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Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Spontaneous mutations arise infrequently during DNA replication due to errors in the process. A key factor behind these errors is tautomeric shifts in nitrogenous bases, where bases transition from keto to enol forms or amino to imino forms. This shift can alter base-pairing rules, leading to mutations. Additionally, reactive oxygen species (ROS) arising from aerobic metabolism can damage DNA, resulting in depurination (loss of a purine base) or depyrimidination (loss of a pyrimidine base).
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Benchmarking de Operadores de Mutación Molecular para el Diseño Evolutivo de Fármacos

Raúl Acosta Murillo1, Patricio Adrián Zapata-Morin1, José Carlos Ortiz-Bayliss2

  • 1Department of Microbiology and Immunology, School of Biological Sciences, Universidad Autónoma de Nuevo León, Pedro de Alba SN, San Nicolás de los Garza 66455, Nuevo Leon, Mexico.

International journal of molecular sciences
|December 11, 2025
PubMed
Resumen

La elección de la estrategia de mutación molecular adecuada es clave para el diseño de fármacos impulsado por IA. El Algoritmo Genético Basado en Grafos ofrece alta validez y eficiencia, mientras que otros impactan la complejidad molecular y la bioactividad de manera diferente.

Palabras clave:
diseño de fármacos asistido por computadoraoperadores genéticosmutación de moléculasrecombinación de moléculas

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Área de la Ciencia:

  • Química computacional
  • Bioinformática
  • Descubrimiento de fármacos

Sus antecedentes:

  • Los algoritmos genéticos son herramientas poderosas para el diseño de fármacos.
  • Los operadores de mutación molecular son cruciales para explorar el espacio químico.
  • La optimización de estos operadores mejora la eficiencia del descubrimiento de fármacos impulsado por IA.

Objetivo del estudio:

  • Comparar cinco estrategias de mutación molecular para algoritmos genéticos en el diseño de fármacos.
  • Evaluar su eficiencia computacional, validez molecular e impacto en la complejidad.
  • Evaluar su influencia en la bioactividad y la conservación estructural.

Principales métodos:

  • Se evaluó el Algoritmo Genético Basado en Grafos, el Modelo Generativo Basado en Grafos, SmilesClickChem, el Token SELFIES y la Mutación de Token SMILES.
  • Se evaluó la eficiencia computacional, la validez molecular, la complejidad y la conservación estructural.
  • Se analizaron los cambios inducidos por la mutación en la potencia pIC50 y la bioactividad.

Principales resultados:

  • El Algoritmo Genético Basado en Grafos mostró la mayor validez molecular (96,5%) y eficiencia.
  • SmilesClickChem y el Modelo Generativo Basado en Grafos aumentaron la complejidad molecular.
  • El Token SELFIES alteró significativamente la bioactividad, especialmente para las moléculas dirigidas a SRC.

Conclusiones:

  • La elección de la estrategia de mutación impacta los resultados del diseño de fármacos, equilibrando validez, diversidad y costo.
  • El Algoritmo Genético Basado en Grafos es adecuado para el descubrimiento rápido de fármacos.
  • Los hallazgos guían el refinamiento de algoritmos evolutivos para la generación molecular y la selección de candidatos.