Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces

Abstract

Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID energy functions. The most relevant points are selected by a newly developed filtering cascade and clustered to pharmacophore features with a density-based algorithm. Using five different protein classes, the ability of this method to identify essential pharmacophore features was compared to structure-based pharmacophores derived from ligand-target interactions. This method represents an extremely valuable instrument for drug design in a situation of scarce ligand information available, but also in the case of underexplored therapeutic targets, as well as to investigate protein allosteric pockets and protein-protein interactions.

Next generation 3D pharmacophore modeling

“…Molecular field‐based programs take the points where the energy of a MIF represents a local minimum, termed “hotspots,” and convert them into pharmacophore features according to the type of probe that forms the most energetically favorable interaction at this point. Molecular field‐based hotspot detection can also be performed by employing noncommercial software such as AutoGrid within AutoDock which provides access to energy grid maps for various atom types …”

In silico discovery and biological validation of ligands of FAD synthase, a promising new antimicrobial target

“…Therefore, these protocols usually implement a funnel-like strategy, which start from fast but less accurate methods (where a large number of molecules are filtered) and more accurate and time-consuming tools are used in the last steps [13][14][15]. Usually, pharmacophore-based tools are implemented in the first stages of VS, given their ability to quickly screen large compounds libraries [16][17][18]. While more sophisticated tools such as docking or molecular dynamics (MD) are implemented in the latter steps to predict ligand affinities [11,13,[19][20][21][22][23][24][25][26].…”

In silicodiscovery and biological validation of ligands of FAD synthase, a promising new antimicrobial target

“…Therefore, these protocols usually implement a funnel-like 15 strategy, which start from fast but less accurate methods (where a large number of 16 molecules are filtered) and more accurate and time-consuming tools are used in the last 17 steps [13][14][15]. Usually, pharmacophore-based tools are implemented in the first stages of 18 VS, given their ability to quickly screen large compounds libraries [16][17][18]. While more 19 sophisticated tools such as docking or molecular dynamics (MD) are implemented in the 20 latter steps to predict ligand affinities [11,13,[19][20][21][22][23][24][25][26].…”

“…Special attention deserve the tools used in the first steps of the VS, because these 22 impact the ability of the protocol to explore large compound libraries and the chemical 23 space of the compounds, such as the pharmacophore-based strategies [16][17][18][27][28][29][30].…”

“…Flexi-Pharma: pharmacophore filtering from ligand-free receptor 267 conformations 268 Pharmacophore-based VS strategies are computationally efficient. These strategies are 269 able to explore large compound libraries using pharmacophores: an ensemble of 270 physico-chemical features that ensure the optimal interactions within the active site of a 271 specific biological target [16]. Therefore, the first stage of the protocol implements a 272 phamacophore-based VS strategy [31].…”