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Computer-aided approaches for human norovirus drug discovery: a comprehensive review

Giuseppe Palazzo, Salvatore Ferla Orcid Logo, Marcella Bassetto

Expert Opinion on Drug Discovery, Volume: 20, Issue: 12, Pages: 1589 - 1606

Swansea University Authors: Giuseppe Palazzo, Salvatore Ferla Orcid Logo

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DOI (Published version): 10.1080/17460441.2025.2601118

Abstract

Introduction: Human norovirus is the leading global cause of viral acute gastroenteritis, with an estimated ~685 million cases and ~200,000 deaths annually. No licensed antivirals or vaccines are currently available. Despite historical limitations in robust in vitro models, structure and ligand-base...

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Published in: Expert Opinion on Drug Discovery
ISSN: 1746-0441 1746-045X
Published: Informa UK Limited 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa71235
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last_indexed 2026-01-14T05:32:56Z
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spelling 2026-01-13T11:46:46.2628125 v2 71235 2026-01-13 Computer-aided approaches for human norovirus drug discovery: a comprehensive review 9775f22a8c2879b1722cfc4b995faed3 Giuseppe Palazzo Giuseppe Palazzo true false d4c62248f510e3b221916989a7bbe6a6 0000-0002-5918-9237 Salvatore Ferla Salvatore Ferla true false 2026-01-13 MEDS Introduction: Human norovirus is the leading global cause of viral acute gastroenteritis, with an estimated ~685 million cases and ~200,000 deaths annually. No licensed antivirals or vaccines are currently available. Despite historical limitations in robust in vitro models, structure and ligand-based computational approaches – supported by protease and polymerase crystal structures – have identified multiple chemotypes as potential antivirals. Areas covered: This review provides an overview of all studies reported to date, indexed in public databases, in which computer-aided drug discovery (CADD) techniques have been employed. The authors report the computational methodologies used, the chemical structures of the identified compounds, and, if available, their biological activities. Where in silico results lack experimental validation, the authors highlight limitations and propose minimal validation assays. Expert opinion: The absence of 3D structures for most viral proteins has limited the identification of novel chemotypes through CADD approaches. Furthermore, the lack of biological validation after in silico studies may slow down progress in this field, as researchers might focus on compounds that seem promising only at the computational level. Emerging systems such as human intestinal enteroids, together with AI/ML augmented CADD, can accelerate optimization and triage of non-nucleoside and covalent protease inhibitors. Journal Article Expert Opinion on Drug Discovery 20 12 1589 1606 Informa UK Limited 1746-0441 1746-045X Norovirus, antiviral-research, computer-aided drug discovery, medicinal chemistry, structure-based drug design 11 12 2025 2025-12-11 10.1080/17460441.2025.2601118 Review COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee G.P. is supported by an EPSRC PhD studentship. 2026-01-13T11:46:46.2628125 2026-01-13T11:33:36.9583375 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Pharmacy Giuseppe Palazzo 1 Salvatore Ferla 0000-0002-5918-9237 2 Marcella Bassetto 3 71235__35978__121c142fa24048208ba1075d410cd31a.pdf 71235.VOR.pdf 2026-01-13T11:37:56.1236100 Output 4658546 application/pdf Version of Record true © 2025 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Computer-aided approaches for human norovirus drug discovery: a comprehensive review
spellingShingle Computer-aided approaches for human norovirus drug discovery: a comprehensive review
Giuseppe Palazzo
Salvatore Ferla
title_short Computer-aided approaches for human norovirus drug discovery: a comprehensive review
title_full Computer-aided approaches for human norovirus drug discovery: a comprehensive review
title_fullStr Computer-aided approaches for human norovirus drug discovery: a comprehensive review
title_full_unstemmed Computer-aided approaches for human norovirus drug discovery: a comprehensive review
title_sort Computer-aided approaches for human norovirus drug discovery: a comprehensive review
author_id_str_mv 9775f22a8c2879b1722cfc4b995faed3
d4c62248f510e3b221916989a7bbe6a6
author_id_fullname_str_mv 9775f22a8c2879b1722cfc4b995faed3_***_Giuseppe Palazzo
d4c62248f510e3b221916989a7bbe6a6_***_Salvatore Ferla
author Giuseppe Palazzo
Salvatore Ferla
author2 Giuseppe Palazzo
Salvatore Ferla
Marcella Bassetto
format Journal article
container_title Expert Opinion on Drug Discovery
container_volume 20
container_issue 12
container_start_page 1589
publishDate 2025
institution Swansea University
issn 1746-0441
1746-045X
doi_str_mv 10.1080/17460441.2025.2601118
publisher Informa UK Limited
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Pharmacy{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Pharmacy
document_store_str 1
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description Introduction: Human norovirus is the leading global cause of viral acute gastroenteritis, with an estimated ~685 million cases and ~200,000 deaths annually. No licensed antivirals or vaccines are currently available. Despite historical limitations in robust in vitro models, structure and ligand-based computational approaches – supported by protease and polymerase crystal structures – have identified multiple chemotypes as potential antivirals. Areas covered: This review provides an overview of all studies reported to date, indexed in public databases, in which computer-aided drug discovery (CADD) techniques have been employed. The authors report the computational methodologies used, the chemical structures of the identified compounds, and, if available, their biological activities. Where in silico results lack experimental validation, the authors highlight limitations and propose minimal validation assays. Expert opinion: The absence of 3D structures for most viral proteins has limited the identification of novel chemotypes through CADD approaches. Furthermore, the lack of biological validation after in silico studies may slow down progress in this field, as researchers might focus on compounds that seem promising only at the computational level. Emerging systems such as human intestinal enteroids, together with AI/ML augmented CADD, can accelerate optimization and triage of non-nucleoside and covalent protease inhibitors.
published_date 2025-12-11T05:33:35Z
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