A novel approach toward the prediction of the glass transition temperature: Application of the EVM model,a designer QSPR equation for the prediction of acrylate and methacrylate polymers

We describe an original QSPR model called the EVM model (Energy, Volume, Mass) to calculate the glass transition temperature (T_g) of aliphatic acrylate and methacrylate homopolymers using classical molecular mechanics and dynamics. The latter was used to calculate an energy density function related to the cylindrical volume of a 20 monomer unit polymer segment (TSSV, Total Space around a Standard deviation Volume). We then calculated the T_g as a function of this density function and the repeat unit molecular weight, although no interchain interactions were taken into account. For linear and branched aliphatic acrylate and methacrylate polymers, the standard deviation from linear regression was 12 K, and the r² was 0.96. The model allows calculation of the T_g with an average absolute error of error of 10% for linear and branched derivatives not included in the original linear regression analysis. The results obtained with the EVM model are compared with those obtained with Bicerano's model. © 1997 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 35: 2579–2590, 1997     

Calculations of Hyperpolarizabilities for Para-disubstituted Benzenes with the QSPR

A quantitative structure-property relationship (QSPR) was made for the prediction of the hyperpolarizabilities(β) ofpara-disubstituted benzenes with the nonlinear optical properties, and the βcal2 calculated by this model accorded better with the experimental values (βexpt) compared with theβcal1 calculated at the CPHF/6-31G*//HF/STO-3G level of theory, especially whenβ was big.     

Viscoelastic properties of fibrinogen adsorbed to the surface of biomaterials used in blood-contacting medical devices

The hemocompatibility of polymeric vascular implants is in part dependent on the propensity of fibrinogen to adsorb to the implant surface. Fibrinogen surface adsorption was measured in real time using a quartz crystal microbalance with dissipation monitoring (QCM-D). Six new, biodegradable tyrosine-derived polycarbonates were used as test surfaces. Stainless steel, poly(L-lactic acid), poly(D,L-lactide-co-glycolide), and poly(ethylene terephthalate) surfaces served as controls and provided a comparison of the test surfaces with those of commonly used biomaterials. Our study addressed the question regarding to which extent systematic variations in polymer structure can be used to optimize X-ray visibility and provide tunable degradation rates while generating protein-repellant surface properties that minimize fibrinogen adsorption. QCM-D revealed surface-dependent changes in fibrinogen layer thickness (2 to 37 nm), adsorbed wet mass (0.2 to 4.3 microg/cm2), and viscosity (0.001 to 0.005 kg/ms). While we did not find an overall correlation between surface air-water contact angle measurements and fibrinogen adsorption (R2 = 0.08), our data demonstrate that gradually increasing the poly(ethylene glycol) content within a subgroup of polymers having the same polymer backbone will lead to decreased fibrinogen adsorption. Within this subgroup of polymers, there was a strong correlation between decreasing air-water contact angles and decreasing fibrinogen adsorption (R2 = 0.95). We conclude that it is possible to minimize fibrinogen adsorption to tyrosine-derived polycarbonates while optimizing X-ray visibility and degradation rates. Some of the tyrosine-derived polycarbonates were identified as useful materials for the design of blood-contacting implants on the basis of their substantially lower levels of fibrinogen adsorption relative to the commonly used controls.     

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

The half-wave potential (E_1/2) is an important electrochemical property of organic compounds. In this work, a quantitative structure-property relationship (QSPR) analysis has been conducted on the half-wave reduction potential (E_1/2) of 40 substituted benzoxazines by means of both a heuristic method (HM) and a non-linear radial basis function neural network (RBFNN) modeling method. The statistical parameters provided by the HM model (R² =0.946; F=152.576; RMSCV=0.0141) and the RBFNN model (R²=0.982; F=1034.171 and RMS =0.0209) indicated satisfactory stability and predictive ability. The obtained models showed that benzoxazines with larger Min valency of a S atom (MVSA), lower Relative number of H atom (RNHA) and Min n-n repulsion for a C-H bond (MnnRCHB) and Minimal Electrophilic Reactivity Index for a C atom (MERICA) can be more easily reduced. This QSPR approach can contribute to a better understanding of structural factors of the organic compounds that contribute to the E_1/2, and can be useful in predicting the E_1/2 of other compounds.      

A Novel Lu Index to QSPR Studies of Aldehydes and Ketones

A novel index based on the hyper-Wiener index, named Lu, was proposed. The relative bond length between two adjacent vertices in a molecular graph was taken into account in the definition of the Lu index. The usefulness of the new index in QSPR study was verified by its correlation with a number of organic compounds including aliphatic aldehydes and ketones. For each of the physical properties (the normal boiling points, molar refractions and gas heat capacities at 25°C), high quality QSPR models were obtained. The final models were validated to be statistically reliable using the leave-one-out cross validation and/or an external test set. The correlation coefficients (> 0.99) of all constructed models indicate the necessity of such an index, and show the potential of the Lu index for QSAR/QSPR studies.     

VoteDock: Consensus docking method for prediction of protein–ligand interactions

Molecular recognition plays a fundamental role in all biological processes, and that is why great efforts have been made to understand and predict protein–ligand interactions. Finding a molecule that can potentially bind to a target protein is particularly essential in drug discovery and still remains an expensive and time‐consuming task. In silico, tools are frequently used to screen molecular libraries to identify new lead compounds, and if protein structure is known, various protein–ligand docking programs can be used. The aim of docking procedure is to predict correct poses of ligand in the binding site of the protein as well as to score them according to the strength of interaction in a reasonable time frame. The purpose of our studies was to present the novel consensus approach to predict both protein–ligand complex structure and its corresponding binding affinity. Our method used as the input the results from seven docking programs (Surflex, LigandFit, Glide, GOLD, FlexX, eHiTS, and AutoDock) that are widely used for docking of ligands. We evaluated it on the extensive benchmark dataset of 1300 protein–ligands pairs from refined PDBbind database for which the structural and affinity data was available. We compared independently its ability of proper scoring and posing to the previously proposed methods. In most cases, our method is able to dock properly approximately 20% of pairs more than docking methods on average, and over 10% of pairs more than the best single program. The RMSD value of the predicted complex conformation versus its native one is reduced by a factor of 0.5 Å. Finally, we were able to increase the Pearson correlation of the predicted binding affinity in comparison with the experimental value up to 0.5. © 2010 Wiley Periodicals, Inc. J Comput Chem 32: 568–581, 2011     

拓扑化学行为及其对镧系元素和锕系元素的QSPR应用

提出拓扑化学行为概念,把对化合物性质最具影响力的因素归纳为拓扑生长力和拓扑阻滞力。根据该原理,利用价电子轨道能量对价电子距离矩阵进行修正。研究表明OET(轨道能量拓扑指数)对镧系元素和锕系元素的物理化学性质具有良好的应用，尤其是对尚未借助QSPR(定量结构性质关系)手段进行研究的光谱性质。LOO CV(留一法交叉检验)的结果验证了模型的良好稳定性和预测能力,采用的检验参数有：PRESS/SSY，SEP_CV，R_CV，S_PRESS 和PSE，其中PRESS/SSY比值介于0.000 6和0.114 8之间。与文献进行比较,本文方法所得结果与之接近或更好。研究显示正是基于拓扑化学行为才有本文方法良好和较广的应用。     

Analysis and prediction of protein folding rates using quadratic response surface models

Understanding the relationship between amino acid sequences and folding rates of proteins is an important task in computational and molecular biology. In this work, we have systematically analyzed the composition of amino acid residues for proteins with different ranges of folding rates. We observed that the polar residues, Asn, Gln, Ser, and Lys, are dominant in fast folding proteins whereas the hydrophobic residues, Ala, Cys, Gly, and Leu, prefer to be in slow folding proteins. Further, we have developed a method based on quadratic response surface models for predicting the folding rates of 77 two- and three-state proteins. Our method showed a correlation of 0.90 between experimental and predicted protein folding rates using leave-one-out cross-validation method. The classification of proteins based on structural class improved the correlation to 0.98 and it is 0.99, 0.98, and 0.96, respectively, for all-alpha, all-beta, and mixed class proteins. In addition, we have utilized Baysean classification theory for discriminating two- and three-state proteins, which showed an accuracy of 90%. We have developed a web server for predicting protein folding rates and it is available at http://bioinformatics.myweb.hinet.net/foldrate.htm.     

QSPR studies on the photoinduced-fluorescence behaviour of pharmaceuticals and pesticides

Fluorimetric analysis is still a growing line of research in the determination of a wide range of organic compounds, including pharmaceuticals and pesticides, which makes necessary the development of new strategies aimed at improving the performance of fluorescence determinations as well as the sensitivity and, especially, the selectivity of the newly developed analytical methods. In this paper are presented applications of a useful and growing tool suitable for fostering and improving research in the analytical field. Experimental screening, molecular connectivity and discriminant analysis are applied to organic compounds to predict their fluorescent behaviour after their photodegradation by UV irradiation in a continuous flow manifold (multicommutation flow assembly). The screening was based on online fluorimetric measurement and comprised pre-selected compounds with different molecular structures (pharmaceuticals and some pesticides with known ‘native’ fluorescent behaviour) to study their changes in fluorescent behaviour after UV irradiation. Theoretical predictions agree with the results from the experimental screening and could be used to develop selective analytical methods, as well as helping to reduce the need for expensive, time-consuming and trial-and-error screening procedures.