Partition Coefficient and Molecular Flexibility: The Concept of Lipophilicity Space

Abstract

The rationale of this study was to investigate molecular flexibility and its influence on physicochemical properties with a view to uncovering additional information on the fuzzy concept of dynamic molecular structure. Indeed, it is now known that computed molecular interaction fields (MIFs) such as molecular electrostatic potentials (MEPs) and lipophilicity potentials (MLPs) are conformation-dependent, as are dipole moments. A database of 125 compounds was used whose conformational space was explored, while conformation-dependent parameters were computed for each non-redundant conformer found in the conformational space of the compounds. These parameters were the virtual log P (log P(MLP), calculated by a MLP approach), the apolar surface area (ASA), polar surface area (PSA), and solvent-accessible surface (SAS). For each compound, the range taken by each parameter (its property space) was divided by the number of rotors taken as an index of flexibility, yielding a parameter termed 'molecular sensitivity'. This parameter was poorly correlated with others (i.e., it contains novel information) and showed the compounds to fall into two broad classes. 'Sensitive' molecules are those whose computed property ranges are markedly sensitive to conformational effects, whereas 'insensitive' (in fact, less sensitive) molecules have property ranges which are comparatively less affected by conformational fluctuations. A pharmacokinetic application is presented.

Molecular Interaction Fields (MIFs) to Predict Lipophilicity and ADME Profile of Antitumor Pt(II) Complexes

“…VolSurf, ALMOND, MetaSite (12)). In particular, here we used VolSurf 2D descriptors, since these latter quantitatively characterize polarity and hydrophobicity, which are the main factors governing lipophilicity (13), and we already used them to calculate virtual log P N alk of molecules in the alkane/water system (14,15).…”

Chemodiversity and Molecular Plasticity: Recognition Processes as Explored by Property Spaces

“…As discussed in the section titled 'Property space and QSAR analyses', it should be noted that the first one is a 2D descriptor, while RMSD and variation in radius of gyration require simulations and depend on the constraining effects exerted by the simulated medium. The different nature of such flexibility descriptors is confirmed by the fair correlations between them as computed considering a large dataset of compounds (rotors vs RMSD: r 2 = 0.49; rotors vs radius variation: r 2 = 0.59; RMSD vs radius variation: r 2 = 0.44) [39].…”

“…The concept of molecular sensitivity and the discrimination between 'sensitive' and 'insensitive' (in fact, less sensitive) molecules was substantiated by considering the property space of a heterogeneous set of 125 biologically active compounds [39]. Despite what one would expect a priori, there is only a fair correlation between property ranges and molecular flexibility (as defined by the number of rotors, r 2 @ 0.5, FiguRe 5a) and this underlines that information encoded by property spaces cannot be reduced to mere structural variability.…”

“…The property space descriptors found also interesting applications in predicting ADME parameters, since they were successfully exploited to predict both transdermal permeability and volume of distribution, both of which represent a measure of the relative partitioning of drugs between plasma and tissues [34,39]. In both cases, the remarkable enhancement of the predictive models exerted by the introduction of property space parameters emphasizes the relevance of accounting for molecular plasticity when modeling permeation processes, which depend on the adaptability a molecule can exhibit when inserted in media of different polarity.…”

Predicting the physicochemical profile of diastereoisomeric histidine‐containing dipeptides by property space analysis

“…On the other hand, this suggests that accounting for conformational factors by considering a single (albeit optimized) conformation is not enough to take the greater informational complexity into account. Thus, a study based on a database of 125 heterogeneous compounds showed that the 3D approaches can be slightly improved by including in the predictive relationships property space descriptors that account for the dynamic profile of flexible molecules . Similarly, a recent study indicated that it is possible to derive truly accurate log P predictions for homogenous sets of molecules by combining their log P values computed by a 3D method with molecular flexibility descriptors.…”