DockingVersus Pharmacophore Model Generation: A Comparison of High-Throughput Virtual Screening Strategies for the Search of Human Rhinovirus Coat Protein Inhibitors

Abstract

Inhibition of the human rhinovirus coat protein is an intensively studied approach towards finding a therapy for common cold. We present the results of a docking study using the tool LigandFit and a database of 1000 drug-like compounds seeded with known active HRV coat protein inhibitors. One scoring function performed especially well in ranking the active molecules at high positions. The conformations and positions from the docking process were found to be in good agreement with the X-ray data. Furthermore, highly selective pharmacophore hypotheses were generated in a structure-based approach. They include information on necessary chemical functions as well as on the required shape. When applied in 3D database screening, they selectively retrieved compounds with known antirhinoviral activity from large data sets. We compare these two virtual screening methods and summarise their benefits but also the observed disadvantages. Finally, a focussed virtual library for a special class of rhinovirus coat protein inhibitors was generated with our novel tool ilib diverse and screened with the pharmacophore models described.

Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets

“…Several studies have been performed to assess various DBVS methods and compare which docking programs are the most successful in identifying active hits [7][8][9][10] . The conclusion is that no docking program may outperform other docking programs for all the tested targets, and the performance of each tested docking program is highly dependent on the nature of the target binding site [5] .Nevertheless, few case studies for a direct comparison on the performances between PBVS and DBVS have been reported [11] . To gain a general view for the discrimination between these two types of approach in prioritizing actives from a database with decoys, we performed a benchmark comparison between the performances of PBVS and DBVS.…”

“…Nevertheless, few case studies for a direct comparison on the performances between PBVS and DBVS have been reported [11] . To gain a general view for the discrimination between these two types of approach in prioritizing actives from a database with decoys, we performed a benchmark comparison between the performances of PBVS and DBVS.…”

Pharmacophore Modelling: A Forty Year Old Approach and its Modern Synergies

“…Perhaps the major drawback of ligand-based pharmacophores is that they are always dependent on the properties of already known ligands [16], whereas hot spot derived structure-based pharmacophores are only indirectly influenced by existing ligands if holo protein structures are used to identify the hot spots. Moreover, the hot spot analysis may cover the entire binding site, regardless of the portion occupied by known co-complexed ligands, thus leading to the possibility of selecting structurally diverse inhibitors.…”

“…When used as search queries, ligand-based pharmacophores search for compounds with a threedimensional arrangement of chemical functionalities (i.e. pharmacophoric features) common to known active ligands, thus potentially preventing the exploration of new favourable interaction patterns unsatisfied by existing ligands [15,16]. However, potential hits or leads identified through pharmacophore-based methods must be experimentally tested to assess their biological activity.…”

Current Status of Virtual Screening as Analysed by Target Class

“…Several recent comparisons of ligand-based and structure based methods [3,[5][6][7][8][9][10][11] have been published, along with comparisons of virtual screening and HTS [12][13][14][15][16][17][18][19][20]. This review also does not cover the multitude of papers over the last decade where docking of a few synthesised inhibitors is used to attempt to rationalise relative binding potencies, or the considerable ongoing effort in validating both the docking methodologies themselves and the subsequent scoring and ranking of hits.…”