Engineering Agatoxin,a Cystine-Knot Peptide from Spider Venom,as a Molecular Probe for In Vivo Tumor Imaging

Background

Cystine-knot miniproteins, also known as knottins, have shown great potential as molecular scaffolds for the development of targeted therapeutics and diagnostic agents. For this purpose, previous protein engineering efforts have focused on knottins based on the Ecballium elaterium trypsin inhibitor (EETI) from squash seeds, the Agouti-related protein (AgRP) neuropeptide from mammals, or the Kalata B1 uterotonic peptide from plants. Here, we demonstrate that Agatoxin (AgTx), an ion channel inhibitor found in spider venom, can be used as a molecular scaffold to engineer knottins that bind with high-affinity to a tumor-associated integrin receptor.

Methodology/Principal Findings

We used a rational loop-grafting approach to engineer AgTx variants that bound to α_vβ₃ integrin with affinities in the low nM range. We showed that a disulfide-constrained loop from AgRP, a structurally-related knottin, can be substituted into AgTx to confer its high affinity binding properties. In parallel, we identified amino acid mutations required for efficient in vitro folding of engineered integrin-binding AgTx variants.Molecular imaging was used to evaluate in vivo tumor targeting and biodistribution of an engineered AgTx knottin compared to integrin-binding knottins based on AgRP and EETI.Knottin peptides were chemically synthesized and conjugated to a near-infrared fluorescent dye. Integrin-binding AgTx, AgRP, and EETI knottins all generated high tumor imaging contrast in U87MG glioblastoma xenograft models. Interestingly, EETI-based knottins generated significantly lower non-specific kidney imaging signals compared to AgTx and AgRP-based knottins.

Conclusions/Significance

In this study, we demonstrate that AgTx, a knottin from spider venom, can be engineered to bind with high affinity to a tumor-associated receptor target. This work validates AgTx as a viable molecular scaffold for protein engineering, and further demonstrates the promise of using tumor-targeting knottins as probes for in vivo molecular imaging.     

Knottin cyclization: impact on structure and dynamics

Background  

Present in various species, the knottins (also referred to as inhibitor cystine knots) constitute a group of extremely stable miniproteins with a plethora of biological activities. Owing to their small size and their high stability, knottins are considered as excellent leads or scaffolds in drug design. Two knottin families contain macrocyclic compounds, namely the cyclotides and the squash inhibitors. The cyclotide family nearly exclusively contains head-to-tail cyclized members. On the other hand, the squash family predominantly contains linear members. Head-to-tail cyclization is intuitively expected to improve bioactivities by increasing stability and lowering flexibility as well as sensitivity to proteolytic attack.     

Asteropsins B–D,sponge-derived knottins with potential utility as a novel scaffold for oral peptide drugs

Background

Known linear knottins are unsuitable as scaffolds for oral peptide drug due to their gastrointestinal instability. Herein, a new subclass of knottin peptides from Porifera is structurally described and characterized regarding their potential for oral peptide drug development.

Methods

Asteropsins B–D (ASPB, ASPC, and ASPD) were isolated from the marine sponge Asteropus sp. The tertiary structures of ASPB and ASPC were determined by solution NMR spectroscopy and that of ASPD by homology modeling.

Results

The isolated asteropsins B–D, together with the previously reported asteropsin A (ASPA), compose a new subclass of knottins that share a highly conserved structural framework and remarkable stability against the enzymes in gastrointestinal tract (chymotrypsin, elastase, pepsin, and trypsin) and human plasma.

Conclusion

Asteropsins can be considered as promising peptide scaffolds for oral bioavailability.

General significance

The structural details of asteropsins provide essential information for the engineering of orally bioavailable peptides.     

In vitro-engineered non-antibody protein therapeutics

Antibodies have proved to be a valuable mode of therapy for numerous diseases, mainly owing to their high target binding affinity and specificity. Unfortunately, antibodies are also limited in several respects, chief amongst those being the extremely high cost of manufacture. Therefore, non-antibody binding proteins have long been sought after as alternative therapies. New binding protein scaffolds are constantly being designed or discovered with some already approved for human use by the FDA. This review focuses on protein scaffolds that are either already being used in humans or are currently being evaluated in clinical trials. Although not all are expected to be approved, the significant benefits ensure that these molecules will continue to be investigated and developed as therapeutic alternatives to antibodies. Based on the location of the amino acids that mediate ligand binding, we place all the protein scaffolds under clinical development into two general categories: scaffolds with ligand-binding residues located in exposed flexible loops, and those with the binding residues located in protein secondary structures, such as α-helices. Scaffolds that fall under the first category include adnectins, anticalins, avimers, Fynomers, Kunitz domains, and knottins, while those belonging to the second category include affibodies, β-hairpin mimetics, and designed ankyrin repeat proteins (DARPins). Most of these scaffolds are thermostable and can be easily produced in microorganisms or completely synthesized chemically. In addition, many of these scaffolds derive from human proteins and thus possess very low immunogenic potential. Additional advantages and limitations of these protein scaffolds as therapeutics compared to antibodies will be discussed.     

适配体结合蛋白质靶标的亲和力表征方法及其在疾病诊断中的应用

核酸适配体是通过体外指数富集配体系统进化（SELEX）技术筛选获得,并能够和蛋白质靶标高特异性、高亲和力结合的单链寡核苷酸。核酸适配体不但具有抗体的识别特性,而且具有自己独特的优良性能,目前已应用于分析检验、食品安全和生物医药等各个领域。蛋白质具有多种多样的生物功能以及临床诊断价值。因此,核酸适配体针对蛋白质靶标并在蛋白质相关的基础研究领域受到广泛的关注。核酸适配体应用性能的优劣取决于与其靶标蛋白质的亲和力与特异性。本文主要综述核酸适配体对蛋白质靶标的亲和力表征方法,以及在药物研发、肿瘤检测、生物成像以及生物传感器方面的应用。     

Learning the drug target-likeness of a protein

Current drug discovery and development approaches rely extensively on the identification and validation of appropriate targets; for example, those with marketable and robust therapeutics. Wide-ranging efforts have been directed at this problem and various approaches have been developed to identify disease-associated genes as candidates. In this work, we show with statistical significance that successful drug targets, in addition to their linkage to disease, share common characteristics that are disease-independent. For example, marked differences in functional category, tissue specificity, and sequence variability are observed between known targets and average proteins. These results lead to an interesting hypothesis: potentially good drug targets shall have some desired properties, which we refer to as "drug target-likeness" that are beyond their disease-associations. Because of the limited availability of comprehensive protein characteristics data, we tried to learn the drug target-likeness property at the sequence level. Results show that a support vector machine model is able to accurately distinguish targets from nontargets entirely with sequence features. It is our hope that these encouraging results will invite future systematic proteomic scale experiments to gather necessary protein characteristics data for the accurate and predictive definition of "drug target-likeness", providing a new perspective toward understanding and pursuing effective therapeutics.     

Peptide inhibitors of protein kinases-discovery, characterisation and use

Protein kinases are now the second largest group of drug targets, and most protein kinase inhibitors in clinical development are directed towards the ATP-binding site. However, these inhibitors must compete with high intracellular ATP concentrations and they must discriminate between the ATP-binding sites of all protein kinases as well the other proteins that also utilise ATP. It would therefore be beneficial to target sites on protein kinases other than the ATP-binding site. This review describes the discovery, characterisation and use of peptide inhibitors of protein kinases. In many cases, the development of these peptides has resulted from an understanding of the specific protein-binding partners for a particular protein kinase. In addition, novel peptide sequences have been discovered in library screening approaches and have provided new leads in the discovery and/or design of peptide inhibitors of protein kinases. These approaches are therefore providing exciting new opportunities in the development of ATP non-competitive inhibitors of protein kinases.     

Focusing in on structural genomics: the University of Queensland structural biology pipeline

The flood of new genomic sequence information together with technological innovations in protein structure determination have led to worldwide structural genomics (SG) initiatives. The goals of SG initiatives are to accelerate the process of protein structure determination, to fill in protein fold space and to provide information about the function of uncharacterized proteins. In the long-term, these outcomes are likely to impact on medical biotechnology and drug discovery, leading to a better understanding of disease as well as the development of new therapeutics. Here we describe the high throughput pipeline established at the University of Queensland in Australia. In this focused pipeline, the targets for structure determination are proteins that are expressed in mouse macrophage cells and that are inferred to have a role in innate immunity. The aim is to characterize the molecular structure and the biochemical and cellular function of these targets by using a parallel processing pipeline. The pipeline is designed to work with tens to hundreds of target gene products and comprises target selection, cloning, expression, purification, crystallization and structure determination. The structures from this pipeline will provide insights into the function of previously uncharacterized macrophage proteins and could lead to the validation of new drug targets for chronic obstructive pulmonary disease and arthritis.     

药物靶标蛋白在蛋白网络中的分布

药物靶标发现是目前生物学研究领域的热点和难点问题。从已有药物靶标中寻找规律可以为新靶标的发现总结规律,提供依据。随着功能基因组学的发展,这种组学数据的积累为这一问题的研究提供了契机。本文研究了已有靶标在蛋白网络中的分布,并分析了它们的蛋白功能域组成情况。结果显示靶标基因倾向位于网络的核心区域,并且集中在一些特定蛋白家族中。这些规律的总结将对药物研发过程中药物靶点的选择提供一定的帮助。     

Identification of intracellular targets of small molecular weight chemical compounds using affinity chromatography

Efforts to characterize small molecular weight chemical inhibitors of pharmacological interest tend to identify molecules with high efficiency and selectivity, to meet the two criteria required for the clinical development of a drug: efficacy and harmlessness. Drug candidates are expected to inhibit efficiently the target they have been optimized against (for example, a particular type of protein kinase). These hits are also designed to not interfere (or as little as possible) with the activity of other cellular enzymes/proteins to reduce undesired side effects. Here we discuss the use of immobilized drugs as affinity chromatography matrices to purify and identify their bona fide intracellular targets. This method not only allows the systematic investigation of the selectivity of pharmacological compounds but also the anticipation of their putative adverse effects.     

Towards structure-based protein drug design

Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein-protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein-ligand interactions, protein-protein interactions are more complicated and present more challenges for design. Over the last decade, both sampling efficiency and scoring accuracy of protein-protein docking have increased significantly. We have developed several strategies for structure-based protein drug design. A grafting strategy for key interaction residues has been developed and successfully applied in designing erythropoietin receptor-binding proteins. Similarly to small-molecule design, we also tested de novo protein-binder design and a virtual screen of protein binders using protein-protein docking calculations. In comparison with the development of structure-based small-molecule drug design, we believe that structure-based protein drug design has come of age.     

Cupricyclins, novel redox-active metallopeptides based on conotoxins scaffold

Highly stable natural scaffolds which tolerate multiple amino acid substitutions represent the ideal starting point for the application of rational redesign strategies to develop new catalysts of potential biomedical and biotechnological interest. The knottins family of disulphide-constrained peptides display the desired characteristics, being highly stable and characterized by hypervariability of the inter-cysteine loops. The potential of knottins as scaffolds for the design of novel copper-based biocatalysts has been tested by engineering a metal binding site on two different variants of an ω-conotoxin, a neurotoxic peptide belonging to the knottins family. The binding site has been designed by computational modelling and the redesigned peptides have been synthesized and characterized by optical, fluorescence, electron spin resonance and nuclear magnetic resonance spectroscopy. The novel peptides, named Cupricyclin-1 and -2, bind one Cu(2+) ion per molecule with nanomolar affinity. Cupricyclins display redox activity and catalyze the dismutation of superoxide anions with an activity comparable to that of non-peptidic superoxide dismutase mimics. We thus propose knottins as a novel scaffold for the design of catalytically-active mini metalloproteins.     

Aptamers as tools for target validation

Synthetic nucleic acid ligands, called aptamers, bind to protein targets with high specificity and affinity. They are very potent inhibitors of protein function and their application can greatly enhance the process of target validation and drug development. An important benefit of this technology is the recent development of rapidly identifying these sophisticated ligands for almost any target molecule in multi-parallel, automated workstations. The aptamer technology is thus well-suited to addressing the growing demand for high-throughput analysis and functional validation of potential drug targets. Numerous examples have shown the potency of aptamers in inhibiting the function of proteins in cell culture and in vivo models. The technology is complementary to genetic knockout or siRNA approaches as it provides highly valuable information at the proteomic level. In addition, the aptamer technology has recently been extended to developing aptamer drugs and identifying functionally equivalent small molecule leads.     

Network Neighbors of Drug Targets Contribute to Drug Side-Effect Similarity

In pharmacology, it is essential to identify the molecular mechanisms of drug action in order to understand adverse side effects. These adverse side effects have been used to infer whether two drugs share a target protein. However, side-effect similarity of drugs could also be caused by their target proteins being close in a molecular network, which as such could cause similar downstream effects. In this study, we investigated the proportion of side-effect similarities that is due to targets that are close in the network compared to shared drug targets. We found that only a minor fraction of side-effect similarities (5.8 %) are caused by drugs targeting proteins close in the network, compared to side-effect similarities caused by overlapping drug targets (64%). Moreover, these targets that cause similar side effects are more often in a linear part of the network, having two or less interactions, than drug targets in general. Based on the examples, we gained novel insight into the molecular mechanisms of side effects associated with several drug targets. Looking forward, such analyses will be extremely useful in the process of drug development to better understand adverse side effects.     

Protein interaction network analysis—Approach for potential drug target identification in Mycobacterium tuberculosis

In host-parasite diseases like tuberculosis, non-homologous proteins (enzymes) as drug target are first preference. Most potent drug target can be identified among large number of non-homologous protein through protein interaction network analysis. In this study, the entire promising dimension has been explored for identification of potential drug target. A comparative metabolic pathway analysis of the host Homo sapiens and the pathogen M. tuberculosis H37Rv has been performed with three level of analysis. In first level, the unique metabolic pathways of M. tuberculosis have been identified through its comparative study with H. sapiens and identification of non-homologous proteins has been done through BLAST similarity search. In second level, choke-point analysis has been performed with identified non-homologous proteins of metabolic pathways. In third level, two type of analysis have been performed through protein interaction network. First analysis has been done to find out the most potential metabolic functional associations among all identified choke point proteins whereas second analysis has been performed to find out the functional association of high metabolic interacting proteins to pathogenesis causing proteins. Most interactive metabolic proteins which have highest number of functional association with pathogenesis causing proteins have been considered as potential drug target. A list of 18 potential drug targets has been proposed which are various stages of progress at the TBSGC and proposed drug targets are also studied for other pathogenic strains.As a case study, we have built a homology model of identified drug targets histidinol-phosphate aminotransferase (HisC1) using MODELLER software and various information have been generated through molecular dynamics which will be useful in wetlab structure determination. The generated model could be further explored for insilico docking studies with suitable inhibitors.     

Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) – a drug’s ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.     

Exploration of Target Spaces in the Human Genome for Protein and Peptide Drugs

After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However,owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target s...     

Robustness and Evolvability of the Human Signaling Network

Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores.