RESEARCH & DEVELOPMENT
Advanced Computational Drug Discovery Tools Through user friendly web servers
The discovery of new drugs is a very slow and costly process, but advanced computational drug discovery techniques can drastically speed it up. However, such tools are very complicated for nonexpert users. We provide an overview about how user friendly web servers can dramatically help them. Antonio J Banegas-Luna, Bioinformatics and High Performance Computing Research Group (BIO-HPC), Universidad Católica San Antonio de Murcia (UCAM) Maria Paredes-Ramos, PhD student, Metals in Environment and Medicine (METMED), Physical Chemistry Department, Universidade de Courña(UDC) Marién M Moreno, Bioinformatics and High Performance Computing Research Group (BIO-HPC), Universidad Católica San Antonio de Murcia (UCAM) Josefina M Vegara-Meseguer, Bioinformatics and High Performance Computing Research Group (BIO-HPC), Higher Polytechnic School, Universidad Católica San Antonio de Murcia (UCAM) Horacio Pérez-Sánchez, Principal Investigator, Bioinformatics and High Performance Computing Research Group (BIO-HPC), Universidad Católica San Antonio de Murcia (UCAM)
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rug discovery is one of the most time- and cost-consuming processes in the industry. From active pharmaceutical ingredients (API) discovery to final approval it involves a total duration of 10 – 15 years (Figure 1) and US$1 – US$2 billion investment. After the protein target identification, the search for a specific drug-like molecule that matches the binding site is an arduous process which requires the screening of hundreds of molecules to test their bioactivity. Employing an experimental trial-and-error procedure, this task would take years to be accomplished. Thus, during the past few decades, different theoretical approaches based on quantum and molecular mechanics have been developed to simulate and test real systems before entering the laboratory.
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P H A RM A F O C U S A S I A
ISSUE 38 - 2020
The explosion of biotechnology resources has enabled the disease process to be better understood and evaluated for drug targets. So, nowadays, drug design cannot be imagined without computational aided methodologies such as CADD. Therefore, CADD has gained importance in the pharmaceutical industry, at research centres, and universities. CADD involves techniques such as molecular docking or virtual screening, which are employed to inspect the binding poses of a ligand (or a database of ligands) on a particular receptor. Despite being much more efficient than the aforementioned experimental ones by far, these procedures require large calculations and extensive chemical data repositories to simulate their highly complicated systems. Hence, its
related computational cost, in terms of memory and processing capacity, is huge. Accordingly, to transcend computing barriers of the traditional personal computers (PCs), high-performance computing systems have been developed. High Performance Computing (HPC) is the application typically used for solving advanced computational problems that are too large for standard computers and performing research activities through computer modeling, simulation and analysis. Computer-aided drug discovery methodologies have become essential components of the drug discovery and Virtual Screening (VS) methodologies have emerged as efficient alternatives for the discovery of new drug candidates. Protein-ligand interactions are common targets for medicine. Refining
