The role of LasR active site amino acids in the interaction with the Acyl Homoserine Lactones (AHLs) analogues: A computational study

The present work combines molecular docking calculations, 3D-QSAR, molecular dynamics simulations and free binding energy calculations (MM/PBSA and MM/GBSA) in a set of 28 structural analogues of acyl homoserine lactones with Quorum Sensing antagonist activity. The aim of this work is to understand how ligand binds and is affected by the molecular microenvironment in the active site of the LasR receptor for pseudomonas aeruginosa. We also study the stability of the interaction to find key structural characteristics that explain the antagonist activities of this set of ligands. This information is relevant for the rational modification or design of molecules and their identification as powerful LasR modulators.The analysis of molecular docking simulations shows that the 28 analogues have a similar binding mode compared to the native ligand. The carbonyl groups belonging to the lactone ring and the amide group of the acyl chain are oriented towards the amino acids forming hydrogen bond like interactions. The difference in antagonist activity is due to location and orientation of the LasR side chains within the hydrophobic pocket in its binding site. Additionally, we carried out molecular dynamics simulations to understand the conformational changes in the ligand-receptor interaction and the stability of each complex. Results show a direct relationship among the interaction energies of the ligands and the activities as an antagonist of the LasR receptor.     

A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID study of the species differences in the carcinogenicity of benzene derivatives chemicals

A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID methods was applied as a tool to study and predict the mechanism of action of 100 carcinogenic benzene derivatives. Two 3D-QSAR models were obtained: (i) model of mouse carcinogenicity on the basis of 100 chemicals (model 1) and (ii) model of the differences in mouse and rat carcinogenicity on the basis of 73 compounds (model 2). 3D-QSAR regression maps indicated the important differences in species carcinogenicity, and the molecular positions associated with them. In order to evaluate the role of P450 metabolic process in carcinogenicity, the following approaches were used. The 3D models of CYP2E1 for mouse and rat were built up. A docking study was applied and the important ligand-protein residues interactions and oxidation positions of the molecules were identified. A new approach for quantitative assessment of metabolism pathways was developed, which enabled us to describe the species differences in CYP2E1 metabolism, and how it can be related to differences in the carcinogenic potential for a subset of compounds. The binding energies of the important substituents (local-binding energy-LBE) were calculated, in order to quantitatively demonstrate the contribution of the substituents in metabolic processes. Furthermore, a computational procedure was used for determining energetically favourable binding sites (GRID examination) of the enzymes. The GRID procedure allowed the identification of some important differences, related to species metabolism in CYP2E1. Comparing GRID, 3D-QSAR maps and LBE results, a similarity was identified, indicating a relationship between P450 metabolic processes and the differences in the carcinogenicity.     

Binding research on flavones as ligands of β-amyloid aggregates by fluorescence and their 3D-QSAR, docking studies

The K(d)s (dissociation constants) of 21 flavone derivatives have been obtained by fluorescence in vitro when binding with Aβ(1-40) (β-amyloid(1-40)) aggregates protein. Extensive 3D-QSAR (quantitative structure-activity relationship) studies were performed on the fluorescent flavones, which are excellent ligands of Aβ(1-40) aggregates protein. Comparative molecular similarity indices analysis (CoMSIA) technique was used to relate the binding affinities with the ligand structures, and the QSAR model was obtained using the CoMFA technique. The QSAR model was proved to statistically significant and have high predictive power: the CoMSIA model yielded the cross-validated q2 = 0.512 and the non-cross-validated r2 = 0.911. This model showed that electrostatic (22.5%) and H-bond interaction (acceptor 15.3%; donor 45.1%) properties played major roles in ligand binding process. The QSAR model was further graphically interpreted in terms of field contribution maps. In order to further investigate the specific binding site of the flavones in the Aβ(1-40) aggregates, preliminary docking studies were performed. According to the 3D-QSAR results, the possible binding site in the protein was proposed in order to direct the molecular docking studies. A good correlation (R2: 0.846) between the calculated binding energies and the experimental binding affinities (pK(d)s) suggests that the identified binding site is reliable. The 3D-QSAR model and the information of the ligand-protein interaction will be helpful in the selection of flavones to be structurally modified and labeled by a radio nuclide for imaging Aβ(1-40) aggregates in the AD (Alzheimer's disease) brain.     

Conformational analysis and docking study of potent factor XIIIa inhibitors having a cyclopropenone ring

A conformational analysis and docking study of potent factor XIIIa inhibitors having a cyclopropenone ring were carried out in an attempt to obtain structural insight into the inhibition mechanism. First, stable conformers of the inhibitors alone were obtained from the conformational analysis by systematic search and molecular dynamics. Next, a binding form model of factor XIIIa was built based on an X-ray crystal structure of the enzyme. Finally, the docking study of the inhibitors into the model’s binding site was performed. From the resulting stable complex structures, it was found that the cyclopropenone ring fits the active site located at the base of the binding cavity with high complementarity. The carbonyl oxygen of the cyclopropenone ring formed a hydrogen bond to the indole NH group of Trp279 and the terminal carbon atom of the reactive C=C double bond was in close proximity to the sulfur atom of the catalytic residue, Cys314. This binding mode suggests a possible inhibition mechanism, whereby the cysteine residue reacts with the cyclopropenone ring of the inhibitor, forming an enzyme-ligand adduct. In addition, the higher interaction energies between factor XIIIa and the inhibitors alluded to the probable binding sites of the ligand side chain.     

用分子对接方法研究肝素与孕激素受体相互结合模式(英文)

用分子对接模拟软件研究了肝素与孕激素受体的相互作用。以肝素中的一糖单位作为探针对孕激素受体蛋白进行搜索,获得肝素组成单位与孕激素受体的特异性结合模式。结果发现,2-O-硫酸-α-L 艾杜糖醛酸(2-O-sulfated iduronic acid,IdoA(2S))作为肝素的核心组成单糖之一,与孕激素受体的结合能力最好。分子对接结果显示 IdoA(2S)深入到孕激素受体的 helix2 和 helix 11 所包围的结合口袋,与孕激素受体结合结构域关键残基 Asn 719 形成稳固的氢键;并与孕激素受体结合结构域的关键残基 Met 909 残基侧链近距离接触,揭示了 IdoA(2S)可能具有的孕激素受体拮抗效应的分子作用机制。本模拟实验所建立的模型能够部分解释肝素抑制孕激素依赖性乳腺癌的现象,同时推测了其相应机理。     

In silico investigation into the interactions between murine 5-HT3 receptor and the principle active compounds of ginger (Zingiber officinale)

Gingerols and shogaols are the primary non-volatile actives within ginger (Zingiber officinale). These compounds have demonstrated in vitro to exert 5-HT₃ receptor antagonism which could benefit chemotherapy-induced nausea and vomiting (CINV). The site and mechanism of action by which these compounds interact with the 5-HT₃ receptor is not fully understood although research indicates they may bind to a currently unidentified allosteric binding site. Using in silico techniques, such as molecular docking and GRID analysis, we have characterized the recently available murine 5-HT₃ receptor by identifying sites of strong interaction with particular functional groups at both the orthogonal (serotonin) site and a proposed allosteric binding site situated at the interface between the transmembrane region and the extracellular domain. These were assessed concurrently with the top-scoring poses of the docked ligands and included key active gingerols, shogaols and dehydroshogaols as well as competitive antagonists (e.g. setron class of pharmacologically active drugs), serotonin and its structural analogues, curcumin and capsaicin, non-competitive antagonists and decoys. Unexpectedly, we found that the ginger compounds and their structural analogs generally outscored other ligands at both sites. Our results correlated well with previous site-directed mutagenesis studies in identifying key binding site residues. We have identified new residues important for binding the ginger compounds. Overall, the results suggest that the ginger compounds and their structural analogues possess a high binding affinity to both sites. Notwithstanding the limitations of such theoretical analyses, these results suggest that the ginger compounds could act both competitively or non-competitively as has been shown for palonosetron and other modulators of CYS loop receptors.     

Prediction of the receptor conformation for iGluR2 agonist binding: QM/MM docking to an extensive conformational ensemble generated using normal mode analysis

Highly flexible proteins constitute a significant challenge in molecular docking within the field of drug design. Depending on the efficacy of the bound ligand, the ligand-binding domain (LBD) of the ionotropic glutamate receptor iGluR2 adopts markedly different degrees of domain closure due to large-scale domain movements. With the purpose of predicting the induced domain closure of five known iGluR2 partial to full agonists we performed a validation study in which normal mode analysis (NMA) was employed to generate a 25-membered ensemble of iGluR2 LBD structures with gradually changing domain closures, followed by accurate QM/MM docking to the ensemble. Based on the docking scores we were able to predict the correct optimal degree of closure for each ligand within 1–3° deviation from the experimental structures. We demonstrate that NMA is a useful tool for reliable ensemble generation and that we are able to predict the ligand induced conformational change of the receptor through docking to such an ensemble. The described protocol expands and improves the information that can be obtained from computational docking when dealing with a flexible receptor.     

Prediction of the receptor conformation for iGluR2 agonist binding: QM/MM docking to an extensive conformational ensemble generated using normal mode analysis

Highly flexible proteins constitute a significant challenge in molecular docking within the field of drug design. Depending on the efficacy of the bound ligand, the ligand-binding domain (LBD) of the ionotropic glutamate receptor iGluR2 adopts markedly different degrees of domain closure due to large-scale domain movements. With the purpose of predicting the induced domain closure of five known iGluR2 partial to full agonists we performed a validation study in which normal mode analysis (NMA) was employed to generate a 25-membered ensemble of iGluR2 LBD structures with gradually changing domain closures, followed by accurate QM/MM docking to the ensemble. Based on the docking scores we were able to predict the correct optimal degree of closure for each ligand within 1–3° deviation from the experimental structures. We demonstrate that NMA is a useful tool for reliable ensemble generation and that we are able to predict the ligand induced conformational change of the receptor through docking to such an ensemble. The described protocol expands and improves the information that can be obtained from computational docking when dealing with a flexible receptor.     

苯酰胺类组蛋白去乙酰化酶抑制剂的分子对接及三维定量构效关系研究

利用surflex-dock模块对59个苯酰胺类抑制剂和组蛋白去乙酰化酶进行了对接研究,分析了配体和受体的相互作用模式,所得结论与文献报道的实验结果符合。并利用比较分子力场分析方法(comparative molecular field anal-ysis,CoMFA)对此类抑制剂分子进行了三维定量构效关系研究,所建模型交叉验证相关系数q~2=0.640,非交叉验证相关系数r~2=0.932,有较好的预测能力。CoMFA得到的立体场和静电场的等值线图可用于指导新型药物的设计与合成。     

A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis,molecular docking,density functional and molecular dynamics simulation study

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r² = 0.82 and cross validation correlation co-efficient q² = 0.70. External validation result displays high predictive power with r² (o) value of 0.88 and r² (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (−11.17 kcal/mol) and lower docking energy −37.84 kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50 ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein.     

Computational investigation of interactions between human H2 receptor and its agonists

Type 2 histamine receptor (H(2)R) is widely distributed in the body. Its main function is modulating the secretion of gastric acid. Most gastric acid-related diseases are closely associated with it. In this study, a combination of pharmacophore modeling, homology modeling, molecular docking and molecular dynamics methods were performed on human H(2)R and its agonists to investigate interaction details between them. At first, a pharmacophore model of H(2)R agonists was developed, which was then validated by QSAR and database searching. Afterwards, a model of the H(2)R was built utilizing homology modeling method. Then, a reference agonist was docked into the receptor model by induced fit docking. The 'induced' model can dramatically improve the recovery ratio from 46.8% to 69.5% among top 10% of the ranked database in the simulated virtual screening. The pharmocophore model and the receptor model matched very well each other, which provided valuable information for future studies. Asp98, Asp186 and Tyr190 played key roles in the binding of H(2)R agonists, and direct interactions were observed between the three residues and agonists. Residue Tyr250 could also form a hydrogen bond with H(2)R agonists. These findings would be very useful for the discovery of novel and potent H(2)R agonists.     

Molecular modeling study of CP-690550 derivatives as JAK3 kinase inhibitors through combined 3D-QSAR,molecular docking,and dynamics simulation techniques

To develop more potent JAK3 kinase inhibitors, a series of CP-690550 derivatives were investigated using combined molecular modeling techniques, such as 3D-QSAR, molecular docking and molecular dynamics (MD). The leave-one-out correlation (q²) and non-cross-validated correlation coefficient (r²) of the best CoMFA model are 0.715 and 0.992, respectively. The q² and r² values of the best CoMSIA model are 0.739 and 0.995, respectively. The steric, electrostatic, and hydrophobic fields played important roles in determining the inhibitory activity of CP-690550 derivatives. Some new JAK3 kinase inhibitors were designed. Some of them have better inhibitory activity than the most potent Tofacitinib (CP-690550). Molecular docking was used to identify some key amino acid residues at the active site of JAK3 protein. 10 ns MD simulations were successfully performed to confirm the detailed binding mode and validate the rationality of docking results. The calculation of the binding free energies by MMPBSA method gives a good correlation with the predicted biological activity. To our knowledge, this is the first report on MD simulations and free energy calculations for this series of compounds. The combination results of this study will be valuable for the development of potent and novel JAK3 kinase inhibitors.     

tPSODock:基于化学得分函数和两层粒子群算法的计算机分子对接程序

药物分子对接是计算机辅助药物设计的主要方法之一。利用化学得分函数(Chemscor)作为能量函数,以及将一种新的优化算法一两层粒子群算法作为搜索算法,得到了一种新的计算机分子对接程序：tPSODock。利用tPSODock计算了100个蛋白质一配体的复合物,并且与Consdock和Autodock3．0计算结果进行了对比,结果显示88％的计算结果RMSD小于2．0A,优于Consdock以及Autodock的计算结果。说明tPSODock在是一种高效的分子对接软件,可以用于大规模数据库的筛选工作,适合新药的开发和研制。     

Molecular insight into mutation-induced conformational change in metastasic bowel cancer BRAF kinase domain and its implications for selective inhibitor design

Oncogenic BRAF V600E mutation confers constitutive activation for the kinase and is closely related to the pathogenesis of metastasic bowel cancer (MBC). Here, the V600E-induced conformational change in MBC BRAF kinase domain is characterized systematically at structural, energetic and dynamic levels. The mutation is observed to cause a conformational conversion of the kinase’s activation loop from DFG-out to DFG-in, thus activating the kinase. Electrostatic force is primarily responsible for the conformational conversion and stabilization of DFG-in associated with the mutation. Molecular docking calculations are employed to analyze the binding mode difference of mutant-selective inhibitors between the DFG-out and DFG-in conformations of BRAF kinase. It is revealed that the mutation can reshape inhibitor selectivity profile by altering kinase loop conformation. Several compounds are determined to have a high or moderate selectivity for mutant over wild-type kinase. The selectivity is primarily originated from hydrogen bond interactions of inhibitor ligands with mutant rather than wild type due to the conformational difference in kinase domain.     

Molecular modeling of sigma 1 receptor ligands: a model of binding conformational and electrostatic considerations

We have performed molecular modeling studies on several sigma 1 specific ligands, including PD144418, spipethiane, haloperidol, pentazocine, and others to develop a pharmacophore for sigma 1 receptor-ligand binding, under the assumption that all the compounds interact at the same receptor binding site. The modeling studies have investigated the conformational and electrostatic properties of the ligands. Superposition of active molecules gave the coordinates of the hypothetical 5-point sigma 1 pharmacophore, as follows: R1 (0.85, 7.26, 0.30); R2 (5.47, 2.40, -1.51); R3 (-2.57, 4.82, -7.10); N (-0.71, 3.29, -6.40); carbon centroid (3.16, 4.83, -0.60), where R1, R2 were constructed onto the aromatic ring of each compound to represent hydrophobic interactions with the receptor; and R3 represents a hydrogen bond between the nitrogen atom and the receptor. Additional analyses were used to describe secondary binding sites to electronegative groups such as oxygen or sulfur atom. Those coordinates are (2.34, 5.08, -4.18). The model was verified by fitting other sigma 1 receptor ligands. This model may be used to search conformational databases for other possibly active ligands. In conjunction with rational drug design techniques the model may be useful in design and synthesis of novel sigma 1 ligands of high selectivity and potency. Calculations were performed using Sybyl 6.5.     

Studies of tricyclic piperazine/piperidine furnished molecules as novel integrin αvβ3/αIIbβ3 dual antagonists using 3D-QSAR and molecular docking

The development of injectable integrin α(v)β(3)/α(IIb)β(3) dual antagonists attracts much attention of research for treating of acute ischemic diseases in recent years. In this work, based on a dataset composed of 102 tricyclic piperazine/piperidine furnished dual α(v)β(3) and α(IIb)β(3) antagonists, a variety of in silico modeling approaches including the comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), and molecular docking were applied to reveal the requisite 3D structural features impacting the biological activities. Our statistical results show that the ligand-based 3D-QSAR models for both the α(v)β(3) and α(IIb)β(3) studies exhibited satisfactory internal and external predictability, i.e., for the CoMFA models, results of Q(2)=0.48, R(ncv)(2)=0.87, R(pred)(2)=0.71 for α(v)β(3) and Q(2)=0.50, R(ncv)(2)=0.85, R(pred)(2)=0.72 for α(IIb)β(3) analysis were obtained, and for the CoMSIA ones, the outcomes of Q(2)=0.55, R(ncv)(2)=0.90, R(pred)(2)=0.72 for α(v)β(3) and Q(2)=0.52, R(ncv)(2)=0.88, R(pred)(2)=0.74 for α(IIb)β(3) were achieved respectively. In addition, through a comparison between 3D-QSAR contour maps and docking results, it is revealed that that the most crucial interactions occurring between the tricyclic piperazine/piperidine derivatives and α(v)β(3)/α(IIb)β(3) receptor ligand binding pocket are H-bonding, and the key amino acids impacting the interactions are Arg214, Asn215, Ser123, and Lys253 for α(v)β(3), but Arg214, Asn215, Ser123 and Tyr190 for α(IIb)β(3) receptors, respectively. Halogen-containing groups at position 15 and 16, benzene sulfonamide substituent at position 23, and the replacement of piperazine with 4-aminopiperidine of ring B may increase the α(v)β(3)/α(IIb)β(3) antagonistic activity. The potencies for antagonists to inhibit isolated α(v)β(3) and α(IIb)β(3) are linear correlated, indicating that similar interaction mechanisms may exist for the series of molecules. To our best knowledge this is the first report on 3D-QSAR modeling of these dual α(v)β(3)/α(IIb)β(3) antagonists. The results obtained should provide information for better understanding of the mechanism of antagonism and thus be helpful in design of novel potent dual α(v)β(3)/α(IIb)β(3) antagonists.     

Computational determination of binding structures and free energies of glucose 6-phosphate dehydrogenase with novel steroid inhibitors

Glucose 6-phosphate dehydrogenase (G6PD), the first and the rate-limiting enzyme in the pentose phosphate pathway (PPP), catalyzes the oxidation of G6P to 6-phosphogluconolactone and the reduction of NADP⁺ to NADPH. Its key role in cancer promotes the development of a potent and selective inhibitor that might increase cancer cell death when combined with radiotherapy. In the present study, we investigated the detailed binding modes and binding free energies for G6PD interacting with a promising series of recently developed inhibitors, i.e., the steroid derivatives, by performing molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. The docking indicates that the inhibitors occupy the binding sites of both G6P and NADP⁺. The calculated binding free energies on the basis of the MD-simulated enzyme–inhibitor complexes are in good agreement with the experimental activity data for all of the examined inhibitors. The valuable insights into the detailed enzyme–inhibitor binding including the important intermolecular interactions, e.g., the hydrogen bond interaction and the hydrophobic interaction, have been provided. The computational results provide new insights into future rational design of more potent inhibitors of G6PD as a treatment for cancer.