Molecular descriptors polar surface area

The MEP at the molecular surface has been used for many QSAR and QSPR applications. Quantum mechanically calculated MEPs are more detailed and accurate at the important areas of the surface than those derived from net atomic charges and are therefore usually preferable [Ij. However, any of the techniques based on MEPs calculated from net atomic charges can be used for full quantum mechanical calculations, and vice versa. The best-known descriptors based on the statistics of the MEP at the molecular surface are those introduced by Murray and Politzer [44]. These were originally formulated for DFT calculations using an isodensity surface. They have also been used very extensively with semi-empirical MO techniques and solvent-accessible surfaces [1, 2]. The charged polar surface area (CPSA) descriptors proposed by Stanton and Jurs [45] are also based on charges derived from semi-empirical MO calculations. 

One of the simplest and most common ways to evaluate a molecule for ADME properties is a qualitative examination of its basic descriptor values such as molecular weight (MW), ClogP for lipophilicity, polar surface area (PSA), counts of hydrogen bond donors and acceptors (HBD, HBA), and count of rotatable bonds (RB). This type of approach popularized by Lipinski s famous Rule of 5 was published a decade ago [6]. Lipinski et al. established cutoffs for MW (500), ClogP (5), HBA (10), and HBD (5). These cutoffs were based on the 90th percentile of distributions of molecules in the World Drug Index having USAN or INN names. The Rule of 5 considers a violation of any two of these cutoffs to be an alert for poor absorption or permeability. 

We can also look at other literature datasets to gain an idea of how similar our compounds are to compounds for which QMPRPlus gives very good predictions. We have looked at four simple descriptors molecular weight, topological polar surface area [40], chemical complexity [41], and rotatable bond count, using John Bradshaw s... 

A more profound visual difference of the chemical space covered by natural products and synthetic drugs was presented by Derek Tan, in which he applied a similar PCA analysis of 20 synthetic drugs (including ten best sellers of 2004) and 20 natural products.7 For this analysis, Tan used nine molecular descriptors—molecular weight, clog P, H-bond donors, H-bond acceptors, rotatable bonds, polar surface area (PSA), chiral centres, N and O atoms—and then applied PCA to reduce nine-dimensional vectors to two-dimensional vectors before re-plotting the data. 

Empirical, semiempirical, and ab initio methods have been used extensively to calculate molecular descriptors. These molecular property descriptors help capture important characteristics of compounds such as bioavailability and receptor affinity. Descriptors such as octanol-water partition coefficient (log P), HOMO/LUMO energies, hammett a, total energy, heats of formation, ionization potential, atomic charges, electron densities, dipole/quadrupole moments, volume, and polar surface area are common examples. For an excellent review of physicochemical descriptors, the reader is directed to the following reference. ... 

Most of the commercial molecular modeling systems also provide some property calculations, which range from simply calculating the polar surface area of a structure to a full range of topological and physicochemical descriptors. These may be based on fragment additivity, like most of the programs mentioned above, or they may involve correlations with quantum mechanical or even molecular dynamics-based calculations. 

Martin proposed a bioavailability score based on several molecular properties including polar surface area (PSA), rule-of-5, and molecular charged state. With the descriptors used, this is an example aiming to estimate oral absorption and not bioavailability [19] hence, the title of this work is misleading. A score was developed to assign the probability that a compound has an F more than 10% in the rat. We do not consider this as a meaningful cutoff. Better would be F more than 30% in man [30]. 

Computationally derived descriptors (e.g., molecular weight, size, shape, polarity, electrostatic interactions, charge, lipophilicity, hydrogen bonding capacity, polar surface area). 

To quantify the conformational sensitivity of molecular descriptors, the conformational pairwise sensitivity (CPS) was proposed as the difference between conformationally dependent physico-chemical properties P, such as, for example, dipole moments, polar surface area, or 3D calculated logP, over the difference between geometry-dependent molecular descriptors D [Vistoli, Pedretti et al., 2005], This quantity is defined as... 

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