<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-18T07:17:53Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2445/225051" metadataPrefix="oai_dc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2445/225051</identifier><datestamp>2026-04-08T14:42:53Z</datestamp><setSpec>com_2072_1057</setSpec><setSpec>col_2072_478917</setSpec><setSpec>col_2072_478924</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>Quantum mechanical-based strategies in drug discovery: Finding the pace to new challenges in drug design</dc:title>
   <dc:creator>Ginex, Tiziana</dc:creator>
   <dc:creator>Vázquez Lozano, Javier</dc:creator>
   <dc:creator>Estarellas, Carolina</dc:creator>
   <dc:creator>Luque Garriga, F. Xavier</dc:creator>
   <dc:subject>Disseny de medicaments</dc:subject>
   <dc:subject>Bioquímica quàntica</dc:subject>
   <dc:subject>Drug design</dc:subject>
   <dc:subject>Quantum biochemistry</dc:subject>
   <dc:description>The expansion of the chemical space to tangible libraries containing billions of synthesizable molecules opens exciting opportunities for drug discovery, but also challenges the power of computer-aided drug design to prioritize the best candidates. This directly hits quantum mechanics (QM) methods, which provide chemically accurate properties, but subject to small- sized systems. Preserving accuracy while optimizing the computational cost is at the heart of many efforts to develop high-quality, efficient QM-based strategies, reflected in refined algorithms and computational approaches. The design of QM- tailored physics-based force fields and the coupling of QM with machine learning, in conjunction with the computing perfor- mance of supercomputing resources, will enhance the ability to use these methods in drug discovery. The challenge is formi- dable, but we will undoubtedly see impressive advances that will define a new era. </dc:description>
   <dc:date>2025-12-18T12:06:18Z</dc:date>
   <dc:date>2025-12-18T12:06:18Z</dc:date>
   <dc:date>2024-06-04</dc:date>
   <dc:date>2025-12-18T12:06:18Z</dc:date>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:identifier>0959-440X</dc:identifier>
   <dc:identifier>https://hdl.handle.net/2445/225051</dc:identifier>
   <dc:identifier>749047</dc:identifier>
   <dc:identifier>38914031</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>Reproducció del document publicat a: https://doi.org/10.1016/j.sbi.2024.102870</dc:relation>
   <dc:relation>Current Opinion in Structural Biology, 2024, vol. 87</dc:relation>
   <dc:relation>https://doi.org/10.1016/j.sbi.2024.102870</dc:relation>
   <dc:rights>cc-by-nc (c) Ginex, Tiziana et al., 2024</dc:rights>
   <dc:rights>http://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:format>9 p.</dc:format>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>Elsevier</dc:publisher>
   <dc:source>Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)</dc:source>
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