胰蛋白酶和苯酰氨类抑制剂结合自由能的预测

用基于线性响应近似的自由能预测方法计算胰蛋白酶和苯酰氨类抑制剂的结合 自由能。计算结果表明,单参数,双参数和三参数模型具有相似的线性回归系数, 但三参数和双参数模型的交互验证回归系数要明显优于单参数模型。从预测能力来 看,双参数模型和三参数模型都能够很好地预测测试集中抑制剂的结合自由能,其 中双参数模型预测的结果要略优于三参数模型的预测结果。对测试集中的抑制剂, 双参数模型预测得到的预测自由能和实际自由能之间平均绝对误差仅为1.15 kJ/mol。自由能计算模型以及分子动力学轨迹能很好地解释抑制剂结构和活性的 关系,为药物设计提供了重要的结构信息。     

Studies of the mechanism of selectivity of protein tyrosine phosphatase 1B (PTP1B) bidentate inhibitors using molecular dynamics simulations and free energy calculations

Bidentate inhibitors of protein tyrosine phosphatase 1B (PTP1B) are considered as a group of ideal inhibitors with high binding potential and high selectivity in treating type II diabetes. In this paper, the binding models of five bidentate inhibitors to PTP1B, TCPTP, and SHP-2 were investigated and compared by using molecular dynamics (MD) simulations and free energy calculations. The binding free energies were computed using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology. The calculation results show that the predicted free energies of the complexes are well consistent with the experimental data. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition analysis indicates that the residues ARG24, ARG254, and GLN262 in the second binding site of PTP1B are essential for the high selectivity of inhibitors. Furthermore, the residue PHE182 close to the active site is also important for the selectivity and the binding affinity of the inhibitors. According to our analysis, it can be concluded that in most cases the polarity of the portion of the inhibitor that binds to the second binding site of the protein is positive to the affinity of the inhibitors while negative to the selectivity of the inhibitors. We expect that the information we obtained here can help to develop potential PTP1B inhibitors with more promising specificity.     

Synthesis of Novel Nonpeptidic Thrombin Inhibitors

A novel class of nonpeptidic, active, and selective thrombin inhibitors has resulted from X‐ray‐structure‐based design and subsequent improvement of the initial lead molecules. These inhibitors possess a bi‐ or tricyclic central core structure with attached side chains to reach the three binding pockets (selectivity S1 pocket, distal D pocket, and proximal P pocket) present in the active site of the enzyme. The key step in the preparation of these compounds is the 1,3‐dipolar cycloaddition between an azomethine ylide, prepared in situ by the decarboxylative method from an aromatic aldehyde and an α‐amino acid, with an N‐substituted maleimide (e.g., see Schemes 1 and 2). All potent inhibitors contain an amidinium residue in the side chain for incorporation into the S1 pocket, which was introduced in the last step of the synthesis by a Pinner reaction. The compounds were tested in biological assays for activity against thrombin and the related serine protease trypsin. The first‐generation lead compounds (±)‐ 11 and (±)‐ 19 (Scheme 1) with a bicyclic central scaffold showed K_i values for thrombin inhibition of 18 μM and 0.67 μM , respectively. Conformationally more restricted second‐generation analogs (Scheme 2) were more active ((±)‐ 22i : K_i=90 nM (Table 1)); yet the selectivity for thrombin over trypsin remained weak. In the third‐generation compounds, a small lipophilic side chain for incorporation into the hydrophobic P pocket was introduced (Schemes 7 and 8). Since this pocket is present in thrombin but not in trypsin, an increase in binding affinity was accompanied by an increase in selectivity for thrombin over trypsin. The most selective inhibitor (K_i=13 nM , 760‐fold selectivity for thrombin over trypsin; Table 2) was (±)‐ 1 with an i‐Pr group for incorporation into the P pocket. Optical resolution of (±)‐ 1 (Scheme 9) provided (+)‐ 1 with a K_i value of 7 nM and a 740‐fold selectivity, whereas (−)‐ 1 was 800‐fold less active (K_i=5.6 μM , 21‐fold selectivity). The absolute configuration of the stronger‐binding enantiomer was assigned based on the X‐ray crystal structure of the complex formed between thrombin and this inhibitor. Compound (+)‐ 1 mimics the natural thrombin substrate, fibrinogen, which binds to the enzyme with the Ph group of a phenylalanine (piperonyl in (+)‐ 1 ) in the distal D pocket, with the i‐Pr group of a valine (i‐Pr in (+)‐ 1 ) in the proximal P pocket, and with a guanidinium side chain of an arginine residue (phenylamidinium group in (+)‐ 1 ) in the selectivity S1 pocket of thrombin. A series of analogs of (±)‐ 1 with the phenylamidinium group replaced by aromatic and aliphatic rings bearing OH or NH₂ groups (Schemes 10 – 14) were not effectively bound by thrombin. A number of X‐ray crystal‐structure analyses of free inhibitors confirmed the high degree of preorganization of these compounds in the unbound state. Since all inhibitors prefer similar modes of association with thrombin, detailed information on the strength of individual intermolecular bonding interactions and their incremental contribution to the overall free energy of complexation was generated in correlative binding and X‐ray studies. The present study demonstrates that defined mutations in highly preorganized inhibitors provide an attractive alternative to site‐directed mutagenesis in exploring molecular‐recognition phenomena at enzyme active sites.     

A fluorine scan of the phenylamidinium needle of tricyclic thrombin inhibitors: effects of fluorine substitution on pKa and binding affinity and evidence for intermolecular C-F...CN interactions

The H-atoms of the phenylamidinium needle of tricyclic thrombin inhibitors, which interacts with Asp189 at the bottom of the selectivity pocket S1 of the enzyme, were systematically exchanged with F-atoms in an attempt to improve the pharmacokinetic properties by lowering the pK(a) value. Both the pK(a) values and the inhibitory constants K(i) against thrombin and trypsin were decreased upon F-substitution. Interestingly, linear free energy relationships (LFERs) revealed that binding affinity against thrombin is much more affected by a decrease in pK(a) than the affinity against trypsin. Surprising effects of F-substitutions in the phenylamidinium needle on the pK(a) value of the tertiary amine centre in the tricyclic scaffold of the inhibitors were observed and subsequently rationalised by X-ray crystallographic analysis and ab initio calculations. Evidence for highly directional intermolecular C-F...CN interactions was obtained by analysis of small-molecule X-ray crystal structures and investigations in the Cambridge Structural Database (CSD).     

分子动力学研究V82A和L90M变异对HIV PR-IDV复合物的影响

为了说明V82A和L90M变异对蛋白酶(PR)和茚地那韦(IDV)复合物的影响,进行了5.5ns的MD模拟.用MM-PBSA方法计算了体系的结合自由能,计算和实验结果一致.分解自由能为不同能量项说明,这两个变异引起熵的贡献变化大于焓的贡献变化.分解自由能到每个残基说明Wild,V82A和L90M具有相似的结合模式,结合能的贡献主要来源于A28/A28',I50/I50'和I84/I84'这六个残基组,详细分析了Wild和IDV的结合模式,对比分析了V82A和L90M变异引起结合模式的细小变化.V82A变异引起结合模式的变化是由于变异后位阻减小导致的.L90M变异引起D25和L90间的作用增强并引起结合模式的细小变化.研究结果有助于更好地理解变异对抑制剂和HIV-1PR结合模式的影响,并可以用来帮助设计更高效的PR抑制剂.     

Mechanistic Insights into the Mechanism of Inhibitor Selectivity toward the Dark Kinase STK17B against Its High Homology STK17A

As a member of the death-associated protein kinase (DAPK) family, STK17B plays an important role in the regulation of cellular apoptosis and has been considered as a promising drug target for hepatocellular carcinoma. However, the highly conserved ATP-binding site of protein kinases represents a challenge to design selective inhibitors for a specific DAPK isoform. In this study, molecular docking, multiple large-scale molecular dynamics (MD) simulations, and binding free energy calculations were performed to decipher the molecular mechanism of the binding selectivity of PKIS43 toward STK17B against its high homology STK17A. MD simulations revealed that STK17A underwent a significant conformational arrangement of the activation loop compared to STK17B. The binding free energy predictions suggested that the driving force to control the binding selectivity of PKIS43 was derived from the difference in the protein–ligand electrostatic interactions. Furthermore, the per-residue free energy decomposition unveiled that the energy contribution from Arg41 at the phosphate-binding loop of STK17B was the determinant factor responsible for the binding specificity of PKIS43. This study may provide useful information for the rational design of novel and potent selective inhibitors toward STK17B.     

Calculation of absolute binding free energies for charged ligands and effects of long-range electrostatic interactions

A recently proposed molecular dynamics method for estimating binding free energies is applied to the complexation of two charged benzamidine inhibitors with trypsin. The difficulties with calculations of absolute binding energies for charged molecules, associated with long-range electrostatic contributions, are discussed and it is shown how to deal with these effectively. In particular, energetic effects caused by the trunction of dipole-dipole interactions in the medium surrounding the charged ligand are examined and found to be significant. Calculations of the absolute binding energy for benzamidine using the free energy perturbation approach are also reported. These simulations illustrate the typical problems associated with annihilation transformations of molecules bound inside proteins. © 1996 by John Wiley & Sons, Inc.     

A computational analysis of the binding model of MDM2 with inhibitors

Abstract  

It is a new and promising strategy for anticancer drug design to block the MDM2-p53 interaction using a non-peptide small-molecule inhibitor. We carry out molecular dynamics simulations to study the binding of a set of six non-peptide small-molecule inhibitors with the MDM2. The relative binding free energies calculated using molecular mechanics Poisson–Boltzmann surface area method produce a good correlation with experimentally determined results. The study shows that the van der Waals energies are the largest component of the binding free energy for each complex, which indicates that the affinities of these inhibitors for MDM2 are dominated by shape complementarity. The A-ligands and the B-ligands are the same except for the conformation of 2,2-dimethylbutane group. The quantum mechanics and the binding free energies calculation also show the B-ligands are the more possible conformation of ligands. Detailed binding free energies between inhibitors and individual protein residues are calculated to provide insights into the inhibitor-protein binding model through interpretation of the structural and energetic results from the simulations. The study shows that G1, G2 and G3 group mimic the Phe19, Trp23 and Leu26 residues in p53 and their interactions with MDM2, but the binding model of G4 group differs from the original design strategy to mimic Leu22 residue in p53.     

γ-环糊精和波尼松龙的相互作用分子动力学模拟和自由能计算

运用分子动力学（Molecular dynamics,MD）和MM—PBSA（molecular mechanics／Poisson Boltzmann surfaeearea）相结合的方法预测了γ-环糊精（γ-cyclodextrin,γ-CD）和波尼松龙的包结模式．在MD模拟过程中,波尼松龙分别采用A环和D环两种取向从γ-CD大口端进入其空腔．在MD轨迹采样基础上,采用高效MM—PBSA方法计算了两种取向的包结自由能．结果表明,计算包结自由能值和实验包结自由能值非常吻合．进一步分析各个能量项,发现范德华相互作用能为包结的主要驱动力．通过比较两种取向的包结自由能大小,预测D环取向为优势包结模式．     

Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors

(V600E)B-RAF kinase is the most frequent onco-genic protein kinase mutation in melanoma and is a promising target to treat malignant melanoma. In this work, a molecular modeling study combining QM-polarized ligand docking, molecular dynamics, free energy calculation, and three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed on a series of pyridoimidazolone compounds as the inhibitors of (V600E)B-RAF kinase to understand the binding mode between the inhibitors and (V600E)B-RAF kinase and the structural requirement for the inhibiting activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by QM-polarized ligand docking strategy. The obtained models have a good predictive ability in both internal and external validation. Furthermore, molecular dynamics simulation and free energy calculations were employed to determine the detailed binding process and to compare the binding mode of the inhibitors with different activities. The binding free energies calculated by MM/PBSA gave a good correlation with the experimental biological activity. The decomposition of free energies by MM/GBSA indicates the van der Waals interaction is the major driving force for the interaction between the inhibitors and (V600E)B-RAF kinase. The hydrogen bond interactions between the inhibitors with Glu501 and Asp594 of the (V600E)B-RAF kinase help to stabilize the DFG-out conformation. The results from this study can provide some insights into the development of novel potent (V600E)B-RAF kinase inhibitors.     

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。     

A Three‐Site Mechanism for Agonist/Antagonist Selective Binding to Vasopressin Receptors

Molecular‐dynamics simulations with metadynamics enhanced sampling reveal three distinct binding sites for arginine vasopressin (AVP) within its V₂‐receptor (V₂R). Two of these, the vestibule and intermediate sites, block (antagonize) the receptor, and the third is the orthosteric activation (agonist) site. The contacts found for the orthosteric site satisfy all the requirements deduced from mutagenesis experiments. Metadynamics simulations for V₂R and its V_1aR‐analog give an excellent correlation with experimental binding free energies by assuming that the most stable binding site in the simulations corresponds to the experimental binding free energy in each case. The resulting three‐site mechanism separates agonists from antagonists and explains subtype selectivity.     

Structural and energetic insight into the interactions between the benzolactam inhibitors and tumor marker HSP90α

The heat shock protein 90α (HSP90α) provides a promising molecular target for cancer therapy. A series of novel benzolactam inhibitors exhibited distinct inhibitory activity for HSP90α. However, the structural basis for the impact of distinct R₁ substituent groups of nine benzolactam inhibitors on HSP90α binding affinities remains unknown. In this study, we carried out molecular docking, molecular dynamics (MD) simulations, and molecular mechanics and generalized Born/surface area (MM–GBSA) binding free energy calculations to address the differences. Molecular docking studies indicated that all nine compounds presented one conformation in the ATP-binding site of HSP90α N-terminal domain. MD simulations and subsequent MM–GBSA calculations revealed that the hydrophobic interactions between all compounds and HSP90α contributed the most to the binding affinity and a good linear correlation was obtained between the calculated and the experimental binding free energies (R = 0.88). The per residue decomposition revealed that the most remarkable differences of residue contributions were found in the residues Ala55, Ile96, and Leu107 defining a hydrophobic pocket for the R₁ group, consistent with the analysis of binding modes. This study may be helpful for the future design of novel HSP90α inhibitors.     

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.     

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。     

Profiling the structural determinants for the selectivity of representative factor-Xa and thrombin inhibitors using combined ligand-based and structure-based approaches

The current study deciphers the combined ligand- and structure-based computational insights to profile structural determinants for the selectivity of representative diverse classes of FXa-selective and thrombin-selective as well as dual FXa-thrombin high affinity inhibitors. The thrombin-exclusive insertion 60-loop (D-pocket) was observed to be one of the most notable recognition sites for the known thrombin-selective inhibitors. Based on the topological comparison of four common active-site pockets (S1-S4) of FXa and thrombin, the greater structural disparity was observed in the S4-pocket, which was more symmetrical (U-shaped) in FXa as compared to thrombin mainly due to the presence of L99 and I174 residues in latter in place of Y99 and F174 respectively in former protease. The S2 pocket forming partial roof at the entry of 12 ? deep S1-pocket, with two extended β-sheets running antiparallel to each other by undergoing U-turn (～180?), has two conserved glycine residues forming H-bonds with the bound ligand for governing ligand binding affinity. The docking, scoring, and binding pose comparison of the representative high-affinity and selective inhibitors into the active sites of FXa and thrombin revealed critical residues (S214, Y99, W60D) mediating selectivity through direct- and long-range electrostatic interactions. Interestingly, most of the thrombin-selective inhibitors attained S-shaped conformation in thrombin, while FXa-selective inhibitors attained L-shaped conformations in FXa. The role of residue at 99th position of FXa and thrombin toward governing protease selectivity was further substantiated using molecular dynamics simulations on the wild-type and mutated Y99L FXa bound to thrombin-selective inhibitor 2. Furthermore, predictive CoMFA (FXa q2 = 0.814; thrombin q2 = 0.667) and CoMSIA (FXa q2 = 0.807; thrombin q2 = 0.624) models were developed and validated (FXa r2(test) = 0.823; thrombin r(2)(test) = 0.816) to feature molecular determinants of ligand binding affinity using the docking-based conformational alignments (DBCA) of 141 (88(train)+53(test)) and 39 (27(train)+11(test)) nonamidine class of potent FXa (0.004 ≤ K(i) (nM) ≤ 4700) and thrombin (0.001 ≤ K(i) (nM) ≤ 940) inhibitors, respectively. Interestingly, the ligand-based insights well corroborated with the structure-based insights in terms of the role of steric, electrostatic, and hydrophobic parameters for governing the selectivity for the two proteases. The new computational insights presented in this study are expected to be valuable for understanding and designing potent and selective antithrombotic agents.     

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。     

The application of three approximate free energy calculations methods to structure based ligand design: Trypsin and its complex with inhibitors

Three approximate free energy calculation methods are examined and applied to an example ligand design problem. The first of the methods uses a single simulation to estimate the relative binding free energies for related ligands that are not simulated. The second method is similar, except that it uses only first derivatives of free energy with respect to atomic parameters (most often charge, van der Waals equilibrium distance, and van der Waals well depth) to calculate free energy differences. The last method PROFEC (Pictorial Representation of Free Energy Components), generates contour maps that show how binding free energy changes when additional particles are added near the ligand. These three methods are applied to a benzamidine/trypsin complex. They each reproduce the general trends in the binding free energies, indicating that they might be useful for suggesting how ligands could be modified to improve binding and, consequently, useful in structure-based drug design.     

新型二氟甲基磷酸类酪氨酸蛋白磷酸酯酶1B抑制剂的分子动力学模拟和结合自由能计算

通过分子对接建立了一系列含二氟甲基磷酸基团(DFMP)或二氟甲基硫酸基团(DFMS)的抑制剂与酪氨酸蛋白磷酸酯酶1B(PTP1B)的相互作用模式, 并通过1 ns的分子动力学模拟和molecular mechanics/generalized Born surface area (MM/GBSA)方法计算了其结合自由能. 计算获得的结合自由能排序和抑制剂与靶酶间结合能力排序一致; 通过基于主方程的自由能计算方法, 获得了抑制剂与靶酶残基间相互作用的信息, 这些信息显示DFMP/DFMS基团的负电荷中心与PTP1B的221位精氨酸正电荷中心之间的静电相互作用强弱决定了此类抑制剂的活性, 进一步的分析还显示位于DFMP/DFMS基团中的氟原子或其他具有适当原子半径的氢键供体原子会增进此类抑制剂与PTP1B活性位点的结合能力.