Specific Target Research Articles

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.

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.

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.

MHW-GAN: Multidiscriminator Hierarchical Wavelet Generative Adversarial Network for Multimodal Image Fusion.

Image fusion technology aims to obtain a comprehensive image containing a specific target or detailed information by fusing data of different modalities. However, many deep learning-based algorithms consider edge texture information through loss functions instead of specifically constructing network modules. The influence of the middle layer features is ignored, which leads to the loss of detailed information between layers. In this article, we propose a multidiscriminator hierarchical wavelet generative adversarial network (MHW-GAN) for multimodal image fusion. First, we construct a hierarchical wavelet fusion (HWF) module as the generator of MHW-GAN to fuse feature information at different levels and scales, which avoids information loss in the middle layers of different modalities. Second, we design an edge perception module (EPM) to integrate edge information from different modalities to avoid the loss of edge information. Third, we leverage the adversarial learning relationship between the generator and three discriminators for constraining the generation of fusion images. The generator aims to generate a fusion image to fool the three discriminators, while the three discriminators aim to distinguish the fusion image and edge fusion image from two source images and the joint edge image, respectively. The final fusion image contains both intensity information and structure information via adversarial learning. Experiments on public and self-collected four types of multimodal image datasets show that the proposed algorithm is superior to the previous algorithms in terms of both subjective and objective evaluation.

Synthetic Protocols, Structural Activity Relationship, and Biological Activity of Piperazine and its Derivatives.

The versatile basic structure of piperazine allows for the development and production of newer bioactive molecules that can be used to treat a wide range of diseases. Piperazine derivatives are unique and can easily be modified for the desired pharmacological activity. The two opposing nitrogen atoms in a six-membered piperazine ring offer a large polar surface area, relative structural rigidity, and more acceptors and donors of hydrogen bonds. These properties frequently result in greater water solubility, oral bioavailability, and ADME characteristics, as well as improved target affinity and specificity. Various synthetic protocols have been reported for piperazine and its derivatives. In this review, we focused on recently published synthetic protocols for the synthesis of the piperazine and its derivatives. The structure-activity relationship concerning different biological activities of various piperazine-containing drugs was also highlighted to provide a good understanding to researchers for future research on piperazines.

Theranostic Nanomaterials to Overcome the Challenges in Peptide-based Cancer Therapy

: Globally, the number of cancer cases and death rates are increasing, making it necessary to develop new and improved medications for the treatment of cancer.Owing to a broad range of physio-chemical properties, Antimicrobial Peptides (AMPs) possessing tumoricidal properties and Anticancer Peptides (ACPs) are promising alternatives for enhanced cancer therapy. Recently, biopharmaceuticals have changed the rules of radiation therapy and chemotherapy by introducing peptide therapy for cancer treatments. However, several limitations obstruct the clinical efficacy of peptide-based cancer therapies, which include limited target specificity, oral intake, and half-life payloads. The integration of theranostic nanomaterials could be facilitated as a transformative strategy to address these challenges and enhance the potential of peptide-based cancer therapy. Increasing applications of recent times of peptide-nano hybrids have addressed the crucial issues related to conventional peptide-based drug therapy by enhancing the druggability. This review aims to explore the impact of nano-formulated peptides as an anticancer agent, highlighting the involvement of nanotechnology as an enabling tool.

Phytocompounds and lipid-based drug delivery system for neurodegenerative diseases

Across the annals of time, organic molecules sourced from nature have found innumerable uses within the realms of healthcare, pharmaceuticals, and the study of living organisms. This abundant source of natural compounds has exhibited immense promise in the cure of diverse ailments, mainly neurodegenerative diseases owing to their minimum toxic and adverse effects. However, different challenges exist with phytocompounds from plants such as poor permeation, poor solubility (water/lipid), unsteadiness under extremely acidic pH conditions, and lack of targeting specificity. Furthermore, as a result of the existence of blood-brain barrier membrane and inconvenient pharmacokinetics characteristics of phytocompounds, their passage into the brain is constrained. In order to address this issue and augment the transportation of medications into the brain at a therapeutically effective level, it is imperative to formulate an innovative and pragmatic strategy. Many papers have shown that nanoformulations containing phytocompounds (resveratrol, quercetin, ferulic acid, curcumin, berberine, etc.) effectively improved many neurodegenerative diseases such as Parkinson’s, Alzheimer’s and Huntington’s diseases. This study provides an overview of phytocompounds that are used in nanosized lipid drug delivery systems. These systems are categorized according to lipid types and preparation techniques used in the formulation. Some studies regarding these systems and phytocompounds are also summarized.

Key Magnetized Exosomes for Effective Targeted Delivery of Doxorubicin Against Breast Cancer Cell Types in Mice Model.

Exosomes (Exos) are promising drug delivery systems due to their low immunogenicity, minimal toxicity, high biocompatibility, and effective delivery capabilities. However, addressing the cardiotoxicity and other toxic side effects associated with anthracyclines has proven challenging. In this study, we loaded doxorubicin (Dox) into Exos derived from human placental mesenchymal stem cells (MSCs) and modified them with carboxylated Fe3O4 nanoparticles (NPs) to create an Exo-Dox-NP delivery system. Using an external magnetic force (MF), we regulated the distribution of Exos for targeted Dox delivery in breast cancer treatment. We characterized and determined the drug-loading efficiency of Exo-Dox-NPs, their uptake by tumor cells, and the modulation of drug release. The therapeutic efficacy of Exo-Dox-NPs was evaluated through both in vitro and in vivo anti-tumor experiments. Our results indicated that Exo-Dox-NPs remain stable in the bloodstream while releasing the drug in the acidic environment of tumor cells and their lysosomes. As a drug delivery system, Exo-Dox-NPs enhanced Dox absorption by tumor cells, demonstrating high targeting specificity. Moreover, Exo-Dox-NPs inhibited the migration of breast cancer cells, as confirmed by scratch migration and Transwell Matrigel invasion assays. In vivo experiments confirmed the effective targeting and delivery of Dox to malignant tumors using Exo-Dox-NPs/MFs, with the Exo-Dox-NP/MF formulation exhibiting the most potent anti-tumor activity. The utilization of Exos as carriers for Dox showed promising efficacy in breast cancer management. Carboxylated Fe3O4 NPs demonstrated to be suitable targeting agents, potentially advancing the development of natural nanocarriers for combination cancer therapy.

Therapeutic targeting of senescent cells in the CNS.

Senescent cells accumulate throughout the body with advanced age, diseases and chronic conditions. They negatively impact health and function of multiple systems, including the central nervous system (CNS). Therapies that target senescent cells, broadly referred to as senotherapeutics, recently emerged as potentially important treatment strategies for the CNS. Promising therapeutic approaches involve clearing senescent cells by disarming their pro-survival pathways with 'senolytics'; or dampening their toxic senescence-associated secretory phenotype (SASP) using 'senomorphics'. Following the pioneering discovery of first-generation senolytics dasatinib and quercetin, dozens of additional therapies have been identified, and several promising targets are under investigation. Although potentially transformative, senotherapies are still in early stages and require thorough testing to ensure reliable target engagement, specificity, safety and efficacy. The limited brain penetrance and potential toxic side effects of CNS-acting senotherapeutics pose challenges for drug development and translation to the clinic. This Review assesses the potential impact of senotherapeutics for neurological conditions by summarizing preclinical evidence, innovative methods for target and biomarker identification, academic and industry drug development pipelines and progress in clinical trials.

AI-driven antibody design with generative diffusion models: current insights and future directions.

Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and time costs. Recent strides in computational and artificial intelligence (AI), especially generative diffusion models, have begun to address these challenges, offering novel approaches for antibody design. This review delves into specific diffusion-based generative methodologies tailored for antibody design tasks, de novo antibody design, and optimization of complementarity-determining region (CDR) loops, along with their evaluation metrics. We aim to provide an exhaustive overview of this burgeoning field, making it an essential resource for leveraging diffusion-based generative models in antibody design endeavors.

Enhancement of Stress Granule Formation by a Chiral Compound Targeting G3BP1 via eIF2α Phosphorylation.

The chirality of a chemical differentiates it from its mirror-image counterpart. This unique property has significant implications in chemistry, biology, and drug discovery, where chiral chemicals display high selectivity and activity in achieving target specificity and reducing attrition rates in drug development. Stress granules (SGs) are dynamic assemblies of proteins and RNA that form in the cytoplasm of cells under stress conditions. Modulating their formation or disassembly could offer a novel approach to treating a wide range of diseases. This has led to significant interest in SGs as potential therapeutic targets. This study examined the NTF2-like domain of G3BP1 as a possible target for SG modulation. Molecular docking was used to simulate the interactions of compounds with the domain, and a potential candidate with a chiral structure was identified. The experiments showed that the compound induced the formation of SG-like granules. Importantly, the ability of this compound to modulate SG offers valuable insights into a new mechanism underlying the dynamics and promoting the assembly of SGs, and this new mechanism, in turn, holds potential for the development of drugs with diverse mechanisms of action and potentially synergistic effects.

Radiosynthesis and Preclinical Evaluation of [99mTc]Tc-Tigecycline Radiopharmaceutical to Diagnose Bacterial Infections.

As a primary source of mortality and disability, bacterial infections continue to develop a severe threat to humanity. Nuclear medicine imaging (NMI) is known for its promising potential to diagnose deep-seated bacterial infections. This work aims to develop a new technetium-99m (99mTc) labeled tigecycline radiopharmaceutical as an infection imaging agent. Reduced 99mTc was used to make a coordinate complex with tigecycline at pH 7.7-7.9 at room temperature. Instantaneous thin-layer chromatography impregnated with silica gel (ITLC-SG) and ray detector equipped high-performance liquid chromatography (ray-HPLC) was performed to access the radiolabeling yield and radiochemical purity (RCP). More than 91% labeling efficiency was achieved after 25 min of mild shaking of the reaction mixture. The radiolabeled complex was found intact up to 4 h in saline. Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) infection-induced rats were used to record the biodistribution of the radiopharmaceutical and its target specificity; 2 h' post-injection biodistribution revealed a 2.39 ± 0.29 target/non-target (T/NT) ratio in the E. coli infection-induced animal model, while a 2.9 ± 0.31 T/NT value was recorded in the S. aureus bacterial infection-induced animal model. [99mTc]Tc-tigecycline scintigraphy was performed in healthy rabbits using a single photon emission computed tomography (SPECT) camera. Scintigrams showed normal kidney perfusion and excretion into the bladder. In conclusion, the newly developed [99mTc]Tc-tigecycline radiopharmaceutical could be considered to diagnose broad-spectrum bacterial infections.

Molecular imaging supports the development of multispecific cancer antibodies.

Multispecific antibodies are engineered antibody derivatives that can bind to two or more distinct epitopes or antigens. Unlike mixtures of monospecific antibodies, the binding properties of multispecific antibodies enable two specific molecules to be physically linked, a characteristic with important applications in cancer therapy. The field of multispecific antibodies is highly dynamic and expanding rapidly; to date, 15 multispecific antibodies have been approved for clinical use, of which 11 were approved for oncological indications, and more than 100 new antibodies are currently in clinical development. Nevertheless, substantial challenges limit the applications of multispecific antibodies in cancer therapy, particularly inefficient targeting of solid tumours and substantial adverse effects. Both PET and single photon emission CT imaging can reveal the biodistribution and complex pharmacology of radiolabelled multispecific antibodies. This Review summarizes the insights obtained from preclinical and clinical molecular imaging studies of multispecific antibodies, focusing on their structural properties, such as molecular weight, shape, target specificity, affinity and avidity. The opportunities associated with use of molecular imaging studies to support the clinical development of multispecific antibody therapies are also highlighted.

A novel carboxylesterase 2-targeted fluorescent probe with cholic acid as a recognition group for early diagnosis of drug- and environment-related liver diseases

Due to the detrimental effects of various harmful substances—such as carcinogens, drug toxicity, and environmental pollutants—on the liver, which can trigger or exacerbate conditions like hepatocellular carcinoma (HCC), drug-induced liver injury (DILI), and non-alcoholic fatty liver disease (NAFLD), accurate detection and monitoring of these diseases are crucial for effective treatment. Carboxylesterase 2 (CES2) is primarily found in the liver and, as a potential biomarker, its accurate detection can enhance the early diagnosis and treatment efficacy of liver diseases. Traditional fluorescence probes for CES2 detection suffer from non-specific recognition groups, leading to poor targeting specificity. To address this limitation, we propose a novel CES2-responsive fluorescent probe utilizing cholic acid (CA) as a recognition group. The probe, LAN-CA, was synthesized by esterifying CA with a near-infrared fluorophore, LAN-OH. This novel fluorescent probe leverages the unique affinity of CA for hepatocytes, ensuring that LAN-CA remains and accumulates specifically within the hepatoenteric circulation. In vitro experiments showed that the probe exhibits superior optical performance compared to traditional benzoate-based probe (LAN-PH), with a detection limit of 0.015 μg/mL. Examination of 56 common biological interferents demonstrated that using CA as a recognition group offers high selectivity. Cell experiments confirmed that LAN-CA is an effective tool for monitoring endogenous CES2 in live cells. Comprehensive evaluations of fluorescence imaging in various mouse models of liver diseases, such as HCC, DILI, and NAFLD, demonstrated that LAN-CA provides exceptional imaging accuracy and therapeutic monitoring capabilities. In conclusion, this probe not only can be a promising tool for accurate liver disease diagnosis, but also can provide valuable insights into treatment efficacy.

Phyto-nanotechnology: A novel beneficial strategy for Alzheimer's disease therapy

Alzheimer's disease, a neurodegenerative condition, is characterized by the slow and progressive deterioration of the cognitive functions of geriatric patients. It occurs due to exacerbation of neurons in the brain, indicated by loss of memory, mood instability, and even death. The aggregation of amyloid β protein and neurofibrillary tangles-atypical forms of tau protein is the major cause of this disease. Phytoconstituents have been frequently employed in treating Alzheimer's disease. These natural compounds act through different molecular mechanisms to treat the disease. However, their potential in Alzheimer's disease therapy may be limited due to poor blood-brain barrier permeability, off-target effects, low bioavailability, etc. In recent times, nanotechnology has gained attraction to overcome these challenges. This article focuses on the potential phytoconstituents for Alzheimer's disease treatment and the associated limitations. Moreover, it highlights various nanoformulation strategies employed to penetrate the blood-brain barrier effectively, avoid side effects, improve bioavailability, and target specificity in treating Alzheimer's disease. The integration of nanotechnology with plant-derived compounds has the potential to revolutionize the therapeutic landscape for Alzheimer's disease.

Novel targeting liposomes with enhanced endosomal escape for co-delivery of doxorubicin and curcumin

Effective endosomal escape is crucial for enhancing the efficiency of nanodrug delivery systems. In this study, we developed a novel liposomal system utilizing acid-sensitive N-(3-amino-propyl) imidazole cholesterol (IM-Chol), specifically designed for the targeted co-delivery of doxorubicin (DOX) and curcumin (CUR) to hepatocellular carcinoma (HCC). Designated as GA-IM-LIP@DOX/CUR, this liposomal system incorporates glycyrrhetinic acid (GA) to improve target specificity toward HCC cells. Notably, both drugs exhibited pH-sensitive release profiles, facilitating precise drug release within acidic environments. Our investigation into cellular uptake demonstrated that modified liposomes, GA-IM-LIP@FITC and IM-LIP@FITC, achieved progressively enhanced intracellular accumulation of FITC compared to unmodified liposomes. Competitive inhibition assays utilizing free GA further validated the targeting efficacy of GA. Moreover, the GA-IM-LIP@FITC and IM-LIP@FITC groups exhibited rapid endosomal escape of FITC within the first two hours, in contrast to delayed escape observed in the LIP@FITC group, confirming that the protonation of IM-Chol promotes drug release into the cytosol. In vivo studies substantiated that GA-IM-LIP@DOX/CUR effectively inhibited tumor growth. This research provides significant insights into the design and functionality of the GA-IM-LIP@DOX/CUR liposomal system, underscoring its potential to enhance drug delivery strategies in the treatment of HCC.

Chem-CRISPR/dCas9FCPF: a platform for chemically induced epigenome editing.

Epigenetic aberration is one of the major driving factors in human cancer, often leading to acquired resistance to chemotherapies. Various small molecule epigenetic modulators have been reported. Nonetheless, outcomes from animal models and clinical trials have underscored the substantial setbacks attributed to pronounced on- and off-target toxicities. To address these challenges, CRISPR/dCas9 technology is emerging as a potent tool for precise modulation of epigenetic mechanism. However, this technology involves co-expressing exogenous epigenetic modulator proteins, which presents technical challenges in preparation and delivery with potential undesirable side effects. Recently, our research demonstrated that Cas9 tagged with the Phe-Cys-Pro-Phe (FCPF)-peptide motif can be specifically targeted by perfluorobiphenyl (PFB) derivatives. Here, we integrated the FCPF-tag into dCas9 and established a chemically inducible platform for epigenome editing, called Chem-CRISPR/dCas9FCPF. We designed a series of chemical inhibitor-PFB conjugates targeting various epigenetic modulator proteins. Focusing on JQ1, a panBET inhibitor, we demonstrate that c-MYC-sgRNA-guided JQ1-PFB specifically inhibits BRD4 in close proximity to the c-MYC promoter/enhancer, thereby effectively repressing the intricate transcription networks orchestrated by c-MYC as compared with JQ1 alone. In conclusion, our Chem-CRISPR/dCas9FCPF platform significantly increased target specificity of chemical epigenetic inhibitors, offering a viable alternative to conventional fusion protein systems for epigenome editing.