Prediction of cytochrome P450-mediated bioactivation using machine learning models and in vitro validation.

Cytochrome P450 (P450)-mediated bioactivation, which can lead to the hepatotoxicity through the formation of reactive metabolites (RMs), has been regarded as the major problem of drug failures. Herein, we purposed to establish machine learning models to predict the bioactivation of P450. On the basis of the literature-derived bioactivation dataset, models for Benzene ring, Nitrogen heterocycle and Sulfur heterocycle were developed with machine learning methods, i.e., Random Forest, Random Subspace, SVM and Naïve Bayes. The models were assessed by metrics like "Precision", "Recall", "F-Measure", "AUC" (Area Under the Curve), etc. Random Forest algorithms illustrated the best predictability, with nice AUC values of 0.949, 0.973 and 0.958 for the test sets of Benzene ring, Nitrogen heterocycle and Sulfur heterocycle models, respectively. 2D descriptors like topological indices, 2D autocorrelations and Burden eigenvalues, etc. contributed most to the models. Furthermore, the models were applied to predict the occurrence of bioactivation of an external verification set. Drugs like selpercatinib, glafenine, encorafenib, etc. were predicted to undergo bioactivation into toxic RMs. In vitro, IC50 shift experiment was performed to assess the potential of bioactivation to validate the prediction. Encorafenib and tirbanibulin were observed of bioactivation potential with shifts of 3-6 folds or so. Overall, this study provided a reliable and robust strategy to predict the P450-mediated bioactivation, which will be helpful to the assessment of adverse drug reactions (ADRs) in clinic and the design of new candidates with lower toxicities.

Super-Resolution Imaging of Autophagy by a Preferred Pair of Self-Labeling Protein Tags and Fluorescent Ligands.

Autophagy is a core recycling process for homeostasis, with its dysfunction associated with tumorigenesis and various diseases. Yet, its subtle intracellular details are covered due to the limited resolution of conventional microscopies. The major challenge for modern super-resolution microscopy deployment is the lack of a practical labeling system, which could provide robust fluorescence with fidelity in the context of the dynamic autophagy microenvironment. Herein, a representative autophagy marker LC3 protein is selected to develop two hybrid self-labeling systems with tetramethylrhodamine (TMR) fluorophores through SNAP/Halo-tag technologies. A systematic investigation indicated that the match of the LC3-Halo and TMR ligand remarkably outperforms that of LC3-SNAP, as the former Halo system exhibited more robust single-molecule brightness (440 vs 247), total photon numbers (45600 vs 13500), and dwell time of the initial bright state (0.82 vs 0.40 s) than the latter. With the aid of this desirable Halo system, for the first time, live-cell ferritinophagy is monitored with a spatial resolution of ∼50 nm, which disclosed reduced sizes of autophagosomes (∼650 nm, ferritinophagy) than those in nonselective (∼840 nm, mammalian target of rapamycin (mTOR)) and selective autophagy (∼900 nm, mitophagy).

Association between ABCB1 C3435T polymorphism and antiepileptic drug resistance in epilepsy: An updated meta-analysis based on 62 studies.

OBJECTIVE: Previous clinical studies and meta-analyses have shown controversial results on the association between C3435T polymorphism of the ABCB1 gene and anti-epileptic drug (AED) resistance. Based on the fact that sample size and confounding factors could contribute to the inconsistency, we performed an updated meta-analysis by including the most recent studies, and subgroup analysis was conducted to evaluate the effect of confounding factors on the association. MATERIALS AND METHODS: We searched articles in 6 electronic databases including PubMed, Medline, Embase, Web of science, Cochrane Library, CNKI (China National Knowledge Infrastructure) for relevant articles up to June 2020. RESULTS: The current analysis showed that the C allele of C3435T variant was a risk factor for drug resistance in the overall populations (C allele vs. T allele, OR: 1.13; 95% CI: 1.02 - 1.25; p = 0.02) and in the Caucasians (C allele vs. T allele, OR: 1.09; 95% CI: 1.09 - 1.43; p = 0.002), while no association was observed in Asians and Indians. Particularly, our study reported for the first time that the 3435T allele was more common in epilepsy patients with drug resistance in the Tunisian population (C allele vs. T allele, OR: 0.31; 95% CI: 0.15 - 0.65; p = 0.002). In addition, our present analysis suggested an association between C3435T and AED resistance in cryptogenic, symptomatic, but not in idiopathic patients. Subgroup studies based on age and gender showed no association. CONCLUSION: AED resistance in Caucasian and Tunisian populations may benefit from ABCB1 C3435T genotyping. We recommend that more details, such as gender and etiology of epilepsy, should be taken into account to draw a reliable conclusion in future studies.

Conformational turn triggers regio-selectivity in the bioactivation of thiophene-contained compounds mediated by cytochrome P450.

In the present work, we performed Density Functional Theory calculations to explore the bioactivation mechanism of thiophene-containing molecules mediated by P450s. For this purpose, relatively large size compounds, 2,5-diaminothiophene derivatives were selected particularly for this investigation. Here we found the successive regio-selectivity triggered by conformational turn played a significant role in the occurrence of bioactivation. 2,5-Diaminothiophene was oxidized to a 2,5-diimine thiophene-reactive intermediate by Compound I (Cpd I) through successive activations of two N-H bonds (H3-N11 and H1-N6). This reaction exhibited three special characteristics: (1) self-controlled regio-selectivity during the oxidation process. There was a large scale of conformational turn in the abstraction of the first H atom which triggers the selection of the second H for abstraction. (2) Proton-shuttle mechanism. In high spin (HS) state, proton-shuttle mechanism was observed for the abstraction of the second H atom. (3) Spin-selective manner. In protein environment, the energy barrier in HS state was much lower than that in low spin state. The novel proposed bioactivation mechanism of 2,5-diaminothiophene compounds can help us in rational design of thiophene-contained drugs avoiding the occurrence of bioactivation.

Cytotoxic Trichothecene Macrolides Produced by the Endophytic Myrothecium roridum.

Six new macrolides named myrothecines D-G (1-4), 16-hydroxymytoxin B (5), and 14'-dehydrovertisporin (6), including four 10,13-cyclotrichothecane derivatives, in addition to 12 known compounds (7-18), were isolated from three endophytic Myrothecium roridum, IFB-E008, IFB-E009, and IFB-E012. The isolated compounds were characterized by MS, NMR, CD, and single-crystal X-ray crystallography. The isolated macrolides exhibited an antiproliferation effect against chronic myeloid leukemia K562 and colorectal carcinoma SW1116 cell lines. Compounds 1-6 were cytotoxic, with IC50 values ranging between 56 nM and 16 µM. Since slight structural changes led to obvious activity differences, the CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methods were then used to explore the 3D QSAR (three-dimensional quantitative structure-activity relationship) of these macrolides. The result showed that the steric, electrostatic, hydrophobic, and H-bond acceptor factors were involved in their cytotoxicity and provided an in-depth understanding of the structure-activity relationships of these metabolites.

Correction to: CBFA2T2 is associated with a cancer stem cell state in renal cell carcinoma.

[This corrects the article DOI: 10.1186/s12935-017-0473-z.].

The association between CYP2C9/2C19 polymorphisms and phenytoin maintenance doses in Asian epileptic patients: A systematic review and meta-analysis
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OBJECTIVE: Therapeutic response to phenytoin (PHT), a first-line antiepileptic drug (AED), is highly variable, in part likely due to genetic factors. Genetic polymorphisms in cytochrome P450 (CYP) 2C9 and CYP2C19 are expected to affect the metabolism of PHT and consequently affect its maintenance doses. We aimed to clarify the effects of genetic polymorphisms in both enzymes on daily PHT maintenance dosage in Asian epileptic patients by meta-analysis. MATERIALS AND METHODS: A systematic literature search was conducted in PubMed and EMBASE for relevant studies published prior to April 14, 2017. RevMan 5.2.3 software was used to analyze the relationship between CYP2C9/2C19 polymorphisms and PHT maintenance doses. RESULTS: A total of 6 studies with 993 patients fulfilling the inclusion criteria were included in our meta-analysis. The homozygous and heterozygous CYP2C19 mutation group (i.e., CYP2C19*2/*2, CYP2C19*3/*3, or CYP2C19*2/*3 group) required significant decrease of PHT maintenance dose. The starting maintenance dose suggested in this group is 4.38 mg/kg/day. Patients with heterozygous CYP2C9 or both heterozygous CYP2C9 and CYP2C19 showed a trend but not a statistically-significant decrease of PHT dose, but dosage adjustment was recommended. CONCLUSION: The meta-analysis indicates that CYP2C9 and CYP2C19 polymorphisms are associated with lower PHT maintenance dosage in Asian epileptic patients. Ethnic differences can influence PHT maintenance dose.
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CBFA2T2 is associated with a cancer stem cell state in renal cell carcinoma.

BACKGROUND: Renal cell carcinoma (RCC) is the most common kidney cancer, accounting for approximately 80-90% of all primary kidney cancer. Treatment for patients with advanced RCC remains unsatisfactory. Rare cancer stem cells (CSCs) are proposed to be responsible for failure of current treatment. METHODS: OncoLnc was used as a tool for interactively exploring survival correlations. Gene manipulation and expression analysis were carried out using siRNA, RT-PCR and Western blotting. Wound healing and invasion assays were used for phenotypical characterization. Aldefluor assay and FACS sorting Sphere culture were used to determine the "stemness" of CSCs. Co-Immunoprecipitation (Co-IP) was used to examine the interaction between OCT4 and CBFA2T2. Student's t-test and Chi square test was used to analyze statistical significance. RESULTS: CBFA2T2 expression can significantly predict the survival of RCC patients. Knocking-down of CBFA2T2 can inhibit cell migration and invasion in RCC cells in vitro, and reduce ALDHhigh CSCs populations. CBFA2T2 expression is necessary for sphere-forming ability and cancer stem cells marker expression in RCC cell lines. CONCLUSIONS: Our data suggest that CBFA2T2 expression correlates with aggressive characteristics of RCC and CBFA2T2 is required for maintenance of "stemness" through regulation of stem cells factors, thereby highlighting CBFA2T2 as a potential therapeutic target for RCC treatment.

Regulation profile of phosphatidylcholines (PCs) and lysophosphatidylcholines (LPCs) components towards UDP-glucuronosyltransferases (UGTs) isoforms.

1.Endogenous compounds have been reported to be the regulators of UDP-glucuronosyltransferases (UGTs) isoforms. This study aims to investigate the regulatory effects of the activity of UGT isoforms by two important lipid components phosphatidylcholine (PC) and lysophosphatidylcholines (LPC) using in vitro incubation system. 2.UGTs supersomes-catalyzed 4-methylumbelliferone (4-MU) glucuronidation was used as the probe reaction to evaluate the inhibition of compounds towards UGT isoforms except UGT1A4, and UGT1A4-catalyzed trifluoperazine (TFP) glucuronidation reaction was utilized to phenotype the activity of UGT1A4. 3.About 50 µM of LPC15:0, LPC16:0, LPC17:0, LPC18:0, LPC18:1 and PC16:0, 2:0 exhibited inhibition towards more than 90% activity of UGT isoforms, and other LPC and PC components showed negligible inhibitory potential towards all the UGT isoforms. UGT1A6 and UGT1A8 were identified to be the most sensitive UGT isoforms susceptible for the inhibition by LPC15:0, LPC16:0, LPC17:0, LPC18:0, LPC18:1 and PC16:0, 2:0, indicating the strong influence of these LPC and PC components towards UGT1A6 and UGT1A8-catalyzed metabolic reaction when the concentrations of these components increased.

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q(2) (cross-validated correlation coefficient) = 0.557, R(2)ncv (non-cross-validated correlation coefficient) = 0.740, R(2)pre (predicted correlation coefficient) = 0.749 and Q(2) = 0.598, R(2)ncv = 0.767, R(2)pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4.

Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s) on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s) and the site(s) of modification. The newly established model was applied to predict the metabolic site(s) of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s) of CYP3A4 on steroids with high predictive accuracy.

Herb-drug interaction prediction based on the high specific inhibition of andrographolide derivatives towards UDP-glucuronosyltransferase (UGT) 2B7.

Herb-drug interaction strongly limits the clinical application of herbs and drugs, and the inhibition of herbal components towards important drug-metabolizing enzymes (DMEs) has been regarded as one of the most important reasons. The present study aims to investigate the inhibition potential of andrographolide derivatives towards one of the most important phase II DMEs UDP-glucuronosyltransferases (UGTs). Recombinant UGT isoforms (except UGT1A4)-catalyzed 4-methylumbelliferone (4-MU) glucuronidation reaction and UGT1A4-catalyzed trifluoperazine (TFP) glucuronidation were employed to firstly screen the andrographolide derivatives' inhibition potential. High specific inhibition of andrographolide derivatives towards UGT2B7 was observed. The inhibition type and parameters (Ki) were determined for the compounds exhibiting strong inhibition capability towards UGT2B7, and human liver microsome (HLMs)-catalyzed zidovudine (AZT) glucuronidation probe reaction was used to furtherly confirm the inhibition behavior. In combination of inhibition parameters (Ki) and in vivo concentration of andrographolide and dehydroandrographolide, the potential in vivo inhibition magnitude was predicted. Additionally, both the in vitro inhibition data and computational modeling results provide important information for the modification of andrographolide derivatives as selective inhibitors of UGT2B7. Taken together, data obtained from the present study indicated the potential herb-drug interaction between Andrographis paniculata and the drugs mainly undergoing UGT2B7-catalyzed metabolic elimination, and the andrographolide derivatives as potential candidates for the selective inhibitors of UGT2B7.

A model of in vitro UDP-glucuronosyltransferase inhibition by bile acids predicts possible metabolic disorders.

Increased levels of bile acids (BAs) due to the various hepatic diseases could interfere with the metabolism of xenobiotics, such as drugs, and endobiotics including steroid hormones. UDP-glucuronosyltransferases (UGTs) are involved in the conjugation and elimination of many xenobiotics and endogenous compounds. The present study sought to investigate the potential for inhibition of UGT enzymes by BAs. The results showed that taurolithocholic acid (TLCA) exhibited the strongest inhibition toward UGTs, followed by lithocholic acid. Structure-UGT inhibition relationships of BAs were examined and in vitro-in vivo extrapolation performed by using in vitro inhibition kinetic parameters (Ki) in combination with calculated in vivo levels of TLCA. Substitution of a hydrogen with a hydroxyl group in the R1, R3, R4, R5 sites of BAs significantly weakens their inhibition ability toward most UGTs. The in vivo inhibition by TLCA toward UGT forms was determined with following orders of potency: UGT1A4 > UGT2B7 > UGT1A3 > UGT1A1 ∼ UGT1A7 ∼ UGT1A10 ∼ UGT2B15. In conclusion, these studies suggest that disrupted homeostasis of BAs, notably taurolithocholic acid, found in various diseases such as cholestasis, could lead to altered metabolism of xenobiotics and endobiotics through inhibition of UGT enzymes.

Diverse effects of α-/ß-estradiol on catalytic activities of human UDP-glucuronosyltransferases (UGT).

ß-estradiol (ß-E2) and α-estradiol (α-E2) act as an endo- and an exon-estrogen in humans, respectively. There is a structural variation in C17-OH configuration of the two estrogens. UDP-glucuronosyltransferases (UGT) are responsible for termination of activities of a variety of endogenous hormones, clinical drugs, and environmental toxicants. The current study was conducted to investigate the effects of the two estrogens towards catalytic activities of UGTs. It was found that ß-E2 could decrease activities of UGT1A9, - 2B4 and - 2B7, with Ki values of a few micro-molars. ß-E2 could additionally accelerate the activity of UGT2B17 via promoting enzyme-substrate binding and increasing the turn over number. Comparatively, α-E2 displayed much stronger inhibitory potentials towards UGT2B7 and - 2B4, but showed little influence to UGT1A9 and - 2B17. The Ki values for inhibition of UGT2B7 in glucuronidation of different substrates by α-E2 were in a nanomolar range that is only about 1/100-1/50 of ß-E2. UGT2B7 structural model was fatherly constructed to explore the mechanism underlying dramatically different inhibition selectivity of the two estrogens. Compared to ß-E2, α-E2 formed more hydrophobic and hydrogen-bonded interactions with the residues in the active pocket. It is concluded that the configuration of E2-17-OH determines the inhibitory potentials towards UGTs. The results are useful in better understanding ligand selectivity of UGTs, as well as in further development of α-E2 in health protection.

A novel model to predict O-glycosylation sites using a highly unbalanced dataset.

In silico approaches have become an alternative method to study O-glycosylation. In this paper, we developed a linear interpretable model for O-glycosylation prediction based on an unbalanced dataset, analyzing the underlying biological knowledge of glycosylation. A training set of 4446 sites involving 468 positive sites and 3978 negative sites was developed during this research. The sites were encoded using the amino acid index (AAindex), and the forward stepwise procedure utilized for feature selection. The linear discriminant analysis with an equal a priori probability (PP-LDA) was employed to develop the interpretable model. Performance of the model was verified using both the internal leave-one-out cross-validation and external validation methods. Two non-linear algorithms, the supervised support vector machine and the unsupervised self-organizing competitive neural network, were used as comparisons. The PP-LDA model exhibited improved classification results with accuracy of 82.1% for cross-validations and 80.3% for external prediction. Further analysis of this linear model indicated that the properties at position R(1) and the properties relative to hydrophobicity contributed more to the glycosylation prediction. However, the alpha and turn propensities at the C-terminal, together with physicochemical properties at the N-terminal, are also relative to the glycosylation activity. This model is not only capable of predicting the possibility of glycosylation using an unbalanced dataset, but is also helpful to understand the underlying biological mechanisms of glycosylation. Considering the publicly accessibility of our prediction model, a downloadable program is provided in our supply materials.

Computational prediction for the metabolism of human UDP-glucuronosyltransferase 1A1 substrates.

UDP-glucuronosyltransferase (UGT) 1A1, one of the most important isoforms in UGTs superfamily, has attracted increasing concerns for its special role in the clearance and detoxification of endogenous and exogenous substances. To avoid the clinical drug-drug interactions, it is of great importance to have the knowledge of the metabolic profile of UGT1A1 substrates early. Herein, we purposed to establish machine learning models to predict the metabolic propeties of UGT1A1 substrates. On the basis of the literature-derived substrates database of UGT1A1, automatic metabolism prediction models for the aromatic hydroxyl (ArOH) and carboxyl (COOH) groups were developed with eight machine learning methods, among which, three methods, i.e. Random Forest, Random Subspace and J48, illustrated the best performance either for the aromatic hydroxyl and the carboxyl model. The models illustrated good robustness when they were evaluated with functions like "Precision", "Recall", "F-Measure", "AUC", "MCC", etc. Nice accuracy was observed for the aromatic hydroxyl and carboxyl model of these methods, whose AUCs ranged from 0.901 to 0.997. Additionally, the ArOH model was applied to predict the UGT1A1-mediated metabolism of an external set. Two new unknown substrates, cytochrome P450 (CYPs)-mediated metabolites of gefitinib, were predicted and identified, which were validated by in vitro assays. In summary, this study provides a reliable and robust strategy to predict UGT1A1 metabolites, which will be helpful either in rational-optimization of drug metabolism or in avoiding drug-drug interactions in clinic.

Discovery and Characterization of the Key Constituents in Ginkgo biloba Leaf Extract With Potent Inhibitory Effects on Human UDP-Glucuronosyltransferase 1A1.

Human UDP-glucuronosyltransferase 1A1 (hUGT1A1) is one of the most essential phase II enzymes in humans. Dysfunction or strong inhibition of hUGT1A1 may result in hyperbilirubinaemia and clinically relevant drug/herb-drug interactions (DDIs/HDIs). Recently, a high-throughput fluorescence-based assay was constructed by us to find the compounds/herbal extracts with strong inhibition against intracellular hUGT1A1. Following screening of over one hundred of herbal products, the extract of Ginkgo biloba leaves (GBL) displayed the most potent hUGT1A1 inhibition in HeLa-UGT1A1 cells (Hela cells overexpressed hUGT1A1). Further investigations demonstrated that four biflavones including bilobetin, isoginkgetin, sciadopitysin and ginkgetin, are key constituents responsible for hUGT1A1 inhibition in living cells. These biflavones potently inhibit hUGT1A1 in both human liver microsomes (HLM) and living cells, with the IC50 values ranging from 0.075 to 0.41 µM in living cells. Inhibition kinetic analyses and docking simulations suggested that four tested biflavones potently inhibit hUGT1A1-catalyzed NHPN-O-glucuronidation in HLM via a mixed inhibition manner, showing the K i values ranging from 0.07 to 0.74 µM. Collectively, our findings uncover the key constituents in GBL responsible for hUGT1A1 inhibition and decipher their inhibitory mechanisms against hUGT1A1, which will be very helpful for guiding the rational use of GBL-related herbal products in clinical settings.

Dynamic communication between androgen and coactivator: mutually induced conformational perturbations in androgen receptor ligand-binding domain.

The transcriptional activity of androgen receptor (AR) is regulated by the sequential binding of various ligands (e.g., dihydrotestosterone, DHT) and coactivators (e.g., SRC/p160) to the AR ligand binding domain (LBD) (Askew et al., J Biol Chem 2007; 282:25801-25816, Lee and Chang, Cell Mol Life Sci 2003;60:1613-1622). However, the synergism between the recruitments of coactivator (SRC 2-3) and ligand (such as DHT) to AR at atomic level remains unclear. Thus, in this work, extensive explicit-solvent molecular dynamics (MD) simulations on four independent trajectories, that is, AR-apo (unbound), DHT·AR, AR·SRC, and DHT·AR·SRC, are performed to investigate the potential communications between the two events in the AR transcriptional process. The MD simulations, analysis of the dynamical cross-correlation maps, comparisons of the binding energy, and thermodynamic analysis reveal a definite structural and functional link between Activation Function-2 (AF-2) surface and the ligand binding site influenced by the binding of ligand and coactivator to the LBD: (I) The DHT binding can increase the LBD volume to 753.0 A³ from its compact ligand-free state (372.1 A³), resulting in a group of helices (1, 2, 8, and loop 20) to move outward and exert added traction on the ligand binding pathway, which subsequently leads to rearrange the AF-2 region to well recruit the SRC; (II) Similarly, the SRC recruitment is also found to facilitate the ligand binding through transmitting a concomitant push-pull effort from the AF-2 surface to the DHT binding site, leading to the opening of entrance to the LBD formed by Val684, Met745, and Arg752, increase of the volume of binding pocket (896.4 A³) and stabilization of the dynamic structure of the LBD. These results, in a dynamic form, initially show a bidirectional structural and functional relay between the bound DHT and SRC that establishes AR functional potency.

Mechanism of microRNA-target interaction: molecular dynamics simulations and thermodynamics analysis.

MicroRNAs (miRNAs) are endogenously produced approximately 21-nt riboregulators that associate with Argonaute (Ago) proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target) and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1) three important (PAZ, Mid and PIWI) domains exist in Argonaute which define the global dynamics of the protein; 2) the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3) it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5'-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg(2+)) plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA). Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago.

Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics.

In recent years, great interest has been paid to the development of compounds with high selectivity for central dopamine (DA) D3 receptors, an interesting therapeutic target in the treatment of different neurological disorders. In the present work, based on a dataset of 110 collected benzazepine (BAZ) DA D3 antagonists with diverse kinds of structures, a variety of in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), homology modeling, molecular docking and molecular dynamics (MD) were carried out to reveal the requisite 3D structural features for activity. Our results show that both the receptor-based (Q(2) = 0.603, R(2) (ncv) = 0.829, R(2) (pre) = 0.690, SEE = 0.316, SEP = 0.406) and ligand-based 3D-QSAR models (Q(2) = 0.506, R(2) (ncv) =0.838, R(2) (pre) = 0.794, SEE = 0.316, SEP = 0.296) are reliable with proper predictive capacity. In addition, a combined analysis between the CoMFA, CoMSIA contour maps and MD results with a homology DA receptor model shows that: (1) ring-A, position-2 and R(3) substituent in ring-D are crucial in the design of antagonists with higher activity; (2) more bulky R(1) substituents (at position-2 of ring-A) of antagonists may well fit in the binding pocket; (3) hydrophobicity represented by MlogP is important for building satisfactory QSAR models; (4) key amino acids of the binding pocket are CYS101, ILE105, LEU106, VAL151, PHE175, PHE184, PRO254 and ALA251. To our best knowledge, this work is the first report on 3D-QSAR modeling of the new fused BAZs as DA D3 antagonists. These results might provide information for a better understanding of the mechanism of antagonism and thus be helpful in designing new potent DA D3 antagonists.