Molecules

Drug discovery starts with known function, either of a compound or a protein, in-turn prompting investigations to probe 3D structure of the compound-protein interface. As protein structure determines function, we hypothesized that unique 3D structural motifs represent primary information denoting unique function that can drive discovery of novel agents. Using a physics-based protein structure analysis platform developed by us, designed to conduct computationally intensive analysis at supercomputing speeds, we probed a high-resolution protein x-ray crystallographic library developed by us. We selected 3D structural motifs whose function was not otherwise established, that offered environments supporting binding of drug-like chemicals and were present on proteins that were not established therapeutic targets. For each of eight potential binding pockets on six different proteins we accessed a 60 million compound library and used our analysis platform to evaluate binding. Using eight-day colony formation assays acquired compounds were screened for efficacy against human breast, prostate, colon and lung cancer cells and toxicity against human bone marrow stem cells. Compounds selectively inhibiting cancer growth segregated to two pockets on separate proteins. The compound, Dxr2-017, exhibited selective activity against human melanoma cells in the NCI-60 cell line screen, had an IC50 of 19 nM against human melanoma M14 cells in our eight-day assay, while over 2100-fold higher concentrations inhibited stem cells by less than 30%. We show that Dxr2-017 induces anoikis, a unique form of programmed cell death in need of targeted therapeutics. The predicted target protein for Dxr2-017 is expressed in bacteria, not in humans. This supports our strategy of focusing on unique 3D structural motifs. It is known that functionally important 3D structures are evolutionarily conserved. Here we demonstrate proof-of-concept that protein structure represents high value primary data to support discovery of novel therapeutics. This approach is widely applicable. Author summaryWe introduce the concept that protein 3D structure represents primary information which can support downstream investigations, in this instance leading to the discovery of novel anticancer therapeutics.

Overexpression of the polyspecific efflux transporter, P-glycoprotein (P-gp, MDR1, ABCB1), is a major mechanism by which cancer cells acquire multidrug resistance (MDR), the resistance to diverse chemotherapeutic drugs. Inhibiting drug transport by P-gp can resensitize cancer cells to chemotherapy, but there are no P-gp inhibitors available to patients. Clinically unsuccessful P-gp inhibitors tend to bind at the pumps transmembrane drug binding domains and are often P-gp transport substrates, resulting in lowered intracellular concentration of the drug and altered pharmacokinetics. In prior work, we used computationally accelerated drug discovery to identify novel P-gp inhibitors that target the pumps cytoplasmic nucleotide binding domains. Our first-draft study provided conclusive evidence that the nucleotide binding domains of P-gp are viable targets for drug discovery. Here we develop an enhanced, computationally accelerated drug discovery pipeline that expands upon our prior work by iteratively screening compounds against multiple conformations of P-gp with molecular docking. Targeted molecular dynamics simulations with our homology model of human P-gp were used to generate docking receptors in conformations mimicking a putative drug transport cycle. We offset the increased computational complexity using custom Tanimoto chemical datasets, which maximize the chemical diversity of ligands screened by docking. Using our expanded, virtual-assisted pipeline, we identified nine novel P-gp inhibitors that reverse MDR in two types of P-gp overexpressing human cancer cell lines, reflecting a 13.4% hit rate. Of these inhibitors, all were non-toxic to non-cancerous human cells, and six were not likely to be transport substrates of P-gp. Our novel P-gp inhibitors are chemically diverse and are good candidates for lead optimization. Our results demonstrate that the nucleotide binding domains of P-gp are an underappreciated target in the effort to reverse P-gp-mediated multidrug resistance in cancer.

The homeostasis of eukaryotic cells is inseverable of that of the endoplasmic reticulum (ER). The main function of this organelle is the synthesis and folding of a significant portion of cellular proteins, while also being the major calcium reservoir of the cell. Upon unresolved ER stress, a set of stress response signaling pathways that are collectively labeled as the unfolded protein response (UPR) is activated. Prolonged or intense activation of this molecular machinery may be deleterious. It is known that compromised ER homeostasis, and consequent UPR activation, characterize the pathogenesis of neurodegenerative disease. In an effort to discover new small molecules capable of countering ER stress, we subjected a panel of over 100 natural molecules to a battery of assays designed to evaluate several hallmarks of ER stress. The effect of the compounds on calcium homeostasis, key gene and protein expression, and levels of protein aggregation were evaluated in fibroblasts, and subsequently in neuronal cells. This framework resulted in the identification of several bioactive molecules capable of countering ER stress and deleterious events associated to it, among which delphinidin stands out as the most promising candidate against neurodegeneration.

IF1 protein inhibits F1F0 ATP hydrolysis (and not F1F0 ATP synthesis). Across investigated species more IF1 protein, and less F1F0 ATP hydrolysis, correlates with greater maximal lifespan. Increased IF1 protein, and decreased F1F0 ATP hydrolysis, safely reduces a biomarker of aging in mice. Body temperature decrease, in mice administered with a small molecule drug that selectively inhibits F1F0 ATP hydrolysis (which doesnt inhibit F1F0 ATP synthesis), is evidence that F1F0 ATP hydrolysis is used for metabolic heat generation in vivo. Instrumental to homeothermy, which is a new fundamental discovery. A further discovery is that cancer cells subvert F1F0 ATP hydrolysis to drive their distinctive Warburg metabolism and so selective drug inhibition of F1F0 ATP hydrolysis exerts potent anticancer activity. When the body is in an ambient temperature of 37{degrees}C (or more), no metabolic heat generation is needed for the body to be at 37{degrees}C, and so a large dose of a F1F0 ATP hydrolysis inhibiting anticancer drug may be administered, which may slow aging. So, here might be an entirely new class of anticancer drugs that may (when appropriately used) help, instead of harm, normal cells. Distinct from present anticancer drugs, which greatly harm normal cells, causing horrific side-effects, which kill many and cause many others to abandon cancer treatment. In short, this paper teaches how mammals metabolically generate heat, why different mammal species have different maximal lifespans, and new anticancer drugs, that are predicted to slow aging. SIGNIFICANCEHas nature taught us how to slow aging? Different mammal species age at different rates, conferring different maximal lifespans. For example, the maximal lifespan of a mouse is 4 years, while that of a bowhead whale is 211 years. So, aging is modifiable. But how? A clue might be body size: smaller mammal species tend to age faster than larger ones. In geometry, by its square-cube law, smaller objects have a greater surface-area to volume ratio than larger objects. Meaning smaller mammal species more readily lose their metabolically generated heat. And so, per unit time, each gram of a smaller mammal species needs to generate more metabolic heat than each gram of a larger mammal species, to keep their body temperature around 37{degrees}C. The chemical reactions that the body uses to obtain energy from food (e.g., to keep the body warm) produce harmful by-products: Reactive Oxygen Species (ROS), which cause molecular damage. The accumulation of which might be aging. Per unit time, each gram of a smaller mammal species generates more metabolic heat, uses more food, produces more ROS, and ages more. Newly reported herein is a chemical reaction that homeotherms use to generate heat (F1F0 ATP hydrolysis). By the 2nd Law of Thermodynamics, whenever energy converts from one form to another, some of this energy must be dissipated as heat (no energy conversion can be 100% efficient). Ive discovered, in homeotherms, ATP synthase enzyme hydrolyses some of the ATP it synthesizes (i.e., performs F1F0 ATP hydrolysis). Causing futile cycling between ATP synthesis and ATP hydrolysis, conditional upon passing and pumping protons along a concentration gradient respectively. So, cyclically interconverting between potential and chemical energies, which (by the inefficiency of energy conversions) generates heat to maintain body temperature. Across a set of mammal species: per unit time, each gram of smaller (shorter-living) mammal species do more of this heat generating reaction (F1F0 ATP hydrolysis) than each gram of larger (longer-living) mammal species. Because they have less IF1 protein (activity per unit mass), where IF1 protein selectively inhibits F1F0 ATP hydrolysis (doesnt inhibit F1F0 ATP synthesis). Across these mammal species, maximal lifespan is inversely proportional to the use (per unit time per unit mass) of F1F0 ATP hydrolysis. That drives the inverse proportionality between metabolic rate per unit mass and maximal lifespan, which causes the inverse proportionality between heart rate and maximal lifespan, observed across these mammal species. Increased IF1 protein, and decreased F1F0 ATP hydrolysis, safely reduces a biomarker of aging in mice. So, correlational and interventional data. My interpretation of data herein is that different mammal species have different maximal lifespans because of different IF1 protein activity (per unit mass). Where more IF1 protein activity (per unit mass) confers longer lifespan. A small-molecule drug that selectively inhibits F1F0 ATP hydrolysis, which doesnt inhibit F1F0 ATP synthesis, is shown to dose-dependently reduce metabolic heat generation (and metabolic rate thereby) in mice. Higher dose reduces it more. Such a drug is predicted to slow aging. Indeed, its mechanism of action (selectively inhibiting F1F0 ATP hydrolysis) is shown to safely decrease intracellular ROS concentration in mice. Less metabolic heat generation doesnt necessarily mean lower body temperature. Body temperature can be the same with less metabolic heat generation by proportionally greater body insulation, such as wearing more or better clothing, and/or a conducive ambient temperature. A human, in typical clothing, is most comfortable at an ambient temperature around 20.3{degrees}C. But much of the world is hotter, at least for part of the year, especially when close to the equator (43% of the worlds population lives in the tropics). Such a drug might, by dose-dependently reducing metabolic heat generation, increase thermal comfort in hot places, possibly slowing aging. To illustrate: a relatively small drug dose might increase a clothed persons preferred ambient temperature to 23{degrees}C, a higher dose to 27{degrees}C, an even higher dose to 32{degrees}C, and so on. When metabolic heat generation is low, the preferred ambient temperature is close to 37{degrees}C. When the ambient temperature is 37{degrees}C or more, no metabolic heat generation is needed for the body to be at 37{degrees}C. I predict when such a drug is applied topically to a small body part, such as to the face in a cosmetic cream, it will reduce metabolic heat generation at that location, reducing metabolic rate and thereby slow aging there. Wherein heat transfer from the rest of the body, via blood flow, maintains this body part at around 37{degrees}C, because topical use cant reduce body temperature at any ambient temperature. Less F1F0 ATP hydrolysis, enough predicted to slow aging by two-thirds, has been proven safe in mice, at least when localized to a body part. Slowing the aging of even just a small part of the body has cosmetic and - because many diseases of aging are highly localized (for example, to the eyes: e.g., Age-Related Macular Degeneration) - medical applications. Probably the incidence and progression of age-related diseases correlates with age/aging because aging is causal to them, and so a single drug that slows aging might confer therapeutic benefit for many, varied diseases of aging. Such diseases must be beaten to avert the otherwise coming demographic/economic crisis in which too much of the population suffers, and is debilitated by, at least one of them. A drug to slow aging is a desperate want and has been since the dawn of mankind. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=157 HEIGHT=200 SRC="FIGDIR/small/466310v4_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1862f22org.highwire.dtl.DTLVardef@8061f6org.highwire.dtl.DTLVardef@9f65f0org.highwire.dtl.DTLVardef@dd9f11_HPS_FORMAT_FIGEXP M_FIG C_FIG

Radioresistance remains a primary obstacle in tumor radiotherapy, with no clinically approved radiosensitizers due to toxicity concerns. To identify effective and safe radiosensitizers, a natural products database containing 79,263 compounds are docked against a hybrid target library of four DNA damage response (DDR)-related proteins, comprising both experimental and artificial intelligence (AI)-predicted structures generated by AlphaFold3 and RoseTTAFold All-Atom models. Retrospectively, AI-modeled structures show comparable AUC and logAUC values to experimental structures. Prospectively, compounds screened by AI-modeled structures versus those by experimental structures exhibit limited overlap, e.g., 10% for ataxia telangiectasia mutated (ATM), 22.2% for ATM- and Rad3-related (ATR), 7.7% for DNA-dependent protein kinase catalytic subunit (DNA-PKcs), and 40% for Poly (ADP-ribose) polymerase 1 (PARP1). This highlights structural complementarity of AI-modeled structures when docking against small-scale compound libraries. Two compounds exhibiting lower binding free energy than the DNA-PKcs co-crystallized ligand were selected and validated as effective radiosensitizers in tumor cells. Proteomic analyses reveal shared DDR dysregulation but distinct repair pathway vulnerabilities behind both compounds, which activate TP53-associated apoptosis and senescence as cellular endpoints by modulating the synergistic interplay between DDR and spindle checkpoints. These findings highlight their potential as context-dependent radiosensitizers, providing novel candidates and strategies to overcome tumor radioresistance.

Hylocereus polyrhizus, locally known as red dragon fruit, is valued for its nutritional benefits including high levels of antioxidants and is gaining popularity as both a food and a medicinal plant. The present study addressed the in vivo and in silico chemopreventive potential of Hylocereus polyrhizus peel extract (HPPE) in DMBA-croton oil induced skin carcinogenic model mice. The mRNA expression level of pro-inflammatory cytokines and inflammatory mediators in tumor mass were estimated by real time-RT-qPCR. In addition, molecular docking and molecular dynamic simulation analyses were conducted on the reported compounds. In the in vivo chemopreventive activity assessment, the peel extract at 500 mg/kg was found effective in reducing total tumor number, yield, burden, incidence, and weight. Total proteins and endogenous antioxidants (GSH, SOD, CAT) levels in liver and skin tissues from mice were significantly (P<0.05) elevated. In addition, the HPPE at 500 mg/kg dose significantly reduced (P<0.05) the gene expression of pro-inflammatory cytokines such as TNF-, IL-1{beta}, IL-6, IL-18, and inflammatory mediators like TGF-{beta}1, COX-2, and NF{kappa}B. In the molecular docking studies, reported compounds including Quercimeritrin, Rutin, and Kaempferol 3-O-{beta}-D-glucopyranoside were identified as the top-performing compounds, with a docking score of - 7.4, -7.1 and -7.0 kcal/mol against TGF-{beta}1 protein. This indicates stronger binding interactions compared to vincristine (-5.3 kcal/mol). In drug-likeness assessment, all compounds demonstrated the most favourable ADMET and pharmacokinetic profile. Furthermore, MDS data showed greater dynamic stability for Kaempferol 3-O-{beta}-D-glucopyranoside and Rutin, while vincristine exhibited higher fluctuations. The results suggest that HPPE may serve as a potential inhibitor of skin carcinogenesis through upregulating endogenous antioxidants as well as suppressing different proinflammatory and inflammatory cytokines. Quercimeritrin, Rutin, and Kaempferol 3-O-{beta}-D-glucopyranoside might be the probable leads responsible for this chemopreventive activity. Highlights{checkmark} Hylocereus polyrhizus peel extract (HPPE) demonstrated notable chemopreventive potential against skin cancer. {checkmark}HPPE significantly increased endogenous antioxidants (GSH, SOD, CAT) in liver and skin tissues, suggesting enhanced cellular defense mechanisms. {checkmark}Gene expression of pro-inflammatory cytokines (TNF-, IL-1{beta}, IL-6, IL-18) and inflammatory mediators (TGF-{beta}1, COX-2, NF{kappa}B) were notably suppressed by HPPE. {checkmark}Quercimeritrin (CID: 5282160) demonstrated strong binding to TGF-{beta}1 with a docking score of -7.4 kcal/mol, outperforming vincristine (-5.3 kcal/mol). {checkmark}Kaempferol 3-O-beta-D-glucopyranoside (CID: 5282102) and rutin (CID: 5280805) showed the best ADMET, pharmacokinetic profiles, and molecular stability, supporting their potential as lead compounds.

As the COVID-19 pandemic continues to pose a health risk concern to humans, despite a significant increase in vaccination rates, an effective prevention and treatment of SARS-CoV-2 infection is being sought worldwide. Herbal medicines have been used for years and played a tremendous role in several epidemics of respiratory viral infections. Thus, they are considered as a promising platform to combat SARS-CoV-2. Previously, we reported that common dandelion (Taraxacum officinale) leaf extract and its high molecular weight compounds strongly suppressed in vitro lung cell infection by SARS-CoV-2 Spike D614 and Delta variant pseudotyped lentivirus. We now here demonstrate that T. officinale extract protects against the most prominent Omicron variant using hACE2-TMPRSS2 overexpressing A549 cells as in vitro model system. Notably, compared to the original D614, and the Delta variant, we could confirm a higher efficacy. Short-term interval treatment of only 30 min was then sufficient to block the infection by 80% at 10 mg/mL extract. Further subfractionation of the extract identified compounds larger than 50 kDa as effective ACE2-Spike binding inhibitors. In summary, the evolution of SARS-CoV-2 virus to the highly transmissible Omicron variant did not lead to resistance, but rather increased sensitivity to the preventive effect of the extract.

Maerua edulis exhibits significant antiproliferative activity against HeLa cells, with hexane and ethyl acetate extracts showing IC50 values of 0.02% and 47.42 {micro}g/mL, respectively. Gas Chromatography-Mass Spectrometry (GC-MS) analysis identified key phytochemicals such as diisooctyl phthalate, squalene, and stigmasta-3,5-diene, which were associated with the regulation of apoptotic and cell cycle-related genes (BCL2, CDK2, TP53). Gene expression assays confirmed the modulation of these targets, suggesting the therapeutic potential of M. edulis in cervical cancer. Further in vivo studies are recommended to validate these findings and establish its safety profile.

Flavonoids have been widely investigated for their antiviral and anti-inflammatory properties, but their mechanisms of action often remain insufficiently defined. In the present study, high-purity flavonoids were evaluated using an integrated workflow combining molecular docking, LigPlot+ interaction mapping, surface plasmon resonance (SPR), fluorescence-based TMPRSS2 inhibition assays, and cell-based viability studies. Docking with AutoDock Vina identified Hesperidin as the strongest overall candidate among the compounds evaluated. Hesperidin showed strong active-site engagement with TMPRSS2, including interactions with catalytic residues His296, Asp345, and Ser441, and stable binding within the SARS-CoV-2 main protease (Mpro) pocket. Comparative docking showed weaker or more peripheral interaction patterns for Rutin and moderate Spike binding for Hesperidin and Rutin. Experimental validation demonstrated dose-dependent inhibition of TMPRSS2 activity with an IC50 of 79.1 {micro}M for Hesperidin and 43.5 {micro}M for Hesperetin, while Rutin showed partial inhibition without a defined IC50 in the tested range. In Calu-3 cells, pre-treatment with Hesperidin or Rutin reduced SARS-CoV-2 Spike-induced cytotoxicity by approximately 30% without detectable intrinsic toxicity at the concentrations tested Docking analysis of Hesperidin and Rutin with the SARS-CoV-2 Spike protein revealed moderate interaction patterns involving residues such as Asn343, Ser371, and Val367. Hydrogen bond distances were generally in the range of approximately 2.9-3.3 [A], indicating moderate stabilization compared with the stronger active-site interactions observed for Hesperidin in TMPRSS2. The resulting binding poses suggest that these flavonoids can associate with structurally relevant regions of the Spike receptor-binding domain; however, they do not strongly overlap with the key residues required for ACE2 interaction. Rutin, in particular, exhibited a more peripheral and distributed binding mode within the Spike-ACE2 complex, indicating limited potential for direct disruption of the binding interface. In addition to SARS-CoV-2 targets, docking analysis extended to influenza viral proteins revealed moderate interaction of Hesperidin with hemagglutinin (HA) and strong catalytic-pocket binding of Rutin to neuraminidase (NA), involving key residues associated with enzymatic activity. These findings broaden the scope of the study to include influenza viral entry and release mechanisms, supporting a multi-virus, multi-target framework.

Since its establishment in 1971, the Protein Data Bank (PDB) has been using Cartesian coordinate system (CCS) as the standard framework for protein structure description with x, y, z. Despite the interconvertibility of CCS and spherical coordinate systems (SCS,{rho} , {theta} and{phi} ), CCS remains to date the default and the only framework for protein structure description in PDB. Recent advances in protein structure prediction (e.g., AlphaFold) revolutionized the field by integrating deep learning algorithms with experimental structural data, achieving unprecedented accuracy of protein structure prediction and relying on Cartesian representation of protein structures to extract geometric features. To this end, questions remain about what drives the next stage of continued performance improvement of protein structure prediction. Therefore, this article introduces an alternative coordinate system for protein structure description and feature extraction. Using Caenopore-5 as an example, this article redefines protein backbone structures using atomic bonding networks (ABN) within the SCS framework (ABN-SCS), leading to the extraction of a set of spherical parameters ({rho}, {theta} and{phi} ) from the NMR ensemble of Caenopore-5, encompassing 477 covalent bonds and 80 peptide bonds within its backbone for each structural model in its NMR ensemble. Finally, this work demonstrates that ABN-SCS enables characterization of spherical bond-level geometries, expanding the feature space available for computational pipelines such as AlphaFold2, and argues that integrating ABN-SCS features into protein structure prediction pipelines can enhance geometric fidelity, and that the time is now ripe for the trapped spherical features [{rho}, {theta}, {phi}] to be integrated into algorithms such as AF2 towards protein structure prediction with improved performance.

Assaying cellular responses to antimicrobial molecules is a path to understanding modes of action of potential drugs. This is often achieved via transcriptomics and proteomics, but simple and inexpensive methods for rapid characterization are lacking. To bridge this gap, we assayed changes in the abundance of a panel of 64 "sentinel" proteins fused to GFP in the yeast Saccharomyces cerevisiae using flow cytometry. This method produced expected patterns for classical antifungals and allowed inference of common mechanisms between known and novel compounds. Single-cell data also revealed diverging responses in mitochondrial protein abundance in response to thiazolidine antifungals, and perturbations of the cell cycle caused by various compounds. Finally, the method provided insight into the unknown mode of action of alkylated nucleosides, which can be used against fungi residing on works of art. These substances elevate levels of proteins involved in the biosynthesis of aromatic amino acids (AAA), as well as in oxidative stress. Furthermore, deficiencies of Trp and Tyr biosynthesis increased the efficacy of these compounds, while antioxidants reduced it. Most surprisingly, antioxidant effectiveness relied on AAA biosynthesis. Thus, our approach and its possible modifications for other microbes provides an easy and reliable platform for revealing modes of action of novel compounds.

Natural products (NPs) are metabolites of great importance due to their fundamental biological role in performing specialized activities, ranging from basic cellular functions to complex ecological interactions. These metabolites have contributed to innovating fields such as agriculture and medicine due to their optimized biological activities, a consequence of evolution. A key factor in ensuring that isolated NPs are novel is to search scientific literature and compare pre-existing chemical entities with the new isolate. Unfortunately, articles are typically not machine-readable, a problem that hinders efficient searching and increases the chances of unintended rediscovery. In addition, the time required to add new compound discoveries to compound databases hinders computational studies on cell metabolism and Quantitative Structure-Activity Relationships (QSAR). Here, we present a modularized tool that uses text mining techniques to retrieve chemical entities and taxonomic mentions present in scientific literature, called NPMINE (Natural Products MINIng). We were able to analyze 55,382 scientific articles from some of the most important applied chemistry journals from Brazil and the world, consistently recovering the expected taxonomic and structural information. This processing resulted in 120,970 unique InChI Keys potentially associated with 21,526 unique species mentioned. Using the PubChem BioAssay database we show how QSAR models can be used to mine active leads. The results indicate that NPMINE not only facilitates natural products cataloging, but also assists in biological source assignment and structure-activity relationships, a time-consuming task, typically performed in low throughput.

FK-binding protein 1A, a member of immunophilin family of proteins, is a protein with a wide variety of roles in cellular processes, including regulation of immune system, calcium intake metabolism through ryanodine receptors, TGF-{beta} signaling and EGFR regulation. As a protein originally defined as the cellular target of premier immunosuppresant drugs, FK506 and Rapamycin, it has been a protein studied for further pharmacological uses. In this study, we have overexpressed, purified and crystallized apo-FKBP1A. Here, we are showing the FKBP1A crystal structure, calculated at cryogenic temperature at a very high resolution of 1.05 [A], obtained with a home source X-ray Turkish DeLight. Docking studies, with drug repurposing in mind were carried out with Molegro Virtual Docker software. Docking results will prove useful in future pharmaceutical studies done on FKBP1A, and similar proteins.

Olanzapine, an antipsychotic drug, is well known for its complex polymorphism. Although widely investigated, the crystal structure of one of its anhydrous polymorphs, form III, is still unknown. Its appearance, always in concomitance with form II and I, and the impossibility of isolating it from that mixture, has prevented its structure determination so far. The scenario has changed with the emerging field of 3D electron diffraction (3D ED) technique and its great advantages in the characterization of polyphasic mixture of nanosized crystals. In this study we show how the application of 3D ED allows the ab-initio structure determination and dynamical refinement of this elusive crystal structure unknown for more than 20 years. Olanzapine form III is monoclinic and shows a similar but shifted packing with respect to form II. It is remarkably different from the lowest energy structures predicted by the energy minimization algorithms of crystal structure prediction.

Plants within the Hypericaceae family have been traditionally used for their medicinal properties, showcasing a wide range of effects such as antibacterial, antiviral, and antioxidant qualities. Hypericum alpestre (HA) extracts have exhibited significant cytotoxicity against various cancer cell lines. The phenolic compounds found in HA extracts have attracted attention for their potential in cancer prevention. L-NAME, known for its ability to inhibit nitric oxide synthase (NOS) activity, has emerged as a promising approach in cancer therapy. However, the precise molecular mechanisms underlying the anticancer effects of HA and L-NAME remain unclear. This study aims to clarify the impact of HA and L-NAME on the PI3K/Akt signaling pathway in A549 lung adenocarcinoma cells, with a specific focus on TNFa/COX-2 and VEGFa/MMP-2 pathways. In silico analysis, they identified the compounds with the highest affinity for PI3K/Akt, a finding validated by subsequent in vitro experiments. Furthermore, the combination of herbs and L-NAME exhibited superior efficacy compared to the herb and 5-FU combination, as evidenced by the promotion of apoptosis. Both the herb alone and the combination of the herb with L-NAME demonstrated inhibitory effects on the TNFa/COX-2 and VEGFa/MMP-2 pathways. This therapeutic approach is hypothesized to operate through the PI3k/Akt cell signaling pathway. A better understanding of the interaction between HA polyphenols and PI3K/Akt signaling could pave the way for novel therapeutic strategies against cancer, including drug-resistant tumors.

Orange (Citrus reticulata Blanco) peel contains a flavonoid glycoside hesperidin (HSD) as the primary component. HSD, upon enzymatic hydrolysis, forms hesperetin (HST) aglycone derivate. These two flavonoids have been predicted to have in-silico affinities for ACE2 and SARS-CoV-2 spike, crucial proteins in SARS-CoV-2 infection mechanisms. However, in vitro antiviral testing of orange peel extract, HSD, and HST has not been reported. This study presents for the first time a pseudovirus entry assay approach to test the anti-SARS-CoV-2 effect of HSD, HST, and orange peel extract prepared by hydrodynamic cavitation (HCV). We used a non-virulent pseudovirus model as an alternative to the original virus to target the entry point and enable research to be conducted outside the BSL-3 facility. Based on HPLC analysis, the test results showed that HCV contained HSD at about 4% w/w. Moreover, HSD 1 and 10 M, HST 10 M, and HCV 1 g/ml showed inhibition of pseudovirus entry in 293/hACE2 cells with percentages inhibition 25.92, 37.40, 27.32, and 38.97 %, respectively. Despite HCV 1 g/ml showing about 6 % lower inhibitory activity than HSD 1 M in pseudovirus entry assay, it holds potential as a supplement or source of raw material for HSD as a SARS-CoV-2 antiviral.

Breast cancer (BC) is a prevalent form of cancer observed in women across the globe, constituting over a quarter of all female BC cases. The treatment of BC continues to require significant efficacy, aiming to achieve high success rates while minimizing adverse effects on the body as a whole. In the current study, 3-epicaryoptin was tested for the molecular mechanism of its anti-cancer activity in the human breast cancer cell line, MCF-7. We investigated cell viability by MTT assay, cell cycle kinetics and apoptosis, immunofluorescence straining, molecular modelling, and ADMET profiling. MTT assay results showed that 3-epicaryoptin was found cytotoxic against MCF-7 cells with an IC50 value of 344.64 {micro}g mL-1 for 48 h. Flow cytometric analysis exhibited that 3-epicaryoptin halted the MCF-7 cells in the G2/M phase and subsequently induced apoptosis in a time-dependent manner. Our immunofluorescence studies indicated that 3-epicaryoptin inhibited microtubule polymerization in MCF-7 cells. Furthermore, molecular docking followed by molecular dynamics (MD) simulation studies demonstrated the ability of 3-epicaryoptin to interact with the tubulin protein at the colchicine binding pockets. Overall, our results suggest that 3-epicaryoptin can inhibit the proliferation of human breast cancer cells by depolymerizing of cellular microtubule networks, which causes cell cycle arrest and promotes apoptotic cell death. Therefore, it has been indicated that the natural product 3-epicaryoptin exhibited considerable promise as a potent therapeutic agent capable of inducing apoptosis in breast cancer cells.

Streptomyces lunaelactis strains have been isolated from moonmilk deposits which are calcium carbonate speleothems used for centuries in traditional medicine for their antimicrobial properties. Genome mining revealed that these strains are a remarkable example of a Streptomyces species with huge heterogeneity regarding their content in biosynthetic gene clusters (BGCs) for specialized metabolite production. BGC 28a is one of the cryptic BGCs that is only carried by a subgroup of S. lunaelactis strains for which in silico analysis predicted the production of nonribo-somal peptide antibiotics containing the non-proteogenic amino acid piperazic acid (Piz). Comparative metabolomics of culture extracts of S. lunaelactis strains either or not holding BGC 28a combined with MS/MS-guided peptidogenomics and 1H/13C NMR allowed to identify the cyclic hexapeptide with the amino acid sequence (D-Phe)-(L-HO-Ile)-(D-Piz)-(L-Piz)-(D-Piz)-(L-Piz), called lunaemycin A, as the main compound synthesized by BGC 28a. Molecular networking further identified 18 additional lunaemycins, 14 of them having their structure elucidated by HRMS/MS. Antimicrobial assays demonstrated a huge bactericidal activity of lunaemycins against Gram-positive bacteria including multi-drug resistant clinical isolates. Our work demonstrates how accurate in silico analysis of a cryptic BGC can highly facilitate the identification, the structural elucidation, and the bioactivity of its associated specialized metabolites.

Mutations in p53 are common in different cancer types and are reported to protect cancer via different mechanisms. R175H, R248Q, and R273H are the hotspot mutations of p53 and are suggested to increase aerobic glycolysis in cancer cells. Cancer cells rely mostly upon aerobic glycolysis, so it will be interesting to target these three p53 mutants for designing alternative cancer therapy. The class of compounds studied for their potential to target energy metabolism of cancer cells is called mitocans. The current study is an approach to explore if these selected 3 mutants of p53 may act as suitable target(s) for natural mitocans. Hereby, we selected 60 phytocompounds altogether from Andrographis paniculata and Centella asiatica and docked against all three p53 mutants, using Autodock vina. 11 compounds were sorted based on their binding energies and drug-like properties, and toxicity levels prediction showed asiatic acid to be the most significant. As asiatic acid was observed to significantly bind with R248Q only, R248Q-Asiatic acid was identified for molecular dynamics simulation using GROMACS which showed significant interactions. In conclusion, mutant R248Q was observed to be the best target for asiatic acid, though additional in-vitro experiments are important to validate the findings of this study.

We recently proposed an approach for cancer therapy involving a "paradoxical" activation of oncogenic signaling combined with the inhibition of stress responses. However, as with any other treatment, resistance can also emerge with hyperactivation therapy. In this study, we explored how cancer cells can acquire resistance to a drug that hyperactivates oncogenic signaling using the Protein Phosphatase 2A (PP2A) LB-100 as an example. Our findings indicated that PEBP1 depletion confers resistance to LB-100 in different cancer models. Mechanistically, resistance is mediated by a reduced conversion of the prodrug LB-100 into the active metabolite endothall in the absence of PEBP1. Our data are compatible with a model in which PEBP1 is a hydrolase that can convert the prodrug LB-100 into the active endothall.