Prof. Marcelo Marti holds a Ms.S. in Molecular Biology and a PhD in Theoretical Chemistry and Biophysics, both at the University of Buenos Aires. He is a Full Professor at the Department of Biological Chemistry (Universidad de Buenos Aires) and a Principal Researcher at the Argentinean Council of Science. His research interests lie in understanding the molecular basis of protein functions and genomics using bioinformatic tools. He has published over 100 articles in top ranked international journals in the field including over 3000 citations (h index = 33).

Prof. Turjanski is a Full Professor in Bioinformatics at the University of Buenos Aires and a Principal Researcher at the Argentinean Council of Science. He obtained his PhD in Chemistry at the University of Buenos Aires and obtained a PhD position at the Fogarty Center at NIH, 2005-2008.

He has been the head of the National Center for Interdisciplinary Science, at the Ministry of Sciences and Technology, Facultad de Ciencias Exactas y Naturales from 2015-2019, and the head of the Binational Center of Bioinformatics (Argentina/Spain). He was a member of the Argentinian Committee at the European Molecular Biology Lab and the head of the Argentinian Bioinformatics Platform since 2012. He has published over 100 indexed articles, with a h-index of 25.

Dr. Fernandez Do Porto holds a degree in Biology and a PhD in Biological Chemistry, both from the University of Buenos Aires. His research interests focus on pathogen genomics, integrating omics data, and structural and functional bioinformatics for drug discovery. He is an Independent researcher at the Argentinean Council of Science and a Full Professor in the Biological Chemistry department, Exact and Natural Sciences School, Buenos Aires University. He has published over 40 indexed articles.

Prioritizing Drug Targets in Pathogenic Bacteria by Harnessing Structural Biology, Metabolic Analysis, and Omics Data Integration.- Regulatory small RNAs as antimicrobial drug targets.- Riboswitches as antimicrobial targets.- Pre-selection of compounds for lead identification in virtual screening campaigns.- Docking and Bias Docking.- Molecular Dynamics and its Significance in Drug Discovery.- Deep Learning Strategies for Enhanced Molecular Docking and Virtual Screening.- Integrating computational approaches from non-synonymous sequence variations to molecular structure for drug repositioning targeting the SARS-CoV-2 Spike protein.