On the usage of lipophilic descriptors for molecular similarity evaluation
[eng] Three-dimensional ligand-based virtual screening methods have been used for many years in drug discovery, with a variable success depending on different factors, such as the complexity of the target system or the suitability of the molecular descriptors. New approaches are still necessary to c...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/141939 |
| Acceso en línea: | https://hdl.handle.net/2445/141939 http://hdl.handle.net/10803/667608 |
| Access Level: | acceso abierto |
| Palabra clave: | Disseny de medicaments Estructura molecular Lligands (Bioquímica) Lipofília Drug design Molecular structure Ligands (Biochemistry) Lipophilicity |
| Sumario: | [eng] Three-dimensional ligand-based virtual screening methods have been used for many years in drug discovery, with a variable success depending on different factors, such as the complexity of the target system or the suitability of the molecular descriptors. New approaches are still necessary to cover the broad spectrum of relationships that a drug-like molecule may establish with the organism. In spite of the complexity of processes that modulate the activity of a drug, most tools are primarily focused on the use of shape or electrostatic descriptors. In contrast, since the importance of lipophilicity in pharmacodynamics and pharmacokinetics process, an exact representation of the 3D pattern of hydrophobic/hydrophilic regions can be a valuable guideline to enhance the molecular similarity studies. In this scenario, PharmScreen was conceived as a tool to exploit lipophilic 3D similarity. Exploiting the MST contributions to octanol/water partition coefficients, the capacity to perform correct molecular overlays and distinguish between active and inactive molecules is discussed. The overlap algorithm is validated against the AstraZeneca test, which comprises 121 experimentally derived sets of molecular overlays. The results point out the suitability of the MST-based hydrophobic parameters for generating molecular overlays, as correct predictions were obtained for 94%, 79%, and 54% of the molecules classified into easy, moderate, and hard sets, respectively. Moreover, the results point out that this accuracy is attained at a much lower degree of identity between the templates used by hydrophobic/HB fields and electrostatic/steric ones. On the other hand, the topological hydrophobic descriptors proposed are applied over 3D-QSAR models. In this context, the Miertus–Scrocco–Tomasi-derived hydrophobic descriptors have been shown to provide models for structure–activity relationships with a predictive accuracy comparable to traditional techniques based on electrostatic/steric parameters. The results reported support the assumption that lipophilicity, supplemented by HB acceptors/donors, provides a useful signature to enrich the information that can be retrieved from (i) molecular alignment and (ii) QSAR models, complementing the results obtained traditionally from electrostatic and steric properties. Taken together, lipophilicity is presented as a valuable alternative for the molecular similarity study. In addition, the applicability of our descriptors in structure-based methods has been explored in order to re-evaluate the complexes constituted by docking techniques (in our case, Glide). Since (de)solvation is fundamental for the establishment of the ligand-receptor complex, it can be expected that the docked ligands in the same pocket share lipophilic characteristics, even if there are several binding modes. However, approximations that affect solvation contribution are applied in the docking score functions, and by extension, some docking programs show problems performing VS especially in hydrophobic binding pockets. Specific binding typically requires the formation of key interactions between targets and ligands. Thus, 3D similarity relative to experimental binding modes could be sufficient to distinguish active compounds from decoys. In view of the results obtained the similarity descriptors proposed are introduced as a valid scoring function for discerning between active and inactive compounds. These findings support the usefulness of lipophilicity as driver descriptors in molecular similarity studies promoting their use in virtual screening campaigns considering LB approaches or in combination with SB. As conclusion, results obtained from the analysis of hydrophobic/hydrophilic descriptors presented in this thesis opens a new window to explore the vast chemical space, complementing the information derived from traditional descriptors in ligand- and structure-based approaches. |
|---|