Field-based virtual screening: New trends to increase the chemical diversity of your leads

: Computational chemistry methods can significantly reduce experimental costs in early stages of a drug development project by filtering out unsuitable candidates and discovering new chemical matter. Molecular alignment is a key pre-requisite for 3D similarity evaluation between compounds and pharmacophore elucidation. Relying on the hypothesis that the variation in maximal achievable binding affinity for an optimized drug-like molecule is largely due to desolvation, we explore herein a novel small molecule 3D alignment strategy that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond donor/acceptor groups in each compound. A brief description of the method, as implemented in the software package PharmScreen, is presented. The computational procedure is calibrated by using a dataset of 402 molecules pertaining to 14 distinct targets taken from the literature and validated against the CCDC AstraZeneca test set of 121 experimentally derived molecular overlays. The results confirm the suitability of MST based-hydrophobic parameters for generating molecular overlays with correct predictions obtained for 100%, 93%, and 55% of the molecules classified into easy, moderate and hard sets, respectively. The potential of this tool in a drug discovery campaign is then evaluated in a retrospective study with the aim to evaluate the correlations between activities and similarity score of a series of sigma-1 receptor ligands. The results confirm the suitability of the tool for Drug Discovery purposes finding the 67% of the most active ligands (≤ 10 nM) in Q1 of the ranking and the most active compound in position five.


Abstract:
Computational chemistry methods can significantly reduce experimental costs in early stages of a drug development project by filtering out unsuitable candidates and discovering new chemical matter. Molecular alignment is a key pre-requisite for 3D similarity evaluation between compounds and pharmacophore elucidation. Relying on the hypothesis that the variation in maximal achievable binding affinity for an optimized drug-like molecule is largely due to desolvation, we explore herein a novel small molecule 3D alignment strategy that exploits the partitioning of molecular hydrophobicity into atomic contributions in conjunction with information about the distribution of hydrogen-bond donor/acceptor groups in each compound. A brief description of the method, as implemented in the software package PharmScreen, is presented. The computational procedure is calibrated by using a dataset of 402 molecules pertaining to 14 distinct targets taken from the literature and validated against the CCDC AstraZeneca test set of 121 experimentally derived molecular overlays. The results confirm the suitability of MST basedhydrophobic parameters for generating molecular overlays with correct predictions obtained for 100%, 93%, and 55% of the molecules classified into easy, moderate and hard sets, respectively. The potential of this tool in a drug discovery campaign is then evaluated in a retrospective study with the aim to evaluate the correlations between activities and similarity score of a series of sigma-1 receptor ligands. The results confirm the suitability of the tool for Drug Discovery purposes finding the 67% of the most active ligands (≤10 nM) in Q1 of the ranking and the most active compound in position five. Keywords: Drug Discovery; Virtual Screening; Molecular Alignment; Ligand-based; Hydrophobicity Speech Goals • Present the virtual screening techniques and how they can help finding better leads with high chemical diversity respect the reference structure.
-Hydrophobicity in CADD -The value of considering multiple fields (electrostatic, steric and hydrophobic) when performing molecular alignment and virtual screening -The importance of finding chemical diversity using in-silico technologies -Case study "What is the essence of a molecule? What is it made of? What will it do?" There is no single measure of similarity:

Strawberry Orange Basketball
Which Two Are More Similar ?
6 Structurally similar molecules tend to have similar properties: Problem: Subjective concept, with multiple ways of defining similarity The weighting of these descriptors • Mathematical expression of the similarity function.

NONSUPERPOSITIONAL
The analysis of atomic distances to a set of reference positions

SUPERPOSITIONAL Correct alignment is critical
Hydrophobicity vs Binding Affinity And Activity

Hydrophobic similarity coefficient
A correlation emerges between the pIC 50 / pK i and the global hydrophobic similarity index Explore correlations between activities and molecular similarity.
➢ As reference was used a ligand from a crystal structure external to the papers. ➢ Virtual screening with PharmScreen using hydrophobic and hydrogen bonds fields.
• Ligands with higher activity found in the initial results  -Reduces the search space in initial drug discovery stages -Can provide significant savings in a drug discovery project • Pharmacelera's field-based virtual screening technology: -Full 3D representation of all relevant fields of interaction (shape, electrostatic and hydrophobic) for molecular alignment AND similarity -Atomic-level LogP partitioning with semi-empirical quantum mechanical solvation models Interaction fields are chemotype agnostic → more chemical diversity found