Literature DB >> 31605102

DRUDIT: web-based DRUgs DIscovery Tools to design small molecules as modulators of biological targets.

Antonino Lauria1, Salvatore Mannino1, Carla Gentile1, Giuseppe Mannino1, Annamaria Martorana1, Daniele Peri2.   

Abstract

MOTIVATION: New in silico tools to predict biological affinities for input structures are presented. The tools are implemented in the DRUDIT (DRUgs DIscovery Tools) web service. The DRUDIT biological finder module is based on molecular descriptors that are calculated by the MOLDESTO (MOLecular DEScriptors TOol) software module developed by the same authors, which is able to calculate more than one thousand molecular descriptors. At this stage, DRUDIT includes 250 biological targets, but new external targets can be added. This feature extends the application scope of DRUDIT to several fields. Moreover, two more functions are implemented: the multi- and on/off-target tasks. These tools applied to input structures allow for predicting the polypharmacology and evaluating the collateral effects.
RESULTS: The applications described in the article show that DRUDIT is able to predict a single biological target, to identify similarities among biological targets, and to discriminate different target isoforms. The main advantages of DRUDIT for the scientific community lie in its ease of use by worldwide scientists and the possibility to be used also without specific, and often expensive, hardware and software. In fact, it is fully accessible through the WWW from any device to perform calculations. Just a click or a tap can start tasks to predict biological properties for new compounds or repurpose drugs, lead compounds, or unsuccessful compounds. To date, DRUDIT is supported by four servers each able to execute 8 jobs simultaneously.
AVAILABILITY AND IMPLEMENTATION: The web service is accessible at the www.drudit.com URL and its use is free of charge. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Year:  2020        PMID: 31605102     DOI: 10.1093/bioinformatics/btz783

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  6 in total

1.  In Silico Insights into the SARS CoV-2 Main Protease Suggest NADH Endogenous Defences in the Control of the Pandemic Coronavirus Infection.

Authors:  Annamaria Martorana; Carla Gentile; Antonino Lauria
Journal:  Viruses       Date:  2020-07-26       Impact factor: 5.048

2.  In Silico Identification of Small Molecules as New Cdc25 Inhibitors through the Correlation between Chemosensitivity and Protein Expression Pattern.

Authors:  Antonino Lauria; Annamaria Martorana; Gabriele La Monica; Salvatore Mannino; Giuseppe Mannino; Daniele Peri; Carla Gentile
Journal:  Int J Mol Sci       Date:  2021-04-02       Impact factor: 5.923

3.  The dimer-monomer equilibrium of SARS-CoV-2 main protease is affected by small molecule inhibitors.

Authors:  Lucia Silvestrini; Norhan Belhaj; Lucia Comez; Yuri Gerelli; Antonino Lauria; Valeria Libera; Paolo Mariani; Paola Marzullo; Maria Grazia Ortore; Antonio Palumbo Piccionello; Caterina Petrillo; Lucrezia Savini; Alessandro Paciaroni; Francesco Spinozzi
Journal:  Sci Rep       Date:  2021-04-29       Impact factor: 4.379

4.  Synthesis, biological evaluation, and in silico studies of novel chalcone- and pyrazoline-based 1,3,5-triazines as potential anticancer agents.

Authors:  Leydi M Moreno; Jairo Quiroga; Rodrigo Abonia; Antonino Lauria; Annamaria Martorana; Henry Insuasty; Braulio Insuasty
Journal:  RSC Adv       Date:  2020-09-15       Impact factor: 4.036

5.  Phytochemical Profile and Antioxidant, Antiproliferative, and Antimicrobial Properties of Rubus idaeus Seed Powder.

Authors:  Giuseppe Mannino; Graziella Serio; Raimondo Gaglio; Gabriele Busetta; Lorenza La Rosa; Antonino Lauria; Luca Settanni; Carla Gentile
Journal:  Foods       Date:  2022-08-27

6.  Off-Target-Based Design of Selective HIV-1 PROTEASE Inhibitors.

Authors:  Gabriele La Monica; Antonino Lauria; Alessia Bono; Annamaria Martorana
Journal:  Int J Mol Sci       Date:  2021-06-04       Impact factor: 5.923

  6 in total

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