Integrated strategy reveals the protein interface between cancer targets Bcl-2 and NAF-1

Tamir, Sagi; Rotem‐Bamberger, Shahar; Katz, Chen; Morcos, Faruck; Hailey, Kendra L.; Zuris, John A.; Wang, Charles; Conlan, Andrea R.; Lipper, Colin H.; Paddock, Mark L.; Mittler, Ron; Onuchic, José N.; Jennings, Patricia A.; Friedler, Assaf; Nechushtai, Rachel

doi:10.1073/pnas.1403770111

Cited by 61 publications

(58 citation statements)

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“…Preliminary results demonstrated the complementary role of DCA in the prediction of drug targets for treating human breast cancer (22,32). Earlier work used DCA and FTmap to predict the binding interface between the nutrient-deprivation autophagy factor-1 (NAF-1) and the B-cell lymphoma-2 (Bcl-2), as well as discover a NAF-1 small molecular binder, MAD-28, which may disrupt NAF-1/Bcl-2 binding.…”

Section: Druggable Interface Identification Design Frameworkmentioning

confidence: 99%

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Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

Bai

Morcos

Cheng

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Protein−protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein−protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular dockingbased screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.protein−protein interface | druggable surface | hot spots | direct coupling analysis | drug design P rotein−protein interactions (PPIs) mediate a wide range of important cellular functions, including signal transduction and enzymatic processes. The regulation of these interactions has drawn intense focus in physiology and pathology, where PPI interfaces have emerged as a new class of molecular targets for pharmacological intervention (1, 2). The design of drugs to target PPIs, however, faces numerous challenges (3). Although over 41,000 unique human protein interactions have been experimentally discovered and reported on Human Protein Reference Database (4), only ∼2,500 nonredundant multiprotein complexes have experimentally determined structures available in the Protein Data Bank (5). Therefore, the current experimental methods cannot accommodate the high demand for structural details of these interactions. Even when the structural complexes are known, targeting PPIs with small molecules poses a significant challenge. Many protein interfaces have large, featureless surfaces that lack obvious small-molecule binding pockets, making it difficult to design drugs with the ability to modulate (inhibit or stabilize) the PPIs with the necessary selectivity and potency (6).In the past two decades, two major classes of computational methods for protein−protein interface prediction have emerged (7): (i) data-driven methods (8-13) and (ii) molecular docking methods (14). Data-driven methods include homology modeling (8, 9), machine learning (10), and coevolution-based statistical models (11-13). These approaches make predictions using homologous data as templates or by extracting interaction patterns from data using statistical mo...

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Section: Druggable Interface Identification Design Frameworkmentioning

confidence: 99%

“…Thus, coevolutionary patterns in protein sequence data can be used to identify functional complex interfaces. Extracting this rich information has been an area of great focus (12,13,22), particularly with the advancement of sequencing technologies over the recent decades (23).…”

Section: Druggable Interface Identification Design Frameworkmentioning

confidence: 99%

Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

Bai

Morcos

Cheng

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Pocket 1 covers patches of highly conserved residues (I102, K55′, V57′, and D64) and five of the nine conserved core amino acids of the [2Fe-2S] binding motif (C83, H87, Y71, F82, and D84). Moreover, a large portion of residues in NAF-1 (S92, A96, A109, C110, D111, and H114), corresponding to the residues (G62, A69, F82, C83, D84, and H87) in pocket 1 of mNT, overlap with putative interfacial binding residues between proteins Bcl-2 and NAF-1, which were identified in an integrated experimental and direct coupling analysis strategy (27). These overlapping residues interact with several residues of the BH4 domain and the BH2 domain of Bcl-2 (SI Appendix, Fig.…”

Section: Mad-28 Localizes To Mitochondria and Causes A Decrease Inmentioning

confidence: 99%

The Fe-S cluster-containing NEET proteins mitoNEET and NAF-1 as chemotherapeutic targets in breast cancer

Bai

Morcos

Sohn

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Identification of novel drug targets and chemotherapeutic agents is a high priority in the fight against cancer. Here, we report that MAD-28, a designed cluvenone (CLV) derivative, binds to and destabilizes two members of a unique class of mitochondrial and endoplasmic reticulum (ER) 2Fe-2S proteins, mitoNEET (mNT) and nutrient-deprivation autophagy factor-1 (NAF-1), recently implicated in cancer cell proliferation. Docking analysis of MAD-28 to mNT/NAF-1 revealed that in contrast to CLV, which formed a hydrogen bond network that stabilized the 2Fe-2S clusters of these proteins, MAD-28 broke the coordinative bond between the His ligand and the cluster's Fe of mNT/NAF-1. Analysis of MAD-28 performed with control (Michigan Cancer Foundation; MCF-10A) and malignant (M.D. Anderson-metastatic breast; MDA-MB-231 or MCF-7) human epithelial breast cells revealed that MAD-28 had a high specificity in the selective killing of cancer cells, without any apparent effects on normal breast cells. MAD-28 was found to target the mitochondria of cancer cells and displayed a surprising similarity in its effects to the effects of mNT/NAF-1 shRNA suppression in cancer cells, causing a decrease in respiration and mitochondrial membrane potential, as well as an increase in mitochondrial iron content and glycolysis. As expected, if the NEET proteins are targets of MAD-28, cancer cells with suppressed levels of NAF-1 or mNT were less susceptible to the drug. Taken together, our results suggest that NEET proteins are a novel class of drug targets in the chemotherapeutic treatment of breast cancer, and that MAD-28 can now be used as a template for rational drug design for NEET Fe-S cluster-destabilizing anticancer drugs.NEET proteins | mitocan | iron-sulfur proteins | mitochondria | rational drug design

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“…Although structural details are lacking, several proteins have been reported to interact with antiapoptotic Bcl-2 family members in a BH3-independent manner, including p53 (15), the nutrient deprivation autophagy factor 1 protein (NAF-1) (16), and the nuclear orphan receptors NR4A1 (Nur77) (17)(18) and NR4A3 (Nor-1) (19). Binding of Nur77 to anti-apoptotic Bcl-2 proteins at the surface of mitochondria has been proposed to induce a conformational change that exposes the BH3 domain residues in Bcl-2 helix ␣2 (18), converting Bcl-2 from cytoprotective to pro-apoptotic.…”

mentioning

confidence: 99%

Orphan Nuclear Receptor NR4A1 Binds a Novel Protein Interaction Site on Anti-apoptotic B Cell Lymphoma Gene 2 Family Proteins

Godoi

Wilkie-Grantham

Hishiki

et al. 2016

Journal of Biological Chemistry

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B cell lymphoma gene 2 (Bcl-2) family proteins are key regulators of programmed cell death and important targets for drug discovery. Pro-apoptotic and anti-apoptotic Bcl-2 family proteins reciprocally modulate their activities in large part through protein interactions involving a motif known as BH3 (Bcl-2 homology 3). Nur77 is an orphan member of the nuclear receptor family that lacks a BH3 domain but nevertheless binds certain anti-apoptotic Bcl-2 family proteins (Bcl-2, Bfl-1, and Bcl-B), modulating their effects on apoptosis and autophagy. We used a combination of NMR spectroscopy-based methods, mutagenesis, and functional studies to define the interaction site of a Nur77 peptide on anti-apoptotic Bcl-2 family proteins and reveal a novel interaction surface. Nur77 binds adjacent to the BH3 peptide-binding crevice, suggesting the possibility of crosstalk between these discrete binding sites. Mutagenesis of residues lining the identified interaction site on Bcl-B negated the interaction with Nur77 protein in cells and prevented Nur77-mediated modulation of apoptosis and autophagy. The findings establish a new protein interaction site with the potential to modulate the apoptosis and autophagy mechanisms governed by Bcl-2 family proteins.In metazoans, Bcl-2 5 family proteins regulate several cellular processes, most prominently apoptosis (programmed cell death) and also autophagy (1, 2). Based on primary amino acid sequence similarity, members of the Bcl-2 protein family share at least one of four modular components, termed Bcl-2 homology (BH) domains. Of these, BH3 has an amphipathic ␣-helical structure and plays a pivotal role in both the activation of proapoptotic and the suppression of anti-apoptotic members of the family. For example, the BH3 domains of Bim, Bid, and Puma trigger conformational changes in the executioners Bax and Bak, leading to their oligomerization and permeation of the outer mitochondrial membrane. Downstream consequences of Bax and Bak activation include release of cytochrome c and, ultimately, the activation of caspase-9 and other cell death proteases. Conversely, the BH3 domains of these and other BH3-carrying proteins bind anti-apoptotic Bcl-2 family proteins and inhibit their ability to prevent Bax/Bak oligomerization in the outer mitochondrial membrane.The BH3 domain of pro-apoptotic proteins operates analogous to a ligand to interact with a predominantly hydrophobic receptor-like binding crevice on the surfaces of anti-apoptotic Bcl-2 family proteins. In addition to regulating apoptosis, the BH3-binding pocket on anti-apoptotic Bcl-2 family proteins has been reported to bind a BH3-like domain in the autophagy protein Beclin-1, and this interaction has been shown to play an important role in regulating autophagy (3). Prior work has dissected the binding affinity of various BH3 peptides (ligands) to anti-apoptotic Bcl-2 proteins (receptors), and three-dimensional structural data are available for several of these pairs (reviewed in Ref. 4).Targeting the BH3-binding cleft of anti-apo...

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Integrated strategy reveals the protein interface between cancer targets Bcl-2 and NAF-1

Cited by 61 publications

References 31 publications

Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

The Fe-S cluster-containing NEET proteins mitoNEET and NAF-1 as chemotherapeutic targets in breast cancer

Orphan Nuclear Receptor NR4A1 Binds a Novel Protein Interaction Site on Anti-apoptotic B Cell Lymphoma Gene 2 Family Proteins

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