Identificaci\'on de nuevos medicamentos a trav\'es de m\'etodos computacionales

TL;DR

This paper proposes a computational methodology for in silico drug discovery to address the challenges of handling large, distributed data sources in developing new medications.

Contribution

It introduces a novel in silico methodology for drug identification that manages large, distributed datasets, filling a gap in existing computational tools.

Findings

Developed a new in silico drug discovery methodology

Addresses data handling across multiple databases

Facilitates faster drug identification processes

Abstract

Resumen: El desarrollo de nuevos medicamentos es un problema complejo que carece de una soluci\'on \'unica y autom\'atica desde un punto de vista computacional, debido a la carencia de programas que permitan manejar grandes vol\'umenes de informaci\'on que est\'an distribuidos a lo largo de todo el mundo entre m\'ultiples bases de datos. Por ello se describe una metodolog\'ia que permita realizar experimentos in silico para la identificaci\'on actual de nuevos medicamentos. Abstract: The development of new drugs is a problem that nowadays has no solution in terms of computational power due to the lack of software for handling the big volume of available information; besides, these data are stored in multiple formats and are distributed all around the world. To resolve that, a development of an in silico drug design methodology.