Identification of a universal 6-lncRNA prognostic signature for three pathologic subtypes of renal cell carcinoma

Renal cell carcinoma (RCC) is the most common adult renal epithelial cancer susceptible to metastasis and patients with irresectable RCC always have a poor prognosis. Long noncoding RNAs (lncRNAs) have recently been documented as having critical roles in the etiology of RCC. Nevertheless, the prognostic significance of lncRNA-based signature for outcome prediction in patients with RCC has not been well investigated. Therefore, it is essential to identify a lncRNA-based signature for predicting RCC prognosis. In the current study, we comprehensively analyzed the RNA sequencing data of the three main pathological subtypes of RCC (kidney renal clear cell carcinoma [KIRC], kidney renal papillary cell carcinoma [KIRP], and kidney chromophobe carcinoma [KICH]) from The Cancer Genome Atlas (TCGA) database, and identified a 6-lncRNA prognostic signature with the help of a step-wise multivariate Cox regression model. The 6-lncRNA signature stratified the patients into low- and high-risk groups with significantly different prognosis. Multivariate Cox regression analysis showed that predictive value of the 6-lncRNA signature was independent of other clinical or pathological factors in the entire cohort and in each cohort of RCC subtypes. In addition, the three independent prognostic clinical factors (including age, pathologic stage III, and stage IV) was also stratified into low- and high-risk groups basis on the risk score, and the stratification analyses demonstrated that the high-risk score was a poor prognostic factor. In conclusion, these findings indicate that the 6-lncRNA signature is a novel prognostic biomarker for all three subtypes of RCC, and can increase the accuracy of predicting overall survival.     

In-silico analysis of Sirt2 from Schistosoma mansoni: structures,conformations, and interactions with inhibitors

Sirtuins are NAD+-dependent lysine deacetylases member of the class III HDAC family. These are demonstrated to be therapeutic targets in parasitic diseases like schistosomiasis. Observations suggested that sirtuin enzyme is necessary for the functionality of fe/male reproductive system, due to which SmSirt2 is treated as a potential therapeutic target. There are no structural and molecular features of SmSirt2 have been reported yet. In this study, homology modeling has been used to determine the three-dimensional features of the SmSITRT2. Further, structure validation has been performed by energy minimization and Ramachandran plot. Validated structures are further subjected to molecular docking and virtual screening to find the best lead molecules for downstream analysis. Ten lead molecules were selected while comparing virtual screening of hSirt2 and SmSirt2 both. These leads are further compared with AKG2 which is known inhibitor of hSirt2 (?8.8 kcal/mol). Out of selected 10 leads, four of them (ZINC23995485 (?9.5 kcal/mol), ZINC53298162 (?9.4 kcal/mol), ZINC70927268 (?10.0 kcal/mol), ZINC89878705 (?11.2 kcal/mol)) have shown better interaction with SmSirt2, in which ZINC89878705 (?11.2 kcal/mol) shows a more compact packing as compared to AKG2 and rest of ligands. These molecules could be further subject to in vitro study and model of SmSirt2 has been proposed for further structure-based drug design projects concerning sirtuins from Schistosoma mansoni.     

Structural insight into Mycobacterium tuberculosis maltosyl transferase inhibitors: pharmacophore-based virtual screening,docking, and molecular dynamics simulations

Pharmacophore-based virtual screening, subsequent docking, and molecular dynamics (MD) simulations have been done to identify potential inhibitors of maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE). Ligand and structure-based pharmacophore models representing its primary binding site (pbs) and unique secondary binding site 2 (sbs2), respectively, were constructed based on the three dimensional structure of mtb GlgE. These pharmacophore models were further used for screening of ZINC and antituberculosis compounds database (ATD). Virtually screened molecules satisfying Lipinski’s rule of five were then analyzed using docking studies and have identified 23 molecules with better binding affinity than its natural substrate, maltose. Four top scoring ligands from ZINC and ATD that either binds to pbs or sbs2 have been subjected to 10 ns each MD simulations and binding free energy calculations. Results of these studies have confirmed stable protein ligand binding. Results reported in the article are likely to be helpful in antitubercular therapeutic development research.     

Molecular docking and virtual screening for novel protein tyrosine phosphatase 1B (PTP1B) inhibitors

Protein tyrosine phosphatase 1B (PTP1B) functions as major negative regulator of insulin and leptin signaling pathways. In view of this, PTP1B is an significant target for drug development against cancer, diabetes and obesity. The aim of the current study is to identify PTP1B inhibitors by means of virtual screening with docking. 523,366 molecules from ZINC database have been screened and based on DOCK grid scores and hydrogen bonding interactions five new potential inhibitors were identified. ZINC12502589, ZINC13213457, ZINC25721858, ZINC31392733 and ZINC04096400 were identified as potential lead molecules for inhibition of PTP1B. The identified molecules were subjected to Lipinski''s rule of five parameters and found that they did not violate any rule. More specific analysis of pharmacological parameters may be scrutinized through a complete ADME/Tox evaluation. Pharma algorithm was used to Calculate ADME–Tox profiles for such molecules. In general, all the molecules presented advantages and as well as disadvantages when compared to each other. No marked difference in health effects and toxicity profiles were observed among these molecules.     

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening,molecular dynamics simulation,and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol^?1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.     

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer’s disease

Alzheimer’s disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.     

Structural and energetic understanding of novel natural inhibitors of Mycobacterium tuberculosis malate synthase

Persistent infection by Mycobacterium tuberculosis requires the glyoxylate shunt. This is a bypass to the tricarboxylic acid cycle in which isocitrate lyase (ICL) and malate synthase (MS) catalyze the net incorporation of carbon during mycobacterial growth on acetate or fatty acids as the primary carbon source. To identify a potential antitubercular compound, we performed a structure-based screening of natural compounds from the ZINC database (n = 1 67 740) against the M tuberculosis MS (MtbMS) structure. The ligands were screened against MtbMS, and 354 ligands were found to have better docking score. These compounds were assessed for Lipinski and absorption, distribution, metabolism, excretion, and toxicity prediction where 15 compounds were found to fit well for redocking studies. After refinement by molecular docking and drug-likeness analysis, four potential inhibitors (ZINC1483899, ZINC1754310, ZINC2269664, and ZINC15729522) were identified. These four ligands with phenyl-diketo acid were further subjected to molecular dynamics simulation to compare the dynamics and stability of the protein structure after ligand binding. The binding energy analysis was calculated to determine the intermolecular interactions. Our results suggested that the four compounds had a binding free energy of −201.96, −242.02, −187.03, and −169.02 kJ·mol⁻¹, for compounds with IDs ZINC1483899, ZINC1754310, ZINC2269664, and ZINC15729522, respectively. We concluded that two compounds (ZINC1483899 and ZINC1754310) displayed considerable structural and pharmacological properties and could be probable drug candidates to fight against M tuberculosis parasites.     

Designing and optimization of novel human LMTK3 inhibitors against breast cancer – a computational approach

Estrogen receptor-α (ERα) is expressed more in patients with breast cancer and its level correlated with endocrine resistance. LMTK3 is reported as breast cancer target with regulation of estrogen receptor-α (ERα) through phosphorylation. In this computational study, structure-based inhibitor screening was performed on human LMTK3 using ZINC database. ATP-binding cavity with critical residues involved in the LMTK3 phosphorylation was used as target site for the screening. From the large ligand library, the best compounds were screen with three-phase virtual screening methods in Dockblaster, AutoDock Vina and AutoDock, respectively. The evaluation of ligands was carried out by binding energy and weak interactions, such as hydrogen bond interactions and hydrophobic contacts, in the target site that favors LMTK3 inhibition. Top compounds were found to be more effective in druglikeness activity by ADME prediction. The stability and binding affinity of ligand complexes were optimized by trajectory analysis such as RMSD, Rg, SASA and interhydrogen bonds from molecular dynamics simulations. The behavior of protein motion after ligand binding was illustrated by eigenvectors from principal component analysis (PCA). In addition, binding free energy of the LMTK3–ligand complexes were calculated by MM/PBSA methods and results supported the strong binding in dynamic system. Thus, the computational studies illustrated the structural insights on LMTK3 inhibition mechanism by ligands ZINC04670539, ZINC05607079 and ZINC04344028, also proposed as potent lead candidates. Our findings step towards developing novel LMTK3 inhibitors and identified lead candidates can be future breast cancer drugs with further experimental studies.     

Identification of novel natural inhibitors of Opisthorchis felineus cytochrome P450 using structure-based screening and molecular dynamic simulation

Opisthorchis felineus is the etiological agent of opisthorchiasis in humans. O. felineus cytochrome P450 (OfCYP450) is an important enzyme in the parasite xenobiotic metabolism. To identify the potential anti-opisthorchid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,65,869) against the OfCYP450. The ligands were screened against OfCYP450 in four sequential docking modes that resulted in 361 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 10 compounds were found to fit well with re-docking studies. After refinement by docking and drug-likeness analyses, four potential inhibitors (ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789) were identified. These ligands with reference compounds (itraconazole and fluconazole) were further subjected to molecular dynamics simulation (MDS) and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the OfCYP450 and bound complexes. The binding energy analyses were also calculated. The results suggested that the compounds had a negative binding energy with ?259.41, ?110.09, ?188.25, ?163.30, ?202.10, and ?158.79 kJ mol^?1 for itraconazole, fluconazole, and compounds with IDs ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789, respectively. These lead compounds displayed significant pharmacological and structural properties to be drug candidates. On the basis of MDS results and binding energy analyses, we concluded that ZINC8790946, ZINC70707116, and ZINC85878789 have excellent potential to inhibit OfCYP450.     

Screening and molecular dynamics simulation of compounds inhibiting MurB enzyme of drug-resistant Mycobacterium tuberculosis: An in-silico approach

Mycobacterium tuberculosis (MTB) is becoming more and more resistant to drugs and it is a common problem, making current antimicrobials ineffective and highlighting the need for new TB drugs. One of the promising targets for treating MTB is MurB enzymes. This study aimed to identify potential inhibitors of MurB enzymes in M. tuberculosis, as drug resistance among MTB is a significant problem. Attempts are being made to conduct a virtual screening of 30,417 compounds, and thirty-two compounds were chosen for further analysis based on their binding conformations. The selected compounds were assessed for their drug-likeness, pharmacokinetics, and physiochemical characteristics, and seven compounds with binding energy lower than flavin (FAD) were identified. Further, molecular dynamics simulation analysis of these seven compounds found that four of them, namely DB12983, DB15688, ZINC084726167, and ZINC254071113 formed stable complexes with the MurB binding site, exhibiting promising inhibitory activity. These compounds have not been mentioned in any other study, indicating their novelty. The study suggests that these four compounds could be promising candidates for treating MTB, but their effectiveness needs to be validated through in vitro and in vivo experiments. Overall, the findings of this study provide new insight into potential drug targets and candidates for combating drug-resistant MTB.     

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with ?96.462, ?143.549, and ?122.526 kJ mol^?1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.     

Identification of Putative Plant-Based ALR-2 Inhibitors to Treat Diabetic Peripheral Neuropathy

Diabetic peripheral neuropathy (DPN) is a common diabetes complication (DM). Aldose reductase -2 (ALR-2) is an oxidoreductase enzyme that is most extensively studied therapeutic target for diabetes-related complications that can be inhibited by epalrestat, which has severe adverse effects; hence the discovery of potent natural inhibitors is desired. In response, a pharmacophore model based on the properties of eplarestat was generated. The specified pharmacophore model searched the NuBBE_DB database of natural compounds for prospective lead candidates. To assess the drug-likeness and ADMET profile of the compounds, a series of in silico filtering procedures were applied. The compounds were then put through molecular docking and interaction analysis. In comparison to the reference drug, four compounds showed increased binding affinity and demonstrated critical residue interactions with greater stability and specificity. As a result, we have identified four potent inhibitors: ZINC000002895847, ZINC000002566593, ZINC000012447255, and ZINC000065074786, that could be used as pharmacological niches to develop novel ALR-2 inhibitors.     

Metabolic pathway analysis and molecular docking analysis for identification of putative drug targets in Toxoplasma gondii: novel approach

Toxoplasma gondii is an obligate intracellular apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, toxoplasma develops into chronic infection that cannot be eliminated by host's immune response or by currently used drugs. In most cases, chronic infections are largely asymptomatic unless the host becomes immune compromised. Thus, toxoplasma is a global health problem and the situation has become more precarious due to the advent of HIV infections and poor toleration of drugs used to treat toxoplasma infection, having severe side effects and also resistance have been developed to the current generation of drugs. The emergence of these drug resistant varieties of T. gondii has led to a search for novel drug targets. We have performed a comparative analysis of metabolic pathways of the host Homo sapiens and the pathogen T. gondii. The enzymes in the unique pathways of T. gondii, which do not show similarity to any protein from the host, represent attractive potential drug targets. We have listed out 11 such potential drug targets which are playing some important work in more than one pathway. Out of these, one important target is Glutamate dehydrogenase enzyme; it plays crucial part in oxidation reduction, metabolic process and amino acid metabolic process. As this is also present in the targets of tropical diseases of TDR (Tropical disease related Drug) target database and no PDB and MODBASE 3D structural model is available, homology models for Glutamate dehydrogenase enzyme were generated using MODELLER9v6. The model was further explored for the molecular dynamics simulation study with GROMACS, virtual screening and docking studies with suitable inhibitors against the NCI diversity subset molecules from ZINC database, by using AutoDock-Vina. The best ten docking solutions were selected (ZINC01690699, ZINC17465979, ZINC17465983, ZINC18141294_03, ZINC05462670, ZINC01572309, ZINC18055497_01, ZINC18141294, ZINC05462674 and ZINC13152284_01). Further the Complexes were analyzed through LIGPLOT. On the basis of Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds, specifically ZINC01690699 (as it has minimum energy score and one of the highest number of interactions with the active site residue), could be promising inhibitors for T. gondii using Glutamate dehydrogenase as Drug target.     

Deciphering structural stability and binding mechanisms of potential antagonists with smoothened protein

Identification of new potential inhibitors against Hedgehog pathway activator protein Smoothened (SMO) is considered to be of higher importance to improvise the future cancer therapeutics. Different SMO inhibitors/drugs (e.g. Cyclopamine, Vismodegib, Taladegib) used till date are found to be associated with several drug-related resistivity and toxicity. To explore the ability of new drug/inhibitor molecules, which can show better/similar binding and dynamic stability as compared to known inhibitors, virtual screening against SMO is performed followed by the comparative docking and molecular dynamic studies. ‘ZINC12368305’ is found to be the best molecule among the entire data-set, as it shows the highest binding affinity and stable conformations. Here, an integrative approach using Dynamic Graph Theory is introduced to gain the molecular insights of the structural integrity of these protein complexes at the residue level by analyzing the corresponding Protein Contact Networks along the Molecular Dynamics trajectories. The study further focuses to understand the detailed binding mechanisms of available inhibitor/drug molecules along with the newly predicted molecule. It is observed that a unique big cluster of low fluctuating residues at the vicinity of the drug binding pocket of the SMO in ZINC12368305-bound complex is present and driving it toward a more stable region. A close inspection on this site reveals the presence of a stable Pi–Pi interaction between the pyrazole group-associated phenanthrene ring of ZINC12368305 and aromatic ring of Phe484 of SMO, which could be the potential factor of ZINC12368305 to create a more stable complex with SMO as compared to the other inhibitors.     

Long non-coding RNA GAS5 sensitizes renal cell carcinoma to sorafenib via miR-21/SOX5 pathway

Although the use of sorafenib appears to increase the survival rate of renal cell carcinoma (RCC) patients, there is also a proportion of patients who exhibit a poor primary response to sorafenib treatment. Therefore, it is critical to elucidate the mechanisms underlying sorafenib resistance and find representative biomarkers for sorafenib treatment in RCC patients. Herein, we identified that a long noncoding RNA GAS5 was downregulated in sorafenib nonresponsive RCCs. GAS5 overexpression conferred sorafenib sensitive to nonresponsive RCC cells, whereas knockdown of GAS5 promoted responsive RCC cells resistant to sorafenib treatment in vitro and in vivo. Mechanistically, GAS5 functioned as competing endogenous RNA to repress miR-21, which controlled its down-stream target SOX5. We proposed that GAS5 was responsible for sorafenib resistance in RCC cells and GAS5 exerted its function through the miR-21/ SOX5 axis. Our findings suggested that GAS5 downregulation may be a new marker of poor response to sorafenib and GAS5 could be a potential therapeutic target for sorafenib treatment in RCC.     

Targeting the NTPase site of Zika virus NS3 helicase for inhibitor discovery

Abstract

The major threats linked to Zika virus (ZIKV) are microcephaly, Guillain-Barre syndrome, and the ability to transfer through sexual transmission. Despite these threats, Zika specific FDA approved drugs or vaccines are not available as of yet. Additionally, the involvement of pregnant women makes the drug screening process lengthy and complicated in terms of safety and minimum toxicity of the molecules. Since NS3 helicase of ZIKV performs the critical function of unwinding double-stranded RNA during replication, it is considered as a promising drug target to block ZIKV replication. In the present study, we have exploited the NTPase site of ZIKV NS3 helicase for screening potential inhibitor compounds by molecular docking, and molecular dynamics (MD) simulation approaches. NS3 helicase hydrolyzes the ATP to use its energy for unwinding RNA. We have chosen twenty natural compounds from ZINC library with known antiviral properties and a helicase focused library (HFL) of small molecules from Life Chemicals compounds. After going through docking, the top hit molecules from ZINC and HFL library were further analysed by MD simulations to find out stable binding poses. Finally, we have reported the molecules with potential of binding at NTPase pocket of ZIKV NS3 helicase, which could be further tested on virus through in vitro experiments to check their efficacy.

Communicated by Ramaswamy H. Sarma