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

CISD2 counteracts the inhibition of ER-mitochondrial calcium transfer by anti-apoptotic BCL-2

CISD2, a 2Fe2S cluster domain-containing protein, is implicated in Wolfram syndrome type 2, longevity and cancer. CISD2 is part of a ternary complex with IP3 receptors (IP3Rs) and anti-apoptotic BCL-2 proteins and enhances BCL-2's anti-autophagic function. Here, we examined how CISD2 impacted the function of BCL-2 in apoptosis and in controlling IP3R-mediated Ca2+ signaling. Using purified proteins, we found a direct interaction between the cytosolic region of CISD2 and BCL-2's BH4 domain with a submicromolar affinity. At the functional level, the cytosolic region of CISD2, as a purified protein, did not affect the ability of BCL-2 to inhibit BAX-pore formation. In a cellular context, loss of CISD2 did not impede the suppression of apoptosis by BCL-2. Also, in Ca2+-signaling assays, absence of CISD2 did not affect the inhibition of IP3R-mediated Ca2+ release by BCL-2. Combined, these experiments indicate that CISD2 is not essential for BCL-2 function in apoptosis and cytosolic Ca2+ signaling. Instead, CISD2 overexpression enhanced BCL-2-mediated suppression of cytosolic IP3R-mediated Ca2+ release. However, consistent with the presence of CISD2 and BCL-2 at mitochondria-associated ER membranes (MAMs), the most striking effect was observed at the level of ER-mitochondrial Ca2+ transfer. While BCL-2 overexpression inhibited ER-mitochondrial Ca2+ transfer, overexpression of CISD2 together with BCL-2 abrogated the effect of BCL-2. The underlying mechanism is linked to ER-mitochondrial contact sites, since BCL-2 reduced ER-mitochondrial contact sites while co-expression of CISD2 together with BCL-2 abolished this effect. These findings reveal a unique interplay between BCL-2 and CISD2 at Ca2+-signaling nanodomains between ER and mitochondria.

Eicosatrienoic acid enhances the quality of in vitro matured porcine oocytes by reducing PRKN-mediated ubiquitination of CISD2

Oocytes and early embryos are exposed to many uncontrollable factors that trigger endoplasmic reticulum (ER) stress during in vitro culture. Prevention of ER stress is an effective way to improve the oocyte maturation rate and oocyte quality. Increasing evidence suggests that dietary intake of sufficient n-3 polyunsaturated fatty acids (PUFAs) is associated with health benefits, particularly in the domain of female reproductive health. We found that supplementation of eicosatrienoic acid (ETA) during in vitro maturation (IVM) of oocyte significantly downregulated ER stress-related genes. Mitochondria-associated membranes (MAMs) are communications areas between the ER and mitochondria. Inositol 1,4,5-trisphosphate receptor (IP3R) is a key calcium channels in MAMs and, participates in the regulation of many cellular functions. Notably, the MAM area was significantly decreased in ETA-treated oocytes. CDGSH iron sulfur domain 2 (CISD2) is presents in MAMs, but its role in oocytes is unknown. ETA treatment significantly increased CISD2 expression, and siRNA-mediated knockdown of CISD2 blocked the inhibitory effect of ETA on IP3R. Transcriptomic sequencing and immunoprecipitation experiments showed that ETA treatment significantly decreased expression of the E3 ubiquitin ligase PRKN. PRKN induced ubiquitination and degradation of CISD2, indicating that the PRKN-mediated ubiquitin-proteasome system regulates CISD2. In conclusion, our study reveals the mechanism by which ETA supplementation during IVM alleviates mitochondrial calcium overload under ER stress conditions by decreasing PRKN-mediated ubiquitination of CISD2 and facilitating inhibition of IP3R by CISD2/BCL-2. This improves oocyte quality and subsequent embryo developmental competence prior to implantation.

CISD3/MiNT is required for complex I function, mitochondrial integrity, and skeletal muscle maintenance

Mitochondria play a central role in muscle metabolism and function. A unique family of iron-sulfur proteins, termed CDGSH Iron Sulfur Domain-containing (CISD/NEET) proteins, support mitochondrial function in skeletal muscles. The abundance of these proteins declines during aging leading to muscle degeneration. Although the function of the outer mitochondrial CISD/NEET proteins, CISD1/mitoNEET and CISD2/NAF-1, has been defined in skeletal muscle cells, the role of the inner mitochondrial CISD protein, CISD3/MiNT, is currently unknown. Here, we show that CISD3 deficiency in mice results in muscle atrophy that shares proteomic features with Duchenne muscular dystrophy. We further reveal that CISD3 deficiency impairs the function and structure of skeletal muscles, as well as their mitochondria, and that CISD3 interacts with, and donates its [2Fe-2S] clusters to, complex I respiratory chain subunit NADH Ubiquinone Oxidoreductase Core Subunit V2 (NDUFV2). Using coevolutionary and structural computational tools, we model a CISD3-NDUFV2 complex with proximal coevolving residue interactions conducive of [2Fe-2S] cluster transfer reactions, placing the clusters of the two proteins 10 to 16 Å apart. Taken together, our findings reveal that CISD3/MiNT is important for supporting the biogenesis and function of complex I, essential for muscle maintenance and function. Interventions that target CISD3 could therefore impact different muscle degeneration syndromes, aging, and related conditions.

The crosslinks between ferroptosis and autophagy in asthma

Autophagy is an evolutionarily conserved cellular process capable of degrading various biological molecules and organelles via the lysosomal pathway. Ferroptosis is a type of oxidative stress-dependent regulated cell death associated with the iron accumulation and lipid peroxidation. The crosslinks between ferroptosis and autophagy have been focused on since the dependence of ferroptosis on autophagy was discovered. Although the research and theories on the relationship between autophagy and ferroptosis remain scattered and fragmented, the crosslinks between these two forms of regulated cell death are closely related to the treatment of various diseases. Thereof, asthma as a chronic inflammatory disease has a tight connection with the occurrence of ferroptosis and autophagy since the crosslinked signal pathways may be the crucial regulators or exactly regulated by cells and secretion in the immune system. In addition, non-immune cells associated with asthma are also closely related to autophagy and ferroptosis. Further studies of cross-linking asthma inflammation with crosslinked signaling pathways may provide us with several key molecules that regulate asthma through specific regulators. The crosslinks between autophagy and ferroptosis provide us with a new perspective to interpret and understand the manifestations of asthma, potential drug discovery targets, and new therapeutic options to effectively intervene in the imbalance caused by abnormal inflammation in asthma. Herein, we introduce the main molecular mechanisms of ferroptosis, autophagy, and asthma, describe the role of crosslinks between ferroptosis and autophagy in asthma based on their common regulatory cells or molecules, and discuss potential drug discovery targets and therapeutic applications in the context of immunomodulatory and symptom alleviation.

MitoNEET's Reactivity of Lys55 toward Pyridoxal Phosphate Demonstrates its Activity as a Transaminase Enzyme

MitoNEET is a [2Fe-2S] redox active mitochondrial protein belonging to the CDGSH iron-sulfur domain (CISD) family of proteins. MitoNEET has been implicated as a potential target for drug development to treat various disorders, including type-2 diabetes, cancer, and Parkinson's disease. However, the specific cellular function(s) for mitoNEET still remains to be fully elucidated, and this presents a significant roadblock in rational drug development. Here, we show that mitoNEET binds the enzymatic cofactor pyridoxal phosphate (PLP) specifically at only one of its 11 lysine residues, Lys55. Lys55 is part of the soluble portion of the protein and is in a hydrogen-bonding network with the histidine residue that ligates the [2Fe-2S] cluster. In the presence of mitoNEET, PLP catalyzes the transamination reaction of the amino acid cysteine and the alpha-keto acid 2-oxoglutarate to form 3-mercaptopyruvate and glutamate. This work identifies, for the first time, mitoNEET as an enzyme with cysteine transaminase activity.

Dysregulated Ca2+ Homeostasis as a Central Theme in Neurodegeneration: Lessons from Alzheimer's Disease and Wolfram Syndrome

Calcium ions (Ca²⁺) operate as important messengers in the cell, indispensable for signaling the underlying numerous cellular processes in all of the cell types in the human body. In neurons, Ca²⁺ signaling is crucial for regulating synaptic transmission and for the processes of learning and memory formation. Hence, the dysregulation of intracellular Ca²⁺ homeostasis results in a broad range of disorders, including cancer and neurodegeneration. A major source for intracellular Ca²⁺ is the endoplasmic reticulum (ER), which has close contacts with other organelles, including mitochondria. In this review, we focus on the emerging role of Ca²⁺ signaling at the ER–mitochondrial interface in two different neurodegenerative diseases, namely Alzheimer’s disease and Wolfram syndrome. Both of these diseases share some common hallmarks in the early stages, including alterations in the ER and mitochondrial Ca²⁺ handling, mitochondrial dysfunction and increased Reactive oxygen species (ROS) production. This indicates that similar mechanisms may underly these two disease pathologies and suggests that both research topics might benefit from complementary research.

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families. Does successful inference mainly rely on correlations from structural contacts or from phylogeny, or both? Do these two types of signal combine constructively or hinder each other? To address these questions, we generate and analyze synthetic data produced using a minimal model that allows us to control the amounts of structural constraints and phylogeny. We show that correlations from these two sources combine constructively to increase the performance of partner inference by DCA or MI. Furthermore, signal from phylogeny can rescue partner inference when signal from contacts becomes less informative, including in the realistic case where inter-protein contacts are restricted to a small subset of sites. We also demonstrate that DCA-inferred couplings between non-contact pairs of sites improve partner inference in the presence of strong phylogeny, while deteriorating it otherwise. Moreover, restricting to non-contact pairs of sites preserves inference performance in the presence of strong phylogeny. In a natural data set, as well as in realistic synthetic data based on it, we find that non-contact pairs of sites contribute positively to partner inference performance, and that restricting to them preserves performance, evidencing an important role of phylogeny.

Disrupting CISD2 function in cancer cells primarily impacts mitochondrial labile iron levels and triggers TXNIP expression

The CISD2 (NAF-1) protein plays a key role in regulating cellular homeostasis, aging, cancer and neurodegenerative diseases. It was found to control different calcium, reactive oxygen species (ROS), and iron signaling mechanisms. However, since most studies of CISD2 to date were conducted with cells that constitutively lack, overexpress, or contain mutations in CISD2, the relationships between these different signaling processes are unclear. To address the hierarchy of signaling events occurring in cells upon CISD2 disruption, we developed an inducible system to express CISD2, or the dominant-negative H114C inhibitor of CISD2, in human breast cancer cells. Here, we report that inducible disruption of CISD2 function causes an immediate disruption in mitochondrial labile iron (mLI), and that this disruption results in enhanced mitochondrial ROS (mROS) levels. We further show that alterations in cytosolic and ER calcium levels occur only after the changes in mLI and mROS levels happen and are unrelated to them. Interestingly, disrupting CISD2 function resulted in the enhanced expression of the tumor suppressor thioredoxin-interacting protein (TXNIP) that was dependent on the accumulation of mLI and associated with ferroptosis activation. CISD2 could therefore regulate the expression of TXNIP in cancer cells, and this regulation is dependent on alterations in mLI levels.

Uniting the divergent Wolfram syndrome-linked proteins WFS1 and CISD2 as modulators of Ca2+ signaling

[Figure: see text].

CISD2 Promotes Resistance to Sorafenib-Induced Ferroptosis by Regulating Autophagy in Hepatocellular Carcinoma

Purpose

Sorafenib is a multi-kinase inhibitor that is used as a standard treatment for advanced hepatocellular carcinoma (HCC). However, the mechanism of sorafenib resistance in HCC is still unclear. It has been shown that CISD2 expression is related to the progression and poor prognosis of HCC. Here, we show a new role for CISD2 in sorafenib resistance in HCC.

Methods

Bioinformatic analysis was used to detect the expression of negative regulatory genes of ferroptosis in sorafenib-resistant samples. The concentration gradient method was used to establish sorafenib-resistant HCC cells. Western blot was used to detect the protein expression of CISD2, LC3, ERK, PI3K, AKT, mTOR, and Beclin1 in HCC samples. Quantitative real-time PCR (qPCR) was used to detect gene expression. CISD2 shRNA and Beclin1 shRNA were transfected to knock down the expression of the corresponding genes. Cell viability was detected by a CCK-8 assay. ROS were detected by DCFH-DA staining, and MDA and GSH were detected with a Lipid Peroxidation MDA Assay Kit and Micro Reduced Glutathione (GSH) Assay Kit, respectively. Flow cytometry was used to detect apoptosis and the levels of ROS and iron ions.

Results

CISD2 was highly expressed in HCC cells compared with normal cells and was associated with poor prognosis in patients. Knockdown of CISD2 promoted a decrease in the viability of drug-resistant HCC cells. CISD2 knockdown promoted sorafenib-induced ferroptosis in resistant HCC cells. The levels of ROS, MDA, and iron ions increased, but the change in GSH was not obvious. Knockdown of CISD2 promoted uncontrolled autophagy in resistant HCC cells. Inhibition of autophagy attenuated CISD2 knockdown-induced ferroptosis. The autophagy promoted by CISD2 knockdown was related to Beclin1. When CISD2 and Beclin1 were inhibited, the effect on ferroptosis was correspondingly weakened.

Conclusion

Inhibition of CISD2 promoted sorafenib-induced ferroptosis in resistant cells, and this process promoted excessive iron ion accumulation through autophagy, leading to ferroptosis. The combination of CISD2 inhibition and sorafenib treatment is an effective therapeutic strategy for resistant HCC.

CISD2 plays a role in age-related diseases and cancer

CDGSH iron-sulfur domain 2 (Cisd2) is an evolutionarily conserved protein that plays an important regulatory role in aging-related diseases and cancers. Since its discovery, Cisd2 has been identified as a regulatory factor for the aging of the human body and the regulation of mammalian lifespan. Cisd2 is also an oncoprotein that regulates the occurrence and development of cancer. Cisd2 mediates the occurrence of diseases related to human aging and the proliferation, differentiation, metastasis, and invasion of various cancer cells through various mechanisms. Multiple studies have shown that Cisd2 expression is related to the clinical characteristics of aging-related diseases and patients with cancer, and its expression profile is a novel diagnostic and prognostic biomarker for a variety of human diseases. Modulating the expression or function of Cisd2 may be a potential treatment strategy for different diseases. In this review, we summarize the role of Cisd2 in human aging-related diseases and various cancers, as well as the biological functions, underlying mechanisms, and potential clinical significance.

MiR-127-3p targeting CISD1 regulates autophagy in hypoxic-ischemic cortex

Neonatal hypoxic-ischemic (HI) injury derived from asphyxia during perinatal period, is a serious complication of neonatal asphyxia and the main cause of neonatal acute death and chronic neurological injury. Aberrant autophagy occurs in many nervous system diseases, but its role and underlying mechanism in HI injury is largely unknown. Here, we successfully constructed a newborn rat model of HI brain injury, and the knockout-miR-127-3p (KO-miR-127-3p) rats were structured by using CRISPR/Cas9. Subsequently, the in vitro functional experiments, in vivo zea-longa scores, as well as bioinformatics analyses and biological experiments were applied. The expression of autophagy-related proteins, including ATG12, P62, Beclin-1, LC3II in HI cortex with miR-127-3p knockout was significantly decreased, and autophagic vacuoles were disappeared. Moreover, miR-127-3p has a specific regulatory effect on CISD1 expression, another crucial molecule in autophagy process. Accordingly, the overexpression of CISD1 effectively inhibited the autophagic cell death and physiological dysfunction in the brain of HI injury, whereas si-CISD1 reversed the neuroprotective effects of KO-miR-127-3p. Our findings explained the underlying mechanism for HI injury, and miR-127-3p targeting CISD1 signal could be supposed as a new treatment strategy to prevent and treat HI injury.

The Role of Mitochondria in the Chemoresistance of Pancreatic Cancer Cells

The first-line chemotherapies for patients with unresectable pancreatic cancer (PC) are 5-fluorouracil (5-FU) and gemcitabine therapy. However, due to chemoresistance the prognosis of patients with PC has not been significantly improved. Mitochondria are essential organelles in eukaryotes that evolved from aerobic bacteria. In recent years, many studies have shown that mitochondria play important roles in tumorigenesis and may act as chemotherapeutic targets in PC. In addition, according to recent studies, mitochondria may play important roles in the chemoresistance of PC by affecting apoptosis, metabolism, mtDNA metabolism, and mitochondrial dynamics. Interfering with some of these factors in mitochondria may improve the sensitivity of PC cells to chemotherapeutic agents, such as gemcitabine, making mitochondria promising targets for overcoming chemoresistance in PC.

Cancer cell death strategies by targeting Bcl-2's BH4 domain

The Bcl-2-family proteins have long been known for their role as key regulators of apoptosis. Overexpression of various members of the family is associated with oncogenesis. Its founding member, anti-apoptotic Bcl-2 regulates cell death at different levels, whereby Bcl-2 emerged as a major drug target to eradicate cancers through cell death. This resulted in the development of venetoclax, a Bcl-2 antagonist that acts as a BH3 mimetic. Venetoclax already entered the clinic to treat relapse chronic lymphocytic leukemia patients. Here, we discuss the role of Bcl-2 as a decision-maker in cell death with focus on the recent advances in anti-cancer therapeutics that target the BH4 domain of Bcl-2, thereby interfering with non-canonical functions of Bcl-2 in Ca²⁺-signaling modulation. In particular, we critically discuss previously developed tools, including the peptide BIRD-2 (Bcl-2/IP₃R-disrupter-2) and the small molecule BDA-366. In addition, we present a preliminary analysis of two recently identified molecules that emerged from a molecular modeling approach to target Bcl-2's BH4 domain, which however failed to induce cell death in two Bcl-2-dependent diffuse large B-cell lymphoma cell models. Overall, antagonizing the non-canonical functions of Bcl-2 by interfering with its BH4-domain biology holds promise to elicit cell death in cancer, though improved tools and on-target antagonizing small molecules remain necessary and ought to be designed.

Decoding Protein-protein Interactions: An Overview

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

CISD2 maintains cellular homeostasis

CDGSH Iron Sulfur Domain 2 (CISD2) is the causative gene for the disease Wolfram syndrome 2 (WFS2; MIM 604928), which is an autosomal recessive disorder showing metabolic and neurodegenerative manifestations. CISD2 protein can be localized on the endoplasmic reticulum (ER), outer mitochondrial membrane (OMM) and mitochondria-associated membrane (MAM). CISD2 plays a crucial role in the regulation of cytosolic Ca²⁺ homeostasis, ER integrity and mitochondrial function. Here we summarize the most updated publications and discuss the central role of CISD2 in maintaining cellular homeostasis. This review mainly focuses on the following topics. Firstly, that CISD2 has been recognized as a prolongevity gene and the level of CISD2 is a key determinant of lifespan and healthspan. In mice, Cisd2 deficiency shortens lifespan and accelerates aging. Conversely, a persistently high level of Cisd2 promotes longevity. Intriguingly, exercise stimulates Cisd2 gene expression and thus, the beneficial effects offered by exercise may be partly related to Cisd2 activation. Secondly, that Cisd2 is down-regulated in a variety of tissues and organs during natural aging. Three potential mechanisms that may mediate the age-dependent decrease of Cisd2, via regulating at different levels of gene expression, are discussed. Thirdly, the relationship between CISD2 and cell survival, as well as the potential mechanisms underlying the cell death control, are discussed. Finally we discuss that, in cancers, CISD2 may functions as a double-edged sword, either suppressing or promoting cancer development. This review highlights the importance of the CISD2 in aging and age-related diseases and identifies the urgent need for the translation of available genetic evidence into pharmaceutic interventions in order to alleviate age-related disorders and extend a healthy lifespan in humans.

Frustration and Direct-Coupling Analyses to Predict Formation and Function of Adeno-Associated Virus

Adeno-associated virus (AAV) is a promising gene therapy vector because of its efficient gene delivery and relatively mild immunogenicity. To improve delivery target specificity, researchers use combinatorial and rational library design strategies to generate novel AAV capsid variants. These approaches frequently propose high proportions of nonforming or noninfective capsid protein sequences that reduce the effective depth of synthesized vector DNA libraries, thereby raising the discovery cost of novel vectors. We evaluated two computational techniques for their ability to estimate the impact of residue mutations on AAV capsid protein-protein interactions and thus predict changes in vector fitness, reasoning that these approaches might inform the design of functionally enriched AAV libraries and accelerate therapeutic candidate identification. The Frustratometer computes an energy function derived from the energy landscape theory of protein folding. Direct-coupling analysis (DCA) is a statistical framework that captures residue coevolution within proteins. We applied the Frustratometer to select candidate protein residues predicted to favor assembled or disassembled capsid states, then predicted mutation effects at these sites using the Frustratometer and DCA. Capsid mutants were experimentally assessed for changes in virus formation, stability, and transduction ability. The Frustratometer-based metric showed a counterintuitive correlation with viral stability, whereas a DCA-derived metric was highly correlated with virus transduction ability in the small population of residues studied. Our results suggest that coevolutionary models may be able to elucidate complex capsid residue-residue interaction networks essential for viral function, but further study is needed to understand the relationship between protein energy simulations and viral capsid metastability.

Statistical physics of interacting proteins: Impact of dataset size and quality assessed in synthetic sequences

Identifying protein-protein interactions is crucial for a systems-level understanding of the cell. Recently, algorithms based on inverse statistical physics, e.g., direct coupling analysis (DCA), have allowed to use evolutionarily related sequences to address two conceptually related inference tasks: finding pairs of interacting proteins and identifying pairs of residues which form contacts between interacting proteins. Here we address two underlying questions: How are the performances of both inference tasks related? How does performance depend on dataset size and the quality? To this end, we formalize both tasks using Ising models defined over stochastic block models, with individual blocks representing single proteins and interblock couplings protein-protein interactions; controlled synthetic sequence data are generated by Monte Carlo simulations. We show that DCA is able to address both inference tasks accurately when sufficiently large training sets of known interaction partners are available and that an iterative pairing algorithm allows to make predictions even without a training set. Noise in the training data deteriorates performance. In both tasks we find a quadratic scaling relating dataset quality and size that is consistent with noise adding in square-root fashion and signal adding linearly when increasing the dataset. This implies that it is generally good to incorporate more data even if their quality are imperfect, thereby shedding light on the empirically observed performance of DCA applied to natural protein sequences.

Epistatic contributions promote the unification of incompatible models of neutral molecular evolution

Mathematical models of evolution help us understand mechanisms driving protein-sequence change. Previous models recapitulate a disjoint subset of statistical features of natural sequences. We present a neutral evolution model that unifies features including extreme variance of the molecular clock’s tick rate and the observation of an evolutionary Stokes shift, an irreversible effect of mutations in the fitness landscape during sequence evolution. We show that interactions between amino acid sites, which inform our fitness metric, are required to observe these features. These interactions are inferred by using direct coupling analysis, which has been successfully utilized to predict protein structures, dynamics, and complexes from coevolutionary information. We anticipate our model will have applications in phylogenetics, ancestral reconstruction of sequences, and protein design.

We introduce a model of amino acid sequence evolution that accounts for the statistical behavior of real sequences induced by epistatic interactions. We base the model dynamics on parameters derived from multiple sequence alignments analyzed by using direct coupling analysis methodology. Known statistical properties such as overdispersion, heterotachy, and gamma-distributed rate-across-sites are shown to be emergent properties of this model while being consistent with neutral evolution theory, thereby unifying observations from previously disjointed evolutionary models of sequences. The relationship between site restriction and heterotachy is characterized by tracking the effective alphabet dynamics of sites. We also observe an evolutionary Stokes shift in the fitness of sequences that have undergone evolution under our simulation. By analyzing the structural information of some proteins, we corroborate that the strongest Stokes shifts derive from sites that physically interact in networks near biochemically important regions. Perspectives on the implementation of our model in the context of the molecular clock are discussed.

Coevolutionary Couplings Unravel PAM-Proximal Constraints of CRISPR-SpCas9

The clustered regularly interspaced short palindromic repeats (CRISPR) system, an immune system analog found in prokaryotes, allows a single-guide RNA to direct a CRISPR-associated protein (Cas) with combined helicase and nuclease activity to DNA. The presence of a specific protospacer adjacent motif (PAM) next to the DNA target site plays a crucial role in determining both efficacy and specificity of gene editing. Herein, we introduce a coevolutionary framework to computationally unveil nonobvious molecular interactions in CRISPR systems and experimentally probe their functional role. Specifically, we use direct coupling analysis, a statistical inference framework used to infer direct coevolutionary couplings, in the context of protein/nucleic acid interactions. Applied to Streptococcus pyogenes Cas9, a Hamiltonian metric obtained from coevolutionary relationships reveals, to our knowledge, novel PAM-proximal nucleotide preferences at the seventh position of S. pyogenes Cas9 PAM (5'-NGRNNNT-3'), which was experimentally confirmed by in vitro and functional assays in human cells. We show that coevolved and conserved interactions point to specific clues toward rationally engineering new generations of Cas9 systems and may eventually help decipher the diversity of this family of proteins.

Phylogenetic correlations can suffice to infer protein partners from sequences

Determining which proteins interact together is crucial to a systems-level understanding of the cell. Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among paralogous proteins from sequence data. This success of DCA at predicting protein-protein interactions could be mainly based on its known ability to identify pairs of residues that are in contact in the three-dimensional structure of protein complexes and that coevolve to remain physicochemically complementary. However, interacting proteins possess similar evolutionary histories. What is the role of purely phylogenetic correlations in the performance of DCA-based methods to infer interaction partners? To address this question, we employ controlled synthetic data that only involve phylogeny and no interactions or contacts. We find that DCA accurately identifies the pairs of synthetic sequences that share evolutionary history. While phylogenetic correlations confound the identification of contacting residues by DCA, they are thus useful to predict interacting partners among paralogs. We find that DCA performs as well as phylogenetic methods to this end, and slightly better than them with large and accurate training sets. Employing DCA or phylogenetic methods within an Iterative Pairing Algorithm (IPA) allows to predict pairs of evolutionary partners without a training set. We further demonstrate the ability of these various methods to correctly predict pairings among real paralogous proteins with genome proximity but no known direct physical interaction, illustrating the importance of phylogenetic correlations in natural data. However, for physically interacting and strongly coevolving proteins, DCA and mutual information outperform phylogenetic methods. We finally discuss how to distinguish physically interacting proteins from proteins that only share a common evolutionary history.

Many biologically important protein-protein interactions are conserved over evolutionary time scales. This leads to two different signals that can be used to computationally predict interactions between protein families and to identify specific interaction partners. First, the shared evolutionary history leads to highly similar phylogenetic relationships between interacting proteins of the two families. Second, the need to keep the interaction surfaces of partner proteins biophysically compatible causes a correlated amino-acid usage of interface residues. Employing simulated data, we show that the shared history alone can be used to detect partner proteins. Similar accuracies are achieved by algorithms comparing phylogenetic relationships and by methods based on Direct Coupling Analysis (DCA), which are primarily known for their ability to detect the second type of signal. Using natural sequence data, we show that in cases with shared evolutionary history but without known physical interactions, both methods work with similar accuracy, while for some physically interacting systems, DCA and mutual information outperform phylogenetic methods. We propose methods allowing both to predict interactions between protein families and to find interacting partners among paralogs.

Redox-dependent gating of VDAC by mitoNEET

This work demonstrates that the outer mitochondrial-anchored [2Fe-2S] mitoNEET is able to bind within the central cavity of the voltage-dependent anion channel (VDAC) and regulate its gating in a redox-dependent manner. These findings have implications for ferroptosis, apoptosis, and iron metabolism by linking VDAC function, mitoNEET, and the redox environment of the cell. Furthermore, these findings introduce a potential player to the many mechanisms that may alter VDAC’s governance in times of homeostasis or strife.

MitoNEET is an outer mitochondrial membrane protein essential for sensing and regulation of iron and reactive oxygen species (ROS) homeostasis. It is a key player in multiple human maladies including diabetes, cancer, neurodegeneration, and Parkinson’s diseases. In healthy cells, mitoNEET receives its clusters from the mitochondrion and transfers them to acceptor proteins in a process that could be altered by drugs or during illness. Here, we report that mitoNEET regulates the outer-mitochondrial membrane (OMM) protein voltage-dependent anion channel 1 (VDAC1). VDAC1 is a crucial player in the cross talk between the mitochondria and the cytosol. VDAC proteins function to regulate metabolites, ions, ROS, and fatty acid transport, as well as function as a “governator” sentry for the transport of metabolites and ions between the cytosol and the mitochondria. We find that the redox-sensitive [2Fe-2S] cluster protein mitoNEET gates VDAC1 when mitoNEET is oxidized. Addition of the VDAC inhibitor 4,4′-diisothiocyanatostilbene-2,2′-disulfonate (DIDS) prevents both mitoNEET binding in vitro and mitoNEET-dependent mitochondrial iron accumulation in situ. We find that the DIDS inhibitor does not alter the redox state of MitoNEET. Taken together, our data indicate that mitoNEET regulates VDAC in a redox-dependent manner in cells, closing the pore and likely disrupting VDAC’s flow of metabolites.

The role of coevolutionary signatures in protein interaction dynamics, complex inference, molecular recognition, and mutational landscapes

Evolution imposes constraints at the interface of interacting biomolecules in order to preserve function or maintain fitness. This pressure may have a direct effect on the sequence composition of interacting biomolecules. As a result, statistical patterns of amino acid or nucleotide covariance that encode for physical and functional interactions are observed in sequences of extant organisms. In recent years, global pairwise models of amino acid and nucleotide coevolution from multiple sequence alignments have been developed and utilized to study molecular interactions in structural biology. In proteins, for which the energy landscape is funneled and minimally frustrated, a direct connection between the physical and sequence space landscapes can be established. Estimating coevolutionary information from sequences of interacting molecules has a broad impact in molecular biology. Applications include the accurate determination of 3D structures of molecular complexes, inference of protein interaction partners, models of protein-protein interaction specificity, the elucidation, and design of protein-nucleic acid recognition as well as the discovery of genome-wide epistatic effects. The current state of the art of coevolutionary analysis includes biomedical applications ranging from mutational landscapes and drug-design to vaccine development.

NEET Proteins: A New Link Between Iron Metabolism, Reactive Oxygen Species, and Cancer

SIGNIFICANCE

Cancer cells accumulate high levels of iron and reactive oxygen species (ROS) to promote their high metabolic activity and proliferation rate. However, high levels of iron and ROS can also lead to enhanced oxidative stress and the activation of cell death pathways such as apoptosis and ferroptosis. This has led to the proposal that different drugs that target iron and/or ROS metabolism could be used as anticancer drugs. However, due to the complex role iron and ROS play in cells, the majority of these drugs yielded mixed results, highlighting a critical need to identify new players in the regulation of iron and ROS homeostasis in cancer cells. Recent Advances: NEET proteins belong to a newly discovered class of iron-sulfur proteins (2Fe-2S) required for the regulation of iron and ROS homeostasis in cells. Recent studies revealed that the NEET proteins NAF-1 (CISD2) and mitoNEET (CISD1) play a critical role in promoting the proliferation of cancer cells, supporting tumor growth and metastasis. Moreover, the function of NEET proteins in cancer cells was found to be dependent of the degree of lability of their 2Fe-2S clusters.

CRITICAL ISSUES

NEET proteins could represent a key regulatory link between the maintenance of high iron and ROS in cancer cells, the activation of cell death and survival pathways, and cellular proliferation.

FUTURE DIRECTIONS

Because the function of NEET proteins depends on the lability of their clusters, drugs that target the 2Fe2S clusters of NEET proteins could be used as promising anticancer drugs.

Cathepsin B defines leader cells during the collective invasion of salivary adenoid cystic carcinoma

Cathepsin B (CTSB) has been reported to be involved in cancer metastasis by altering extracellular matrix (ECM) remodeling and facilitating invasion. However, the contribution of CTSB to collective cell invasion in salivary adenoid cystic carcinoma (SACC) and the underlying mechanisms remain unclear. The present study demonstrated that collective cell invasion is commonly observed in SACC without a complete epithelial-mesenchymal transition signature. CTSB was found to be overexpressed in the invasive front of SACC compared to the tumor center, and was associated with a poor prognosis of patients with SACC. Subsequently, a 3D spheroid invasion assay was established in order to recapitulate the collective cell invasion of SACC and the results revealed that CTSB was only expressed in leader cells. The knockdown of CTSB by siRNA inhibited the migration and invasion of SACC-83 cells and impaired the formation of leader cells. CTSB knockdown also disrupted cytoskeletal organization, altered cell morphology and inhibited ECM remodeling by downregulating matrix metalloproteinase-9, focal adhesion kinase and Rho/ROCK function. Therefore, the present study provides evidence that CTSB may define leader cells in SACC and is required for collective cell invasion as a potential key regulator of ECM remodeling.

Coevolutionary Signals and Structure-Based Models for the Prediction of Protein Native Conformations

The analysis of coevolutionary signals from families of evolutionarily related sequences is a recent conceptual framework that provides valuable information about unique intramolecular interactions and, therefore, can assist in the elucidation of biomolecular conformations. It is based on the idea that compensatory mutations at specific residue positions in a sequence help preserve stability of protein architecture and function and leave a statistical signature related to residue-residue interactions in the 3D structure of the protein. Consequently, statistical analysis of these correlated mutations in subsets of protein sequence alignments can be used to predict which residue pairs should be in spatial proximity in the native functional protein fold. These predicted signals can be then used to guide molecular dynamics (MD) simulations to predict the three-dimensional coordinates of a functional amino acid chain. In this chapter, we introduce a general and efficient methodology to perform coevolutionary analysis on protein sequences and to use this information in combination with computational physical models to predict the native 3D conformation of functional polypeptides. We present a step-by-step methodology that includes the description and application of software tools and databases required to infer tertiary structures of a protein fold. The general pipeline includes instructions on (1) how to obtain direct amino acid couplings from protein sequences using direct coupling analysis (DCA), (2) how to incorporate such signals as interaction potentials in C_α structure-based models (SBMs) to drive protein-folding MD simulations, (3) a procedure to estimate secondary structure and how to include such estimates in the topology files required in the MD simulations, and (4) how to build full atomic models based on the top C_α candidates selected in the pipeline. The information presented in this chapter is self-contained and sufficient to allow a computational scientist to predict structures of proteins using publicly available algorithms and databases.

The anti-apoptotic proteins NAF-1 and iASPP interact to drive apoptosis in cancer cells

We reveal a novel interaction between the two anti-apoptotic proteins iASPP and NAF-1, which are overexpressed in many types of cancer cells, and propose that this interaction is required for apoptosis activation in cancer cells. A peptide derived from the interaction interface inhibits apoptosis in cells.

Suppression of apoptosis is a key Hallmark of cancer cells, and reactivation of apoptosis is a major avenue for cancer therapy. We reveal an interaction between the two anti-apoptotic proteins iASPP and NAF-1, which are overexpressed in many types of cancer cells and tumors. iASPP is an inhibitory member of the ASPP protein family, whereas NAF-1 belongs to the NEET 2Fe–2S protein family. We show that the two proteins are stimulated to interact in cells during apoptosis. Using peptide array screening and computational methods we mapped the interaction interfaces of both proteins to residues 764–778 of iASPP that bind to a surface groove of NAF-1. A peptide corresponding to the iASPP 764–780 sequence stabilized the NAF-1 cluster, inhibited NAF-1 interaction with iASPP, and inhibited staurosporine-induced apoptosis activation in human breast cancer, as well as in PC-3 prostate cancer cells in which p53 is inactive. The iASPP 764–780 IC₅₀ value for inhibition of cell death in breast cancer cells was 13 ± 1 μM. The level of cell death inhibition by iASPP 764–780 was altered in breast cancer cells expressing different levels and/or variants of NAF-1, indicating that the peptide activity is associated with NAF-1 function. We propose that the interaction between iASPP and NAF-1 is required for apoptosis activation in cancer cells. This interaction uncovers a new layer in the highly complex regulation of cell death in cancer cells and opens new avenues of exploration into the development of novel anticancer drugs that reactivate apoptosis in malignant tumors.

Inferring interaction partners from protein sequences using mutual information

Functional protein-protein interactions are crucial in most cellular processes. They enable multi-protein complexes to assemble and to remain stable, and they allow signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interacting partners, and thus in correlations between their sequences. Pairwise maximum-entropy based models have enabled successful inference of pairs of amino-acid residues that are in contact in the three-dimensional structure of multi-protein complexes, starting from the correlations in the sequence data of known interaction partners. Recently, algorithms inspired by these methods have been developed to identify which proteins are functional interaction partners among the paralogous proteins of two families, starting from sequence data alone. Here, we demonstrate that a slightly higher performance for partner identification can be reached by an approximate maximization of the mutual information between the sequence alignments of the two protein families. Our mutual information-based method also provides signatures of the existence of interactions between protein families. These results stand in contrast with structure prediction of proteins and of multi-protein complexes from sequence data, where pairwise maximum-entropy based global statistical models substantially improve performance compared to mutual information. Our findings entail that the statistical dependences allowing interaction partner prediction from sequence data are not restricted to the residue pairs that are in direct contact at the interface between the partner proteins.

CISD2 inhibition overcomes resistance to sulfasalazine-induced ferroptotic cell death in head and neck cancer

Sulfasalazine has been repurposed to induce ferroptotic cancer cell death via inhibition of x_c^--cystine/glutamate antiporter (xCT). However, cancer cells are capable of developing mechanisms to evade cell death. Therefore, we sought to determine the molecular mechanisms underlying resistance to sulfasalazine-induced ferroptosis in head and neck cancer (HNC). The effects of sulfasalazine and pioglitazone were tested in various HNC cell lines. The effects of these drugs and inhibition and overexpression of CISD2 gene were determined by evaluating viability, cell death, lipid ROS production, mitochondrial iron, and mouse tumor xenograft models. SAS induced ferroptotic cell death in HNC at different levels. CISD2 expression showed an association between its expression and ferroptosis resistance. CISD2 overexpression conferred resistance to ferroptosis by sulfasalazine. Silencing CISD2 gene rendered resistant HNC cells susceptible to sulfasalazine-induced ferroptosis, with increased levels of lipid ROS and mitochondrial ferrous iron. Pioglitazone induced over-accumulation of mitochondrial iron and ROS and sensitized resistant HNC cells to sulfasalazine treatment in vitro and in a mouse tumor-xenograft model. CISD2 inhibition overcomes HNC resistance to ferroptotic cell death induced by sulfasalazine via increased accumulation of mitochondrial ferrous iron and lipid ROS.

The cisd gene family regulates physiological germline apoptosis through ced-13 and the canonical cell death pathway in Caenorhabditis elegans

Programmed cell death, which occurs through a conserved core molecular pathway, is important for fundamental developmental and homeostatic processes. The human iron-sulfur binding protein NAF-1/CISD2 binds to Bcl-2 and its disruption in cells leads to an increase in apoptosis. Other members of the CDGSH iron sulfur domain (CISD) family include mitoNEET/CISD1 and Miner2/CISD3. In humans, mutations in CISD2 result in Wolfram syndrome 2, a disease in which the patients display juvenile diabetes, neuropsychiatric disorders and defective platelet aggregation. The C. elegans genome contains three previously uncharacterized cisd genes that code for CISD-1, which has homology to mitoNEET/CISD1 and NAF-1/CISD2, and CISD-3.1 and CISD-3.2, both of which have homology to Miner2/CISD3. Disrupting the function of the cisd genes resulted in various germline abnormalities including distal tip cell migration defects and a significant increase in the number of cell corpses within the adult germline. This increased germ cell death is blocked by a gain-of-function mutation of the Bcl-2 homolog CED-9 and requires functional caspase CED-3 and the APAF-1 homolog CED-4. Furthermore, the increased germ cell death is facilitated by the pro-apoptotic, CED-9-binding protein CED-13, but not the related EGL-1 protein. This work is significant because it places the CISD family members as regulators of physiological germline programmed cell death acting through CED-13 and the core apoptotic machinery.

Phylogenetic analysis of the CDGSH iron-sulfur binding domain reveals its ancient origin

The iron-sulfur (2Fe-2S) binding motif CDGSH appears in many important plant and animal proteins that regulate iron and reactive oxygen metabolism. In human it is found in CISD1-3 proteins involved in diabetes, obesity, cancer, aging, cardiovascular disease and neurodegeneration. Despite the important biological role of the CDGSH domain, its origin, evolution and diversification, are largely unknown. Here, we report that: (1) the CDGSH domain appeared early in evolution, perhaps linked to the heavy use of iron-sulfur driven metabolism by early organisms; (2) a CISD3-like protein with two CDGSH domains on the same polypeptide appears to represent the ancient archetype of CDGSH proteins; (3) the origin of the human CISD3 protein is linked to the mitochondrial endosymbiotic event; (4) the CISD1/2 type proteins that contain only one CDGSH domain, but function as homodimers, originated after the divergence of bacteria and archaea/eukaryotes from their common ancestor; and (5) the human CISD1 and CISD2 proteins diverged about 650–720 million years ago, and CISD3 and CISD1/2 share their descent from an ancestral CISD about 1–1.1 billion years ago. Our findings reveal that the CDGSH domain is ancient in its origin and shed light on the complex evolutionary path of modern CDGSH proteins.

The unique fold and lability of the [2Fe-2S] clusters of NEET proteins mediate their key functions in health and disease

NEET proteins comprise a new class of [2Fe-2S] cluster proteins. In human, three genes encode for NEET proteins: cisd1 encodes mitoNEET (mNT), cisd2 encodes the Nutrient-deprivation autophagy factor-1 (NAF-1) and cisd3 encodes MiNT (Miner2). These recently discovered proteins play key roles in many processes related to normal metabolism and disease. Indeed, NEET proteins are involved in iron, Fe-S, and reactive oxygen homeostasis in cells and play an important role in regulating apoptosis and autophagy. mNT and NAF-1 are homodimeric and reside on the outer mitochondrial membrane. NAF-1 also resides in the membranes of the ER associated mitochondrial membranes (MAM) and the ER. MiNT is a monomer with distinct asymmetry in the molecular surfaces surrounding the clusters. Unlike its paralogs mNT and NAF-1, it resides within the mitochondria. NAF-1 and mNT share similar backbone folds to the plant homodimeric NEET protein (At-NEET), while MiNT's backbone fold resembles a bacterial MiNT protein. Despite the variation of amino acid composition among these proteins, all NEET proteins retained their unique CDGSH domain harboring their unique 3Cys:1His [2Fe-2S] cluster coordination through evolution. The coordinating exposed His was shown to convey the lability to the NEET proteins' [2Fe-2S] clusters. In this minireview, we discuss the NEET fold and its structural elements. Special attention is given to the unique lability of the NEETs' [2Fe-2S] cluster and the implication of the latter to the NEET proteins' cellular and systemic function in health and disease.

CISD2 enhances the chemosensitivity of gastric cancer through the enhancement of 5-FU-induced apoptosis and the inhibition of autophagy by AKT/mTOR pathway

Gastric cancer (GC) is a prevalent upper gastrointestinal tumor characterized by high morbidity and mortality due to imperfect screening systems and the rapid development of resistance to 5‐fluorouracil (5‐FU). CDGSH iron sulfur domain 2 (CISD2) has been recently regarded as a candidate oncogene in several types of tumors. It is, therefore, necessary to investigate its biological function and clinical significance in gastric cancer. In this study, the down‐regulated expression level of CISD2 in GC compared with adjacent normal tissues was evaluated by quantitative RT‐PCR and Western blotting. An immunohistochemical analysis indicated that CISD2 expression in GC was significantly correlated with age (P = 0.002), Lauren's classification (P = 0.001), and differentiation (P = 0.049). Two cell lines, MKN1 and BGC823, were used to analyze the role of CISD2 in gastric carcinogenesis and response to 5‐FU through CCK‐8 assays, the RT‐CES system, Transwell assays, flow cytometry, and confocal fluorescence microscopy. The overexpression of CISD2 resulted in reduced cellular growth and proliferation, inhibition of metastatic ability, and increased apoptosis. 5‐FU treatment increased endogenous as well as exogenous overexpression of CISD2 in GC cells. Further investigation revealed that CISD2 enhanced sensitivity to 5‐FU via an increase in apoptosis and inhibition of protective autophagy through the activation of the AKT/mTOR pathway. In conclusion, CISD2 is down‐regulated in gastric cancer, and its effects on the inhibition of cellular proliferation, metastatic ability, and increased chemotherapy sensitivity are mediated by antagonism to 5‐FU‐induced autophagy through the AKT/mTOR pathway.

Autophagy and Ferroptosis - What's the Connection?

PURPOSE OF REVIEW

Autophagy is a conserved intracellular degradation system and plays a dual role in cell death, depending on context and phase. Ferroptosis is a new form of regulated cell death that mainly depends on iron accumulation and lipid peroxidation. In this review, we summarize the processes of autophagy and ferroptosis and discuss their crosstalk mechanisms at the molecular level.

RECENT FINDINGS

The original study shows that ferroptosis is morphologically, biochemically, and genetically distinct from autophagy and other types of cell death. However, recent studies demonstrate that activation of ferroptosis is indeed dependent on the induction of autophagy. Additionally, many ferroptosis regulators such as SLC7A11, GPX4, NRF2, p53, HSPB1, CISD1, FANCD2, and ACSL4 have been identified as potential regulators of autophagy.

SUMMARY

This review not only highlights the importance of autophagy as an emerging mechanism of ferroptosis, but also raises new insights regarding regulated cell death.

Interactions between mitoNEET and NAF-1 in cells

The NEET proteins mitoNEET (mNT) and nutrient-deprivation autophagy factor-1 (NAF-1) are required for cancer cell proliferation and resistance to oxidative stress. NAF-1 and mNT are also implicated in a number of other human pathologies including diabetes, neurodegeneration and cardiovascular disease, as well as in development, differentiation and aging. Previous studies suggested that mNT and NAF-1 could function in the same pathway in mammalian cells, preventing the over-accumulation of iron and reactive oxygen species (ROS) in mitochondria. Nevertheless, it is unknown whether these two proteins directly interact in cells, and how they mediate their function. Here we demonstrate, using yeast two-hybrid, in vivo bimolecular fluorescence complementation (BiFC), direct coupling analysis (DCA), RNA-sequencing, ROS and iron imaging, and single and double shRNA lines with suppressed mNT, NAF-1 and mNT/NAF-1 expression, that mNT and NAF-1 directly interact in mammalian cells and could function in the same cellular pathway. We further show using an in vitro cluster transfer assay that mNT can transfer its clusters to NAF-1. Our study highlights the possibility that mNT and NAF-1 function as part of an iron-sulfur (2Fe-2S) cluster relay to maintain the levels of iron and Fe-S clusters under control in the mitochondria of mammalian cells, thereby preventing the activation of apoptosis and/or autophagy and supporting cellular proliferation.

Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone

Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.

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

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 docking-based 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.

iTRAQ-Based Proteomic Analysis of Ginsenoside F2 on Human Gastric Carcinoma Cells SGC7901

Ginsenoside F2 (F2), a protopanaxdiol type of saponin, was reported to inhibit human gastric cancer cells SGC7901. To better understand the molecular mechanisms of F2, an iTRAQ-based proteomics approach was applied to define protein expression profiles in SGC7901 cells in response to lower dose (20 μM) and shorter duration (12 hour) of F2 treatment, compared with previous study. 205 proteins were screened in terms of the change in their expression level which met our predefined criteria. Further bioinformatics and experiments demonstrated that F2 treatment downregulated PRR5 and RPS15 and upregulated RPL26, which are implicated in ribosomal protein-p53 signaling pathway. F2 also inhibited CISD2, Bcl-xl, and NLRX1, which are associated with autophagic pathway. Furthermore, it was demonstrated that F2 treatment increased Atg5, Atg7, Atg10, and PUMA, the critical downstream effectors of ribosomal protein-p53 signaling pathway, and Beclin-1, UVRAG, and AMBRA-1, the important molecules in Bcl-xl/Beclin-1 pathway. The 6 differentially abundant proteins, PRR5, CISD2, Bcl-xl, NLRX1, RPS15, and RPL26, were confirmed by western blot. Taken together, ribosomal protein-p53 signaling pathway and Bcl-xl/Beclin-1 pathway might be the most significantly regulated biological process by F2 treatment in SGC7901 cells, which provided valuable insights into the deep understanding of the molecular mechanisms of F2 for gastric cancer treatment.

Elucidating modes of activation and herbicide resistance by sequence assembly and molecular modelling of the Acetolactate synthase complex in sugarcane

Acetolactate synthase (ALS) catalyzes the first portion of the biosynthetic pathway leading to the generation of branched-chain amino acids. As such it is essential for plant health and is a major target for herbicides. ALS is a very poorly characterized molecule in sugarcane. The enzyme is activated and inhibited by a regulatory subunit (known as VAT1 in plants) whose mode of action is entirely unknown. Using Saccharum halepense as a template we have assembled the ALS gene of sugarcane (Saccharum hybrid) and have modelled the structure of ALS based on an Arabidopsis template (the first ALS model for a monocot). We have also assembled the ALS regulatory proteins (VAT1 and VAT2) from sugarcane and show that VAT2 is specific to true grasses. Employing a bacterial model, we have generated a structural model for VAT1, which explains why the separate domains of the proteins bind to either leucine or valine but not both. Using co-evolution studies we have determined molecular contacts by which we modelled the docking of VAT1 to ALS. In conclusion, we demonstrate how the binding of VAT1 to ALS activates ALS and show how VAT1 can also confer feedback inhibition to ALS. We validate our ALS model against biochemical data and employ this model to explain the function of a novel herbicide binding mutant in sugarcane.

Functional Implications of the spectrum of BCL2 mutations in Lymphoma

Mutations in the translocated BCL2 gene are often detected in diffuse large B-cell lymphomas (DLBCLs), indicating both their significance and pervasiveness. Large series genome sequencing of more than 200 DLBCLs has identified frequent BCL2 mutations clustered in the exons coding for the BH4 domain and the folded loop domain (FLD) of the protein. However, BCL2 mutations are mostly contemplated to represent bystander events with negligible functional impact on the pathogenesis of DLBCL. BCL2 arbitrates apoptosis through a classic interaction between its hydrophobic groove forming BH1-3 domains and the BH3 domain of pro-apoptotic members of the BCL2 family. The effects of mutations are mainly determined by the ability of the mutated BCL2 to mediate apoptosis by this inter-member protein binding. Nevertheless, BCL2 regulates diverse non-canonical pathways that are unlikely to be explained by canonical interactions. In this review, first, we identify recurrent missense mutations in the BH4 domain and the FLD reported in independent lymphoma sequencing studies. Second, we discuss the probable consequences of mutations on the binding ability of BCL2 to non-BCL2 family member proteins crucial for 1) maintaining mitochondrial energetics and calcium hemostasis such as VDAC, IP3R, and RyR and 2) oncogenic pathways implicated in the acquisition of the 'hallmarks of cancer' such as SOD, Raf-1, NFAT, p53, HIF-1α, and gelsolin. The study also highlights the likely ramifications of mutations on binding of BCL2 antagonists and BH3 profiling. Based on our analysis, we believe that an in-depth focus on BCL2 interactions mediated by these domains is warranted to elucidate the functional significance of missense mutations in DLBCL. In summary, we provide an extensive overview of the pleiotropic functions of BCL2 mediated by its physical binding interaction with other proteins and the various ways BCL2 mutations would affect the normal function of the cell leading to the development of DLBCL.

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

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 cross-talk 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.

Affinity purification-mass spectrometry analysis of bcl-2 interactome identified SLIRP as a novel interacting protein

Members of the bcl-2 protein family share regions of sequence similarity, the bcl-2 homology (BH) domains. Bcl-2, the most studied member of this family, has four BH domains, BH1–4, and has a critical role in resistance to antineoplastic drugs by regulating the mitochondrial apoptotic pathway. Moreover, it is also involved in other relevant cellular processes such as tumor progression, angiogenesis and autophagy. Deciphering the network of bcl-2-interacting factors should provide a critical advance in understanding the different functions of bcl-2. Here, we characterized bcl-2 interactome by mass spectrometry in human lung adenocarcinoma cells. In silico functional analysis associated most part of the identified proteins to mitochondrial functions. Among them we identified SRA stem–loop interacting RNA-binding protein, SLIRP, a mitochondrial protein with a relevant role in regulating mitochondrial messenger RNA (mRNA) homeostasis. We validated bcl-2/SLIRP interaction by immunoprecipitation and immunofluorescence experiments in cancer cell lines from different histotypes. We showed that, although SLIRP is not involved in mediating bcl-2 ability to protect from apoptosis and oxidative damage, bcl-2 binds and stabilizes SLIRP protein and regulates mitochondrial mRNA levels. Moreover, we demonstrated that the BH4 domain of bcl-2 has a role in maintaining this binding.

Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics

Experimentally derived structural constraints have been crucial to the implementation of computational models of biomolecular dynamics. For example, not only does crystallography provide essential starting points for molecular simulations but also high-resolution structures permit for parameterization of simplified models. Since the energy landscapes for proteins and other biomolecules have been shown to be minimally frustrated and therefore funneled, these structure-based models have played a major role in understanding the mechanisms governing folding and many functions of these systems. Structural information, however, may be limited in many interesting cases. Recently, the statistical analysis of residue co-evolution in families of protein sequences has provided a complementary method of discovering residue-residue contact interactions involved in functional configurations. These functional configurations are often transient and difficult to capture experimentally. Thus, co-evolutionary information can be merged with that available for experimentally characterized low free-energy structures, in order to more fully capture the true underlying biomolecular energy landscape.

Activation of apoptosis in NAF-1-deficient human epithelial breast cancer cells

Maintaining iron (Fe) ion and reactive oxygen species homeostasis is essential for cellular function, mitochondrial integrity and the regulation of cell death pathways, and is recognized as a key process underlying the molecular basis of aging and various diseases, such as diabetes, neurodegenerative diseases and cancer. Nutrient-deprivation autophagy factor 1 (NAF-1; also known as CISD2) belongs to a newly discovered class of Fe-sulfur proteins that are localized to the outer mitochondrial membrane and the endoplasmic reticulum. It has been implicated in regulating homeostasis of Fe ions, as well as the activation of autophagy through interaction with BCL-2. Here we show that small hairpin (sh)RNA-mediated suppression of NAF-1 results in the activation of apoptosis in epithelial breast cancer cells and xenograft tumors. Suppression of NAF-1 resulted in increased uptake of Fe ions into cells, a metabolic shift that rendered cells more susceptible to a glycolysis inhibitor, and the activation of cellular stress pathways that are associated with HIF1α. Our studies suggest that NAF-1 is a major player in the metabolic regulation of breast cancer cells through its effects on cellular Fe ion distribution, mitochondrial metabolism and the induction of apoptosis.

CISD2 associated with proliferation indicates negative prognosis in patients with hepatocellular carcinoma

BACKGROUND

An evolutionarily conserved gene, the CDGSH iron sulfur domain 2 (CISD2), functions to control mammalian life span and regulates human cells proliferation. However, the role of CISD2 in HCC remains unclear. This study was aimed at investigating the expression pattern and clinicopathological significance of CISD2 in patients with HCC.

METHODS

The mRNA and protein expression levels of CISD2 were analyzed in six HCC lines and eight paired hepatic cancer tumors by real-time PCR, Western blotting and immunohistochemical staining. Statistical analysis was used to evaluate the clinicopathological significance of CISD2 expression. Short hairpin RNA interfering approach was employed to suppress endogenous CISD2 expression in hepatic cancer cells to determine its role in proliferation.

RESULTS

CISD2 expression in liver cancer cell lines and tissues was significantly up-regulated at both the RNA and protein levels compared with that in normal cells and adjacent non-tumorous liver tissues (ANT). CISD2 was an independent prognostic factor for poor prognosis. It was correlated with tumor size (P=0.001), number of tumors (P=0.003), surgical margin (P=0.006), hepatitis B surface antigen (HBsAg) infection (P=0.002) and recurrence (P<0.001) of liver cancer. Multivariate analysis suggested that CISD2 expression was an independent prognostic indicator for the survival of patients with HCC. HCC patients with high CISD2 expression displayed a shorter overall survival and a higher recurrence rate than those with low CISD2 expression (P<0.05, respectively). Additionally, stable down-expression of CISD2 in hepatoma cells suppressed cell proliferation in vitro. Similarly, an in vivo assay showed that CISD2 down-regulation in hepatoma cells inhibited remarkably tumorigenic potential in tumor size and weight.

CONCLUSIONS

CISD2 protein may serve as a candidate prognostic marker and a novel therapeutic target for HCC and play an important role in promoting proliferation and enhanced progression of HCC.

Dimeric interactions and complex formation using direct coevolutionary couplings

We develop a procedure to characterize the association of protein structures into homodimers using coevolutionary couplings extracted from Direct Coupling Analysis (DCA) in combination with Structure Based Models (SBM). Identification of dimerization contacts using DCA is more challenging than intradomain contacts since direct couplings are mixed with monomeric contacts. Therefore a systematic way to extract dimerization signals has been elusive. We provide evidence that the prediction of homodimeric complexes is possible with high accuracy for all the cases we studied which have rich sequence information. For the most accurate conformations of the structurally diverse dimeric complexes studied the mean and interfacial RMSDs are 1.95Å and 1.44Å, respectively. This methodology is also able to identify distinct dimerization conformations as for the case of the family of response regulators, which dimerize upon activation. The identification of dimeric complexes can provide interesting molecular insights in the construction of large oligomeric complexes and be useful in the study of aggregation related diseases like Alzheimer's or Parkinson's.

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

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.