LiraSearch — ultrafast ligand shape and electrostatic matching server

Clicks: 27
ID: 314140
2026
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Abstract
Abstract Summary Spherical harmonics have emerged as a powerful framework for molecular shape and electrostatic comparison in ligand-based virtual screening. Here, we present LiraSearch, a high-performance implementation and web server that uses spherical harmonics expansions to encode and compare three-dimensional (3D) molecular shapes and electrostatic potential (ESP) surfaces of drug-like compounds. Molecular surfaces are transformed into compact, low-dimensional spherical harmonics descriptors that capture both geometric and electrostatic features. These descriptors enable rapid similarity calculations between query molecules and large compound libraries while exploiting the rotational invariance of spherical harmonics to avoid explicit alignment. The representation is robust to moderate conformational variation and is effective at identifying structurally diverse active compounds sharing similar pharmacophoric patterns, facilitating scaffold hopping in ligand discovery workflows. Previous studies have shown that spherical harmonic surface representations achieve high retrieval performance with relatively low expansion orders and compact descriptors. By integrating these representations into an efficient screening pipeline, LiraSearch enables rapid similarity searches across ultralarge chemical libraries while preserving both geometric and electrostatic fidelity. This framework provides a scalable, mathematically rigorous approach to ligand similarity searching and can support early-stage hit discovery as well as downstream applications, such as protein–ligand docking and structure-based pharmacophore modelling. Availability and implementation LiraSearch is a set of open-source programs developed in C/C ++, Python and Julia. The source code is available at https://github.com/gaintherapeutics/LiraSearch, and the server is at https://usegalaxy.eu/? tool\_id=lirasearch. Supplementary information Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7161720104 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Rinaldo W. Montalvão, Simon Bray, Marcos Veríssimo-Alves, Elena Cubero, Björn Grüning, Vitor B. Pinheiro
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag139
URL
https://doi.org/10.1093/bioadv/vbag139
Keywords Keywords not found

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