PTPlB和1，2-萘醌类抑制剂的分子动力学模拟

采用分子动力学和分子力学相结合的方法，研究了一类1，2-萘醌类抑制剂与酪氨酸蛋白磷酸酯酶PTP1B之间的相互作用模式．计算得到的抑制剂和靶酶之间的相互作用模式显示范德华相互作用、疏水相互作用以及氢键作用是主要的作用模式．计算结果还表明抑制剂和PTP1B的相互作用能△E越低，抑制剂活性越高．通过计算各种能量对△E的贡献，以及对复合物结构参数的分析，发现抑制剂和受体之间疏水相互作用是造成抑制剂活性差别的主要原因．这为设计其他非酸类抑制剂提供了信息．     

PTP1B和1,2-萘醌类抑制剂的分子动力学模拟

采用分子动力学和分子力学相结合的方法 ,研究了一类 1,2 萘醌类抑制剂与酪氨酸蛋白磷酸酯酶PTP1B之间的相互作用模式 .计算得到的抑制剂和靶酶之间的相互作用模式显示范德华相互作用、疏水相互作用以及氢键作用是主要的作用模式 .计算结果还表明抑制剂和PTP1B的相互作用能ΔE越低 ,抑制剂活性越高 .通过计算各种能量对ΔE的贡献 ,以及对复合物结构参数的分析 ,发现抑制剂和受体之间疏水相互作用是造成抑制剂活性差别的主要原因 .这为设计其他非酸类抑制剂提供了信息     

表皮生长因子受体和抑制剂之间分子对接的研究

研究了表皮生长因子受体(EGFR)和4-苯胺喹唑啉类抑制剂之间的相互作用模式，表皮生长因子受体的三维结构通过同源蛋白模建的方法得到，而抑制剂和靶酶结合复合物结构则通过分子力学和分子动力学结合的方法计算得到。从模拟结果得到的抑制剂和靶酶之间的相互作用模式表明范德华相互作用、疏水相互作用以及氢键相互作用对抑制剂的活性都有重要的影响，抑制剂的苯胺部分位于活性口袋的底部，能够与受体残基的非极性侧链产生很强的范德华和疏水相互作用，抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏水性相互作用，而抑制剂喹唑啉环上的氮原子能和周围的残基形成较强的氢键相互作用，对抑制剂的活性有较大的影响，计算得到抑制剂和靶酶之间的非键相互作用能以及抑制剂和靶酶之间的相互作用信息能够很好地解释抑制剂活性和结构的关系，为全新抑制剂的设计提供了重要的结构信息。     

VEGFR-2 与抑制剂Sunitinib 的分子对接及分子动力学研究

用分子对接方法研究了VEGFR-2 和抑制剂Sunitinib 的相互作用模式, 并对其复合物进行了10 ns 的分子动力学(Molecular Dynamics, MD)模拟. 结果表明, 抑制剂Sunitinib 能与VEGFR-2 中位于活性空腔的Glu885, Ile888, His1026,Asp1028, Asp1046 五个氨基酸残基形成疏水作用; 另外, VEGFR-2 中His1026, Cys1024, Asp1046 三个氨基酸残基能与Sunitinib 形成三个作用强度不同的氢键. 这些基团之间的相互作用是Sunitinib 抑制VEGFR-2 活性的关键因素. 研究结果可为VEGFR-2 抑制剂的结构改良、分子设计、合成提供理论参考, 并有助于寻找活性更高、效果更好的抗肿瘤药物.     

Hydroxamate类抑制剂与MMP-3的结合自由能的计算

用自由能微扰方法(FEP)计算了两种hydroxamate类的抑制剂和MMP-3的相对结合自由能。在计算中,对于催化区的锌离子与其共价结合的配体(包括抑制和组氨酸)采用了键合的模型,抑制剂和周围配体的部分电荷的计算采用两步静电势收敛方法。自由能计算采用了慢增长(Slowgrowth)和固定窗口增长(Fixedwidthwindowgrowth)两种方法,并且在每次计算中都采用了双向采样(Double-widesampling)的策略。两种方法计算得到的相对结合自由能都能和实验值很好的符合。同时从动力学模拟的得到的分子轨迹得到了抑制剂和受体之间相互作用模式,抑制剂的P1部分可以和受体的S1'口袋形成很强范德华和疏水相互作用,P1上的苯环可以和Tyr223上的苯环形成较好的π键堆积相互作用。     

乙酰胆碱酯酶AChE与1,7-二氮杂咔唑抑制剂的作用机理的分子动力学模拟

通过分子对接、分子动力学（MD）模拟以及成键自由能分析方法,从原子水平上模拟研究了3种1,7-二氮杂咔唑衍生物（分别记为M1、M2和M3）与AChE的结合模式及相互作用机理,分析和讨论了研究体系的静电相互作用和范德华相互作用（vdW）。用MM-PBSA方法计算的3种抑制剂与AChE之间的结合自由能与抑制剂的实验生物活性数据（IC₅₀值）相对应。分析结果表明,残基S286与抑制剂之间形成的氢键作用有利于抑制剂与AChE之间的结合。范德华相互作用,尤其是抑制剂与关键残基W279和Y334的作用,对抑制剂与AChE之间的结合自由能有较大的贡献,在区分抑制剂M1（或M2）和M3的生物活性上发挥着重要的作用。     

乙酰胆碱酯酶AChE与1,7-二氮杂咔唑抑制剂的作用机理的分子动力学模拟

通过分子对接、分子动力学(MD)模拟以及成键自由能分析方法,从原子水平上模拟研究了3种1,7-二氮杂咔唑衍生物(分别记为M1、M2和M3)与ACh E的结合模式及相互作用机理,分析和讨论了研究体系的静电相互作用和范德华相互作用(vd W)。用MM-PBSA方法计算的3种抑制剂与ACh E之间的结合自由能与抑制剂的实验生物活性数据(IC50值)相对应。分析结果表明,残基S286与抑制剂之间形成的氢键作用有利于抑制剂与ACh E之间的结合。范德华相互作用,尤其是抑制剂与关键残基W279和Y334的作用,对抑制剂与ACh E之间的结合自由能有较大的贡献,在区分抑制剂M1(或M2)和M3的生物活性上发挥着重要的作用。     

多肽抑制剂抑制淀粉质多肽42构象转换的分子动力学模拟和结合自由能计算

应用分子动力学模拟和结合自由能计算方法研究了多肽抑制剂KLVFF、VVIA和LPFFD抑制淀粉质多肽42 (Aβ42)构象转换的分子机理. 结果表明, 三种多肽抑制剂均能够有效抑制Aβ42的二级结构由α-螺旋向β-折叠的构象转换. 另外, 多肽抑制剂降低了Aβ42分子内的疏水相互作用, 减少了多肽分子内远距离的接触, 有效抑制了Aβ42的疏水塌缩, 从而起到稳定其初始构象的作用. 这些抑制剂与Aβ42之间的疏水和静电相互作用(包括氢键)均有利于它们抑制Aβ42的构象转换. 此外, 抑制剂中的带电氨基酸残基可以增强其和Aβ42之间的静电相互作用(包括氢键), 并降低抑制剂之间的聚集, 从而大大增强对Aβ42构象转换的抑制能力. 但脯氨酸的引入会破坏多肽的线性结构, 从而大大降低其与Aβ42 之间的作用力. 上述分子模拟的结果揭示了多肽抑制剂KLVFF、VVIA和LPFFD抑制Aβ42构象转换的分子机理, 对于进一步合理设计Aβ的高效短肽抑制剂具有非常重要的理论指导意义.     

FKBP12蛋白与其抑制剂结合的分子动力学模拟和结合自由能计算

FKBP12 (FK506-binding protein-12)是一种具有神经保护和促神经再生作用的蛋白. 采用分子动力学模拟取样, 运用MM-GBSA方法计算了FKBP12和3个抑制剂(GPI-1046, 308和107)的绝对结合自由能, GPI-1046的结合能最小, 308小于107的结合能. 通过能量分解的方法考察了FKBP12蛋白的主要残基与抑制剂之间的相互作用和识别, 计算结果表明: 3个抑制剂具有相似的结合模式, Ile56和Tyr82主要表现为氢键作用, Tyr26, Phe46, Val55, Ile56, Trp59, Tyr82, Tyr87和Phe99形成疏水作用区. 计算结果和实验结果吻合.     

EGFR和4-苯胺喹唑啉类抑制剂之间相互作用模式的研究

采用分子动力学和MM/PBSA相结合的方法预测了表皮生长因子受体和4-苯胺喹 啉类抑制剂的相互作用模式。在分子动力学采样的基础上,采用MM/PBSA的方法分 别预测了四种可能结合模式下表皮生长因子受体和4-苯胺喹唑啉类抑制剂间的结合 自由能。在MM/PBSA计算中,受体和抑制剂之间的非键相互作用能采用分子力学 (MM)的方法得到;溶剂效应中极性部分对自由能的贡献通过解Possion- Boltzmanne (PB)方程的方法得到;溶液效应中非极性部分对自由能的贡献则通过 分子表面积计算(SA)的方法得到。计算表明,在四种结合模式下,表皮生长因子受 体和4-苯胺喹唑啉类抑制剂之间的结合自由能有较大的差别。在最佳的相互作用模 式中,抑制剂的苯胺部分位于活性口袋的底部,能够与受体残基的非极性侧链产生 很强的范德华和疏水相互作用。抑制剂喹唑啉环上的N(1)原子能够和Met-769上的 NH形成稳定的氢键,而抑制剂上的N(3)原子则和周围的一个水分子形成氢键。同时 ,抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏 水相互作用。最佳结合模式能够很好地解释已有抑制剂结构和活性间的关系。     

MMP-2和Hydroxamate类抑制剂绝对自由能的计算

采用基于线性响应近似的自由能计算方法计算了一类hydroxamate抑制剂和MMP-2的绝对结合自由能。计算中,催化锌离子和MMP-2以及配体之间采用了非键模型。分子动力学模拟结果显示,采用非键模型时,催化Zn离子采用五配位的形式,但配位键的形式和初始结构比较有很大的差别。通过拟合,分别得到了单参数、双参数以及三参数的自由能预测模型,其中,含有常数校正项的三参数模型具有最佳的预测能力,预测自由能和实际自由能之间平均绝对误差仅为2.38kJ/mol。     

Molecular docking studies of a group of hydroxamate inhibitors with gelatinase-A by molecular dynamics

We have performed docking and molecular dynamics simulations of hydroxamates complexed with human gelatinase-A (MMP-2) to gain insight into the structural and energetic preferences of these inhibitors. The study was conducted on a selected set of eleven compounds with variation in structure and activity. Molecular dynamics simulations were performed at 300 K for 100 ps with equilibration for 50 ps. The structural analyses of the trajectories indicate that the coordinate bond interactions, the hydrogen bond interactions, the van der Waals interactions as well as the hydrophobic interactions between ligand and receptor are responsible simultaneously for the preference of inhibition and potency. The ligand hydroxamate group is coordinated to the catalytic zinc ion and form stable hydrogen bonds with the carbonyl oxygen of Gly 162. The P1 group makes extensive van der Waals and hydrophobic contacts with the nonpolar side chains of several residues in the S1 subsite, including Leu 197, Val 198, Leu 218 and Tyr 223. Moreover, four to eight hydrogen bonds between hydroxamates and MMP-2 are formed to stabilize the inhibitors in the active site. Compared with the P2 and P3 groups, the P1 groups of inhibitors are oriented regularly, which is produced by the restrain of the S1 subsite. From the relationship between the length of the nonpolar P1 group and the biological activity, we confirm that MMP-2 has a pocket-like S1 subsite, not a channel-like S1 subsite proposed by Kiyama (Kiyama, R. et al., J. Med. Chem. 42 (1999), 1723). The energetic analyses show that the experimental binding free energies can be well correlated with the interactions between the inhibitors and their environments, which could be used as a simple score function to evaluate the binding affinities for other similar hydroxamates. The validity of the force field parameters and the MD simulations can be fully testified by the satisfactory agreements between the experimental structure-activity relationship and the information from the structural and energetic analyses. The information generated from the predicted complexes should be useful for further work in the area of structure-based design of new compounds.     

Molecular docking of cathepsin L inhibitors in the binding site of papain

The papain/CLIK-148 coordinate system was employed as a model to study the interactions of a nonpeptide thiocarbazate inhibitor of cathepsin L ( 1). This small molecule inhibitor, a thiol ester containing a diacyl hydrazine functionality and one stereogenic center, was most active as the S-enantiomer, with an IC 50 of 56 nM; the R-enantiomer ( 2) displayed only weak activity (33 microM). Correspondingly, molecular docking studies with Extra Precision Glide revealed a correlation between score and biological activity for the two thiocarbazate enantiomers when a structural water was preserved. The molecular interactions between 1 and papain were very similar to the interactions observed for CLIK-148 ( 3a and 3b) with papain, especially with regard to the hydrogen-bonding and lipophilic interactions of the ligands with conserved residues in the catalytic binding site. Subsequent docking of virtual compounds in the binding site led to the identification of a more potent inhibitor ( 5), with an IC 50 of 7.0 nM. These docking studies revealed that favorable energy scores and correspondingly favorable biological activities could be realized when the virtual compound design included occupation of the S2, S3, and S1' subsites by hydrophobic and aromatic functionalities of the ligand, and at least three hydrogen bonding contacts between the ligand and the conserved binding site residues of the protein.     

Calculation of relative binding affinities of fructose 1,6-bisphosphatase mutants with adenosine monophosphate using free energy perturbation method

The free energy perturbation (FEP) methodology is the most accurate means of estimating relative binding affinities between inhibitors and protein variants. In this article, the importance of hydrophobic and hydrophilic residues to the binding of adenosine monophosphate (AMP) to the fructose 1,6-bisphosphatase (FBPase), a target enzyme for type-II diabetes, was examined by FEP method. Five mutations were made to the FBPase enzyme with AMP inhibitor bound: 113Tyr --> 113Phe, 31Thr --> 31Ala, 31Thr --> 31Ser, 177Met --> 177Ala, and 30Leu --> 30Phe. These mutations test the strength of hydrogen bonds and van der Waals interactions between the ligand and enzyme. The calculated relative free energies indicated that: 113Tyr and 31Thr play an important role, each via two hydrogen bonds affecting the binding affinity of inhibitor AMP to FBPase, and any changes in these hydrogen bonds due to mutations on the protein will have significant effect on the binding affinity of AMP to FBPase, consistent to experimental results. Also, the free energy calculations clearly show that the hydrophilic interactions are more important than the hydrophobic interactions of the binding pocket of FBPase.     

G protein- and agonist-bound serotonin 5-HT2A receptor model activated by steered molecular dynamics simulations

A 5-HT(2A) receptor model was constructed by homology modeling based on the β(2)-adrenergic receptor and the G protein-bound opsin crystal structures. The 5-HT(2A) receptor model was transferred into an active conformation by an agonist ligand and a G(αq) peptide in four subsequent steered molecular dynamics (MD) simulations. The driving force for the transformation was the addition of several known intermolecular and receptor interhelical hydrogen bonds enforcing the necessary helical and rotameric movements. Subsquent MD simulations without constraints confirmed the stability of the activated receptor model as well as revealed new information about stabilizing residues and bonds. The active 5-HT(2A) receptor model was further validated by retrospective ligand screening of more than 9400 compounds, whereof 182 were known ligands. The results show that the model can be used in drug discovery for virtual screening and structure-based ligand design as well as in GPCR activation studies.     

Simulation analysis of the cellulase Cel7A carbohydrate binding module on the surface of the cellulose Iβ

The Family 7 cellobiohydrolase (Cel7A) from Trichoderma reesei consists of a carbohydrate-binding module (CBM) joined by a linker to a catalytic domain. Cellulose hydrolysis is limited by the accessibility of Cel7A to crystalline substrates, which is perceived to be primarily mediated by the CBM. Here, the binding of CBM to the cellulose Iβ fiber is characterized by combined Brownian dynamics (BD) and molecular dynamics (MD) simulations. The results confirm that CBM prefers to dock to the hydrophobic than to the hydrophilic fiber faces. Both electrostatic (ES) and van der Waals (VDW) interactions are required for achieving the observed binding preference. The VDW interactions play a more important role in stabilizing the CBM-fiber binding, whereas the ES interactions contribute through the formation of a number of hydrogen bonds between the CBM and the fiber. At long distances, an ES steering effect is also observed that tends to align the CBM in an antiparallel manner relative to the fiber axis. Furthermore, the MD results reveal hindered diffusion of the CBM on all fiber surfaces. The binding of the CBM to the hydrophobic surfaces is found to involve partial dewetting at the CBM-fiber interface coupled with local structural arrangements of the protein. The present simulation results complement and rationalize a large body of previous work and provide detailed insights into the mechanism of the CBM-cellulose fiber interactions.     

Rational design of peptide ligand for affinity chromatography of tissue-type plasminogen activator by the combination of docking and molecular dynamics simulations

Combined docking and molecular dynamics (MD) simulations are carried out for the rational design of affinity peptide ligand of tissue-type plasminogen activator (t-PA). Ten amino acids that have high affinity to three different regions of t-PA are identified by the amino acids location method on the basis of candidate pocket structure of t-PA. Then, 14 tetrapeptides are built and docked into the candidate pocket of t-PA. The absolute value of the D(score) calculated from the docking simulation is used to assess the affinity of a peptide for t-PA. Consequently, six tetrapeptides that have high D(score) values are selected and linked to a spacer arm of [NH(CH(2))(6)NH(2)] that is present on EAH Sepharose gel. The linked compounds are further evaluated by docking into the candidate pocket of t-PA. As a result, the tetrapeptide QDES with the highest D(score) value is selected. Molecular surface analysis with the MOLCAD program reveals that electrostatic interactions and hydrogen bonds (H-bonds) contribute to the affinity interactions between the tetrapeptide and t-PA. MD simulations indicate that QDES-t-PA complex keeps stable, and the distances between the carboxyl groups of Asp189, Gln192 and Asp194 and the charged amino group of glutamine change little. Moreover, all the nine H-bonds found in the docking simulation are confirmed by the MD simulations. It is also found that three water molecules act as bridges between the ligand and the protein pocket by hydrogen bonding. Finally, high binding affinity and specificity of the peptide ligand are confirmed by the purification of t-PA from crude porcine heart extract using the immobilized-ligand column for affinity chromatography.     

Subtype selectivity and flexibility of ionotropic glutamate receptors upon antagonist ligand binding

The binding modes of a set of known ionotropic glutamate receptor antagonist-ligands have been studied using homology modeling, molecular docking, molecular dynamics (MD) simulations and ab initio quantum mechanical calculations. The core structure of the studied ligands is the decahydroisoquinoline ring, which has a carboxylic acid group at position three and different negatively-charged substituents (R) at position six. The binding affinities of these molecules have been reported earlier. From the current study, the carboxylate group of the decahydroisoquinoline ring hydrogen bonds with Arg485, the amino group with Pro478 and Thr480, and the negatively charged substituent R interacts with the positively charged N-terminus of helix-F. The subtype selectivity of these ligands seems to be strongly dependent on the amino acid at position 650 (GluR2: leucine, GluR5: valine), which affects the conformation of the ligand and ligand-receptor interactions, but depends considerably on the size of the R-group of the ligand. In addition, the MD simulations also revealed that the relative positions of the S1 and S2 domains can alter significantly showing different "closure" and "rotational movements" depending on the antagonist-ligand that is bound. Accordingly, molecular docking of antagonist ligands into static crystal structures cannot sufficiently explain ligand binding and subtype selectivity.