Fragment-based Approach Research Articles

Validation of a smartphone-compatible MIP-based sensor for bisphenol A determination in wastewater samples.

A handheld smartphone-compatible molecularly imprinted polymer (MIP)-based sensor was developed for the analysis of bisphenol A (BPA) in wastewater samples. Sensing elements based on ethylene glycol methacrylate phosphate (EGMP)-containing MIP films were designed and optimized using molecular dynamics simulations. The highly porous MIP films were synthesized via in situ polymerization, employing a fragment-based approach. The colorimetric response was based on the 4-aminoantipyrine method, while the MIP films were further utilized to detect BPA with a smartphone. The proposed sensor exhibited a wide linear range from 5 to 250μM, with a limit of detection (LOD) of 5μM (S/N = 3). Furthermore, the designed analytical system demonstrated excellent analytical performance in terms of selectivity, stability, and reproducibility. During sensor validation, real wastewater samples were successfully tested for BPA, showcasing the feasibility of the smartphone-compatible MIP-based sensor. Recovery values of 87.1-114.6% underscored the efficacy and reliability of the developed sensor system.

Identification of a cell-active chikungunya virus nsP2 protease inhibitor using a covalent fragment-based screening approach

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that has been responsible for numerous large-scale outbreaks in the last twenty years. Currently, there are no FDA-approved therapeutics for any alphavirus infection. CHIKV nonstructural protein 2 (nsP2), which contains a cysteine protease domain, is essential for viral replication, making it an attractive target for a drug discovery campaign. Here, we optimized a CHIKV nsP2 protease (nsP2pro) biochemical assay for the screening of a 6,120-compound cysteine-directed covalent fragment library. Using a 50% inhibition threshold, we identified 153 hits (2.5% hit rate). In dose-response follow-up, RA-0002034, a covalent fragment that contains a vinyl sulfone warhead, inhibited CHIKV nsP2pro with an IC50 of 58 ± 17 nM, and further analysis with time-dependent inhibition studies yielded a kinact /KI of 6.4 × 103 M-1s-1. LC-MS/MS analysis determined that RA-0002034 covalently modified the catalytic cysteine in a site-specific manner. Additionally, RA-0002034 showed no significant off-target reactivity in proteomic experiments or against a panel of cysteine proteases. In addition to the potent biochemical inhibition of CHIKV nsP2pro activity and exceptional selectivity, RA-0002034 was tested in cellular models of alphavirus infection and effectively inhibited viral replication of both CHIKV and related alphaviruses. This study highlights the identification and characterization of the chemical probe RA-0002034 as a promising hit compound from covalent fragment-based screening for development toward a CHIKV or pan-alphavirus therapeutic.

First fragment-based screening identifies new chemotypes inhibiting ERAP1-metalloprotease

Inhibition of endoplasmic reticulum aminopeptidase 1 (ERAP1) by small-molecules is being eagerly investigated for the treatment of various autoimmune diseases and in the field of immuno-oncology after its active involvement in antigen presentation and processing. Currently, ERAP1 inhibitors are at different stages of clinical development, which highlights its significance as a promising drug target. In the present work, we describe the first-ever successful identification of several ERAP1 inhibitors derived from a fragment-based screening approach. We applied an enzymatic activity assay to a large library of ∼3000 fragment entries in order to retrieve 32 hits. After a multi-faceted selection process, we prioritized 3 chemotypes for SAR optimization and strategic modifications provided 2 series (2-thienylacetic acid and rhodanine scaffolds) with improved analogues at the low micromolar range of ERAP1 inhibition. We report also evidence of selectivity against homologous aminopeptidase IRAP, combined with complementary in silico docking studies to predict the binding mode and site of inhibition. Our compounds can be the starting point for future fragment growing and rational drug development, incorporating new chemical modalities.

Lasamide, a Potent Human Carbonic Anhydrase Inhibitor from the Market: Inhibition Profiling and Crystallographic Studies.

Lasamide is a synthetic precursor and a contaminant of the diuretic Furosemide manufacturing process and represents a highly valuable building block for fragment-based drug discovery approaches. We assessed the ability of Lasamide to inhibit in vitro the human-expressed Carbonic Anhydrases by means of the stopped-flow technique, and we assessed its binding modes within hCAs II and XII-mimic catalytic clefts by X-ray crystallography. Interestingly, an unprecedented crystal form for the hCA IX mimic H-tag is reported and discussed herein.

Development of Fragment-Based Inhibitors of the Bacterial Deacetylase LpxC with Low Nanomolar Activity.

In a fragment-based approach using NMR spectroscopy, benzyloxyacetohydroxamic acid-derived inhibitors of the bacterial deacetylase LpxC bearing a substituent to target the uridine diphosphate-binding site of the enzyme were developed. By appending privileged fragments via a suitable linker, potent LpxC inhibitors with promising antibacterial activities could be obtained, like the one-digit nanomolar LpxC inhibitor (S)-13j [Ki (EcLpxC C63A) = 9.5 nM; Ki (PaLpxC): 5.6 nM]. To rationalize the observed structure-activity relationships, molecular docking and molecular dynamics studies were performed. Initial in vitro absorption-distribution-metabolism-excretion-toxicity (ADMET) studies of the most potent compounds have paved the way for multiparameter optimization of our newly developed isoserine-based amides.

Exploring molecular fragments for fraction unbound in human plasma of chemicals: a fragment-based cheminformatics approach

ABSTRACT Fraction unbound in plasma (f u,p) of drugs is an significant factor for drug delivery and other biological incidences related to the pharmacokinetic behaviours of drugs. Exploration of different molecular fragments for f u,p of different small molecules/agents can facilitate in identification of suitable candidates in the preliminary stage of drug discovery. Different researchers have implemented strategies to build several prediction models for f u,p of different drugs. However, these studies did not focus on the identification of responsible molecular fragments to determine the fraction unbound in plasma. In the current work, we tried to focus on the development of robust classification-based QSAR models and evaluated these models with multiple statistical metrics to identify essential molecular fragments/structural attributes for fractions unbound in plasma. The study unequivocally suggests various N-containing aromatic rings and aliphatic groups have positive influences and sulphur-containing thiadiazole rings have negative influences for the f u,p values. The molecular fragments may help for the assessment of the f u,p values of different small molecules/drugs in a speedy way in comparison to experiment-based in vivo and in vitro studies.

Structure-Informed Design of an Ultra Bright RNA-activated Fluorophore.

Fluorogenic RNAs such as the Mango aptamers are uniquely powerful tools for imaging RNA. A central challenge has been to develop brighter, more specific, and higher affinity aptamer-ligand systems for cellular imaging. Here, we report an ultra-bright fluorophore for the Mango II system discovered using a structure-informed, fragment-based small molecule microarray approach. The new dye, Structure informed, Array-enabled LigAnD 1 (SALAD1) exhibits 3.5-fold brighter fluorescence than TO1-Biotin and subnanomolar aptamer affinity. Improved performance comes solely from alteration of dye-RNA interactions, without alteration of the chromophore itself. Multiple high-resolution structures reveal a unique and specific binding mode for the new dye resulting from improved pocket occupancy, a more defined binding pose, and a novel bonding interaction with potassium. The dye notably improves in-cell confocal RNA imaging. This work provides both introduces a new RNA-activated fluorophore and also a powerful demonstration of how to leverage fragment-based ligand discovery against RNA targets.

Exploring an Intracellular Allosteric Site of CC-Chemokine Receptor4 from 3D Models, Probe Simulations, and Mutagenesis.

We applied our previously developed probe confined dynamic mapping protocol, which combines enhanced sampling molecular dynamics (MD) simulations and fragment-based approaches, to identify the binding site of GSK2239633A (N-[[3-[[3-[(5-chlorothiophen-2-yl)sulfonylamino]-4-methoxyindazol-1-yl]methyl]phenyl]methyl]-2-hydroxy-2-methylpropanamide), a selective CC-chemokine receptor type 4 (CCR4) negative allosteric modulator, using CCR4 homology and AlphaFold models. By comparing the performance across five computational models, we identified conserved (K3108.49 and Y3047.53) and non-conserved (M2436.36) residue hotspots for GSK2239633A binding, which were validated by mutagenesis and bioluminescence resonance energy transfer assay. Further analysis of 3D models and MD simulations highlighted the pair of residues 6.36 and 7.56 that might account for antagonist selectivity among chemokine receptors. Our in silico protocol provides a promising approach for characterizing ligand binding sites in membrane proteins, considering receptor dynamics and adaptability and guiding protein template selection for ligand design.

Comprehensive nontargeted analysis of fluorosurfactant byproducts and reaction products in wastewater from semiconductor manufacturing

Semiconductor manufacturing employs per- and polyfluoroalkyl substances (PFAS) as fluoroasurfactants to enhance the quality of photolithography lines. Our research, employing a fragment-based approach to investigate nontarget PFAS, overcomes conventional homologous series limitations. In a mixture of PFAS standards used as a quality control sample, 92% (36 out of 39 compounds spanning 11 compound classes) were detectable through the fragment-based nontarget procedure. This indicates the effectiveness of this approach in identifying the hydrophobic and hydrophilic characteristics of various fluorosurfactants. Eighty-three PFAS were detected in wastewater and effluent samples from semiconductor industry, including 29 newly discovered compounds, categorized into three groups. First, besides detecting perfluorobutane sulfonamido ethanol (FBSE), various fluoroalkyl chain structures of FBSE derivatives were initially identified in wastewater. These include perfluorobutyl ether sulfonamido ethanol, unsaturated FBSE, and hydrogen-substituted FBSE. These derivatives were also detected in trace amounts in commercial authentic standards of FBSE. To quantify their presence, we analyzed the FBSE derivatives from the authentic standard, and the relative proportions of these derivatives contribute to approximately 0.5%. This suggests that the FBSE derivative series detected in wastewater may arise from byproducts of chemical formulations used in the manufacturing of semiconductors. Second, transformation products from FBSE during oxidation, including the first identified intermediate transformation compounds, perfluorobutane sulfonamido acetaldehyde and its hydrate, were discovered. Third, diverse reaction products are generated from the intricate processes of semiconductor manufacturing, which utilize strong acids, bases, and solvents under UV light or heated conditions. These processes include the formation of PFAS-related compounds through hydration, sulfonation, oxidation, and nitrification. This study revealed 25 isomeric PFAS, encompassing headgroup isomers and functional tail group isomers. These findings underscore the importance of comprehending diverse reactions and the overall emission compositions of PFAS in semiconductor wastewater, highlighting its complexity and presenting challenges for subsequent wastewater treatment.

14-3-3 Protein-Protein Interactions: From Mechanistic Understanding to Their Small-Molecule Stabilization.

Protein-protein interactions (PPIs) are of utmost importance for maintenance of cellular homeostasis. Herein, a central role can be found for 14-3-3 proteins. These hub-proteins are known to bind hundreds of interaction partners, thereby regulating their activity, localization, and/or stabilization. Due to their ability to bind a large variety of client proteins, studies of 14-3-3 protein complexes flourished over the last decades, aiming to gain greater molecular understanding of these complexes and their role in health and disease. Because of their crucial role within the cell, 14-3-3 protein complexes are recognized as highly interesting therapeutic targets, encouraging the discovery of small molecule modulators of these PPIs. We discuss various examples of 14-3-3-mediated regulation of its binding partners on a mechanistic level, highlighting the versatile and multi-functional role of 14-3-3 within the cell. Furthermore, an overview is given on the development of stabilizers of 14-3-3 protein complexes, from initially used natural products to fragment-based approaches. These studies show the potential of 14-3-3 PPI stabilizers as novel agents in drug discovery and as tool compounds to gain greater molecular understanding of the role of 14-3-3-based protein regulation.

Watermelon: setup and validation of an in silico fragment-based approach

We present a new computational approach, named Watermelon, designed for the development of pharmacophore models based on receptor structures. The methodology involves the sampling of potential hotspots for ligand interactions within a protein target’s binding site, utilising molecular fragments as probes. By employing docking and molecular dynamics (MD) simulations, the most significant interactions formed by these probes within distinct regions of the binding site are identified. These interactions are subsequently transformed into pharmacophore features that delineates key anchoring sites for potential ligands. The reliability of the approach was experimentally validated using the monoacylglycerol lipase (MAGL) enzyme. The generated pharmacophore model captured features representing ligand-MAGL interactions observed in various X-ray co-crystal structures and was employed to screen a database of commercially available compounds, in combination with consensus docking and MD simulations. The screening successfully identified two new MAGL inhibitors with micromolar potency, thus confirming the reliability of the Watermelon approach.

Correlation of protein binding pocket properties with hits’ chemistries used in generation of ultra-large virtual libraries

Although the size of virtual libraries of synthesizable compounds is growing rapidly, we are still enumerating only tiny fractions of the drug-like chemical universe. Our capability to mine these newly generated libraries also lags their growth. That is why fragment-based approaches that utilize on-demand virtual combinatorial libraries are gaining popularity in drug discovery. These à la carte libraries utilize synthetic blocks found to be effective binders in parts of target protein pockets and a variety of reliable chemistries to connect them. There is, however, no data on the potential impact of the chemistries used for making on-demand libraries on the hit rates during virtual screening. There are also no rules to guide in the selection of these synthetic methods for production of custom libraries. We have used the SAVI (Synthetically Accessible Virtual Inventory) library, constructed using 53 reliable reaction types (transforms), to evaluate the impact of these chemistries on docking hit rates for 40 well-characterized protein pockets. The data shows that the virtual hit rates differ significantly for different chemistries with cross coupling reactions such as Sonogashira, Suzuki–Miyaura, Hiyama and Liebeskind–Srogl coupling producing the highest hit rates. Virtual hit rates appear to depend not only on the property of the formed chemical bond but also on the diversity of available building blocks and the scope of the reaction. The data identifies reactions that deserve wider use through increasing the number of corresponding building blocks and suggests the reactions that are more effective for pockets with certain physical and hydrogen bond-forming properties.

Structure-Function Analysis of the Essential Mycobacterium tuberculosis P450 Drug Target, CYP121A1.

Cytochrome P450 CYP121A1 is a well-known drug target against Mycobacterium tuberculosis, the human pathogen that causes the deadly disease tuberculosis (TB). CYP121A1 is a unique P450 enzyme because it uses classical and non-classical P450 catalytic processes and has distinct structural features among P450s. However, a detailed investigation of CYP121A1 protein structures in terms of active site cavity dynamics and key amino acids interacting with bound ligands has yet to be undertaken. To address this research knowledge gap, 53 CYP121A1 crystal structures were investigated in this study. Critical amino acids required for CYP121A1's overall activity were identified and highlighted this enzyme's rigid architecture and substrate selectivity. The CYP121A1-fluconazole crystal structure revealed a novel azole drug-P450 binding mode in which azole heme coordination was facilitated by a water molecule. Fragment-based inhibitor approaches revealed that CYP121A1 can be inhibited by molecules that block the substrate channel or by directly interacting with the P450 heme. This study serves as a reference for the precise understanding of CYP121A1 interactions with different ligands and the structure-function analysis of P450 enzymes in general. Our findings provide critical information for the synthesis of more specific CYP121A1 inhibitors and their development as novel anti-TB drugs.

Discovery and development of macrocyclic peptide modulators of the cannabinoid 2 receptor

The cannabinoid type 2 receptor (CB2R), a G protein-coupled receptor, is an important regulator of immune cell function and a promising target to treat chronic inflammation and fibrosis. While CB2R is typically targeted by small molecules, including endo-, phyto-, and synthetic cannabinoids, peptides-owing to their size-may offer a different interaction space to facilitate differential interactions with the receptor. Here, we explore plant-derived cyclic cystine-knot peptides as ligands of the CB2R. Cyclotides are known for their exceptional biochemical stability. Recently, they gained attention as G protein-coupled receptor modulators and as templates for designing peptide ligands with improved pharmacokinetic properties over linear peptides. Cyclotide-based ligands for CB2R were profiled based on a peptide-enriched extract library comprising nine plants. Employing pharmacology-guided fractionation and peptidomics, we identified the cyclotide vodo-C1 from sweet violet (Viola odorata) as a full agonist of CB2R with an affinity (Ki) of 1μM and a potency (EC50) of 8μM. Leveraging deep learning networks, we verified the structural topology of vodo-C1 and modeled its molecular volume in comparison to the CB2R ligand binding pocket. In a fragment-based approach, we designed and characterized vodo-C1-based bicyclic peptides (vBCL1-4), aiming to reduce size and improve potency. Opposite to vodo-C1, the vBCL peptides lacked the ability to activate the receptor but acted as negative allosteric modulators or neutral antagonists of CB2R. This study introduces a macrocyclic peptide phytocannabinoid, which served as a template for the development of synthetic CB2R peptide modulators. These findings offer opportunities for future peptide-based probe and drug development at cannabinoid receptors.

Peptidic Compound as DNA Binding Agent: In Silico Fragment-based Design, Machine Learning, Molecular Modeling, Synthesis, and DNA Binding Evaluation.

Cancer remains a global burden, with increasing mortality rates. Current cancer treatments involve controlling the transcription of malignant DNA genes, either directly or indirectly. DNA exhibits various structural forms, including the G-quadruplex (G4), a secondary structure in guanine-rich regions. G4 plays a crucial role in cellular processes by regulating gene expression and telomerase function. Researchers have recently identified G4-stabilizing binding agents as promising anti-cancer compounds. Additionally, peptides have emerged as effective anticancer pharmaceuticals due to their ability to form multiple hydrogen bonds, electrostatic interactions, and van der Waals forces. These properties enable peptides to bind to specific areas of DNA chains selectively. However, despite these advancements, designing G4-binding peptides remains challenging due to a lack of comprehensive information. In our present study, we employed an in silico fragment-based approach to design G4- binding peptides. This innovative method combines machine learning classification, molecular docking, and dynamics simulation. AutoDock Vina and Gromacs performed molecular docking and MD simulation, respectively. The machine learning algorithm was implemented by Scikit-learn. Peptide synthesis was performed using the SPPS method. The DNA binding affinity was measured by applying spectrophotometric titration. As a result of this approach, we identified a high-scoring peptide (p10; sequence: YWRWR). The association constant (Ka) between p10 and the ctDNA double helix chain was 4.45 × 105 M-1. Molecular modeling studies revealed that p10 could form a stable complex with the G4 surface. The obtained Ka value of 4.45 × 105 M-1 indicates favorable interactions. Our findings highlight the role of machine learning and molecular modeling approaches in designing new G4-binding peptides. Further research in this field could lead to targeted treatments that exploit the unique properties of G4 structures.

HIPPO: HIstogram-based Pseudo-POtential for scoring protein-ssRNA fragment-based docking poses

BackgroundThe RNA-Recognition motif (RRM) is a protein domain that binds single-stranded RNA (ssRNA) and is present in as much as 2% of the human genome. Despite this important role in biology, RRM-ssRNA interactions are very challenging to study on the structural level because of the remarkable flexibility of ssRNA. In the absence of atomic-level experimental data, the only method able to predict the 3D structure of protein-ssRNA complexes with any degree of accuracy is ssRNA’TTRACT, an ssRNA fragment-based docking approach using ATTRACT. However, since ATTRACT parameters are not ssRNA-specific and were determined in 2010, there is substantial opportunity for enhancement.ResultsHere we present HIPPO, a composite RRM-ssRNA scoring potential derived analytically from contact frequencies in near-native versus non-native docking models. HIPPO consists of a consensus of four distinct potentials, each extracted from a distinct reference pool of protein-trinucleotide docking decoys. To score a docking pose with one potential, for each pair of RNA–protein coarse-grained bead types, each contact is awarded or penalised according to the relative frequencies of this contact distance range among the correct and incorrect poses of the reference pool. Validated on a fragment-based docking benchmark of 57 experimentally solved RRM-ssRNA complexes, HIPPO achieved a threefold or higher enrichment for half of the fragments, versus only a quarter with the ATTRACT scoring function. In particular, HIPPO drastically improved the chance of very high enrichment (12-fold or higher), a scenario where the incremental modelling of entire ssRNA chains from fragments becomes viable. However, for the latter result, more research is needed to make it directly practically applicable. Regardless, our approach already improves upon the state of the art in RRM-ssRNA modelling and is in principle extendable to other types of protein-nucleic acid interactions.

Abstract 7148: Small molecule inhibitor of FEN1 nuclease utilizing a novel metal-binding pharmacophore synergizes with inhibitors of USP1, PARP, PARG and ATR

Abstract Flap endonuclease 1 (FEN1) is a structure-specific metallonuclease that cleaves 5’ DNA flaps during replication and repair. FEN1 is an attractive target for development of anticancer therapeutics because it is overexpressed in many tumor types and has a large number of synthetic lethality partners including genes in Homologous Recombination (HR) pathway (Mengwasser et al., 2019; Guo et al., 2020). Utilizing fragment-based drug discovery approach we identified a novel metal-binding pharmacophore that binds to the two magnesium ions in the FEN1 active site. Further elaboration using fragment growth strategies resulted in highly potent and selective inhibitors. The current lead (BSM-1516) is ~65-fold more potent against FEN1 than its related enzyme Exonuclease 1 (Exo1) in biochemical assays (IC50 of 7 nM and 460 nM, respectively), an improvement of more than an order of magnitude in selectivity compared to earlier efforts. FEN1 target engagement in live cells was validated by cellular thermal shift assay (CETSA EC50 of 24 nM). Inhibition of FEN1 led to its increased association with chromatin in S-phase cells and recruitment of PARP1 enzyme. In clonogenic assay, BRCA2-deficient DLD1 cells were ~15-fold more sensitive to FEN1 inhibition than their isogenic BRCA2-wild-type counterparts (EC50 of 350 nM and 5 µM, respectively), confirming the increased susceptibility of HR deficient cancer cells to FEN1 inhibition. Treatment of BRCA2-deficient but not wild-type DLD1 cells with BSM-1516 resulted in cell cycle arrest and dose-dependent decrease of S-phase BrdU incorporation into DNA. Cell cycle arrest of BRCA2-deficient DLD1 cells was accompanied by DNA damage signaling and by accumulation of chromatin-bound RPA32, a marker of ssDNA. To explore synthetic lethal interactions of FEN1 with other DNA repair genes we performed FEN1-inhibitor-anchored CRISPR screen. This analysis revealed that in addition to HR pathway inactivation, genomic perturbations in EXO1, USP1 and PARP1 genes sensitized cells to FEN1 inhibition. Synergistic relationships of BSM-1516 and its combination potential were further explored in viability studies with a panel of DDR inhibitors (n=25) in BRCA2-proficient and deficient cell lines. Strong synergy was identified with multiple drug classes that included inhibitors of USP1 (KSQ-4279), PARP (Olaparib, Niraparib, Talazoparib, AZD5305), PARG (PDD 00017273) and ATR (AZD6738, VE-822, Elimusertib). In vitro ADME assays and in vivo PK studies showed that BSM-1516 has properties suitable for in vivo testing, either as a single agent or in combination with synergistic DDR inhibitors, an investigation that is currently underway. Citation Format: Jason Munguia, Sanjay Agarwalla, Elaine Guo, Dave Martin, Junhua Fan, Dave Lonergan, David Puerta, Zachary Zimmerman, Konstantin Taganov. Small molecule inhibitor of FEN1 nuclease utilizing a novel metal-binding pharmacophore synergizes with inhibitors of USP1, PARP, PARG and ATR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7148.

Fragment-based drug design of novel inhibitors targeting lipoprotein (a) kringle domain KIV-10-mediated cardiovascular disease.

Cardiovascular diseases (CVDs) are the leading cause of death globally, attributed to a complex etiology involving metabolic, genetic, and protein-related factors. Lipoprotein(a) (Lp(a)), identified as a genetic risk factor, exhibits elevated levels linked to an increased risk of cardiovascular diseases. The lipoprotein(a) kringle domains have recently been identified as a potential target for the treatment of CVDs, in this study we utilized a fragment-based drug design approach to design a novel, potent, and safe inhibitor for lipoprotein(a) kringle domain. With the use of fragment library (61,600 fragments) screening, combined with analyses such as MM/GBSA, molecular dynamics simulation (MD), and principal component analysis, we successfully identified molecules effective against the kringle domains of Lipoprotein(a). The hybridization process (Breed) of the best fragments generated a novel 249 hybrid molecules, among them 77 exhibiting superior binding affinity (≤ -7kcal/mol) compared to control AZ-02 (-6.9kcal/mol), Importantly, the top ten molecules displayed high similarity to the control AZ-02. Among the top ten molecules, BR1 exhibited the best docking energy (-11.85kcal/mol ), and higher stability within the protein LBS site, demonstrating the capability to counteract the pathophysiological effects of lipoprotein(a) [Lp(a)]. Additionally, principal component analysis (PCA) highlighted a similar trend of motion during the binding of BR1 and the control compound (AZ-02), limiting protein mobility and reducing conformational space. Moreover, ADMET analysis indicated favorable drug-like properties, with BR1 showing minimal violations of Lipinski's rules. Overall, the identified compounds hold promise as potential therapeutics, addressing a critical need in cardiovascular medicine. Further preclinical and clinical evaluations are needed to validate their efficacy and safety, potentially ushering in a new era of targeted therapies for CVDs.

Exploring Aqueous Coordination Chemistry of Highly Lewis Acidic Metals with Emerging Isotopes for Nuclear Medicine.

Nuclear medicine harnesses radioisotopes for the diagnosis and treatment of disease. While the isotopes 99mTc and 111In have enabled the clinical diagnosis of millions of patients over the past 3 decades, more recent clinical translation of numerous 68Ga/177Lu-based radiopharmaceuticals for diagnostic imaging and therapy underscores the clinical utility of metal-based radiopharmaceuticals in mainstream cancer treatment. In addition to such established radionuclides, advancements in radioisotope production have enabled the production of radionuclides with a broad range of half-lives and emission properties of interest for nuclear medicine. Chemical means to form kinetically inert, in vivo-compatible species that can be modified with disease-targeting vectors is imperative. This presents a challenge for radiosiotopes of elements where the aqueous chemistry is still underdeveloped and poorly understood. Here, we discuss our efforts to date in exploring the aqueous, radioactive coordination chemistry of highly Lewis acidic metal ions and how our discoveries apply to the diagnosis and treatment of cancer in preclinical models of disease. The scope of this Account includes approaches to aqueous coordination of to-date understudied highly Lewis acidic metal ions with radioisotopes of emerging interest and the modulation of well-understood coordination environments of radio-coordination complexes to induce metal-catalyzed reactivity for separation and pro-drug applications.First, we discuss the development of seven-coordinate, small-cavity macrocyclic chelator platform mpatcn/picaga as an exemplary case study, which forms robust complexes with 44Sc/47Sc isotopes. Due to the high chemical hardness and pronounced Lewis acidity of the Sc3+ ion, the displacement of ternary ligand H2O by 18/natF- can be achieved to form an inert Sc-18/natF bond. Corresponding coordination complex natSc-18F is in vivo compatible and forms a theranostic tetrad with corresponding 44Sc/47Sc, 177Lu complexes all exhibiting homologous biodistribution profiles. Another exceptionally hard, highly Lewis acidic ion with underdeveloped aqueous chemistry and emerging interest in nuclear medicine is 45Ti4+. To develop de novo approaches to the mononuclear chelation of this ion under aqueous conditions, we employed a fragment-based bidentate ligand screening approach which identified two leads. The screen successfully predicted the formation of [45Ti][Ti(TREN-CAM)], a Ti-triscatechol complex that exhibits remarkable in vivo stability. Furthermore, the fragment-based screen also identified approaches that enabled solid-phase separation of Ti4+ and Sc3+ of interest in streamlining the isotope production of 45Ti and accessing new ways to separate 44Ti/44Sc for the development of a long-lived generator system. In addition to establishing the inert chelation of Ti4+ and Sc3+, we introduce controlled, metal-induced reactivity of corresponding coordination complexes on macroscopic and radiotracer scales. Metal-mediated autolytic amide bond cleavage (MMAAC) enables the temperature-dependent release of high-molar-activity, ready-to-inject radiopharmaceuticals; cleavage is selectively triggered by coordinated trivalent Lewis acid nat/68Ga3+ or Sc3+. Following the scope of reactivity and mechanistic studies, we validated MMAAC for the synthesis of high-molar-activity radiopharmaceuticals to image molecular targets with low expression and metal-mediated prodrug hydrolysis in vivo.This Account summarizes how developing the aqueous coordination chemistry and tuning the chemical reactivity of metal ions with high Lewis acidity at the macroscopic and tracer scales directly apply to the radiopharmaceutical synthesis with clinical potential.

A fragment-based approach for computing the long-term visual evolution of historical maps

Cartography, as a strategic technology, is a historical marker. Maps are tightly connected to the cultural construction of the environment. The increasing availability of digital collections of historical map images provides an unprecedented opportunity to study large map corpora. Corpus linguistics has led to significant advances in understanding how languages change. Research on large map corpora could in turn significantly contribute to understanding cultural and historical changes. We develop a methodology for cartographic stylometry, with an approach inspired by structuralist linguistics, considering maps as visual language systems. As a case study, we focus on a corpus of 10,000 French and Swiss maps, published between 1600 and 1950. Our method is based on the fragmentation of the map image into elementary map units. A fully interpretable feature representation of these units is computed by contrasting maps from different, coherent cartographic series, based on a set of candidate visual features (texture, morphology, graphical load). The resulting representation effectively distinguishes between map series, enabling the elementary units to be grouped into types, whose distribution can be examined over 350 years. The results show that the analyzed maps underwent a steady abstraction process during the 17th and 18th centuries. The 19th century brought a lasting scission between small- and large-scale maps. Macroscopic trends are also highlighted, such as a surge in the production of fine lines, and an increase in map load, that reveal cultural fashion processes and shifts in mapping practices. This initial research demonstrates how cartographic stylometry can be used for exploratory research on visual languages and cultural evolution in large map corpora, opening an effective dialogue with the history of cartography. It also deepens the understanding of cartography by revealing macroscopic phenomena over the long term.