Hierarchical analysis of the target-based scoring function modification for the example of selected class A GPCRs.

Computational methods, especially molecular docking-based calculations, have become indispensable in the modern drug discovery workflow. The constantly increasing chemical space requires fast, robust but most of all highly predictive methods to search for new bioactive agents. Thus, the scoring function (SF) is a useful and broadly applied energy-based element of docking software, allowing quick and effective evaluation of a ligand's propensity to bind to selected protein targets. Despite many spectacular successes of molecular docking applications in virtual screening (VS), the obtained results are often far from ideal, leading to incorrect selection of hit molecules and poor pose prediction. In our study we focused on docking calculation for the selected class A G-protein coupled receptors (GPCRs), with experimentally determined 3D structures and a sufficient set of known ligands with affinity values reported in the ChEMBL database. Our goal is to investigate how much the energy-based scoring function for this particular target class changes when changing from the default to the re-estimated weighting scheme on the specified energy terms in the SF definition. Additionally, we want to verify if indeed more accurate results are obtained when considering different levels of the biological hierarchy, namely: the whole class A GPCRs, sub-subfamilies, or just the individual proteins while applying default or specifically designed weighting coefficients. The performed calculation and evaluation factor values suggest a significant improvement of docking results for the designed SF definition. This individual approach improves the accuracy of binding affinity prediction and active compound recognition. The designed scoring function for classes, sub-subfamilies, or proteins leads to a significant improvement of molecular docking performance, especially at the level of individual proteins. Our results show that to increase the efficiency and predictive power of molecular docking calculations applied in classical VS, the strategy based on the individual approach for scoring function definition for selected proteins should be considered.

Electrostatic potential and non-covalent interactions analysis for the design of selective 5-HT7 ligands.

Despite the significant improvement of methodology in the field of the in silico drug discovery, the search for selective drugs is still far from trivial. This is especially relevant in the case of designing new medicaments for treatment of central nervous system disorders. In this work, we present a new approach based on the molecular docking and the following electronic properties analysis of ligands' binding poses (electrostatic potential distribution analysis and quantitative topological analysis of the electron density distribution). The proposed protocol significantly increases the success rate of the selective 5-HT7R ligands against 5-HT1AR selection from the prepared databases (the rise from 33.3% to 77.8% and from 22.7% to 62.5% for training and testing sets, respectively). The presented approach can be applied as a supportive method in the virtual screening of ligands databases.

The engineered ß-lactoglobulin with complementarity to the chlorpromazine chiral conformers.

Chlorpromazine (CPZ) is a phenothiazine acting as dopamine antagonist. Aside from application in schizophrenia therapy, chlorpromazine is found to be a putative inhibitor of proteins involved in cancers, heritable autism disorder and prion diseases. Four new ß-lactoglobulin variants with double or triple substitutions: I56F/L39A, F105L/L39A, I56F/L39A/M107F or F105L/L39A/M107F changing the shape of the binding pocket were produced and their chlorpromazine binding properties have been investigated by X-ray crystallography, circular dichroism, isothermal titration calorimetry and thermophoresis. The CD spectra and crystal structures revealed that mutations do not affect the protein overall structure but in comparison to WT protein, variants possessing I56F substitution had lower stability while mutation F105L increased melting temperature of the protein. The new variants showed affinity to chlorpromazine in the range 4.2-15.4 × 103 M-1. The CD spectra and crystal structures revealed complementarity of the binding pocket shape, to only one chlorpromazine chiral conformer. The (aR)-CPZ was bonded to variants containing I56F substitution while variants with F105L substitution preferred (aS)-CPZ.