Next-Generation Reduction Sensitive Lipid Conjugates of Tenofovir: Antiviral Activity and Mechanism of Release

The pharmacokinetic properties of tenofovir (TFV) and other charged nucleoside analogues are dramatically improved upon conjugation to a lipid prodrug. We previously prepared reduction-sensitive lipid conjugates of TFV that demonstrate superior antiviral activity compared to other lipid conjugates including the clinically approved formulation, tenofovir disoproxil fumarate (TDF). In continuation of that work, we have synthesized next-generation conjugates with reduced cytotoxicity that retain potent antiviral activity against HIV-1 and HBV with a therapeutic index >100000 for our most potent conjugate. We also show that disulfide reduction is not responsible for prodrug cleavage unless 3-<i>exo</i>-<i>tet</i> intramolecular cyclization can occur, suggesting that enzymatic hydrolysis is predominantly responsible for activity of our prodrugs in vitro

Reduction Sensitive Lipid Conjugates of Tenofovir: Synthesis, Stability, and Antiviral Activity

The therapeutic value of numerous small molecules hinges on their ability to permeate the plasma membrane. This is particularly true for tenofovir (TFV), adefovir, and other antiviral nucleosides that demonstrate potent antiviral activity but poor bioavailability. Using TFV as a model substrate, we hybridized two disparate prodrug strategies to afford novel reduction-sensitive lipid conjugates of TFV that exhibit subnanomolar activity toward HIV-1 and are stable in human plasma for more than 24 h with a therapeutic index approaching 30000. These compounds significantly rival the clinically approved formulation of TFV and revitalize the potential of disulfide-bearing prodrugs which have seen limited in vitro and in vivo success since their debut over 20 years ago. We further demonstrate the utility of these conjugates as a tool to indirectly probe the enzymatic hydrolysis of phosphonomonoesters that may further advance the development of other prodrug strategies for nucleosides, peptides, and beyond

A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds

HIV resistance emerging against antiretroviral drugs represents a great threat to the continued prolongation of the lifespans of HIV-infected patients. Therefore, methods capable of predicting resistance susceptibility in the development of compounds are in great need. By targeting the major reverse transcription residues Y181, K103, and L100, we used the biological activities of compounds against these enzymes and the wild-type reverse transcriptase to create Naïve Bayes Networks. Through this machine learning approach, we could predict, with high accuracy, whether a compound would be susceptible to a loss of potency due to resistance. Also, we could perfectly predict retrospectively whether compounds would be susceptible to both a K103 mutant RT and a Y181 mutant RT. In the study presented here, our method outperformed a traditional molecular mechanics approach. This method should be of broad interest beyond drug discovery efforts, and serves to expand the utility of machine learning for the prediction of physical, chemical, or biological properties using the vast information available in the literature

A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds

HIV resistance emerging against antiretroviral drugs represents a great threat to the continued prolongation of the lifespans of HIV-infected patients. Therefore, methods capable of predicting resistance susceptibility in the development of compounds are in great need. By targeting the major reverse transcription residues Y181, K103, and L100, we used the biological activities of compounds against these enzymes and the wild-type reverse transcriptase to create Naïve Bayes Networks. Through this machine learning approach, we could predict, with high accuracy, whether a compound would be susceptible to a loss of potency due to resistance. Also, we could perfectly predict retrospectively whether compounds would be susceptible to both a K103 mutant RT and a Y181 mutant RT. In the study presented here, our method outperformed a traditional molecular mechanics approach. This method should be of broad interest beyond drug discovery efforts, and serves to expand the utility of machine learning for the prediction of physical, chemical, or biological properties using the vast information available in the literature

Novel Cyclopropyl-Indole Derivatives as HIV Non-Nucleoside Reverse Transcriptase Inhibitors

The HIV pandemic represents one of the most serious diseases to face mankind in both a social and economic context, with many developing nations being the worst afflicted. Due to ongoing resistance issues associated with the disease, the design and synthesis of anti-HIV agents presents a constant challenge for medicinal chemists. Utilizing molecular modeling, we have designed a series of novel cyclopropyl indole derivatives as HIV non-nucleoside reverse transcriptase inhibitors and carried out their preparation. These compounds facilitate a double hydrogen bonding interaction to Lys101 and efficiently occupy the hydrophobic pockets in the regions of Tyr181/188 and Val179. Several of these compounds inhibited HIV replication as effectively as nevirapine when tested in a phenotypic assay

Examples of compounds of interest as sphingoid base/ceramide analog pharmaceutical leads

<p><b>Copyright information:</b></p><p>Taken from " Biodiversity of sphingoid bases (“sphingosines”) and related amino alcohols"</p><p></p><p>Journal of Lipid Research 2008;49(8):1621-1639.</p><p>Published online 1 Aug 2008</p><p>PMCID:PMC2444003.</p><p></p

Structure–Activity Relationships and Pharmacophore Model of a Noncompetitive Pyrazoline Containing Class of GluN2C/GluN2D Selective Antagonists

Here we describe the synthesis and structure–activity relationship for a class of pyrazoline-containing dihydroquinolone negative allosteric modulators of the NMDA receptor that show strong subunit selectivity for GluN2C- and GluN2D-containing receptors over GluN2A- and GluN2B-containing receptors. Several members of this class inhibit NMDA receptor responses in the nanomolar range and are more than 50-fold selective over GluN1/GluN2A and GluN1/GluN2B NMDA receptors, as well as AMPA, kainate, GABA, glycine, nicotinic, serotonin, and purinergic receptors. Analysis of the purified enantiomers of one of the more potent and selective compounds shows that the <i>S</i>-enantiomer is both more potent and more selective than the <i>R-</i>enantiomer. The <i>S</i>-enantiomer had an IC₅₀ of 0.17–0.22 μM at GluN2D- and GluN2C-containing receptors, respectively, and showed over 70-fold selectivity over other NMDA receptor subunits. The subunit selectivity of this class of compounds should be useful in defining the role of GluN2C- and GluN2D-containing receptors in specific brain circuits in both physiological and pathophysiological conditions

The Structure–Activity Relationship of a Tetrahydroisoquinoline Class of <i>N</i>‑Methyl‑d‑Aspartate Receptor Modulators that Potentiates GluN2B-Containing <i>N</i>‑Methyl‑d‑Aspartate Receptors

We have identified a series of positive allosteric NMDA receptor (NMDAR) modulators derived from a known class of GluN2C/D-selective tetrahydroisoquinoline analogues that includes CIQ. The prototypical compound of this series contains a single isopropoxy moiety in place of the two methoxy substituents present in CIQ. Modifications of this isopropoxy-containing scaffold led to the identification of analogues with enhanced activity at the GluN2B subunit. We identified molecules that potentiate the response of GluN2B/GluN2C/GluN2D, GluN2B/GluN2C, and GluN2C/GluN2D-containing NMDARs to maximally effective concentrations of agonist. Multiple compounds potentiate the response of NMDARs with submicromolar EC₅₀ values. Analysis of enantiomeric pairs revealed that the <i>S</i>-(−) enantiomer is active at the GluN2B, GluN2C, and/or GluN2D subunits, whereas the <i>R</i>-(+) enantiomer is only active at GluN2C/D subunits. These results provide a starting point for the development of selective positive allosteric modulators for GluN2B-containing receptors

Design, Synthesis, and Structure–Activity Relationship of a Novel Series of GluN2C-Selective Potentiators

NMDA receptors are tetrameric complexes composed of GluN1 and GluN2A–D subunits that mediate a slow Ca²⁺<b>-</b>permeable component of excitatory synaptic transmission. NMDA receptors have been implicated in a wide range of neurological diseases and thus represent an important therapeutic target. We herein describe a novel series of pyrrolidinones that selectively potentiate only NMDA receptors that contain the GluN2C subunit. The most active analogues tested were over 100-fold selective for recombinant GluN2C-containing receptors over GluN2A/B/D-containing NMDA receptors as well as AMPA and kainate receptors. This series represents the first class of allosteric potentiators that are selective for diheteromeric GluN2C-containing NMDA receptors

Pyrazolo-Piperidines Exhibit Dual Inhibition of CCR5/CXCR4 HIV Entry and Reverse Transcriptase

We report novel anti-HIV-1 agents with combined dual host–pathogen pharmacology. Lead compound <b>3</b>, composed of a pyrazole-piperidine core, exhibits three concurrent mechanisms of action: (1) non-nucleoside reverse transcriptase inhibition, (2) CCR5-mediated M-tropic viral entry inhibition, and (3) CXCR4-based T-tropic viral entry inhibition that maintains native chemokine ligand binding. This discovery identifies important tool compounds for studying viral infectivity and prototype agents that block HIV-1 entry through dual chemokine receptor ligation