8 research outputs found
Hsp90 Inhibitors, Part 1: Definition of 3‑D QSAutogrid/R Models as a Tool for Virtual Screening
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
Hsp90 Inhibitors, Part 1: Definition of 3‑D QSAutogrid/R Models as a Tool for Virtual Screening
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
Histone Deacetylase Inhibitors: Structure-Based Modeling and Isoform-Selectivity Prediction
An enhanced version of comparative binding energy (COMBINE)
analysis,
named COMBINEr, based on both ligand-based and structure-based alignments
has been used to build several 3-D QSAR models for the eleven human
zinc-based histone deacetylases (HDACs). When faced with an abundance
of data from diverse structure–activity sources, choosing the
best paradigm for an integrative analysis is difficult. A common example
from studies on enzyme–inhibitors is the abundance of crystal
structures characterized by diverse ligands complexed with different
enzyme isoforms. A novel comprehensive tool for data mining on such
inhomogeneous set of structure–activity data was developed
based on the original approach of Ortiz, Gago, and Wade, and applied
to predict HDAC inhibitors’ isoform selectivity. The COMBINEr
approach (apart from the AMBER programs) has been developed to use
only software freely available to academics
Histone Deacetylase Inhibitors: Structure-Based Modeling and Isoform-Selectivity Prediction
An enhanced version of comparative binding energy (COMBINE)
analysis,
named COMBINEr, based on both ligand-based and structure-based alignments
has been used to build several 3-D QSAR models for the eleven human
zinc-based histone deacetylases (HDACs). When faced with an abundance
of data from diverse structure–activity sources, choosing the
best paradigm for an integrative analysis is difficult. A common example
from studies on enzyme–inhibitors is the abundance of crystal
structures characterized by diverse ligands complexed with different
enzyme isoforms. A novel comprehensive tool for data mining on such
inhomogeneous set of structure–activity data was developed
based on the original approach of Ortiz, Gago, and Wade, and applied
to predict HDAC inhibitors’ isoform selectivity. The COMBINEr
approach (apart from the AMBER programs) has been developed to use
only software freely available to academics
Histone Deacetylase Inhibitors: Structure-Based Modeling and Isoform-Selectivity Prediction
An enhanced version of comparative binding energy (COMBINE)
analysis,
named COMBINEr, based on both ligand-based and structure-based alignments
has been used to build several 3-D QSAR models for the eleven human
zinc-based histone deacetylases (HDACs). When faced with an abundance
of data from diverse structure–activity sources, choosing the
best paradigm for an integrative analysis is difficult. A common example
from studies on enzyme–inhibitors is the abundance of crystal
structures characterized by diverse ligands complexed with different
enzyme isoforms. A novel comprehensive tool for data mining on such
inhomogeneous set of structure–activity data was developed
based on the original approach of Ortiz, Gago, and Wade, and applied
to predict HDAC inhibitors’ isoform selectivity. The COMBINEr
approach (apart from the AMBER programs) has been developed to use
only software freely available to academics
Hsp90 Inhibitors, Part 2: Combining Ligand-Based and Structure-Based Approaches for Virtual Screening Application
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 IC<sub>50</sub> values ranging between 18 and 63 μM
as hits for a subsequent medicinal chemistry optimization procedure
Histone Deacetylase Inhibitors: Structure-Based Modeling and Isoform-Selectivity Prediction
An enhanced version of comparative binding energy (COMBINE)
analysis,
named COMBINEr, based on both ligand-based and structure-based alignments
has been used to build several 3-D QSAR models for the eleven human
zinc-based histone deacetylases (HDACs). When faced with an abundance
of data from diverse structure–activity sources, choosing the
best paradigm for an integrative analysis is difficult. A common example
from studies on enzyme–inhibitors is the abundance of crystal
structures characterized by diverse ligands complexed with different
enzyme isoforms. A novel comprehensive tool for data mining on such
inhomogeneous set of structure–activity data was developed
based on the original approach of Ortiz, Gago, and Wade, and applied
to predict HDAC inhibitors’ isoform selectivity. The COMBINEr
approach (apart from the AMBER programs) has been developed to use
only software freely available to academics
2-(Alkyl/Aryl)Amino-6-Benzylpyrimidin-4(3<i>H</i>)-ones as Inhibitors of Wild-Type and Mutant HIV-1: Enantioselectivity Studies
The single enantiomers of two pyrimidine-based HIV-1
non-nucleoside
reverse transcriptase inhibitors, <b>1</b> (MC1501) and <b>2</b> (MC2082), were tested in both cellular and enzyme assays.
In general, the <i>R</i> forms were more potent than their <i>S</i> counterparts and racemates and (<i>R</i>)-<b>2</b> was more efficient than (<i>R</i>)-<b>1</b> and the reference compounds, with some exceptions. Interestingly,
(<i>R</i>)-<b>2</b> displayed a faster binding to
K103N RT with respect to WT RT, while (<i>R</i>)-<b>1</b> showed the opposite behavior