EGFR酪氨酸激酶抑制剂的药效团模型构建

以80个作用方式相同, 分子结构特征不同的表皮生长因子受体酪氨酸激酶(EGFR TK)竞争性抑制剂为训练集, 利用计算机药物辅助软件Catalyst, 构建不同的药效团模型, 并结合酪氨酸激酶的作用位点等因素, 筛选出一个含有两个芳环中心, 一个疏水中心和一个阳离子基团的具有较好预测能力(RMS=0.438, Correl=0.908, Weight=1.52, Config=17.36)的药效团模型, 为设计和合成新型结构的EGFR TK抑制剂提供参考.     

取代脱氧脲苷的量子化学计算及分子对接

5取代6氮杂2’脱氧脲苷是一类疱疹单纯一型病毒胸苷激酶(ＨＳＶ1ＴＫ)抑制剂.研究此类化合物的合成、结构、杀菌活性及构效关系一直为科学界所关注[1-3].ＨＳＶ1ＴＫ可以催化胸苷的磷酸化反应,使生成胸苷磷酸脂,在ＤＮＡ合成的控制中起着重要的作用.其晶体结构的发表[4],使得我们能从分子水平上研究此类酶抑制剂与酶活性中心的作用机制,模拟其作用方式,从而实现ＨＳＶ1ＴＫ抑制剂的全新设计.本文从化合物(Ｉ)和(ＩＩ)(见图1)晶体结构出发,使用美国Ｔｒｉｐｏｓ公司开发的三维分子模拟软件包ＳＹＢＹＬ63[5],采用ＭＯＰＡＣ界面中ＰＭ3[6]程…     

Recent Advances in Pain Management: Relevant Protein Kinases and Their Inhibitors

The purpose of this review is to underline the protein kinases that have been established, either in fundamental approach or clinical trials, as potential biological targets in pain management. Protein kinases are presented according to their group in the human kinome: TK (Trk, RET, EGFR, JAK, VEGFR, SFK, BCR–Abl), CMGC (p38 MAPK, MEK, ERK, JNK, ASK1, CDK, CLK2, DYRK1A, GSK3, CK2), AGC (PKA, PKB, PKC, PKMζ, PKG, ROCK), CAMK, CK1 and atypical/other protein kinases (IKK, mTOR). Examples of small molecule inhibitors of these biological targets, demonstrating an analgesic effect, are described. Altogether, this review demonstrates the fundamental role that protein kinase inhibitors could play in the development of new pain treatments.     

猪伪狂犬病毒胸苷激酶的三维结构模建与配体设计

以伪狂犬病毒(PRV)Fa为材料, 克隆测序胸苷激酶(TK)基因, 采用同源模建方法构建胸苷激酶的三维结构模型, 并经Ramachandran图和Profile_3D图验证了模型的可靠性. 采用InsightⅡ/Binding site, Delphi和Affinity方法定位了胸苷激酶的活性位点Site 1, 在此基础上设计出胸苷激酶抑制小分子N-苯基-N'-甲基脲, 通过柔性分子对接法阐明了胸苷激酶抑制剂与靶酶活性位点的相互作用模式, 发现模式中特异性的氢键相互作用可能是对靶酶产生抑制活性的重要分子基础. 研究结果为合理设计PRV胸苷激酶抑制剂, 探索新的治疗及预防伪狂犬病方案奠定了基础.     

Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation

The present study describes a successful application of computational approaches to identify novel Leishmania donovani (Ld) AdoHcyase inhibitors utilizing the differences for Ld AdoHcyase NAD(+) binding between human and Ld parasite. The development and validation of the three-dimensional (3D) structures of Ld AdoHcyase using the L. major AdoHcyase as template has been carried out. At the same time, cloning of the Ld AdoHcyase gene from clinical strains, its overexpression and purification have been performed. Further, the model was used in combined docking and molecular dynamics studies to validate the binding site of NAD in Ld. The hierarchical structure based virtual screening followed by the synthesis of five active hits and enzyme inhibition assay has resulted in the identification of novel Ld AdoHcyase inhibitors. The most potent inhibitor, compound 5, may serve as a "lead" for developing more potent Ld AdoHcy hydrolase inhibitors as potential antileishmanial agents.     

Field-Template,QSAR, Ensemble Molecular Docking,and 3D-RISM Solvation Studies Expose Potential of FDA-Approved Marine Drugs as SARS-CoVID-2 Main Protease Inhibitors

Currently, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has infected people among all countries and is a pandemic as declared by the World Health Organization (WHO). SARS-CoVID-2 main protease is one of the therapeutic drug targets that has been shown to reduce virus replication, and its high-resolution 3D structures in complex with inhibitors have been solved. Previously, we had demonstrated the potential of natural compounds such as serine protease inhibitors eventually leading us to hypothesize that FDA-approved marine drugs have the potential to inhibit the biological activity of SARS-CoV-2 main protease. Initially, field-template and structure–activity atlas models were constructed to understand and explain the molecular features responsible for SARS-CoVID-2 main protease inhibitors, which revealed that Eribulin Mesylate, Plitidepsin, and Trabectedin possess similar characteristics related to SARS-CoVID-2 main protease inhibitors. Later, protein–ligand interactions are studied using ensemble molecular-docking simulations that revealed that marine drugs bind at the active site of the main protease. The three-dimensional reference interaction site model (3D-RISM) studies show that marine drugs displace water molecules at the active site, and interactions observed are favorable. These computational studies eventually paved an interest in further in vitro studies. Finally, these findings are new and indeed provide insights into the role of FDA-approved marine drugs, which are already in clinical use for cancer treatment as a potential alternative to prevent and treat infected people with SARS-CoV-2.     

Comparative protein modeling of 1-deoxy-D-xylulose-5-phosphate reductoisomerase enzyme from Plasmodium falciparum: a potential target for antimalarial drug discovery

Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (Pf-DXR) is a potential target for antimalarial chemotherapy. The three-dimensional model (3D) of this enzyme was determined by means of comparative modeling through multiple alignment followed by intensive optimization, minimization, and validation. The resulting model demonstrates a reasonable topology as gauged from the Ramachandran plot and acceptable three-dimensional structure compatibility as assessed by the Profiles-3D score. The modeled monomeric subunit consists of three domains: (1) N-terminal NADPH binding domain, (2) connective or linker domain (with most of the active site residues located in this domain), and (3) a C-terminal domain. This structure proved to be consistent with known DXR crystal structures from other species. The predicted active site compared favorably with those of the templates and appears to have an active site with a highly conserved architecture. Additionally, the model explains several site-directed mutagenesis data. Besides using several protein structure-checking programs to validate the model, a set of known inhibitors of DXR were also docked into the active site of the modeled Pf-DXR. The docked scores correlated reasonably well with experimental pIC50 values with a regression coefficient (R2) equal to 0.84. Results of the current study should prove useful in the early design and development of inhibitors by either de novo drug design or virtual screening of large small-molecule databases leading to development of new antimalarial agents.     

Monte Carlo and modified Tanford-Kirkwood results for macromolecular electrostatics calculations

The understanding of electrostatic interactions is an essential aspect of the complex correlation between structure and function of biological macromolecules. It is also important in protein engineering and design. Theoretical studies of such interactions are predominantly done within the framework of Debye-Hückel theory. A classical example is the Tanford-Kirkwood (TK) model. Besides other limitations, this model assumes an infinitesimally small macromolecule concentration. By comparison to Monte Carlo (MC) simulations, it is shown that TK predictions for the shifts in ion binding constants upon addition of salt become less reliable even at moderately macromolecular concentrations. A simple modification based on colloidal literature is suggested to the TK scheme. The modified TK models suggested here satisfactorily predict MC and experimental shifts in the calcium binding constant as a function of protein concentration for the calbindin D(9k) mutant and calmodulin.     

Prediction of cytochrome P450 3A4, 2D6, and 2C9 inhibitors and substrates by using support vector machines

Statistical learning methods have been used in developing filters for predicting inhibitors of two P450 isoenzymes, CYP3A4 and CYP2D6. This work explores the use of different statistical learning methods for predicting inhibitors of these enzymes and an additional P450 enzyme, CYP2C9, and the substrates of the three P450 isoenzymes. Two consensus support vector machine (CSVM) methods, "positive majority" (PM-CSVM) and "positive probability" (PP-CSVM), were used in this work. These methods were first tested for the prediction of inhibitors of CYP3A4 and CYP2D6 by using a significantly higher number of inhibitors and noninhibitors than that used in earlier studies. They were then applied to the prediction of inhibitors of CYP2C9 and substrates of the three enzymes. Both methods predict inhibitors of CYP3A4 and CYP2D6 at a similar level of accuracy as those of earlier studies. For classification of inhibitors of CYP2C9, the best CSVM method gives an accuracy of 88.9% for inhibitors and 96.3% for noninhibitors. The accuracies for classification of substrates and nonsubstrates of CYP3A4, CYP2D6, and CYP2C9 are 98.2 and 90.9%, 96.6 and 94.4%, and 85.7 and 98.8%, respectively. Both CSVM methods are potentially useful as filters for predicting inhibitors and substrates of P450 isoenzymes. These methods generally give better accuracies than single SVM classification systems, and the performance of the PP-CSVM method is slightly better than that of the PM-CSVM method.     

Structure-based rational quest for potential novel inhibitors of human HMG-CoA reductase by combining CoMFA 3D QSAR modeling and virtual screening

3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGR) catalyzes the formation of mevalonate. In many classes of organisms, this is the committed step leading to the synthesis of essential compounds, such as cholesterol. However, a high level of cholesterol is an important risk factor for coronary heart disease, for which an effective clinical treatment is to block HMGR using inhibitors like statins. Recently the structures of catalytic portion of human HMGR complexed with six different statins have been determined by a delicate crystallography study (Istvan and Deisenhofer Science 2001, 292, 1160-1164), which established a solid basis of structure and mechanism for the rational design, optimization, and development of even better HMGR inhibitors. In this study, three-dimensional quantitative structure-activity relationship (3D QSAR) with comparative molecular field analysis (CoMFA) was performed on a training set of up to 35 statins and statin-like compounds. Predictive models were established by using two different ways: (1) Models-fit, obtained by SYBYL conventional fit-atom molecular alignment rule, has cross-validated coefficients (q2) up to 0.652 and regression coefficients (r2) up to 0.977. (2) Models-dock, obtained by FlexE by docking compounds into the HMGR active site, has cross-validated coefficients (q2) up to 0.731 and regression coefficients (r2) up to 0.947. These models were further validated by an external testing set of 12 statins and statin-like compounds. Integrated with CoMFA 3D QSAR predictive models, molecular surface property (electrostatic and steric) mapping and structure-based (both ligand and receptor) virtual screening have been employed to explore potential novel hits for the HMGR inhibitors. A representative set of eight new compounds of non-statin-like structures but with high pIC(50) values were sorted out in the present study.     

Designing Novel Compounds for the Treatment and Management of RET-Positive Non-Small Cell Lung Cancer—Fragment Based Drug Design Strategy

Rearranged during transfection (RET) is an oncogenic driver receptor that is overexpressed in several cancer types, including non-small cell lung cancer. To date, only multiple kinase inhibitors are widely used to treat RET-positive cancer patients. These inhibitors exhibit high toxicity, less efficacy, and specificity against RET. The development of drug-resistant mutations in RET protein further deteriorates this situation. Hence, in the present study, we aimed to design novel drug-like compounds using a fragment-based drug designing strategy to overcome these issues. About 18 known inhibitors from diverse chemical classes were fragmented and bred to form novel compounds against RET proteins. The inhibitory activity of the resultant 115 hybrid molecules was evaluated using molecular docking and RF-Score analysis. The binding free energy and chemical reactivity of the compounds were computed using MM-GBSA and density functional theory analysis, respectively. The results from our study revealed that the developed hybrid molecules except for LF21 and LF27 showed higher reactivity and stability than Pralsetinib. Ultimately, the process resulted in three hybrid molecules namely LF1, LF2, and LF88 having potent inhibitory activity against RET proteins. The scrutinized molecules were then subjected to molecular dynamics simulation for 200 ns and MM-PBSA analysis to eliminate a false positive design. The results from our analysis hypothesized that the designed compounds exhibited significant inhibitory activity against multiple RET variants. Thus, these could be considered as potential leads for further experimental studies.     

3D-QSAR studies on indole and 7-azoindole derivatives as ROCK-2 inhibitors: An integrative computational approach

Rho Kinases (ROCK) has been found to regulate a wide range of fundamental cell functions such as contraction, motility, proliferation, and apoptosis. Recent experiments have defined new functions of ROCKs in cells, including centrosome positioning and cell-size regulation, which might contribute to various physiological and pathological states. In this study, we have performed pharmacophore modeling and 3D QSAR studies on a series of 36 indoles and 7-azoindoles derivatives as ROCK2 inhibitors to elucidate the structural variations with their inhibitory activities. Ligand based CoMFA and CoMSIA models were generated based on three different alignment methods such as systematic search, simulated annealing and pharmacophore. A total of 15 CoMFA models and 27 CoMSIA were generated using different alignments. One model from each alignment is selected based on the statistical values. Contour maps of the selected models were compared, analysed and reported. The 3D QSAR study revealed that electro positive group linked to the methoxy-benzene ring position of the structure will enhance the biological activity and bulkier substitutions are preferred in the methyl dihydroindole region. Also, it is found that the hydrogen bond donor substituted at the R₁ position enhances the inhibitory activity. In future, this study would give proper guidelines to further enhance the activity of novel inhibitors for ROCK2.     

3D QSAR selectivity analyses of carbonic anhydrase inhibitors: insights for the design of isozyme selective inhibitors

A 3D QSAR selectivity analysis of carbonic anhydrase (CA) inhibitors using a data set of 87 CA inhibitors is reported. After ligand minimization in the binding pockets of CA I, CA II, and CA IV isoforms, selectivity CoMFA and CoMSIA 3D QSAR models have been derived by taking the affinity differences (DeltapKi) with respect to two CA isozymes as independent variables. Evaluation of the developed 3D QSAR selectivity models allows us to determine amino acids in the respective CA isozymes that possibly play a crucial role for selective inhibition of these isozymes. We further combined the ligand-based 3D QSAR models with the docking program AUTODOCK in order to screen for novel CA inhibitors. Correct binding modes are predicted for various CA inhibitors with respect to known crystal structures. Furthermore, in combination with the developed 3D QSAR models we could successfully estimate the affinity of CA inhibitors even in cases where the applied scoring function failed. This novel strategy to combine AUTODOCK poses with CoMFA/CoMSIA 3D QSAR models can be used as a guideline to assess the relevance of generated binding modes and to accurately predict the binding affinity of newly designed CA inhibitors that could play a crucial role in the treatment of pathologies such as tumors, obesity, or glaucoma.     

A selective irreversible inhibitor targeting a PDZ protein interaction domain

Irreversible inhibitors of proteases have proven themselves useful tools for determining which proteases are active under given conditions in tissues or cells and for studying the functional role that a protease plays in physiological processes. The application of such techniques to the study of the activity and function of protein-protein interactions has been hindered by the lack of guiding principles for the mechanistic design of irreversible inhibitors targeting the "active site" of a protein interaction. We report herein the first example of a mechanism-based irreversible inhibitor of a protein interaction that has been specifically targeted to one member of the PDZ family of protein interaction domains: the second PDZ domain of the membrane-associated guanylate kinase MAGI3. This inhibitor was designed using rationally directed computational evaluation to take advantage of a conserved histidine in the PDZ domain by introducing an ionizable group that will be held in close proximity to that nucleophile during binding. The novel compound exhibits all of the characteristics of an irreversible inhibitor of the interaction of the tumor suppressor PTEN with MAGI3 in in vitro models. In cells, the inhibitor can be shown to release PTEN from sequestration by MAGI3 and consequently upregulate the PKB signaling pathway.     

Beyond the Förster formulation for resonance energy transfer: the role of dark states

Resonance Energy Transfer (RET) is investigated in pairs of charge-transfer (CT) chromophores. CT chromophores are an interesting class of π conjugated chromophores decorated with one or more electron-donor and acceptor groups in polar (D-π-A), quadrupolar (D-π-A-π-D or A-π-D-π-A) or octupolar (D(-π-A)(3) or A(-π-D)(3)) structures. Essential-state models accurately describe low-energy linear and nonlinear spectra of CT-chromophores and proved very useful to describe spectroscopic effects of electrostatic interchromophore interactions in multichromophoric assemblies. Here we apply the same approach to describe RET between CT-chromophores. The results are quantitatively validated by an extensive comparison with time-dependent density functional theory (TDDFT) calculations, confirming that essential-state models offer a simple and reliable approach for the calculation of electrostatic interchromophore interactions. This is an important result since it sets the basis for more refined treatments of RET: essential-state models are in fact easily extended to account for molecular vibrations in truly non-adiabatic approaches and to account for inhomogeneous broadening effects due to polar solvation. Optically forbidden (dark) states of quadrupolar and octupolar chromophores offer an interesting opportunity to verify the reliability of the dipolar approximation. In striking contrast with the dipolar approximation that strictly forbids RET towards or from dark states, our results demonstrate that dark states can take an active role in RET with interaction energies that, depending on the relative orientation of the chromophores, can be even larger than those relevant to allowed states. Essential-state models, whose predictions are quantitatively confirmed by TDDFT results, allow us to relate RET interaction energies towards allowed and dark states to the supramolecular symmetry of the RET-pair, offering reliable design strategies to optimize RET-interactions.     

Synthesis,Kinetics, and Molecular Docking of Novel 9‐(2‐Hydroxypropyl)purine Nucleoside Analogs as Ligands of Herpesviral Thymidine Kinases

In the context of broadening the knowledge on substrate specificity of Herpes simplex virus type 1 thymidine kinase (HSV‐1 TK) and Varicella‐Zoster virus thymidine kinase (VZV TK), new derivatives of 9‐(2‐hydroxypropyl)‐substituted adenine, chloropurine, hypoxanthine, guanine, thiopurine, and (methylsulfanyl)purine were synthesized and subjected to in vitro phosphorylation and binding affinity assays. The interactions between the compounds and the crystallographically determined active site residues of HSV‐1 TK have been studied by molecular modeling with the Lamarckian genetic algorithm of docking program AutoDock 3.0. All compounds mentioned bind to both enzymes in the low mM to sub‐mM range, comparable to binding affinities of existing prodrugs. Findings from the docking procedure indicate multiple binding modes for all of the compounds and are in accordance with the results of phosphorylation and binding‐affinity studies. Furthermore, the studies reveal that hypoxanthine derivatives represent a new class of TK substrates and thiopurine derivatives a new class of TK inhibitors.     

Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure–activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.