Marco Pistolozzi

dblp:209/7646 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1

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
1 paper
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 › drug discovery › drug design
computer-aided drug design
0.312017
HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques · Bioinform. 2017
Bioinformatics and computational biology › molecular informatics › cheminformatics
molecular similarity
0.312017
HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques · Bioinform. 2017
Bioinformatics and computational biology › drug discovery
virtual screening
0.312017
HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques · Bioinform. 2017
Bioinformatics and computational biology › molecular informatics
cheminformatics
0.112017
HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques · Bioinform. 2017

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

3d shape similarity · 0.32d fingerprint similarity · 0.3
YearPublicationVenuePosition
2017 HybridSim-VS: a web server for large-scale ligand-based virtual screening using hybrid similarity recognition techniques
abstract
SUMMARY: Molecular-similarity searches based on two-dimensional (2D) fingerprint and three-dimensional (3D) shape represent two widely used ligand-based virtual screening (VS) methods in computer-aided drug design. 2D fingerprint-based VS utilizes the binary fragment information on a known ligand, whereas 3D shape-based VS takes advantage of geometric information for predefined features from a 3D conformation. Given their different advantages, it would be desirable to hybridize 2D fingerprint and 3D shape molecular-similarity approaches in drug discovery. Here, we presented a general hybrid molecular-similarity protocol, referred to as HybridSim, obtained by combining the 2D fingerprint- and 3D shape-based similarity search methods and evaluated its performance on 595,036 actives and decoys for 40 pharmaceutically relevant targets available in the Directory of Useful Decoys Enhanced (DUD-E). Our results showed that HybridSim significantly improved the overall performance in 40 VS projects as compared with using only 2D fingerprint and 3D shape methods. Furthermore, HybridSim-VS, the first online platform using the proposed HybridSim method coupled with 17,839,945 screenable and purchasable compounds, was developed to provide large-scale and proficient VS capabilities to experts and nonexperts in the field. AVAILABILITY AND IMPLEMENTATION: HybridSim-VS web server is freely available at http://www.rcidm.org/HybridSim-VS/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jinling Shang, Xi Dai, Yecheng Li, Marco Pistolozzi, Ling Wang 0008
Bioinform.4