In silico Thermodynamic Evaluation of the Effectiveness of RT-LAMP Primers for SARS-CoV-2 Variants Detection

Pâmella Miranda1, 2, *, Pedro A. Alves3, 4, Rubens L. do Monte-Neto3, Gerald Weber1
1 Departamento de Fı́sica, Universidade Federal de Minas Gerais, Belo Horizonte-MG, Brazil
2 Programa Interunidades de Pós-Graduação em Bioinformática, Universidade Federal de Minas Gerais, Belo Horizonte-MG, Brazil
3 Instituto René Rachou – Fundação Oswaldo Cruz, Belo Horizonte-MG, Brazil
4 Centro de Tecnologia em Vacinas, Belo Horizonte-MG, Brazil

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Creative Commons License
© 2024 The Author(s). Published by Bentham Open.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Departamento de Fı́sica, Universidade Federal de Minas Gerais, Belo Horizonte-MG, Brazil; E-mail:



Viral mutations are the primary cause of mismatches in primer-target hybridisation, affecting the sensibility of molecular techniques, and potentially leading to detection dropouts. Despite its importance, little is known about the quantitative effect of mismatches in primer-target hybridisation. We have used up-to-date and highly detailed thermodynamic model parameters of DNA mismatches to evaluate the sensibility to variants of SARS-CoV-2 RT-LAMP primers.


We aligned 18 RT-LAMP primer sets, which underwent clinical validation, to the genomes of the wild-type strain (ws), 7 variants and 4 subvariants, and calculated hybridisation temperatures allowing up to three consecutive mismatches. We calculated the coverage when the mismatched melting temperature fell by more than 5°C in comparison to the matched alignments. If no mismatches were considered, the average coverage found was 94% for ws, falling to the lowest value for Omicron, i.e., 84%.


However, considering mismatches, the coverage was much higher, i.e., 97% (ws) to 88% (Omicron). Stabilizing mismatches (higher melting temperatures) accounted for roughly 1/3 of this increase. The number of primer dropouts increased for each new variant; however, the effect was much less severe if mismatches were considered.


We suggest using melting temperature calculations to continuously assess the trend of primer dropouts.

Keywords: DNA mismatches, Diagnosis, LAMP primer design, SARS-CoV-2, DNA thermodynamic models, Melting temperature calculations.