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Simple Summary: Non-small cell lung cancer (NSCLC) is marked by low survival and resistance to platinum-based chemotherapy. Recent studies have emphasized the critical role of DNA repair mechanisms in NSCLC tumorigenesis and response to treatment. XPG endonuclease, a crucial component of the Nucleotide Excision Repair (NER) pathway, has emerged as a promising biomarker of clinical outcome in advanced NSCLC and its downregulation improved cisplatin efficacy by increasing DNA damage. However, so far, no study has been carried out with the purpose of identifying XPG inhibitors. This work thus aims to discover potential small-molecule inhibitors of XPG to be used in combination with cisplatin therapy to enhance its efficacy in NSCLC patients. NSCLC is marked by low survival and resistance to platinum-based chemotherapy. The XPG endonuclease has emerged as a promising biomarker for predicting the prognosis of cisplatin-treated patients and its downregulation having been reported to increase cisplatin efficacy. This study presents an integrated strategy for identifying small molecule inhibitors of XPG to improve cisplatin therapy in NSCLC. A structure-based virtual screening approach was adopted, including a structural and physicochemical analysis of the protein, and a library of small molecules with reported inhibitory activities was retrieved. This analysis identified Lys84 as a crucial residue for XPG activity by targeting its interaction with DNA. After molecular docking and virtual screening calculations, 61 small molecules were selected as potential XPG inhibitors, acquired from the ChemBridge database and then validated in H1299 cells, a NSCLC cell line exhibiting the highest ERCC5 expression. The MTS assay was performed as a first screening approach to determine whether these potential inhibitors could enhance cisplatin-induced cytotoxicity. Overall, among the eight compounds identified as the most promising, three of them revealed to significantly increase the impact of cisplatin. The inherent cytotoxicity of these compounds was further investigated in a non-tumoral lung cell line (BEAS-2B cells), which resulted in the identification of two non-cytotoxic candidates to be used in combination with cisplatin in order to improve its efficacy in NSCLC therapy. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) continues to be a major global health challenge and a leading cause of death from infectious diseases. Inspired by the results from a previous work by our group on antimycobacterial N-alkylnitrobenzamides, which are structurally related to the nitrobenzamide family of decaprenylphosphoryl-β-d-ribose oxidase (DprE1) inhibitors, the present study explored a broad array of substituted benzamides. We particularly focused on previously unexplored 3,5-dinitrobenzamide derivatives. Starting with 3,5-dinitrobenzoic acid, we synthesized a diverse library of amides, incorporating both linear and cyclic amine moieties and also assessed the impact of terminal aromatic groups connected through ether, ester, or amide bonds on the bioactivity of the compounds. The synthesis primarily utilized nucleophilic addition/elimination, SN2, and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of linker. The most interesting compounds (c2, d1, and d2, MIC = 0.031 μg/mL) exhibited activities against Mycobacterium Tuberculosis (Mtb) H37Rv comparable to isoniazid. Complementary computational studies helped elucidate potential interactions with DprE1, enhancing our understanding of the molecular basis of their action. Our findings suggest that the most active compounds provide a promising foundation for the continued development of new antimycobacterial agents. [ABSTRACT FROM AUTHOR]

Modifications in DNA repair pathways are recognized as prognostic markers and potential therapeutic targets in various cancers, including non-small cell lung cancer (NSCLC). Overexpression of ERCC1 correlates with poorer prognosis and response to platinum-based chemotherapy. As a result, there is a pressing need to discover new inhibitors of the ERCC1–XPF complex that can potentiate the efficacy of cisplatin in NSCLC. In this study, we developed a structure-based virtual screening strategy targeting the inhibition of ERCC1 and XPF interaction. Analysis of crystal structures and a library of small molecules known to act against the complex highlighted the pivotal role of Phe293 (ERCC1) in maintaining complex stability. This residue was chosen as the primary binding site for virtual screening. Using an optimized docking protocol, we screened compounds from various databases, ultimately identifying more than one hundred potential inhibitors. Their capability to amplify cisplatin-induced cytotoxicity was assessed in NSCLC H1299 cells, which exhibited the highest ERCC1 expression of all the cell lines tested. Of these, 22 compounds emerged as promising enhancers of cisplatin efficacy. Our results underscore the value of pinpointing crucial molecular characteristics in the pursuit of novel modulators of the ERCC1–XPF interaction, which could be combined with cisplatin to treat NSCLC more effectively. [ABSTRACT FROM AUTHOR]

Cancer is a complex multifactorial disease whose pathophysiology involves multiple metabolic pathways, including the ubiquitin–proteasome system, for which several proteasome inhibitors have already been approved for clinical use. However, the resistance to existing therapies and the occurrence of severe adverse effects is still a concern. The purpose of this study was the discovery of novel scaffolds of proteasome inhibitors with anticancer activity, aiming to overcome the limitations of the existing proteasome inhibitors. Thus, a structure-based virtual screening protocol was developed using the structure of the human 20S proteasome, and 246 compounds from virtual databases were selected for in vitro evaluation, namely proteasome inhibition assays and cell viability assays. Compound 4 (JHG58) was shortlisted as the best hit compound based on its potential in terms of proteasome inhibitory activity and its ability to induce cell death (both with IC50 values in the low micromolar range). Molecular docking studies revealed that compound 4 interacts with key residues, namely with the catalytic Thr1, Ala20, Thr21, Lys33, and Asp125 at the chymotrypsin-like catalytic active site. The hit compound is a good candidate for additional optimization through a hit-to-lead campaign. [ABSTRACT FROM AUTHOR]

Urease is a metalloenzyme that catalyzes the hydrolysis of urea, and its modulation has an important role in both the agricultural and medical industry. Even though numerous molecules have been tested against ureases of different species, their clinical translation has been limited due to chemical and metabolic stability as well as side effects. Therefore, screening new compounds against urease would be of interest in part due to rising concerns regarding antibiotic resistance. In this work, we collected and curated a diverse set of 2640 publicly available small-molecule inhibitors of jack bean urease and developed a classifier using a random forest machine learning method with high predictive performance. In addition, the physicochemical features of compounds were paired with molecular docking and protein–ligand fingerprint analysis to gather insight into the current activity landscape. We observed that the docking score could not differentiate active from inactive compounds within each chemical family, but scores were correlated with compound activity when all compounds were considered. Additionally, a decision tree model was built based on 2D and 3D Morgan fingerprints to mine patterns of the known active-class compounds. The final machine learning model showed good prediction performance against the test set (81% and 77% precision for active and inactive compounds, respectively). Finally, this model was employed, as a proof-of-concept, on an in-house library to predict new hits that were then tested against urease and found to be active. This is, to date, the largest, most diverse dataset of compounds used to develop predictive in silico models. Overall, the results highlight the usefulness of using machine learning classifiers and molecular docking to predict novel urease inhibitors. [ABSTRACT FROM AUTHOR]

Seaweeds are a great source of compounds with cytotoxic properties with the potential to be used as anticancer agents. This study evaluated the cytotoxic and proteasome inhibitory activities of 12R-hydroxy-bromosphaerol, 12S-hydroxy-bromosphaerol, and bromosphaerol isolated from Sphaerococcus coronopifolius. The cytotoxicity was evaluated on malignant cell lines (A549, CACO-2, HCT-15, MCF-7, NCI-H226, PC-3, SH-SY5Y, and SK-MEL-28) using the MTT and LDH assays. The ability of compounds to stimulate the production of hydrogen peroxide (H2O2) and to induce mitochondrial dysfunction, the externalization of phosphatidylserine, Caspase-9 activity, and changes in nuclear morphology was also studied on MCF-7 cells. The ability to induce DNA damage was also studied on L929 fibroblasts. The proteasome inhibitory activity was estimated through molecular docking studies. The compounds exhibited IC50 values between 15.35 and 53.34 µM. 12R-hydroxy-bromosphaerol and 12S-hydroxy-bromosphaerol increased the H2O2 levels on MCF-7 cells, and bromosphaerol induced DNA damage on fibroblasts. All compounds promoted a depolarization of mitochondrial membrane potential, Caspase-9 activity, and nuclear condensation and fragmentation. The compounds have been shown to interact with the chymotrypsin-like catalytic site through molecular docking studies; however, only 12S-hydroxy-bromosphaerol evidenced interaction with ALA20 and SER169, key residues of the proteasome catalytic mechanism. Further studies should be outlined to deeply characterize and understand the potential of those bromoditerpenes for anticancer therapeutics. [ABSTRACT FROM AUTHOR]

Necroptosis has emerged as an exciting target in oncological, inflammatory, neurodegenerative, and autoimmune diseases, in addition to acute ischemic injuries. It is known to play a role in innate immune response, as well as in antiviral cellular response. Here we devised a concerted in silico and experimental framework to identify novel RIPK1 inhibitors, a key necroptosis factor. We propose the first in silico model for the prediction of new RIPK1 inhibitor scaffolds by combining docking and machine learning methodologies. Through the data analysis of patterns in docking results, we derived two rules, where rule #1 consisted of a four-residue signature filter, and rule #2 consisted of a six-residue similarity filter based on docking calculations. These were used in consensus with a machine learning QSAR model from data collated from ChEMBL, the literature, in patents, and from PubChem data. The models allowed for good prediction of actives of >90, 92, and 96.4% precision, respectively. As a proof-of-concept, we selected 50 compounds from the ChemBridge database, using a consensus of both molecular docking and machine learning methods, and tested them in a phenotypic necroptosis assay and a biochemical RIPK1 inhibition assay. A total of 7 of the 47 tested compounds demonstrated around 20–25% inhibition of RIPK1's kinase activity but, more importantly, these compounds were discovered to occupy new areas of chemical space. Although no strong actives were found, they could be candidates for further optimization, particularly because they have new scaffolds. In conclusion, this screening method may prove valuable for future screening efforts as it allows for the exploration of new areas of the chemical space in a very fast and inexpensive manner, therefore providing efficient starting points amenable to further hit-optimization campaigns. [ABSTRACT FROM AUTHOR]

Simple Summary: Treatment of glioblastoma is hampered by the activation of compensatory survival mechanisms by malignant cells that lead to drug resistance. Moreover, the blood–brain barrier (BBB) precludes the brain entrance of most drugs. We hypothesized that computer-assisted drug discovery tools would reveal novel multi-targeting drug candidates with BBB-permeant and favorable ADMET properties. We aimed to discover molecules with predicted ability to inhibit the EGFR/PI3Kp110β pathway and to validate their efficacy and safety in biological assays. We used quantitative structure–activity relationship models and structure-based virtual screening, and assessed ADMET properties, to identify BBB-permeant drug candidates. Moreover, we tested their anti-tumor efficacy and BBB safety and permeation in cell models. We found two EGFR, two PI3Kp110β, and, mostly, two dual inhibitors with anti-tumor effects. Among them, one EGFR and two PI3Kp110β inhibitors were able to cross the BBB endothelium without compromising it. These studies revealed novel drug candidates for glioblastoma treatment. The epidermal growth factor receptor (EGFR) is upregulated in glioblastoma, becoming an attractive therapeutic target. However, activation of compensatory pathways generates inputs to downstream PI3Kp110β signaling, leading to anti-EGFR therapeutic resistance. Moreover, the blood–brain barrier (BBB) limits drugs' brain penetration. We aimed to discover EGFR/PI3Kp110β pathway inhibitors for a multi-targeting approach, with favorable ADMET and BBB-permeant properties. We used quantitative structure–activity relationship models and structure-based virtual screening, and assessed ADMET properties, to identify BBB-permeant drug candidates. Predictions were validated in in vitro models of the human BBB and BBB-glioma co-cultures. The results disclosed 27 molecules (18 EGFR, 6 PI3Kp110β, and 3 dual inhibitors) for biological validation, performed in two glioblastoma cell lines (U87MG and U87MG overexpressing EGFR). Six molecules (two EGFR, two PI3Kp110β, and two dual inhibitors) decreased cell viability by 40–99%, with the greatest effect observed for the dual inhibitors. The glioma cytotoxicity was confirmed by analysis of targets' downregulation and increased apoptosis (15–85%). Safety to BBB endothelial cells was confirmed for three of those molecules (one EGFR and two PI3Kp110β inhibitors). These molecules crossed the endothelial monolayer in the BBB in vitro model and in the BBB-glioblastoma co-culture system. These results revealed novel drug candidates for glioblastoma treatment. [ABSTRACT FROM AUTHOR]

Proteasome inhibitors have shown relevant clinical activity in several hematological malignancies, namely in multiple myeloma and mantle cell lymphoma, improving patient outcomes such as survival and quality of life, when compared with other therapies. However, initial response to the therapy is a challenge as most patients show an innate resistance to proteasome inhibitors, and those that respond to the therapy usually develop late relapses suggesting the development of acquired resistance. The mechanisms of resistance to proteasome inhibition are still controversial and scarce in the literature. In this review, we discuss the development of proteasome inhibitors and the mechanisms of innate and acquired resistance to their activity—a major challenge in preclinical and clinical therapeutics. An improved understanding of these mechanisms is crucial to guiding the design of new and more effective drugs to tackle these devastating diseases. In addition, we provide a comprehensive overview of proteasome inhibitors used in combination with other chemotherapeutic agents, as this is a key strategy to combat resistance. [ABSTRACT FROM AUTHOR]

Proteasome emerged as an important target in recent pharmacological research due to its pivotal role in degrading proteins in the cytoplasm and nucleus of eukaryotic cells, regulating a wide variety of cellular pathways, including cell growth and proliferation, apoptosis, DNA repair, transcription, immune response, and signaling processes. The last two decades witnessed intensive efforts to discover 20S proteasome inhibitors with significant chemical diversity and efficacy. To date, the US FDA approved to market three proteasome inhibitors: bortezomib, carfilzomib, and ixazomib. However new, safer and more efficient drugs are still required. Computer-aided drug discovery has long being used in drug discovery campaigns targeting the human proteasome. The aim of this review is to illustrate selected in silico methods like homology modeling, molecular docking, pharmacophore modeling, virtual screening, and combined methods that have been used in proteasome inhibitors discovery. Applications of these methods to proteasome inhibitors discovery will also be presented and discussed to raise improvements in this particular field. [ABSTRACT FROM AUTHOR]

Glycogen phosphorylase (GP) is a key enzyme in the glycogenolysis pathway. GP inhibitors are currently under investigation as a new liver-targeted approach to managing type 2 diabetes mellitus (DM). The aim of the present study was to evaluate the inhibitory activity of a panel of 52 structurally related chromone derivatives; namely, flavonoids, 2-styrylchromones, 2-styrylchromone-related derivatives [2-(4-arylbuta-1,3-dien-1-yl)chromones], and 4- and 5-styrylpyrazoles against GP, using in silico and in vitro microanalysis screening systems. Several of the tested compounds showed a potent inhibitory effect. The structure–activity relationship study indicated that for 2-styrylchromones and 2-styrylchromone-related derivatives, the hydroxylations at the A and B rings, and in the flavonoid family, as well as the hydroxylation of the A ring, were determinants for the inhibitory activity. To support the in vitro experimental findings, molecular docking studies were performed, revealing clear hydrogen bonding patterns that favored the inhibitory effects of flavonoids, 2-styrylchromones, and 2-styrylchromone-related derivatives. Interestingly, the potency of the most active compounds increased almost four-fold when the concentration of glucose increased, presenting an IC50 < 10 µM. This effect may reduce the risk of hypoglycemia, a commonly reported side effect of antidiabetic agents. This work contributes with important considerations and provides a better understanding of potential scaffolds for the study of novel GP inhibitors. [ABSTRACT FROM AUTHOR]

Multiple myeloma is an incurable plasma cell neoplastic disease representing about 10–15% of all haematological malignancies diagnosed in developed countries. Proteasome is a key player in multiple myeloma and proteasome inhibitors are the current first-line of treatment. However, these are associated with limited clinical efficacy due to acquired resistance. One of the solutions to overcome this problem is a polypharmacology approach, namely combination therapy and multitargeting drugs. Several polypharmacology avenues are currently being explored. The simultaneous inhibition of EZH2 and Proteasome 20S remains to be investigated, despite the encouraging evidence of therapeutic synergy between the two. Therefore, we sought to bridge this gap by proposing a holistic in silico strategy to find new dual-target inhibitors. First, we assessed the characteristics of both pockets and compared the chemical space of EZH2 and Proteasome 20S inhibitors, to establish the feasibility of dual targeting. This was followed by molecular docking calculations performed on EZH2 and Proteasome 20S inhibitors from ChEMBL 25, from which we derived a predictive model to propose new EZH2 inhibitors among Proteasome 20S compounds, and vice versa, which yielded two dual-inhibitor hits. Complementarily, we built a machine learning QSAR model for each target but realised their application to our data is very limited as each dataset occupies a different region of chemical space. We finally proceeded with molecular dynamics simulations of the two docking hits against the two targets. Overall, we concluded that one of the hit compounds is particularly promising as a dual-inhibitor candidate exhibiting extensive hydrogen bonding with both targets. Furthermore, this work serves as a framework for how to rationally approach a dual-targeting drug discovery project, from the selection of the targets to the prediction of new hit compounds. [ABSTRACT FROM AUTHOR]

A pharmacophore model for inhibitors of Escherichia coli's DNA Gyrase B was developed, using computer-aided drug design. Subsequently, docking studies showed that 2,5(6)-substituted benzimidazole derivatives are promising molecules, as they possess key hydrogen bond donor/acceptor groups for an efficient interaction with this bacterial target. Furthermore, 5(6)-bromo-2-(2-nitrophenyl)-1H-benzimidazole, selected as a core molecule, was prepared on a multi-gram scale through condensation of 4-bromo-1,2-diaminobenzene with 2-nitrobenzaldehyde using a sustainable approach. The challenging functionalization of the 5(6)-position was carried out via palladium-catalyzed Suzuki–Miyaura and Buchwald-Hartwig amination cross-coupling reactions between N-protected-5-bromo-2-nitrophenyl-benzimidazole and aryl boronic acids or sulfonylanilines, with yields up to 81%. The final designed molecules (2-(aminophen-2-yl)-5(6)-substituted-1H-benzimidazoles), which encompass the appropriate functional groups in the 5(6)-position according to the pharmacophore model, were obtained in yields up to 91% after acid-mediated N-boc deprotection followed by Pd-catalyzed hydrogenation. These groups are predicted to favor interactions with DNA gyrase B residues Asn46, Asp73, and Asp173, aiming to promote an inhibitory effect. [ABSTRACT FROM AUTHOR]

Phenylketonuria (PKU) is a genetic disease caused by deficient activity of human phenylalanine hydroxylase (hPAH) that, when untreated, can lead to severe psychomotor impairment. Protein misfolding is recognized as the main underlying pathogenic mechanism of PKU. Therefore, the use of stabilizers of protein structure and/or activity is an attractive therapeutic strategy for this condition. Here, we report that 3-hydroxyquinolin-2(1H)-one derivatives can act as protectors of hPAH enzyme activity. Electron paramagnetic resonance spectroscopy demonstrated that the 3-hydroxyquinolin-2(1H)-one compounds affect the coordination of the non-heme ferric center at the enzyme active-site. Moreover, surface plasmon resonance studies showed that these stabilizing compounds can be outcompeted by the natural substrate l-phenylalanine. Two of the designed compounds functionally stabilized hPAH by maintaining protein activity. This effect was observed on the recombinant purified protein and in a cellular model. Besides interacting with the catalytic iron, one of the compounds also binds to the N-terminal regulatory domain, although to a different location from the allosteric l-Phe binding site, as supported by the solution structures obtained by small-angle X-ray scattering. [ABSTRACT FROM AUTHOR]

HIV-2 infection is frequently neglected in HIV/AIDS campaigns. However, a special emphasis must be given to HIV-2 as an untreated infection that also leads to AIDS and death, and for which the efficacy of most available drugs is limited against HIV-2. HIV envelope glycoproteins mediate binding to the receptor CD4 and co-receptors at the surface of the target cell, enabling fusion with the cell membrane and viral entry. Here, we developed and optimized a computer-assisted drug design approach of an important HIV-2 glycoprotein that allows us to explore and gain further insights at the molecular level into protein structures and interactions crucial for the inhibition of HIV-2 cell entry. The 3D structure of a key HIV-2ROD gp125 region was generated by a homology modeling campaign. To disclose the importance of the main structural features and compare them with experimental results, 3D-models of six mutants were also generated. These mutations revealed the selective impact on the behavior of the protein. Furthermore, molecular dynamics simulations were performed to optimize the models, and the dynamic behavior was tackled to account for structure flexibility and interactions network formation. Structurally, the mutations studied lead to a loss of aromatic features, which is very important for the establishment of π-π interactions and could induce a structural preference by a specific coreceptor. These new insights into the structure-function relationship of HIV-2 gp125 V3 and surrounding regions will help in the design of better models and the design of new small molecules capable to inhibit the attachment and binding of HIV with host cells. [ABSTRACT FROM AUTHOR]

Lipoaminoacids (LAA) are an important group of biosurfactants, formed by a polar hydrophilic part (amino acid) and a hydrophobic tail (lipid). The gemini LAA structures allow the formation of a supramolecular complex with bioactive molecules, like DNA, which provides them with good transfection efficiency. Since lipases are naturally involved in lipid and protein metabolism, they are an alternative to the chemical production of LAA, offering an eco-friendly biosynthetic process option. This work aimed to design the production of novel cystine derived gemini through a bioconversion system using immobilized lipases. Three lipases were used: porcine pancreatic lipase (PPL); lipase from Thermomyces lanuginosus (TLL); and lipase from Rizhomucor miehei (RML). PPL was immobilized in sol-gel lenses. L-cystine dihydrochloride and dodecylamine were used as substrates for the bioreaction. The production of LAA was evaluated by thin layer chromatography (TLC), and colorimetric reaction with eosin. The identification and quantification was carried out by High Performance Liquid Chromatographer-Mass Spectrometry (HPLC-MS/MS). The optimization of media design included co-solvent (methanol, dimethylsulfoxide), biphasic (n-hexane and 2-propanol) or solvent-free media, in order to improve the biocatalytic reaction rates and yields. Moreover, a new medium was tested where dodecylamine was melted and added to the cystine and to the biocatalyst, building a system of mainly undissolved substrates, leading to 5 mg/mL of LAA. Most of the volume turned into foam, which indicated the production of the biosurfactant. For the first time, the gemini derived cystine lipoaminoacid was produced, identified, and quantified in both co-solvent and solvent-free media, with the lipases PPL, RML, and TLL. [ABSTRACT FROM AUTHOR]

Drug discovery now faces a new challenge, where the availability of experimental data is no longer the limiting step, and instead, making sense of the data has gained a new level of importance, propelled by the extensive incorporation of cheminformatics and bioinformatics methodologies into the drug discovery and development pipeline. These enable, for example, the inference of structure-activity relationships that can be useful in the discovery of new drug candidates. One of the therapeutic applications that could benefit from this type of data mining is proteasome inhibition, given that multiple compounds have been designed and tested for the last 20 years, and this collection of data is yet to be subjected to such type of assessment. This study presents a retrospective overview of two decades of proteasome inhibitors development (680 compounds), in order to gather what could be learned from them and apply this knowledge to any future drug discovery on this subject. Our analysis focused on how different chemical descriptors coupled with statistical tools can be used to extract interesting patterns of activity. Multiple instances of the structure-activity relationship were observed in this dataset, either for isolated molecular descriptors (e.g., molecular refractivity and topological polar surface area) as well as scaffold similarity or chemical space overlap. Building a decision tree allowed the identification of two meaningful decision rules that describe the chemical parameters associated with high activity. Additionally, a characterization of the prevalence of key functional groups gives insight into global patterns followed in drug discovery projects, and highlights some systematically underexplored parts of the chemical space. The various chemical patterns identified provided useful insight that can be applied in future drug discovery projects, and give an overview of what has been done so far. [ABSTRACT FROM AUTHOR]

The role of metalloproteinases (MMPs) on the migration and invasion of cancer cells has been correlated with tumor aggressiveness, namely with the up-regulation of MMP-2 and 9. Herein, two pyridine-containing macrocyclic compounds, [15]pyN5 and [16]pyN5, were synthesized, chemically characterized and evaluated as potential MMP inhibitors for breast cancer therapy using 3D and 2D cellular models. [15]pyN5 and [16]pyN5 (5–20 µM) showed a marked inhibition of MMPs activity (100% at concentrations ≥ 7.5 μM) when compared to ARP-100, a known MMP inhibitor. The inhibitory activity of [15]pyN5 and [16]pyN5 was further supported through in silico docking studies using Goldscore and ChemPLP scoring functions. Moreover, although no significant differences were observed in the invasion studies in the presence of all MMPs inhibitors, cell migration was significantly inhibited by both pyridine-containing macrocycles at concentrations above 5 μM in 2D cells (p < 0.05). In spheroids, the same effect was observed, but only with [16]pyN5 at 20 μM and ARP-100 at 40 μM. Overall, [15]pyN5 and [16]pyN5 led to impaired breast cancer cell migration and revealed to be potential inhibitors of MMPs 2 and 9. [ABSTRACT FROM AUTHOR]