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Gerard Pujadas

dblp:89/3533 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0003-2598-8089ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein structure prediction
decoy generation
0.112012
DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets · Bioinform. 2012
Bioinformatics and computational biology
drug discovery
0.112012
DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets · Bioinform. 2012
Bioinformatics and computational biology › drug discovery
virtual screening
0.112012
DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets · Bioinform. 2012
Bioinformatics and computational biology › molecular informatics › molecular modeling
molecular docking
0.112006
BDT: an easy-to-use front-end application for automation of massive docking tasks and complex docking strategies with AutoDock · Bioinform. 2006

Methods — techniques the papers use, named apart from their topics

tanimoto coefficient · 0.1physical descriptors · 0.1MACCS fingerprints · 0.1autogrid · 0.1autodock · 0.1
YearPublicationVenuePosition
2024 Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery
abstract
This opinion article addresses a major issue in molecular biology and drug discovery by highlighting the complications that arise from combining polyproteins and their functional products within the same database entry. This problem, exemplified by the discovery of novel inhibitors for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease, has an influence on our ability to retrieve precise data and hinders the development of targeted therapies. It also emphasizes the need for improved database practices and underscores their significance in advancing scientific research. Furthermore, it emphasizes the need of learning from the SARS-CoV-2 pandemic in order to improve global preparedness for future health crises.
Ariadna Llop-Peiró, Gerard Pujadas, Santiago Garcia-Vallvé
Briefings Bioinform.2
2012 DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets
abstract
UNLABELLED: Decoys are molecules that are presumed to be inactive against a target (i.e. will not likely bind to the target) and are used to validate the performance of molecular docking or a virtual screening workflow. The Directory of Useful Decoys database (http://dud.docking.org/) provides a free directory of decoys for use in virtual screening, though it only contains a limited set of decoys for 40 targets.To overcome this limitation, we have developed an application called DecoyFinder that selects, for a given collection of active ligands of a target, a set of decoys from a database of compounds. Decoys are selected if they are similar to active ligands according to five physical descriptors (molecular weight, number of rotational bonds, total hydrogen bond donors, total hydrogen bond acceptors and the octanol-water partition coefficient) without being chemically similar to any of the active ligands used as an input (according to the Tanimoto coefficient between MACCS fingerprints). To the best of our knowledge, DecoyFinder is the first application designed to build target-specific decoy sets. AVAILABILITY: A complete description of the software is included on the application home page. A validation of DecoyFinder on 10 DUD targets is provided as Supplementary Table S1. DecoyFinder is freely available at http://URVnutrigenomica-CTNS.github.com/DecoyFinder.
Adrià Cereto-Massagué, Laura Guasch, Cristina Valls, Miquel Mulero, Gerard Pujadas, Santiago Garcia-Vallvé
Bioinform.5
2006 BDT: an easy-to-use front-end application for automation of massive docking tasks and complex docking strategies with AutoDock
abstract
MOTIVATION: AutoGrid/AutoDock is one of the most popular software packages for docking, but its automation is not trivial for tasks such as (1) the virtual screening of a library of ligands against a set of possible receptors; (2) the use of receptor flexibility and (3) making a blind-docking experiment with the whole receptor surface. This is an obstacle for research teams in the fields of Chemistry and the Life Sciences who are interested in conducting this kind of experiment but do not have enough programming skills. To overcome these limitations, we have designed BDT, an easy-to-use graphic interface for AutoGrid/AutoDock. AVAILABILITY: BDT is available for free, upon request, for non-commercial research.
Montserrat Vaqué, Anna Arola-Arnal, Carles Aliagas, Gerard Pujadas
Bioinform.4