基于原子表面的蛋白质水合自由能预测模型

提出了一种计算蛋白质水合自由能的简化模型（SAWSA 2）.模型把蛋白质分子中的原子分为20种不同的原子类型,通过每类原子的溶剂可及化表面以及相应的溶剂化参数,就可以得到分子的水合自由能.不同原子类型的溶剂化参数通过110个蛋白质分子水合自由能拟合得到,水合自由能的标准值采用了基于求解Possion-Boltzmann方程（PB）以及分子表面计算（SA） 相结合的方法.采用得到的模型,预测了20个蛋白质分子的水合自由能,预测值的相对值和绝对值都能和PB/SA的计算值很好地吻合,大大优于两种已报导的水合自由能模型.     

基于分子表面的水化自由能预测方法

报导了一种基于加权原子表面的水合自由能预测（SAWSA）.对于不同原子类型的溶剂化参数，其参数化分为三个步骤：首先用SMARTS 语言确定不同的原子类型；然后计算每个原子的溶剂可及化表面；最后用遗传算法来优化不同原子类型的溶剂化参数.采用该模型，计算了18个蛋白质分子的水合自由能，预测结果和PB/SA的计算结果呈现了很好的线性关系（r=0.99).计算表明，SAWSA模型对有机小分子和生物大分子都具有很好的预测能力.     

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。     

基元通量模式预测酵母生长现象

本文通过EFM预测了基因突变后的酵母细胞生长现象, 模拟预测结果和实验结果吻合很好; 与FBA方法得到的模拟结果相比较, EFM方法能更好地把基因突变和其表型(生长)联系起来.     

14种结合自由能评价函数的比较

采用LigandFit作为构象采样工具，以230个蛋白质-配体复合物组成的预测集，系统地比较了14种自由能评价函数（Ligscore1、Ligscore2、Plp1、Plp2、Jain、Pmf、Ludi1、Ludi2、Ludi3、D-score、Pmf-score、G-score、Chemscore以及Xscore）对蛋白质和小分子之间的结合模式以及结合自由能的预测能力. Plp1、Plp2、G-score、Pmf和Xscore在预测测试集结合自由能时得到的分数同实验测定的结合自由能的线性相关系数大于50%. 在识别配体分子实验结合构象的能力方面， 选择测试构象与实际构象间的位置均方根偏差rmsd≤0.20 nm作为评价标准，14种评价函数的成功率从46%到77%不等，其中Ligscore1、Ligscore2、Plp1、Plp2以及Xscore的成功率都在70%以上. 将评价函数中的2个或者3个组合得到一组共同评价函数可以进一步提高实验构象的预测能力， 其预测成功率可以达到80%. 实验表明Xscore、Plp1和Plp2在对接和评价方面都得到较好的结果.     

聚合物溶液体系玻璃化转变温度与组成之间的关系

大量的文献报道了聚合物溶液体系中聚合物玻璃化转变温度(Tg)与组成之间的关系,这些理论公式大多是基于经典热力学理论,自由体积等理论得到的,这些结果在一些聚合物溶液体系中与实验结果是符合的.在一些聚合物-溶剂体系中,Tg与组成的关系之间出现了反常的"cusp"点,两个玻璃化温度等现象,部分理论值与预测值出现较大偏差,可以用自由体积理论和自聚集理论加以定性的解释.但是依然缺乏普遍的理论来解释和预测上面现象的发生,需要进一步完善和发展聚合物溶液体系中玻璃化转变温度与组成之间的关系.     

脂肪酸多聚甘油酯分子结构与性能相关性研究

采用量子化学MM+和AM1方法计算聚甘油和脂肪酸多聚甘油酯的分子结构参数,然后用逐步线性回归方法建立脂肪酸多聚甘油酯HLB值的定量结构性质(QSPR)模型,所得的预测模型中包含四个参数(单位质量分子所含氧原子数Xo、生成热ΔfHm、电子能Ee和水合能Eh),预测值及外部检验的复相关系数(R2)和标准偏差(SD)分别为0.9553、0.73722和0.9678、6.34426。结果表明,量子化学方法计算简单,对脂肪酸多聚甘油酯结构的表征能力较强,所建QSPR模型具有能较好的预测能力和较强的稳健性,并在一定程度上阐明了脂肪酸多聚甘油酯分子结构与性能之间的关系。     

GABA受体抑制剂的柔性原子受体模型研究

利用Flarm软件为GABA受体抑制剂建立了其抑制家蝇和大鼠GABA受体的柔性原子受体模型， 很好地模拟了两种受体与药物分子结合的情况，具有较好的预测能力，预测集的预测值与实验值的相关系数（r2）分别达到0.923和0.733，模型的结果与药效团模型有很大的一致性，为揭示药物与两种受体作用的区别提供了依据.     

量子化学参数对氯代苯理化生物活（毒）性的研究

采用Chemoffice 8.0中的MOPAC-AM1算法对12个氯代苯分子和苯的9种量子化学参数进行计算,并将计算得到的结构参数作为描述符引入定量结构-活性相关(QSAR)研究,运用多元逐步回归法建立了氯代苯的5种理化生物活(毒) 性与量化参数的多元回归方程, 相关系数均大于0.98 , 其计算值与试验值较吻合; 同时对部分无实验数据的氯代苯进行预测.     

乙苯裂解机理和超临界压力下的动力学模拟

基于乙苯燃烧机理的去氧处理获得的乙苯裂解机理, 采用QRRK/MSC算法代码对小分子产物的高压裂解相关参数进行改进, 构建了高压条件下乙苯裂解的136个物种及626步反应的机理. 在超临界压力和高温条件下的动力学模拟表明, 乙苯裂解机理的气相分子产率和转化率的模拟结果与实验结果相吻合. 采用敏感度分析对机理的控速步骤进行验证, 考察了机理中的关键反应, 结果表明本机理能较好地预测高压实验结果, 可应用于超临界裂解换热的计算模拟.     

Improving the performance of the coupled reference interaction site model-hyper-netted chain (RISM-HNC)/simulation method for free energy of solvation

The coupled reference interaction site model-hyper-netted chain (RISM-HNC)/ simulation methodology determines solvation free energies as a function of the set of all radial distribution functions of solvent atoms about atomic solute sites. These functions are determined from molecular dynamics (MD) or Monte Carlo (MC) simulations rather than from solving the RISM and HNC equations iteratively. Previous applications of the method showed that it can predict relative free energies of solvation for small solutes accurately. However, the errors scale with the system size. In this study, we propose the use of the hard-sphere free energy as the reference and a linear response approximation to improve the performance, i.e., accuracy and robustness, of the method, particularly removing the size dependency of the error. The details of the new formalism are presented. To validate the proposed formalism, solvation free energies of N-methylacetamide and methylamine are computed using the new RISM-HNC-based expressions in addition to a linear response expression, which are compared to previous thermodynamic integration and thermodynamic perturbation results performed with the same force field. Additionally, free energies of solvation for cyclohexane, pyridine, benzene and derivatives, and other small organic molecules are calculated and compared to experimental values.     

Hybrid Solvation Model with First Solvation Shell for Calculation of Solvation Free Energy

We present a hybrid solvation model with first solvation shell to calculate solvation free energies. This hybrid model combines the quantum mechanics and molecular mechanics methods with the analytical expression based on the Born solvation model to calculate solvation free energies. Based on calculated free energies of solvation and reaction profiles in gas phase, we set up a unified scheme to predict reaction profiles in solution. The predicted solvation free energies and reaction barriers are compared with experimental results for twenty bimolecular nucleophilic substitution reactions. These comparisons show that our hybrid solvation model can predict reliable solvation free energies and reaction barriers for chemical reactions of small molecules in aqueous solution.     

Prediction of molecular solvation free energy based on the optimization of atomic solvation parameters with genetic algorithm

We propose an improved solvent contact model to estimate the solvation free energy of an organic molecule from individual atomic contributions. The modification of the solvation model involves the optimization of three kinds of parameters in the solvation free energy function: atomic fragmental volume, maximum atomic occupancy, and atomic solvation parameters. All of these atomic parameters for 24 atom types are developed by the operation of a standard genetic algorithm in such a way as to minimize the difference between experimental and calculated solvation free energies. The data set for experimental solvation free energies is divided into a training set of 131 compounds and a test set of 24 compounds. Linear regressions with the optimized atomic parameters yield fits with the squared correlation coefficients (r2) of 0.89 and 0.86 for the training set and for the test set, respectively. Overall, the results indicate that the improved solvent contact model with the newly developed atomic parameters would be a useful tool for rapid calculation of molecular solvation free energies in aqueous solution.     

Calculation of the solvation free energy of neutral and ionic molecules in diverse solvents

The solvation free energy density (SFED) model was modified to extend its applicability and predictability. The parametrization process was performed with a large, diverse set of solvation free energies that included highly polar and ionic molecules. The mean absolute error for 1200 solvation free energies of the 379 neutral molecules in 9 organic solvents and water was 0.40 kcal/mol, and for 90 hydration free energies of ions was 1.7 kcal/mol. Overall, the calculated solvation free energies of a wide range of solute functional groups in diverse solvents were consistent with experimental data.     

Free energy of solvation from molecular dynamics simulation applying Voronoi-Delaunay triangulation to the cavity creation

The free energy of solvation for a large number of representative solutes in various solvents has been calculated from the polarizable continuum model coupled to molecular dynamics computer simulation. A new algorithm based on the Voronoi-Delaunay triangulation of atom-atom contact points between the solute and the solvent molecules is presented for the estimation of the solvent-accessible surface surrounding the solute. The volume of the inscribed cavity is used to rescale the cavitational contribution to the solvation free energy for each atom of the solute atom within scaled particle theory. The computation of the electrostatic free energy of solvation is performed using the Voronoi-Delaunay surface around the solute as the boundary for the polarizable continuum model. Additional short-range contributions to the solvation free energy are included directly from the solute-solvent force field for the van der Waals-type interactions. Calculated solvation free energies for neutral molecules dissolved in benzene, water, CCl4, and octanol are compared with experimental data. We found an excellent correlation between the experimental and computed free energies of solvation for all the solvents. In addition, the employed algorithm for the cavity creation by Voronoi-Delaunay triangulation is compared with the GEPOL algorithm and is shown to predict more accurate free energies of solvation, especially in solvents composed by molecules with nonspherical molecular shapes.     

The treatment of solvation by a generalized Born model and a self-consistent charge-density functional theory-based tight-binding method

We present a model to calculate the free energies of solvation of small organic compounds as well as large biomolecules. This model is based on a generalized Born (GB) model and a self-consistent charge-density functional theory-based tight-binding (SCC-DFTB) method with the nonelectrostatic contributions to the free energy of solvation modeled in terms of solvent-accessible surface areas (SA). The parametrization of the SCC-DFTB/GBSA model has been based on 60 neutral and six ionic molecules composed of H, C, N, O, and S, and spanning a wide range of chemical groups. Effective atomic radii as parameters have been obtained through Monte Carlo Simulated Annealing optimization in the parameter space to minimize the differences between the calculated and experimental free energies of solvation. The standard error in the free energies of solvation calculated by the final model is 1.11 kcal mol(-1). We also calculated the free energies of solvation for these molecules using a conductor-like screening model (COSMO) in combination with different levels of theory (AM1, SCC-DFTB, and B3LYP/6-31G*) and compared the results with SCC-DFTB/GBSA. To assess the efficiency of our model for large biomolecules, we calculated the free energy of solvation for a HIV protease-inhibitor complex containing 3,204 atoms using the SCC-DFTB/GBSA and the SCC-DFTB/COSMO models, separately. The computed relative free energies of solvation are comparable, while the SCC-DFTB/GBSA model is three to four times more efficient, in terms of computational cost.     

Extended solvent-contact model approach to SAMPL4 blind prediction challenge for hydration free energies

Extended solvent-contact model was applied to the blind prediction of the hydration free energies of 47 organic molecules included in the SAMPL4 data set. To obtain a suitable prediction tool, we constructed a hydration free energy function involving three kinds of atomic parameters. With respect to total 34 atom types introduced to describe all SAMPL4 molecules, 102 atomic parameters were defined and optimized with a standard genetic algorithm in such a way to minimize the difference between the experimental hydration free energies and those calculated with the hydration free energy function. In this parameterization, we used a training set comprising 77 organic molecules with varying sizes and shapes. The estimated hydration free energies for the SAMPL4 molecules compared reasonably well with the experimental results with the associated squared correlation coefficient and root mean square deviation of 0.89 and 1.46 kcal/mol, respectively. Based on the comparative analysis of experimental and computational hydration free energies of the SAMPL4 molecules, the methods for further improvement of the present hydration model are suggested.     

New approach to free energy of solvation applying continuum models to molecular dynamics simulation

A new approach to the calculation of the free energy of solvation from trajectories obtained by molecular dynamics simulation is presented. The free energy of solvation is computed as the sum of three contributions originated at the cavitation of the solute by the solvent, the solute-solvent nonpolar (repulsion and dispersion) interactions, and the electrostatic solvation of the solute. The electrostatic term is calculated based on ideas developed for the broadly used continuum models, the cavitational contribution from the excluded volume by the Claverie-Pierotti model, and the Van der Waals term directly from the molecular dynamics simulation. The proposed model is tested for diluted aqueous solutions of simple molecules containing a variety of chemically important functions: methanol, methylamine, water, methanethiol, and dichloromethane. These solutions were treated by molecular dynamics simulations using SPC/E water and the OPLS force field for the organic molecules. Obtained free energies of solvation are in very good agreement with experimental data.