time relationships of macrocyclic Gαq protein inhibitors

The macrocyclic depsipeptides YM-254890 (YM) and FR900359 (FR) are potent inhibitors of Gα_q/11 proteins. They are important pharmacological tools and have potential as therapeutic drugs. The hydrogenated, tritium-labeled YM and FR derivatives display largely different residence times despite similar structures. In the present study we established a competition-association binding assay to determine the dissociation kinetics of unlabeled G_q protein inhibitors. Structure-affinity and structure-residence time relationships were analyzed. Small structural modifications had a large impact on residence time. YM and FR exhibited 4- to 10-fold higher residence times than their hydrogenated derivatives. While FR showed pseudo-irreversible binding, YM displayed much faster dissociation from its target. The isopropyl anchor present in FR and some derivatives was essential for slow dissociation. These data provide a basis for future drug design toward modulating residence times of macrocyclic G_q protein inhibitors, which has been recognized as a crucial determinant for therapeutic outcome.

Selectivity and Ranking of Tight-Binding JAK-STAT Inhibitors Using Markovian Milestoning with Voronoi Tessellations

Janus kinases (JAK), a group of proteins in the nonreceptor tyrosine kinase (NRTKs) family, play a crucial role in growth, survival, and angiogenesis. They are activated by cytokines through the Janus kinase-signal transducer and activator of a transcription (JAK-STAT) signaling pathway. JAK-STAT signaling pathways have significant roles in the regulation of cell division, apoptosis, and immunity. Identification of the V617F mutation in the Janus homology 2 (JH2) domain of JAK2 leading to myeloproliferative disorders has stimulated great interest in the drug discovery community to develop JAK2-specific inhibitors. However, such inhibitors should be selective toward JAK2 over other JAKs and display an extended residence time. Recently, novel JAK2/STAT5 axis inhibitors (N-(1H-pyrazol-3-yl)pyrimidin-2-amino derivatives) have displayed extended residence times (hours or longer) on target and adequate selectivity excluding JAK3. To facilitate a deeper understanding of the kinase-inhibitor interactions and advance the development of such inhibitors, we utilize a multiscale Markovian milestoning with Voronoi tessellations (MMVT) approach within the Simulation-Enabled Estimation of Kinetic Rates v.2 (SEEKR2) program to rank order these inhibitors based on their kinetic properties and further explain the selectivity of JAK2 inhibitors over JAK3. Our approach investigates the kinetic and thermodynamic properties of JAK-inhibitor complexes in a user-friendly, fast, efficient, and accurate manner compared to other brute force and hybrid-enhanced sampling approaches.

Finding alternatives to 5-fluorouracil: application of ensemble-based virtual screening for drug repositioning against human thymidylate synthase

5-fluorouracil and analogs are used in the treatment of many solid tumours. However, there are many cases of resistance and high toxicity associated with 5-fluorouracil chemotherapy. Repurposing FDA drugs against human thymidylate synthase revealed a number of FDA drugs that have a potential to be further developed for the treatment of various cancers for which 5-fluorouracil and analogs have been used for chemotherapy. Four FDA drugs prioritized for further validation included Erismodegib, Irinotecan, Conivaptan and Ergotamine. The role of water in mediating drug interactions and its contribution to the total binding energy was also shown. MM-PBSA calculations revealed that the binding affinity was the lowest for the hTS-Ergotamine complex (-66.702 ± 1.807 kJ/mol) suggesting moderate inhibition despite a large energetic contribution from van der Waal interactions (-190.889 ± 1.027 kJ/mol).Communicated by Ramaswamy H. Sarma.

Montelukast, cysteinyl leukotriene receptor 1 antagonist, inhibits cardiac fibrosis by activating APJ

Montelukast, cysteinyl leukotriene receptor 1 (CysLT1R) antagonist, is used clinically for patients with asthma, chronic obstructive pulmonary diseases (COPD), and allergic rhinitis. It has been reported that CysLT1R antagonists could reduce the risks of cardiovascular diseases in animal studies. Cardiac fibrosis is one of the major causes of heart failure. But little is known about the role of Montelukast in cardiac fibrosis and its underlying mechanism. In transverse aortic constriction (TAC) mice, Montelukast improved cardiac pumping function and inhibited cardiac fibrosis by down-regulation of the proteins related to the fibrosis, such as connective tissue growth factor (CTGF), Transforming Growth Factor β (TGF-β), and Alpha-smooth muscle actin (α-SMA). Montelukast reduced cell proliferation and collagen production in neonatal cardiac fibroblasts (CFs) with the pretreatment of 20% serum, while down-regulating the expression of TGF-β, CTGF and α-SMA. Molecules docking methods estimated a high affinity of Montelukast to Apelin receptor (APJ) and an effective chemical structure for Montelukast binding APJ. In Chinese hamster ovary (CHO) cells with stable overexpressing APJ, Montelukast inhibited forskolin (1 μM)-mediated cyclic adenosine monophosphate (cAMP) production and extracellular signal-regulated kinase1/2 (ERK1/2) phosphorylation, while these effects were reversed by pertussis toxin (PTX) pretreatment. APJ silence disrupted the effects of Montelukast in CFs pretreatment by serum 20%. So we concluded that Montelukast inhibited cardiac fibrosis due presumably to the coupling to the APJ-mediated Gi signaling pathway, which may be a promising therapeutic target for cardiac fibrosis.

Drug Discovery for Mycobacterium tuberculosis Using Structure-Based Computer-Aided Drug Design Approach

Developing new, more effective antibiotics against resistant Mycobacterium tuberculosis that inhibit its essential proteins is an appealing strategy for combating the global tuberculosis (TB) epidemic. Finding a compound that can target a particular cavity in a protein and interrupt its enzymatic activity is the crucial objective of drug design and discovery. Such a compound is then subjected to different tests, including clinical trials, to study its effectiveness against the pathogen in the host. In recent times, new techniques, which involve computational and analytical methods, enhanced the chances of drug development, as opposed to traditional drug design methods, which are laborious and time-consuming. The computational techniques in drug design have been improved with a new generation of software used to develop and optimize active compounds that can be used in future chemotherapeutic development to combat global tuberculosis resistance. This review provides an overview of the evolution of tuberculosis resistance, existing drug management, and the design of new anti-tuberculosis drugs developed based on the contributions of computational techniques. Also, we show an appraisal of available software and databases on computational drug design with an insight into the application of this software and databases in the development of anti-tubercular drugs. The review features a perspective involving machine learning, artificial intelligence, quantum computing, and CRISPR combination with available computational techniques as a prospective pathway to design new anti-tubercular drugs to combat resistant tuberculosis.

Data evaluation for surface-sensitive label-free methods to obtain real-time kinetic and structural information of thin films: A practical review with related software packages

Interfacial layers are important in a wide range of applications in biomedicine, biosensing, analytical chemistry and the maritime industries. Given the growing number of applications, analysis of such layers and understanding their behavior is becoming crucial. Label-free surface sensitive methods are excellent for monitoring the formation kinetics, structure and its evolution of thin layers, even at the nanoscale. In this paper, we review existing and commercially available label-free techniques and demonstrate how the experimentally obtained data can be utilized to extract kinetic and structural information during and after formation, and any subsequent adsorption/desorption processes. We outline techniques, some traditional and some novel, based on the principles of optical and mechanical transduction. Our special focus is the current possibilities of combining label-free methods, which is a powerful approach to extend the range of detected and deduced parameters. We summarize the most important theoretical considerations for obtaining reliable information from measurements taking place in liquid environments and, hence, with layers in a hydrated state. A thorough treamtmaent of the various kinetic and structural quantities obtained from evaluation of the raw label-free data are provided. Such quantities include layer thickness, refractive index, optical anisotropy (and molecular orientation derived therefrom), degree of hydration, viscoelasticity, as well as association and dissociation rate constants and occupied area of subsequently adsorbed species. To demonstrate the effect of variations in model conditions on the observed data, simulations of kinetic curves at various model settings are also included. Based on our own extensive experience with optical waveguide lightmode spectroscopy (OWLS) and the quartz crystal microbalance (QCM), we have developed dedicated software packages for data analysis, which are made available to the scientific community alongside this paper.

Near cut-off wavelength operation of resonant waveguide grating biosensors

Numerical simulations and analytical calculations are performed to support the design of grating-coupled planar optical waveguides for biological sensing. Near cut-off and far from cut-off modes are investigated, and their characteristics and suitability for sensing are compared. The numerical simulations reveal the high sensitivity of the guided mode intensity near the cut-off wavelength for any refractive index change along the waveguide. Consequently, it is sufficient to monitor the intensity change of the near cut-off sensing mode, which leads to a simpler sensor design compared to those setups where the resonant wavelength shift of the guided mode is monitored with high precision. The operating wavelength and the sensitivity of the proposed device can be tuned by varying the geometrical parameters of the corrugated waveguide. These results may lead to the development of highly sensitive integrated sensors, which have a simple design and therefore are cost-effective for a wide range of applications. These numerical findings are supported with experimental results, where the cut-off sensing mode was identified.

Lighting Up the Plasma Membrane: Development and Applications of Fluorescent Ligands for Transmembrane Proteins

Despite the fact that transmembrane proteins represent the main therapeutic targets for decades, complete and in-depth knowledge about their biochemical and pharmacological profiling is not fully available. In this regard, target-tailored small-molecule fluorescent ligands are a viable approach to fill in the missing pieces of the puzzle. Such tools, coupled with the ability of high-precision optical techniques to image with an unprecedented resolution at a single-molecule level, helped unraveling many of the conundrums related to plasma proteins' life-cycle and druggability. Herein, we review the recent progress made during the last two decades in fluorescent ligand design and potential applications in fluorescence microscopy of voltage-gated ion channels, ligand-gated ion channels and G-coupled protein receptors.

Systematic review on role of structure based drug design (SBDD) in the identification of anti-viral leads against SARS-Cov-2

The outbreak of existing public health distress is threatening the entire world with emergence and rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The novel coronavirus disease 2019 (COVID-19) is mild in most people. However, in some elderly people with co-morbid conditions, it may progress to pneumonia, acute respiratory distress syndrome (ARDS) and multi organ dysfunction leading to death. COVID-19 has caused global panic in the healthcare sector and has become one of the biggest threats to the global economy. Drug discovery researchers are expected to contribute rapidly than ever before. The complete genome sequence of coronavirus had been reported barely a month after the identification of first patient. Potential drug targets to combat and treat the coronavirus infection have also been explored. The iterative structure-based drug design (SBDD) approach could significantly contribute towards the discovery of new drug like molecules for the treatment of COVID-19. The existing antivirals and experiences gained from SARS and MERS outbreaks may pave way for identification of potential drug molecules using the approach. SBDD has gained momentum as the essential tool for faster and costeffective lead discovery of antivirals in the past. The discovery of FDA approved human immunodeficiency virus type 1 (HIV-1) inhibitors represent the foremost success of SBDD. This systematic review provides an overview of the novel coronavirus, its pathology of replication, role of structure based drug design, available drug targets and recent advances in in-silico drug discovery for the prevention of COVID-19. SARSCoV- 2 main protease, RNA dependent RNA polymerase (RdRp) and spike (S) protein are the potential targets, which are currently explored for the drug development.

Direct Keap1-kelch inhibitors as potential drug candidates for oxidative stress-orchestrated diseases: A review on In silico perspective

The recent outcry in the search for direct keap1 inhibitors requires a quicker and more effective drug discovery process which is an inherent property of the Computer Aided Drug Discovery (CADD) to bring drug candidates into the clinic for patient's use. This Keap1 (negative regulator of ARE master activator) is emerging as a therapeutic strategy to combat oxidative stress-orchestrated diseases. The advances in computer algorithm and compound databases require that we highlight the functionalities that this technology possesses that can be exploited to target Keap1-Nrf2 PPI. Therefore, in this review, we uncover the in silico approaches that had been exploited towards the identification of keap1 inhibition in the light of appropriate fitting with relevant amino acid residues, we found 3 and 16 other compounds that perfectly fit keap1 kelch pocket/domain. Our goal is to harness the parameters that could orchestrate keap1 surface druggability by utilizing hotspot regions for virtual fragment screening and identification of hotspot residues.

High-Throughput Screening Platforms in the Discovery of Novel Drugs for Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) are incurable and debilitating conditions that result in progressive degeneration and/or death of nerve cells in the central nervous system (CNS). Identification of viable therapeutic targets and new treatments for CNS disorders and in particular, for NDDs is a major challenge in the field of drug discovery. These difficulties can be attributed to the diversity of cells involved, extreme complexity of the neural circuits, the limited capacity for tissue regeneration, and our incomplete understanding of the underlying pathological processes. Drug discovery is a complex and multidisciplinary process. The screening attrition rate in current drug discovery protocols mean that only one viable drug may arise from millions of screened compounds resulting in the need to improve discovery technologies and protocols to address the multiple causes of attrition. This has identified the need to screen larger libraries where the use of efficient high-throughput screening (HTS) becomes key in the discovery process. HTS can investigate hundreds of thousands of compounds per day. However, if fewer compounds could be screened without compromising the probability of success, the cost and time would be largely reduced. To that end, recent advances in computer-aided design, in silico libraries, and molecular docking software combined with the upscaling of cell-based platforms have evolved to improve screening efficiency with higher predictability and clinical applicability. We review, here, the increasing role of HTS in contemporary drug discovery processes, in particular for NDDs, and evaluate the criteria underlying its successful application. We also discuss the requirement of HTS for novel NDD therapies and examine the major current challenges in validating new drug targets and developing new treatments for NDDs.

Equilibrium and Kinetic Measurements of Ligand Binding to HiBiT-tagged GPCRs on the Surface of Living Cells

G-protein coupled receptors (GPCRs) remain at the forefront of drug discovery efforts. Detailed assessment of features contributing to GPCR ligand engagement in a physiologically relevant environment is imperative to the development of new therapeutics with improved efficacy. Traditionally, binding properties such as affinity and kinetics were obtained using biochemical radioligand binding assays. More recently, the high specificity of resonance energy transfer has been leveraged toward the development of homogeneous cell-based proximity assays with capacity for real-time kinetic measurements. This suite of ligand binding protocols couples the specificity of bioluminescent resonance energy transfer (BRET) with the sensitivity afforded by the luminescent HiBiT peptide. The BRET format is used to quantify dynamic interactions between ligands and their cognate HiBiT-tagged GPCRs through competitive binding with fluorescent Tracers. At the same time, high affinity complementation of HiBiT with the cell impermeable LgBiT limits the bright bioluminescence donor signal to the cell surface and eliminates luminescence background from unoccupied receptors present in intracellular compartments.

Combination of MS Binding Assays and affinity selection mass spectrometry for screening of structurally homogenous libraries as exemplified for a focused oxime library addressing the neuronal GABA transporter 1

This study presents an efficient screening approach based on combination of mass spectrometry (MS) based binding assays (MS Binding Assays) and affinity selection mass spectrometry (ASMS) customized for screening of structurally homogeneous libraries sharing a common mass spectrometric fragmentation pattern. After reaction of a nipecotic acid derivative possessing a hydroxylamine functionality with aldehydes, the resulting oxime library was screened accordingly toward the GABA transporter subtype 1 (GAT1), a drug target for several neurological disorders. After assessing sublibraries' activities for inhibition of reporter ligand binding, hits in active ones were directly identified. This could be achieved by recording mass transitions for the reporter ligand as well as those predicted for the library components in a single LC-MS/MS run with a triple quadrupole mass spectrometer in the multiple reaction monitoring mode. Identification of hits with a predefined affinity could be reliably accomplished by calculation of IC₅₀-values from specific binding concentrations of library constituents and reporter ligand. Application of this strategy revealed six hits, from which two of them were resynthesized for further biological evaluation. Thereby, the best one displayed a pK_i of 7.38 in MS Binding Assays and a pIC₅₀ of 6.82 in [³H]GABA uptake assays for GAT1.

High-Throughput Screening: today's biochemical and cell-based approaches

High-throughput screening (HTS) provides starting chemical matter in the adventure of developing a new drug. In this review, we survey several HTS methods used today for hit identification, organized in two main flavors: biochemical and cell-based assays. Biochemical assays discussed include fluorescence polarization and anisotropy, FRET, TR-FRET, and fluorescence lifetime analysis. Binding-based methods are also surveyed, including NMR, SPR, mass spectrometry, and DSF. On the other hand, cell-based assays discussed include viability, reporter gene, second messenger, and high-throughput microscopy assays. We devote some emphasis to high-content screening, which is becoming very popular. An advisable stage after hit discovery using phenotypic screens is target deconvolution, and we provide an overview of current chemical proteomics, in silico, and chemical genetics tools. Emphasis is made on recent CRISPR/dCas-based screens. Lastly, we illustrate some of the considerations that inform the choice of HTS methods and point to some areas with potential interest for future research.

Detection of morphine in urine based on a surface plasmon resonance imaging immunoassay

Based on the surface plasmon resonance imaging (SPRi) technique, a new detection method for morphine in urine samples was developed. Sample labelling was not required, and qualitative and quantitative analysis could be completed in 20 minutes. According to an indirect competitive immunoassay, the mixture of morphine at different concentrations and morphine antibody at a certain concentration as the mobile phase was reacted with morphine BSA fixed on a chip surface in a competitive way. A calibration curve was obtained by correlating the signals generated from SPRi with the concentrations of morphine. By the addition of morphine to a blank urine sample, this method was confirmed to be feasible for the detection of morphine in actual urine. The limit of detection was as low as 9.59 ng mL-1. This method is fast and sensitive and can be applied in many fields.

Identification of peptidomimetic compounds as potential inhibitors against MurA enzyme of Mycobacterium tuberculosis

Increasing prevalence of resistance to anti-tubercular drugs has become the foremost challenge now. According to WHO, over half a million of multidrug resistance cases (rifampicin, isoniazid, etc.) were reported in 2017, mostly emerging from countries such as China, India, and Russia. Therefore, developing new drugs or repurposing existing ones is need of the hour. The Mycobacterium cell wall biogenesis pathway offers many attractive targets for drug discovery against Tuberculosis (TB). MurA, a transferase enzyme that catalyzes the initial step of peptidoglycan (PG) biosynthesis, is one among them. A peptidoglycan layer resides over the plasma membrane and is an integral component of the bacterial cell wall. Therefore, disruption of their formation through inhibition of MurA enzyme should lead to deficiency in Mycobacterium cell synthesis. Based on this strategy, we have designed this study where two libraries of peptidomimetic compounds (Asinex & ChemDiv) were first screened against our modeled MurA structure and then validated through molecular dynamic simulations. From our virtual screening, top four compounds (ChemDiv: D675-0102, D675-0217; Asinex: BDE25373574, BDE 26717803) were selected based on their docking scores, binding energies, and interactions with catalytic site residues, for further evaluation. Results revealed stable ligand-MurA interactions throughout 50 ns of MD simulation and also druggability acceptable pharmacokinetic profile for all four compounds. Thus, based on our findings, these compounds could be considered as potential inhibitors of Mycobacterium MurA enzyme and hence be further tested for in vitro experimental validation as TB therapeutic drug candidate.Communicated by Ramaswamy H. Sarma.

A Library Screening Strategy Combining the Concepts of MS Binding Assays and Affinity Selection Mass Spectrometry

The primary objective of early drug development is to identify hits and leads for a target of interest. To achieve this aim, rapid, and reliable screening techniques for a huge number of compounds are needed. Mass spectrometry based binding assays (MS Binding Assays) represent a well-established technique for library screening based on competitive binding experiments revealing active sublibraries due to reduced binding of a reporter ligand and following hit identification for active libraries by deconvolution in further competitive binding experiments. In the present study, we combined the concepts of MS Binding Assays and affinity selection mass spectrometry (ASMS) to improve the efficiency of the hit identification step. In that case, only a single competitive binding experiment is performed that is in the first step analyzed for reduced binding of the reporter ligand and—only if a sublibrary is active—additionally for specific binding of individual library components. Subsequently, affinities of identified hits as well as activities of reduced sublibraries (i.e., all sublibrary components without hit) are assessed in additional competitive binding experiments. We exemplified this screening concept for the identification of ligands addressing the most widespread GABA transporter subtype in the brain (GAT1) studying in the beginning a library composed of 128 and further on a library of 1,280 well-characterized GAT1 inhibitors, drug substances, and pharmacological tool compounds. Determination of sublibraries' activities was done by quantification of bound NO711 as reporter ligand and hit identification for the active ones achieved in a further LC-ESI-MS/MS run in the multiple reaction monitoring mode enabling detection of all sublibrary components followed by hit verification and investigation of reduced sublibraries in further competitive binding experiments. In this way, we could demonstrate that all GAT1 inhibitors reducing reporter ligand binding below 50% at a concentration of 1 μM are detected reliably without generation of false positive or false negative hits. As the described strategy is apart from its reliability also highly efficient, it can be assumed to become a valuable tool in early drug research, especially for membrane integrated drug targets that are often posing problems in established screening techniques.

A modular DNA scaffold to study protein-protein interactions at single-molecule resolution

The residence time of a drug on its target has been suggested as a more pertinent metric of therapeutic efficacy than the traditionally used affinity constant. Here, we introduce junctured-DNA tweezers as a generic platform that enables real-time observation, at the single-molecule level, of biomolecular interactions. This tool corresponds to a double-strand DNA scaffold that can be nanomanipulated and on which proteins of interest can be engrafted thanks to widely used genetic tagging strategies. Thus, junctured-DNA tweezers allow a straightforward and robust access to single-molecule force spectroscopy in drug discovery, and more generally in biophysics. Proof-of-principle experiments are provided for the rapamycin-mediated association between FKBP12 and FRB, a system relevant in both medicine and chemical biology. Individual interactions were monitored under a range of applied forces and temperatures, yielding after analysis the characteristic features of the energy profile along the dissociation landscape.

Surface plasmon resonance (SPR) biosensors for food allergen detection in food matrices

Food allergies are recognized as a growing public health concern, with an estimated 3% of adults and 6-8% of children affected by food allergy disorders. Hence, food allergen detection, labeling, and management have become significant priorities within the food industry, and there is an urgent requirement for reliable, sensitive, and user-friendly technologies to trace food allergens in food products. In this critical review, we provide a comprehensive overview of the principles and applications of surface plasmon resonance (SPR) biosensors in the identification and quantification of food allergens (milk, egg, peanut, and seafood), including fiber-optic surface plasmon resonance (FOSPR), surface plasmon resonance imaging (SPRI), localized surface plasmon resonance (LSPR), and transmission surface plasmon resonance (TSPR). Moreover, the characteristics and fitness-for-purpose of each reviewed SPR biosensor is discussed, and the potential of newly developed SPR biosensors for multi-allergen real-time detection in a complex food system is highlighted. Such SPR biosensors are also required to facilitate the reliable, high-throughput, and real-time detection of food allergens by the food control industry and food safety control officials to easily monitor cross-contamination during food processing.

A Structure-Based Drug Discovery Paradigm

Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the “big data” generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

Covalent affixation of histidine-tagged proteins tethered onto Ni-nitrilotriacetic acid sensors for enhanced surface plasmon resonance detection of small molecule drugs and kinetic studies of antibody/antigen interactions

Covalent affixation of histidine-tagged proteins tethered onto Ni-nitrilotriacetic acid sensors for enhanced surface plasmon resonance detection.

Integrating Molecular Docking and Molecular Dynamics Simulations

Computational methods, applied at the early stages of the drug design process, use current technology to provide valuable insights into the understanding of chemical systems in a virtual manner, complementing experimental analysis. Molecular docking is an in silico method employed to foresee binding modes of small compounds or macromolecules in contact with a receptor and to predict their molecular interactions. Moreover, the methodology opens up the possibility of ranking these compounds according to a hierarchy determined using particular scoring functions. Docking protocols assign many approximations, and most of them lack receptor flexibility. Therefore, the reliability of the resulting protein-ligand complexes is uncertain. The association with the costly but more accurate MD techniques provides significant complementary with docking. MD simulations can be used before docking since a series of "new" and broader protein conformations can be extracted from the processing of the resulting trajectory and employed as targets for docking. They also can be utilized a posteriori to optimize the structures of the final complexes from docking, calculate more detailed interaction energies, and provide information about the ligand binding mechanism. Here, we focus on protocols that offer the docking-MD combination as a logical approach to improving the drug discovery process.

Discovery of monoamine oxidase inhibitors by medicinal chemistry approaches

Neuropsychiatric disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD) and depression, have seriously inconvenienced the lives of patients. Growing evidence indicates that these diseases are closely related to the monoamine oxidase (MAO) enzyme, making it an attractive target for the exploitation of potent MAO inhibitors (MAOIs) with high selectivity and low side effects. Although various MAOIs have been discovered, the discovery of an ideal MAOI is not an easy task. In this review, we discuss the currently available rational design strategies for obtaining ideal MAOIs, including ligand-based and receptor-based design strategies, and these strategies were further illustrated with the aid of specific examples from the recent literature. To better understanding the biological activity of MAO, we also highlight the binding modes of typical inhibitors against MAO. Besides, advanced strategies for finding upcoming potent MAOIs were prospected.

Probing Membrane Receptors with Enhanced Raman Imaging

Our lab has shown that nanoparticles functionalized with short peptides can selectively bind to receptor proteins in vitro. Our results indicate that the Raman signals observed from purified receptors in surface enhanced Raman scattering (SERS) experiments match those observed with tip-enhanced Raman scattering (TERS) experiments performed on membrane receptors in intact cell membranes. Analysis of the observed Raman signals suggest the signals arise from the amino-acids in the protein receptor responsible for binding and recognition of the ligand attached to the nanoparticle probe. Further experiments show the variance in the data correlates with affinity of the nanoparticle probe with a specific receptor. This result illustrates a new approach to studying membrane receptors.

Homogeneous Assay for Target Engagement Utilizing Bioluminescent Thermal Shift

Protein thermal shift assays (TSAs) provide a means for characterizing target engagement through ligand-induced thermal stabilization. Although these assays are widely utilized for screening libraries and validating hits in drug discovery programs, they can impose encumbering operational requirements, such as the availability of purified proteins or selective antibodies. Appending the target protein with a small luciferase (NanoLuc) allows coupling of thermal denaturation with luminescent output, providing a rapid and sensitive means for assessing target engagement in compositionally complex environments such as permeabilized cells. The intrinsic thermal stability of NanoLuc is greater than mammalian proteins, and our results indicate that the appended luciferase does not alter thermal denaturation of the target protein. We have successfully applied the NanoLuc luciferase thermal shift assay (NaLTSA) to several clinically relevant protein families, including kinases, bromodomains, and histone deacetylases. We have also demonstrated the suitability of this assay method for library screening and compound profiling.

Overview of the detection methods for equilibrium dissociation constant KD of drug-receptor interaction

Drug-receptor interaction plays an important role in a series of biological effects, such as cell proliferation, immune response, tumor metastasis, and drug delivery. Therefore, the research on drug-receptor interaction is growing rapidly. The equilibrium dissociation constant (KD) is the basic parameter to evaluate the binding property of the drug-receptor. Thus, a variety of analytical methods have been established to determine the KD values, including radioligand binding assay, surface plasmon resonance method, fluorescence energy resonance transfer method, affinity chromatography, and isothermal titration calorimetry. With the invention and innovation of new technology and analysis method, there is a deep exploration and comprehension about drug-receptor interaction. This review discusses the different methods of determining the KD values, and analyzes the applicability and the characteristic of each analytical method. Conclusively, the aim is to provide the guidance for researchers to utilize the most appropriate analytical tool to determine the KD values.

Electromagnetic Nanoparticles for Sensing and Medical Diagnostic Applications

A modeling and design approach is proposed for nanoparticle-based electromagnetic devices. First, the structure properties were analytically studied using Maxwell's equations. The method provides us a robust link between nanoparticles electromagnetic response (amplitude and phase) and their geometrical characteristics (shape, geometry, and dimensions). Secondly, new designs based on "metamaterial" concept are proposed, demonstrating great performances in terms of wide-angle range functionality and multi/wide behavior, compared to conventional devices working at the same frequencies. The approach offers potential applications to build-up new advanced platforms for sensing and medical diagnostics. Therefore, in the final part of the article, some practical examples are reported such as cancer detection, water content measurements, chemical analysis, glucose concentration measurements and blood diseases monitoring.

Simultaneous Multiple MS Binding Assays for the Dopamine, Norepinephrine, and Serotonin Transporters

In this work, we present label-free, mass-spectrometry-based binding assays (MS Binding Assays), targeting the human dopamine, norepinephrine, and serotonin transporters (hDAT, hNET, and hSERT) in simultaneous binding experiments. Using a validated LC-ESI-MS/MS method for quantification of the selective dopamine transporter inhibitor (R,R)-4-(2-benzhydryloxyethyl)-1-(4-fluorobenzyl)piperidin-3-ol ((R,R)-D-84), the selective norepinephrine transporter inhibitor (S,S)-reboxetine, and the selective serotonin reuptake inhibitor (S)-citalopram, binding affinities at the three monoamine transporters could be characterized simultaneously in a single binding experiment. The performed simultaneous saturation and competition experiments yielded results that are in good accordance with those determined in MS Binding Assays addressing the monoamine transporters individually. The results obtained from this study underscore the potential of MS Binding Assays for simultaneous affinity determination at different targets, which is difficult to accomplish with conventional radioligand binding assays.

Mining the Potential of Label-Free Biosensors for In Vitro Antipsychotic Drug Screening

The pharmaceutical industry is facing enormous challenges due to high drug attribution rates. For the past decades, novel methods have been developed for safety and efficacy testing, as well as for improving early development stages. In vitro screening methods for drug-receptor binding are considered to be good alternatives for decreasing costs in the identification of drug candidates. However, these methods require lengthy and troublesome labeling steps. Biosensors hold great promise due to the fact that label-free detection schemes can be designed in an easy and low-cost manner. In this paper, for the first time in the literature, we aimed to compare the potential of label-free optical and impedimetric electrochemical biosensors for the screening of antipsychotic drugs (APDs) based on their binding properties to dopamine receptors. Particularly, we have chosen a currently-used atypical antipsychotic drug (Buspirone) for investigating its dopamine D3 receptor (D3R) binding properties using an impedimetric biosensor and a nanoplasmonic biosensor. Both biosensors have been specifically functionalized and characterized for achieving a highly-sensitive and reliable analysis of drug-D3R binding. Our biosensor strategies allow for comparing different affinities against the D3R, which facilitates the identification of strong or weak dopamine antagonists via in vitro assays. This work demonstrates the unique potential of label-free biosensors for the implementation of cost-efficient and simpler analytical tools for the screening of antipsychotic drugs.

Combining Mass Spectrometry and X-Ray Crystallography for Analyzing Native-Like Membrane Protein Lipid Complexes

Membrane proteins represent a challenging family of macromolecules, particularly related to the methodology aimed at characterizing their three-dimensional structure. This is mostly due to their amphipathic nature as well as requirements of ligand bindings to stabilize or control their function. Recently, Mass Spectrometry (MS) has become an important tool to identify the overall stoichiometry of native-like membrane proteins complexed to ligand bindings as well as to provide insights into the transport mechanism across the membrane, with complementary information coming from X-ray crystallography. This perspective article emphasizes MS findings coupled with X-ray crystallography in several membrane protein lipid complexes, in particular transporters, ion channels and molecular machines, with an overview of techniques that allows a more thorough structural interpretation of the results, which can help us to unravel hidden mysteries on the membrane protein function.

Simultaneous Multiple MS Binding Assays Addressing D1 and D2 Dopamine Receptors

MS Binding Assays are a label-free alternative to radioligand binding assays. They provide basically the same capabilities as the latter, but use a non-labeled reporter ligand instead of a radioligand. In contrast to radioligand binding assays, MS Binding Assays offer-owing to the selectivity of mass spectrometric detection-the opportunity to monitor the binding of different reporter ligands at different targets simultaneously. The present study shows a proof of concept for this strategy as exemplified for MS Binding Assays selectively addressing D₁ and D₂ dopamine receptors in a single binding experiment. A highly sensitive, rapid and robust LC-ESI-MS/MS quantification method capable of quantifying both SCH23390 and raclopride, selectively addressing D₁ and D₂ receptors, respectively, was established and validated for this purpose. Based thereon, simultaneous saturation and competition experiments with SCH23390 and raclopride in the presence of both D₁ and D₂ receptors were performed and analyzed by LC-MS/MS within a single chromatographic cycle. The present study thus demonstrates the feasibility of this strategy and the high versatility of MS Binding Assays that appears to surpass that common for conventional radioligand binding assays.

New methodologies in screening of antibiotic residues in animal-derived foods: Biosensors

Antibiotics are leading medicine asset for fighting against microbial infection, but also one of the important causes of death worldwide. Many antibiotics used as therapeutics and growth promotion agents in animals can lead to antibiotic residues in animal-derived food which harm the health of people. Hence, it is vital to screen antibiotic residues in animal derived foods. Typical methods for screening antibiotic residues are based on microbiological growth inhibition and immunological analyses. However these two methods have some disadvantages, such as poor sensitive, lack of specificity and etc. Therefore, it is necessary to develop simple, more efficient and high sensitive screening methods of antibiotic residues. These assays have been introduced for the screening of numerous food samples. Biosensors are emerging methods, applied in screening antibiotic residues in animal-derived foods. Two types of biosensors, whole-cell based biosensors and surface plasmon resonance-based sensors have been extensively used. Their advantages include portability, small sample requirement, high sensitivity and good specificity over the traditional screening methods.

Competitive ligands facilitate dissociation of the complex of bifunctional inhibitor and protein kinase

Dissociation of the complex of a ligand and a protein usually follows the kinetic profile of the first order process and the rate of dissociation is not affected by the presence of competitive ligands. We discovered that dissociation of the complex between a bifunctional ligand and a protein kinase (the catalytic subunit of cAMP-dependent protein kinase), an enzyme possessing 2 different substrate binding sites, was accelerated (facilitated) over 50-fold in the presence of competitive ligands at higher concentrations. Structurally diverse compounds revealed >10-fold different efficiency for acceleration of dissociation of the complex. These results show that the kinetic behavior of flexible biomolecular complexes possessing two spatially separated contact areas is highly dynamic. This property of biomolecular complexes should be carefully considered for effective application of bifunctional ligands for regulation of activity of target proteins in cells.

Surface plasmon resonance based competitive immunoassay for Cd2+

In this study, a label-free, specific and sensitive surface plasmon resonance (SPR) based competitive immunoassay was used for detecting Cd²⁺ in water samples.

Surface plasmon resonance sensor for antibiotics detection based on photo-initiated polymerization molecularly imprinted array

A surface plasmon resonance (SPR) sensor combined with nanoscale molecularly imprinted polymer (MIP) film as recognition element was developed for selective detection of the antibiotic ciprofloxacin (CIP). The MIP film on SPR sensor chip was prepared by in situ photo-initiated polymerization method which has the advantages of short polymerization time, controllable thickness and good uniformity. The surface wettability and thickness of MIP film on SPR sensor chip were characterized by static contact angle measurement and stylus profiler. The MIP-SPR sensor exhibited high selectivity, sensitivity and good stability for ciprofloxacin. The imprinting factors of the MIP-SPR sensor to ciprofloxacin and its structural analogue ofloxacin were 2.63 and 3.80, which is much higher than those to azithromycin, dopamine and penicillin. The SPR response had good linear relation with CIP concentration over the range 10^-11-10^-7molL^-1. The MIP-SPR sensor also showed good repeatability and stability during cyclic detections. On the basis of the photo-initiated polymerization method, a surface plasmon resonance imaging (SPRi) chip modified with three types of MIP sensing spots was fabricated. The MIPs-SPRi sensor shows different response patterns to ciprofloxacin and azithromycin, revealing the ability to recognize different antibiotic molecules.

Binding Kinetics in Drug Discovery

Over the last years, researchers have increasingly become interested in measuring and understanding drugs' binding kinetics, namely the time in which drug and its target associate and dissociate. Historically, drug discovery programs focused on the optimization of target affinity as a proxy of in-vivo efficacy. However, often the efficacy of a ligand is not appropriately described by the in-vitro measured drug-receptor affinity, but rather depends on the lifetime of the in-vivo drug-receptor interaction. In this review we review recent works that highlight the importance of binding kinetics, molecular determinants for rational optimization and the recent emergence of computational methods as powerful tools in measuring and understanding binding kinetics.

Functional Stability of the Human Kappa Opioid Receptor Reconstituted in Nanodiscs Revealed by a Time-Resolved Scintillation Proximity Assay

Long-term functional stability of isolated membrane proteins is crucial for many in vitro applications used to elucidate molecular mechanisms, and used for drug screening platforms in modern pharmaceutical industry. Compared to soluble proteins, the understanding at the molecular level of membrane proteins remains a challenge. This is partly due to the difficulty to isolate and simultaneously maintain their structural and functional stability, because of their hydrophobic nature. Here we show, how scintillation proximity assay can be used to analyze time-resolved high-affinity ligand binding to membrane proteins solubilized in various environments. The assay was used to establish conditions that preserved the biological function of isolated human kappa opioid receptor. In detergent solution the receptor lost high-affinity ligand binding to a radiolabelled ligand within minutes at room temperature. After reconstitution in Nanodiscs made of phospholipid bilayer the half-life of high-affinity ligand binding to the majority of receptors increased 70-fold compared to detergent solubilized receptors—a level of stability that is appropriate for further downstream applications. Time-resolved scintillation proximity assay has the potential to screen numerous conditions in parallel to obtain high levels of stable and active membrane proteins, which are intrinsically unstable in detergent solution, and with minimum material consumption.