2DQSPR approach towards the lipophilicity of n-arylhydroxamic acids: A key role of steric and hydrogen bond factors using PLS method

Introduction

The logarithmic n-octanol/water partition coefficient (logP O/W ) is widely used to represent molecular lipophilicity. A lipophilicity parameter is a useful tool in the field of quantitative structure-activity relationships (QSARs) for several biological effects, because lipophilicity affects absorption, transmembrane transport, bioavilability hydrophobic drug receptor interaction, metabolism, pharmacological activity as well as toxicity of molecule [1,2] Lipophilicity of chemicals is important both for predicting pharmacokinetics and pharmcodynamics of drugs and toxicants [3] . LogP O/W is also an important parameter in studying their environmental fate, e.g. bioaccumulation in fish or absorption on soil and sediments. Therefore, accurate logP O/W values are important for the prediction of biological or environmental properties of compound. The hydroxamic acid functional group, -C(=O) N⋅ROH, is a key structural constitutent of many biomolecules, some of which are naturally occurring [4] and others, such as the peroxidose, matrix metalloproteinase and urease inhibitors [5,6] are of synthetic origin. Hydroxamic acids represent a wide spectrum of bioactive compounds that have hypotensive [7] , anticancer [8][9][10][11][12] , antitumor [13][14][15] , antimalarial [16][17][18][19][20] , antituberculosis and antifungal as key functional of potential chemotherapeutics targeting cardiovascular, HIV and Alzheimer's diseases [21,22] . Quantitative structure-property relationship (QSPR) has been demonstrated to be an effective computational tool in understanding the interrelation between the structure of molecule and their properties [23][24][25][26] . Therefore, the objective of the present investigation to develop QSPR model for logP O/W of the hydroxamic acidsbased on molecular descriptors by partial least square (PLS) regression. The commonly available compute programmes: XLOGP, KowWin, CLOGP, ALOGPS and MilogP were used to estimate the logP data for hydroxamic acids. The results obtained are computed with experimental logP O/W of hydroxamic acids.

Materials and Methods

Materials

The experimental results of the logarithmic n-octanol/water partition coefficient (logP O/W ) of hydroxamic acids are taken from literature [27,28] and are summarized in (Table 1).

Lipophilicity calculations

A number of different computer programmes have been recently developed for the estimation of lipophilocity of compounds based on their structure. In the study, five commonly available computer programmes based on different calculation methods for computing logP have been compared. The validity of these programmes was evaluated by how well the calculated log P values agreed with this experimentally determined logPO/W values for hydroxamic acids.

The SMILES (Simplified Molecular Input Line Entry System) notation created by the structure drawing programs Cambridge softs chemdraw pro was used as chemical structure for all programs commonly available computer programs were used to estimate logP O/W of Hydroxamic Acids are as XLOGP (based on atom contribution) [29] , KowWin (based on atom/fragment contribution) [30] and CLOGP (based on fragmental contributions) [31], ALOGPS2.2 (based on atom type electrotopological state, indices and neutral networking modeling [32][33][34][35] , and MilogP (based on group contribution) [36] . LogP data obtained with five software packages will listed in Table 1.

Molecular modeling

The PM6 Hamiltonian method of MOPAC 2009 contained in the Ampac software version 9 [37] was used to compute semiemperical quantum chemical descriptors. Bio-Loom program of Biobyte co-operation [38] was used to compute excess molar refraction, XRM. The data are listed on Table 2.

Results and Discussion

Correlation between experimental logo/w and computated log P values

The correlation between the log Po/w and obtained by computation were summaries in Table 2. The experimentally determined log P O/W values correlate with the lipophilicity data (logP) computed using software XLOGP (r 2 =0.4190), KowWin (r 2 =0.5563), CLOGP (r 2 =0.5688), ALOGPS (r 2 =0.4022) and MilogP (r 2 =0.5202).

The cross-validation (q 2 ) value of experimental logP versus computational logP are shown in figure show that the programs used in present study did not give reasonable data for this set of compound (q 2 ≤0.5)

PLS analysis

In a PLS model, variable importance in the projection (VIP) is a parameter that shows that the importance of variable.

According to the manual of simca-p (version 11), VIP is the sum and all model dimensions of the contribution of variable influences (VIN) given PLS dimension (a) and a given x term (k), VIN 2 is computed form the squared PLS weight of that x term multiplied by the parent explained the sum of squares (SS) by that PLS dimension. VIP value is calculated from the accumulated value and all PLS dimension, divide by the total percent explained SS by the PLS,

Model and multiplied by the number of terms in the model.

The terms with values of VIP are the most relvant for explaining depended variable.

To obtain an optimal model the following PLS analysis procedure are adopted. At first, a PLS model with all the predictor variables was calculated. Then the variable with the lowest VIP value was eliminated and a new PLS regression was performed, leading to a new PLS model. This procedure was repeated till only main predictor variables were recommended the optimal PLS model was selected with respected to the statistics Q 2 cum , the root mean square error of calibration (RMSEC) and the root mean square of prediction (RMSEP). PLS analysis was initially applied to the complete data set of 15 compounds and 9 descriptors. The preliminary analysis yielded a model which accounts for 93.6% of the variation in logP O/W (r 2 =0.936) at a predictability level of 73.0% (q 2 =0.730). It was improved by removing that parameters which did not make significant contributions to logP O/W (E HOMO , E LUMO and Dm ) .

Analytical QSPR equation thus obtained is as follow, logP O/W = 3.160x10 -1 (Vx) + 3.140 x 10 -1 (α) + 2.890x10 -1 (β) + 3.132 x10 -1 (I Cl ) + 2.531 x 10 In model I, six predictor variables involved which are condensed into two PLS components. The VIP values of Vx, α and β are larger than 1, indicating that these three descriptors are more significant than I Cl , E HOMO -E LUMO and XMR. 6 and Table 7, respectively.

Acknowledgement

Authors are thankful to molinspiration.com, semichem.com and Bio-Loom program, trail version by BioByte Cooperation, USA for the free evaluation softwares.

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