Scaffold hopping of α-rubromycin enables direct access to FDA-approved cromoglicic acid as a SARS-CoV-2 M^Pro inhibitor

The COVID-19 pandemic is still active around the globe despite the newly introduced vaccines. Hence, finding effective medications or repurposing available ones could offer great help during this serious situation. During our anti-COVID-19 investigation of microbial natural products (MNPs), we came across α-rubromycin, an antibiotic derived from Streptomyces collinus ATCC19743, which was able to suppress the catalytic activity (IC50 = 5.4 µM and Ki = 3.22 µM) of one of the viral key enzymes (i.e., MPro). However, it showed high cytotoxicity toward normal human fibroblasts (CC50 = 16.7 µM). To reduce the cytotoxicity of this microbial metabolite, we utilized a number of in silico tools (ensemble docking, molecular dynamics simulation, binding free energy calculation) to propose a novel scaffold having the main pharmacophoric features to inhibit MPro with better drug-like properties and reduced/minimal toxicity. Nevertheless, reaching this novel scaffold synthetically is a time-consuming process, particularly at this critical time. Instead, this scaffold was used as a template to explore similar molecules among the FDA-approved medications that share its main pharmacophoric features with the aid of pharmacophore-based virtual screening software. As a result, cromoglicic acid (aka cromolyn) was found to be the best hit, which, upon in vitro MPro testing, was 4.5 times more potent (IC50 = 1.1 µM and Ki = 0.68 µM) than α-rubromycin, with minimal cytotoxicity toward normal human fibroblasts (CC50 > 100 µM). This report highlights the potential of MNPs in providing unprecedented scaffolds with a wide range of therapeutic efficacy. It also revealed the importance of cheminformatics tools in speeding up the drug discovery process, which is extremely important in such a critical situation

Multireactive PV-electrophiles for cysteine directed bioconjugation

In der vorliegenden Arbeit werden drei neue Klassen von modular zugänglichen Elektrophilen für die Biokonjugation von Cystein vorgestellt. Diethynyl-phosphinate (DPs) wurden als bisreaktive Elektrophile für die cysteinselektive Markierung von Peptiden, Proteinen und Antikörpern entwickelt. In diesen Molekülen können beide elektronenarmen Dreifachbindungen unter physiologischen Bedingungen mit Thiol-Nukleophilen reagieren und die erhaltenen Konjugate sind in menschlichem Plasma und in Gegenwart großer Mengen an reduziertem Glutathion stabil. Darüber hinaus wurden DPs in der selektiven Herstellung verschiedener Protein-(Doppel)-Konjugate angewandt. Neben der klassischen Proteinmodifikation können DPs auch zur kovalenten Verbrückung der Disulfidbrücken von Antikörpern eingesetzt werden. Weiters wurde mit Hilfe von Dichtefunktionaltheorie-Berechnungen werden Ethinyl-triazolyl-phosphinate (ETP) als eine neue Klasse hochreaktiver Elektrophile für die Cystein-Biokonjugation entdeckt. Die Berechnungen zeigen, dass sowohl die elektronenziehenden als auch die π-Elektronen donierenden Eigenschaften des Triazolrings die Reaktivität erhöhen. Vor allem aber wird gezeigt, dass ETP-Elektrophile über die chemoselektive Cu(I)-katalysierte Azid-Alkin-Cycloaddition in ein azidhaltiges Molekül eingebaut werden können. Da diese Reaktion problemlos in wässrigen Puffersystemen abläuft, konnte eine Vielzahl funktioneller Elektrophile, einschließlich elektrophiler Peptide und Proteine, aus DPs erzeugt werden. Schließlich wurden Diethinylphosphinoxide als chemoselektive Reagenzien zur Disulfidvererbrückung untersucht. Insbesondere Diethinyl-Triazolyl-Phosphinoxide (DTP) sind vielversprechende Kandidaten, da sie die modulare Synthese von ETP-Elektrophilen mit den beiden reaktiven Gruppen in DPs kombinieren. Die Fähigkeit der DTP-Reagenzien, Disulfide zu verbrücken, wurde durch die Bildung mehrerer funktioneller Antikörperkonjugate gezeigt.The present work introduces three new classes of modular accessible electrophiles for cysteine bioconjugation. Diethynyl-phosphinates (DPs) were developed as bisreactive electrophiles for the cysteine-selective modification of peptides, proteins and antibodies. Both electrophilic alkynes can react with thiol-nucleophiles under physiological conditions. The corresponding double-conjugates are stable in human plasma and in the presence of a large excess reduced glutathione. Furthermore, the general applicability of diethynyl phosphinates for cysteine selective bioconjugation was established by the generation of various protein-(double)-conjugates and their application in cell experiments. Additionally, DPs can be employed to covalently rebridge the interchain disulfides of therapeutically relevant IgG1 antibodies. Furthermore, with the help of density functional theory based calculations, ethynyl-triazolyl-phosphinates (ETP) were discovered as a new class of highly reactive electrophilic warheads for cysteine bioconjugation. According to the calculations, both the electron withdrawing as well as the π-electron donating properties of the triazole-ring enhance the reactivity of the electrophile. Most importantly, it was demonstrated that ETP electrophiles can be incorporated into a given azide containing molecule via the chemoselective CuI-catalyzed azide alkyne cycloaddition. ETP-reagents were used to obtain functional peptide-, protein- and antibody-conjugates, as well as site-specifically linked diubiquitins. Finally, diethynyl phosphine oxides were explored as chemoselective reagents for disulfide rebridging. Especially diethynyl-triazolyl-phosphine oxides (DTP) are promising candidates since they combine the modular synthesis of ETP-electrophiles with the two reactive groups present in diethynyl phosphinates. The capability of DTP-reagents to rebridged disulfides was proven by the formation several functional antibody conjugates

Investigation into biological and biomimetic transmembrane systems

Membranes are essential components of living organisms, which serve as effective barriers that separate distinct chemical environments on either side of the membrane. Chemists have designed biological and synthetic systems to functionalise membrane-embedded systems for a variety of applications such as sensing, sequencing, reaction mechanistic studies, and therapeutics. The continuous interest in functionalising membranes, combined with incomplete understanding of the underlying factors determining their mechanisms inspired the investigations undertaken in this work. This Thesis employs both experimental and computational methods to explore two distinct applications for sequencing and therapeutics, respectively. (1) Engineered biological nanopores have found great success in DNA sequencing. The Bayley group previously reported a molecular hopper, which makes sub-nanometer steps by thiol-disulfide interchange along a track with cysteine footholds within a protein nanopore. In Chapter 2, the hopping rate was optimized with a view towards rapid enzymeless biopolymer characterization during translocation within nanopores. I first used a nanopore approach to systematically profile the reactivity of individual cysteine footholds along an engineered protein track at the single-molecule level. Using this approach, I calculated the pKa of cysteine thiols and the pH-independent rate constants for the reaction between thiolates and a disulfide molecule. This reactivity profile guided site-specific mutagenesis. Together with the optimization of experimental conditions, the overall stepping rate of a DNA cargo along a five-cysteine track was accelerated. This work extends the practical application of this enzymeless system as a sequencing method for biopolymers beyond DNA. (2) Synthetic anion transporters have attracted significant attention as promising therapeutics for ion channel diseases. In Chapter 3, I use computational modelling to investigate the chloride binding and transmembrane transport mechanisms of E-/Z-switchable synthetic transporters. Using a model system,I developed a workflow to construct full energy profiles for the transmembrane transport process. These results revealed the importance of pre-organization of the Z-isomer and the balance between the energy barrier of transport and the solubility of the transporter. Additionally, in Chapter 4, I present a predictive machine-learning (ML) approach for estimating the chloride transport activity of a variety of synthetic chloride transporters. The ML models, employing both classification and regression frameworks, exhibited remarkable performance across a diverse range of systems. Moreover, they offered insights crucial for future design efforts, e.g., identifying key structural features and experimental conditions that influence the observed transport activity. Overall, this work bridges biological and molecular design, computational modelling and data-driven approaches to advance the development of two applications to functionalise membranes for sequencing and therapeutics. It provides interpretable molecular models as well as structure-activity relationships that will aid hypothesis generation and contribute to synthetic advances in both fields

Metabolic and Mechanistic Studies in the Safety Evaluation of Trans-Cinnamaldehyde

Imperial Users onl

Diffusion of tin from TEC-8 conductive glass into mesoporous titanium dioxide in dye sensitized solar cells

The photoanode of a dye sensitized solar cell is typically a mesoporous titanium dioxide thin film adhered to a conductive glass plate. In the case of TEC-8 glass, an approximately 500 nm film of tin oxide provides the conductivity of this substrate. During the calcining step of photoanode fabrication, tin diffuses into the titanium dioxide layer. Scanning Electron Microscopy and Electron Dispersion Microscopy are used to analyze quantitatively the diffusion of tin through the photoanode. At temperatures (400 to 600 °C) and times (30 to 90 min) typically employed in the calcinations of titanium dioxide layers for dye sensitized solar cells, tin is observed to diffuse through several micrometers of the photoanode. The transport of tin is reasonably described using Fick\u27s Law of Diffusion through a semi-infinite medium with a fixed tin concentration at the interface. Numerical modeling allows for extraction of mass transport parameters that will be important in assessing the degree to which tin diffusion influences the performance of dye sensitized solar cells

Lead optimization for new antimalarials and Successful lead identification for metalloproteinases: A Fragment-based approach Using Virtual Screening

Lead optimization for new antimalarials and Successful lead identification for metalloproteinases: A Fragment-based approach Using Virtual Screening Computer-aided drug design is an essential part of the modern medicinal chemistry, and has led to the acceleration of many projects. The herein described thesis presents examples for its application in the field of lead optimization and lead identification for three metalloproteins. DOXP-reductoisomerase (DXR) is a key enzyme of the mevalonate independent isoprenoid biosynthesis. Structure-activity relationships for 43 DXR inhibitors are established, derived from protein-based docking, ligand-based 3D QSAR and a combination of both approaches as realized by AFMoC. As part of an effort to optimize the properties of the established inhibitor Fosmidomycin, analogues have been synthesized and tested to gain further insights into the primary determinants of structural affinity. Unfortunately, these structures still leave the active Fosmidomycin conformation and detailed reaction mechanism undetermined. This fact, together with the small inhibitor data set provides a major challenge for presently available docking programs and 3D QSAR tools. Using the recently developed protein tailored scoring protocol AFMoC precise prediction of binding affinities for related ligands as well as the capability to estimate the affinities of structurally distinct inhibitors has been achieved. Farnesyltransferase is a zinc-metallo enzyme that catalyzes the posttranslational modification of numerous proteins involved in intracellular signal transduction. The development of farnesyltransferase inhibitors is directed towards the so-called non-thiol inhibitors because of adverse drug effects connected to free thiols. A first step on the way to non-thiol farnesyltransferase inhibitors was the development of an CAAX-benzophenone peptidomimetic based on a pharmacophore model. On its basis bisubstrate analogues were developed as one class of non-thiol farnesyltransferase inhibitors. In further studies two aryl binding and two distinct specificity sites were postulated. Flexible docking of model compounds was applied to investigate the sub-pockets and design highly active non-thiol farnesyltransferase inhibitor. In addition to affinity, special attention was paid towards in vivo activity and species specificity. The second part of this thesis describes a possible strategy for computer-aided lead discovery. Assembling a complex ligand from simple fragments has recently been introduced as an alternative to traditional HTS. While frequently applied experimentally, only a few examples are known for computational fragment-based approaches. Mostly, computational tools are applied to compile the libraries and to finally assess the assembled ligands. Using the metalloproteinase thermolysin (TLN) as a model target, a computational fragment-based screening protocol has been established. Starting with a data set of commercially available chemical compounds, a fragment library has been compiled considering (1) fragment likeness and (2) similarity to known drugs. The library is screened for target specificity, resulting in 112 fragments to target the zinc binding area and 75 fragments targeting the hydrophobic specificity pocket of the enzyme. After analyzing the performance of multiple docking programs and scoring functions forand the most 14 candidates are selected for further analysis. Soaking experiments were performed for reference fragment to derive a general applicable crystallization protocol for TLN and subsequently for new protein-fragment complex structures. 3-Methylsaspirin could be determined to bind to TLN. Additional studies addressed a retrospective performance analysis of the applied scoring functions and modification on the screening hit. Curios about the differences of aspirin and 3-methylaspirin, 3-chloroaspirin has been synthesized and affinities could be determined to be 2.42 mM; 1.73 mM und 522 μM respectively. The results of the thesis show, that computer aided drug design approaches could successfully support projects in lead optimization and lead identification. fragments in general, the fragments derived from the screening are docke

High-Throughput Approaches for the Assessment of Factors Influencing Bioavailability of Small Molecules in Pre-Clinical Drug Development

A bioactive molecule must pass many hurdles to be designated as a good pharmaceutical lead or hit compound. It should have a significant activity, selectivity, bioavailability, and metabolic half-life. Many factors have been identified that influence the free drug concentration or bioavailability of orally administered drugs in the earliest development stages. In vitro pre-clinical assays have been developed to measure these parameters. The small molecule properties that are investigated here include aqueous solubility, permeability, reactivity (electrophilicity), small molecule-protein binding, and displacement of protein-bound molecules (drug-drug interactions). The development of rapid and miniaturized assays to quantify these factors is presented herein. First, a 384-well filter plate based assay was developed to determine the aqueous compound solubility to greatly decrease the time and amount of compound necessary for analysis. Secondly, one of the most common and simple permeability assays (parallel artificial membrane permeability assay, PAMPA) was optimized using a filter membrane impregnated with a long chain alkane (hexadecane) solution as an artificial membrane. Thirdly, permeability was also determined rapidly with the use of Immobilized Artificial Membrane (IAM) and C18 stationary phases by HPLC. The solitary and sequential usage of these columns was compared. Fourthly, a novel fluorescence-based high-throughput assay was developed to identify electrophilic molecules rapidly, in parallel, among small molecule libraries using only sub-milligram quantities. Subsequently, a filtration-based assay to estimate compound binding with plasma protein was developed for a 384-well plate format. This assay not only increases the throughput, but also addresses non-specific compound binding to the filtration apparatus, which is problematic with other ultrafiltration methods. Finally, a simple high-throughput competitive protein binding assay was developed based on the multiplexing of fluorescent small molecule probes with different spectroscopic and binding properties. The inhibition of probe-protein binding has been identified as a good indicator for plasma protein binding

Analysis of Multitarget Activities and Assay Interference Characteristics of Pharmaceutically Relevant Compounds

The availability of large amounts of data in public repositories provide a useful source of knowledge in the field of drug discovery. Given the increasing sizes of compound databases and volumes of activity data, computational data mining can be used to study different characteristics and properties of compounds on a large scale. One of the major source of identification of new compounds in early phase of drug discovery is high-throughput screening where millions of compounds are tested against many targets. The screening data provides opportunities to assess activity profiles of compounds. This thesis aims at systematically mining activity data from publicly available sources in order to study the nature of growth of bioactive compounds, analyze multitarget activities and assay interference characteristics of pharmaceutically relevant compounds in context of polypharmacology. In the first study, growth of bioactive compounds against five major target families is monitored over time and compound-scaffold-CSK (cyclic skeleton) hierarchy is applied to investigate structural diversity of active compounds and topological diversity of their scaffolds. The next part of the thesis is based on the analysis of screening data. Initially, extensively assayed compounds are mined from the PubChem database and promiscuity of these compounds is assessed by taking assay frequencies into account. Next, DCM (dark chemical matter) or consistently inactive compounds that have been extensively tested are systematically extracted and their analog relationships with bioactive compounds are determined in order to derive target hypotheses for DCM. Further, PAINS (pan-assay interference compounds) are identified in the extensively tested set of compounds using substructure filters and their assay interference characteristics are studied. Finally, the limitations of PAINS filters are addressed using machine learning models that can distinguish between promiscuous and DCM PAINS. Structural context dependence of PAINS activities is studied by assessing predictions through feature weighting and mapping