Nur77 Serves as a Potential Prognostic Biomarker That Correlates with Immune Infiltration and May Act as a Good Target for Prostate adenocarcinoma

Prostate adenocarcinoma (PRAD) is the most frequent malignancy, and is the second leading cause of death due to cancer in men. Thus, new prognostic biomarkers and drug targets for PRAD are urgently needed. As we know, nuclear receptor Nur77 is important in cancer development and changes in the tumor microenvironment; whereas, the function of Nur77 in PRAD remains to be elucidated. The TCGA database was used to explore the Nur77 expression and its role in the prognosis of PRAD. It was shown that Nur77 was down regulated in PRAD, and low Nur77 expression was correlated with advanced clinical pathologic characteristics (high grade, histological type, age) and poor prognosis. Furthermore, key genes screening was examined by univariate Cox analysis and Kaplan-Meier survival. Additionally, Nur77 was closely related to immune infiltration and some anti-tumor immune functions. The differentially expressed genes (DEGs) were presented by protein-protein interaction (PPI) network analysis. Therefore, the expression level of Nur77 might help predict the survival of PRAD cases, which presents a new insight and a new target for the treatment of PRAD. In vitro experiments verified that natural product malayoside targeting Nur77 exhibited significant therapeutic effects on PRAD and largely induced cell apoptosis by up-regulating the expression of Nur77 and its mitochondrial localization. Taken together, Nur77 is a prognostic biomarker for patients with PRAD, which may refresh the profound understanding of PRAD individualized treatment.

Dissociation mechanism of GDP from Cdc42 via DOCK9 revealed by molecular dynamics simulations

Cell division control protein 42 homolog (Cdc42) influences a variety of cellular responses such as cell migration and polarity. Deregulation of Cdc42 has been associated with several human diseases and developmental disorders. Over-activation of Cdc42 through guanine nucleotide exchange factor (GEF) is a critical event for Cdc42 involved cancer metastasis. Members of DOCK family of GEF are important activators of Cdc42. However, this activation mechanism is still unknown. Molecular dynamics (MD) simulations and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) calculations were employed to investigate the central step of the activation of Cdc42: the dissociation mechanism of GDP from Cdc42 via DOCK9. Simulation results show that Mg²⁺ ion has a remarkable influence on the conformational change of switch I of Cdc42 through residue Pro34 which functions as a "clasp" to control the flexibility of switch I. In the GDP dissociation process, the Mg²⁺ ion leave first to result in a suitable conformation of Cdc42 for following DOCK9 binding to. When DOCK9 binds to Cdc42, it changes the orientations of residues Lys16, Thr17, Cys18 and Phe28 of Cdc42 to weaken the interactions between Cdc42 and GDP to release GDP. This study first elucidates the dissociation mechanism of GDP from Cdc42 via DOCK9 and identifies the essential residues of Cdc42 in this process. These simulation results are consistent with the recent findings of biochemical and amino acid mutational studies, and the observations are beneficial to understand the activation mechanism of Cdc42 and to provide insights for designing compounds targeting on Cdc42 related cancer metastasis.

Exploring the structural determinants of novel xanthine derivatives as A2B adenosine receptor antagonists: a computational study

Adenosine is a ubiquitous endogenous nucleoside that controls numerous physiological functions via interacting with its specific G-coupled receptors. Activation of adenosine receptors (AdoRs), particularly A_2B AdoRs promotes the release of inflammatory cytokines; reduces vascular permeabilization and induces angiogenesis, thereby making A_2B AdoR becomes a potentially pharmacological target for drug development. Presently, for investigating the structural determinants of 164 xanthine derivatives as A_2B AdoR antagonists, we performed an in silico study integrating with 3D-QSAR, docking and molecular dynamics (MD) simulation. The obtained optimal model shows strong predictability (Q² = 0.647, R²_ncv = 0.955, and R²_pred = 0.848). Additionally, to explore the binding mode of the ligand with A_2B AdoR and to understand their binding mechanism, docking analysis, MD simulations (20 ns), and the calculation of binding free energy were also carried out. Finally, the structural determinants of these xanthine derivatives were identified and a total of 20 novel A_2B AdoR antagonists with improved potency were computationally designed, and their synthetic feasibility and selectivity were also evaluated. The information derived from the present study offers a better appreciation for exploring the interaction mechanism of the ligand with A_2B AdoR, which could be helpful for designing novel potent A_2B AdoR antagonists. Communicated by Ramaswamy H. Sarma.

Systems Pharmacology Dissection of Multiscale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis

As a chronic inflammatory and angiogenic disease with increased morbidity and mortality, rheumatoid arthritis (RA) is characterized by the proliferation of synovial tissue and the accumulation of excessive mononuclear infiltration, which always results in the joint deformity, disability, and eventually the destruction of the bone and cartilage. Traditional Chinese Medicine (TCM), with rich history of proper effectiveness in treating the inflammatory joint disease containing RA, has long combated such illness from, actually, an integrative and holistic point of view. However, its "multi-components" and "multi-targets" features make it very difficult to decipher the molecular mechanisms of RA from a systematic perspective if employing only routine methods. Presently, an innovative systems-pharmacology approach was introduced, which combined the ADME screening model, drug targeting, and network pharmacology, to explore the action mechanisms of botanic herbs for the treatment of RA. As a result, we uncovered 117 active compounds and 85 key molecular targets from seven RA-related herbs, which are mainly implicated in four signaling pathways, that is, vascular endothelial growth factor, PI3K-Akt, Toll-like receptor, and T-cell-receptor pathways. Additionally, the network relationships among the active components, target proteins, and pathways were further built to uncover the pharmacological characters of these herbs. Besides, molecular dynamics (MD) simulations and molecular mechanics-Poisson-Boltzmann surface area calculations were carried out to explore the binding interactions between the compounds and their receptors as well as to investigate the binding affinity of the ligand to their protein targets. In vitro experiments by ligand binding assays validate the reliability of the drug-target interactions as well as the MD results. The high binding affinities and good inhibitions of the active compounds indicate that the potential therapeutic effects of these herbal medicines for treating RA are exerted probably through the modulation of these relevant proteins, which further validates the rationality and reliability of the drug-target interactions as well as our the network-based analytical methods. This work may be of help for not only understanding the action mechanisms of TCM and for discovering new drugs from plants for the treatment of RA, but also providing a novel potential method for modern medicine in treating complex diseases.

Computational Study Exploring the Interaction Mechanism of Benzimidazole Derivatives as Potent Cattle Bovine Viral Diarrhea Virus Inhibitors

Bovine viral diarrhea virus (BVDV) infections are prevailing in cattle populations on a worldwide scale. The BVDV RNA-dependent RNA polymerase (RdRp), as a promising target for new anti-BVDV drug development, has attracted increasing attention. To explore the interaction mechanism of 65 benzimidazole scaffold-based derivatives as BVDV inhibitors, presently, a computational study was performed based on a combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations. The resultant optimum CoMFA and CoMSIA models present proper reliabilities and strong predictive abilities (with Q(2) = 0. 64, R(2)ncv = 0.93, R(2)pred = 0.80 and Q(2) = 0. 65, R(2)ncv = 0.98, R(2)pred = 0.86, respectively). In addition, there was good concordance between these models, molecular docking, and MD results. Moreover, the MM-PBSA energy analysis reveals that the major driving force for ligand binding is the polar solvation contribution term. Hopefully, these models and the obtained findings could offer better understanding of the interaction mechanism of BVDV inhibitors as well as benefit the new discovery of more potent BVDV inhibitors.

Profiling the interaction mechanism of indole-based derivatives targeting the HIV-1 gp120 receptor

A glycoprotein exposed on a viral surface, human immunodeficiency virus type 1 (HIV-1) gp120 is essential for virus entry into cells as it plays a vital role in seeking out specific cell surface receptors for entry.

Anti-HIV drug development through computational methods

Although highly active antiretroviral therapy (HAART) is effective in controlling the progression of AIDS, the emergence of drug-resistant strains increases the difficulty of successful treatment of patients with HIV infection. Increasing numbers of patients are facing the dilemma that comes with the running out of drug combinations for HAART. Computational methods play a key role in anti-HIV drug development. A substantial number of studies have been performed in anti-HIV drug development using various computational methods, such as virtual screening, QSAR, molecular docking, and homology modeling, etc. In this review, we summarize recent advances in the application of computational methods to anti-HIV drug development for five key targets as follows: reverse transcriptase, protease, integrase, CCR5, and CXCR4. We hope that this review will stimulate researchers from multiple disciplines to consider computational methods in the anti-HIV drug development process.

Molecular docking and molecular dynamics studies on the interactions of hydroxylated polybrominated diphenyl ethers to estrogen receptor alpha

Environmental estrogens have attracted great concerns. Recent studies have indicated that some hydroxylated polybrominated diphenyl ethers (HO-PBDEs) can interact with estrogen receptor (ER), and exhibit estrogenic activity. However, interactions between HO-PBDEs and ER are not well understood. In this work, molecular docking and molecular dynamics (MD) simulations were performed to characterize interactions of two HO-PBDEs (4'-HO-BDE30 and 4'-HO-BDE121) with ERα. Surflex-Dock was employed to reveal the probable binding conformations of the compounds at the active site of ERα; MD simulation was used to determine the detailed binding process. The driving forces of the binding between HO-PBDEs and ERα were van der Waals and electrostatic interactions. The decomposition of the binding free energy indicated that the hydrogen bonds between the residues Glu353, Gly521 and ligands were crucial for anchoring the ligands into the active site of ERα and stabilizing their conformations. The results showed that different interaction modes and different specific interactions with some residues were responsible for the different estrogenic activities of the two HO-PBDEs.

Impact of resistance mutations on inhibitor binding to HIV-1 integrase

HIV-1 integrase (IN) is essential for HIV-1 replication, catalyzing two key reaction steps termed 3' processing and strand transfer. Therefore, IN has become an important target for antiviral drug discovery. However, mutants have emerged, such as E92Q/N155H and G140S/Q148H, which confer resistance to raltegravir (RAL), the first IN strand transfer inhibitor (INSTI) approved by the FDA, and to the recently approved elvitegravir (EVG). To gain insights into the molecular mechanisms of ligand binding and drug resistance, we performed molecular dynamics (MD) simulations of homology models of the HIV-1 IN and four relevant mutants complexed with viral DNA and RAL. The results show that the structure and dynamics of the 140s' loop, comprising residues 140 to 149, are strongly influenced by the IN mutations. In the simulation of the G140S/Q148H double mutant, we observe spontaneous dissociation of RAL from the active site, followed by an intrahelical swing-back of the 3'-OH group of nucleotide A17, consistent with the experimental observation that the G140S/Q148H mutant exhibits the highest resistance to RAL compared to other IN mutants. An important hydrogen bond between residues 145 and 148 is present in the wild-type IN but not in the G140S/Q148H mutant, accounting for the structural and dynamical differences of the 140s' loop and ultimately impairing RAL binding in the double mutant. End-point free energy calculations that broadly capture the experimentally known RAL binding profiles elucidate the contributions of the 140s' loop to RAL binding free energies and suggest possible approaches to overcoming drug resistance.

Exploring the desumoylation process of SENP1: a study combined MD simulations with QM/MM calculations on SENP1-SUMO1-RanGAP1

The small ubiquitin-related modifier (SUMO)-specific protease (SENP) processes SUMOs to mature forms and deconjugates them from various modified substrates. Loss of the equilibrium from desumoylation catalyzed by abnormal SENP1 is associated with cancers and transcription factor activity. In spite of the significant role of SENP1, the molecular basis of its desumoylation remains unclear. Here, MD simulations and QM/MM methods are combined to investigate the catalytic mechanism of desumoylation. The results showed that substrate SUMO1-RanGAP1 fitted into the catalytic pocket of SENP1 by the break of internal hydrophobic interactions and the isomerization of isopeptide from trans to cis. After that, the nucleophilic sulfur anion of Cys603 in SENP1 attacked the carbonyl carbon of Gly97 of SUMO1 to trigger the reaction, and then a tetrahedral intermediate and an acyl-enzyme intermediate were generated in turn, leading to the final release of enzyme SENP1 and two products, free SUMO1 and RanGAP1. In the process, nucleophilic attack was identified as the rate-determining step with a potential energy barrier of 20.2 kcal/mol. These results are in agreement with experimental data from mutagenesis and other experiments. Our findings elucidate the catalytic mechanism of SENP1 with its substrate and may provide a better understanding of SENP desumoylation. In particular, we have identified key residues in SENP1 needed for desumoylation that might be beneficial for the design of novel inhibitors of SENP1-related diseases.

In silico investigations of anti-androgen activity of polychlorinated biphenyls

Polychlorinated biphenyls (PCBs) have attracted great concern as global environmental pollutants and representative endocrine disruptors. In this work, a molecular model study combining three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations was performed to explore the structural requirement for the anti-androgen activities of PCBs and to reveal the binding mode between the PCBs and androgen receptor (AR). The best comparative molecular similarity indices analysis (CoMSIA) model, obtained from receptor-based alignment, shows leave-one-out cross-validated correlation coefficient (q(2)) of 0.665 and conventional correlation coefficient (R(2)) of 0.945. The developed model has a highly predictive ability in both internal and external validation. Furthermore, the interaction mechanisms of PCBs to AR were analyzed by molecular docking and MD simulation. Molecular docking indicated that all the PCBs in the data set docked in a hydrophobic pocket. The Binding free energies calculated by Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) not only exhibited a good correlation with the experimental activity, but also could explain the activity difference of the studied compounds. The binding free energy decomposition analysis indicates that the van der Waals interaction is the major driving force for the binding process.

Computational insights into the binding modes of Sr-Rex with cofactor NADH/NAD+ and operator DNA

The transcriptional repressor Rex plays key roles in modulating respiratory gene expression. It senses the redox poise of the NAD(H) pool. Rex from Streptomyces rimosus (Sr-Rex) is a newly identified protein. Its structure and complex with substrates are not determined yet. In this study, the three-dimensional (3D) structural models of Sr-Rex dimer and its complex with cofactors were constructed by homology modeling. The stability of the constructed Sr-Rex models and the detailed interactions between Sr-Rex and cofactors were further investigated by molecular dynamics simulations. The results demonstrated that the conformation of Sr-Rex changed a lot when binding with the reduced NADH or oxidized NAD(+). Once binding with NADH, the Sr-Rex dimer displayed an opener conformation, which would weaken the interaction of Sr-Rex with Rex operator DNA (ROP). Key residues responsible for the binding were then identified. The computational results were consistent with experimental results, and hence provided insights into the molecular mechanism of Sr-Rex binding with ROP and NADH/NAD(+), which might be helpful for the development of biosensor.

Computational investigation of the HIV-1 Rev multimerization using molecular dynamics simulations and binding free energy calculations

The HIV Rev protein mediates the nuclear export of viral mRNA, and is thereby essential for the production of late viral proteins in the replication cycle. Rev forms a large organized multimeric protein-protein complex for proper functioning. Recently, the three-dimensional structures of a Rev dimer and tetramer have been resolved and provide the basis for a thorough structural analysis of the binding interaction. Here, molecular dynamics (MD) and binding free energy calculations were performed to elucidate the forces thriving dimerization and higher order multimerization of the Rev protein. It is found that despite the structural differences between each crystal structure, both display a similar behavior according to our calculations. Our analysis based on a molecular mechanics-generalized Born surface area (MM/GBSA) and a configurational entropy approach demonstrates that the higher order multimerization site is much weaker than the dimerization site. In addition, a quantitative hot spot analysis combined with a mutational analysis reveals the most contributing amino acid residues for protein interactions in agreement with experimental results. Additional residues were found in each interface, which are important for the protein interaction. The investigation of the thermodynamics of the Rev multimerization interactions performed here could be a further step in the development of novel antiretrovirals using structure based drug design. Moreover, the variability of the angle between each Rev monomer as measured during the MD simulations suggests a role of the Rev protein in allowing flexibility of the arginine rich domain (ARM) to accommodate RNA binding.

Computational insights into the different catalytic activities of CYP2A13 and CYP2A6 on NNK

The human cytochrome P450 2A13 (CYP2A13) and P450 2A6 (CYP2A6) are 94% identical in amino acid sequence, but they metabolize many substrates with different efficiencies. Previous experimental results have shown that CYP2A13 exhibited catalytic activity that was more than 300-fold higher than CYP2A6 toward 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), a carcinogen present in tobacco products. At present, however, the structural determinants accounting for the differential catalytic activities of these two isozymes toward NNK remain unclear. In the present study, molecular docking combined with molecular dynamics simulation and binding free energy calculation was performed to investigate the above issue. The results demonstrate that NNK was able to form a hydrogen bond with Asn297 in either CYP2A13 or CYP2A6. The hydrogen-bond acceptor was the pyridine nitrogen of NNK in the CYP2A13 complex, but it changed to the carbonyl oxygen in the CYP2A6 complex. NNK interacted with the residues in helix I and the K-β2 loop in CYP2A13, whereas it preferred to contact with the phenylalanine cluster in CYP2A6. The residues in helix I and the K-β2 loop of CYP2A13 played a vital role in keeping NNK in a more stable binding state. The binding free energies calculated by MM-GBSA were in agreement with the experimental results.

Molecular modeling of human cytochrome P450 2W1 and its interactions with substrates

The human cytochrome P450 2W1 (CYP2W1) was categorized into the so-called "orphan" CYPs because of its unknown enzymatic function. However, recent studies showed that the recombinant CYP2W1 exhibited broad catalytic activity towards several chemicals. Furthermore, this enzyme was selectively expressed in some forms of cancers, whereas a very low expression was found in human normal issues. These render CYP2W1 as a potential drug target for cancer therapy. At present, however, little information is available on the active site topology and the substrate binding modes of CYP2W1. In this study, the three-dimensional model of CYP2W1 was constructed using the homology modeling method. Two known substrates, benzphetamine and indole, were then docked into the active site, and refined by molecular dynamics simulations. The interaction energy between the substrates and the enzyme was calculated and analyzed by using the MM-GBSA method. The results indicated that the constructed CYP2W1 model can account for the regioselectivity of this enzyme towards the known substrates and van der Waals interactions were the driving force for the substrate binding. Several key residues were identified to be responsible for the binding of indole and benzphetamine with CYP2W1. These findings provide useful information for the detailed characterization of the biological roles of CYP2W1 and structure-based drug design of this enzyme.