In recent years, there has been an increased interest in using macrocyclic compounds for drug discovery and development. For docking of these commonly large and flexible compounds to be addressed, a screening and a validation set were assembled from the PDB consisting of 16 and 31 macrocycle-containing protein complexes, respectively. The macrocycles were docked in Glide by rigid docking of pregenerated conformational ensembles produced by the macrocycle conformational sampling method (MCS) in Schrödinger Release 2015-3 or by direct Glide flexible docking after performing ring-templating. The two protocols were compared to rigid docking of pregenerated conformational ensembles produced by an exhaustive Monte Carlo multiple minimum (MCMM) conformational search and a shorter MCMM conformational search (MCMM-short). The docking accuracy was evaluated and expressed as the RMSD between the heavy atoms of the ligand as found in the X-ray structure after refinement and the poses obtained by the docking protocols. The median RMSD values for top-scored poses of the screening set were 0.83, 0.80, 0.88, and 0.58 Å for MCMM, MCMM-short, MCS, and Glide flexible docking, respectively. There was no statistically significant difference in the performance between rigid docking of pregenerated conformations produced by the MCS and direct docking using Glide flexible docking. However, the flexible docking protocol was 2-times faster in docking the screening set compared to that of the MCS protocol. In a final study, the new Prime-MCS method was evaluated in Schrödinger Release 2016-3. This method is faster compared that of to MCS; however, the conformations generated were found to be suboptimal for rigid docking. Therefore, on the basis of timing, accuracy, and ease of set up, standard Glide flexible docking with prior ring-templating is recommended over current gold standard protocols using rigid docking of pregenerated conformational ensembles.

Herein we describe the design, synthesis, inhibitory potency, and pharmacokinetic properties of a novel class of achiral peptidomimetic HCV NS3 protease inhibitors. The compounds are based on a dipeptidomimetic pyrazinone glycine P3P2 building block in combination with an aromatic acyl sulfonamide in the P1P1' position. Structure-activity relationship data and molecular modeling support occupancy of the S2 pocket from elongated R(6) substituents on the 2(1H)-pyrazinone core and several inhibitors with improved inhibitory potency down to Ki = 0.11 μM were identified. A major goal with the design was to produce inhibitors structurally dissimilar to the di- and tripeptide-based HCV protease inhibitors in advanced stages of development for which cross-resistance might be an issue. Therefore, the retained and improved inhibitory potency against the drug-resistant variants A156T, D168V, and R155K further strengthen the potential of this class of inhibitors. A number of the inhibitors were tested in in vitro preclinical profiling assays to evaluate their apparent pharmacokinetic properties. The various R(6) substituents were found to have a major influence on solubility, metabolic stability, and cell permeability.

Macrocycles represent an important class of medicinally relevant small molecules due to their interesting biological properties. Therefore, a firm understanding of their conformational preferences is important for drug design. Given the importance of macrocycle-protein modelling in drug discovery, we envisaged that a systematic study of both classical and recent specialized methods would provide guidance for other practitioners within the field. In this study we compare the performance of the general, well established conformational analysis methods Monte Carlo Multiple Minimum (MCMM) and Mixed Torsional/Low-Mode sampling (MTLMOD) with two more recent and specialized macrocycle sampling techniques: MacroModel macrocycle Baseline Search (MD/LLMOD) and Prime macrocycle conformational sampling (PRIME-MCS). Using macrocycles extracted from 44 macrocycle-protein X-ray crystallography complexes, we evaluated each method based on their ability to (i) generate unique conformers, (ii) generate unique macrocycle ring conformations, (iii) identify the global energy minimum, (iv) identify conformers similar to the X-ray ligand conformation after Protein Preparation Wizard treatment (X-rayppw), and (v) to the X-rayppw ring conformation. Computational speed was also considered. In addition, conformational coverage, as defined by the number of conformations identified, was studied. In order to study the relative energies of the bioactive conformations, the energy differences between the global energy minima and the energy minimized X-rayppw structures and, the global energy minima and the MCMM-Exhaustive (1,000,000 search steps) generated conformers closest to the X-rayppw structure, were calculated and analysed. All searches were performed using relatively short run times (10,000 steps for MCMM, MTLMOD and MD/LLMOD). To assess the performance of the methods, they were compared to an exhaustive MCMM search using 1,000,000 search steps for each of the 44 macrocycles (requiring ca 200 times more CPU time). Prior to our analysis, we also investigated if the general search methods MCMM and MTLMOD could also be optimized for macrocycle conformational sampling. Taken together, our work concludes that the more general methods can be optimized for macrocycle modelling by slightly adjusting the settings around the ring closure bond. In most cases, MCMM and MTLMOD with either standard or enhanced settings performed well in comparison to the more specialized macrocycle sampling methods MD/LLMOD and PRIME-MCS. When using enhanced settings for MCMM and MTLMOD, the X-rayppw conformation was regenerated with the greatest accuracy. The, MD/LLMOD emerged as the most efficient method for generating the global energy minima. Graphic abstract

Background: Biological consequences of novel signature mutations in the p53 gene of tumors from patients exposed to Aristolochia medicines are not yet known. Results: N131Y, a prominent Aristolochia-linked mutation, confers cancer-associated behavior to cells. Conclusion: Rare mutations in cancer genes can have profound consequences to protein function. Significance: N131Y is a candidate biomarker of Aristolochia-related disease and target for pharmacological rescue of p53 function.

Herein, novel hepatitis C virus NS3/4A protease inhibitors based on a P2 pyrimidinyloxyphenylglycine in combination with various regioisomers of an aryl acyl sulfonamide functionality in P1 are presented. The P1' 4-(trifluoromethyl)phenyl side chain was shown to be particularly beneficial in terms of inhibitory potency. Several inhibitors with K i-values in the nanomolar range were developed and included identification of promising P3-truncated inhibitors spanning from P2-P1'. Of several different P2 capping groups that were evaluated, a preference for the sterically congested Boc group was revealed. The inhibitors were found to retain inhibitory potencies for A156T, D168V, and R155K variants of the protease. Furthermore, in vitro pharmacokinetic profiling showed several beneficial effects on metabolic stability as well as on apparent intestinal permeability from both P3 truncation and the use of the P1' 4-(trifluoromethyl)phenyl side chain.