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Updated: Jun 18, 2026

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro
Published on: September 26, 2025
Multiobjective optimization of pharmacophore hypotheses: bias toward low-energy conformations
Eleanor J Gardiner1, David A Cosgrove, Robin Taylor
1Department of Information Studies, University of Sheffield, Regent Court, 211 Portobello Street, Sheffield S1 4DP, United Kingdom. e.gardiner@sheffield.ac.uk
Abstract:
Two methods are described for biasing conformational search during pharmacophore elucidation using a multiobjective genetic algorithm (MOGA). The MOGA explores conformation on-the-fly while simultaneously aligning a set of molecules such that their pharmacophoric features are maximally overlaid. By using a clique detection method to generate overlays of precomputed conformations to initialize the population (rather than starting from random), the speed of the algorithm has been increased by 2 orders of magnitude. This increase in speed has enabled the program to be applied to greater numbers of molecules than was previously possible. Furthermore, it was found that biasing the conformations explored during search time to those found in the Cambridge Structural Database could also improve the quality of the results.
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