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 IC₅₀ 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