Specific Target Research Articles

Development and Biological Characterization of Cancer Biomimetic Membrane Nanovesicles for Enhancing Therapy Efficacy in Human Glioblastoma Cells

As nanocarriers of a new generation, biomimetic nanovesicles are an emerging class of therapeutic tools whose surface is integrated or fabricated with biomaterials capable of mimicking the biological features and functions of native cells. Thanks to this, biomimetic nanovesicles, in particular, those made by plasma membrane moieties, possess greatly improved biocompatibility, high target specificity, a long retention time, and minimal undesired immune responses. For these reasons, a multitude of progenitor cells including cancer ones were employed as templates to generate biomimetic or membrane-camouflaged nanovesicles hosting different therapeutic compounds. In this contribution, different membrane-derived biomimetic vesicles (M-NVs) were generated by osmotic lysis or plasma membrane isolation approaches from normal and cancer cell lines and assayed against in vitro models of human glioblastoma. M-NVs were compared in their cellular internalization degrees of DNA and proteins, morphologically and molecularly characterized, expressing an extracellular membrane-associated marker. Then, Rose Bengal (RB), a photoactivable drug characterized by a relatively low cellular uptake, was incorporated into nascent glioblastoma-derived M-NVs and finally administered to homotypic receiving cells, showing an increased degree of internalization as well as induced cytotoxic effects, even in the absence of photodynamic direct stimulation. Similar results were also obtained assaying lyophilized M-NVs loaded with RB. In conclusion, M-NVs generated by cell membranes effectively deliver several cargoes, including therapeutic molecules, maintain functionality after lyophilization, and show significant internalization effects, making them a promising strategy for therapeutic applications against human glioblastoma cells.

SQ31f is a potent non-tuberculous mycobacteria antibiotic by specifically targeting the mycobacterial F-ATP synthase.

Non-tuberculous mycobacteria (NTM) infection presents a growing global health problem and requires new antibiotics targeting enzymes that are essential for the pathogens under various metabolic conditions, with high target specificity, good solubility and with attractive combinatory potency. SQ31f was synthesized by a simplified synthesis protocol, and its effect on growth inhibition of fast- and slow-growing NTM and clinical isolates, whole-cell ATP depletion, ex vivo macrophages and its potency in combination with other antibiotics were evaluated. Molecular docking studies were employed to assess SQ31f's binding mode. We present- squaramide SQ31f as a novel anti-NTM inhibitor targeting the NTM F1FO-ATP synthase, essential for ATP formation, regulation of ATP homeostasis and proton motive force under multiple growth conditions. The potency of SQ31f in growth inhibition of fast- and slow-growing NTM and clinical isolates correlates with whole-cell ATP depletion, which is not caused by altered oxygen consumption. SQ31f's high aqueous solubility enables binding to the waterfilled cytosolic proton half channel in the subunits a-c interface of the FO domain. As presented for the fast-growing Mycobacterium abscessus, the compound is active against intracellular-residing M. abscessus. Importantly, SQ31f shows an additive effect of the anti-M. abscessus drugs clofazimine, rifabutin or amikacin, and an attractive potentiation of linezolid, clarithromycin, or the oral pair tebipenem and avibactam. SQ31f represents an attractive inhibitor to tackle the issues associated with NTM drug tolerance and toxicity. Its combinatory potency with anti-M. abscessus drugs holds potential for overcoming resistance, while also reducing intensive compound synthesis and associated costs.

Machine Learning Framework for Conotoxin Class and Molecular Target Prediction

Conotoxins are small and highly potent neurotoxic peptides derived from the venom of marine cone snails which have captured the interest of the scientific community due to their pharmacological potential. These toxins display significant sequence and structure diversity, which results in a wide range of specificities for several different ion channels and receptors. Despite the recognized importance of these compounds, our ability to determine their binding targets and toxicities remains a significant challenge. Predicting the target receptors of conotoxins, based solely on their amino acid sequence, remains a challenge due to the intricate relationships between structure, function, target specificity, and the significant conformational heterogeneity observed in conotoxins with the same primary sequence. We have previously demonstrated that the inclusion of post-translational modifications, collisional cross sections values, and other structural features, when added to the standard primary sequence features, improves the prediction accuracy of conotoxins against non-toxic and other toxic peptides across varied datasets and several different commonly used machine learning classifiers. Here, we present the effects of these features on conotoxin class and molecular target predictions, in particular, predicting conotoxins that bind to nicotinic acetylcholine receptors (nAChRs). We also demonstrate the use of the Synthetic Minority Oversampling Technique (SMOTE)-Tomek in balancing the datasets while simultaneously making the different classes more distinct by reducing the number of ambiguous samples which nearly overlap between the classes. In predicting the alpha, mu, and omega conotoxin classes, the SMOTE-Tomek PCA PLR model, using the combination of the SS and P feature sets establishes the best performance with an overall accuracy (OA) of 95.95%, with an average accuracy (AA) of 93.04%, and an f1 score of 0.959. Using this model, we obtained sensitivities of 98.98%, 89.66%, and 90.48% when predicting alpha, mu, and omega conotoxin classes, respectively. Similarly, in predicting conotoxins that bind to nAChRs, the SMOTE-Tomek PCA SVM model, which used the collisional cross sections (CCSs) and the P feature sets, demonstrated the highest performance with 91.3% OA, 91.32% AA, and an f1 score of 0.9131. The sensitivity when predicting conotoxins that bind to nAChRs is 91.46% with a 91.18% sensitivity when predicting conotoxins that do not bind to nAChRs.

Engineering Solutions for Drug Delivery System

This paper examines the evolution of engineering solutions in drug delivery systems, emphasizing the role of nanotechnology in overcoming current challenges in precision medicine. It addresses key challenges in drug delivery, including targeting specificity, minimizing adverse effects, and enhancing the efficiency of drug carriers. Both top-down and bottom-up engineering approaches are examined, with case studies highlighting successful applications in cancer therapy, gene delivery, and implantable devices. The paper also investigates future trends, such as smart and active delivery systems, and discusses the interdisciplinary collaboration required for these advances. By integrating material science, bioengineering, and pharmaceutical technology, this research presents innovative solutions aimed at improving therapeutic efficacy and minimizing toxicity. Keywords: Drug delivery systems, Nanotechnology, Top-down engineering, Bottom-up engineering, Gene therapy, Smart drug delivery.

Macrophage membrane-mediated targeted curcumin biomimetic nanoparticles delivery for diagnosis and treatment of spinal cord injury by suppressing neuroinflammation and ferroptosis

Spinal cord injury (SCI) is a severe and debilitating central nervous system disorder characterized by permanent motor and sensory deficits, with limited effective treatment options available. Recent advancements have been made in the functionalization of biomimetic surfaces of nanoparticles through the incorporation of synthetic bionic and naturally derived cell membranes. One emerging strategy involves integrating biomimetic features into therapeutic agents to achieve low immunogenicity, high targeting specificity, and prolonged drug half-life. In this study, we detail the preparation of nanoparticles via the self-assembly of the amphiphilic diblock copolymer PEG-b-PHPMA with curcumin and PCPDTBT in water, followed by macrophage cell membrane coating using an extrusion method, resulting in the formation of stable curcumin-loaded nanoparticles coated with cell membrane (MM@Cur). Our experimental results demonstrate that MM@Cur treatment specifically targets the SCI site, effectively mitigates ferroptosis and central inflammation in a mouse model featuring spinal cord contusion, and enhances the recovery of the motor function of hind limbs post-SCI. Therefore, our findings highlight MM@Cur as a highly targeted biomimetic nanoparticle possessing potent anti-ferroptosis and anti-inflammatory properties, offering a promising therapeutic approach for the restoration of hind limb function post-spinal cord injury

Neutrophil-Mimetic Upconversion Photosynthetic Nanosystem Derived from Microalgae for Targeted Treatment of Thromboembolic Stroke.

Thromboembolic stroke constitutes the majority of brain strokes, resulting in elevated mortality and morbidity rates, as well as significant societal and economic burdens. Although intravenous thrombolysis serves as the standard clinical treatment, its narrow therapeutic window and the inflammatory response induced by tissue plasminogen activator (tPA) administration limit its efficacy. In the initial stages of stroke, the abrupt cessation of blood flow leads to an energy metabolism disorder, marked by a substantial decrease in adenosine triphosphate (ATP) and nicotinamide adenine dinucleotide phosphate (NADPH) levels, causing irreversible damage to neural cells. In this study, we introduce a neutrophil-mimetic, microalgae-derived upconversion photosynthetic nanosystem designed for targeted treatment of thromboembolic stroke. This system features upconversion nanoparticles coated with a thylakoid membrane and wrapped in an activated neutrophil membrane, further decorated with ROS-responsive thrombolytic tPA on its surface. The neutrophil-mimetic design facilitates high targeting specificity and accumulation at the thrombus site after intravenous administration. Upon exposure to elevated levels of reactive oxygen species (ROS) at the thrombus location, the nanosystem promptly demonstrated potent thrombolytic efficacy through the surface-modified tPA. Furthermore, near-infrared II (NIR-II) laser irradiation activated the generation of ATP and NADPH, which inhibited inflammatory cell infiltration, platelet activation, oxidative stress, and neuronal injury. This constructed nanoplatform not only showcases exceptional targeting efficiency at the stroke site and controllable release of the thrombolytic agent but also facilitates ATP/NADPH-mediated thrombolytic, anti-inflammatory, antioxidative stress, and neuroprotective effects. Additionally, it offers valuable insights into the potential therapeutic applications of microalgae-based derivatives in managing thromboembolic stroke.

Macrophage-T cell hybrid membrane-camouflaged biomimetic nanoparticles ameliorate autoimmune myocarditis via suppressing macrophage pyroptosis by target gene silencing

Abstract Background Current management of myocarditis mainly relies on conventional approaches and immunosuppressive therapies. However, these strategies often yield limited efficacy. Our previous research revealed the pivotal role of macrophage pyroptosis in myocarditis pathogenesis. Therefore, targeted intervention to inhibit macrophage pyroptosis may provide new insights into myocarditis treatment. Purpose We previously identified interferon regulatory factor 1 (IRF1) as the key modulator of macrophage pyroptosis in myocarditis. In this study, we synthesized a nano-delivery platform consisting of a macrophage-T cell hybrid membrane-coated zeolitic imidazolate framework-8 (ZIF-8) encapsulating IRF1-small interfering RNA (siRNA@ZIF@HM). We aimed to evaluate its targeting capability and therapeutic efficacy for macrophage pyroptosis in myocarditis. Methods The fabrication of siRNA@ZIF@HM was validated using transmission electron microscopy (TEM) and dynamic light scattering (DLS). Cellular uptake, cytotoxicity, endolysosome escape, IRF1 silencing, and anti-pyroptotic effect were assessed using mouse bone marrow-derived macrophages and the mouse macrophage cell line J774A.1 and RAW264.7. An experimental autoimmune myocarditis (EAM) mouse model was induced in Balb/c mice for in vivo investigations. Pharmacokinetics and targeting capability were determined with ex vivo fluorescence imaging and immunofluorescence staining. Subsequently, mice were randomly allocated into control, EAM + siRNA, EAM + siRNA@ZIF, and EAM + siRNA@ZIF@HM groups to assess the therapeutic efficacy. Additionally, the biodistribution and biosafety of siRNA@ZIF@HM were also evaluated. Results TEM, DLS, and element mapping confirmed the successful fabrication of siRNA@ZIF@HM, with a diameter of approximately 130 nm. The nanoparticle exhibited pH responsiveness and membrane markers of macrophage and T lymphocytes (Figure 1). It demonstrated high targeting specificity for pro-inflammatory macrophages and myocarditis. Immunofluorescence microscopy revealed successful endolysosome escape of IRF1-siRNA in macrophages. Consequently, the nanoparticle significantly silenced IRF1 protein expression and suppressed macrophage pyroptosis both in vivo and in vitro, resulting in the amelioration of autoimmune myocarditis (Figure 2). Furthermore, the nanoparticle showed good biocompatibility with no significant changes observed in other organs. Conclusions The pH-responsive, macrophage-T cell hybrid membrane-coated biomimetic nanoparticle demonstrates promising capability for targeted siRNA delivery to myocardial inflammation sites, particularly pro-inflammatory macrophages. Additionally, targeting IRF1-mediated macrophage pyroptosis represents a potential therapeutic strategy for myocarditis treatment.Figure 1Figure 2

Engineering Stimuli-Responsive Materials for Precision Medicine.

Over the past decade, precision medicine has garnered increasing attention, making significant strides in discovering new therapeutic drugs and mechanisms, resulting in notable achievements in symptom alleviation, pain reduction, and extended survival rates. However, the limited target specificity of primary drugs and inter-individual differences have often necessitated high-dosage strategies, leading to challenges such as restricted deep tissue penetration rates and systemic side effects. Material science advancements present a promising avenue for these issues. By leveraging the distinct internal features of diseased regions and the application of specific external stimuli, responsive materials can be tailored to achieve targeted delivery, controllable release, and specific biochemical reactions. This review aims to highlight the latest advancements in stimuli-responsive materials and their potential in precision medicine. Initially, we introduce disease-related internal stimuli and capable external stimuli, elucidating the reaction principles of responsive functional groups. Subsequently, we provide a detailed analysis of representative pre-clinical achievements of stimuli responsive materials across various clinical applications, including enhancements in the treatment of cancers, injury diseases, inflammatory diseases, infection diseases, and high-throughput microfluidic biosensors. Finally, we discuss some clinical challenges, such as off-target effects, long-term impacts of nano-materials, potential ethical concerns, and offer insights into future perspectives of stimuli-responsive materials.

Human epidermal growth factor receptor 2(Her2)-targeted pH-responsive MR/NIRF bimodal imaging-mediated nano-delivery system for the diagnosis and treatment of undifferentiated thyroid cancer.

Undifferentiated thyroid cancer (ATC) is highly malignant and does not respond well to sorafenib (SRF) treatment owing to the lack of specificity of SRF targeting. Drug delivery nanosystems can improve the efficiencies of drug in treating various cancer types. However, many conventional drug delivery nanosystems lack targeting and exhibit unresponsive drug release. Therefore, we developed a pH-responsive nano-targeted drug delivery systems using human serum albumin (HSA) as a carrier to generate manganese dioxide (MnO2)@HSA nanoparticles (NPs), then encapsulated SRF and the fluorescent dye indocyanine green (ICG) and finally modifyed the targeting antibody pertuzumab in the outer layer of the nano complexes, resulting in SRF/ICG/MnO2@HSA-pertuzumab (HISMP) NPs. This system targets human epidermal growth factor receptor 2 on the cell membrane surface of thyroid cancer cells and is designed to accumulate at tumor sites. Then, pH-responsive release of divalent manganese ions, ICG, and SRF enables magnetic resonance/fluorescence (MR/NIRF) dual-modality imaging and precise drug delivery for diagnostic and therapeutic integration. Various characterization analyses including transmission electron microscopy, Fourier infrared spectroscopy, and particle size analysis confirm that we successfully synthesized HISMP NPs with a diameter of 150.709nm. The results of CCK8 cytotoxicity and apoptosis assays show that HISMP NPs exhibited high cytotoxicity and induce apoptosis in thyroid cancer cells. In vivo MR/NIRF imaging experiments confirmed that the HISMP NPs specifically aggregated at tumor sites and have good in vivo MR/NIRF imaging ability and effective anti-tumor activity. The nano-delivery system is expected to provide a theoretical foundation for the efficient ATC diagnosis and therapy.

Artificial Internalizing Receptors: Intracellular Delivery of Cargo Through Bio-Orthogonal Recognition.

Drug targeting is a methodology that helps to overcome the side effects of therapeutic molecules. However, insufficient targeting specificity and the on-target/off-site delivery leave much room for improvement in the targeting endeavors. One approach to enhance the specificity of drug targeting is to engineer artificial receptors with recognition ligands not observed in nature. To this end, artificial internalizing receptors that feature cholesterylamine as the artificial pull-in mechanism, and an anti-fluorescein antibody as the exofacial recognition and capture tool are developed. Fluorescein labeling is among the most routine techniques in biochemistry and can readily provide a way to make cognate derivatives for receptor-mediated endocytosis using these artificial receptors. Herein, the synthesis and the structure-activity relationship for these artificial receptors are detailed, their potency and efficacy in mediating drug delivery for the antibody-drug conjugates are illustrated, and the scope and limitations of targeting the chemically engineered cells via artificial receptors are investigated. Taken together, the presented data explore an innovative approach to drug targeting and contribute to the development of techniques in cell engineering using the tools of chemistry.

Targeted Therapy in Breast Cancer: Advantages and Advancements of Antibody-Drug Conjugates, a Type of Chemo-Biologic Hybrid Drugs.

Cancer is a significant health challenge globally, with millions of people affected every year, resulting in high morbidity and mortality. Although other treatment options are available with limitations, chemotherapy, either standalone or combined with other therapeutic procedures, is the most commonly used practice of treating cancer. In chemotherapy, cancer cells/malignant tumors are targeted; however, due to less target specificity, along with malignant cells, normal cells are also affected, which leads to various off-target effects (side effects) that impact the patient quality of life. Out of all the different types of cancers, breast cancer is the most common type of cancer in humans worldwide. Current anticancer drug discovery research aims to develop therapeutics with higher potency and lower toxicity, which is only possible through target-specific therapy. Antibody-drug conjugates (ADCs) are explicitly designed to target malignant tumors and minimize off-target effects by reducing systemic cytotoxicity. Several ADCs have been approved for clinical use and have shown moderate to good efficacy so far. Considering various aspects, chemotherapy and ADCs are useful in treating cancer. However, ADCs provide a more focused and less toxic approach, which is especially helpful in cases where resistance to chemotherapy (drug resistance) occurs and in the type of malignancies in which specific antigens are overexpressed. Ongoing ADC research aims to develop more target-specific cancer treatments. In short, this study presents a concise overview of ADCs specific to breast cancer treatment. This study provides insight into the classifications, mechanisms of action, structural aspects, and clinical trial phases (current status) of these chemo-biologic drugs (ADCs).

An internal loop region is responsible for inherent target specificity of bacterial Cold-shock proteins.

Cold shock proteins (Csps), of around 70 amino acids, share a protein fold for the cold shock domain (CSD) that contains RNA binding motifs, RNP1 and RNP2, and constitute one family of bacterial RNA-binding proteins. Despite similar amino acid composition, Csps have been shown to individually possess inherent specific functions. Here we identify the molecular differences in Csps that allow selective recognition of RNA targets. Using chimeras and mutants of Escherichia coli CspD and CspA, we demonstrate that Lys43-Ala44 in an internal loop of CspD and the N-terminal portion with Lys4 of CspA are important for determining their target specificities. Pull-down assays suggest these distinct specificities reflect differences in the ability to act on the target RNAs rather than differences in binding to the RNA targets. A phylogenetic tree constructed from 1,573 Csps reveals that the Csps containing Lys-Ala in the loop form a monophyletic clade, and the members in this clade are shown to have target specificities similar to E. coli CspD. The phylogenetic tree also finds a small cluster of Csps containing Lys-Glu in the loop, and these exhibit different specificity than E. coli CspD. Examination of this difference suggests a role of the loop of CspD type proteins in recognition of specific targets. Additionally, each identified type of Csp shows a different distribution pattern among bacteria. Our findings provide a basis for subclassification of Csps based on target RNA specificity, which will be useful for understanding of the functional specialization of Csps.

Structure-Activity Relationships and Target Selectivity of Phenylsulfonylamino-Benzanilide Inhibitors Based on S1647 at the SLC10 Carriers ASBT, NTCP, and SOAT.

The intestinal bile acid carrier ASBT (SLC10A2), the hepatic bile acid carrier NTCP (SLC10A1), and the steroid sulfate carrier SOAT (SLC10A6), all members of the solute carrier family SLC10, are established drug targets. The ASBT inhibitors odevixibat, maralixibat, and elobixibat are used to treat intrahepatic cholestasis, cholestatic pruritus, and obstipation. The peptide drug bulevirtide blocks binding of the hepatitis B and D viruses to NTCP and thereby inhibits the virus's entry into hepatocytes. Experimental SOAT inhibitors have antiproliferative effects on hormone-dependent breast cancer cells. The phenylsulfonylamino-benzanilide S1647 is an inhibitor of ASBT and SOAT. The present study aimed to comparatively analyze a set of newly synthesized and commercially available S1647 derivatives for their transport inhibition against ASBT, NTCP, and SOAT. Structure-activity relationships were systematically analyzed regarding potency and target specificity to elucidate whether this compound class is worth being further developed in preclinical studies for pharmacological ASBT, NTCP, and/or SOAT inhibition.

Hydrogel-based fluorescence assay kit for simultaneous determination of ceftazidime and avibactam

Monitoring the concentration of antibiotics rapidly and cost-effectively is crucial for accurate clinical medication and timely identification of drug-induced illnesses. Here, we constructed a novel fluorescent assay kit to monitor Zavicefta, an effective antibiotic composed of avibactam (AVI) and ceftazidime (CFZ) to treat carbapenem-resistant gram-negative bacteria infections. AVI can emit fluorescence, but CFZ cannot. To enable simultaneous measurement of both in one kit, we designed molecularly imprinted polymer (MIP) modified quantum dots (QDs) for CFZ determination. MIPs have received significant attention as an artificial antibody due to their exceptional specificity for various targets, particularly drugs with small molecular weight. Under the excitation wavelength of 350 nm, the detection process involves a decrease in QDs’ fluorescence signal at 600 nm owing to the “gate effect” between MIP and CFZ and the internal filtration effect between CFZ and QDs. Simultaneously, a fluorescence emission characteristic peak at 420 nm for AVI emerges. In addition, to simplify the operation procedure and improve determination throughput, the detection agents were incorporated into a hydrogel and placed in a 96-well plate, enabling concurrent quantification of AVI and CFZ within the respective range of 80–1000 μM and 1–1000 μM. The developed assay kit successfully determined AVI and CFZ in human serums and therapeutic drug monitoring in a live rabbit model. Recoveries of AVI and CFZ were 92.7–114%, with relative standard deviations below 6.0%. Moreover, a smartphone was employed to read the fluorescence signals, which was beneficial for cost reduction and out-of-lab analysis. This study will deliver a pragmatic resolution to developing high-throughput assay kits for drug determination.Graphical

Endothelium-targeted NF-κB siRNA nanogel for magnetic resonance imaging and visualized-anti-inflammation treatment of atherosclerosis

Atherosclerosis-induced lethal cardiovascular disease remains a severe healthcare threat due to the limited drug efficiency and untimely prediction of high-risk events caused by inadequate target specificity of medications, incapable recognition of insensitive patients, and variable morphology of vulnerable plaques. Therefore, it is necessary to develop efficient strategies to improve the diagnosis accuracy and achieve visualized treatment of atherosclerosis. Herein, we establish an inflamed endothelium-targeted three-in-one nucleic acid nanogel system that can reverse the inflammatory state of endothelial cells (ECs) in plaques and simultaneously achieve real-time monitoring of the therapy process for efficient atherosclerosis diagnosis and treatment. For this purpose, contrast agent (Gd-DOTA) and VCAM-1-targeted peptide (VP) are first covalently conjugated onto DNA strands by click reaction respectively, which could self-assemble into Y-shaped structures (Gd-Y1 and VP-Y2 motifs) with magnetic resonance (MR) imaging and endothelium targeting capacities. Thereafter, NF-κB subunit p65-targeting siRNA (siNF-κB) is crosslinked with Gd-Y1 and VP-Y2 motifs to construct the endothelium-targeting nanogel platform. With contrast agents inside, the nanogel enables MR-based diagnosis and visualized therapy of atherosclerosis, providing accurate prognostic analysis and indications for treatment results, which ensures timely disclosure of insensitive individuals and avoids acute lethal events. By delivering siNF-κB to inflammatory endothelium, the nanogel significantly regresses plaques in both the aorta and carotid artery with reduced inflammation cytokines, collagens, macrophages, and apoptotic cells, providing a potential anti-inflammation strategy to treat atherosclerosis and avoid acute cardiovascular disease.

Emerging RNAi Therapies to Treat Hypertension.

Hypertension (HTN), often dubbed the "silent killer," poses a significant global health challenge, affecting over 1.3 billion individuals. Despite advances in treatment, effective long-term blood pressure (BP) control remains elusive, necessitating novel therapeutic approaches. Poor control of BP remains a leading cause of cardiovascular morbidity and mortality worldwide and is becoming an even larger global health problem due to the aging population, rising rates of obesity, poorer dietary patterns and overall cardiometabolic health, and suboptimal rates of patient adherence and optimal BP control. Ribonucleic acid interference (RNAi) technology, which leverages the body's natural gene-silencing mechanism, has emerged as a promising strategy for several diseases and has recently been tested for its antihypertensive effects. We systematically reviewed peer-reviewed articles from databases including PubMed, EMBASE, and Scopus for studies examining RNAi's role in managing HTN, focusing on mechanisms, clinical utility, and safety profile. Key early-phase trials of some RNAi-leading candidate drugs are detailed. Also highlighted are challenges such as target specificity, delivery mechanisms, durability of effect, and immunogenicity. We conclude by summarizing how RNAi has a significant potential role in HTN therapy due to their unique benefits, such as long-term duration of action, infrequent dosing, and lack of major side effects.

Intersecting Peptidomics and Bioactive Peptides in Drug Therapeutics

Abstract: Peptidomics is the study of total peptides that describe the functions, structures, and interactions of peptides within living organisms. It comprises bioactive peptides derived naturally or synthetically designed that exhibit various therapeutic properties against microbial infections, cancer progression, inflammation, etc. With the current state of the art, Bioinformatics tools and techniques help analyse large peptidomics data and predict peptide structure and functions. It also aids in designing peptides with enhanced stability and efficacy. Peptidomics studies are gaining importance in therapeutics as they offer increased target specificity with the least side effects. The molecular size and flexibility of peptides make them a potential drug candidate for designing protein-protein interaction inhibitors. These features increased their drug potency with the considerable increase in the number of peptide drugs available in the market for various health commodities. The present review extensively analyses the peptidomics field, focusing on different bioactive peptides and therapeutics, such as anticancer peptide drugs. Further, the review provides comprehensive information on in silico tools available for peptide research. The importance of personalised peptide medicines in disease therapy is discussed along with the case study. Further, the major limitations of peptide drugs and the different strategies to overcome those limitations are reviewed.

How Biologics Have Changed the Drug Discovery Landscape.

Advances in molecular biology and molecular genetics as well as major scientific breakthroughs in immunology and oncology have led to the rapid growth of biologic therapeutics. Their success has resulted in significant changes to virtually every step in the drug discovery and development process. Biologics are produced by living organisms, and screening libraries are generated by immunization or phage display. Lead optimization utilizes sophisticated protein engineering to improve drug-like properties and targeting specificity. The manufacturing process for biologics is complex and requires highly specialized facilities. Determination of pharmacology and safety must overcome the complications associated with species specificity. Initial clinical testing must proceed more slowly and carefully due to the limited predictive utility of preclinical data. In summary, the drug discovery and development process has been dramatically altered by biologic therapeutics and will continue to evolve with the introduction of messenger RNA-based therapeutics and the application of artificial intelligence.

Present Scenario and Future Landscape of Payloads for ADCs: Focus on DNA-Interacting Agents

ADCs have emerged as a promising class of therapeutics, combining the targeting specificity of monoclonal antibodies with the cytotoxic potency of small-molecule drugs. Although the majority of approved ADCs are still based on microtubule binder payloads, the recent success of topoisomerase I inhibitors has revitalized interest in the identification of novel agents overcoming present limitations in the field including narrow therapeutic window and chemoresistance. The success of DNA binders as payload for ADCs has been very limited, up to now, due, among other factors, to high hydrophobicity and planar chemical structures resulting in most cases in ADCs with a strong tendency to aggregate, poor plasma stability, and limited therapeutic index. Some of these molecules, however, continue to be of interest due to their favorable properties in terms of cytotoxic potency even in chemoresistant settings, bystander and immunogenic cell death effects, and known combinability with approved drugs. We critically evaluated several clinically tested ADCs containing DNA binders, focusing on payload physicochemical properties, cytotoxic potency, and obtained clinical results. Our analysis suggests that further exploration of certain chemical classes, specifically anthracyclines and duocarmycins, based on the optimization of physicochemical parameters, reduction of cytotoxic potency, and careful design of targeting molecules is warranted. This approach will possibly result in a novel generation of payloads overcoming the limitations of clinically validated ADCs.

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.