Ensemble completeness in conformer sampling: the case of small macrocycles

Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity

We evaluated a workflow to reliably sample the conformational space of a set of 47 peptidic macrocycles. Starting from SMILES strings, we use accelerated molecular dynamics simulations to overcome high energy barriers, in particular, the cis-trans isomerization of peptide bonds. We find that our approach performs very well in polar solvents like water and dimethyl sulfoxide. Interestingly, the protonation state of a secondary amine in the ring only slightly influences the conformational ensembles of our test systems. For several of the macrocycles, determining the conformational distribution in chloroform turns out to be considerably more challenging. Especially, the choice of partial charges crucially influences the ensembles in chloroform. We address these challenges by modifying initial structures and the choice of partial charges. Our results suggest that special care has to be taken to understand the configurational distribution in apolar solvents, which is a key step toward a reliable prediction of membrane permeation of macrocycles and their chameleonic properties.

Insight into the corrosion inhibiting potential and anticancer activity of 1-(4-methoxyphenyl)-5-methyl-N'-(2-oxoindolin-3-ylidene)-1H-1,2,3-triazole-4-carbohydrazide via computational approaches

Cancer is a major health concern globally. Orthodox and traditional medicine have actively been explored to manage this disease. Also, corrosion is a natural catastrophe that weakens and deteriorates metallic structures and their alloys causing major structural failures and severe economic implications. Designing and exploring multi-functional materials are beneficial since they are adaptive to different fields including engineering and pharmaceutics. In this study, we examined the anti-corrosion and anti-cancer potentials of 1-(4-methoxyphenyl)-5-methyl-N'-(2-oxoindolin-3-ylidene)-1H-1,2,3-triazole-4-carbohydrazide (MAC) using computational approaches. The molecular reactivity descriptors and charge distribution parameters of MAC were studied in gas and water at density functional theory (DFT) at B3LYP/6-311++G(d,p) theory level. The binding and mechanism of interaction between MAC and iron surface was studied using Monte Carlo (MC) and molecular dynamics (MD) simulation in hydrochloric acid medium. From the DFT, MC, and MD simulations, it was observed that MAC interacted spontaneously with iron surface essentially via van der Waal and electrostatic interactions. The near-parallel alignment of the corrosion inhibitor on iron plane facilitates its adsorption and isolation of the metal surface from the acidic solution. Further, the compound was docked in the binding pocket of anaplastic lymphoma kinase (ALK: 4FNZ) protein to assess its anti-cancer potential. The binding score, pharmacokinetics, and drug-likeness of MAC were compared with the reference drug (Crizotinib). The MAC displayed binding scores of -5.729 kcal/mol while Crizotinib has -3.904 kcal/mol. MD simulation of the complexes revealed that MAC is more stable and exhibits more favourable hydrogen bonding with the ALK receptor's active site than Crizotinib.Communicated by Ramaswamy H. Sarma.

Dynamic Docking of Macrocycles in Bound and Unbound Protein Structures with DynaDock

Macrocycles are interesting molecules with unique features due to their conformationally constrained yet flexible ring structure. This characteristic poses a difficult challenge for computational modeling studies since they rely on accurate structural descriptions. In particular, molecular docking calculations suffer from the lack of ring flexibility during pose generation, which is often compensated by using pregenerated ligand conformer ensembles. Moreover, receptor structures are mainly treated rigidly, which limits the use of many docking tools. In this study, we optimized our previous molecular dynamics-based sampling and docking pipeline specifically designed for the accurate prediction of macrocyclic compounds. We developed a dihedral classification procedure for in-depth conformational analysis of the macrocyclic rings and extracted structural ensembles that were subsequently docked in both bound and unbound protein structures employing a fully flexible approach. Our results suggest that including a ring conformer close to the bound state in the starting ensemble increases the chance of successful docking. The bioactive conformations of a diverse set of ligands could be predicted with high and decent accuracy in bound and unbound protein structures, respectively, due to the incorporation of full molecular flexibility in our approach. The remaining unsuccessful docking calculations were mainly caused by large flexible substituents that bind to surface-exposed binding sites, rather than the macrocyclic ring per se and could be further improved by explicit molecular dynamics simulations of the docked complex.