2014
Antonia, Caroli; Flavio, Ballante; Richard B, Wickersham III; Federico, Corelli; Rino, Ragno
Hsp90 Inhibitors, Part 2: Combining Ligand-Based and Structure-Based Approaches for Virtual Screening Application Journal Article
In: Journal of Chemical Information and Modeling, 54 (3), pp. 970-977, 2014.
Abstract | Links | BibTeX | Tags: 3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Molecular Modeling, MPGRS, Pharmacophoric Model, PLS, Virtual Screening
@article{Caroli2014,
title = {Hsp90 Inhibitors, Part 2: Combining Ligand-Based and Structure-Based Approaches for Virtual Screening Application},
author = { Caroli Antonia and Ballante Flavio and Richard B, Wickersham III and Corelli Federico and Ragno Rino},
editor = {American Chemical Society},
url = {http://pubs.acs.org/doi/abs/10.1021/ci400760a},
doi = {10.1021/ci400760a},
year = {2014},
date = {2014-03-04},
journal = {Journal of Chemical Information and Modeling},
volume = {54},
number = {3},
pages = {970-977},
abstract = {Hsp90 continues to be an important target for pharmaceutical discovery. In this project, virtual screening (VS) for novel Hsp90 inhibitors was performed using a combination of Autodock and Surflex-Sim (LB) scoring functions with the predictive ability of 3-D QSAR models, previously generated with the 3-D QSAutogrid/R procedure. Extensive validation of both structure-based (SB) and ligand-based (LB), through realignments and cross-alignments, allowed the definition of LB and SB alignment rules. The mixed LB/SB protocol was applied to virtually screen potential Hsp90 inhibitors from the NCI Diversity Set composed of 1785 compounds. A selected ensemble of 80 compounds were biologically tested. Among these molecules, preliminary data yielded four derivatives exhibiting IC50 values ranging between 18 and 63 μM as hits for a subsequent medicinal chemistry optimization procedure.},
keywords = {3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Molecular Modeling, MPGRS, Pharmacophoric Model, PLS, Virtual Screening},
pubstate = {published},
tppubtype = {article}
}
Flavio, Ballante; Antonia, Caroli; Richard B, Wickersham III; Rino, Ragno
Hsp90 inhibitors, part 1: definition of 3-D QSAutogrid/R models as a tool for virtual screening Journal Article
In: Journal of Chemical Information and Modeling, 54 (3), pp. 956-969, 2014.
Abstract | Links | BibTeX | Tags: 3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Pharmacophoric Model, PLS, Virtual Screening
@article{Ballante2014,
title = {Hsp90 inhibitors, part 1: definition of 3-D QSAutogrid/R models as a tool for virtual screening},
author = { Ballante Flavio and Caroli Antonia and Richard B, Wickersham III and Ragno Rino},
editor = {American Chemical Society},
url = {http://pubs.acs.org/doi/abs/10.1021/ci400759t},
doi = {10.1021/ci400759t},
year = {2014},
date = {2014-03-04},
journal = {Journal of Chemical Information and Modeling},
volume = {54},
number = {3},
pages = {956-969},
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.},
keywords = {3-D QSAutogrid/R, 3D QSAR, HSP90, Ligand-Based Design, Molecular Docking, Pharmacophoric Model, PLS, Virtual Screening},
pubstate = {published},
tppubtype = {article}
}
Flavio, Ballante
Application of Medicinal Chemistry Methods on Different Classes of Drugs PhD Thesis
Sapienza University of Rome, 2014.
Abstract | Links | BibTeX | Tags: 3-D QSAutogrid/R, 3D QSAR, Biochemistry, BSAO, Chemoinformatics, Chemometrics, COMBINEr, CoMFA, DABO, DockAccessor, Docking Assessment, HCV NS5B, HDAC, HIV-1, HIV-RT, HSP90, HUVEC, Ligand-Based Design, Molecular Docking, Molecular Modeling, MPGRS, NNRTIs, Opioid-Receptor Antagonists, Organic Chemistry, Pharmacophoric Model, PLS, Tuberculosis, VEGFR-2, Virtual Screening
@phdthesis{Ballante2014b,
title = {Application of Medicinal Chemistry Methods on Different Classes of Drugs},
author = { Ballante Flavio},
editor = {PADIS},
url = {http://hdl.handle.net/11573/918780 },
year = {2014},
date = {2014-01-27},
address = {Department of Chemistry and Tecnology of Drugs},
school = {Sapienza University of Rome},
abstract = {The present doctoral thesis is the result of the work carried out during the three years of my PhD scholarship at the Rome Center for Molecular Design laboratory (RCMD, Department of Chemistry and Drug Technologies, Sapienza University of Rome), under the supervision of Prof. Rino Ragno. The research activity was focused mainly on the design, optimization and application of computational strategies to derive quantitative structure-activity relationships (QSAR, 3-D QSAR, and COMBINE) on different molecular classes of current interest, such as: opioid receptor antagonists (OPAs), Hepatitis C Virus NS5B-Polymerase Inhibitors (NS5B-NNIs), Hystone Deacetylase Inhibitors (HDACIs), Anti- tubercular agents, vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors, HSP90 inhibitors, HIV-1 reverse transcriptase inhibitors (NNRTIs), Bovine Serum Amine Oxidase (BSAO) substrates, etc... Moreover two research periods abroad were performed: the first framed in a LLP Erasmus program collaboration, was conducted for six months at the Laboratoire d'Ingénierie et Moléculaire Pharmacologique Biochimie (LIMBP) of the Université de Lorraine Metz (France), directed by Prof. Gilbert Kirsch, and characterized by the application of organic synthesis to obtain new thienopyrimidinone derivatives as potential inhibitors of vascular endothelial growth factor receptor-2 (VEGFR-2); the second took place, for three months, at the Department of Biochemistry and Molecular Biophysics in Washington University School of Medicine in Saint Louis (MO, USA), under the supervision of Prof. Garland R. Marshall, investigating the activity profile of new Histone Deacetylases (HDACs) inhibitors by the application of the Mobility Shift Assay Technology. Main purpose of this doctoral thesis is to highlight the activities carried out in the different research projects, the applied methodologies and the obtained results. The text starts describing those studies whose results were published in scientific journals (chapters I-VI): the author decided to omit some procedural details, completely reported in the published papers, that would make the text too long, tedious and redundant; therefore readers who want to delve these aspects can also refer to Chapter XII in which is possible to read the original papers; on the contrary for studies that have not yet been published, as those characterizing the Chapters VII and VIII, discussion is adequately detailed. Chapters IX and X report the scientific activities carried out in France and in USA respectively; Chapter XI summarizes all the scientific activities accomplished during the entire PhD course, whereas Chapter XII, as mentioned, contains the published articles.},
keywords = {3-D QSAutogrid/R, 3D QSAR, Biochemistry, BSAO, Chemoinformatics, Chemometrics, COMBINEr, CoMFA, DABO, DockAccessor, Docking Assessment, HCV NS5B, HDAC, HIV-1, HIV-RT, HSP90, HUVEC, Ligand-Based Design, Molecular Docking, Molecular Modeling, MPGRS, NNRTIs, Opioid-Receptor Antagonists, Organic Chemistry, Pharmacophoric Model, PLS, Tuberculosis, VEGFR-2, Virtual Screening},
pubstate = {published},
tppubtype = {phdthesis}
}