Identification of New Lead Molecules Against UBE2NL Enzyme for Cancer Therapy

Extracellular-Vesicle-Associated UBE2NL and HIST2H3PS2 Promote Tumor Aggressiveness and Metastasis in Gynecologic Cancer

Extracellular vesicles (EVs) play pivotal roles in tumor progression and metastasis by mediating intercellular communication within the tumor microenvironment. In this study, we identified two novel EX cargo proteins-UBE2NL and HIST2H3PS2-derived from highly aggressive epithelial ovarian cancer (EOC) cells and mesenchymal-type ovarian stromal progenitor cells (MSC-OCSPCs) but absent in less aggressive SKOV3 cells. Quantitative proteomic profiling via LC-MS/MS and TCGA-integrated analysis revealed that high expression of these genes correlated with advanced tumor stages and poor overall survival in EOC, and high HIST2H3PS2 expression predicted poor survival in endometrial cancer (EC). Functionally, UBE2NL and HIST2H3PS2 overexpression promoted EOC cell invasiveness, which was further enhanced by EX-mediated autocrine and paracrine effects. In contrast, the knockdown of UBE2NL reduced cell invasiveness and prolonged mouse survival in vivo. Moreover, HIST2H3PS2-enriched EXs significantly increased peritoneal dissemination and ascites in murine models. These findings suggest that EX-packaged UBE2NL and HIST2H3PS2 drive tumor aggressiveness and metastasis in gynecologic cancers, highlighting their potential as prognostic biomarkers and therapeutic targets.

Identification of NS2B-NS3 Protease Inhibitors for Therapeutic Application in ZIKV Infection: A Pharmacophore-Based High-Throughput Virtual Screening and MD Simulations Approaches

Zika virus (ZIKV) pandemic and its implication in congenital malformations and severe neurological disorders had created serious threats to global health. ZIKV is a mosquito-borne flavivirus which spread rapidly and infect a large number of people in a shorter time-span. Due to the lack of effective therapeutics, this had become paramount urgency to discover effective drug molecules to encounter the viral infection. Various anti-ZIKV drug discovery efforts during the past several years had been unsuccessful to develop an effective cure. The NS2B-NS3 protein was reported as an attractive therapeutic target for inhibiting viral proliferation, due to its central role in viral replication and maturation of non-structural viral proteins. Therefore, the current in silico drug exploration aimed to identify the novel inhibitors of Zika NS2B-NS3 protease by implementing an e-pharmacophore-based high-throughput virtual screening. A 3D e-pharmacophore model was generated based on the five-featured (ADPRR) pharmacophore hypothesis. Subsequently, the predicted model is further subjected to the high-throughput virtual screening to reveal top hit molecules from the various small molecule databases. Initial hits were examined in terms of binding free energies and ADME properties to identify the candidate hit exhibiting a favourable pharmacokinetic profile. Eventually, molecular dynamic (MD) simulations studies were conducted to evaluate the binding stability of the hit molecule inside the receptor cavity. The findings of the in silico analysis manifested affirmative evidence for three hit molecules with -64.28, -55.15 and -50.16 kcal/mol binding free energies, as potent inhibitors of Zika NS2B-NS3 protease. Hence, these molecules holds the promising potential to serve as a prospective candidates to design effective drugs against ZIKV and related viral infections.

Protein binding sites for drug design

Drug development is a lengthy and challenging process that can be accelerated at early stages by new mathematical approaches and modern computers. To address this important issue, we are developing new mathematical solutions for the detection and characterization of protein binding sites that are important for new drug development. In this review, we present algorithms based on graph theory combined with molecular dynamics simulations that we have developed for studying biological target proteins to provide important data for optimizing the early stages of new drug development. A particular focus is the development of new protein binding site prediction algorithms (ProBiS) and new web tools for modeling pharmaceutically interesting molecules-ProBiS Tools (algorithm, database, web server), which have evolved into a full-fledged graphical tool for studying proteins in the proteome. ProBiS differs from other structural algorithms in that it can align proteins with different folds without prior knowledge of the binding sites. It allows detection of similar binding sites and can predict molecular ligands of various types of pharmaceutical interest that could be advanced to drugs to treat a disease, based on the entire Protein Data Bank (PDB) and AlphaFold database, including proteins not yet in the PDB. All ProBiS Tools are freely available to the academic community at http://insilab.org and https://probis.nih.gov.

ProBiS-Fold Approach for Annotation of Human Structures from the AlphaFold Database with No Corresponding Structure in the PDB to Discover New Druggable Binding Sites

ProBiS (Protein Binding Sites), a local structure-based comparison algorithm, is used in the new ProBiS-Fold web server to annotate human structures from the AlphaFold database without a corresponding structure in the Protein Data Bank (PDB) to discover new druggable binding sites. The ProBiS algorithm is used to compare each query protein structure predicted by the AlphaFold approach with the protein structures from the PDB to identify similarities between known binding sites found in the PDB and yet unknown binding sites in the AlphaFold database. Ligands bound in these identified similar PDB sites are then transferred to each query protein from the AlphaFold database, and binding sites are identified as ligand clusters on an AlphaFold protein. Small molecule binding sites are assigned druggability scores based on the similarity of their ligands to known drugs, allowing them to be ranked according to their perceived and actual potential for drug development. ProBiS-Fold provides interactive and downloadable binding sites for the entire human structural proteome, including more than 3000 new druggable binding sites that have no corresponding structure in the PDB, taking into account AlphaFold's model quality, to enable protein structure-function relationship studies and pharmaceutical drug discovery research. The web server is freely accessible to academic users at http://probis-fold.insilab.org.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Exploring the Lead Compounds for Zika Virus NS2B-NS3 Protein: an e-Pharmacophore-Based Approach

The rapid spread of the Zika virus and its association with the abnormal brain development constitute a global health emergency. With a continuing spread of the mosquito vector, the exposure is expected to accelerate in the coming years. Despite number of efforts, there is still no proper vaccine or medicine to combat this virus. Of note, the NS2B-NS3 protein is proven to be the potential target for the Zika virus therapeutics. Hence, e-pharmacophore-based drug design strategy was employed to identify potent inhibitors of NS2B-NS3 protein from ASINEX database consisting of 467,802 molecules. A 3D e-pharmacophore model was generated using PHASE module of Schrödinger Suite. The generated model consists of one hydrogen bond acceptor (A), two hydrogen bond donors (D), and two aromatic rings (R), ADDRR. The model was further evaluated for its ability to screen actives using enrichment analysis. Subsequently, high-throughput virtual screening protocol was employed, and the resultant hit molecules were also examined for its binding free energies and ADME properties using Prime MM-GBSA and Qikprop module of Schrodinger packages, respectively. Finally, the screened hit molecule was subjected to molecular dynamics simulation to examine its stability. Overall, the results from our analysis suggest that compound BAS 19192837 could be a potent inhibitor for the NS2B-NS3 protein of the Zika virus. It is also noteworthy to mention that our results are in good agreement with literature evidences. We hope that this result is of immense importance in designing potential drug molecules to combat the spread of Zika virus in the near future.

New Insights into the Role of E2s in the Pathogenesis of Diseases: Lessons Learned from UBE2O

Intracellular communication via ubiquitin (Ub) signaling impacts all aspects of cell biology and regulates pathways critical to human development and viability; therefore aberrations or defects in Ub signaling can contribute to the pathogenesis of human diseases. Ubiquitination consists of the addition of Ub to a substrate protein via coordinated action of E1-activating, E2-conjugating and E3-ligating enzymes. Approximately 40 E2s have been identified in humans, and most are thought to be involved in Ub transfer; although little information is available regarding the majority of them, emerging evidence has highlighted their importance to human health and disease. In this review, we focus on recent insights into the pathogenetic roles of E2s (particularly the ubiquitin-conjugating enzyme E2O [UBE2O]) in debilitating diseases and cancer, and discuss the tantalizing prospect that E2s may someday serve as potential therapeutic targets for human diseases.

Ligand-Based Pharmacophore Screening Strategy: a Pragmatic Approach for Targeting HER Proteins

Targeting ErbB family of receptors is an important therapeutic option, because of its essential role in the broad spectrum of human cancers, including non-small cell lung cancer (NSCLC). Therefore, in the present work, considerable effort has been made to develop an inhibitor against HER family proteins, by combining the use of pharmacophore modelling, docking scoring functions, and ADME property analysis. Initially, a five-point pharmacophore model was developed using known HER family inhibitors. The generated model was then used as a query to screen a total of 468,880 compounds of three databases namely ZINC, ASINEX, and DrugBank. Subsequently, docking analysis was carried out to obtain hit molecules that could inhibit the HER receptors. Further, analysis of GLIDE scores and ADME properties resulted in one hit namely BAS01025917 with higher glide scores, increased CNS involvement, and good pharmaceutically relevant properties than reference ligand, afatinib. Furthermore, the inhibitory activity of the lead compounds was validated by performing molecular dynamic simulations. Of note, BAS01025917 was found to possess scaffolds with a broad spectrum of antitumor activity. We believe that this novel hit molecule can be further exploited for the development of a pan-HER inhibitor with low toxicity and greater potential.

Inhibitory Effect and Mechanism of Mesenchymal Stem Cells Cultured in 3D System on Hepatoma Cells HepG2

Mesenchymal stem cells (MSCs) exhibit the feature of homing to tumor site and being immunosuppressive, which have broad prospects in tumor therapy. However, MSCs are commonly cultured in a two-dimensional (2D) condition, which would gradually loss some in vivo important properties. In this study, we built a three-dimensional (3D) system with collagen/Matrigel scaffolds to culture MSCs. The results indicated that MSCs in 3D scaffolds showed higher proliferation ability than that of in 2D cells. In vitro, 3D-cultured MSC-conditioned media (CM) significantly inhibited the proliferation of hepatoma cells HepG2 than that of in 2D-cultured MSC-CM and control groups. In vivo, animal transplantation experiment showed that the treatment of 3D-cultured MSC-CM could further significantly delay the tumor initiation and decrease the tumor volume. The microarray, quantitative PCR, and ELISA assay found that MSCs cultured in the 3D system expressed and secreted more amounts of IL-24. RT-PCR and western blot results showed that IL-24 can activate JAK1-STAT3 pathway via IL22R1 and IL20R2, and further inhibit the proliferation of HepG2 cells. Taken together, these results demonstrated that MSCs cultured in the 3D system had an inhibitory effect on the proliferation of HepG2 cells, probably through secreting more IL-24, which activated JAK1-STAT3 signaling and finally inhibited the cell proliferation to delay tumor initiation. This study also provided a simpler and more reliable approach for MSCs to suppress tumor cells, and provided effective experimental data for clinical treatment of tumor and experimental basis.