Specific Target Research Articles

Fluorescence Thermal Shift Assay based High Through-put Screening in Small Molecule Drug Discovery: A Brief Overview

Background: The Early drug discovery process was majorly phenotypic, lacking target specificity, and mechanism of action causing short and/or long-term toxicological impacts on the patients leading to several drug withdrawals from the market. Biochemical procedures and methods used in drug discovery and development make it lengthy in terms of time requiring approx. 15 years with the investment of billions of dollars for a new drug molecule. Technological advancement leading to the identification of protein structures through crystallography paved a new path toward targeted drug discovery. Objective: This paper provides a brief overview of the use of the fluorescence thermal shift assay (FTSA) as a high throughput (HTS) screening technique in small molecule drug discovery. Methods: The article discusses the principles of thermal denaturation techniques and how they are applied in drug discovery. It highlights the advantages of FTSA over other biophysical methods, including its label-free, cost-effective, and high HTS nature. The review also presents a comparative analysis of FTSA with techniques such as isothermal titration calorimetry (ITC), mass spectrometry (MS), nuclear magnetic resonance (NMR), surface plasmon resonance (SPR), X-ray crystallography(X-RD), circular dichroism (CD), and differential scanning calorimetry (DSC). Results: The FTSA technique is described as a powerful tool that addresses the limitations of larger protein requirements, specific assay development, and low HTS associated with other thermal denaturation methods. Unlike biochemical and cellular assays that measure secondary effects, FTSA directly estimates the binding of small molecules to target proteins. Conclusion: The review concludes that FTSA is the only biophysical method that satisfies the three key prerequisites of being label-free, cost-effective, and suitable for high HTS screening in small molecule drug discovery.

Anti-ferroptosis exosomes engineered for targeting M2 microglia to improve neurological function in ischemic stroke.

Stroke is a devastating disease affecting populations worldwide and is the primary cause of long-term disability. The inflammatory storm plays a crucial role in the progression of stroke. In the acute phase of ischemic stroke, there is a transient increase in anti-inflammatory M2 microglia followed by a rapid decline. Due to the abundant phospholipid in brain tissue, lipid peroxidation is a notable characteristic of ischemia/reperfusion (I/R), constituting a structural foundation for ferroptosis in M2 microglia. Slowing down the decrease in M2 microglia numbers and controlling the inflammatory microenvironment holds significant potential for enhancing stroke recovery. We found that the ferroptosis inhibitor can modulate inflammatory response in MCAO mice, characterizing that the level of M2 microglia-related cytokines was increased. We then confirmed that different subtypes of microglia exhibit distinct sensitivities to I/R-induced ferroptosis. Adipose-derived stem cells derived exosome (ADSC-Exo) effectively decreased the susceptibility of M2 microglia to ferroptosis via Fxr2/Atf3/Slc7a11, suppressing the inflammatory microenvironment and promoting neuronal survival. Furthermore, through plasmid engineering, a more efficient M2 microglia-targeted exosome, termed M2pep-ADSC-Exo, was developed. In vivo and in vitro experiments demonstrated that M2pep-ADSC-Exo exhibits significant targeting specificity for M2 microglia, further inhibiting M2 microglia ferroptosis and improving neurological function in ischemic stroke mice. Collectively, we illustrated a novel potential therapeutic mechanism that Fxr2 in ADSC-Exo could alleviate the M2 microglia ferroptosis via regulating Atf3/Slc7all expression, hence inhibiting the inflammatory microenvironment, improving neurofunction recovery in cerebral I/R injury. We obtained a novel exosome, M2pep-ADSC-Exo, through engineered modification, which exhibits improved targeting capabilities toward M2 microglia. This provides a new avenue for the treatment of stroke.

Aptamer-RIBOTAC Strategy Enabling Tumor-Specific Targeted Degradation of MicroRNA for Precise Cancer Therapy.

MicroRNA (miRNA) molecules play crucial roles in a variety of diseases, making miRNA targeting a burgeoning field in medicinal chemistry. Ribonuclease targeting chimeras (RIBOTACs) present a compelling approach for RNA degradation. However, small molecule-based RIBOTAC requires an expensive and time-consuming screening process, and is difficult to directly target miRNA due to its short length lacking secondary structure. Antisense oligonucleotide (ASO)-based RIBOTAC is easy to design but with poor cell permeability. While both of them lack the specificity for tumor targeting. In this study, the first Aptamer-RIBOTAC (ARIBOTAC) chimera is designed based on ASO to achieve precise degradation of miRNA in a tumor cell-specific manner for precise cancer therapy. This chimera exhibits a remarkable ability to specifically identify and enter cancer cells, trigger localized activation of endogenous RNase L, and selectively cleave miRNAs that are complementary to ASO. The efficacy and universality of the ARIBOTAC strategy both in vitro and in vivo by degrading oncogenic miR-210-3p and miR-155-5p are validated. These findings underscore the potential of the ARIBOTAC strategy as a promising avenue for cancer therapy by precisely targeting cancer-associated miRNAs.

Development of scoring-assisted generative exploration (SAGE) and its application to dual inhibitor design for acetylcholinesterase and monoamine oxidase B

De novo molecular design is the process of searching chemical space for drug-like molecules with desired properties, and deep learning has been recognized as a promising solution. In this study, I developed an effective computational method called Scoring-Assisted Generative Exploration (SAGE) to enhance chemical diversity and property optimization through virtual synthesis simulation, the generation of bridged bicyclic rings, and multiple scoring models for drug-likeness. In six protein targets, SAGE generated molecules with high scores within reasonable numbers of steps by optimizing target specificity without a constraint and even with multiple constraints such as synthetic accessibility, solubility, and metabolic stability. Furthermore, I suggested a top-ranked molecule with SAGE as dual inhibitors of acetylcholinesterase and monoamine oxidase B through multiple desired property optimization. Therefore, SAGE can generate molecules with desired properties by optimizing multiple properties simultaneously, indicating the importance of de novo design strategies in the future of drug discovery and development.Scientific contribution The scientific contribution of this study lies in the development of the Scoring-Assisted Generative Exploration (SAGE) method, a novel computational approach that significantly enhances de novo molecular design. SAGE uniquely integrates virtual synthesis simulation, the generation of complex bridged bicyclic rings, and multiple scoring models to optimize drug-like properties comprehensively. By efficiently generating molecules that meet a broad spectrum of pharmacological criteria—including target specificity, synthetic accessibility, solubility, and metabolic stability—within a reasonable number of steps, SAGE represents a substantial advancement over traditional methods. Additionally, the application of SAGE to discover dual inhibitors for acetylcholinesterase and monoamine oxidase B not only demonstrates its potential to streamline and enhance the drug development process but also highlights its capacity to create more effective and precisely targeted therapies. This study emphasizes the critical and evolving role of de novo design strategies in reshaping the future of drug discovery and development, providing promising avenues for innovative therapeutic discoveries.

AdeIJK Pump-Specific Inhibitors Effective against Multidrug Resistant Acinetobacter baumannii.

Multidrug-resistant Acinetobacter baumannii is a serious threat pathogen rapidly spreading in clinics and causing a range of complicated human infections. The major contributor to A. baumannii antibiotic resistance is the overproduction of AdeIJK and AdeABC multidrug efflux pumps of the resistance-nodulation-division (RND) superfamily of proteins. The dominant role of efflux in antibiotic resistance and the relatively high permeability of the A. baumannii outer membrane to amphiphilic compounds make this pathogen a promising target for the discovery of clinically relevant efflux pump inhibitors. In this study, we identified 4,6-diaminoquoniline analogs with inhibitory activities against A. baumannii AdeIJK efflux pump and followed up on these compounds with a focused synthetic program to improve the target specificity and to reduce cytotoxicity. We identified several candidates that potentiate antibacterial activities of antibiotics erythromycin, tetracycline, and novobiocin not only in the laboratory antibiotic susceptible strain A. baumannii ATCC17978 but also in multidrug-resistant clinical isolates AB5075 and AYE. The best analogs potentiated the activities of antibiotics in low micromolar concentrations, did not have antibacterial activities on their own, inhibited AdeIJK-mediated efflux of its fluorescent substrate ethidium ion, and had low cytotoxicity in A549 human lung epithelial cells.

Surface Glycans of Microvesicles Derived from Endothelial Cells, as Probed Using Plant Lectins

Glycans of MVs are proposed to be candidates for mediating targeting specificity or at least promoting it. In contrast to exosomes, glycomic studies of MVs are largely absent. We studied the glycoprofile of endothelial cell-derived MVs using 21 plant lectins, and the results show the dominance of oligolactosamines and their α2-6-sialylated forms as N-glycans and low levels of α2-3-sialylated glycans. The low levels of α2-3-sialosides could not be explained by the action of extracellular glycosidases. Additionally, the level of some Man-containing glycans was also decreased in MVs. Spatial masking as the causative relationship between these low level glycans (as glycosphingolipids) by integral proteins or proteoglycans (thus, their lack of interaction with lectins) seems unlikely. The results suggest that integral proteins do not pass randomly into MVs, but instead only some types, differing in terms of their specific glycosylation, are integrated into MVs.

How Do Behavioral Framing, Linguistic Certainty, and Target Specification Impact Responses to Vaping Prevention Messages?

While research on youth vaping prevention has begun to grow, little work has examined language choice in vaping prevention messages. This study examined adolescents’ responses to vaping prevention statements that varied on three features: behavioral framing, linguistic certainty, and target specification. We conducted a 2 (behavioral framing) by 2 (linguistic certainty) by 2 (target specification) by 3 (risk type) plus control condition between-subjects experiment using a national probability sample. Adolescents (N = 1,603) were randomly assigned to one of 25 conditions in which they viewed a vaping prevention statement (or a control statement about vape litter) followed by measures of perceived message effectiveness (PME), perceived severity and susceptibility of vaping risks, message trustworthiness, message relevance, and intentions to seek more information about vaping risks. Results showed main effects of behavioral framing, such that a declarative frame (“Vaping can … ”) led to higher PME, higher perceived severity, and greater information seeking intentions than a contingent frame (“If you vape, it can…”), while an interaction revealed that most declarative frame effects were driven by adolescents who were susceptible to vaping. There were also main effects of linguistic certainty, such that the word “can” (“Vaping can … ”) led to higher PME, higher perceived susceptibility and severity, and greater information seeking intentions than the word “could” (“Vaping could … ”). No main effect of target specification (“you” vs. “teens”) was observed. Overall, findings suggest that vaping prevention messages that communicate greater certainty have greater behavior change potential.

Heme-Mimetic Photosensitizer with Iron-Targeting and Internalizing Properties for Enhancing PDT Activity and Promoting Infected Diabetic Wound Healing.

The management of multibacterial infections remains clinically challenging in the care and treatment of chronic diabetic wounds. Photodynamic therapy (PDT) offers a promising approach to addressing bacterial infections. However, the limited target specificity and internalization properties of traditional photosensitizers (PSs) toward Gram-negative bacteria pose significant challenges to their antibacterial efficacy. In this study, we designed an iron heme-mimetic PS (MnO2@Fe-TCPP(Zn)) based on the iron dependence of bacteria that can be assimilated by bacteria and retained in different bacteria strains (Escherichia coli, Staphylococcus aureus, and methicillin-resistant Staphylococcus aureus) and which shows high PDT antibacterial efficacy. For accelerated wound healing after antibacterial treatment, MnO2@Fe-TCPP(Zn) was loaded into a zwitterionic hydrogel with biocompatibility and antifouling properties to form a nanocomposite antibacterial hydrogel (PSB-MnO2@Fe-TCPP(Zn)). In the multibacterial infectious diabetic mouse wound model, the PSB-MnO2@Fe-TCPP(Zn) hydrogel dressing rapidly promoted skin regeneration by effectively inhibiting bacterial infections, eliminating inflammation, and promoting angiogenesis. This study provides an avenue for developing broad-spectrum antibacterial nanomaterials for combating the antibiotic resistance crisis and promoting the healing of complex bacterially infected wounds.

Antifungal Potential of Secondary Metabolites Derived from Arcangelisia flava (L.) Merr.: An Analysis of In Silico Enzymatic Inhibition and In Vitro Efficacy against Candida Species

Considering the escalating resistance to conventional antifungal medications, it is critical to identify novel compounds that can efficiently counteract this challenge. The purpose of this research was to elucidate the fungicidal properties of secondary metabolites derived from Arcangelisia flava, with a specific focus on their efficacy against Candida species. This study utilized a combination approach comprising laboratory simulations and experiments to discern and evaluate the biologically active constituents present in the dichloromethane extract of A. flava. The in vitro experiments demonstrated that compounds 1 (palmatine) and 2 (fibraurin) exhibited antifungal properties. The compounds exhibited minimum inhibitory concentrations (MICs) ranging from 15.62 to 62.5 µg/mL against Candida sp. Moreover, compound 1 demonstrated a minimum fungicidal concentration (MFC) of 62.5 µg/mL against Candida glabrata and C. krusei. In contrast, compound 2 exhibited an MFC of 125 µg/mL against both Candida species. Based on a molecular docking study, it was shown that compounds 1 and 2 have a binding free energy of −6.6377 and −6.7075 kcal/mol, respectively, which indicates a strong affinity and specificity for fungal enzymatic targets. This study utilized pharmacophore modeling and Density Functional Theory (DFT) simulations to better understand the interaction dynamics and structural properties crucial for antifungal activity. The findings underscore the potential of secondary metabolites derived from A. flava to act as a foundation for creating novel and highly efficient antifungal treatments, specifically targeting fungal diseases resistant to existing treatment methods. Thus, the results regarding these compounds can provide references for the next stage in antifungal drug design. Further investigation is necessary to thoroughly evaluate these natural substances’ clinical feasibility and safety characteristics, which show great potential as antifungal agents.

Intelligent Magnetic Microrobots with Fluorescent Internal Memory for Monitoring Intragastric Acidity

AbstractThis study investigates the dynamic fluctuations of pH caused by gastric acid secretion, a process of both biological and clinical significance, with microrobots. Abnormal patterns of acidity often indicate gastrointestinal diseases, underlying the importance of precise intragastric pH monitoring. Traditional methods using fluorescent probes face challenges due to their faint solid‐state fluorescence, limited target specificity, and accuracy. To overcome these obstacles, pH‐responsive fluorescent organic microparticles decorated with magnetite (Fe3O4) nanoparticles are engineered. These microrobots exhibit a unique fluorescence switching capability at a critical pH, enabling the monitoring of gastric acidity. The magnetic part of these microrobots ensures magnetic maneuverability to enable targeted navigation. The microrobots’ fluorescence switching mechanism is elucidated through comprehensive spectroscopy, microscopy, and X‐ray diffraction analyses, revealing molecular‐level structural transformations upon interaction with gastric acid and antacids. These transformations, specifically protonation and deprotonation of the microrobots’ fluorescent components, prompt a distinct fluorescence response correlating with pH shifts. In vitro and ex vivo experiments, simulating stomach conditions, confirm the microrobots’ efficacy in pH‐responsive imaging. The results showcase the promising diagnostic potential of microrobots for gastrointestinal tract diseases, marking a significant advancement in imaging‐based medical diagnostics at targeted locations.

Conquering new grounds: plant organellar C-to-U RNA editing factors can be functional in the plant cytosol.

Plant mitochondrial and chloroplast transcripts are subject to numerous events of specific cytidine-to-uridine (C-to-U) RNA editing to correct genetic information. Key protein factors for this process are specific RNA-binding pentatricopeptide repeat (PPR) proteins, which are encoded in the nucleus and post-translationally imported into the two endosymbiotic organelles. Despite hundreds of C-to-U editing sites in the plant organelles, no comparable editing has been found for nucleo-cytosolic mRNAs raising the question why plant RNA editing is restricted to chloroplasts and mitochondria. Here, we addressed this issue in the model moss Physcomitrium patens, where all PPR-type RNA editing factors comprise specific RNA-binding and cytidine deamination functionalities in single proteins. To explore whether organelle-type RNA editing can principally also take place in the plant cytosol, we expressed PPR56, PPR65 and PPR78, three editing factors recently shown to also function in a bacterial setup, together with cytosolic co-transcribed native targets in Physcomitrium. While we obtained unsatisfying results upon their constitutive expression, we found strong cytosolic RNA editing under hormone-inducible expression. Moreover, RNA-Seq analyses revealed varying numbers of up to more than 900 off-targets in other cytosolic transcripts. We conclude that PPR-mediated C-to-U RNA editing is not per se incompatible with the plant cytosol but that its limited target specificity has restricted its occurrence to the much less complex transcriptomes of mitochondria and chloroplast in the course of evolution.

Current Advancements in Anti-Cancer Chimeric Antigen Receptor T Cell Immunotherapy and How Nanotechnology May Change the Game.

Chimeric antigen receptor (CAR)-T cell immunotherapy represents a cutting-edge advancement in the landscape of cancer treatment. This innovative therapy has shown exceptional promise in targeting and eradicating malignant tumors, specifically leukemias and lymphomas. However, despite its groundbreaking successes, (CAR)-T cell therapy is not without its challenges. These challenges, particularly pronounced in the treatment of solid tumors, include but are not limited to, the selection of appropriate tumor antigens, managing therapy-related toxicity, overcoming T-cell exhaustion, and addressing the substantial financial costs associated with treatment. Nanomedicine, an interdisciplinary field that merges nanotechnology with medical science, offers novel strategies that could potentially address these limitations. Its application in cancer treatment has already led to significant advancements, including improved specificity in drug targeting, advancements in cancer diagnostics, enhanced imaging techniques, and strategies for long-term cancer prevention. The integration of nanomedicine with (CAR)-T cell therapy could revolutionize the treatment landscape by enhancing the delivery of genes in (CAR)-T cell engineering, reducing systemic toxicity, and alleviating the immunosuppressive effects within the tumor microenvironment. This review aims to explore how far (CAR)-T cell immunotherapy has come alone, and how nanomedicine could strengthen it into the future. Additionally, the review will examine strategies to limit the off-target effects and systemic toxicity associated with (CAR)-T cell therapy, potentially enhancing patient tolerance and treatment outcomes.

Cancer therapy with antibodies.

The greatest challenge in cancer therapy is to eradicate cancer cells with minimal damage to normal cells. Targeted therapy has been developed to meet that challenge, showing a substantially increased therapeutic index compared with conventional cancer therapies. Antibodies are important members of the family of targeted therapeutic agents because of their extraordinarily high specificity to the target antigens. Therapeutic antibodies use a range of mechanisms that directly or indirectly kill the cancer cells. Early antibodies were developed to directly antagonize targets on cancer cells. This was followed by advancements in linker technologies that allowed the production of antibody-drug conjugates (ADCs) that guide cytotoxic payloads to the cancer cells. Improvement in our understanding of the biology of T cells led to the production of immune checkpoint-inhibiting antibodies that indirectly kill the cancer cells through activation of the T cells. Even more recently, bispecific antibodies were synthetically designed to redirect the T cells of a patient to kill the cancer cells. In this Review, we summarize the different approaches used by therapeutic antibodies to target cancer cells. We discuss their mechanisms of action, the structural basis for target specificity, clinical applications and the ongoing research to improve efficacy and reduce toxicity.

Radiolabelling and preclinical characterisation of [89Zr]Zr-Df-ATG-101 bispecific to PD-L1/4-1BB.

ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo. ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies. The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo. [89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101.

A Review for Uncovering the "Protein-Nanoparticle Alliance": Implications of the Protein Corona for Biomedical Applications.

Understanding both the physicochemical and biological interactions of nanoparticles is mandatory for the biomedical application of nanomaterials. By binding proteins, nanoparticles acquire new surface identities in biological fluids, the protein corona. Various studies have revealed the dynamic structure and nano-bio interactions of the protein corona. The binding of proteins not only imparts new surface identities to nanoparticles in biological fluids but also significantly influences their bioactivity, stability, and targeting specificity. Interestingly, recent endeavors have been undertaken to harness the potential of the protein corona instead of evading its presence. Exploitation of this 'protein-nanoparticle alliance' has significant potential to change the field of nanomedicine. Here, we present a thorough examination of the latest research on protein corona, encompassing its formation, dynamics, recent developments, and diverse bioapplications. Furthermore, we also aim to explore the interactions at the nano-bio interface, paving the way for innovative strategies to advance the application potential of the protein corona. By addressing challenges and promises in controlling protein corona formation, this review provides insights into the evolving landscape of the 'protein-nanoparticle alliance' and highlights emerging.

Harnessing Nanochaperone-Mediated Autophagy for Selective Clearance of Pathogenic Tau Protein in Alzheimer's Disease.

Accumulation of pathological tau is a hallmark of Alzheimer's disease (AD), which correlates more closely with cognitive impairment than does the amyloid-β (Aβ) burden. Autophagy is a powerful process for the clearance of toxic proteins including aberrant tau. However, compromised autophagy is demonstrated in neurodegeneration including AD, and current autophagy inducers remain enormously challenging due to inability of restoring autophagy pathway and lack of targeting specificity. Here, pathogenic tau-specific autophagy based on customized nanochaperone is developed for AD treatment. In this strategy, the nanochaperone can selectively bind to pathogenic tau and maintain tau homeostasis, thereby ensuring microtubule stability which is important for autophagy pathway. Meanwhile, the bound pathogenic tau can be sequestered in autophagosomes by in situ autophagy activation of nanochaperone. Consequently, autophagosomes wrapping with pathogenic tau are able to be trafficked along the stabilized microtubule to achieve successful fusion with lysosomes, resulting in the enhancement of autophagic flux and pathologic tau clearance. After treatment with this nanochaperone-mediated autophagy strategy, the tau burden, neuron damages, and cognitive deficits of AD mice are significantly alleviated in the brain. Therefore, this work represents a promising candidate for AD-targeted therapy and provides new insights into future design of anti-neurodegeneration drugs.

Computer-Aided Drug Discovery Approaches in the Identification of Anticancer Drugs from Natural Products: A Review.

Natural plant sources are essential in the development of several anticancer drugs, such as vincristine, vinblastine, vinorelbine, docetaxel, paclitaxel, camptothecin, etoposide, and teniposide. However, various chemotherapies fail due to adverse reactions, drug resistance, and target specificity. Researchers are now focusing on developing drugs that use natural compounds to overcome these issues. These drugs can affect multiple targets, have reduced adverse effects, and are effective against several cancer types. Developing a new drug is a highly complex, expensive, and time-consuming process. Traditional drug discovery methods take up to 15 years for a new medicine to enter the market and cost more than one billion USD. However, recent Computer Aided Drug Discovery (CADD) advancements have changed this situation. This paper aims to comprehensively describe the different CADD approaches in identifying anticancer drugs from natural products. Data from various sources, including Science Direct, Elsevier, NCBI, and Web of Science, are used in this review. In-silico techniques and optimization algorithms can provide versatile solutions in drug discovery ventures. The structure-based drug design technique is widely used to understand chemical constituents' molecular-level interactions and identify hit leads. This review will discuss the concept of CADD, in-silico tools, virtual screening in drug discovery, and the concept of natural products as anticancer therapies. Representative examples of molecules identified will also be provided.

Current Expansion of Silver and Gold Nanomaterials towards Cancer Theranostics: Development of Therapeutics

Abstract: Nanomaterial-based therapeutics is an emerging tool for the treatment of numerous types of cancer. Various types of polymeric, lipid and inorganic nanoparticles (NPs) result in a wider series of applications in cancer diagnosis and therapeutics. The NPs properties are due to high surface area to volume ratio, surface plasmon resonance, absorption in the visible spectrum and light scattering. These unique characteristics of NPs arise due to their optical surface properties for conjugation/surface modification and smaller size. In cancer therapeutics, NPs based products are used as a biomarker for early detection/diagnosis of tumours, drug nano-conjugates for the delivery of chemotherapeutic drugs to the tumour-specific site, chemo-protective agents, etc. : Furthermore, other advantages of NPs are biocompatibility, lesser toxicity, enhanced permeability and retention effect, higher stability, and specific targeting with a selective accumulation of nano drugs in the tissue of the tumour. The selective targeting of NPs to tumour tissue is possible by adding surface-active targeting agents i.e., antibodies. The selective transport of drug NPs conjugates to the cancer cells is increased and extravagated due to permeable vasculature from endothelial cells gap while failing the transport of drug NPs conjugates in normal cells. This review emphasizes metallic NPs, including silver NPs (AgNPs) and gold NPs (AuNPs), which are extensively reconnoitered in various applications in cellular targeting, imaging, drug delivery, DNA-NPs conjugates for biosensor/point of care devices development, photothermal/photodynamic therapy, protein-protein interaction, etc. In addition, this review discussed different synthetic methods of AgNPs and AuNPs and characterization methods. Furthermore, it highlighted the different properties and applications of AgNPs and AuNPs in cancer theranostics.

One-pot assay using a target-driven split aptamer recognition and assembly strategy for convenient and rapid detection of gliotoxin

An aptamer targeting gliotoxin (GTX) was optimized to increase the binding affinity by approximately 20 times and achieve higher structural stability and targeting specificity. Molecular dynamics simulations were used to explore the molecular mechanism and key action sites underlying the recognition of GTX by the optimized aptamer. Subsequently, the optimized aptamer was split into two fragments and a convenient and rapid one-pot assay for GTX detection was successfully established using a target-driven split aptamer recognition and assembly strategy. The method exhibited a good linear range of 0.128 nM to 2 μM, a low detection limit of 0.07 nM, and excellent selectivity for GTX. Furthermore, the method had good accuracy and stability in real sample analysis. Therefore, the developed one-pot method provides a reliable, convenient, and cost-effective approach for the widespread application of GTX detection.

Context Disentangling and Prototype Inheriting for Robust Visual Grounding.

Visual grounding (VG) aims to locate a specific target in an image based on a given language query. The discriminative information from context is important for distinguishing the target from other objects, particularly for the targets that have the same category as others. However, most previous methods underestimate such information. Moreover, they are usually designed for the standard scene (without any novel object), which limits their generalization to the open-vocabulary scene. In this paper, we propose a novel framework with context disentangling and prototype inheriting for robust visual grounding to handle both scenes. Specifically, the context disentangling disentangles the referent and context features, which achieves better discrimination between them. The prototype inheriting inherits the prototypes discovered from the disentangled visual features by a prototype bank to fully utilize the seen data, especially for the open-vocabulary scene. The fused features, obtained by leveraging Hadamard product on disentangled linguistic and visual features of prototypes to avoid sharp adjusting the importance between the two types of features, are then attached with a special token and feed to a vision Transformer encoder for bounding box regression. Extensive experiments are conducted on both standard and open-vocabulary scenes. The performance comparisons indicate that our method outperforms the state-of-the-art methods in both scenarios.