ACS Omega

Scar formation is a process that occurs due to increased collagen deposition and uncontrolled inflammation. Previous studies have demonstrated that Pirfenidone (Pf), an FDA approved anti-inflammatory and anti-fibrotic drug can reduce inflammation in vivo as well as regulate activation of LPS-stimulated neutrophils. However, the molecular level mechanism of Pfs action is not well understood. Here, we used neural networks to identify new targets and molecular modeling methods to investigate the Pfs action pathways at the molecular level that are related to its ability to reduce both the inflammatory and remodeling phases of the wound healing process. Out of all the potential targets identified, both molecular docking and molecular dynamics results suggest that Pf has a noteworthy binding preference towards the active conformation of the p38 mitogen activated protein kinase-14 (MAPK14) and it is potentially a type I inhibitor-like molecule. In addition to p38 MAPK (MAPK14), additional potential targets of Pf include AKT1, MAP3K4, MAP2K3, MAP2K6, MSK2, MAP2K2, ERK1, ERK2, and PDK1. We conclude that several proteins/kinases, rather than a single target, are involved in Pfs wound healing ability to regulate signaling, inflammation, and proliferation.

Nanowires (NW) have been extensively studied for Shewanella spp. and Geobacter spp. and are mostly produced by Type IV pili or multiheme c-type cytochrome. Electron transfer via NW is the most studied mechanism in microbially induced corrosion, with recent interest in application in bioelectronics and biosensor. In this study, a machine learning (ML) based tool was developed to classify NW proteins. A manually curated 999 protein collection was developed as an NW protein dataset. Gene ontology analysis of the dataset revealed microbial NW is part of membranal proteins with metal ion binding motifs and plays a central role in electron transfer activity. Random Forest (RF), support vector machine (SVM), and extreme gradient boost (XGBoost) models were implemented in the prediction model and were observed to identify target proteins based on functional, structural, and physicochemical properties with 89.33%, 95.6%, and 99.99% accuracy. Dipetide amino acid composition, transition, and distribution protein features of NW are key important features aiding in the models high performance.

Chemo-resistance remains the main hurdle to cancer therapy, challenging the improvement of clinical outcomes in cancer patients. Therefore, exploratory studies to address chemo-resistance through various approaches are highly rewarding. Nanomedicine is a promising recent advancement in this direction. Comprehensive studies to understand the precise molecular interactions of nanomaterials is necessary to validate their specific "nano induced" effects. Here, we illustrate in detail the specific biological interactions of vanadium pentoxide nanoparticles (VnNp) on triple-negative breast cancer cells and provide initial insights towards its potential in breast cancer management at the cellular level. VnNp shows a time-dependent anti-oxidant and pro-oxidant property in vitro. These nanoparticles specifically accumulate in the lysosomes and mitochondria, modulate various cellular processes including impaired lysosomal function, mitochondrial damage, and induce autophagy. At more extended periods, VnNp influences cell cycle arrest and inhibits cell migration potentiating the onset of apoptosis. Preliminary in vivo studies, on exposing healthy Swiss albino mice to VnNp demonstrated normal blood parameters, organ distribution, and tissue redox balance which further indicated the absence of any adverse organ toxicity. Hence, we foresee tumor-targeting VnNp as a potential drug molecule for future cancer management.

Biophysics is a rapidly advancing field with an incredible breadth of topics. Thus, undergraduate biophysics instructors have to strategize and decide what topics they will cover in their courses. Educational institutions utilize a variety of biophysics textbooks. A common deficiency of each of the existing texts is that it serves well a given set of topics (theory, illustrations, practice problems) and leaves out other areas. A typical example includes good theory and problems for thermodynamics and kinetics while presenting molecular dynamics and various spectroscopic methods in a lacking or outdated way. The authors of this manuscript teach a capstone Biophysical Chemistry three-quarter series (Western Washington University/WWU, Bellingham, WA) which ideally should resonate with the general and major-specific courses the students take within their major at WWU. To achieve this goal and to enrich the traditional lecture-based delivery, the instructors have developed and brought together key pedagogical elements: purpose-built online textbook with a uniform structure of the academic content and practice problems, a study sample (oligopeptide) of biophysical significance with a growing set of experimental and computational data and student-centric in-class activities including computer labs. Our Biophysical series emphasizes concepts and methods of computational structural biology (Molecular Dynamics) and spectroscopic approaches (IR, UV and NMR). Here we describe the details of our integrative approach, summarize key outcomes and chart ways to advance the biophysical chemistry series further. Our textbook can be found through LibreText.

There is great need for novel strategies to tackle antimicrobial resistance, in particular in Gram-negative species such as Escherichia coli that cause opportunistic infections of already compromised patients. Here we demonstrate, following a screen of G-quadruplex (G4) ligand candidates, that a novel pyridinium-functionalized azobenzene L9 shows promising antibacterial activity (MIC values [≤] 4 g/mL) against multi-drug resistant E. coli. Tandem Mass Tag (TMT) proteomics of E. coli treated with sub-lethal concentrations of L9, identified that, consistent with its superior antibacterial activity, L9 treatment influences expression levels of more G4-associated proteins than the analogous ligands L5 (stiff-stilbene) or pyridostatin (PDS), and upregulates multiple essential proteins involved in translation. Biophysical analysis showed L9 binds potential target G4-containing sequences, identified from proteomic experiments and by bioinformatics, with variable affinity, in contrast to the two comparator G4 ligands (L5, PDS) that better stabilize G4 structures but have lower antimicrobial activity. Fluorescence microscopy-based Bacterial Cytological Profiling (BCP) suggests that the L9 mechanism of action is distinct from other antibiotic classes. These findings support strategies discovering potential G4 ligands as antibacterial candidates for priority targets such as multi-drug resistant E. coli, warranting their further exploration as potential novel therapeutic leads with G4-mediated modes of action. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/506212v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@18197a0org.highwire.dtl.DTLVardef@109b120org.highwire.dtl.DTLVardef@14be8eeorg.highwire.dtl.DTLVardef@a97048_HPS_FORMAT_FIGEXP M_FIG C_FIG

Affinity based drug delivery mechanisms increase efficacy and minimalize off target effects when compared to non-specific methods due to the localization of drugs within target areas. While this is beneficial for targeted delivery, introduction of foreign polymeric medical devices into the body provide a potential area of localization due to high affinity between administered drugs and polymers. Previous attempts at creating models to predict affinity between small molecule drugs and polymers require a specific model be trained for each individual polymer failing to incorporate input features of both the polymer (host) and small molecule drug (guest). Within, we propose a universal model built using a neural network and quantitative structure activity relationships to predict the binding energy between guest and host molecules using input features. The trained model returned a correlation value, R2, of 0.9806 and 0.9958 between predicted and experimental binding affinity for the training and validation sets, respectively. This correlates to a mean absolute error of 0.951 kJ/mol and 0.771 kJ/mol for the training and validation sets, respectively. While limited to the current polymers used to train the model, the dataset can be expanded, and models retrained for further applications.

Cortisol is a primary biomarker of stress, released in sweat at concentrations that directly correlate with physiological stress levels. Detecting cortisol non-invasively offers significant potential for real-time stress monitoring and healthcare applications. Biosensors capable of binding cortisol can thus enable the development of novel diagnostic platforms for personalised health management. In our earlier work, a 38-mer peptide fragment derived from the protein 2V95 was identified as a functional binder to cortisol. In the present study, we applied generative artificial intelligence (AI) approaches to expand the sequence space and identify superior candidate peptides with improved binding affinity. By integrating sequence-based and structure-based AI models, we generated and screened a peptide library of nearly 10,000 sequences against cortisol, leading to the identification of high-affinity candidates for further evaluation.

Platinum-based drugs, such as cisplatin, are first-line chemotherapy treatments for patients with cancer. However, the success of these drugs is balanced with severe off-target toxicities and high dosing requirements, prompting the development of selective nanocarriers for targeted drug delivery. This study uses a computationally guided approach to examine the role of amino acids in cisplatin binding within proteins as nanocarriers. Using density functional theory, we quantify the binding of cisplatin to platinum-coordinating amino acids. We then rationally engineer a model MSH6 protein carrier, and evaluate the ability of MSH6 to bind cisplatin via molecular docking simulations. Structure predictions of the engineered MSH6 show that inserting the cisplatin-binding site has a limited impact on the nearby protein architecture of MSH6. Finally, we confirm and reveal cisplatins mechanism of action with DNA binding, and compare the energetic potentials of DNA binding from protein-delivered cisplatin to systemically administered cisplatin. Future studies will use these results to experimentally validate the binding of cisplatin in model protein carriers, and inform the strategic design and experimental development of a protein nanocarrier to achieve targeted drug delivery in cancer. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/699809v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@feee4org.highwire.dtl.DTLVardef@ccc34org.highwire.dtl.DTLVardef@328cd3org.highwire.dtl.DTLVardef@bb8335_HPS_FORMAT_FIGEXP M_FIG C_FIG

In light of the "silent" AMR pandemic, new avenues to combat pathogenic bacteria are needed. In this work, we screened a large molecule library (n=35 684 unique compounds) with the aim of identifying molecules being able to bind and block translation of the prfA-thermosensor transcript in the bacterial pathogen Listeria monocytogenes. Using a thiazole-orange displacement approach, 468 ([~]1.3% of all molecules) showed the ability to reduce fluorescence. After dose response testing, 32 compounds remained promising and eight of them showed sufficient purity and availability to be further validated. Interestingly, four compounds, being structurally very similar, showed specificity for prfA at a varying degree. All four compounds carried 3 aromatic rings with one connecting amine between two of the rings and an amide linking an aliphatic amine side chain. The most selective compounds, M5, showed a Kd of [~]0.8 {micro}M for the prfA RNA at 35{degrees}C. However, none of the eight most efficient compounds were able to inhibit prfA translation in vitro, suggesting that the molecules are able to bind but not affect the stability of the overall structure. Through this work, we have been able to identify a set of molecules, able to bind the prfA thermosensor RNA selectively, but without affecting translation. These molecules could constitute an important scaffold for further drug development.

Inhibitors of DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug discovery. They are also chemical tools to understand the biochemistry of epigenetic processes. Herein, we report five distinct inhibitors of DNMT1 characterized in enzymatic inhibition assays that did not show activity with DNMT3B. It was concluded that the dietary component theaflavin is an inhibitor of DNMT1. Two additional novel inhibitors of DNMT1 are the approved drugs glyburide and panobinostat. The DNMT1 enzymatic inhibitory activity of panobinostat, a known pan inhibitor of histone deacetylases, agrees with experimental reports of its ability to reduce DNMT1 activity in liver cancer cell lines. Molecular docking of the active compounds with DNMT1, and re-scoring with the recently developed Extended Connectivity Interaction Features approach, had an excellent agreement between the experimental IC50 values and docking scores.

The possibility of using RNA-targeting small molecules to treat diseases is gaining traction as the next frontier of drug discovery and development. The chemical characteristics of small molecules that bind to RNA are still relatively poorly understood, particularly in comparison to protein-targeting small molecules. To fill this gap, we have generated an unprecedented amount of RNA-small molecule binding data, and used it to derive physicochemical rules of thumb that could be used to define areas of chemical space enriched for RNA binders - the Small molecules Targeting RNA (STaR) rules of thumb. These rules have been applied to publicly available RNA-small molecule datasets and found to be largely generalizable. Furthermore, a number of patented RNA-targeting compounds and FDA-approved compounds also pass these rules, as well as key RNA binding approved drug case studies including Risdiplam. We anticipate this work will significantly accelerate the exploration of the RNA-targeted chemical space, towards unlocking RNAs potential as a small molecule drug target. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=130 HEIGHT=200 SRC="FIGDIR/small/578268v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@15ced07org.highwire.dtl.DTLVardef@1cd891eorg.highwire.dtl.DTLVardef@e51599org.highwire.dtl.DTLVardef@1ecfa86_HPS_FORMAT_FIGEXP M_FIG C_FIG

Amyloid fibril formation is a hallmark of several protein misfolding diseases, including systemic hereditary amyloidosis (SHA), in which lysozyme aggregates into plaques, causing inflammation in various tissues. SHA is a rare disease with no current drug treatment options. In our efforts to identify potential therapeutics for SHA, we investigated the inhibitory effects of benzamidine (BEN) on the fibrillation of human lysozyme (HL). Multiple biophysical assays demonstrated BENs ability to effectively prevent amyloid formation. Intrinsic fluorescence measurements highlighted BENs interaction with HL. We inferred the binding mode of BEN to HL through ITC experiments, molecular docking, and molecular dynamics simulations, confirmed BENs binding at the active site, particularly near stretch-2 (residues 52-64), a key region in its anti-amyloidogenic activity. This interaction differed from the previously reported interaction with HEWL. Further, microscopy analyses, including scanning electron microscopy (SEM) and transmission electron microscopy (TEM), further supported these findings by showing reduced fibril formation and alterations in fibril morphology in the presence of BEN. Importantly, BEN exhibited no cytotoxic effects in HEK-293 cells, reinforcing its potential as a therapeutic candidate for amyloidosis. These results provide strong evidence of BENs anti-amyloidogenic activity and offer a foundation for future drug development targeting lysozyme amyloidosis.

Emerging fungal pathogens represent a concerning threat to both global health and food security. In this study, we aimed to address our rising vulnerability to fungal pathogens through the development of the Fung-AI pipeline: an AI/ML-driven approach for antifungal discovery. A generative adversarial network (GAN) was trained to generate novel candidate antifungal peptide sequences. Next, in silico antifungal and hemolytic classifiers were built to further prioritize AI-generated peptides for experimental validation. From a pool of [~]10,000 candidates, thirteen peptides were selected for testing over two-stages of experimentation. Five peptides were found to display mild antifungal activity against the wheat pathogen, Fusarium graminearum, with minimal inhibitory concentrations (MICs) ranging from 250 {micro}g/mL to 500 {micro}g/mL. Four of the five peptides also showed activity against the human pathogen, Candida albicans (MIC: 500 {micro}g/mL). Two of our AI-generated antifungal peptides additionally demonstrated low cytotoxicity in HepG2 human liver carcinoma cells (LC50 > 704.2 {micro}g/mL) indicating that they may be useful as scaffolds for future optimization for therapeutic applications. None of our peptides were found to considerably inhibit the emerging pathogen C. auris, suggesting the need for pathogen-specific down-selection of candidate peptides. Overall, we present a proof-of-principle, generative-AI-based approach for the rapid design of de novo antifungal peptides.

We performed a thorough analysis and characterization of multiple batches of Helaina recombinant human lactoferrin (rhLF, Effera) expressed at an industrial scale in a yeast system. Bottom-up LC-MS/MS-based proteomics analysis detected the full sequence of Helaina rhLF protein and confirmed that its amino acid sequence is identical to that of native human LF (Uniprot i.d. P02788). Helaina rhLF had a protein purity of 98% or higher as determined by three orthogonal methods; reversed-phase HPLC, SDS-PAGE, and LC-MS proteomics analysis. N-linked glycans were detected at three known glycosylation sites, namely, Asparagines-156, -497, and -642. The identified N-glycans of Helaina rhLF were predominantly oligomannose structures with five to nine mannoses (M5-M9), which we also report to be present in both the native human and bovine LF. human milk LF (hmLF) possessed lower levels of oligomannose structures and were mainly M5 and M6. Helaina rhLF protein secondary structure was nearly identical to that of hmLF, as revealed by microfluidic modulation spectroscopy. Results of small-angle X-ray scattering (SAXS) and analytical ultracentrifugation analyses confirmed that, like hmLF, Helaina rhLF displayed well-folded globular structures in solution. Reconstructed solvent envelopes of Helaina rhLF, obtained through the SAXS analysis, demonstrated a remarkable fit with the reported crystalline structure of iron-bound native hmLF. Differential scanning calorimetry investigations into the thermal stability of Helaina rhLF revealed two distinct denaturation temperatures at 68.7{+/-}0.9 {degrees}C and 91.9{+/-}0.5 {degrees}C, consistently mirroring denaturation temperatures observed for apo-and holo-hmLF. Overall, the characterization analysis results affirmed that Helaina rhLF was of high purity and exhibited globular structures closely akin to that of hmLF.

Amyloid fibrils are traditionally associated with protein misfolding disorders; however, increasing evidence indicates that they can also perform beneficial biological functions, including antimicrobial defense. Here, we investigated whether structurally distinct amyloid polymorphs of hen egg white lysozyme (HEWL) exhibit enhanced antibacterial activity compared with the native protein. HEWL was converted into two amyloid polymorphs, flexible fibrils (FFs) and rigid fibrils (RFs), and their antibacterial activities were evaluated against the Gram-positive bacterium Staphylococcus aureus and the Gram-negative bacteria Escherichia coli (Top10) and Salmonella Typhimurium. Fibril formation was confirmed by circular dichroism (CD) spectroscopy, thioflavin T (ThT) fluorescence, and transmission electron microscopy (TEM), demonstrating morphologically distinct amyloid assemblies with different secondary-structure organizations. Fluorescence-based bacterial growth assays showed that native HEWL exhibited only moderate antibacterial activity, whereas both amyloid polymorphs produced potent, concentration-dependent bacterial growth inhibition. FFs and RFs consistently displayed greater antibacterial efficacy than native HEWL across all tested strains, with FFs exhibiting slightly stronger activity against S. Typhimurium. At concentrations of 600-800 M, FFs achieved >90% growth inhibition for all bacterial species examined. Cytotoxicity studies using SH-SY5Y human neuroblastoma cells demonstrated minimal toxicity for native HEWL, modest effects for FFs, and substantially greater toxicity for RFs, indicating that amyloid polymorphism influences both antimicrobial activity and mammalian cell compatibility. Collectively, these findings establish a direct relationship between amyloid structure, antibacterial efficacy, and cytotoxicity. The combination of potent antibacterial activity and relatively low cytotoxicity identifies FFs as a promising functional amyloid biomaterial for the development of next-generation antimicrobial materials.

Alzheimers disease (AD) is characterized by progressive neurodegeneration. The critical molecular trigger is believed to be the accumulation of A{beta} neurotoxic oligomers. Given the proteolytic processing of Amyloid Precursor Protein (APP) by {beta}-secretase (beta-site APP cleaving enzyme 1, BACE1) as the key step in the building up of A{beta} oligomers, BACE inhibitors come with therapeutic prospects of preventing or delaying the onset of Alzheimers. To find inhibitory peptides against BACE1, a library of dark peptides was constructed from 4400 intergenic DNA sequences of Escherichia coli. The sequence level analysis was followed by protein structure predictions, molecular docking, and simulation. Based on bioinformatics analysis, 5 potential peptides were screened for experimental validation. Out of these two peptides were identified as lead molecules based on BACE1 inhibitory activity, followed by FRET inhibitory assay, western blot, and RT-PCR. An 86.7 % drop in BACE1 level was observed in the presence of the ECOI2 peptide. Though encouraging results were obtained from in-silico and in-vitro studies, more work is required to study the efficacy of these peptides in suitable animal models.

Summary/AbstractOdorant binding proteins, OBPs, are a diverse family of small, globular, extra-cellular proteins solubilize volatile organic compounds (VOCs) so they can be internalized and transported by an organism. Since their initial discovery in the early eighties 1, thousands of OBPs have been identified through genome sequencing and characterized by fluorescence ligand binding assays 2. While individual OBPs have been studied in the context of their roles in specific organism, there have been no studies towards the understanding of the comparative structure-function relations of all known OBPs, primarily due to a lack of a centralized database that incorporates the binding affinity with the structure of all OBPs. Incorporating OBP information into a database requires not only an extensive search of all existing resources, but also creating a useful platform that relates sequence structures to target functions. Combining 215 functional studies containing 381 unique OBPs from 91 insect species we created a database, iOBPdb: https://iobpdb.herokuapp.com, of OBP binding affinities for a wide range of VOC targets. We demonstrate here that the construction of this initial database provides powerful search and associative capabilities including interrogating odor binding proteins as clusters and groups by sequence similarity versus protein and target molecular weights, and by the functional groups of the VOC targets. The comparative interrogation of the probe-target recognition allows for a more comprehensive understanding of the underlying structural features of all OBPs that had not been possible by only examining the OBPs individually. We present our results in a variety of phylogenetic representations as well as providing the binding profiles of OBP groups to VOC functional moieties. Potential applications include development of molecular probes for biosensors, novel bioassays and drugs, discovery of novel pesticides which inhibit VOC / OBP interactions, as well providing a foundational basis for the functional understanding of odor sensing and perception in the brain. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/498339v2_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@9c2fa0org.highwire.dtl.DTLVardef@1fad38aorg.highwire.dtl.DTLVardef@56175forg.highwire.dtl.DTLVardef@189797_HPS_FORMAT_FIGEXP M_FIG C_FIG

Synthetic opioids such as fentanyl and related analogs have been widely used for pain management. However, their negative side effects, including respiratory depression and high potential for addiction, underscore the need for a deeper understanding of fentanyls interactions with proteins throughout the human body. Fentanyl analogs bind and activate opioid receptors in the central and peripheral nervous systems, triggering numerous downstream signaling pathways. Increasingly, fentanyl has been shown to interact with non-opioid receptors, and elucidation of these non-canonical fentanyl-protein interactions may provide insights into the mechanisms contributing to fentanyls adverse effects and illuminate novel countermeasure strategies. To identify proteins in mammalian tissues that may interact with fentanyl, we designed and synthesized three affinity-based probes (AfBPs) that include the fentanyl core and feature a diazirine photoaffinity group and alkyne handle for click chemistry at different positions. Molecular docking simulations predicted that these AfBPs bind the mu opioid receptor similarly to fentanyl. Affinity-based protein profiling using the FA-T1 probe in vitro in tissues from six animal species identified histamine N-methyltransferase (HNMT), endophilin-B1 (SH3GLB1), fructosamine-3-kinase (FN3K), cutA divalent cation tolerance analog (CUTA), and monoamine oxidase B (MAOB) among the top proteins that bind fentanyl in multiple species and tissue types. Molecular docking of fentanyl and remifentanil with these protein structures identified putative binding sites. The interaction of fentanyl with specific proteins was empirically assessed through protein structural analyses. These findings highlight potential fentanyl-protein interactions that may contribute to the acute and long-term impacts of fentanyl exposures.

Erythrocytosis, a disorder with increased erythrocyte production, has a heterogeneous aetiology, including rare congenital types linked to dysregulation of the oxygen-sensing pathway. Variants in the EGLN1 gene, encoding the prolyl hydroxylase that regulates hypoxia-inducible factor (HIF) stability, are associated with familial erythrocytosis type 3 (ECYT3). In patients with idiopathic erythrocytosis we previously identified two novel EGLN1 variants, c.1072C>T (p.(Pro358Ser)) and c.1124A>G (p.(Glu375Gly)), classified as variants of uncertain significance. Herein, we performed in silico and in vitro analyses to assess their structural and functional effects, using the known pathogenic variant p.(His374Arg) as a positive control. AlphaFold3 predictions revealed minimal conformational changes in the protein core for all variants, while stability predictions suggested reduced protein stability. Functional assays in HEK293 cells demonstrated significantly decreased protein levels and stability for p.(Pro358Ser) and p.(Glu375Gly), comparable to p.(His374Arg). However, luciferase reporter assays showed that, unlike p.(His374Arg), the novel variants did not substantially impair EGLN1 enzymatic activity or activate HIF signalling. Our results suggest that the novel variants may contribute to erythrocytosis through destabilization of EGLN1, supporting further studies to elucidate their precise impact on hypoxia regulation. This study highlights the complexity of studying EGLN1 variants and the importance of functional evaluation for clinical interpretation.

Candida albicans biofilms are a complex multilayer community of cells that are resistant to almost all classes of antifungal drugs. The bottommost layers of biofilms experience nutrient limitation where C. albicans cells are required to respire. We previously reported that a protein Ndu1 is essential for Candida mitochondrial respiration; loss of NDU1 causes inability of C. albicans to grow on alternative carbon sources and triggers early biofilm detachment. Here, we screened a repurposed library of FDA approved small molecule inhibitors, to identify those that prevent NDU1-associated functions. We identified an anti-helminthic drug, Niclosamide (NCL), which not only prevented growth on acetate, C. albicans hyphenation and early biofilm growth, but also completely disengaged fully grown biofilms of drug resistant C. albicans and C. auris from their growth surface. To overcome the sub-optimal solubility and permeability of NCL that is well-known to affect its in vivo efficacy, we developed NCL encapsulated Eudragit EPO (an FDA-approved polymer) nanoparticles (NCL-EPO-NPs) with high niclosamide loading, that also provided long-term stability. The developed NCL-EPO-NPs completely penetrated mature biofilms and attained anti-biofilm activity at low microgram concentrations. NCL-EPO-NPs induced ROS activity in C. albicans, and drastically reduced oxygen consumption rate in the fungus, similar to that seen in an NDU1 mutant. NCL-EPO-NPs also significantly abrogated mucocutaneous candidiasis by fluconazole resistant strains of C. albicans, in mice models of oropharyngeal and vulvovaginal candidiasis. To our knowledge, this is the first study that targets biofilm detachment as a target to get rid of drug-resistant Candida biofilms, and uses nanoparticles of an FDA approved non-toxic drug to improve biofilm penetrability and microbial killing.