The effect of physical organic properties on hydrophobic fields

Summary Physical organic structural properties of small molecules and macromolecules such as bond count, branching and proximity between multiple polar fragments contribute significantly to measured hydrophobicity (log P). These structural properties are encoded in the Rekker and Leo methods of calculating log P as structural-dependent factors. Regardless of the size of the atom primitive set, methods predicting log P with only atom primitives can miss subtle structural detail within series of related compounds. The HINT (Hydropathic INTeractions) model for inter- and intramolecular noncovalent interactions calculates atom-based hydrophobic constants, but uses all Leo-type factors in the calculation rather than a large set of atom primitives. Two types of applications of HINT are discussed: evaluation of the binding of an inhibitor (A74704) to HIV-1 protease, where it is shown that modeling of the protonation state (i.e., Asp²⁵, Asp¹²⁵) in the protein can strongly influence perceived substrate binding; and the use of HINT to calculate a third (hydropathic) field for CoMFA can yield a statistically enhanced and predictive model for molecular design.     

两类促肾上腺皮质释放激素(CRH)拮抗剂的分子场分析

采用比较分子相似性指数分析方法(CoMSIA)及比较分子场分析方法(CoMSIA)研究了两组CRH拮抗剂结构与活性的关系。在两种方法中,都考虑了静电场、立体场以及氢键场对构效关系的影响,结果表明采用CoMSIA得到构效关系模型要明显优于采用CoMFA得到的构效关系模型,在CoMSIA计算中,当引入疏水场时,三维构效关系模型能得到明显的改善,通过这个三维构效关系模型,可以较为精确地预测化合物的活性。通过分析分子场等值面图在空间的分布,可以观察到叠合分子周围的立体、静电以及疏水特征对化合物活性的影响。     

Molecular modeling of triazine type MDR modulators using CoMFA and CoMSIA approaches

In the present study a series of 30 triazine derivatives was investigated by 3D QSAR methods with respect to their MDR reversing activity in vitro. Two approaches were applied and compared: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Molecular models with good predictive power were derived using steric, electrostatic and hydrophobic fields of the compounds. The results indicated the dominant role of the electrostatic and hydrophobic fields for MDR reversing activity of the investigated modulators. The obtained statistical parameters (Qcv2, Qpr2) showed that the CoMFA and CoMSIA models have similar predictivity. The CoMSIA models were slightly better than the CoMFA ones and obtained with lower number of principal components. The models were graphically interpreted using CoMFA and CoMSIA contour plots. The structural regions responsible for the differences in anti-MDR activity were analyzed in respect to their electrostatic and hydrophobic nature. An easier interpretation of the CoMSIA contour plots was noticed.     

Molecular modeling of triazine type MDR modulators using CoMFA and CoMSIA approaches

In the present study a series of 30 triazine derivatives was investigated by 3D QSAR methods with respect to their MDR reversing activity in vitro . Two approaches were applied and compared: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Molecular models with good predictive power were derived using steric, electrostatic and hydrophobic fields of the compounds. The results indicated the dominant role of the electrostatic and hydrophobic fields for MDR reversing activity of the investigated modulators. The obtained statistical parameters ( Q cv 2 , Q pr 2 ) showed that the CoMFA and CoMSIA models have similar predictivity. The CoMSIA models were slightly better than the CoMFA ones and obtained with lower number of principal components. The models were graphically interpreted using CoMFA and CoMSIA contour plots. The structural regions responsible for the differences in anti-MDR activity were analyzed in respect to their electrostatic and hydrophobic nature. An easier interpretation of the CoMSIA contour plots was noticed.     

GPR40 受体苯丙酸类激动剂三维定量构效关系研究

苯丙酸类化合物是G蛋白偶联受体40(GPR40)潜在的生物活性药物。本文基于比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(CoMSIA),分别建立了40个已知活性的GPR40受体苯丙酸类激动剂的三维定量构效关系(3D-QSAR)模型,研究该类激动剂与生物活性之间的关系。CoMFA和CoMSIA模型的交叉验证系数(q~2)分别为0. 527和0. 500,拟合验证系数(r~2)分别为0. 901和0. 860,两个3D-QSAR模型预测值与实验值基本一致,表明模型具有良好的可信度和预测能力。根据两个3D-QSAR模型提供的立体场、静电场、疏水场、氢键供体场和氢键受体场所提供的信息提出优化该类抑制剂结构的药物设计思路,为指导设计更高活性的GPR40激动剂以及GRR40新分子激动活性的预测提供理论依据。     

3D-QSAR modeling of maximum steady-state fluxes of some substituted benzenes and quinolone derivatives through polydimethylsiloxane membrane

The maximum steady-state flux of 79 compounds (substituted benzenes, and quinolones and their derivatives) with a wide range of polarity through a PDMS membrane was predicted using a comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods. Moreover, the contribution of partial atomic charge to mass transport phenomena was further verified by the correlation of atomic charge to apparent permeability through polydimethylsiloxane (PDMS) membranes. The obtained results indicated superiority of CoMSIA model over CoMFA model. The best CoMSIA model is developed based on the combination of electrostatic and hydrophobic and H-bond acceptor fields (CoMSIA-EHA). The contour maps of electrostatic and hydrophobic and H-bond acceptor fields of CoMSIA model provide an interpretable and logical relationship between chemicals structure and their fluxes, which give useful insights for designing new compounds with higher penetration through the membranes.     

Improved CoMFA modeling by optimization of settings

The possibility of improving the predictive ability of comparative molecular field analysis (CoMFA) by settings optimization has been evaluated to show that CoMFA predictive ability can be improved. Ten different CoMFA settings are evaluated, producing a total of 6120 models. This method has been applied to nine different data sets, including the widely used benchmark steroid data set, as well as eight other data sets proposed as QSAR benchmarking data sets by Sutherland et al. (J. Med. Chem. 2004, 47, 5541-5554). All data sets have been studied using training and test sets to allow for both internal (q(2)) and external (r(2)(pred)) predictive ability assessment. CoMFA settings optimization was successful in developing models with improved q(2) and r(2)(pred) as compared to default CoMFA modeling. Optimized CoMFA is compared with comparative molecular similarity indices analysis (CoMSIA) and holographic quantitative structure-activity relationship (HQSAR) models and found to consistently produce models with improved or equivalent q(2) and r(2)(pred). The ability of settings optimization to improve model predictive ability has been validated using both internal and external predictions, and the risk of chance correlation has been evaluated using response variable randomization tests.     

拓扑异构酶Ⅰ抑制剂高喜树碱类化合物的三维定量构效关系研究

针对拓扑异构酶Ⅰ抑制剂高喜树碱类化合物,采用比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)的方法对其进行三维定量构效关系的研究.构建CoMFA模型其q2=0.706,最佳主成分数n=6,非交叉验证系数r2=0.966,标准差S=0.277,F=117.613,立体场和静电场的贡献值分别为0.62和0.38.构建CoMSIA模型其q2=0.696,最佳主成分数n=7,非交叉验证系数r2=0.956,标准差S=0.320,F=74.374,其疏水场和立体场的贡献分别为0.75和0.25.结果显示疏水场和立体场对化合物的活性有较大影响.     

苯并呋喃／噻吩联二苯类PTP1B抑制剂三维构效关系研究

主要采用比较分子力场分析方法（CoMFA）对苯并呋喃／噻吩联二苯类PTP1B (protein tyrosine phosphatase 1B)抑制剂进行了三维构效关系的研究，考察了 静电场、立体场和氢键场对构效关系的影响，交叉系数q^2的值达到0．58，表明 CoMFA得到的构效关系模型比较理想，同时test set中分子的预测活性也表明，模 型具有较好的预测能力，研究还表明，氢键场的加入不一定有利于模型的改善，通 过对分子场等值面图的分析，可以观察到叠合分子周围立体场和静电场对化合物活 性的影响，为改进原有化合物的结构，提高它们的活性提供了指导，还尝试采用比 较分子相似性指数分析方法（CoMFA）对这一系列化合物作了研究，结果表明虽然 CoMFA中加入了疏水场，但是对于研究的体系，CoMFA的模型质量并没有显著提高。     

新型三唑类抗真菌化合物的三维定量构效关系研究

采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA), 系统研究了40个新型三唑类化合物抗真菌活性的三维定量构效关系. 在CoMFA研究中, 研究了两种药效构象对模型的影响, 并考察了网格点步长对统计结果的影响. 在CoMSIA研究中, 系统考察了各种分子场组合、网格点步长和衰减因子对模型统计结果的影响, 发现立体场、静电场、疏水场和氢键受体场的组合得到最佳模型. 所建立CoMFA和CoMSIA模型的交叉相关系数q²值分别为0.718和0.655, 并都具有较强的预测能力. CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯环上各位置取代基对抗真菌活性的影响, 为进一步结构优化提供了重要依据.     

HLA-A*0201限制性CTL表位肽的三维定量构效关系的研究

运用比较分子力场(CoMFA)和比较分子相似性指数分析(CoMFA)方法研究了50个HLA-A^*0201限制性CTL表位九肽结构与亲和性间的关系,另外15个表位九肽作为预测集用于检验模型的预测能力.结果表明采用CoMSIA得到的构效关系模型(q^2=0.628,r^2=0.997,F=840.419)要明显优于采用CoMFA得到的构效关系模型.在CoMSIA计算中,当引入疏水场时,三维构效关系模型得到明显改善,通过该三维构效关系模型,可较精确地估算预测集中15个CTL表位肽与HLA-A^*0201间的亲和力(r^2pred=0.743).通过分析分子场等值面图在空间的分布,可以观察到表位肽分子周围的立体及疏水特征对表位肽与HLA-A^*0201间结合亲和力的影响,从而为进一步对CTL表位肽进行结构改造并基于此进行治疗性疫苗分子设计提供理论基础.     

Three-dimensional Quantitative Structure-activity Relationship Models of HIV-1 Integrase Inhibitors of DKAs

As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds (DKAs) are one kind of potent and selective inhibitors of HIV-1 IN. In the present work, two three-dimensional QSAR techniques (CoMFA and CoMSIA) were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search (AOS) and all-placement search (APS) were used to optimize the CoMFA model. The diketo and keto-enol tautomers of DKAs were also used to establish the CoMFA models. The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favorable internal validation. A comparative analysis with the three models demonstrated that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models would give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors.     

苯并呋喃类N-肉豆蔻酰基转移酶抑制剂的三维定量构效关系研究

摘要采用比较分子力场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA), 系统地研究了40个苯并呋喃类N-肉豆蔻酰基转移酶(NMT)抑制剂的三维定量构效关系. 在CoMFA研究中, 考察了网格点步长对模型统计结果的影响. 在CoMSIA研究中, 研究了各种分子场组合、 网格点步长和衰减因子对模型统计结果的影响, 发现立体场、 静电场、 疏水场和氢键受体场的组合可得到最佳模型. 所建立的CoMFA和CoMSIA模型的交叉相关系数q2值分别为0.759和0.730, 均具有较强的预测能力. 利用CoMFA和CoMSIA模型的三维等值线图直观地解释了化合物的构效关系, 阐明了化合物结构中苯并呋喃环上各位置取代基对抑酶活性的影响, 为进一步结构优化提供了重要依据.     

Very empirical treatment of solvation and entropy: a force field derived from Log Po/w

A non-covalent interaction force field model derived from the partition coefficient of 1-octanol/water solubility is described. This model, HINT for Hydropathic INTeractions, is shown to include, in very empirical and approximate terms, all components of biomolecular associations, including hydrogen bonding, Coulombic interactions, hydrophobic interactions, entropy and solvation/desolvation. Particular emphasis is placed on: (1) demonstrating the relationship between the total empirical HINT score and free energy of association, G _interaction; (2) showing that the HINT hydrophobic-polar interaction sub-score represents the energy cost of desolvation upon binding for interacting biomolecules; and (3) a new methodology for treating constrained water molecules as discrete independent small ligands. An example calculation is reported for dihydrofolate reductase (DHFR) bound with methotrexate (MTX). In that case the observed very tight binding, G _interaction–13.6 kcal mol^–1, is largely due to ten hydrogen bonds between the ligand and enzyme with estimated strength ranging between –0.4 and –2.3 kcal mol^–1. Four water molecules bridging between DHFR and MTX contribute an additional –1.7 kcal mol^–1 stability to the complex. The HINT estimate of the cost of desolvation is +13.9 kcal mol^–1.     

Three-dimensional quantitative structure-activity relationships of steroid aromatase inhibitors

Summary Inhibition of aromatase, a cytochrome P450 that converts androgens to estrogens, is relevant in the therapeutic control of breast cancer. We investigate this inhibition using a three-dimensional quantitative structure-activity relationship (3D QSAR) method known as Comparative Molecular Field Analysis, CoMFA [Cramer III, R.D. et al., J. Am. Chem. Soc., 110 (1988) 5959]. We analyzed the data for 50 steroid inhibitors [Numazawa, M. et al., J. Med. Chem., 37 (1994) 2198, and references cited therein] assayed against androstenedione on human placental microsomes. An initial CoMFA resulted in a three-component model for log(1/K_i), with an explained variance r² of 0.885, and a cross-validated q² of 0.673. Chemometric studies were performed using GOLPE [Baroni, M. et al., Quant. Struct.-Act. Relatsh., 12 (1993) 9]. The CoMFA/GOLPE model is discussed in terms of robustness, predictivity, explanatory power and simplicity. After randomized exclusion of 25 or 10 compounds (repeated 25 times), the q² for one component was 0.62 and 0.61, respectively, while r² was 0.674. We demonstrate that the predictive r² based on the mean activity (Y_m) of the training set is misleading, while the test set Y_m-based predictive r² index gives a more accurate estimate of external predictivity. Using CoMFA, the observed differences in aromatase inhibition among C6-substituted steroids are rationalized at the atomic level. The CoMFA fields are consistent with known, potent inhibitors of aromatase, not included in the model. When positioned in the same alignment, these compounds have distinct features that overlap with the steric and electrostatic fields obtained in the CoMFA model. The presence of two hydrophobic binding pockets near the aromatase active site is discussed: a steric bulk tolerant one, common for C4, C6-alpha and C7-alpha substitutents, and a smaller one at the C6-beta region.     

CBP/P300溴结构域联芳基类抑制剂三维定量构效关系研究

CREB结合蛋白(CBP)和与其高度同源的P300蛋白是组蛋白乙酰化酶的两个亚型,两者通过它们的溴结构域(bromodomain,BRD)与染色质结合,目前,CBP/P300已经成为人类在肿瘤靶点领域中的研究热点。本研究基于CBP/P300溴结构域联芳基类抑制剂建立三维定量构效关系,采用比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(Co MSIA)分别建立35个已知活性抑制剂的3D-QSAR模型,以确定CBP/P300溴结构域联芳基类抑制剂分子结构与生物活性之间的定量关系。Co MFA和Co MSIA模型活性数据p IC50的预测值与实验值基本一致,说明这两个模型具有较高的预测能力和统计学意义。根据Co MFA和Co MSIA模型所提供的立体场、静电场、疏水场、氢键给体场、氢键供体场等信息提出了改善此类抑制剂活性的药物设计思路,为指导设计具有更高活性的新分子和预测更加有效的CBP/P300溴结构域抑制剂提供理论依据。     

Molecular Modeling and Design of Arylthioindole Derivatives as Tubulin Inhibitors

Three-dimensional quantitative structure activity relationship （3D-QSAR） and docking studies of a series of arylthioindole derivatives as tubulin inhibitors against human breast cancer cell line MCF-7 have been carried out. An optimal 3D-QSAR model from the comparative molecular field analysis （CoMFA） for training set with significant statistical quality （R2=0.898） and predictive ability （q2=0.654） was established. The same model was further applied to predict pIC50 values of the compounds in test set, and the resulting predictive correlation coefficient R2（pred） reaches 0.816, further showing that this CoMFA model has high predictive ability. Moreover, the appropriate binding orientations and conformations of these compounds interacting with tubulin are located by docking study, and it is very interesting to find the consistency between the CoMFA field distribution and the 3D topology structure of active site of tubulin. Based on CoMFA along with docking results, some important factors improving the activities of these compounds were discussed in detail and were summarized as follows： the substituents R3-R5 （on the phenyl ring） with higher electronegativity, the substituent R6 with higher eleetropositivity and bigger bulk, the substituent R7 with smaller bulk, and so on. In addition, five new compounds with higher activities have been designed. Such results can offer useful theoretical references for experimental works.     

Design of inhibitors of the MurF enzyme of Streptococcus pneumoniae using docking, 3D-QSAR, and de Novo design

The biosynthetic pathway for formation of the bacterial cell wall (peptidoglycan) presents an attractive target for intervention. This is exploited by many of the clinically useful antibiotics, which inhibit enzymes involved in the later stages of peptidoglycan synthesis. MurF is one of the four amide bond-forming enzymes (d-alanyl-d-alanine ligating enzyme) that catalyzes the ATP-dependent formation of UDP-MurNAc-tripeptide. In the present study, several MurF inhibitors were docked into the active site of MurF to explore their binding modes and also to gain an insight into the crucial ligand-receptor interactions at the molecular level. The final selection of the "bioactive" conformation of every ligand was influenced by consensus scoring in which various independent scoring functions such as GoldScore, ChemScore, HINT score and X-CScore were employed. Subsequently, 3D-QSAR studies using comparative molecular field analysis (CoMFA) and the new approach comparative residue interaction analysis (CoRIA) have been carried out on the enzyme-inhibitor complexes obtained by docking and postscoring analysis. Finally, new inhibitors have been designed using the de novo approach of Ludi, and the activities of the most promising hits have been predicted with the CoMFA and CoRIA models.     

Discodermolide及其衍生物三维定量构效关系的研究

Discodermolide是一种新颖的作用于微管蛋白的抗肿瘤化合物, 具有良好的药用前景. 为了设计出药效更好的类似物, 我们用比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)对discodermolide及其衍生物进行了三维定量构效关系(3D-QSAR)的研究, 并建立了相关的预测模型. 其中, CoMFA模型的交叉验证相关系数(q2)为0.592, 非交叉验证相关系数(r2)为0.982, 标准偏差(SEE)为0.094, F值为119.761; CoMSIA模型的q2为0.544, r2为0.980, SEE为0.098, F值为108.715. 计算结果表明, 获得的CoMFA和CoMSIA模型具有良好的预测能力, 可以应用于指导该类化合物的设计.