Development of new CoMFA and CoMSIA 3D-QSAR models for anti-inflammatory phthalimide-containing TNFα modulators

doi:10.1016/j.bmc.2006.06.042

Bioorganic & Medicinal Chemistry

Volume 14, Issue 20, 15 October 2006, Pages 6874-6885

https://doi.org/10.1016/j.bmc.2006.06.042 Get rights and content

Abstract

In the present study, we describe a new 3D-QSAR analysis of 42 previously reported thalidomide analogues, with the ability to modulate the pro-inflammatory cytokine TNFα, by using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Three statistically significant models were obtained. The best resulting CoMFA and CoMSIA models have conventional r² values of 0.996 and 0.983, respectively. The cross-validated q² values are 0.869 and 0.868, respectively. The analysis of CoMFA and CoMSIA contour maps provided insight into the possible sites for structural modification of the thalidomide analogues for better activity and reduced toxicity.

Graphical abstract

3D-QSAR studies using CoMFA and CoMSIA approaches were performed on a series of anti-inflammatory thalidomide-analogue TNFα modulators.

Introduction

Tumor necrosis factor α (TNFα) is a key cytokine produced primarily by monocytes and macrophages, which is involved in the host immune response, contributing to the pathogenesis of both infectious and autoimmune diseases.¹ During normal host defense, low levels of serum TNFα confer protection against infectious agents, tumors, and tissue damage, and have an important role in the development of the humoral immune response in mice. On the other hand, increased concentrations of TNFα have been shown to trigger the lethal effects of septic shock syndrome.²

Thalidomide, α-N-phthalimideglutarimide (1, Fig. 1), approved by the Food and Drug Administration (FDA) agency in July 1998 for the treatment of erytrema nodosum leprosum (ENL), is an anti-inflammatory and immunomodulatory drug that was originally used as a sedative, although it is now widely associated to its teratogenic and neurotoxic properties.³ Thalidomide (1) selectively inhibits TNFα production by lipopolysaccharide (LPS)-stimulated human monocytes.⁴ Its inhibitory action on TNFα seems to be exerted by enhancing mRNA degradation.5, 6

The levels of other cytokines, such as IL-1β, IL-6, and granulocyte macrophage-colony stimulating factor (GMCSF), are also inhibited by thalidomide, whereas IL-10 is stimulated.⁷ The interest in this drug was renewed due to the potential clinical benefits associated to its selective inhibition of TNFα biosynthesis. Present applications include treatment of ENL,⁸ rheumatoid arthritis,⁹ HIV-associated aphthous ulceration,¹⁰ chronic tuberculosis,¹¹ chronic graft-versus-host disease,¹² and a variety of tumors.¹³

In order to obtain new lead compounds with increased anti-TNFα activity and reduced toxicity, useful for the treatment of chronic anti-inflammatory diseases, novel TNFα inhibitors have been designed using thalidomide (1) as structural template.¹ A good example of that is lenalidomide (2, Revlimid™) (Fig. 1), approved by FDA in December 2005 for the treatment of patients with myelodysplastic syndrome. Lenalidomide (2) is a potent inhibitor of TNFα production, 2000 times more potent than thalidomide (1).¹⁴

This strategy has demanded larger knowledge of the relationships between the chemical structure and the bioactivity profile related to TNFα modulation. In this context, molecular modeling strategies come as important tools in understanding the mechanism of interaction between various receptors and ligands, with prominence for the CoMFA and CoMSIA methods among the most powerful tools in the 3D-QSAR approach.15, 16 Recently, CoMFA and CoMSIA models for a series of thalidomide analogues as angiogenesis inhibitors have been reported, and shed light on the structural requisites that are important for the antiangiogenic activity.¹⁷

In this context, as part of a research program aiming at the discovery of new phthalimide-containing anti-inflammatory prototypes able to modulate selectively the cytokine TNFα,18, 19 we have become interested in applying 3D-QSAR methods to construct CoMFA and CoMSIA models for a series of TNFα modulators that have emerged as potential drugs for the treatment of anti-inflammatory diseases. These studies are especially important because the mechanism of action of these substances is not clear and their target bioreceptor has not been identified yet. The resulting models are expected to give insight into the influence of structural characteristics on the anti-inflammatory profile and thus aid in designing new potent TNFα modulators with fewer side effects.

Section snippets

Results and discussion

After the generation of CoMFA and CoMSIA models, the statistical validity of the models was judged by high values of cross-validated q² (more than 0.8) and non-validated r² (more than 0.9), and also the lowest standard errors of estimation (SEE). The models that fulfill these criteria were selected for discussion.

Conclusions

In this study, the 3D-QSAR methods, CoMFA and CoMSIA, were applied to predict the TNFα modulatory activity of a series of phthalimide-containing derivatives. The best 3D-QSAR models were generated by CoMFA combined steric/electrostatic fields, providing the most significant correlation with biological activity.

This model had good statistical results in terms of q² and r² values, and showed a great predictivity of the test set, in the external validation, showing no outliers. Additionally,

Data set

The 31 and 11 compounds of the training and the test sets (Table 1), respectively, were selected from the literature.24, 25, 26, 27, 28 The anti-TNFα activity of all the 42 compounds used in this study was measured as IC₅₀ (Table 1). These values have been obtained using the same pharmacological protocol on TNFα inhibitory activity in LPS-stimulated human peripheral blood mononuclear cells (PBMC) and were expressed in negative logarithmic units, −log IC₅₀ or pIC₅₀. The elected inhibitors are

Acknowledgments

The authors thank CNPq (Br, #420.015/05-1), FAPERJ (Br), PRONEX-Rio (Br), and IM-INOFAR (Br) for the financial support and fellowships (to C.M.A., E.J.B., and C.A.M.F.).

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Development of new CoMFA and CoMSIA 3D-QSAR models for anti-inflammatory phthalimide-containing TNFα modulators

Abstract

Graphical abstract

Introduction

Section snippets

Results and discussion

Conclusions

Data set

Acknowledgments

Bioorg. Med. Chem.

Bioorg. Med. Chem. Lett.

Bioorg. Med. Chem. Lett.

Bioorg. Med. Chem. Lett.

Bioorg. Med. Chem. Lett.

J. Chromatogr., A.

Ann. Rheum. Dis.

Int. Immunopharmacol.

J. Immunol.

J. Exp. Med.

J. Exp. Med.

Anti-Inflammatory Anti-Allergy Agents Med. Chem.

J. Immunol.

J. Infect. Dis.

Drug Safety

Br. Med. J.