Conformational flexibility has been proposed to significantly affect drug properties outside rule-of-5 (Ro5) chemical space. Here, we investigated the influence of dynamically exposed polarity on cell permeability and aqueous solubility for a structurally diverse set of drugs and clinical candidates far beyond the Ro5, all of which populated multiple distinct conformations as revealed by X-ray crystallography. Efflux-inhibited (passive) Caco-2 cell permeability correlated strongly with the compounds' minimum solvent-accessible 3D polar surface areas (PSA), whereas aqueous solubility depended less on the specific 3D conformation. Inspection of the crystal structures highlighted flexibly linked aromatic side chains and dynamically forming intramolecular hydrogen bonds as particularly effective in providing "chameleonic" properties that allow compounds to display both high cell permeability and aqueous solubility. These structural features, in combination with permeability predictions based on the correlation to solvent-accessible 3D PSA, should inspire drug design in the challenging chemical space far beyond the Ro5.

It has been hypothesised that drugs in the chemical space "beyond the rule of 5" (bRo5) must behavea smolecular chameleons to combine otherwisec onflicting properties, including aqueous solubility,c ell permeability and target binding. Evidence for this has, however,b een limited to the cyclic peptidec yclosporine A. Herein, we show that the non-peptidic and macrocyclic drugs roxithromycin, telithromycin and spiramycin behave as molecular chameleons, with rifampicin showing al ess pronounced behaviour.I n particular roxithromycin, telithromycin and spiramycin display am arked, yet limited flexibility and populate signifi-cantly less polar and more compact conformational ensembles in an apolart han in ap olar environment. In addition to balancingo fm embrane permeability and aqueous solubility, this flexibility also allows binding to targetst hat vary in structure between species. The drugs' passivec ell permeability correlates to their 3D polar surface area and corroborate two theoretical models for permeability,d eveloped for cyclic peptides. We conclude that molecular chameleonicity should be incorporated in the design of orally administered drugs in the bRo5 space.[a] Dr.

Conformational flexibility is a major determinant of the properties of macrocycles and other drugs in beyond rule of 5 (bRo5) space. Prediction of conformations is essential for design of drugs in this space, and we have evaluated three tools for conformational sampling of a set of 10 bRo5 drugs and clinical candidates in polar and apolar environments. The distance-geometry based OMEGA was found to yield ensembles spanning larger structure and property spaces than the ensembles obtained by MOE-LowModeMD (MOE) and MacroModel (MC). Both MC and OMEGA but not MOE generated different ensembles for polar and apolar environments. All three conformational search methods generated conformers similar to the crystal structure conformers for 9 of the 10 compounds, with OMEGA performing somewhat better than MOE and MC. MOE and OMEGA found all six conformers of roxithromycin that were identified by NMR in aqueous solutions, whereas only OMEGA sampled the three conformers observed in chloroform. We suggest that characterization of conformers using molecular descriptors, e.g., the radius of gyration and polar surface area, is preferred to energy- or root-mean-square deviation-based methods for selection of biologically relevant conformers in drug discovery in bRo5 space.

Proteolysis targeting chimeras (PROTACs) induce intracellular degradation of target proteins. Their bifunctional structure puts degraders in a chemical space where ADME properties often complicate drug discovery. Herein we provide the first structural insight into PROTAC cell permeability obtained by NMR studies of a VHL-based PROTAC (1), which is cell permeable despite having a high molecular weight and polarity and a large number of rotatable bonds. We found that 1 populates elongated and polar conformations in solutions that mimic extra- and intracellular compartments. Conformations were folded and had a smaller polar surface area in chloroform, mimicking a cell membrane interior. Formation of intramolecular and nonclassical hydrogen bonds, π–π interactions, and shielding of amide groups from solvent all facilitate cell permeability by minimization of size and polarity. We conclude that molecular chameleonicity appears to be of major importance for 1 to enter into target cells.

ABSTRACT:The cytochrome P450 (P450) superfamily plays an important role in the metabolism of drug compounds, and it is therefore highly desirable to have models that can predict whether a compound interacts with a specific isoform of the P450s. In this work, we provide in silico models for classification of CYP1A2 inhibitors and noninhibitors. Training and test sets consisted of approximately 400 and 7000 compounds, respectively. Various machine learning techniques, such as binary quantitative structure activity relationship, support vector machine (SVM), random forest, kappa nearest neighbor (kNN), and decision tree methods were used to develop in silico models, based on Volsurf and Molecular Operating Environment descriptors. The best models were obtained using the SVM, random forest, and kNN methods in combination with the BestFirst variable selection method, resulting in models with 73 to 76% of accuracy on the test set prediction (Matthews correlation coefficients of 0.51 and 0.52). Finally, a decision tree model based on Lipinski's Rule-of-Five descriptors was also developed. This model predicts 67% of the compounds correctly and gives a simple and interesting insight into the issue of classification. All of the models developed in this work are fast and precise enough to be applicable for virtual screening of CYP1A2 inhibitors or noninhibitors or can be used as simple filters in the drug discovery process.Cytochromes P450 (P450s) are heme-containing enzymes found in both prokaryotes and eukaryotes, and they are involved in a wide range of cellular biotransformation functions. From a pharmaceutical perspective, the most important function is the degradation of drugs (Nebert and Russell, 2002). In general, hydrophobic compounds are converted into more hydrophilic species to facilitate excretion.The most important P450 isoforms involved in metabolism of drugs in humans are CYP1A2, CYP2A6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4. CYP1A2 constitutes 12% of the total P450 content in the liver and plays an important role in the metabolic clearance of ϳ5% of currently marketed drugs. The substrates for the CYP1A subfamily are generally characterized as neutral, flat, aromatic, and lipophilic (two to four aromatic rings) with at least one putative hydrogen bond donor (Smith et al., 1997), in agreement with the observed contacts in the recent crystal structure of CYP1A2 (Sansen et al., 2007). Examples of drugs that are CYP1A2 substrates are acetaminophen, caffeine, clozapine, haloperidol, olanzapine, propranolol, tacrine, theophylline, and zolmitriptan (drug interactions: cytochrome P450 drug interaction table, Indiana University School of Medicine, http://medicine.iupui.edu/flockhart/table.htm).In silico approaches are attractive because they can be used in an early stage of the drug discovery process and thereby reduce the number of experimental studies and improve the success rates. For this purpose, various traditional in silico modeling methods and more recently developed nonlinear machine learning methods...