RNA interference in insects: the link between antiviral defense and pest control

RNA interference (RNAi) is a form of gene silencing triggered by double-stranded RNA (dsRNA) that operates in all eukaryotic cells. RNAi has been widely investigated in insects to determine the underlying molecular mechanism, to investigate its role in systemic antiviral defense, and to develop strategies for pest control. When insect cells are infected by viruses, viral dsRNA signatures trigger a local RNAi response to block viral replication and generate virus-derived DNA that confers systemic immunity. RNAi-based insect pest control involves the application of exogenous dsRNA targeting genes essential for insect development or survival, but the efficacy of this approach has limited potency in many pests through a combination of rapid dsRNA degradation, inefficient dsRNA uptake/processing, and ineffective RNAi machinery. This could be addressed by dsRNA screening and evaluation, focusing on dsRNA design and off-target management, as well as dsRNA production and delivery. This review summarizes recent progress to determine the role of RNAi in antiviral defense and as a pest control strategy in insects, addressing gaps between our fundamental understanding of the RNAi mechanism and the exploitation of RNAi-based pest control strategies.

Repurposing of Chronically Used Drugs in Cancer Therapy: A Chance to Grasp

Despite the advancement in drug discovery for cancer therapy, drug repurposing remains an exceptional opportunistic strategy. This approach offers many advantages (faster, safer, and cheaper drugs) typically needed to overcome increased challenges, i.e., side effects, resistance, and costs associated with cancer therapy. However, not all drug classes suit a patient's condition or long-time use. For that, repurposing chronically used medications is more appealing. This review highlights the importance of repurposing anti-diabetic and anti-hypertensive drugs in the global fight against human malignancies. Extensive searches of all available evidence (up to 30 March 2023) on the anti-cancer activities of anti-diabetic and anti-hypertensive agents are obtained from multiple resources (PubMed, Google Scholar, ClinicalTrials.gov, Drug Bank database, ReDo database, and the National Institutes of Health). Interestingly, more than 92 clinical trials are evaluating the anti-cancer activity of 14 anti-diabetic and anti-hypertensive drugs against more than 15 cancer types. Moreover, some of these agents have reached Phase IV evaluations, suggesting promising official release as anti-cancer medications. This comprehensive review provides current updates on different anti-diabetic and anti-hypertensive classes possessing anti-cancer activities with the available evidence about their mechanism(s) and stage of development and evaluation. Hence, it serves researchers and clinicians interested in anti-cancer drug discovery and cancer management.

Design and off-target prediction for antisense oligomers targeting bacterial mRNAs with the MASON web server

Antisense oligomers (ASOs), such as peptide nucleic acids (PNAs), designed to inhibit the translation of essential bacterial genes, have emerged as attractive sequence- and species-specific programmable RNA antibiotics. Yet, potential drawbacks include unwanted side effects caused by their binding to transcripts other than the intended target. To facilitate the design of PNAs with minimal off-target effects, we developed MASON (make antisense oligomers now), a web server for the design of PNAs that target bacterial mRNAs. MASON generates PNA sequences complementary to the translational start site of a bacterial gene of interest and reports critical sequence attributes and potential off-target sites. We based MASON's off-target predictions on experiments in which we treated Salmonella enterica serovar Typhimurium with a series of 10-mer PNAs derived from a PNA targeting the essential gene acpP but carrying two serial mismatches. Growth inhibition and RNA-sequencing (RNA-seq) data revealed that PNAs with terminal mismatches are still able to target acpP, suggesting wider off-target effects than anticipated. Comparison of these results to an RNA-seq data set from uropathogenic Escherichia coli (UPEC) treated with eleven different PNAs confirmed that our findings are not unique to Salmonella We believe that MASON's off-target assessment will improve the design of specific PNAs and other ASOs.

Challenges of Gene Editing Therapies for Genodermatoses

Genodermatoses encompass a wide range of inherited skin diseases, many of which are monogenic. Genodermatoses range in severity and result in early-onset cancers or life-threatening damage to the skin, and there are few curative options. As such, there is a clinical need for single-intervention treatments with curative potential. Here, we discuss the nascent field of gene editing for the treatment of genodermatoses, exploring CRISPR-Cas9 and homology-directed repair, base editing, and prime editing tools for correcting pathogenic mutations. We specifically focus on the optimisation of editing efficiency, the minimisation off-targets edits, and the tools for delivery for potential future therapies. Honing each of these factors is essential for translating gene editing therapies into the clinical setting. Therefore, the aim of this review article is to raise important considerations for investigators aiming to develop gene editing approaches for genodermatoses.

A Machine Learning Approach to Identify the Importance of Novel Features for CRISPR/Cas9 Activity Prediction

The reprogrammable CRISPR/Cas9 genome editing tool's growing popularity is hindered by unwanted off-target effects. Efforts have been directed toward designing efficient guide RNAs as well as identifying potential off-target threats, yet factors that determine efficiency and off-target activity remain obscure. Based on sequence features, previous machine learning models performed poorly on new datasets, thus there is a need for the incorporation of novel features. The binding energy estimation of the gRNA-DNA hybrid as well as the Cas9-gRNA-DNA hybrid allowed generating better performing machine learning models for the prediction of Cas9 activity. The analysis of feature contribution towards the model output on a limited dataset indicated that energy features played a determining role along with the sequence features. The binding energy features proved essential for the prediction of on-target activity and off-target sites. The plateau, in the performance on unseen datasets, of current machine learning models could be overcome by incorporating novel features, such as binding energy, among others. The models are provided on GitHub (GitHub Inc., San Francisco, CA, USA).

Dissection of the epoxyjanthitrem pathway in Epichloë sp. LpTG-3 strain AR37 by CRISPR gene editing

Epichloë festucae var. lolii and Epichloë sp. LpTG-3 are filamentous fungal endophytes of perennial ryegrass (Lolium perenne) that have a substantial impact on New Zealand's agricultural economy by conferring biotic advantages to the host grass. Overall, Epichloë endophytes contribute NZ$200 million to the economy annually, with strain AR37 estimated to contribute NZ$3.6 billion to the New Zealand economy over a 20-year period. This strain produces secondary metabolites, including epoxyjanthitrems, which are a class of indole diterpenes, associated with the observed effects of AR37 on livestock and insect pests. Until very recently, AR37 was intractable to genetic modification but this has changed with the application of CRISPR-Cas9 based gene editing techniques. In this paper, gene inactivation by CRISPR-Cas9 was used to deconvolute the genetic basis for epoxyjanthitrem biosynthesis, including creating an AR37 strain that has been edited to remove the biosynthesis of all indole diterpenes. We show that gene editing of Epichloë can be achieved without off-target events or introduction of foreign DNA (footprint-less) through an AMA1-based plasmid that simultaneously expresses the CRISPR-Cas9 system and selectable marker. Genetic modification events in these transformants were investigated through genome sequencing and in planta chemistry.

CRISPR/Cas and Hepatitis B Therapy: Technological Advances and Practical Barriers

After almost a decade of using CRISPR/Cas9 systems to edit target genes, CRISPR/Cas9 and related technologies are rapidly moving to clinical trials. Hepatitis B virus (HBV), which causes severe liver disease, cannot be cleared by modern antivirals, but represents an ideal target for CRISPR/Cas9 systems. Early studies demonstrated very high antiviral potency of CRISPR/Cas9 and supported its use for developing a cure against chronic HBV infection. This review discusses the key issues that must be solved to make CRISPR/Cas9 an anti-HBV therapy.

Evolution of kinase polypharmacology across HSP90 drug discovery

Most small molecules interact with several target proteins but this polypharmacology is seldom comprehensively investigated or explicitly exploited during drug discovery. Here, we use computational and experimental methods to identify and systematically characterize the kinase cross-pharmacology of representative HSP90 inhibitors. We demonstrate that the resorcinol clinical candidates ganetespib and, to a lesser extent, luminespib, display unique off-target kinase pharmacology as compared with other HSP90 inhibitors. We also demonstrate that polypharmacology evolved during the optimization to discover luminespib and that the hit, leads, and clinical candidate all have different polypharmacological profiles. We therefore recommend the computational and experimental characterization of polypharmacology earlier in drug discovery projects to unlock new multi-target drug design opportunities.

The Off-Targets of Clustered Regularly Interspaced Short Palindromic Repeats Gene Editing

The repurposing of the CRISPR/Cas bacterial defense system against bacteriophages as simple and flexible molecular tools has revolutionized the field of gene editing. These tools are now widely used in basic research and clinical trials involving human somatic cells. However, a global moratorium on all clinical uses of human germline editing has been proposed because the technology still lacks the required efficacy and safety. Here we focus on the approaches developed since 2013 to decrease the frequency of unwanted mutations (the off-targets) during CRISPR-based gene editing.

LATE-a novel sensitive cell-based assay for the study of CRISPR/Cas9-related long-term adverse treatment effects

Since the introduction of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), genome editing has been broadly applied in basic research and applied biotechnology, whereas translation into clinical testing has raised safety concerns. Indeed, although frequencies and locations of off-target events have been widely addressed, little is known about their potential biological consequences in large-scale long-term settings. We have developed a long-term adverse treatment effect (LATE) in vitro assay that addresses potential toxicity of designer nucleases by assessing cell transformation events. In small-scale proof-of-principle experiments we reproducibly detected low-frequency (<0.5%) growth-promoting events in primary human newborn foreskin fibroblasts (NUFF cells) resulting from off-target cleavage in the TP53 gene. Importantly, the LATE assay detected not only off-target effects in TP53 not predicted by popular online tools but also growth-promoting mutations in other tumor suppressor genes, such as p21 and PLZF. It convincingly verified strongly reduced off-target activities of high fidelity compared with first-generation Cas9. Finally, the LATE assay was readily adapted to other cell types, namely clinically relevant human mesenchymal stromal cells (hMSCs) and retinal pigmented epithelial (RPE-1) cells. In conclusion, the LATE assay allows assessment of physiological adverse effects of the CRISPR/Cas system and might therefore be useful for preclinical safety studies.

Improved Functionality of Integration-Deficient Lentiviral Vectors (IDLVs) by the Inclusion of IS2 Protein Docks

Integration-deficient lentiviral vectors (IDLVs) have recently generated increasing interest, not only as a tool for transient gene delivery, but also as a technique for detecting off-target cleavage in gene-editing methodologies which rely on customized endonucleases (ENs). Despite their broad potential applications, the efficacy of IDLVs has historically been limited by low transgene expression and by the reduced sensitivity to detect low-frequency off-target events. We have previously reported that the incorporation of the chimeric sequence element IS2 into the long terminal repeat (LTR) of IDLVs increases gene expression levels, while also reducing the episome yield inside transduced cells. Our study demonstrates that the effectiveness of IDLVs relies on the balance between two parameters which can be modulated by the inclusion of IS2 sequences. In the present study, we explore new IDLV configurations harboring several elements based on IS2 modifications engineered to mediate more efficient transgene expression without affecting the targeted cell load. Of all the insulators and configurations analysed, the insertion of the IS2 into the 3′LTR produced the best results. After demonstrating a DAPI-low nuclear gene repositioning of IS2-containing episomes, we determined whether, in addition to a positive effect on transcription, the IS2 could improve the capture of IDLVs on double strand breaks (DSBs). Thus, DSBs were randomly generated, using the etoposide or locus-specific CRISPR-Cas9. Our results show that the IS2 element improved the efficacy of IDLV DSB detection. Altogether, our data indicate that the insertion of IS2 into the LTR of IDLVs improved, not only their transgene expression levels, but also their ability to be inserted into existing DSBs. This could have significant implications for the development of an unbiased detection tool for off-target cleavage sites from different specific nucleases.

Repurposing of Antimicrobial Agents for Cancer Therapy: What Do We Know?

The substantial costs of clinical trials, the lengthy timelines of new drug discovery and development, along the high attrition rates underscore the need for alternative strategies for finding quickly suitable therapeutics agents. Given that most approved drugs possess more than one target tightly linked to other diseases, it encourages promptly testing these drugs in patients. Over the past decades, this has led to considerable attention for drug repurposing, which relies on identifying new uses for approved or investigational drugs outside the scope of the original medical indication. The known safety of approved drugs minimizes the possibility of failure for adverse toxicology, making them attractive de-risked compounds for new applications with potentially lower overall development costs and shorter development timelines. This latter case is an exciting opportunity, specifically in oncology, due to increased resistance towards the current therapies. Indeed, a large body of evidence shows that a wealth of non-cancer drugs has beneficial effects against cancer. Interestingly, 335 drugs are currently being evaluated in different clinical trials for their potential activities against various cancers (Redo database). This review aims to provide an extensive discussion about the anti-cancer activities exerted by antimicrobial agents and presents information about their mechanism(s) of action and stage of development/evaluation.

Development of an Antigen-Antibody Co-Display System for Detecting Interaction of G-Protein-Coupled Receptors and Single-Chain Variable Fragments

G-protein-coupled receptors (GPCRs), especially chemokine receptors, are ideal targets for monoclonal antibody drugs. Considering the special multi-pass transmembrane structure of GPCR, it is often a laborious job to obtain antibody information about off-targets and epitopes on antigens. To accelerate the process, a rapid and simple method needs to be developed. The split-ubiquitin-based yeast two hybrid system (YTH) was used as a blue script for a new method. By fusing with transmembrane peptides, scFv antibodies were designed to be anchored on the cytomembrane, where the GPCR was co-displayed as well. The coupled split-ubiquitin system transformed the scFv-GPCR interaction signal into the expression of reporter genes. By optimizing the topological structure of scFv fusion protein and key elements, including signal peptides, transmembrane peptides, and flexible linkers, a system named Antigen-Antibody Co-Display (AACD) was established, which rapidly detected the interactions between antibodies and their target GPCRs, CXCR4 and CXCR5, while also determining the off-target antibodies and antibody-associated epitopes. The AACD system can rapidly determine the association between GPCRs and their candidate antibodies and shorten the research period for off-target detection and epitope identification. This system should improve the process of GPCR antibody development and provide a new strategy for GPCRs antibody screening.

Virus and Viroid-Derived Small RNAs as Modulators of Host Gene Expression: Molecular Insights Into Pathogenesis

Virus-derived siRNAs (vsiRNAs) generated by the host RNA silencing mechanism are effectors of plant’s defense response and act by targeting the viral RNA and DNA in post-transcriptional gene silencing (PTGS) and transcriptional gene silencing (TGS) pathways, respectively. Contrarily, viral suppressors of RNA silencing (VSRs) compromise the host RNA silencing pathways and also cause disease-associated symptoms. In this backdrop, reports describing the modulation of plant gene(s) expression by vsiRNAs via sequence complementarity between viral small RNAs (sRNAs) and host mRNAs have emerged. In some cases, silencing of host mRNAs by vsiRNAs has been implicated to cause characteristic symptoms of the viral diseases. Similarly, viroid infection results in generation of sRNAs, originating from viroid genomic RNAs, that potentially target host mRNAs causing typical disease-associated symptoms. Pathogen-derived sRNAs have been demonstrated to have the propensity to target wide range of genes including host defense-related genes, genes involved in flowering and reproductive pathways. Recent evidence indicates that vsiRNAs inhibit host RNA silencing to promote viral infection by acting as decoy sRNAs. Nevertheless, it remains unclear if the silencing of host transcripts by viral genome-derived sRNAs are inadvertent effects due to fortuitous pairing between vsiRNA and host mRNA or the result of genuine counter-defense strategy employed by viruses to enhance its survival inside the plant cell. In this review, we analyze the instances of such cross reaction between pathogen-derived vsiRNAs and host mRNAs and discuss the molecular insights regarding the process of pathogenesis.

Dasatinib Inhibits Lung Cancer Cell Growth and Patient Derived Tumor Growth in Mice by Targeting LIMK1

Lung cancer is a leading cause cancer-related death with diversity. A promising approach to meet the need for improved cancer treatment is drug repurposing. Dasatinib, a second generation of tyrosine kinase inhibitors (TKIs), is a potent treatment agent for chronic myeloid leukemia (CML) approved by FDA, however, its off-targets and the underlying mechanisms in lung cancer have not been elucidated yet. LIM kinase 1 (LIMK1) is a serine/threonine kinase, which is highly upregulated in human cancers. Herein, we demonstrated that dasatinib dose-dependently blocked lung cancer cell proliferation and repressed LIMK1 activities by directly targeting LIMK1. It was confirmed that knockdown of LIMK1 expression suppressed lung cancer cell proliferation. From the in silico screening results, dasatinib may target to LIMK1. Indeed, dasatinib significantly inhibited the LIMK1 activity as evidenced by kinase and binding assay, and computational docking model analysis. Dasatinib inhibited lung cancer cell growth, while induced cell apoptosis as well as cell cycle arrest at the G1 phase. Meanwhile, dasatinib also suppressed the expression of markers relating cell cycle, cyclin D1, D3, and CDK2, and increased the levels of markers involved in cell apoptosis, cleaved caspase-3 and caspase-7 by downregulating phosphorylated LIMK1 (p-LIMK1) and cofilin (p-cofilin). Furthermore, in patient-derived xenografts (PDXs), dasatinib (30 mg/kg) significantly inhibited the growth of tumors in SCID mice which highly expressed LIMK1 without changing the bodyweight. In summary, our results indicate that dasatinib acts as a novel LIMK1 inhibitor to suppress the lung cancer cell proliferation in vitro and tumor growth in vivo, which suggests evidence for the application of dasatinib in lung cancer therapy.

An up-to-date overview of computational polypharmacology in modern drug discovery

INTRODUCTION

In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success.

AREAS COVERED

In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies.

EXPERT OPINION

Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.

Binding site matching in rational drug design: algorithms and applications

Interactions between proteins and small molecules are critical for biological functions. These interactions often occur in small cavities within protein structures, known as ligand-binding pockets. Understanding the physicochemical qualities of binding pockets is essential to improve not only our basic knowledge of biological systems, but also drug development procedures. In order to quantify similarities among pockets in terms of their geometries and chemical properties, either bound ligands can be compared to one another or binding sites can be matched directly. Both perspectives routinely take advantage of computational methods including various techniques to represent and compare small molecules as well as local protein structures. In this review, we survey 12 tools widely used to match pockets. These methods are divided into five categories based on the algorithm implemented to construct binding-site alignments. In addition to the comprehensive analysis of their algorithms, test sets and the performance of each method are described. We also discuss general pharmacological applications of computational pocket matching in drug repurposing, polypharmacology and side effects. Reflecting on the importance of these techniques in drug discovery, in the end, we elaborate on the development of more accurate meta-predictors, the incorporation of protein flexibility and the integration of powerful artificial intelligence technologies such as deep learning.

Computational approach identifies protein off-targets for Isoniazid-NAD adduct: hypothesizing a possible drug resistance mechanism in Mycobacterium tuberculosis

Isoniazid is an important antitubercular molecule identified as a drug of choice in tuberculosis treatment. As such, INH is an inactive prodrug; it acquires an active conformation by forming an adduct with NAD. The adduct targets inhA protein, a reductase responsible for fatty acid chain elongation in the cell wall of Mycobacterium tuberculosis. Resistance to INH is majorly contributed by mutations in inhA, katG and geneic and non-geneic regions associated with efflux genes. Despite being widespread, the mechanism of resistance remains unknown in ∼15% of INH-resistant strains. Studies report that an intracellular increase in NADH concentration prevents inhA inhibition, leading to INH resistance. In the pursuit of finding possible resistance mechanisms, we set out to find NAD binding proteins to explore similarities in structure and NAD binding property of these proteins with that of inhA. We identified 172 NAD binding proteins, of which 53 were identified to have sequence or structural similarity to inhA. By performing docking analysis on selected proteins, we identified INH-adduct to have good binding affinity despite very minimal structural similarity to inhA. This analysis was further supported by principal component analysis, which identified 65 proteins with NAD binding conformation similar to that of inhA. These findings prompt us to hypothesize that upon exposure to INH, bacteria tries to reduce inhA susceptibility by inducing expression of these NAD binding proteins through increase in NADH concentration. This in turn favours off-target binding and leads to decreased binding and potency of INH, thus contributing indirectly to INH resistance.Communicated by Ramaswamy H. Sarma.

Enhanced Genome Editing with Cas9 Ribonucleoprotein in Diverse Cells and Organisms

Site-specific eukaryotic genome editing with CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) systems has quickly become a commonplace amongst researchers pursuing a wide variety of biological questions. Users most often employ the Cas9 protein derived from Streptococcus pyogenes in a complex with an easily reprogrammed guide RNA (gRNA). These components are introduced into cells, and through a base pairing with a complementary region of the double-stranded DNA (dsDNA) genome, the enzyme cleaves both strands to generate a double-strand break (DSB). Subsequent repair leads to either random insertion or deletion events (indels) or the incorporation of experimenter-provided DNA at the site of the break. The use of a purified single-guide RNA and Cas9 protein, preassembled to form an RNP and delivered directly to cells, is a potent approach for achieving highly efficient gene editing. RNP editing particularly enhances the rate of gene insertion, an outcome that is often challenging to achieve. Compared to the delivery via a plasmid, the shorter persistence of the Cas9 RNP within the cell leads to fewer off-target events. Despite its advantages, many casual users of CRISPR gene editing are less familiar with this technique. To lower the barrier to entry, we outline detailed protocols for implementing the RNP strategy in a range of contexts, highlighting its distinct benefits and diverse applications. We cover editing in two types of primary human cells, T cells and hematopoietic stem/progenitor cells (HSPCs). We also show how Cas9 RNP editing enables the facile genetic manipulation of entire organisms, including the classic model roundworm Caenorhabditis elegans and the more recently introduced model crustacean, Parhyale hawaiensis.

Genome-wide determination of on-target and off-target characteristics for RNA-guided DNA methylation by dCas9 methyltransferases

Background

Fusion of DNA methyltransferase domains to the nuclease-deficient clustered regularly interspaced short palindromic repeat (CRISPR) associated protein 9 (dCas9) has been used for epigenome editing, but the specificities of these dCas9 methyltransferases have not been fully investigated.

Findings

We generated CRISPR-guided DNA methyltransferases by fusing the catalytic domain of DNMT3A or DNMT3B to the C terminus of the dCas9 protein from Streptococcus pyogenes and validated its on-target and global off-target characteristics. Using targeted quantitative bisulfite pyrosequencing, we prove that dCas9-BFP-DNMT3A and dCas9-BFP-DNMT3B can efficiently methylate the CpG dinucleotides flanking its target sites at different genomic loci (uPA and TGFBR3) in human embryonic kidney cells (HEK293T). Furthermore, we conducted whole genome bisulfite sequencing (WGBS) to address the specificity of our dCas9 methyltransferases. WGBS revealed that although dCas9-BFP-DNMT3A and dCas9-BFP-DNMT3B did not cause global methylation changes, a substantial number (more than 1000) of the off-target differentially methylated regions (DMRs) were identified. The off-target DMRs, which were hypermethylated in cells expressing dCas9 methyltransferase and guide RNAs, were predominantly found in promoter regions, 5΄ untranslated regions, CpG islands, and DNase I hypersensitivity sites, whereas unexpected hypomethylated off-target DMRs were significantly enriched in repeated sequences. Through chromatin immunoprecipitation with massive parallel DNA sequencing analysis, we further revealed that these off-target DMRs were weakly correlated with dCas9 off-target binding sites. Using quantitative polymerase chain reaction, RNA sequencing, and fluorescence reporter cells, we also found that dCas9-BFP-DNMT3A and dCas9-BFP-DNMT3B can mediate transient inhibition of gene expression, which might be caused by dCas9-mediated de novo DNA methylation as well as interference with transcription.

Conclusion

Our results prove that dCas9 methyltransferases cause efficient RNA-guided methylation of specific endogenous CpGs. However, there is significant off-target methylation indicating that further improvements of the specificity of CRISPR-dCas9 based DNA methylation modifiers are required.

Molecular Connectivity Predefines Polypharmacology: Aliphatic Rings, Chirality, and sp3 Centers Enhance Target Selectivity

Dark chemical matter compounds are small molecules that have been recently identified as highly potent and selective hits. For this reason, they constitute a promising class of possible candidates in the process of drug discovery and raise the interest of the scientific community. To this purpose, Wassermann et al. (2015) have described the application of 2D descriptors to characterize dark chemical matter. However, their definition was based on the number of reported positive assays rather than the number of known targets. As there might be multiple assays for one single target, the number of assays does not fully describe target selectivity. Here, we propose an alternative classification of active molecules that is based on the number of known targets. We cluster molecules in four classes: black, gray, and white compounds are active on one, two to four, and more than four targets respectively, whilst inactive compounds are found to be inactive in the considered assays. In this study, black and inactive compounds are found to have not only higher solubility, but also a higher number of chiral centers, sp3 carbon atoms and aliphatic rings. On the contrary, white compounds contain a higher number of double bonds and fused aromatic rings. Therefore, the design of a screening compound library should consider these molecular properties in order to achieve target selectivity or polypharmacology. Furthermore, analysis of four main target classes (GPCRs, kinases, proteases, and ion channels) shows that GPCR ligands are more selective than the other classes, as the number of black compounds is higher in this target superfamily. On the other side, ligands that hit kinases, proteases, and ion channels bind to GPCRs more likely than to other target classes. Consequently, depending on the target protein family, appropriate screening libraries can be designed in order to minimize the likelihood of unwanted side effects early in the drug discovery process. Additionally, synergistic effects may be obtained by library design toward polypharmacology.

Selective Therapeutic Intervention: A Challenge against Off-Target Effects

Despite the massive global spend on biology-driven drug discovery, tackling the issue of side effects and adverse events resulting from drug promiscuity represents a persistent challenge. Although delivering authentic medical innovations today is more complex than ever, minimization of off-target effects should be a priority.

Preclinical Evaluation of a Lentiviral Vector for Huntingtin Silencing

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder resulting from a polyglutamine expansion in the huntingtin (HTT) protein. There is currently no cure for this disease, but recent studies suggest that RNAi to downregulate the expression of both normal and mutant HTT is a promising therapeutic approach. We previously developed a small hairpin RNA (shRNA), vectorized in an HIV-1-derived lentiviral vector (LV), that reduced pathology in an HD rodent model. Here, we modified this vector for preclinical development by using a tat-independent third-generation LV (pCCL) backbone and removing the original reporter genes. We demonstrate that this novel vector efficiently downregulated HTT expression in vitro in striatal neurons derived from induced pluripotent stem cells (iPSCs) of HD patients. It reduced two major pathological HD hallmarks while triggering a minimal inflammatory response, up to 6 weeks after injection, when administered by stereotaxic surgery in the striatum of an in vivo rodent HD model. Further assessment of this shRNA vector in vitro showed proper processing by the endogenous silencing machinery, and we analyzed gene expression changes to identify potential off-targets. These preclinical data suggest that this new shRNA vector fulfills primary biosafety and efficiency requirements for further development in the clinic as a cure for HD.

"Off-Spotter": very fast and exhaustive enumeration of genomic lookalikes for designing CRISPR/Cas guide RNAs

BACKGROUND

CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR associated nucleases) is a powerful component of the prokaryotic immune system that has been adapted for targeted genetic engineering in higher organisms. A key element of CRISPR/Cas is the "guide" RNA (gRNA) that is ~20 nucleotides (nts) in length and designed to be complementary to the intended target site. An integral requirement of the CRISPR/Cas system is that the target site be followed by a protospacer adjacent motif (PAM). Care needs to be exercised during gRNA design to avoid unintended ("off-target") interactions.

RESULTS

We designed and implemented the Off-Spotter algorithm to assist with the design of optimal gRNAs. When presented with a candidate gRNA sequence and a PAM, Off-Spotter quickly and exhaustively identifies all genomic sites that satisfy the PAM constraint and are identical or nearly-identical to the provided gRNA. Off-Spotter achieves its extreme performance through purely algorithmic means and not through hardware accelerators such as graphical processing units (GPUs). Off-Spotter also allows the user to identify on-the-fly how many and which nucleotides of the gRNA comprise the "seed". Off-Spotter's output includes a histogram showing the number of potential off-targets as a function of the number of mismatches. The output also includes for each potential off-target the site's genomic location, a human genome browser hyperlink to the corresponding location, genomic annotation in the vicinity of the off-target, GC content, etc.

CONCLUSION

Off-Spotter is very fast and flexible and can help in the design of optimal gRNAs by providing several PAM choices, a run-time definition of the seed and of the allowed number of mismatches, and a flexible output interface that allows sorting of the results, optional viewing/hiding of columns, etc. A key element of Off-Spotter is that it does not have a rigid definition of the seed: instead, the user can declare both the seed's location and extent on-the-fly. We expect that this flexibility in combination with Off-Spotter's speed and richly annotated output will enable experimenters to interactively and quickly explore different scenarios and gRNA possibilities.

Target specificity of the CRISPR-Cas9 system

The CRISPR-Cas9 system, naturally a defense mechanism in prokaryotes, has been repurposed as an RNA-guided DNA targeting platform. It has been widely used for genome editing and transcriptome modulation, and has shown great promise in correcting mutations in human genetic diseases. Off-target effects are a critical issue for all of these applications. Here we review the current status on the target specificity of the CRISPR-Cas9 system.