Solvation of Nitrophenol Isomers: Consequences for Solute Electronic Structure and Alkane/Water Partitioning

Abstract

Solute partitioning across a variety of alkane/aqueous interfaces was examined as a function of solute and alkane solvent structure. Solutes include p-nitrophenol (PNP), 3,5-dimethyl-p-nitrophenol (3,5-DMPNP), and 2,6-dimethyl-p-nitrophenol (2,6-DMPNP), the latter two being isomers distinguished solely by the location of methyl substituents on the aromatic ring. The alkane solvents included cylohexane, methylcyclohexane, octane, and iso-octane (2,2,4-trimethylpentane). PNP partitioned preferentially into the water by factors as high as 160:1. The dimethyl isomers partitioned more equally between water and the different alkanes. 2,6-DMPNP showed a 3-fold greater affinity for the alkane phase than 3,5-DMPNP. Ab initio calculations were used to characterize the molecular and electronic structure of the three solutes and to quantify individual contributions to each solute's solvation energy in model aqueous and alkane phases. Differences between 2,6-DMPNP and 3,5-DMPNP partitioning are interpreted based on the ability of the methyl groups in 2,6-DMPNP to weaken hydrogen bonding between the phenol group and adjacent water molecules. This diminished solvation interaction reduces the barrier to solute migration into the nonpolar organic phase despite the fact that 2,6-DMPNP has a larger (calculated) permanent, ground-state dipole than 3,5-DMPNP.

An Accurate Approach for Computational pKa Determination of Phenolic Compounds

“…In particular, the pKa of -NO 2 -substituted phenols was slightly underestimated (0.6 units), whereas with 4-hydroxybenzonitrile, a ΔpKa = 0.3 was obtained. Such remarkable results strengthen the applicability of this method [ 31 , 32 , 33 ]. Cyano and nitro substituents are rarely reported in computational studies on pKa determination and are usually associated with a high ΔpKa [ 34 , 35 ].…”

Coumarin Partitioning in Model Biological Membranes: Limitations of log P as a Predictor

“…7,11 Missing are considerations of how subtle structural changes can affect a solute's affinity for one solvation environment over another. 12 Solute uptake into biological organisms is often reported using either bioaccumulation or bioconcentration factors, with the difference being in the source of solute exposure. 10 Bioaccumulation is defined as an organism's uptake of a solute from any environmental source, including dietary uptake, inhalation, metabolic transformation, dilution through organism growth, and excretion.…”

“…Thus, HTS techniques started to shift the balance from simple solute solubility considerations to a more molecular perspective based on chemical functionality to account for solute−solute and solute−target interactions. 2,5,6,12,16,17 In the l990s, Lipinski et al proposed a set of criteria for evaluating solute affinity for absorption, distribution, metabolism, and excretion (ADME) that is now referred to as the Lipinski Rule of Five (Ro5). 2,17 The Ro5 considers certain molecular properties intended to capture solutes that display effective ADME behavior.…”

“…Solute affinity for biological membranes is an extensively studied topic, given the importance of membrane partitioning in pharmaceutical applications and environmental toxicology. − The ability for solutes to partition into nonpolar phases underpins the general phenomenon of bioaccumulation as the basis for regulatory limits, used to identify harmful levels of pollutants in natural and municipal water systems. − While certain methods can be used to identify solutes that are likely to partition more readily into membranes, most bioaccumulation predictors are based either upon empirical results or models that simply use properties such as functional group additivity and overall solute polarity. , Missing are considerations of how subtle structural changes can affect a solute’s affinity for one solvation environment over another …”

“…HTS provided the ability to screen several compounds quickly; however, the resulting solute libraries required additional filtering to assess chemical functionality. Thus, HTS techniques started to shift the balance from simple solute solubility considerations to a more molecular perspective based on chemical functionality to account for solute–solute and solute–target interactions. ,,,,, …”