Literature DB >> 24564321

Hsp90 inhibitors, part 1: definition of 3-D QSAutogrid/R models as a tool for virtual screening.

Flavio Ballante1, Antonia Caroli, Richard B Wickersham, Rino Ragno.   

Abstract

The multichaperone heat shock protein (Hsp) 90 complex mediates the maturation and stability of a variety of oncogenic signaling proteins. For this reason, Hsp90 has emerged as a promising target for anticancer drug development. Herein, we describe a complete computational procedure for building several 3-D QSAR models used as a ligand-based (LB) component of a comprehensive ligand-based (LB) and structure-based (SB) virtual screening (VS) protocol to identify novel molecular scaffolds of Hsp90 inhibitors. By the application of the 3-D QSAutogrid/R method, eight SB PLS 3-D QSAR models were generated, leading to a final multiprobe (MP) 3-D QSAR pharmacophoric model capable of recognizing the most significant chemical features for Hsp90 inhibition. Both the monoprobe and multiprobe models were optimized, cross-validated, and tested against an external test set. The obtained statistical results confirmed the models as robust and predictive to be used in a subsequent VS.

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Year:  2014        PMID: 24564321     DOI: 10.1021/ci400759t

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  7 in total

1.  Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches.

Authors:  Rino Ragno; Flavio Ballante; Adele Pirolli; Richard B Wickersham; Alexandros Patsilinakos; Stéphanie Hesse; Enrico Perspicace; Gilbert Kirsch
Journal:  J Comput Aided Mol Des       Date:  2015-07-21       Impact factor: 3.686

Review 2.  Heat Shock Protein 90 (HSP90) Inhibitors as Anticancer Medicines: A Review on the Computer-Aided Drug Discovery Approaches over the Past Five Years.

Authors:  Ayanda M Magwenyane; Samuel C Ugbaja; Daniel G Amoako; Anou M Somboro; Rene B Khan; Hezekiel M Kumalo
Journal:  Comput Math Methods Med       Date:  2022-05-31       Impact factor: 2.809

3.  Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants.

Authors:  Nezrina Kurtanović; Nevena Tomašević; Sanja Matić; Elenora Proia; Manuela Sabatino; Lorenzo Antonini; Milan Mladenović; Rino Ragno
Journal:  Molecules       Date:  2022-04-28       Impact factor: 4.927

4.  Disruptor of telomeric silencing 1-like (DOT1L): disclosing a new class of non-nucleoside inhibitors by means of ligand-based and structure-based approaches.

Authors:  Manuela Sabatino; Dante Rotili; Alexandros Patsilinakos; Mariantonietta Forgione; Daniela Tomaselli; Fréderic Alby; Paola B Arimondo; Antonello Mai; Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2018-01-15       Impact factor: 3.686

5.  Prediction of new Hsp90 inhibitors based on 3,4-isoxazolediamide scaffold using QSAR study, molecular docking and molecular dynamic simulation.

Authors:  Maryam Abbasi; Hojjat Sadeghi-Aliabadi; Massoud Amanlou
Journal:  Daru       Date:  2017-06-30       Impact factor: 3.117

6.  Targeting the anti-apoptotic Bcl-2 family proteins: machine learning virtual screening and biological evaluation of new small molecules.

Authors:  Elisabetta Valentini; Simona D'Aguanno; Marta Di Martile; Camilla Montesano; Virginia Ferraresi; Alexandros Patsilinakos; Manuela Sabatino; Lorenzo Antonini; Martina Chiacchiarini; Sergio Valente; Antonello Mai; Gianni Colotti; Rino Ragno; Daniela Trisciuoglio; Donatella Del Bufalo
Journal:  Theranostics       Date:  2022-02-28       Impact factor: 11.556

7.  Hsp90 inhibitors, part 2: combining ligand-based and structure-based approaches for virtual screening application.

Authors:  Antonia Caroli; Flavio Ballante; Richard B Wickersham; Federico Corelli; Rino Ragno
Journal:  J Chem Inf Model       Date:  2014-03-04       Impact factor: 4.956

  7 in total

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