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Background: T cell receptor (TCR)–engineered T cells targeting neoantigens originated from mutations in KRAS gene have demonstrated promising outcomes in clinical trials against solid tumors. However, the challenge lies in developing tumor-specific TCRs that avoid cross-reactivity with self-antigens to minimize the possibility of severe clinical toxicities. Current research efforts have been put towards strategies to eliminate TCR off-target recognition. Methods: Naive T cell repertoire was used for screening KRASG12D-reactive TCRs. Specific TCRs were subsequently identified and their functionality was assessed using TCR Jurkat cells and TCR T cells. Peptide specificity was evaluated using the X-scan assay. To enhance TCR specificity for KRASG12D and reduce their reactivity to self-peptide SMC1A29-38, mammalian TCR display libraries were employed for the design of modification in the complementarity-determining region (CDR). Results: HLA-A*11:01-restricted TCRs targeting the KRASG12D epitope were isolated, and TCR1 was characterized with superior functional avidity and specificity. Alongside a robust recognition of endogenous KRASG12D epitope, this TCR displayed cross-reactivity with the SMC1A29-38 epitope. With an approach utilizing structural-guided mutations in the CDR-1A region of TCR1, we obtained an engineered TCR variant (TCR1a7). Functional characterization of TCR1a7 showed that this TCR not only exhibited enhanced specificity towards KRASG12D, but also demonstrated successful elimination of the off-target recognition of SMC1A29-38. Conclusions: TCRs targeting the KRASG12D peptide could be isolated from naive T cell repertoires. Integrating the TCR-peptide-HLA complex structure with a mammalian TCR library system could serve as a functional strategy to reduce potential TCR cross-reactivity with self-antigens, such as SMC1A29-38. Our findings evidenced an operable method to enhance TCR peptide specificity, while maintaining advanced functional avidity and potent anti-tumor activity. [ABSTRACT FROM AUTHOR]

Background and purpose: MicroRNA (miRNA) therapy is a promising approach to induce cardioprotection. We have previously identified cardiac microRNA‐125b* (microRNA‐125b‐2‐3p; miR‐125b*) as a potential cardioprotective miRNA, termed ProtectomiR. We aimed to characterize the pharmacokinetics and pharmacodynamics, and the effect of miR‐125b* mimic on infarct size using an in vivo mouse model. Experimental approach: To characterize the pharmacokinetics properties of miR‐125b* mimic, a single injection of 10‐μg miR‐125b* mimic or its scramble miRNA control, or vehicle i.v. was given to C57BL/6 mice. MiR‐125b* expression was measured from plasma, heart, kidney and liver samples. Effect of miR‐125b* on area at risk and infarct size was assessed after 45‐min coronary occlusion, followed by 24‐h reperfusion; 10‐μg miR‐125b* mimic or 10‐μg non‐targeting miRNA mimic control or vehicle were administered via the right jugular vein at 10th mins of coronary occlusion. To assess molecular mechanism involved in cardioprotection, expression of mRNA targets of miR‐125b* were measured from ventricular myocardium at 1, 2, 4, 8 or 24 h post‐treatment using quantitative real time polymerase chain reaction. Key results: MiR‐125b* expression was markedly increased in plasma and myocardium 1 h, and in the liver 2h after treatment. Infarct size was significantly reduced after miR‐125b* mimic treatment when compared to the vehicle. The expression of Ccna2, Eef2k and Cacnb2 target mRNAs was significantly reduced 8 h after injection of miR‐125b* mimic. Conclusion and implications: This is the first demonstration of pharmacokinetic and molecular pharmacodynamic properties as well as the cardioprotective effect of miR‐125b* mimic in vivo. LINKED ARTICLES: This article is part of a themed issue Non‐coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc [ABSTRACT FROM AUTHOR]

CRISPR/Cas9 is the most popular genome editing platform for investigating gene function or improving traits in plants. The specificity of gene editing has yet to be evaluated at a genome-wide scale in seed-propagated Camelina sativa (L.) Crantz (camelina) or clonally propagated Solanum tuberosum L. (potato). In this study, seven potato and nine camelina stable transgenic Cas9-edited plants were evaluated for on and off-target editing outcomes using 55x and 60x coverage whole genome shotgun sequencing data, respectively. For both potato and camelina, a prevalence of mosaic somatic edits from constitutive Cas9 expression was discovered as well as evidence of transgenerational editing in camelina. CRISPR/Cas9 editing provided negligible off-target activity compared to background variation in both species. The results from this study guide deployment and risk assessment of genome editing in commercially relevant traits in food crops. [ABSTRACT FROM AUTHOR]

The inhibition of Nav1.7 is a promising strategy for the development of analgesic treatments. Spider venom‐derived peptide toxins are recognized as significant sources of Nav1.7 inhibitors. However, their development has been impeded by limited selectivity. In this study, eight peptide toxins from three distinct spider venom Nav channel families demonstrated robust inhibition of hNav1.7, rKv4.2, and rKv4.3 (rKv4.2/4.3) currents, exhibiting a similar mode of action. The analysis of structure and function relationship revealed a significant overlap in the pharmacophore responsible for inhibiting hNav1.7 and rKv4.2 by HNTX‐III, although Lys25 seems to play a more pivotal role in the inhibition of rKv4.2/4.3. Pharmacophore‐guided rational design is employed for the development of an mGpTx1 analogue, mGpTx1‐SA, which retains its inhibition of hNav1.7 while significantly reducing its inhibition of rKv4.2/4.3 and eliminating cardiotoxicity. Moreover, mGpTx1‐SA demonstrates potent analgesic effects in both inflammatory and neuropathic pain models, accompanied by an improved in vivo safety profile. The results suggest that off‐target inhibition of rKv4.2/4.3 by specific spider peptide toxins targeting hNav1.7 may arise from a conserved binding motif. This insight promises to facilitate the design of hNav1.7‐specific analgesics, aimed at minimizing rKv4.2/4.3 inhibition and associated toxicity, thereby enhancing their suitability for therapeutic applications. [ABSTRACT FROM AUTHOR]

Glycosylase base editor (GBE) can induce C‐to‐G transversion in mammalian cells, showing great promise for the treatment of human genetic disorders. However, the limited efficiency of transversion and the possibility of off‐target effects caused by Cas9 restrict its potential clinical applications. In our recent study, we have successfully developed TaC9‐CBE and TaC9‐ABE by separating nCas9 and deaminase, which eliminates the Cas9‐dependent DNA off‐target effects without compromising editing efficiency. We developed a novel GBE called TaC9‐GBEYE1, which utilizes the deaminase and UNG‐nCas9 guided by TALE and sgRNA, respectively. TaC9‐GBEYE1 showed comparable levels of on‐target editing efficiency to traditional GBE at 19 target sites, without any off‐target effects caused by Cas9 or TALE. The TaC9‐GBEYE1 is a safe tool for gene therapy. [ABSTRACT FROM AUTHOR]

CRISPR/Cas9 is a popular genome editing technology, yet its clinical application is hindered by off-target effects. Many deep learning-based methods are available for off-target prediction. However, few can predict off-target activities with insertions or deletions (indels) between single guide RNA and DNA sequence pairs. Additionally, the analysis of off-target data is challenged due to a data imbalance issue. Moreover, the prediction accuracy and interpretability remain to be improved. Here, we introduce a deep learning-based framework, named Crispr-SGRU, to predict off-target activities with mismatches and indels. This model is based on Inception and stacked BiGRU. It adopts a dice loss function to solve the inherent imbalance issue. Experimental results show our model outperforms existing methods for off-target prediction in terms of accuracy and robustness. Finally, we study the interpretability of this model through Deep SHAP and teacher–student-based knowledge distillation, and find it can provide meaningful explanations for sequence patterns regarding off-target activity. [ABSTRACT FROM AUTHOR]

Background/Objectives: Many pregnant women globally suffer from depression and are routinely prescribed selective serotonin reuptake inhibitors (SSRIs). These drugs function by blocking the re-uptake of serotonin by the serotonin transporter (SERT) into neurons, resulting in its accumulation in the presynaptic cleft. Despite a large amount of research suggesting a potential link to neurodevelopmental disorders in children whose mothers took these drugs during pregnancy, their possible adverse effects are still debated, and results are contradictory. On the other hand, there is an immediate need for improved cell-based models for developmental neurotoxicity studies (DNT) to minimize the use of animals in research. Methods: In this study, we aimed to assess the effects of clinically relevant concentrations of paroxetine (PAR), fluoxetine (FLX), and citalopram (CIT)—on maturing neurons derived from human neural stem cells using multiple endpoints. Results: Although none of the tested concentrations of FLX, CIT, or PAR significantly affected cell viability, FLX (10 µM) exhibited the highest reduction in viability compared to the other drugs. Regarding neurite outgrowth, CIT did not have a significant effect. However, FLX (10 µM) significantly reduced both mean neurite outgrowth and mean processes, PAR significantly reduced mean processes, and showed a trend of dysregulation of multiple genes associated with neuronal development at therapeutic-relevant serum concentrations. Conclusions: Transcriptomic data and uptake experiments found no SERT activity in the system, suggesting that the adverse effects of FLX and PAR are independent of SERT. [ABSTRACT FROM AUTHOR]

【Objective】 The emergence of high-fidelity editors in recent years is expected to widely reduce the off-target effect that occurs during gene editing in poultry with the conventional CRISPR/Cas9 system. However, there is still a lack of data support for the application of these high-fidelity editors in poultry. This study aims to further evaluate their on-target editing effects and off-target characteristics in poultry cells, so as to provide an effective reference for molecular genetic breeding and germplasm resource utilization in poultry. 【Method】 Five high-fidelity Cas9 variants, which have been reported with high accuracy, were selected and co-transfected with the designed sgRNAs in chicken DF-1 cells, and the positive cells were collected for gene sequencing, and the editing efficiency and off-target effect of different high-fidelity editors were compared in parallel.【Result】eCas9 maintained high editing activity while demonstrating low off-target effects in multiple sgRNAs tested against the avian influenza resistance-related gene ANP32B and the reproduction-related gene DAZL. Meanwhile, SuperFiCas9 had the lowest off-target effect among multiple tested high-fidelity variants, but a significant decrease in editing efficiency occurred in gene editing of poultry DF-1 cells. 【Conclusion】 A variety of high-fidelity editors have shown editing activity in poultry cells, among which the eCas9 editor has high efficiency and low off-target properties, and can be used as a preferred high-fidelity editing tool for the genetic improvement of economically important traits and molecular breeding work in chickens. [ABSTRACT FROM AUTHOR]

Background and Aims: Cardiac glycosides (CGs), traditionally used for heart failure, have shown potential as anti‐cancer agents. This study aims to explore their multifaceted mechanisms in cancer cell biology using proteome integral solubility alteration (PISA), focusing on the interaction with key proteins implicated in cellular metabolism and mitochondrial function. Methods: We conducted lysate‐based and intact‐cell PISA assays on cancer cells treated with CGs (Digoxin, Digitoxin, Ouabain) to analyze protein solubility changes. This was followed by mass spectrometric analysis and bioinformatics to identify differentially soluble proteins (DSPs). Molecular docking simulations were performed to predict protein‐CG interactions. Public data including gene expression changes upon CG treatment were re‐analyzed for validation. Results: The PISA assays revealed CGs' broad‐spectrum interactions, particularly affecting proteins like PKM2, ANXA2, SLC16A1, GOT2 and GLUD1. Molecular docking confirmed stable interactions between CGs and these DSPs. Re‐analysis of public data supported the impact of CGs on cancer metabolism and cell signaling pathways. Conclusion: Our findings suggest that CGs could be repurposed for cancer therapy by modulating cellular processes. The PISA data provide insights into the polypharmacological effects of CGs, warranting further exploration of their mechanisms and clinical potential. [ABSTRACT FROM AUTHOR]

Prime editors are CRISPR-based genome engineering tools with significant potential for rectifying patient mutations. However, their usage requires experimental optimization of the prime editing guide RNA (PegRNA) to achieve high editing efficiency. This paper introduces the deep transformer-based model for predicting prime editing efficiency (DTMP-Prime), a tool specifically designed to predict PegRNA activity and prime editing (PE) efficiency. DTMP-Prime facilitates the design of appropriate PegRNA and ngRNA. A transformer-based model was constructed to scrutinize a wide-ranging set of PE data, enabling the extraction of effective features of PegRNAs and target DNA sequences. The integration of these features with the proposed encoding strategy and DNABERT-based embedding has notably improved the predictive capabilities of DTMP-Prime for off-target sites. Moreover, DTMP-Prime is a promising tool for precisely predicting off-target sites in CRISPR experiments. The integration of a multi-head attention framework has additionally improved the precision and generalizability of DTMP-Prime across various PE models and cell lines. Evaluation results based on the Pearson and Spearman correlation coefficient demonstrate that DTMP-Prime outperforms other state-of-the-art models in predicting the efficiency and outcomes of PE experiments.

Simple Summary: Human beings are always associated with small molecules throughout their lives. Chemical proteomics, which selectively identifies small-molecule targets, is an emerging approach for unraveling the mechanism of action of small molecules for therapeutic target identification and drug discovery. This review attempts to introduce representative techniques of chemical proteomics and summarizes examples of identifying small-molecule targets. Throughout the human lifespan, from conception to the end of life, small molecules have an intrinsic relationship with numerous physiological processes. The investigation into small-molecule targets holds significant implications for pharmacological discovery. The determination of the action sites of small molecules provide clarity into the pharmacodynamics and toxicological mechanisms of small-molecule drugs, assisting in the elucidation of drug off-target effects and resistance mechanisms. Consequently, innovative methods to study small-molecule targets have proliferated in recent years, with chemical proteomics standing out as a vanguard development in chemical biology in the post-genomic age. Chemical proteomics can non-selectively identify unknown targets of compounds within complex biological matrices, with both probe and non-probe modalities enabling effective target identification. This review attempts to summarize methods and illustrative examples of small-molecule target identification via chemical proteomics. It delves deeply into the interactions between small molecules and human biology to provide pivotal directions and strategies for the discovery and comprehension of novel pharmaceuticals, as well as to improve the evaluation of drug safety. [ABSTRACT FROM AUTHOR]

Objective: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current computation models only consider very few factors with limited success in clinical toxicity prediction. We aimed to address these issues by developing a machine learning (ML) model to directly predict clinical AEs. Methods: Using a dataset with 759 FDA-approved drugs with known AEs, we first adapted the ConPLex ML model to predict IC 50 values of these FDA-approved drugs against their on-target and off-target binding among 477 protein targets. Subsequently, we constructed a new ML model to predict clinical AEs using IC 50 values of 759 drugs' primary on-target and off-target effects along with tissue-specific protein expression profiles. Results: The adapted ConPLex model predicted drug-target interactions for both on- and off-target effects, as shown by co-localization of the 6 small molecule kinase inhibitors with their respective kinases. The coupled ML models demonstrated good predictive capability of clinical AEs, with accuracy over 75%. Conclusions: Our approach provides a new insight into the mechanistic understanding of in vivo drug toxicity in relationship with drug on-/off-target interactions. The coupled ML models, once validated with larger datasets, may offer advantages to directly predict clinical AEs using in vitro/ex vivo and preclinical data, which will help to reduce drug development failure due to clinical toxicity. [ABSTRACT FROM AUTHOR]

• Neural nets with varying parameters and feature sets are used to assess the performance increase in Cas9activity predictions. • Akaike and Bayesian information criteria were employed to compare the significance of the contributions of feature sets. • Important features include mismatches and nucleotide composition as well as base-pair parameters like opening and stretch. • Valuable insights into the mechanisms of CRISPR/Cas9 genome editing wasobtained by improved understanding of Cas9 behaviour. The CRISPR/Cas9 genome editing technology has transformed basic and translational research in biology and medicine. However, the advances are hindered by off-target effects and a paucity in the knowledge of the mechanism of the Cas9 protein. Machine learning models have been proposed for the prediction of Cas9 activity at unintended sites, yet feature engineering plays a major role in the outcome of the predictors. This study evaluates the improvement in the performance of similar predictors upon inclusion of epigenetic and DNA shape feature groups in the conventionally used sequence-based Cas9 target and off-target datasets. The approach involved the utilization of neural networks trained on a diverse range of parameters, allowing us to systematically assess the performance increase for the meticulously designed datasets- (i) sequence only, (ii) sequence and epigenetic features, and (iii) sequence, epigenetic and DNA shape feature datasets. The addition of DNA shape information significantly improved predictive performance, evaluated by Akaike and Bayesian information criteria. The evaluation of individual feature importance by permutation and LIME-based methods also indicates that not only sequence features like mismatches and nucleotide composition, but also base pairing parameters like opening and stretch, that are indicative of distortion in the DNA-RNA hybrid in the presence of mismatches, influence model outcomes. [ABSTRACT FROM AUTHOR]

CRISPR/Cas9 is the most popular genome editing platform for investigating gene function or improving traits in plants. The specificity of gene editing has yet to be evaluated at a genome-wide scale in seed-propagated Camelina sativa (L.) Crantz (camelina) or clonally propagated Solanum tuberosum L. (potato). In this study, seven potato and nine camelina stable transgenic Cas9-edited plants were evaluated for on and off-target editing outcomes using 55x and 60x coverage whole genome shotgun sequencing data, respectively. For both potato and camelina, a prevalence of mosaic somatic edits from constitutive Cas9 expression was discovered as well as evidence of transgenerational editing in camelina. CRISPR/Cas9 editing provided negligible off-target activity compared to background variation in both species. The results from this study guide deployment and risk assessment of genome editing in commercially relevant traits in food crops.

Recent years have witnessed unprecedented progress in therapeutic gene editing, revolutionizing the approach to treating genetic disorders. In this comprehensive review, we discuss the progression of milestones leading to the emergence of the clustered regularly interspaced short palindromic repeats (CRISPR)-based technology as a powerful tool for precise and targeted modifications of the human genome. CRISPR-Cas9 nuclease, base editing, and prime editing have taken center stage, demonstrating remarkable precision and efficacy in targeted ex vivo and in vivo genomic modifications. Enhanced delivery systems, including viral vectors and nanoparticles, have further improved the efficiency and safety of therapeutic gene editing, advancing their clinical translatability. The exploration of CRISPR-Cas systems beyond the commonly used Cas9, such as the development of Cas12 and Cas13 variants, has expanded the repertoire of gene editing tools, enabling more intricate modifications and therapeutic interventions. Outstandingly, prime editing represents a significant leap forward, given its unparalleled versatility and minimization of off-target effects. These innovations have paved the way for therapeutic gene editing in a multitude of previously incurable genetic disorders, ranging from monogenic diseases to complex polygenic conditions. This review highlights the latest innovative studies in the field, emphasizing breakthrough technologies in preclinical and clinical trials, and their applications in the realm of precision medicine. However, challenges such as off-target effects and ethical considerations remain, necessitating continued research to refine safety profiles and ethical frameworks.

Abstract Background The field of genome editing has been revolutionized by the development of an easily programmable editing tool, the CRISPR–Cas9. Despite its promise, off-target activity of Cas9 posed a great disadvantage for genome editing purposes by causing DNA double strand breaks at off-target locations and causing unwanted editing outcomes. Furthermore, for gene integration applications, which introduce transgene sequences, integration of transgenes to off-target sites could be harmful, hard to detect, and reduce faithful genome editing efficiency. Method Here we report the development of a multicolour fluorescence assay for studying CRISPR–Cas9-directed gene integration at an endogenous locus in human cell lines. We examine genetic integration of reporter genes in transiently transfected cells as well as puromycin-selected stable cell lines to determine the fidelity of multiple CRISPR–Cas9 strategies. Result We found that there is a high occurrence of unwanted DNA integration which tarnished faithful knock-in efficiency. Integration outcomes are influenced by the type of DNA DSBs, donor design, the use of enhanced specificity Cas9 variants, with S-phase regulated Cas9 activity. Moreover, restricting Cas9 expression with a self-cleaving system greatly improves knock-in outcomes by substantially reducing the percentage of cells with unwanted DNA integration. Conclusion Our results highlight the need for a more stringent assessment of CRISPR–Cas9-mediated knock-in outcomes, and the importance of careful strategy design to maximise efficient and faithful transgene integration.

Gene editing therapies are designed to minimise off-target editing. However, it is not widespread practice for common polymorphisms to be considered when identifying potential off-target sites in silico. Nevertheless, genetic variants should be included as they have the potential to alter existing, or to generate new, off-target sites. To facilitate the consideration of common polymorphisms when designing targeted gene therapies we developed PopOff, a web-based tool that integrates minor allele frequencies from the gnomAD variant database into an off-target analysis. We used PopOff to analyse predicted off-target loci from guide RNAs used in four clinical trials and thirty-four research publications. From an analysis of sixty guides, we identified that approximately 20% of off-target loci overlap with a common polymorphism. Of these sites, 6.93% contained variants that reduce the level of mismatch between the off-target locus and guide, and therefore may increase off-target cleavage. In addition, we identified that 0.34% of common polymorphisms generated novel PAM sites, resulting in off-target loci that standard workflows would miss. Our findings demonstrate that common polymorphisms should be considered when designing guides to maximise the safety of CRISPR-based gene therapies. However, this may be problematic in populations where the breadth of genetic diversity remains uncharacterised. [ABSTRACT FROM AUTHOR]

Genome editing via CRISPR/Cas has enabled targeted genetic modifications in various species, including plants. The requirement for specific protospacer-adjacent motifs (PAMs) near the target gene, as seen with Cas nucleases like SpCas9, limits its application. PAMless SpCas9 variants, designed with a relaxed PAM requirement, have widened targeting options. However, these so-call PAMless SpCas9 still show variation of editing efficiency depending on the PAM and their efficiency lags behind the native SpCas9. Here we assess the potential of a PAMless SpCas9 variant for genome editing in the model plant Physcomitrium patens. For this purpose, we developed a SpRYCas9i variant, where expression was optimized, and tested its editing efficiency using the APT as a reporter gene. We show that the near PAMless SpRYCas9i effectively recognizes specific PAMs in P. patens that are not or poorly recognized by the native SpCas9. Pattern of mutations found using the SpRYCas9i are similar to the ones found with the SpCas9 and we could not detect off-target activity for the sgRNAs tested in this study. These findings contribute to advancing versatile genome editing techniques in plants. [ABSTRACT FROM AUTHOR]

Background: The field of genome editing has been revolutionized by the development of an easily programmable editing tool, the CRISPR–Cas9. Despite its promise, off-target activity of Cas9 posed a great disadvantage for genome editing purposes by causing DNA double strand breaks at off-target locations and causing unwanted editing outcomes. Furthermore, for gene integration applications, which introduce transgene sequences, integration of transgenes to off-target sites could be harmful, hard to detect, and reduce faithful genome editing efficiency. Method: Here we report the development of a multicolour fluorescence assay for studying CRISPR–Cas9-directed gene integration at an endogenous locus in human cell lines. We examine genetic integration of reporter genes in transiently transfected cells as well as puromycin-selected stable cell lines to determine the fidelity of multiple CRISPR–Cas9 strategies. Result: We found that there is a high occurrence of unwanted DNA integration which tarnished faithful knock-in efficiency. Integration outcomes are influenced by the type of DNA DSBs, donor design, the use of enhanced specificity Cas9 variants, with S-phase regulated Cas9 activity. Moreover, restricting Cas9 expression with a self-cleaving system greatly improves knock-in outcomes by substantially reducing the percentage of cells with unwanted DNA integration. Conclusion: Our results highlight the need for a more stringent assessment of CRISPR–Cas9-mediated knock-in outcomes, and the importance of careful strategy design to maximise efficient and faithful transgene integration. [ABSTRACT FROM AUTHOR]

CRISPR Cas-9 is a groundbreaking genome-editing tool that harnesses bacterial defense systems to alter DNA sequences accurately. This innovative technology holds vast promise in multiple domains like biotechnology, agriculture and medicine. However, such power does not come without its own peril, and one such issue is the potential for unintended modifications (Off-Target), which highlights the need for accurate prediction and mitigation strategies. Though previous studies have demonstrated improvement in Off-Target prediction capability with the application of deep learning, they often struggle with the precision-recall trade-off, limiting their effectiveness and do not provide proper interpretation of the complex decision-making process of their models. To address these limitations, we have thoroughly explored deep learning networks, particularly the recurrent neural network based models, leveraging their established success in handling sequence data. Furthermore, we have employed genetic algorithm for hyperparameter tuning to optimize these models' performance. The results from our experiments demonstrate significant performance improvement compared with the current state-of-the-art in Off-Target prediction, highlighting the efficacy of our approach. Furthermore, leveraging the power of the integrated gradient method, we make an effort to interpret our models resulting in a detailed analysis and understanding of the underlying factors that contribute to Off-Target predictions, in particular the presence of two sub-regions in the seed region of single guide RNA which extends the established biological hypothesis of Off-Target effects. To the best of our knowledge, our model can be considered as the first model combining high efficacy, interpretability and a desirable balance between precision and recall. [ABSTRACT FROM AUTHOR]

A series of clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 (Cas9) systems have been engineered for genome editing. The most widely used Cas9 is SpCas9 from Streptococcus pyogenes and SaCas9 from Staphylococcus aureus. However, a comparison of their detailed gene editing outcomes is still lacking. By characterizing the editing outcomes of 11 sites in human induced pluripotent stem cells (iPSCs) and K562 cells, we found that SaCas9 could edit the genome with greater efficiencies than SpCas9. We also compared the effects of spacer lengths of single-guide RNAs (sgRNAs; 18–21 nt for SpCas9 and 19–23 nt for SaCas9) and found that the optimal spacer lengths were 20 nt and 21 nt for SpCas9 and SaCas9, respectively. However, the optimal spacer length for a particular sgRNA was 18–21 nt for SpCas9 and 21–22 nt for SaCas9. Furthermore, SpCas9 exhibited a more substantial bias than SaCas9 for nonhomologous end-joining (NHEJ) +1 insertion at the fourth nucleotide upstream of the protospacer adjacent motif (PAM), indicating a characteristic of a staggered cut. Accordingly, editing with SaCas9 led to higher efficiencies of NHEJ-mediated double-stranded oligodeoxynucleotide (dsODN) insertion or homology-directed repair (HDR)-mediated adeno-associated virus serotype 6 (AAV6) donor knock-in. Finally, GUIDE-seq analysis revealed that SaCas9 exhibited significantly reduced off-target effects compared with SpCas9. Our work indicates the superior performance of SaCas9 to SpCas9 in transgene integration-based therapeutic gene editing and the necessity to identify the optimal spacer length to achieve desired editing results.

Computational chemistry lets us model intermolecular interactions in ways assays cannot. My project focuses on the multi-kinase interactions of the cancer drug, imatinib. Most cancer drugs target one kinase, but some affect multiple kinases. Imatinib treats chronic myeloid leukemia by targeting ABL kinase. Proteomics data reveals it can interact with other kinases, such as KIT to treat gastrointestinal stromal tumors, but the mechanisms are unknown. Imatinib has different affinities for similar kinases, such as a 3000x difference between ABL and SRC, despite sharing 50% structural homology. Here, I investigate the conformational differences between free and imatinib-bound ABL, KIT, and SRC using Molecular Dynamics simulations to understand the key imatinib-kinase interactions. The alignment analysis shows the docked conformations are similar to co-crystal structures in the Protein Data Bank. Root-mean-square-deviation and fluctuation (RMSD and RMSF) analysis show that all simulations converge at 45 ns, with some regions exhibiting differential flexibility. Hydrogen bond analysis across 100 ns simulations show that ABL has one main H-bond, KIT has three main H-bonds, and SRC has no main H-bonds. All the drug-kinase complexes feature at least 15 key salt bridge interactions relevant for structural stability. The dihedral distributions reveal that most residues adopt a single conformation, but some can adopt multiple, increasing the protein flexibility. The entropy results quantify the protein disorder, revealing KIT and SRC favors the apoprotein while ABL favors the complex. This signifies that broad protein similarity does not govern imatinib binding, instead, it is explained by smaller structural details.

Abstract Colorectal cancer (CRC) is one of the most common malignant cancers worldwide and seriously threatens human health. The clustered regulatory interspaced short palindromic repeat/CRISPR-associate nuclease 9 (CRISPR/Cas9) system is an adaptive immune system of bacteria or archaea. Since its introduction, research into various aspects of treatment approaches for CRC has been accelerated, including investigation of the oncogenes, tumor suppressor genes (TSGs), drug resistance genes, target genes, mouse model construction, and especially in genome-wide library screening. Furthermore, the CRISPR/Cas9 system can be utilized for gene therapy for CRC, specifically involving in the molecular targeted drug delivery or targeted knockout in vivo. In this review, we elucidate the mechanism of the CRISPR/Cas9 system and its comprehensive applications in CRC. Additionally, we discussed the issue of off-target effects associated with CRISPR/Cas9, which serves to restrict its practical application. Future research on CRC should in-depth and systematically utilize the CRISPR/Cas9 system thereby achieving clinical practice.

Abstract Background Radiolabeled-antibodies usually display non-specific liver accumulation that may impair image analysis and antibody biodistribution. Here, we investigated whether Fc silencing influenced antibody biodistribution. We compared recombinant 89Zr-labeled antibodies (human IgG1 against different targets) with wild-type Fc and with mutated Fc (LALAPG triple mutation to prevent binding to Fc gamma receptors; FcγR). After antibody injection in mice harboring xenografts of different tumor cell lines or of immortalized human myoblasts, we analyzed antibody biodistribution by PET-CT and conventional biodistribution analysis. Results Accumulation in liver was strongly reduced and tumor-specific targeting was increased for the antibodies with mutated Fc compared with wild-type Fc. Conclusion Antibodies with reduced binding to FcγR display lower liver accumulation and better tumor-to-liver ratios. These findings need to be taken into account to improve antibody-based theragnostic approaches.

Hypertension, also known as high or raised blood pressure, is a common condition in which the force of circulating blood pushing against the walls of the body's arteries is excessive. Antihypertensive drugs such as angiotensin II receptor blockers (ARBs) and angiotensinconverting enzyme (ACE) inhibitors, which target different proteins in the same pathway of the renin-angiotensin system, are usually recommended for first-line treatment. Identifying potential off-target proteins and possible side effects correlated with these antihypertensives can help shed light on the potential additional differences of these drugs and yield helpful information for the design and development of future antihypertensives. MAPK8 was identified as a potential off-target protein of valsartan, the chosen representative for ARB, through reverse docking and molecular dynamics. Valsartan exhibited similar binding as the known cocrystallized inhibitor, whereas lisinopril - an ACE inhibitor used for comparison - was unable to form a stable complex with MAPK8. Network analysis further identified E73 and K166 as key residues for valsartan binding while still maintaining the same signaling network as the apo structure. These observations may assist in future studies for the potential polypharmacology of valsartan and for the identification of new indications of already marketed drugs to facilitate drug discovery for other diseases. [ABSTRACT FROM AUTHOR]

Streptococcus pyogenes Cas9 (SpCas9) is the most popular tool in gene editing; however, off-target mutagenesis is one of the biggest impediments in its application. In our previous study, we proposed the HH theory, which states that sgRNA/DNA hybrid (hybrid) extrusion-induced enhancement of hydrophobic interactions between the hybrid and REC3/HNH is a key factor in cleavage initiation. Based on the HH theory, we analyzed the interactions between the REC3 domain and hybrid and obtained 8 mutant sites. We designed 8 SpCas9 variants (V1–V8), used digital droplet PCR to assess SpCas9-induced DNA indels in human cells, and developed high-fidelity variants. Thus, the HH theory may be employed to further optimize SpCas9-mediated genome editing systems, and the resultant V3, V6, V7, and V8 SpCas9 variants may be valuable for applications requiring high-precision genome editing. [ABSTRACT FROM AUTHOR]

In the last two decades, antisense oligonucleotide technology has emerged as a promising approach to tackling various healthcare issues and diseases, such as antimicrobial resistance, cancer, and neurodegenerative diseases. Despite the numerous improvements in the structure and modifications of the antisense oligonucleotides (ASOs), there are still specific problems with their clinical efficacy and preclinical cytotoxicity results. To better understand the effects of the ASOs in this paper, we conducted many MTT assays to assess the general and specific cytotoxicity of four new chimeric ASOs in bacterial cells and human cell lines. We demonstrate the absence of inhibitory activity in the human pathogenic bacteria Staphylococcus aureus by non-specific ASOs. The pVEC-ASO1 and pVEC-ASO2 are designed to have no specific targets in S. aureus. They have only partial hybridization to the guanylate kinase mRNA. The pVEC-ASO3 targets UBA2 mRNA, a hallmark cancer pathology in MYC-driven cancer, while pVEC-ASO4 has no complementary sequences. We discovered some cytotoxicity of the non-specific ASOs in healthy and cancer human cell lines. The results are compared with two other ASOs, targeting specific mRNA in cancer cells. All ASOs are delivered into the cell via the cell-penetrating oligopeptide pVEC, which is attached to them. We draw a good correlation between the thermodynamic stability of ASO/target RNA and the toxicity effect in human cell lines. The data obtained signify the importance of thorough bioinformatic analysis and high specificity in designing and developing novel ASOs for safer therapeutic agents in clinical practice. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Janus kinase (JAK) inhibitors were recently identified as promising drug candidates for repurposing in Alzheimer's disease (AD) due to their capacity to suppress inflammation via modulation of JAK/STAT signaling pathways. Besides interaction with primary therapeutic targets, JAK inhibitor drugs frequently interact with unintended, often unknown, biological off‐targets, leading to associated effects. Nevertheless, the relevance of JAK inhibitors' off‐target interactions in the context of AD remains unclear. METHODS: Putative off‐targets of baricitinib and tofacitinib were predicted using a machine learning (ML) approach. After screening scientific literature, off‐targets were filtered based on their relevance to AD. Targets that had not been previously identified as off‐targets of baricitinib or tofacitinib were subsequently tested using biochemical or cell‐based assays. From those, active concentrations were compared to bioavailable concentrations in the brain predicted by physiologically based pharmacokinetic (PBPK) modeling. RESULTS: With the aid of ML and in vitro activity assays, we identified two enzymes previously unknown to be inhibited by baricitinib, namely casein kinase 2 subunit alpha 2 (CK2‐α2) and dual leucine zipper kinase (MAP3K12), both with binding constant (Kd) values of 5.8 μM. Predicted maximum concentrations of baricitinib in brain tissue using PBPK modeling range from 1.3 to 23 nM, which is two to three orders of magnitude below the corresponding binding constant. CONCLUSION: In this study, we extended the list of baricitinib off‐targets that are potentially relevant for AD progression and predicted drug distribution in the brain. The results suggest a low likelihood of successful repurposing in AD due to low brain permeability, even at the maximum recommended daily dose. While additional research is needed to evaluate the potential impact of the off‐target interaction on AD, the combined approach of ML‐based target prediction, in vitro confirmation, and PBPK modeling may help prioritize drugs with a high likelihood of being effectively repurposed for AD. Highlights: This study explored JAK inhibitors' off‐targets in AD using a multidisciplinary approach.We combined machine learning, in vitro tests, and PBPK modelling to predict and validate new off‐target interactions of tofacitinib and baricitinib in AD.Previously unknown inhibition of two enzymes (CK2‐a2 and MAP3K12) by baricitinib were confirmed using in vitro experiments.Our PBPK model indicates that baricitinib low brain permeability limits AD repurposing.The proposed multidisciplinary approach optimizes drug repurposing efforts in AD research. [ABSTRACT FROM AUTHOR]

The identification of risks associated with novel agricultural products of plant origin obtained via genome editing is an important aspect of genetic engineering. An extensive discussion is currently ongoing worldwide to clarify the similarities and differences between the "old" risks of "classic" GM plants and the "new" ones associated with genome editing, the lack of existing methods for identification and assessment of new risks. We propose here the concept of "safe by design" as applied to protection that is a new interesting tool that introduces good known standards of safety into plant bioengineering. This approach states that design options are identified to minimize or prevent risks and off-target of genome editing at the concept stage. The correlation between experimentally determined and in silico predicted off-target gRNA activity is a major challenge in the CRISPR system application. Today the most studies are focused on efficiency of gRNA design, while we pay attention specifically to the bioinformatics search and study of potential promoters, as the potential risk associates with a possible unplanned change in the transcriptional activity of promoters. We conveyed these strategies in the form of a risk assessment framework for regulation of new genetic technologies. [ABSTRACT FROM AUTHOR]

Abstract INTRODUCTION Janus kinase (JAK) inhibitors were recently identified as promising drug candidates for repurposing in Alzheimer's disease (AD) due to their capacity to suppress inflammation via modulation of JAK/STAT signaling pathways. Besides interaction with primary therapeutic targets, JAK inhibitor drugs frequently interact with unintended, often unknown, biological off‐targets, leading to associated effects. Nevertheless, the relevance of JAK inhibitors’ off‐target interactions in the context of AD remains unclear. METHODS Putative off‐targets of baricitinib and tofacitinib were predicted using a machine learning (ML) approach. After screening scientific literature, off‐targets were filtered based on their relevance to AD. Targets that had not been previously identified as off‐targets of baricitinib or tofacitinib were subsequently tested using biochemical or cell‐based assays. From those, active concentrations were compared to bioavailable concentrations in the brain predicted by physiologically based pharmacokinetic (PBPK) modeling. RESULTS With the aid of ML and in vitro activity assays, we identified two enzymes previously unknown to be inhibited by baricitinib, namely casein kinase 2 subunit alpha 2 (CK2‐α2) and dual leucine zipper kinase (MAP3K12), both with binding constant (Kd) values of 5.8 μM. Predicted maximum concentrations of baricitinib in brain tissue using PBPK modeling range from 1.3 to 23 nM, which is two to three orders of magnitude below the corresponding binding constant. CONCLUSION In this study, we extended the list of baricitinib off‐targets that are potentially relevant for AD progression and predicted drug distribution in the brain. The results suggest a low likelihood of successful repurposing in AD due to low brain permeability, even at the maximum recommended daily dose. While additional research is needed to evaluate the potential impact of the off‐target interaction on AD, the combined approach of ML‐based target prediction, in vitro confirmation, and PBPK modeling may help prioritize drugs with a high likelihood of being effectively repurposed for AD. Highlights This study explored JAK inhibitors' off‐targets in AD using a multidisciplinary approach. We combined machine learning, in vitro tests, and PBPK modelling to predict and validate new off‐target interactions of tofacitinib and baricitinib in AD. Previously unknown inhibition of two enzymes (CK2‐a2 and MAP3K12) by baricitinib were confirmed using in vitro experiments. Our PBPK model indicates that baricitinib low brain permeability limits AD repurposing. The proposed multidisciplinary approach optimizes drug repurposing efforts in AD research.

The recalcitrance exhibited by many maize (Zea mays) genotypes to traditional genetic transformation protocols poses a significant challenge to the large-scale application of genome editing (GE) in this major crop species. Although a few maize genotypes are widely used for genetic transformation, they prove unsuitable for agronomic tests in field trials or commercial applications. This challenge is exacerbated by the predominance of transformable maize lines adapted to temperate geographies, despite a considerable proportion of maize production occurring in the tropics. Ectopic expression of morphogenic regulators (MRs) stands out as a promising approach to overcome low efficiency and genotype dependency, aiming to achieve ’universal’ transformation and GE capabilities in maize. Here, we report the successful GE of agronomically relevant tropical maize lines using a MR-based, Agrobacterium-mediated transformation protocol previously optimized for the B104 temperate inbred line. To this end, we used a CRISPR/Cas9-based construct aiming at the knockout of the VIRESCENT YELLOW-LIKE (VYL) gene, which results in an easily recognizable phenotype. Mutations at VYL were verified in protoplasts prepared from B104 and three tropical lines, regardless of the presence of a single nucleotide polymorphism (SNP) at the seed region of the VYL target site in two of the tropical lines. Three out of five tropical lines were amenable to transformation, with efficiencies reaching up to 6.63%. Remarkably, 97% of the recovered events presented indels at the target site, which were inherited by the next generation. We observed off-target activity of the CRISPR/Cas9-based construct towards the VYL paralog VYL-MODIFIER, which could be partly due to the expression of the WUSCHEL (WUS) MR. Our results demonstrate efficient GE of relevant tropical maize lines, expanding the current availability of GE-amenable genotypes of this major crop.

Colorectal cancer (CRC) is one of the most common malignant cancers worldwide and seriously threatens human health. The clustered regulatory interspaced short palindromic repeat/CRISPR-associate nuclease 9 (CRISPR/Cas9) system is an adaptive immune system of bacteria or archaea. Since its introduction, research into various aspects of treatment approaches for CRC has been accelerated, including investigation of the oncogenes, tumor suppressor genes (TSGs), drug resistance genes, target genes, mouse model construction, and especially in genome-wide library screening. Furthermore, the CRISPR/Cas9 system can be utilized for gene therapy for CRC, specifically involving in the molecular targeted drug delivery or targeted knockout in vivo. In this review, we elucidate the mechanism of the CRISPR/Cas9 system and its comprehensive applications in CRC. Additionally, we discussed the issue of off-target effects associated with CRISPR/Cas9, which serves to restrict its practical application. Future research on CRC should in-depth and systematically utilize the CRISPR/Cas9 system thereby achieving clinical practice. [ABSTRACT FROM AUTHOR]

The lymphocyte-specific protein tyrosine kinase (LCK) is a critical target in leukemia treatment. However, potential off-target interactions involving LCK can lead to unintended consequences. This underscores the importance of accurately predicting the inhibitory reactions of drug molecules with LCK during the research and development stage. To address this, we introduce an advanced ensemble machine learning technique designed to estimate the binding affinity between molecules and LCK. This comprehensive method includes the generation and selection of molecular fingerprints, the design of the machine learning model, hyperparameter tuning, and a model ensemble. Through rigorous optimization, the predictive capabilities of our model have been significantly enhanced, raising test R2 values from 0.644 to 0.730 and reducing test RMSE values from 0.841 to 0.732. Utilizing these advancements, our refined ensemble model was employed to screen an MCE -like drug library. Through screening, we selected the top ten scoring compounds, and tested them using the ADP-Glo bioactivity assay. Subsequently, we employed molecular docking techniques to further validate the binding mode analysis of these compounds with LCK. The exceptional predictive accuracy of our model in identifying LCK inhibitors not only emphasizes its effectiveness in projecting LCK-related safety panel predictions but also in discovering new LCK inhibitors. For added user convenience, we have also established a webserver, and a GitHub repository to share the project. [ABSTRACT FROM AUTHOR]

In silico design of single guide RNA (sgRNA) plays a critical role in clustered regularly interspaced, short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system. Continuous efforts are aimed at improving sgRNA design with efficient on-target activity and reduced off-target mutations. In the last 5 years, an increasing number of deep learning-based methods have achieved breakthrough performance in predicting sgRNA on- and off-target activities. Nevertheless, it is worthwhile to systematically evaluate these methods for their predictive abilities. In this review, we conducted a systematic survey on the progress in prediction of on- and off-target editing. We investigated the performances of 10 mainstream deep learning-based on-target predictors using nine public datasets with different sample sizes. We found that in most scenarios, these methods showed superior predictive power on large- and medium-scale datasets than on small-scale datasets. In addition, we performed unbiased experiments to provide in-depth comparison of eight representative approaches for off-target prediction on 12 publicly available datasets with various imbalanced ratios of positive/negative samples. Most methods showed excellent performance on balanced datasets but have much room for improvement on moderate- and severe-imbalanced datasets. This study provides comprehensive perspectives on CRISPR/Cas9 sgRNA on- and off-target activity prediction and improvement for method development. [ABSTRACT FROM AUTHOR]

Gene editing technology is regarded as a good news to save patients with genetic diseases because of its significant function of specifically changing genetic information. From zinc-finger proteins to transcription activator-like effector protein nucleases gene editing tools are constantly updated. At the same time, scientists are constantly developing a variety of new gene editing therapy strategies, in order to promote gene editing therapy from various aspects and realize the maturity of the technology as soon as possible. In 2016, CRISPR-Cas9-mediated CAR-T therapy was the first to enter the clinical trial stage, indicating that the use of CRISPR-Cas system as the blade of the genetic lancet to save patients is officially on the schedule. The first challenge to achieve this exciting goal is to improve the security of the technology. This review will introduce the gene security issues faced by the CRISPR system as a clinical treatment tool, the current safer delivery methods and the newly developed CRISPR editing tools with higher precision. Many reviews summarize the means of improving the security of gene editing therapy and the comprehensive delivery method, while few articles focus on the threat of gene editing to the genomic security of the treatment target. Therefore, this review focuses on the risks brought by gene editing therapy to the patient genome, which provides a broader perspective for exploring and improving the security of gene editing therapy from two aspects of delivery system and CRISPR editing tools. [ABSTRACT FROM AUTHOR]

Background: Radiolabeled-antibodies usually display non-specific liver accumulation that may impair image analysis and antibody biodistribution. Here, we investigated whether Fc silencing influenced antibody biodistribution. We compared recombinant 89Zr-labeled antibodies (human IgG1 against different targets) with wild-type Fc and with mutated Fc (LALAPG triple mutation to prevent binding to Fc gamma receptors; FcγR). After antibody injection in mice harboring xenografts of different tumor cell lines or of immortalized human myoblasts, we analyzed antibody biodistribution by PET-CT and conventional biodistribution analysis. Results: Accumulation in liver was strongly reduced and tumor-specific targeting was increased for the antibodies with mutated Fc compared with wild-type Fc. Conclusion: Antibodies with reduced binding to FcγR display lower liver accumulation and better tumor-to-liver ratios. These findings need to be taken into account to improve antibody-based theragnostic approaches. [ABSTRACT FROM AUTHOR]

A Cas9/guide RNA-based gene drive strain, AgNosCd-1, was developed to deliver antiparasite effector molecules to the malaria vector mosquito, Anopheles gambiae The drive system targets the cardinal gene ortholog producing a red-eye phenotype. Drive can achieve 98 to 100% in both sexes and full introduction was observed in small cage trials within 6 to 10 generations following a single release of gene-drive males. No genetic load resulting from the integrated transgenes impaired drive performance in the trials. Potential drive-resistant target-site alleles arise at a frequency

Designed donor DNA delivery through viral or nonviral systems to target loci in the host genome is a critical step for gene therapy. Adeno-associated virus and lentivirus are leading vehicles for in vivo and ex vivo delivery of therapeutic genes due to their high delivery and editing efficiency. Nonviral editing tools, such as CRISPR/Cas9, are getting more attention for gene modification. However, there are safety concerns; for example, tumorigenesis due to off-target effects and DNA rearrangement. Analysis tools to detect and characterize on-target and off-target genome modification post editing in the host genome are pivotal for evaluating the success and safety of gene therapy. We developed Target-seq combined with different analysis tools to detect the genome integration site, DNA translocation and off-target events.

Chemotherapy resistance is a persistent clinical problem in relapsed high‐risk neuroblastomas. We tested a panel of 15 drugs for sensitization of neuroblastoma cells to the conventional chemotherapeutic vincristine, identifying tariquidar, an inhibitor of the transmembrane pump P‐glycoprotein (P‐gp/ABCB1), and the ERBB family inhibitor afatinib as the top resistance breakers. Both compounds were efficient in sensitizing neuroblastoma cells to vincristine in trypan blue exclusion assays and in inducing apoptotic cell death. The evaluation of ERBB signaling revealed no functional inhibition, that is, dephosphorylation of the downstream pathways upon afatinib treatment but direct off‐target interference with P‐gp function. Depletion of ABCB1, but not ERRB4, sensitized cells to vincristine treatment. P‐gp inhibition substantially broke vincristine resistance in vitro and in vivo (zebrafish embryo xenograft). The analysis of gene expression datasets of more than 50 different neuroblastoma cell lines (primary and relapsed) and more than 160 neuroblastoma patient samples from the pediatric precision medicine platform INFORM (Individualized Therapy For Relapsed Malignancies in Childhood) confirmed a pivotal role of P‐gp specifically in neuroblastoma resistance at relapse, while the ERBB family appears to play a minor part.

Abstract We present a novel genome-wide off-target prediction method named Extru-seq and compare it with cell-based (GUIDE-seq), in vitro (Digenome-seq), and in silico methods using promiscuous guide RNAs with large numbers of valid off-target sites. Extru-seq demonstrates a high validation rate and retention of information about the intracellular environment, both beneficial characteristics of cell-based methods. Extru-seq also shows a low miss rate and could easily be performed in clinically relevant cell types with little optimization, which are major positive features of the in vitro methods. In summary, Extru-seq shows beneficial features of cell-based and in vitro methods.

Activation-induced cytidine deaminase (AID) plays a crucial role in promoting B cell diversification through somatic hypermutation (SHM) and class switch recombination (CSR). While AID is primarily associated with the physiological function of humoral immune response, it has also been linked to the initiation and progression of lymphomas. Abnormalities in AID have been shown to disrupt gene networks and signaling pathways in both B-cell and T-cell lineage lymphoblastic leukemia, although the full extent of its role in carcinogenesis remains unclear. This review proposes an alternative role for AID and explores its off-target effects in regulating tumorigenesis. In this review, we first provide an overview of the physiological function of AID and its regulation. AID plays a crucial role in promoting B cell diversification through SHM and CSR. We then discuss the off-target effects of AID, which includes inducing mutations of nonIgs, epigenetic modification, and the alternative role as a cofactor. We also explore the networks that keep AID in line. Furthermore, we summarize the offtarget effects of AID in autoimmune diseases and hematological neoplasms. Finally, we assess the off-target effects of AID in solid tumors. The primary focus of this review is to understand how and when AID targets specific gene loci and how this affects carcinogenesis. Overall, this review aims to provide a comprehensive understanding of the physiological and off-target effects of AID, which will contribute to the development of novel therapeutic strategies for autoimmune diseases, hematological neoplasms, and solid tumors. [ABSTRACT FROM AUTHOR]

Saccharomyces cerevisiae is one of widely used industrial strains, it is extremely important to increase its performance via modifying S. cerevisiae; however, there are cumbersome steps and long-cycle by traditional modifying method. CRISPR/Cas9 system is an adaptive defense system found in bacteria and archaea. At present, the CRISPR/Cas9 system has become a powerful tool for genome editing, which can simultaneously modify multiple genes of S. cerevisiae. This review provided a brief overview of the function and construction of CRISPR/Cas9 system in S. cerevisiae gene editing, introduced the design rules and representative design tools of sgRNA targeting sequences, as well as summarized the multiple-gene editing strategy. Moreover, the review discussed the challenges in application of CRISPR/Cas9 system, including off target and low editing efficiency, and their control measures, which may provide the references for better applying CRISPR/Cas9 system modifying S. cerevisiae. [ABSTRACT FROM AUTHOR]

Mitochondrial dysfunction is pivotal in drug-induced acute kidney injury (AKI), but the underlying mechanisms remain largely unknown. Transport proteins embedded in the mitochondrial inner membrane form a significant class of potential drug off-targets. So far, most transporter-drug interactions have been reported for the mitochondrial ADP/ATP carrier (AAC). Since it remains unknown to what extent AAC contributes to drug-induced mitochondrial dysfunction in AKI, we here aimed to better understand the functional role of AAC in the energy metabolism of human renal proximal tubular cells. To this end, CRISPR/Cas9 technology was applied to generate AAC3−/− human conditionally immortalized renal proximal tubule epithelial cells. This AAC3−/− cell model was characterized with respect to mitochondrial function and morphology. To explore whether this model could provide first insights into (mitochondrial) adverse drug effects with suspicion towards AAC-mediated mechanisms, wild-type and knockout cells were exposed to established AAC inhibitors, after which cellular metabolic activity and mitochondrial respiratory capacity were measured. Two AAC3−/− clones showed a significant reduction in ADP import and ATP export rates and mitochondrial mass, without influencing overall morphology. AAC3−/− clones exhibited reduced ATP production, oxygen consumption rates and metabolic spare capacity was particularly affected, mainly in conditions with galactose as carbon source. Chemical AAC inhibition was stronger compared to genetic inhibition in AAC3−/−, suggesting functional compensation by remaining AAC isoforms in our knockout model. In conclusion, our results indicate that ciPTEC-OAT1 cells have a predominantly oxidative phenotype that was not additionally activated by switching energy source. Genetic inhibition of AAC3 particularly impacted mitochondrial spare capacity, without affecting mitochondrial morphology, suggesting an important role for AAC in maintaining the metabolic spare respiration. [ABSTRACT FROM AUTHOR]

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New psychoactive substances (NPS) are introduced on the illicit drug market at a rapid pace. Their molecular targets are often inadequately elucidated, which contributes to the delayed characterization of their pharmacological effects. Inspired by earlier findings, this study set out to investigate the µ opioid receptor (MOR) activation potential of a large set of psychedelics, substances which typically activate the serotonin (5-HT2A) receptor as their target receptor. We observed that some substances carrying the N-benzyl phenethylamine (NBOMe) structure activated MOR, as confirmed by both the NanoBiT® βarr2 recruitment assay and the G protein-based AequoScreen® Ca2+ release assay. The use of two orthogonal systems proved beneficial as some aspecific, receptor independent effects were found for various analogs when using the Ca2+ release assay. The specific 'off-target' effects at MOR could be blocked by the opioid antagonist naloxone, suggesting that these NBOMes occupy the same common opioid binding pocket as conventional opioids. This was corroborated by molecular docking, which revealed the plausibility of multiple interactions of 25I-NBOMe with MOR, similar to those observed for opioids. Additionally, structure–activity relationship findings seen in vitro were rationalized in silico for two 25I-NBOMe isomers. Overall, as MOR activity of these psychedelics was only noticed at high concentrations, we consider it unlikely that for the tested compounds there will be a relevant opioid toxicity in vivo at physiologically relevant concentrations. However, small modifications to the original NBOMe structure may result in a panel of more efficacious and potent MOR agonists, potentially exhibiting a dual MOR/5-HT2A activation potential. [ABSTRACT FROM AUTHOR]

CRISPR/Cas9 technology is capable of precisely editing genomes and is at the heart of various scientific and medical advances in recent times. The advances in biomedical research are hindered because of the inadvertent burden on the genome when genome editors are employed—the off-target effects. Although experimental screens to detect off-targets have allowed understanding the activity of Cas9, that knowledge remains incomplete as the rules do not extrapolate well to new target sequences. Off-target prediction tools developed recently have increasingly relied on machine learning and deep learning techniques to reliably understand the complete threat of likely off-targets because the rules that drive Cas9 activity are not fully understood. In this study, we present a count-based as well as deep-learning-based approach to derive sequence features that are important in deciding on Cas9 activity at a sequence. There are two major challenges in off-target determination—the identification of a likely site of Cas9 activity and the prediction of the extent of Cas9 activity at that site. The hybrid multitask CNN–biLSTM model developed, named CRISP–RCNN, simultaneously predicts off-targets and the extent of activity on off-targets. Employing methods of integrated gradients and weighting kernels for feature importance approximation, analysis of nucleotide and position preference, and mismatch tolerance have been performed. [ABSTRACT FROM AUTHOR]

Off-target evaluation is essential in preclinical safety assessments of novel biotherapeutics, supporting lead molecule selection, endpoint selection in toxicology studies, and regulatory requirements for first-in-human trials. Off-target interaction of a therapeutic antibody and antibody derivatives has been historically assessed via the Tissue Cross-Reactivity (TCR) study, in which the candidate molecule is used as a reagent in immunohistochemistry (IHC) to assess binding of the candidate molecule to a panel of human tissue sections. The TCR approach is limited by the performance of the therapeutic as an IHC reagent, which is often suboptimal to outright infeasible. Furthermore, binding of the therapeutic in IHC conditions typically has poor in vitro to in vivo translation and lacks qualitative data of the identity of putative off-targets limiting the decisional value of the data. More recently, cell-based protein arrays (CBPA) that allow for screening against a large portion of the human membrane proteome and secretome have emerged as a complement, and likely a higher value alternative, to IHC-based off-target assessment. These arrays identify specific protein interactions and may be useful for testing nontraditional antibody-based therapeutic formats that are unsuitable for TCR studies. This article presents an overview of CBPA technologies in the context of TCR and off-target assessment studies. Selected case examples and strategic considerations covering a range of different modalities are presented. [ABSTRACT FROM AUTHOR]