Electrostatic and hydrophobic fields

Moreover, a final 3D-QSAR model vahdation was done using a prospective study with an external test set. The 82 compounds from the data set were used in a lead optimization project. A CoMFA model gave an (cross validated) value of 0.698 for four relevant PLS components and a conventional of 0.938 were obtained for those 82 compounds. The steric descriptors contributed 54% to the total variance, whereas the electrostatic field explained 46%. The CoMSIA model led to an (cross vahdated) value of 0.660 for five PLS components and a conventional of 0.933. The contributions for steric, electrostatic, and hydrophobic fields were 25, 44, and 31%. As a result, it was proved that the basic S4-directed substituents should be replaced against more hydrophobic building blocks to improve pharmacokinetic properties. The structural and chemical interpretation of CoMFA and CoMSIA contour maps directly pointed to those regions in the Factor Xa binding site, where steric, electronic, or hydrophobic effects play a dominant role in ligand-receptor interactions. 

From the studies above, it was shown that the use of 3D-QSAR models led to the identification of binding site regions, where steric, electronic, or hydrophobic effects played a dominant role. Although cationic interactions in both SI and S4 subsites were favorable for in vitro affinity, they might be detrimental for oral bio availability. Thus, the CoMFA steric field contribution could be seen as a balance between pure steric plus hydrophobic effects. The contributions for steric, electrostatic and hydrophobic fields from the CoM-SIA studies were 25, 44, and 31%, respectively. 

A comparative molecular analysis study based on three-dimensional quantum structure-activity relationships was performed by Pajeva and Wiese [159] on 40 phenothiazines and structurally related drugs to predict their MDR modification. More than 350 theoretical models were derived and evaluated using steric, electrostatic and hydrophobic fields alone and in combination. All examined fields were found to contribute to MDR reversing activity, and their hydrophobic fields improved the correlative and predictive power of the models in all cases. The results point out the role of hydropho-bicity as a space-directed molecular property to explain the differences in anti-MDR activity of the drugs under study. 

Molecules are characterized by potential hydrogen bonding, polar, hydrophobic, and electrostatic interactions in 3D space, using 3D molecular fields. Techniques such as Comparative Molecular Field Analysis (CoMFA), which considers the 3D distribution of electrostatic and steric fields, have been applied to congeneric series of enzyme substrates or inhibitors generating 3D QSAR equations. Most examples of such applications are to modeling CYP substrate and inhibitor specificity and these have been extensively reviewed in the literature (Ekins et al., 2000 2001 Ter Laak and Vermeulen, 2001 Ter Laak et al., 2002). 

Mean-field hydrophobic interactions will be briefly presented as well. Finally, implementation of the mean-field electrostatic and hydrophobic potentials to an effective MD approach will be also presented. 

Field-based descriptors The previous indices are mostly atom-based, and although they have proven useful to chemists, more and more work has been done and is currently being done on so-called field-based descriptors. Examples of some fields are the electron density, steric fields, electrostatic potentials, and hydrophobic fields. This definition is the proper starting point for the discussion of quantum similarity, because the electron density plays an important role in these fields as we will discuss extensively. This class of field-based descriptors also is used in 3-D QSAR. 4... 

The model of the first step is well established in electrochemistry, which we briefly describe later in this book. Osada and co-workers extensively studied the second step in detail [172, 129, 173]. Both electrostatic and hydrophobic interactions were assumed in the adsorption process. These models did not take an account of the electric fields and volume change for simplicity. 

CoMSIA (in Ref. [25]—CoMSIA2) models are based on electrostatic and steric fields molecular fields and also involve contributions from the hydrophobic and two hydrogen-bonding molecular fields. All CMF models are based on the use of all afore-mentioned five types of molecular fields. All CoMFA and CoMSIA models were obtained by using a lattice with 2 A spacing expanding at least 4 A in each direction beyond aligned molecules. Only the most predictive CoMFA and CoMSIA models are included in the Table 13.3. 

As noted above, the rapidly changing steric fields near the van der Waais radius of an atom constitute one apparent problem in CoMFA the singularities and rapidly changing electrostatic fields near atomic nuclei present another and the ambiguities associated with the scaling of two different CoMFA fields in the PLS analysis pose a third. CoMSIA was devised to overcome these difficulties by using similarities between a probe atom (placed at each lattice position) and the molecules rather than CoMFA fields. Steric, electrostatic, and hydrophobic similarities are calculated as in the SEAL approach to molecular superposition. ... 

The mapping of properties to surface features in SPERM can be regarded as a limiting case of the last class of local similarity measures to be discussed here, these being measures that are based upon electrostatic, steric, and hydrophobic fields analogous to those that underlie current approaches to 3D QSAR (see Comparative Molecular Field Analysis (CoMFA) and Quantitative Structure-Activity Relationships in Drug Design). 

Figure 3 Serotoninergic neare.st neighbors retrieved in a similarity search using electrostatic, steric, and hydrophobic fields...

The CoMSIA analysis using steric, electrostatic, and lipophilic fields as descriptors gave a model with (f of 0.873 and of 0.954. The CoMSIA steric, electrostatic, and lipophilic fields explained the variance of 8.8, 40.9 and 50.2 %, respectively. This indicated that the hydrophobic interaction was a major factor to explain the field properties of the alkylphosphonates lo. Further attempts to combine the hydrogen bond fields with the standard steric, electrostatic, and lipophilic fields did not lead to any significant improvement = 0.869, = 0.952). Indeed,... 

The stereoelectronic features produce actions at a distance by the agency of the recognition forces they create. These forces are the hydrophobic effect, and the capacity to enter ionic bonds, van der Waals interactions and H-bonding interactions. The most convenient and informative assessment of such recognition forces is afforded by computahon in the form of MIFs, e.g. lipophilicity fields, hydrophobicity fields, molecular electrostatic potentials (MEPs) and H-bonding fields (see Chapter 6) [7-10]. 

The interaction of drug molecules with biological membranes is a three-dimensional (3D) recognition that is mediated by surface properties such as shape, Van der Waals forces, electrostatics, hydrogen bonding, and hydrophobicity. Therefore, the GRID force field [5-7], which is able to calculate energetically favorable interaction sites around a molecule, was selected to produce 3D molecular interaction fields. 

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