Computational study of SENP1 in cancer by novel natural compounds and ZINC database screening.

Introduction: Sentrin-specific protease 1 (SENP1) is a protein whose main function is deSUMOylation. SENP1 inhibits apoptosis, and increases angiogenesis, estrogen and androgen receptor transcription and c-Jun transcription factor, proliferation, growth, cell migration, and invasion of cancer. The in vivo and in vitro studies also demonstrated which natural compounds, especially phytochemicals, minerals, and vitamins, prevent cancer. More than 3,000 plant species have been reported in modern medicine. Natural compounds have many anti-cancerous andanti-turmeric properties such as antioxidative, antiangiogenic, antiproliferative, and pro-apoptotic properties. Methods: In this study, we investigated the interaction of some natural compounds with SENP1 to inhibit its activity. We also screened the ZINC database including natural compounds. Molecular docking was performed, and toxicity of compounds was determined; then, molecular dynamics simulation (MDS) and essential dynamics (ED) were performed on natural compounds with higher free binding energies and minimal side effects. By searching in a large library, virtual screening of the ZINC database was performed using LibDock and CDOCKER, and the final top 20 compounds were allowed for docking against SENP1. According to the docking study, the top three leading molecules were selected and further analyzed by MDS and ED. Results: The results suggest that resveratrol (from the selected compounds) and ZINC33916875 (from the ZINC database) could be more promising SENP1 inhibitory ligands. Discussion: Because these compounds can inhibit SENP1 activity, then they can be novel candidates for cancer treatment. However, wet laboratory experiments are needed to validate their efficacy as SENP1 inhibitors.

Molecular Dynamics Simulation and Essential Dynamics of Deleterious Proline 12 Alanine Single-Nucleotide Polymorphism in PPARγ2 Associated with Type 2 Diabetes, Cardiovascular Disease, and Nonalcoholic Fatty Liver Disease.

Background. Peroxisome proliferator-activated receptor-γ (PPARγ) gene is located at 3p25 position. PPARγ functions as the master regulator of glucose homeostasis and lipoprotein metabolism, and recent studies have reported that it is involved in various metabolic diseases such as diabetes mellitus, hyperlipidemia, coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). PPARγ1 and PPARγ2 are necessary for the development of adipose tissue and insulin sensitivity regulation. But PPARγ2 is the isoform that was controlled in response to nutrient intake and obesity. Methodology. In this study, we used computational techniques to show the impact of Pro12Ala polymorphism on PPARγ2. The 3-D structure of PPARγ2 was modeled using I-TASSER server. The modeled structure was validated with the ZLab server, and the mutation was created with SPDB viewer. Stability prediction tools were used. Molecular dynamics simulation (MDS) was used to understand the structural and functional behavior of the wild type and mutant. Essential dynamics was also applied. Results and Conclusions. Stability prediction tools were showed that this mutation has a destabilizing effect on the PPARγ2 structure. The RMSD, RMSF, Rg, SASA, and DSSP were in line with H-bond results that showed less flexibility in the mutant structure. Essential dynamics was used to verify MDS results. Pro12Ala polymorphism leads to rigidity of the PPARγ2 protein and might disturb the conformational changes and interactions of PPARγ2 and results in type 2 diabetes mellitus (T2DM), CAD, and NAFLD. This study can help scientists to develop a drug therapy against these diseases.

Identification of Natural Products as SENP2 Inhibitors for Targeted Therapy in Heart Failure.

Aims: Sentrin-specific protease -2 (SENP2) is involved in deSUMOylation. Increased deSUMOylation in murine hearts by SENP2 upregulation resulted in cardiac dysfunction and congenital heart defects. Natural compounds via regulating cell proliferation and survival, induce cell cycle cessation, cell death, apoptosis, and producing reactive oxygen species and various enzyme systems cause disease prevention. Then, natural compounds can be suitable inhibitors and since SENP2 is a protein involved in heart disease, so our aim was inhibition of SENP2 by natural products for heart disease treatment. Material and methods: Molecular docking and molecular dynamics simulation of natural products i.e. Gallic acid (GA), Caffeic acid (CA), Thymoquinone (TQ), Betanin, Betanidin, Fisetin, and Ebselen were done to evaluate the SENP2 inhibitory effect of these natural products. The toxicity of compounds was also predicted. Results: The results showed that Betanin constituted a stable complex with SENP2 active site as it revealed low RMSD, high binding energy, and hydrogen bonds. Further, as compared to Ebselen, Betanin demonstrated low toxicity, formed a stable complex with SENP2 via four to seven hydrogen bonds, and constituted more stable MD plots. Therefore, depending upon the outcomes presented herein, Betanin significantly inhibited SENP2 and hence may be considered as a suitable natural compound for the treatment of heart failure. Further clinical trials must be conducted to validate its use as a potential SENP2 inhibitor.

Identification of novel anti-cancer agents, applying in silico method for SENP1 protease inhibition.

The SENP1 (Sentrin-Specific Protease1) is essential for desumoylation. SENP1 plays an essential role in many diseases such as cardiovascular disease, diabetes and cancer via targeting GATA2, NEMO, Pin1, SMAD4 and HIF-1α for deSUMOylation. Considering that, over expression of SENP1 was reported in cancer, thus an optional inhibitor of SENP1 can restitute the balance to the skewed system of SUMO and act as an effective therapeutic agent. The purpose of this study was to select and to sort inhibitors with a stronger binding affinity with SENP1. Molecular docking of SENP1 with natural compounds including Gallic acid, Caffeic acid, Thymoquinone, Thymol, Betaine, Alkannin, Ellagic acid, Betanin, Shikonin, Betanidin and Momordin IC was performed using AutoDock 4, then docking complexes for molecular dynamics (MD) simulation with GROMACS 4.6.5 were applied. Results with RMSD, RMSF, SASA, DSSP, gyrate, H-bond, ADMET and TOPKAT measurements, binding energy and structural features were surveyed. Among those, Gallic acid has shown the most significant results including RMSD and RMSF plots with high stability, high hydrogen bonds, high binding energy and the highest intermolecular bonds with SENP1. Gallic acid demonstrated strong connections and results of toxicity better than Momordin as control. Gallic acid is a phenolic compound which affects several pharmacological and biochemical pathways and has strong antioxidant, anti-inflammatory, antimutagenic and anticancer properties. Further research can improve the appropriate use of plant products drastically. Basic, pre-clinical and clinical research on Gallic acid may provide a roadmap for its ultimate application in the field of cancer prevention.Communicated by Ramaswamy H. Sarma.

Computational drug repurposing of bethanidine for SENP1 inhibition in cardiovascular diseases treatment.

AIMS: Bethanidine (BW467C60) is a newly presented strong adrenergic neuron blocking factor which has a hypotensive operation in man. SENPs are essential for maintaining a balance between SUMOylation and deSUMOylation which can be disturbed by changing the expression of (sentrin-specific proteases) SENPs. SENP1 is the most studied isoform of SENPs. Hypertrophic stimuli can increase SENP1 expression using calcium/calcineurin-NFAT3 signaling in heart. Moreover, SENP1 expression may positively relate to the expression of mitochondrial genes of the heart, and can cause the heart and mitochondrial dysfunction. MATERIALS AND METHODS: In order to inhibit SENP1 using Bethanidine, molecular docking and molecular dynamics (MD) simulation of SENP1 with Bethanidine were performed. Molecular docking showed that Bethanidine can inhibit SENP1. KEY FINDINGS: MD Simulation showed that Bethanidine constitutes a stable complex with SENP1 as was evident from RMSD, RMSF, H-bond and DSSP plots. Free binding energy and the interaction patterns were obtained from molecular docking, and MD trajectory exhibited Bethanidine can be a potential drug candidate for SENP1 inhibition. SIGNIFICANCE: This study supplies enough evidences that Bethanidine is a potential inhibitor of SENP1 and can be applied for the treatment of cardiovascular diseases.

Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases.

Peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PPARGC1A) regulates the expression of energy metabolism's genes and mitochondrial biogenesis. The essential roles of PPARGC1A encouraged the researchers to assess the relation between metabolism-related diseases and its variants. To study Gly482Ser (+1564G/A) single-nucleotide polymorphism (SNP) after PPARGC1A modeling, we substitute Gly482 for Ser482. Stability prediction tools showed that this substitution decreases the stability of PPARGC1A or has a destabilizing effect on this protein. We then utilized molecular dynamics simulation of both the Gly482Ser variant and wild type of the PPARGC1A protein to analyze the structural changes and to reveal the conformational flexibility of the PPARGC1A protein. We observed loss flexibility in the RMSD plot of the Gly482Ser variant, which was further supported by a decrease in the SASA value in the Gly482Ser variant structure of PPARGC1A and an increase of H-bond with the increase of ß-sheet and coil and decrease of turn in the DSSP plot of the Gly482Ser variant. Such alterations may significantly impact the structural conformation of the PPARGC1A protein, and it might also affect its function. It showed that the Gly482Ser variant affects the PPARGC1A structure and makes the backbone less flexible to move. In general, molecular dynamics simulation (MDS) showed more flexibility in the native PPARGC1A structure. Essential dynamics (ED) also revealed that the range of eigenvectors in the conformational space has lower extension of motion in the Gly482Ser variant compared with WT. The Gly482Ser variant also disrupts PPARGC1A interaction. Due to this single-nucleotide polymorphism in PPARGC1A, it became more rigid and might disarray the structural conformation and catalytic function of the protein and might also induce type 2 diabetes mellitus (T2DM), coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). The results obtained from this study will assist wet lab research in expanding potent treatment on T2DM.

Evidence of Omics, Immune Infiltration, and Pharmacogenomic for SENP1 in the Pan-Cancer Cohort.

Sentrin specific-protease 1 (SENP1) is a protein involved in deSUMOylation that is almost overexpressed in cancer. SENP1 has a determinative role in the activation of transcription programs in the innate immune responses and the development B of and C lymphocytes. We found, SENP1 possibly plays a critical role in immune infiltration and acts as an expression marker in PAAD, ESCA, and THYM. CD4+ T cells, CD8+ T cells, and macrophages were more key-related immune cells, indicating that SENP1 might be introduced as a potential target for cancer immunotherapy. We further showed that dysregulation of SENP1 is powerfully associated with decreased patient survival and clinical stage. Total SENP1 protein also increases in cancer. SENP1 is also controlled by transcription factors (TFs) CREB1, KDM5A, REST, and YY1 that regulates apoptosis, cell cycle, cell proliferation, invasion, tumorigenesis, and metastasis. These TFs were in a positive correlation with SENP1. MiR-138-5p, miR-129-1-3p, and miR-129-2-3p also inhibit tumorigenesis through targeting of SENP1. The SENP1 expression level positively correlated with the expression levels of UBN1, SP3, SAP130, NUP98, NUP153 in 32 tumor types. SENP1 and correlated and binding genes: SAP130, NUP98, and NUP153 activated cell cycle. Consistent with this finding, drug analysis was indicated SENP1 is sensitive to cell cycle, apoptosis, and RTK signaling regulators. In the end, SENP1 and its expression-correlated and functional binding genes were enriched in cell cycle, apoptosis, cellular response to DNA damage stimulus. We found that the cell cycle is the main way for tumorigenesis by SENP1. SENP1 attenuates the effect of inhibitory drugs on the cell cycle. We also introduced effective FDA-Approved drugs that can inhibit SENP1. Therefore in the treatments in which these drugs are used, SENP1 inhibition is a suitable approach. This study supplies a wide analysis of the SENP1 across The Cancer Genome Atlas (CGA) cancer types. These results suggest the potential roles of SENP1 as a biomarker for cancer. Since these drugs and the drugs that cause to resistance are applied to cancer treatment, then these two class drugs can use to inhibition of SENP1.

Association study between superoxide Dismutases gene polymorphisms and development of diabetic retinopathy and cataract in Iranian patients with type two diabetes mellitus.

PURPOSE: Reactive oxygen species (ROS) plays pathological roles on development of diabetic retinopathy (DR) and cataract. Superoxide dismutases (SODs) are a set of enzymes to eliminate ROS and cell protection. Based on the diminished activities of SOD1 during DR and cataract, the polymorphisms within SOD1 gene may be associated with these disorders. This study assessed the relationship between SOD1 -251A/G (rs2070424) and SOD1 + 35A/C (rs2234694) gene polymorphisms and DR and cataract in Iranian patients with type 2 diabetes mellitus (T2DM). METHODS: Totally, 141 cases (73 patients with cataract and 68 with DR) with a at least five years history of T2DM and 119 age/gender matched persons without history of DM were included in the case and control groups, respectively. Genomic DNA was extracted from peripheral venous blood cells and genotyping of 251A/G and + 35A/C polymorphisms was done using PCR-RFLP technique. Statistical analysis was done using SPSS version 22. RESULTS: Results showed SOD1 -251A/G and + 35A/C genotype frequency were significantly associated (1.9 folds) with cataract (P = 0.045, OR = 0.524, 95% CI = 0.277-0.991 and P = 0.037, OR = 0.505, 95% CI = 0.265-.0965, respectively). Instead, no significant differences found between SOD -251A/G (P = 0.053, OR = 0.52, 95% CI = 0.276-1.014) and + 35A/C (P = 0.073, OR = 0.547, 95% CI = 0.281-1.063) polymorphisms and DR. Multivariate Logistic Regression model showed significant relationship between BMI, HDL and TC levels and independent predictors of T2DM (P < 0.05). CONCLUSIONS: Based on the results, there was significant association between SOD1 gene polymorphisms and cataract in patients with T2DM. Therefore, SOD1 gene polymorphisms might be a potential marker for increased risk of cataract in patients with T2DM.