A network-driven antiviral discovery pipeline for emerging RNA viruses: a critical perspective from the Red Mexicana de Desarrollo de Antivirales (RMDA)

INTRODUCTION: RNA viruses impose a disproportionate burden of emerging and reemerging infectious diseases in Latin America, yet antiviral discovery in the region remains fragmented, target-limited, and frequently disconnected from translational pathways. This perspective discusses the Red Mexicana de Desarrollo de Antivirales (RMDA) as a network-driven model to organize antiviral discovery against clinically relevant RNA viruses. AREAS COVERED: The authors describe the conceptual architecture of RMDA, a multi-institutional Mexican initiative that integrates computational prioritization, cell-based antiviral evaluation under BSL-2/BSL-3 conditions, mechanistic virology, assessment of pharmacological synergy, in vivo validation, and clinical linkage through healthcare systems such as the Instituto Mexicano del Seguro Social. The framework is supported by prior work from participating groups on host-directed and virus-directed candidates, including metabolic modulators, lipid-lowering agents, nuclear transport inhibitors, natural products, polyphenols, melatonin, and rational drug combinations evaluated against dengue virus, Zika virus, SARS-CoV-2, respiratory syncytial virus, and related RNA viruses. EXPERT OPINION: RMDA provides a scalable and regionally adaptable model for antiviral drug discovery in low- and middle-income settings. By aligning distributed expertise, standardized workflows, and translational decision points, this framework may accelerate candidate prioritization, reduce duplication, and strengthen preparedness against RNA virus threats in Mexico and Latin America.

Authors

Institutions

Publication Details

Journal
Expert Opinion on Drug Discovery
Published
2026-08-14
DOI
https://doi.org/10.1080/17460441.2026.2716137
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A network-driven antiviral discovery pipeline for emerging RNA viruses: a critical perspective from the Red Mexicana de Desarrollo de Antivirales (RMDA)

Alan Santos‐Mena, Luis Adrián De Jesús‐González, Carlos Noe Farfán-Morales, Carlos Daniel Cordero‐Rivera et al.
Expert Opinion on Drug Discovery
Computational Drug Discovery Methods
article

A network-driven antiviral discovery pipeline for emerging RNA viruses: a critical perspective from the Red Mexicana de Desarrollo de Antivirales (RMDA)

Alan Santos‐Mena, Luis Adrián De Jesús‐González, Carlos Noe Farfán-Morales, Carlos Daniel Cordero‐Rivera, Selvin Noé Palacios-Rápalo, Rosa María del Ángel, Juan Fidel Osuna‐Ramos, José Manuel Reyes-Ruíz, Flor Itzel Lira-Hernández, Moisés León-Juárez
article en

Abstract

INTRODUCTION: RNA viruses impose a disproportionate burden of emerging and reemerging infectious diseases in Latin America, yet antiviral discovery in the region remains fragmented, target-limited, and frequently disconnected from translational pathways. This perspective discusses the Red Mexicana de Desarrollo de Antivirales (RMDA) as a network-driven model to organize antiviral discovery against clinically relevant RNA viruses. AREAS COVERED: The authors describe the conceptual architecture of RMDA, a multi-institutional Mexican initiative that integrates computational prioritization, cell-based antiviral evaluation under BSL-2/BSL-3 conditions, mechanistic virology, assessment of pharmacological synergy, in vivo validation, and clinical linkage through healthcare systems such as the Instituto Mexicano del Seguro Social. The framework is supported by prior work from participating groups on host-directed and virus-directed candidates, including metabolic modulators, lipid-lowering agents, nuclear transport inhibitors, natural products, polyphenols, melatonin, and rational drug combinations evaluated against dengue virus, Zika virus, SARS-CoV-2, respiratory syncytial virus, and related RNA viruses. EXPERT OPINION: RMDA provides a scalable and regionally adaptable model for antiviral drug discovery in low- and middle-income settings. By aligning distributed expertise, standardized workflows, and translational decision points, this framework may accelerate candidate prioritization, reduce duplication, and strengthen preparedness against RNA virus threats in Mexico and Latin America.

Expert Opinion on Drug Discovery
Universidad Veracruzana (MX), Institut Pasteur (FR), Mexican Social Security Institute (MX), Universidad Autónoma de Sinaloa (MX), Université Paris Cité (FR), Instituto Nacional de Perinatología (MX), Centre of Advanced Studies (RU), Instituto Politécnico Nacional (MX)
Consejo Nacional de Ciencia y Tecnología, Fundación IMSS
Openalex Percentile: Top 8%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.