Identification of a Novel Protein Arginine Methyltransferase 5 Inhibitor in Non-small Cell Lung Cancer by Structure-Based Virtual Screening

Epigallocatechin-3-gallate inhibit the protein arginine methyltransferase 5 and enhancer of Zeste homolog 2 in breast cancer both in vitro and in vivo

PURPOSE

Histone methyltransferases are enzymes that selectively methylate lysine or arginine residues on both histone and non-histone proteins, categorized into lysine methyltransferases and arginine methyltransferases. Notably, EZH2 and PRMT5 are known for catalyzing trimethylation of H3 at K27 and symmetric dimethylation of H4 at R3, respectively. These methylation events are recognized as characteristic histone-repressive marks in cancer. The over expression of PRMT5 and EZH2 were reported in various cancers and recognized as a drug target. The study aims to explore the inhibitory potential of phytocompound, Epigallocatechin-3-gallate (EGCG), against PRMT5 and EZH2 in the breast cancer model.

METHODS

Screening of an array of phytocompounds was conducted through a combination of in-silico and in-vitro assays. Interactions between EGCG and human PRMT5: MEP50 and EZH2 were evaluated using molecular docking. Binding efficiency was validated, by Surface Plasmon Resonance studies and inhibitory potential was accessed by in vitro methylation followed by western blots, ELISA, and cell-based assays. In-vivo efficacy of EGCG was carried on cell line derived mice xenograft model.

RESULTS

EGCG demonstrated robust interactions with PRMT5:MEP50 complex and EZH2, particularly within the SAM binding site. Surface Plasmon Resonance analysis revealed strong binding affinity in nanomolar concentrations, particularly with PRMT5-MEP50 compared to EZH2. In-vitro assays confirmed EGCG's ability to inhibit PRMT5 and EZH2, leading to a decrease in their catalytic products, namely H4R3me2s and H3K27me3, respectively. EGCG treatment induced both autophagy and apoptosis invitro. In-vivo studies demonstrated significant reductions in tumor size and the proliferation marker ki67, accompanied by a decrease in histone repressive marks.

CONCLUSION

The findings suggest that EGCG effectively inhibits PRMT5 and EZH2, underscoring its potential for combined therapeutic strategies in cancer treatment.

Medicinal chemistry insights into PRMT5 inhibitors

Protein arginine methyltransferase 5 (PRMT5) is a type II PRMT enzyme that plays an important role in protein formation. PRMT5 is widely distributed in the nucleus and is involved in regulating a variety of biological processes, including gene transcription, signaling, and cell proliferation. PRMT5 regulates the function and stability of histones through methylation, affecting important cellular activities such as cell cycle regulation, DNA repair, and RNA processing. Studies have shown that PRMT5 is overexpressed in a variety of tumors and is closely related to the occurrence and development of tumors. In recent years, several PRMT5 inhibitors have entered clinical trials for the treatment of various cancers. In view of their importance, this paper reviews the first generation of PRMT5 inhibitors obtained by high-throughput screening, virtual screening, lead compound optimization and substitution modification, as well as novel PRMT5 inhibitors obtained by PROTAC technology and by synthetic lethal principle. Finally, by comparing the differences between the first generation and the second generation, the challenges and future development directions of PRMT5 inhibitors are discussed.

Identification of mIDH1 R132C/S280F Inhibitors from Natural Products by Integrated Molecular Docking, Pharmacophore Modeling and Molecular Dynamics Simulations

Mutant isocitrate dehydrogenase 1 (mIDH1) is a common driving factor in acute myeloid leukemia (AML), with the R132 mutation accounting for a high proportion. The U.S. Food and Drug Administration (FDA) approved Ivosidenib, a molecular entity that targets IDH1 with R132 mutations, as a promising therapeutic option for AML with mIDH1 in 2018. It was of concern that the occurrence of disease resistance or recurrence, attributed to the IDH1 R132C/S280F second site mutation, was observed in certain patients treated with Ivosidenib within the same year. Furthermore, it should be noted that most mIDH1 inhibitors demonstrated limited efficacy against mutations at this specific site. Therefore, there is an urgent need to investigate novel inhibitors targeting mIDH1 for combating resistance caused by IDH1 R132C/S280F mutations in AML. This study aimed to identify novel mIDH1 R132C/S280F inhibitors through an integrated strategy of combining virtual screening and dynamics simulations. First, 2000 hits were obtained through structure-based virtual screening of the COCONUT database, and hits with better scores than -10.67 kcal/mol were obtained through molecular docking. A total of 12 potential small molecule inhibitors were identified through pharmacophore modeling screening and Prime MM-GBSA. Dynamics simulations were used to study the binding modes between the positive drug and the first three hits and IDH1 carrying the R132C/S280F mutation. RMSD showed that the four dynamics simulation systems remained stable, and RMSF and Rg showed that the screened molecules have similar local flexibility and tightness to the positive drug. Finally, the lowest energy conformation, hydrogen bond analysis, and free energy decomposition results indicate that in the entire system the key residues LEU120, TRP124, TRP267, and VAL281 mainly contribute van der Waals forces to the interaction, while the key residues VAL276 and CYS379 mainly contribute electrostatic forces.

Artificial intelligence: Machine learning approach for screening large database and drug discovery

Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance due to rapidly accumulating mutations. Virtual screening is the most widely used method in computer aided drug discovery. It has a prominent ability in screening drug targets from large molecular databases. Recently, a number of web servers have developed for quickly screening publicly accessible chemical databases. In a nutshell, deep learning algorithms and artificial neural networks have modernised the field. Several drug discovery processes have used machine learning and deep learning algorithms, including peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modelling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Although there are presently a wide variety of data-driven AI/ML tools available, the majority of these tools have, up to this point, been developed in the context of non-communicable diseases like cancer, and a number of obstacles have prevented the translation of these tools to the discovery of treatments against infectious diseases. In this review various aspects of AI and ML in virtual screening of large databases were discussed. Here, with an emphasis on antivirals as well as other disease, offers a perspective on the advantages, drawbacks, and hazards of AI/ML techniques in the search for innovative treatments.

Discovery of novel PRMT5 inhibitors bearing a methylpiperazinyl moiety

Background: PRMT5 is an epigenetics-related enzyme, which plays a critical role in cancer development. Hence PRMT5 inhibition has been validated as a promising therapeutic strategy. Methods & Results: We synthesized a series of methylpiperazinyl derivatives as novel PRMT5 inhibitors that were achieved by scaffold-hopping from EPZ015666 by virtual screening followed by rational drug design. Among all compounds 43g, bearing a thiourea linker, showed antitumor activity across multiple cancer cell lines and reduced the level of symmetric arginine dimethylation of SmD3 dose-dependently. Moreover, 43g selectively inhibited PRMT5 among protein arginine methyltransferase isoforms. Further proteomics analysis revealed that 43g remarkably reduced the global arginine dimethylation level in a cellular context. Conclusion: This work provides new chemical templates for future structural optimization of PRMT5-related cancer treatments.

Protein Arginine Methylation: An Emerging Modification in Cancer Immunity and Immunotherapy

In recent years, protein arginine methyltransferases (PRMTs) have emerged as new members of a gene expression regulator family in eukaryotes, and are associated with cancer pathogenesis and progression. Cancer immunotherapy has significantly improved cancer treatment in terms of overall survival and quality of life. Protein arginine methylation is an epigenetic modification function not only in transcription, RNA processing, and signal transduction cascades, but also in many cancer-immunity cycle processes. Arginine methylation is involved in the activation of anti-cancer immunity and the regulation of immunotherapy efficacy. In this review, we summarize the most up-to-date information on regulatory molecular mechanisms and different underlying arginine methylation signaling pathways in innate and adaptive immune responses during cancer. We also outline the potential of PRMT-inhibitors as effective combinatorial treatments with immunotherapy.

Discovery of Novel HPK1 Inhibitors Through Structure-Based Virtual Screening

Hematopoietic progenitor kinase (HPK1) is a negative regulator of T-cell receptor and B-cell signaling, which has been recognized as a novel antitumor target for immunotherapy. In this work, Glide docking-based virtual screening and kinase inhibition assay were performed to identify novel HPK1 inhibitors. The kinase inhibition assay results demonstrated five compounds with IC50 values below 20 μM, and the most potent one (compound M074-2865) had an IC50 value of 2.93 ± 0.09 μM. Molecular dynamics (MD) simulations were performed to delve into the interaction of sunitinib and the identified compound M074-2865 with the kinase domain of HPK1. The five compounds identified in this work could be considered promising hit compounds for further development of HPK1 inhibitors for immunotherapy.

The arginine methyltransferase PRMT7 promotes extravasation of monocytes resulting in tissue injury in COPD

Extravasation of monocytes into tissue and to the site of injury is a fundamental immunological process, which requires rapid responses via post translational modifications (PTM) of proteins. Protein arginine methyltransferase 7 (PRMT7) is an epigenetic factor that has the capacity to mono-methylate histones on arginine residues. Here we show that in chronic obstructive pulmonary disease (COPD) patients, PRMT7 expression is elevated in the lung tissue and localized to the macrophages. In mouse models of COPD, lung fibrosis and skin injury, reduced expression of PRMT7 associates with decreased recruitment of monocytes to the site of injury and hence less severe symptoms. Mechanistically, activation of NF-κB/RelA in monocytes induces PRMT7 transcription and consequential mono-methylation of histones at the regulatory elements of RAP1A, which leads to increased transcription of this gene that is responsible for adhesion and migration of monocytes. Persistent monocyte-derived macrophage accumulation leads to ALOX5 over-expression and accumulation of its metabolite LTB4, which triggers expression of ACSL4 a ferroptosis promoting gene in lung epithelial cells. Conclusively, inhibition of arginine mono-methylation might offer targeted intervention in monocyte-driven inflammatory conditions that lead to extensive tissue damage if left untreated.

Targeting protein arginine methyltransferase 5 in cancers: Roles, inhibitors and mechanisms

The protein arginine methyltransferase 5 (PRMT5) as the major type II arginine methyltransferase catalyzes the mono- and symmetric dimethylation of arginine residues in both histone and non-histone proteins. Recently, increasing evidence has demonstrated that PRMT5 plays an indispensable role in the occurrence and development of various human cancers by promoting the cell proliferation, invasion, and migration. It has become a promising and valuable target in the cancer epigenetic therapy. This review is to summarize the clinical significance of PRMT5 in the cancers such as lung cancer, breast cancer and colorectal cancer, and the drug discovery targeting PRMT5. Importantly, the existing PRMT5 inhibitors representing different molecular mechanisms, and their pharmacological effect, mechanism of action and biological affinity are analyzed. Clinical status, current problems and future perspective of PRMT5 inhibitors for the treatment of cancers are also discussed, all of which provides crucial help for the future discovery of PRMT5 targeted drugs for cancer treatment.

Acquired resistance to PRMT5 inhibition induces concomitant collateral sensitivity to paclitaxel

Epigenetic regulators play key roles in cancer and are increasingly being targeted for treatment. However, for many, little is known about mechanisms of resistance to the inhibition of these regulators. We have generated a model of resistance to inhibitors of protein arginine methyltransferase 5 (PRMT5). This study was conducted in KrasG12D;Tp53-null lung adenocarcinoma (LUAD) cell lines. Resistance to PRMT5 inhibitors (PRMT5i) arose rapidly, and barcoding experiments showed that this resulted from a drug-induced transcriptional state switch, not selection of a preexisting population. This resistant state is both stable and conserved across variants arising from distinct LUAD lines. Moreover, it brought with it vulnerabilities to other chemotherapeutics, especially the taxane paclitaxel. This paclitaxel sensitivity depended on the presence of stathmin 2 (STMN2), a microtubule regulator that is specifically expressed in the resistant state. Remarkably, STMN2 was also essential for resistance to PRMT5 inhibition. Thus, a single gene is required for both acquisition of resistance to PRMT5i and collateral sensitivity to paclitaxel in our LUAD cells. Accordingly, the combination of PRMT5i and paclitaxel yielded potent and synergistic killing of the murine LUAD cells. Importantly, the synergy between PRMT5i and paclitaxel also extended to human cancer cell lines. Finally, analysis of The Cancer Genome Atlas patient data showed that high STMN2 levels correlate with complete regression of tumors in response to taxane treatment. Collectively, this study reveals a recurring mechanism of PRMT5i resistance in LUAD and identifies collateral sensitivities that have potential clinical relevance.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. The primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure-activity relationship to drug repositioning, protein misfolding to protein-protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Ribavirin inhibits colorectal cancer growth by downregulating PRMT5 expression and H3R8me2s and H4R3me2s accumulation

Eukaryotic translation initiation factor 4E (eIF4E) and protein arginine methyltransferase 5 (PRMT5) are frequently overexpressed in colorectal cancer (CRC) tissues and associated with poor prognosis. Ribavirin, the only clinically approved drug known to target eIF4E, is an anti-viral molecule currently used in hepatitis C therapy. The potential of ribavirin to treat CRC remains largely unknown. Ribavirin treatment in CRC cell lines drastically inhibited cell proliferation and colony formation, induced S phase arrest and reduced cyclin D1, cyclin A/E and proliferating cell nuclear antigen (PCNA) levels in vitro, and suppressed tumorigenesis in mouse model of colitis-associated CRC. Mechanistically, ribavirin treatment significantly reduced PRMT5 and eIF4E protein levels and the accumulation of symmetric dimethylation of histone 3 at arginine 8 (H3R8me2s) and that of histone 4 at arginine 3 (H4R3me2s). Importantly, inhibition of PRMT5 by ribavirin resulted in promoted H3R8 methylation in eIF4E promoter region. Our results demonstrate the anti-cancer efficacy of ribavirin in CRC and suggest that the anti-cancer efficacy of ribavirin may be mediated by downregulating PRMT5 levels but not its enzymatic activity.

Protein Arginine Methyltransferase 5 (PRMT5) and the ERK1/2 & PI3K Pathways: A Case for PRMT5 Inhibition and Combination Therapies in Cancer

The ERK1/2 (RAS, RAF, MEK, ERK) and PI3K (PI3K, AKT, mTOR, PTEN) pathways are the chief signaling pathways for cellular proliferation, survival, and differentiation. Overactivation and hyperphosphorylation of the ERK1/2 & PI3K pathways is frequently observed in cancer and is associated with poor patient prognosis. While it is well known that genetic alterations lead to the dysregulation of the ERK1/2 & PI3K pathways, increasing evidence showcase that epigenetic alterations also play a major role in the regulation of the ERK1/2 & PI3K pathways. Protein Arginine Methyltransferase 5 (PRMT5) is a posttranslational modifier for multiple cellular processes, which is currently being tested as a therapeutic target for cancer. PRMT5 has been shown to be overexpressed in many types of cancers, as well as negatively correlated with patient survival. Numerous studies are indicating that as a posttranslational modifier, PRMT5 is extensively involved in regulating the ERK1/2 & PI3K pathways. In addition, a large number of in vitro and in vivo studies are demonstrating that PRMT5 inhibition, as well as PRMT5 and ERK1/2 & PI3K combination therapies, show significant therapeutic effects in many cancer types. In this review, we explore the vast interactions that PRMT5 has with the ERK1/2 & PI3K pathways, and we make the case for further testing of PRMT5 inhibition, as well as PRMT5 and ERK1/2 & PI3K combination therapies, for the treatment of cancer.

PRMT5 silencing selectively affects MTAP-deleted mesothelioma: In vitro evidence of a novel promising approach

Malignant mesothelioma (MM) is an aggressive asbestos‐related cancer of the serous membranes. Despite intensive treatment regimens, MM is still a fatal disease, mainly due to the intrinsic resistance to current therapies and the lack of predictive markers and new valuable molecular targets. Protein arginine methyltransferase 5 (PRMT5) inhibition has recently emerged as a potential therapy against methylthioadenosine phosphorylase (MTAP)‐deficient cancers, in which the accumulation of the substrate 5'‐methylthioadenosine (MTA) inhibits PRMT5 activity, thus sensitizing the cells to further PRMT5 inhibition. Considering that the MTAP gene is frequently codeleted with the adjacent cyclin‐dependent kinase inhibitor 2A (CDKN2A) locus in MM, we assessed whether PRMT5 could represent a therapeutic target also for this cancer type. We evaluated PRMT5 expression, the MTAP status and MTA content in normal mesothelial and MM cell lines. We found that both administration of exogenous MTA and stable PRMT5 knock‐down, by short hairpin RNAs (shRNAs), selectively reduced the growth of MTAP‐deleted MM cells. We also observed that PRMT5 knock‐down in MTAP‐deficient MM cells reduced the expression of E2F1 target genes involved in cell cycle progression and of factors implicated in epithelial‐to‐mesenchymal transition. Therefore, PRMT5 targeting could represent a promising new therapeutic strategy against MTAP‐deleted MMs.

Protein Arginine Methyltransferases in Cardiovascular and Neuronal Function

The methylation of arginine residues by protein arginine methyltransferases (PRMTs) is a type of post-translational modification which is important for numerous cellular processes, including mRNA splicing, DNA repair, signal transduction, protein interaction, and transport. PRMTs have been extensively associated with various pathologies, including cancer, inflammation, and immunity response. However, the role of PRMTs has not been well described in vascular and neurological function. Aberrant expression of PRMTs can alter its metabolic products, asymmetric dimethylarginine (ADMA), and symmetric dimethylarginine (SDMA). Increased ADMA levels are recognized as an independent risk factor for cardiovascular disease and mortality. Recent studies have provided considerable advances in the development of small-molecule inhibitors of PRMTs to study their function under normal and pathological states. In this review, we aim to elucidate the particular roles of PRMTs in vascular and neuronal function as a potential target for cardiovascular and neurological diseases.

Compound C620-0696, a new potent inhibitor targeting BPTF, the chromatin-remodeling factor in non-small-cell lung cancer

Bromodomain PHD-finger transcription factor (BPTF) is the largest subunit of the nucleosome remodeling factor and plays an important role in chromatin remodeling for gene activation through its association with histone acetylation or methylation. BPTF is also involved in oncogene transcription in diverse progressions of cancers. Despite clinical trials for inhibitors of bromodomain and extra-terminal family proteins in human cancers, no potent and selective inhibitor targeting the BPTF bromodomain has been discovered. In this study, we identified a potential inhibitor, namely, C620-0696, by computational docking modeling to target bromodomain. Results of biolayer interferometry revealed that compound C620-0696 exhibited high binding affinity to the BPTF bromodomain. Moreover, C620-0696 was cytotoxic in BPTF with a high expression of non-small-cell lung cancer (NSCLC) cells. It suppressed the expression of the BPTF target gene c-MYC, which is known as an oncogenic transcriptional regulator in various cancers. C620-0696 also partially inhibited the migration and colony formation of NSCLC cells owing to apoptosis induction and cell cycle blockage. Thus, our study presents an effective strategy to target a bromodomain factor-mediated tumorigenesis in cancers with small molecules, supporting further exploration of the use of these inhibitors in oncology.

How Does Chirality Determine the Selective Inhibition of Histone Deacetylase 6? A Lesson from Trichostatin A Enantiomers Based on Molecular Dynamics

Histone deacetylase 6 (HDAC6) plays a key role in a variety of neurological disorders, which makes it attractive drug target for the treatment of Alzheimer's disease, Parkinson's disease, and memory/learning impairment. The selectivity of HDAC6 inhibitors (sHDAC6Is) are widely considered to be susceptible to the sizes of their Cap group and the physicochemical properties of their linker or zinc-binding group, which makes the discovery of new sHDAC6Is extremely difficult. With the discovery of the distinct selectivity between Trichostatin A (TSA) enantiomers, the chirality residing in the connective units between TSA's Cap and linker shows a great impact on its selectivity. However, the mechanism underlining ( S)-TSA's selectivity is still elusive, and the way chirality switches the selective ( S)-TSA to nonselective ( R)-TSA is unknown. In this study, multiple computational approaches were collectively applied to explore, validate, and differentiate the binding modes of two TSA enantiomers in HDACs (especially the HDAC6) at atomic level. First, two nonconservative residues (G200/M205 and Y197/F202 in HDAC1/6) in loop3 and four conservative residues deep inside the hydrophobic binding pocket were discovered as the decisive residues of ( S)-TSA's selectivity toward HDAC6. Then, a novel mechanism underlying the selectivity of ( S)-TSA toward HDAC6 was proposed, which was composed of the trigger by two nonconservative residues F202 and M205 in HDAC6 and a subsequently improved fit of ( S)-TSA deep inside HDAC6's hydrophobic binding pocket. TSA enantiomers were used as a molecular probe to explore the mechanism underlying sHDAC6Is' selectivity in this study. Because of their decisive roles in ( S)-TSA's selectivity to HDAC6, both F202 and M205 in HDAC6 should be especially considered in the discovery of novel sHDAC6Is.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Discovery of 2-substituted-N-(3-(3,4-dihydroisoquinolin-2(1H)-yl)-2-hydroxypropyl)-1,2,3,4-tetrahydroisoquinoline-6-carboxamide as potent and selective protein arginine methyltransferases 5 inhibitors: Design, synthesis and biological evaluation

Protein arginine methyltransferases 5 (PRMT5) represents an attractive drug target in epigenetic field for the treatment of leukemia and lymphoma. Here, a series of N-(3-(3,4-dihydroisoquinolin-2(1H)-yl)-2-hydroxypropyl)amide derivatives targeting PRMT5 were designed with structure-based approach and synthesized. Among them, compound 46 showed potent and selective PRMT5 inhibition activity with an IC₅₀ of 8.5 nM, which was approximately equivalent with the phase I clinical trial PRMT5 inhibitor GSK-3326595 (IC₅₀ = 5.5 nM). Compound 46 also displayed pronounced anti-proliferative activity in MV4-11 cells (GI₅₀ = 18 nM) and antitumor activity in MV4-11 mouse xenografts model. This molecule can serve as an excellent tool compound for probing the biological function of PRMT5.

Computational study on the selective inhibition mechanism of MS402 to the first and second bromodomains of BRD4

As a member of the bromodomain and extraterminal domain (BET) family, BRD4 is considered as a potential target for cancer treatment. However, because of the highly conservation of its two homologous bromodomains (BD1/BD2), selective inhibition of each bromodomain remains a challenge. MS402 is a domain-selective inhibitor of BRD4-BD1 over BRD4-BD2 reported recently. Understanding the selectivity mechanism would be very useful for the further design of more potent BD1-selectivity inhibitors. Molecular dynamics simulation, adaptive biasing force and multiple-walker adaptive biasing force were performed to study the inhibition and domain-selective mechanism of MS402 toward BRD4-BD1 over BRD4-BD2 here. Results demonstrate BRD4-BD1 binds to MS402 with lower binding free energy than BRD4-BD2. Residues Gln85, Pro86, Asn140, and Ile146 are crucial for MS402's selectively binding to BRD4-BD1. MS402 needs to overcome more energy barrier to dissociate from BD1 than from BD2 pocket. These findings will be helpful for rational structural modification of existing inhibitors to increase their BD1-selectivity.