Graph Laplacian spectral descriptors for alignment-free molecular shape and electrostatic comparison

Abstract

Shape-based virtual screening methods are widely used in drug discovery. Alignment-dependent approaches often provide high screening accuracy but are computationally expensive, whereas alignment-free methods are faster but generally less accurate. Here, we present GE-MolSG, a novel alignment-free molecular descriptor that combines shape and electrostatic information using spectral graph representations derived from the graph Laplacian. GE-MolSG outperforms the established alignment-free ElectroShape method and achieves performance comparable to ESP-Sim without requiring molecular alignment. To demonstrate the extensibility of the graph-based framework, we further explore a proof-of-concept patch-based extension termed GM-MolSG, which incorporates additional surface features. The graph-based formulation provides a flexible and extensible framework for incorporating surface-associated molecular properties into compact descriptors for rapid alignment-free similarity searching.

Metadata

Item Type:	Article
Authors/Creators:	Middleton, J. Ghiandoni, G.M. Packer, M.J. Zhuang, M. https://orcid.org/0000-0002-4546-1033 Gillet, V.J.
Copyright, Publisher and Additional Information:	© The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords:	Virtual screening; 3D; Shape; Graphs; Electrostatics
Dates:	Submitted: 6 June 2026 Accepted: 10 September 2026 Published (online): 20 October 2026 Published: 20 October 2026
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Information, Journalism and Communication
Funding Information:	Funder Grant number Engineering and Physical Sciences Research Council EP/T517835/1
Date Deposited:	11 Nov 2026 15:47
Last Modified:	11 Nov 2026 15:47
Status:	Published online
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1186/s13321-026-01310-6
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:247888

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Graph Laplacian spectral descriptors for alignment-free molecular shape and electrostatic comparison

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