Discovery of Octahydroisoindolone as a Scaffold for the Selective Inhibition of Chitinase B1 from Aspergillus fumigatus: In Silico Drug Design Studies

Chitinases represent an alternative therapeutic target for opportunistic invasive mycosis since they are necessary for fungal cell wall remodeling. This study presents the design of new chitinase inhibitors from a known hydrolysis intermediate. Firstly, a bioinformatic analysis of Aspergillus fumigatus chitinase B1 (AfChiB1) and chitotriosidase (CHIT1) by length and conservation was done to obtain consensus sequences, and molecular homology models of fungi and human chitinases were built to determine their structural differences. We explored the octahydroisoindolone scaffold as a potential new antifungal series by means of its structural and electronic features. Therefore, we evaluated several synthesis-safe octahydroisoindolone derivatives by molecular docking and evaluated their AfChiB1 interaction profile. Additionally, compounds with the best interaction profile (1–5) were docked within the CHIT1 catalytic site to evaluate their selectivity over AfChiB1. Furthermore, we considered the interaction energy (MolDock score) and a lipophilic parameter (aLogP) for the selection of the best candidates. Based on these descriptors, we constructed a mathematical model for the IC50 prediction of our candidates (60–200 μM), using experimental known inhibitors of AfChiB1. As a final step, ADME characteristics were obtained for all the candidates, showing that 5 is our best designed hit, which possesses the best pharmacodynamic and pharmacokinetic character.

Can an Intermediate Rate of Nitrogen Inversion Affect Drug Efficacy?

Nitrogen-inversion rates and diffusion coefficients were measured using 1H NMR for 14 drug-like molecules. The slow nitrogen-inversion rates interconverting the enantiomers of these molecules lay within a postulated intermediate range in terms of their ability to bind to proteins bounded by diffusion constraints, potentially affecting the availability, hence efficacy, of these compounds if they were utilized as drugs. The postulated intermediate range is based on a capture-volume concept, whereby the nitrogen inversion during the time a ligand takes to pass through a volume surrounding the protein binding site, as calculated by the diffusion rate, determines if it will influence ligand binding to the protein. In the systems examined here, the measured nitrogen-inversion rates and the times required to traverse the capture volume differed by a few orders of magnitude. Potentially more consequential are intermediate nitrogen-inversion rates in epimeric cases—since the energies of the interconverting species are unequal, a heavy bias against the eutomer might occur. The implications of an intermediate nitrogen-inversion rate are significant for in silico drug design, drug efficacy, molecular modeling of drug–protein binding, pharmacokinetics, drug enantiomer evaluation, etc. Due consideration of the process should thus be taken into account for drug development directions and in vitro evaluation.

VSPrep: A KNIME Workflow for the Preparation of Molecular Databases for Virtual Screening

Drug discovery is a challenging and expensive field. Hence, novel in silico tools have been developed in early discovery stage to identify and prioritize novel molecules with suitable physicochemical properties. In many in silico drug design projects, molecular databases are screened by virtual screening tools to search for potential bioactive molecules. The preparation of the molecules is therefore a key step in the success of well-established techniques such as docking, similarity or pharmacophore searching. We review here the lists of several toolkits used in different steps during the cleaning of molecular databases, integrated within a KNIME workflow. During the first step of the automatic workflow, salts are removed, and mixtures are split to get one compound per entry. Then compounds with unwanted features are filtered. Duplicated entries are then deleted while considering stereochemistry. As a compromise between exhaustiveness and computational time, most distributed tautomers at physiological pH are computed. Additionally, various flags are applied to molecules by using either classical molecular descriptors, similarity search to known libraries or substructure search rules. Moreover, stereoisomers are enumerated depending on the unassigned chiral centers. Then, three-dimensional coordinates, and optionally conformers, are generated. This workflow has been already applied to several drug design projects and can be used for molecular database preparation upon request.

MolOpt: A Web Server for Drug Design using Bioisosteric Transformation

Background: Bioisosteric replacement is widely used in drug design for lead optimization. However, the identification of a suitable bioisosteric group is not an easy task. Methods: In this work, we present MolOpt, a web server for in silico drug design using bioisosteric transformation. Potential bioisosteric transformation rules were derived from data mining, deep generative machine learning and similarity comparison. MolOpt tries to assist the medicinal chemist in his/her search for what to make next. Results and Discussion: By replacing molecular substructures with similar chemical groups, MolOpt automatically generates lists of analogues. MolOpt also evaluates forty important pharmacokinetic and toxic properties for each newly designed molecule. The transformed analogues can be assessed for possible future study. Conclusion: MolOpt is useful for the identification of suitable lead optimization ideas. The MolOpt Server is freely available for use on the web at http://xundrug.cn/molopt.