Prediction of Log P with Property‐Based Methods

Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method

The logarithm of n-octanol-water partition coefficient (logP) is frequently used as an indicator of lipophilicity in drug discovery, which has substantial impacts on the absorption, distribution, metabolism, excretion, and toxicity of a drug candidate. Considering that the experimental measurement of the property is costly and time-consuming, it is of great importance to develop reliable prediction models for logP. In this study, we developed a transfer free energy-based logP prediction model-FElogP. FElogP is based on the simple principle that logP is determined by the free energy change of transferring a molecule from water to n-octanol. The underlying physical method to calculate transfer free energy is the molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), thus this method is named as free energy-based logP (FElogP). The superiority of FElogP model was validated by a large set of 707 structurally diverse molecules in the ZINC database for which the measurement was of high quality. Encouragingly, FElogP outperformed several commonly-used QSPR or machine learning-based logP models, as well as some continuum solvation model-based methods. The root-mean-square error (RMSE) and Pearson correlation coefficient (R) between the predicted and measured values are 0.91 log units and 0.71, respectively, while the runner-up, the logP model implemented in OpenBabel had an RMSE of 1.13 log units and R of 0.67. Given the fact that FElogP was not parameterized against experimental logP directly, its excellent performance is likely to be expanded to arbitrary organic molecules covered by the general AMBER force fields.

Selective Cannabinoid 2 Receptor Stimulation Reduces Tubular Epithelial Cell Damage after Renal Ischemia-Reperfusion Injury

Ischemia-reperfusion injury (IRI) is a common cause of acute kidney injury (AKI), which is an increasing problem in the clinic and has been associated with elevated rates of mortality. Therapies to treat AKI are currently not available, so identification of new targets that can be modulated to ameliorate renal damage upon diagnosis of AKI is essential. In this study, a novel cannabinoid receptor 2 (CB2) agonist, SMM-295 [3'-methyl-4-(2-(thiophen-2-yl)propan-2-yl)biphenyl-2,6-diol], was designed, synthesized, and tested in vitro and in silico. Molecular docking of SMM-295 into a CB2 active-state homology model showed that SMM-295 interacts well with key amino acids to stabilize the active state. In human embryonic kidney 293 cells, SMM-295 was capable of reducing cAMP production with 66-fold selectivity for CB2 versus cannabinoid receptor 1 and dose-dependently increased mitogen-activated protein kinase and Akt phosphorylation. In vivo testing of the CB2 agonist was performed using a mouse model of bilateral IRI, which is a common model to mimic human AKI, where SMM-295 was immediately administered upon reperfusion of the kidneys after the ischemia episode. Histologic damage assessment 48 hours after reperfusion demonstrated reduced tubular damage in the presence of SMM-295. This was consistent with reduced plasma markers of renal dysfunction (i.e., creatinine and neutrophil gelatinase-associated lipocalin) in SMM-295-treated mice. Mechanistically, kidneys treated with SMM-295 were shown to have elevated activation of Akt with reduced terminal deoxynucleotidyl transferase-mediated digoxigenin-deoxyuridine nick-end labeling (TUNEL)-positive cells compared with vehicle-treated kidneys after IRI. These data suggest that selective CB2 receptor activation could be a potential therapeutic target in the treatment of AKI.

A perspective on the role of quantitative structure-activity and structure-property relationships in herbicide discovery

BACKGROUND

For the last 15 years the agrochemical industry has focused on using genetic modification to put genes that confer resistance to existing commercial herbicides into crop plants rather than on discovering new herbicides with novel modes of action. The widespread appearance of weeds resistant to those herbicides is now causing the industry to revive their herbicide discovery programs.

RESULTS

Elucidation of quantitative structure-activity relationships (QSARs) played a major role in the discovery and development of existing commercial herbicides, but the advent of genetically modified crops has caused published work (at least) in the area to drift from the industrial arena into academic studies. The focus has also turned inward, to refining models for established herbicide targets instead of elucidating new ones.

CONCLUSION

This perspective highlights the importance of QSARs and quantitative structure-property relationships (QSPRs) to herbicide discovery in an historical context and provides some guidance as to how they might profitably be applied going forward.

Influence of molecular properties on oral bioavailability of lipophilic drugs - mapping of bulkiness and different measures of polarity

The biopharmaceutical assessment of new drug candidates based on their chemical structure is important in drug discovery and development. The scope of this study is to focus on lipophilic drugs and to clarify the role of their chemical predictors on oral bioavailability in humans. First their chemical properties were calculated from molecular modeling and the bioavailability data was obtained from the literature. The data was then analyzed by a partial least square method including non-linear terms. Significant coefficients were identified from a group of polarity- and solubility-related properties. Contour plots were constructed mapping molecular weight together with different polarity factors. Depending on the molecular weight a maximal bioavailability was found at solubility parameters of about 31-35 (J/cm(3))(1/2) and HLB values of roughly 4-12. The mapping of lipophilic drugs also revealed that a solubility parameter of less than 20 (J/cm(3))(1/2) or a HLB of smaller than unity is critical for the drug-likeness of new compounds.