Insights into the role of PFKFB3 in cancer

PFKFB3, an isoform of PFK-2, which is highly expressed in cancer cells, has been suggested to be associated with enhanced aerobic glycolysis in cancer by elevating the intracellular levels of key glycolytic activator, Fru-2,6-P2. This work describes the importance of PFKFB3 function in metabolic alterations and adaptations of cancers, providing new insights into the PFKFB3-associated ROS regulation in cancer and suggesting promising strategies for cancer drug development. The first study investigates the therapeutic potential of novel PFKFB3 inhibitors as well as the molecular mechanism of PFKFB3 inhibition. I was able to identify small molecular inhibitors, N4A and YN1, which almost constantly inhibit PFKFB3 and ultimately lead to cancer cell death. I determined the crystal structure of PFKFB3 in complex with those inhibitors and these structures revealed the molecular mechanism of inhibitor-recognition by PFKFB3. Providing direct information on the interaction between a potential drug molecule and its target protein at the molecular level, this study established a framework for future development efforts and validated PFKFB3 as a target for new cancer therapies. The second study investigates the functional involvement of PFKFB3 in ROS regulation within cancer cells. We found PFKFB3 to be S-glutathionylated under excessive oxidative stress, which leads to inactivation of the kinase activity of PFKFB3 Consequently, the activation of PFKFB3, induced by S-glutathionylation, decreases cellular Fru-2,6-P2 levels and reroutes the glucose metabolic flux from glycolysis to the PPP, maintaining oxidative homeostasis in cancer cells. The ability of PFKFB3 to control ROS levels can not only support cancer cell survival but also maintain cell cycle progression. This study provides a new insight into the roles of PFKFB3 as a master switch that senses and controls redox homeostasis in cancer in addition to its role in cancer glycolysis. The functional involvement of PFKFB3 S-glutathionylation in ROS regulation would also suggest a possible role for PFKFB3 in cell cycle progression in cancer cells. Together, this new understanding of PFKFB3 functions in cancer will contribute to the development of appropriate therapeutic strategies for cancer treatment

Investigating combinatorial approaches in virtual screening on human inducible 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFKFB3): A case study for small molecule kinases

Efforts toward improving the predictiveness in tier-based approaches to virtual screening (VS) have mainly focused on protein kinases. Despite their significance as drug targets, small molecule kinases have been rarely tested with these approaches. In this paper, we investigate the efficacy of a pharmacophore screening-combined structure-based docking approach on the human inducible 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase, an emerging target for cancer chemotherapy. Six out of a total 1364 compounds from NCI\u27s Diversity Set II were selected as true actives via throughput screening. Using a database constructed from these compounds, five programs were tested for structure-based docking (SBD) performance, the MOE of which showed the highest enrichments and second highest screening rates. Separately, using the same database, pharmacophore screening was performed, reducing 1364 compounds to 287 with no loss in true actives, yielding an enrichment of 4.75. When SBD was retested with the pharmacophore filtered database, 4 of the 5 SBD programs showed significant improvements to enrichment rates at only 2.5% of the database, with a 7-fold decrease in an average VS time. Our results altogether suggest that combinatorial approaches of VS technologies are easily applicable to small molecule kinases and, moreover, that such methods can decrease the variability associated with single-method SBD approaches. © 2011 Elsevier Inc. All rights reserved

Structure-Based Development of Small Molecule PFKFB3 Inhibitors: A Framework for Potential Cancer Therapeutic Agents Targeting the Warburg Effect

Cancer cells adopt glycolysis as the major source of metabolic energy production for fast cell growth. The HIF-1-induced PFKFB3 plays a key role in this adaptation by elevating the concentration of Fru-2,6-BP, the most potent glycolysis stimulator. As this metabolic conversion has been suggested to be a hallmark of cancer, PFKFB3 has emerged as a novel target for cancer chemotherapy. Here, we report that a small molecular inhibitor, N4A, was identified as an initial lead compound for PFKFB3 inhibitor with therapeutic potential. In an attempt to improve its potency, we determined the crystal structure of the PFKFB3•N4A complex to 2.4 Å resolution and, exploiting the resulting molecular information, attained the more potent YN1. When tested on cultured cancer cells, both N4A and YN1 inhibited PFKFB3, suppressing the Fru-2,6-BP level, which in turn suppressed glycolysis and, ultimately, led to cell death. This study validates PFKFB3 as a target for new cancer therapies and provides a framework for future development efforts

Induction of cell death in HeLa cells by the PFKFB3 inhibitors, N4A and YN1.

<p>The cells were treated with two different concentrations of inhibitors, 25 µM and 50 µM. (<b>A</b>) Induced cell death at two different concentrations of N4A was measured by flow cytometry after double staining with Annexin V and PI. (<b>B</b>) Quantitation of the flow-cytometric data (mean ± SD) showing a dose-related effect of N4A. (<b>C</b>) Cytograms of YN- induced cell death and (<b>D</b>) quantitation of the flow-cytometric data.</p

Experimental evaluation of the hit compounds.

<p>(<b>A</b>) Inhibition potencies of the candidate compounds. The magnitudes of inhibition by compounds at 10 µM each are measured through the enzyme assay and presented as percentiles against the control (□). A same experiment was also performed in the presence of 0.1% Tween-20 (▪), to eliminate false positives caused by nonspecific hydrophobic interactions. (<b>B</b>) Structures of the PFKFB3 inhibitors. (<b>C</b>) Lineweaver-Burk plots showing the competitive inhibition by N4A against Fru-6-P. The inhibitor concentrations used were: 0 µM (▪), 1 µM (○), 2 µM (▴), and 3 µM (<b>□</b>) of N4A. They are also labeled next to individual plots. (<b>D</b>) Lineweaver-Burk plots showing the competitive inhibition by YN1 against Fru-6-P. The inhibitor concentrations used were: 0 µM (▪), 1 µM (○), 2 µM (▴), and 3 µM (<b>□</b>) of N4A. (<b>e</b>) Selectivity of N4A and YN1 on PFKFB isoforms. Results are expressed as percent inhibition at twice the IC₅₀ concentration against PFKFB3 (N4A = 6 µM, YN1 = 1.3 µM).</p

The effects of the PFKFB3 inhibitors on the Fru-2,6-BP levels, the lactate secretions, and the cell growths.

<p>The Fru-2,6-BP levels (<b>A</b>) and the levels of secreted lactate (<b>B</b>) were determined enzymatically at time points 0, 4, 8, 12, 24, or 48 hours after the inhibitor treatments of HeLa cells. The results were normalized to the sample protein concentrations and expressed as a ratio to the value of vehicle-treated. Data are means ± S.E.M. from at least three experiments. Time-dependent effects of 25 µM each of N4A (line with diamond) and YN1 (dotted line with hollow square) on the cellular Fru-2,6-BP levels (<b>A</b>) and the lactate secretions (<b>B</b>) are shown. (<b>C</b>) Growth inhibition by N4A , YN1, and YZ9 on HeLa and T47D cells. Cell numbers were assayed over 36 hours by the trypan blue counting or XTT assay. Data points are expressed as % cell growth of control containing vehicle against logarithmic scale of inhibitor concentrations. Error bars stand for intraexperimental replicates standard deviation.</p

Statistics of reflection data and structure refinements.

<p><i>R</i>_sym = ∑<i>_h</i>(∑<i>_j</i>|<i>I_h,j</i>−<<i>I_h</i>>|/∑<i>_Ih,j</i>), where <i>h</i> = set of Miller indices, <i>j</i> = set of observations of reflection <i>h</i>, and <<i>I_h</i>> = the mean intensity. <i>R</i>_crys = ∑<i>_h</i>||<i>F</i>_o,<i>h</i>|−|<i>F</i>_c,<i>h</i>||/∑<i>_h</i>|<i>F</i>_o,<i>h</i>|. <i>R</i>_free was calculated using 10% of the complete data set excluded from refinement. The numbers in parentheses represent values from the highest resolution shell.</p

The kinetic and biological properties of the PFKFB3 inhibitors.

<p>The kinetic and biological properties of the PFKFB3 inhibitors.</p