Evidence map›Paper›PMID 42222671›Full record

ArticleBioinformatics advances2026

LiraSearch-ultrafast ligand shape and electrostatic matching server.

Rinaldo W Montalvão, Simon Bray, Marcos Veríssimo-Alves, Elena Cubero, Björn Grüning, Vitor B Pinheiro

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Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rinaldo W MontalvãoGain Therapeutics Sucursal España, Gain Therapeutics, Barcelona Science Park, Barcelona, 08028, Spain.ORCID https://orcid.org/0000-0003-0929-1863
Simon BrayGain Therapeutics Inc., Gain Therapeutics, Bethesda, MD 20814, USA.ORCID https://orcid.org/0000-0002-0621-6705
Marcos Veríssimo-AlvesPhysics Dept. - ICEx, Universidade Federal Fluminense, R. Des. Ellis Hermydio Figueira, Volta Redonda, RJ 27213-145, Brazil.ORCID https://orcid.org/0000-0002-8954-3196
Elena CuberoGain Therapeutics Sucursal España, Gain Therapeutics, Barcelona Science Park, Barcelona, 08028, Spain.ORCID https://orcid.org/0000-0002-2239-6670
Björn GrüningBioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, 79110, Germany.ORCID https://orcid.org/0000-0002-3079-6586
Vitor B PinheiroRega Institute for Medical Research, KU Leuven, Leuven, Flemish Brabant 3000, Belgium.ORCID https://orcid.org/0000-0003-2491-0028

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID42222671
PMCPMC13221974

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.