Establishment and Characterization of Amitrole-Induced Mouse Thyroid Adenomatous Nodule-Derived Cell Lines.

Background: Thyroid cancer cell lines have been of great value for the study of thyroid cancer. However, the availability of benign thyroid adenoma cell lines is limited. Methods: Cell lines were established from thyroid adenomatous nodules that developed in mice treated with the goitrogen amitrole. Expression of epithelial, mesenchymal, and thyroid markers of these established cell lines was determined, and the effect of lentivirus-transduced overexpression of NKX2-1, a master regulator of thyroid development, on the thyroid marker expression was examined. Signal transduction and cell proliferation were evaluated after treatment with insulin-like growth factor-I (IGF-I) and the selective IGF-I receptor (IGF-IR) inhibitor NVP-ADW742. Xenograft studies were performed to examine tumorigenicity of the cells in mice. Whole-genome sequencing (WGS) was used to comprehensively determine the genetic mutations in the established two cell lines. Results: Five mouse thyroid adenomatous nodules-derived cell lines named CAT (cells from amitrole-treated thyroids) were established. Among these, two cell lines, CAT458/458s (CAT458s: a subline of CAT458) and CAT459, were found to be positive for epithelial markers and negative for a mesenchymal marker. NKX2-1-positive CAT459 cells showed higher messenger RNA (mRNA) expression of some thyroid differentiation markers than NKX2-1-negative CAT458s cells, and NKX2-1 overexpression increased and/or induced their expression. IGF-I signaling was transduced in thyrotropin receptor (Tshr)-negative CAT458s and 459 cells, and NVP-ADW742 suppressed their proliferation. No tumors developed in mice after subcutaneous injection of CAT458s or 459 cells. The WGS analysis revealed the presence of missense mutations in the tumor suppressor genes such as Polk (encoding DNA polymerase kappa) and Tgfb1 (encoding transforming growth factor beta 1), while no mutations were found in the prominent thyroid cancer-related genes Braf, Trp53 (encoding p53), and Tert (encoding telomerase reverse transcriptase). Conclusions: Two mouse thyroid adenomatous nodule-derived cell lines with different thyroid differentiation marker expression were established. NKX2-1 induced partial differentiation of these cell lines. They lacked tumorigenicity and prominent gene mutations involved in thyroid cancer development, while missense mutations were found in some tumor suppressors as revealed by WGS. The CAT458s and 459 provide a new tool to further clarify the process of thyroid multistep carcinogenesis and differentiation.

Anopheles salivary apyrase regulates blood meal hemostasis and drives malaria parasite transmission.

Mosquito salivary proteins play a crucial role in regulating hemostatic responses at the bite site during blood feeding. In this study, we investigate the function of Anopheles gambiae salivary apyrase (AgApyrase) in Plasmodium transmission. Our results demonstrate that salivary apyrase interacts with and activates tissue plasminogen activator, facilitating the conversion of plasminogen to plasmin, a human protein previously shown to be required for Plasmodium transmission. Microscopy imaging shows that mosquitoes ingest a substantial amount of apyrase during blood feeding which reduces coagulation in the blood meal by enhancing fibrin degradation and inhibiting platelet aggregation. Supplementation of Plasmodium infected blood with apyrase significantly enhanced Plasmodium infection in the mosquito midgut. In contrast, AgApyrase immunization inhibited Plasmodium mosquito infection and sporozoite transmission. This study highlights a pivotal role for mosquito salivary apyrase for regulation of hemostasis in the mosquito blood meal and for Plasmodium transmission to mosquitoes and to the mammal host, underscoring the potential for new strategies to prevent malaria transmission.

TNIK Is a Therapeutic Target in Lung Squamous Cell Carcinoma and Regulates FAK Activation through Merlin.

Lung squamous cell carcinoma (LSCC) is the second most prevalent type of lung cancer. Despite extensive genomic characterization, no targeted therapies are approved for the treatment of LSCC. Distal amplification of the 3q chromosome is the most frequent genomic alteration in LSCC, and there is an urgent need to identify efficacious druggable targets within this amplicon. We identify the protein kinase TNIK as a therapeutic target in LSCC. TNIK is amplified in approximately 50% of LSCC cases. TNIK genetic depletion or pharmacologic inhibition reduces the growth of LSCC cells in vitro and in vivo. In addition, TNIK inhibition showed antitumor activity and increased apoptosis in established LSCC patient-derived xenografts. Mechanistically, we identified the tumor suppressor Merlin/NF2 as a novel TNIK substrate and showed that TNIK and Merlin are required for the activation of focal adhesion kinase. In conclusion, our data identify targeting TNIK as a potential therapeutic strategy in LSCC. SIGNIFICANCE: Targeted therapies have not yet been approved for the treatment of LSCC, due to lack of identification of actionable cancer drivers. We define TNIK catalytic activity as essential for maintaining LSCC viability and validate the antitumor efficacy of TNIK inhibition in preclinical models of LSCC.This article is highlighted in the In This Issue feature, p. 1307.

Analysis of SARS-CoV-2 ORF3a structure reveals chloride binding sites.

SARS-CoV-2 ORF3a is believed to form ion channels, which may be involved in the modulation of virus release, and has been implicated in various cellular processes like the up-regulation of fibrinogen expression in lung epithelial cells, downregulation of type 1 interferon receptor, caspase-dependent apoptosis, and increasing IFNAR1 ubiquitination. ORF3a assemblies as homotetramers, which are stabilized by residue C133. A recent cryoEM structure of a homodimeric complex of ORF3a has been released. A lower-resolution cryoEM map of the tetramer suggests two dimers form it, arranged side by side. The dimer's cryoEM structure revealed that each protomer contains three transmembrane helices arranged in a clockwise configuration forming a six helices transmembrane domain. This domain's potential permeation pathway has six constrictions narrowing to about 1 Å in radius, suggesting the structure solved is in a closed or inactivated state. At the cytosol end, the permeation pathway encounters a large and polar cavity formed by multiple beta strands from both protomers, which opens to the cytosolic milieu. We modeled the tetramer following the arrangement suggested by the low-resolution tetramer cryoEM map. Molecular dynamics simulations of the tetramer embedded in a membrane and solvated with 0.5 M of KCl were performed. Our simulations show the cytosolic cavity is quickly populated by both K+ and Cl-, yet with different dynamics. K+ ions moved relatively free inside the cavity without forming proper coordination sites. In contrast, Cl- ions enter the cavity, and three of them can become stably coordinated near the intracellular entrance of the potential permeation pathway by an inter-subunit network of positively charged amino acids. Consequently, the central cavity's electrostatic potential changed from being entirely positive at the beginning of the simulation to more electronegative at the end.

Electrostatically Driven Guanidinium Interaction Domains that Control Hydrogel-Mediated Protein Delivery In Vivo.

Protein biologics are an important class of drugs, but the necessity for frequent parenteral administration is a major limitation. Drug-delivery materials offer a potential solution, but protein-material adsorption can cause denaturation, which reduces their effectiveness. Here, we describe a new protein delivery platform that limits direct contact between globular protein domains and material matrix, yet from a single subcutaneous administration can be tuned for long-term drug release. The strategy utilizes complementary electrostatic interactions made between a suite of designed interaction domains (IDs), installed onto the terminus of a protein of interest, and a negatively charged self-assembled fibrillar hydrogel. These intermolecular interactions can be easily modulated by choice of ID to control material interaction and desorption energies, which allows regulation of protein release kinetics to fit desired release profiles. Molecular dynamics studies provided a molecular-level understanding of the mechanisms that govern release and identified optimal binding zones on the gel fibrils that facilitate strong ID-material interactions, which are crucial for sustained release of protein. This delivery platform can be easily loaded with cargo, is shear-thin syringe implantable, provides improved protein stability, is capable of a diverse range of in vitro release rates, and most importantly, can accomplish long-term control over in vivo protein delivery.

The upcoming subatomic resolution revolution.

Subatomic resolution macromolecular crystallography has been revealing the most fascinating details of macromolecular structures for many years. This most extreme form of macromolecular crystallography is going through rapid changes. A new generation of superbrilliant X-ray sources and detectors is facilitating the rapid acquisition of high-quality datasets. Equally important, a new breed of methods and highly integrated advanced computational tools for structure refinement and analysis is poised to change the way we use subatomic resolution data and reposition high-resolution macromolecular crystallography in medicinal chemistry studies. Subatomic resolution macromolecular crystallography may soon be a routine source of detailed molecular information besides precise geometries, including binding energies and other chemical descriptors, opening new possibilities of application.

A novel pathway of LPS uptake through syndecan-1 leading to pyroptotic cell death.

Intracellular lipopolysaccharide (LPS) triggers the non-canonical inflammasome pathway, resulting in pyroptosis of innate immune cells. In addition to its well-known proinflammatory role, LPS can directly cause regression of some tumors, although the underlying mechanism has remained unknown. Here we show that secretoglobin(SCGB)3A2, a small protein predominantly secreted in airways, chaperones LPS to the cytosol through the cell surface receptor syndecan-1; this leads to pyroptotic cell death driven by caspase-11. SCGB3A2 and LPS co-treatment significantly induced pyroptosis of macrophage RAW264.7 cells and decreased cancer cell proliferation in vitro, while SCGB3A2 treatment resulted in reduced progression of xenograft tumors in mice. These data suggest a conserved function for SCGB3A2 in the innate immune system and cancer cells. These findings demonstrate a critical role for SCGB3A2 as an LPS delivery vehicle; they reveal one mechanism whereby LPS enters innate immune cells leading to pyroptosis, and they clarify the direct effect of LPS on cancer cells.

Conformational energy range of ligands in protein crystal structures: The difficult quest for accurate understanding.

In this review, we address a fundamental question: What is the range of conformational energies seen in ligands in protein-ligand crystal structures? This value is important biophysically, for better understanding the protein-ligand binding process; and practically, for providing a parameter to be used in many computational drug design methods such as docking and pharmacophore searches. We synthesize a selection of previously reported conflicting results from computational studies of this issue and conclude that high ligand conformational energies really are present in some crystal structures. The main source of disagreement between different analyses appears to be due to divergent treatments of electrostatics and solvation. At the same time, however, for many ligands, a high conformational energy is in error, due to either crystal structure inaccuracies or incorrect determination of the reference state. Aside from simple chemistry mistakes, we argue that crystal structure error may mainly be because of the heuristic weighting of ligand stereochemical restraints relative to the fit of the structure to the electron density. This problem cannot be fixed with improvements to electron density fitting or with simple ligand geometry checks, though better metrics are needed for evaluating ligand and binding site chemistry in addition to geometry during structure refinement. The ultimate solution for accurately determining ligand conformational energies lies in ultrahigh-resolution crystal structures that can be refined without restraints.

Inhibition of phosphoinositol 3 kinase contributes to nanoparticle-mediated exaggeration of endotoxin-induced leukocyte procoagulant activity.

AIM: Disseminated intravascular coagulation is an increasing concern for certain types of engineered nanomaterials. Recent studies have shed some light on the nanoparticle physicochemical properties contributing to this toxicity; however, the mechanisms are poorly understood. Leukocyte procoagulant activity (PCA) is a key factor contributing to the initiation of this toxicity. We have previously reported on the exaggeration of endotoxin-induced PCA by cationic dendrimers. Herein, we report an effort to discern the mechanism. MATERIALS & METHODS: Poly(amidoamine) dendrimers with various sizes and surface functionalities were studied in vitro by the recalcification test, flow cytometry and other relevant assays. RESULTS & CONCLUSION: Cationic dendrimers exaggerated endotoxin-induced PCA, but their anionic or neutral counterparts did not; the cationic charge prompts this phenomenon, but different cationic surface chemistries do not influence it. Cationic dendrimers and endotoxin differentially affect the PCA complex. The inhibition of phosphoinositol 3 kinase by dendrimers contributes to the exaggeration of the endotoxin-induced PCA.

Nanoinformatics workshop report: Current resources, community needs, and the proposal of a collaborative framework for data sharing and information integration.

The quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. Data will not be translated to knowledge. At worst, erroneous conclusions will be drawn and future research may be misdirected. Nanoinformatics can be a powerful approach to enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. In 2012, the nanoinformatics community believed it was important to critically evaluate and refine currently available nanoinformatics approaches in order to best inform the science and support the future of predictive nanotechnology. The Greener Nano 2012: Nanoinformatics Tools and Resources Workshop brought together informatics groups with materials scientists active in nanoscience research to evaluate and reflect on the tools and resources that have recently emerged in support of predictive nanotechnology. The workshop goals were to establish a better understanding of current nanoinformatics approaches and to clearly define immediate and projected informatics infrastructure needs of the nanotechnology community. The theme of nanotechnology environmental health and safety (nanoEHS) was used to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. The benefit here is that the same properties that impact the performance of products could also be the properties that inform EHS. From a decision management standpoint, the dual use of such data should be considered a priority. Key outcomes include a proposed collaborative framework for data collection, data sharing and information integration.

Nanoinformatics: a new area of research in nanomedicine.

Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and -omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings.

Study of interaction energies between the PAMAM dendrimer and nonsteroidal anti-inflammatory drug using a distributed computational strategy and experimental analysis by ESI-MS/MS.

The structure of a dendrimer exhibits a large number of internal and superficial cavities, which can be exploited, to capture and deliver small organic molecules, enabling their use in drug delivery. Structure-based modeling and quantum mechanical studies can be used to accurately understand the interactions between functionalized dendrimers and molecules of pharmaceutical and industrial interest. In this study, we implemented a Metropolis Monte Carlo algorithm to calculate the interaction energy of dendrimer-drug complexes, which can be used for in silico prediction of dendrimer-drug affinity. Initially, a large-scale sampling of different dendrimer-drug conformations was generated using Euler angles. Then, each conformation was distributed on different nodes of a GRID computational system, where its interaction energy was calculated by semiempirical quantum mechanical methods. These energy calculations were performed for four different nonsteroidal anti-inflammatory drugs, each showing different affinities for the PAMAM-G4 dendrimer. The affinities were also characterized experimentally by using Cooks' kinetic method to calculate PAMAM-drug dissociation constants. The quantitative structure-activity relationship between the interaction energies and dissociation constants showed statistical correlations with r(2) > 0.9.

PDB ligand conformational energies calculated quantum-mechanically.

We present here a greatly updated version of an earlier study on the conformational energies of protein-ligand complexes in the Protein Data Bank (PDB) [Nicklaus et al. Bioorg. Med. Chem. 1995, 3, 411-428], with the goal of improving on all possible aspects such as number and selection of ligand instances, energy calculations performed, and additional analyses conducted. Starting from about 357,000 ligand instances deposited in the 2008 version of the Ligand Expo database of the experimental 3D coordinates of all small-molecule instances in the PDB, we created a "high-quality" subset of ligand instances by various filtering steps including application of crystallographic quality criteria and structural unambiguousness. Submission of 640 Gaussian 03 jobs yielded a set of about 415 successfully concluded runs. We used a stepwise optimization of internal degrees of freedom at the DFT level of theory with the B3LYP/6-31G(d) basis set and a single-point energy calculation at B3LYP/6-311++G(3df,2p) after each round of (partial) optimization to separate energy changes due to bond length stretches vs bond angle changes vs torsion changes. Even for the most "conservative" choice of all the possible conformational energies-the energy difference between the conformation in which all internal degrees of freedom except torsions have been optimized and the fully optimized conformer-significant energy values were found. The range of 0 to ~25 kcal/mol was populated quite evenly and independently of the crystallographic resolution. A smaller number of "outliers" of yet higher energies were seen only at resolutions above 1.3 Å. The energies showed some correlation with molecular size and flexibility but not with crystallographic quality metrics such as the Cruickshank diffraction-component precision index (DPI) and R(free)-R, or with the ligand instance-specific metrics such as occupancy-weighted B-factor (OWAB), real-space R factor (RSR), and real-space correlation coefficient (RSCC). We repeated these calculations with the solvent model IEFPCM, which yielded energy differences that were generally somewhat lower than the corresponding vacuum results but did not produce a qualitatively different picture. Torsional sampling around the crystal conformation at the molecular mechanics level using the MMFF94s force field typically led to an increase in energy.

Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology.

After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.

Supramolecular complexes of quantum dots and a polyamidoamine (PAMAM)-folate derivative for molecular imaging of cancer cells.

Polyamidoamine (PAMAM) dendrimers and water-soluble 3-mercaptopropionic acid (MPA)-capped CdSe quantum dots (QDs) were combined to produce a new gel containing supramolecular complexes of QDs/PAMAM dendrimers. The formation of the QDs/PAMAM supramolecular complexes was confirmed by high resolution electron microscopy and Fourier transform infrared (FTIR) analyses. Molecular dynamics simulations corroborated the structure of the new QDs/PAMAM-based supramolecular compound. Finally, on the basis of the prominent fluorescent properties of the supramolecular complexes, PAMAM dendrimer was functionalized with folic acid to produce a new QDs/PAMAM-folate derivative that showed an efficient and selective performance as a marker for gastric cancer cells.

On the role of the SP1 domain in HIV-1 particle assembly: a molecular switch?

Expression of a retroviral protein, Gag, in mammalian cells is sufficient for assembly of immature virus-like particles (VLPs). VLP assembly is mediated largely by interactions between the capsid (CA) domains of Gag molecules but is facilitated by binding of the nucleocapsid (NC) domain to nucleic acid. We have investigated the role of SP1, a spacer between CA and NC in HIV-1 Gag, in VLP assembly. Mutational analysis showed that even subtle changes in the first 4 residues of SP1 destroy the ability of Gag to assemble correctly, frequently leading to formation of tubes or other misassembled structures rather than proper VLPs. We also studied the conformation of the CA-SP1 junction region in solution, using both molecular dynamics simulations and circular dichroism. Consonant with nuclear magnetic resonance (NMR) studies from other laboratories, we found that SP1 is nearly unstructured in aqueous solution but undergoes a concerted change to an α-helical conformation when the polarity of the environment is reduced by addition of dimethyl sulfoxide (DMSO), trifluoroethanol, or ethanol. Remarkably, such a coil-to-helix transition is also recapitulated in an aqueous medium at high peptide concentrations. The exquisite sensitivity of SP1 to mutational changes and its ability to undergo a concentration-dependent structural transition raise the possibility that SP1 could act as a molecular switch to prime HIV-1 Gag for VLP assembly. We suggest that changes in the local environment of SP1 when Gag oligomerizes on nucleic acid might trigger this switch.

Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology

After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.

Metal ions-stimulated iron oxidation in hydroxylases facilitates stabilization of HIF-1 alpha protein.

The exposure of cells to several metal ions stabilizes HIF-1 alpha protein. However, the molecular mechanisms are not completely understood. They may involve inhibition of hydroxylation by either substitution of iron by metal ions or by iron oxidation in the hydroxylases. Here we provide evidence supporting the latter mechanism. We show that HIF-1 alpha stabilization in human lung epithelial cells occurred following exposure to various metal and metalloid ions, including those that cannot substitute for iron in the hydroxylases. In each case addition of the reducing agent ascorbic acid (AA)* abolished HIF-1 alpha protein stabilization. To better understand the role of iron oxidation in hydroxylase inhibition and to define the role of AA in the enzyme recovery we applied molecular modeling techniques. Our results indicate that the energy required for iron substitution by Ni(II) in the enzyme is high and unlikely to be achieved in a biological system. Additionally, computer modeling allowed us to identify a tridentate coordination of AA with the enzyme-bound iron, which explains the specific demand for AA as the iron reductant. Thus, the stabilization of HIF-1 alpha by numerous metal ions that cannot substitute for iron in the enzyme, the alleviation of this effect by AA, and our computer modeling data support the hypothesis of iron oxidation in the hydroxylases following exposure to metal ions.

In-silico nanobio-design. A new frontier in computational biology.

Nanobiology is a fast-emerging discipline that brings the tools of nanotechnology to the biological sciences. The introduction of new techniques may accelerate the development of highly specific biomedical treatments, increase their efficiency, and minimize their side effects. Introducing foreign bodies into the complex machinery of the human body is, however, a great and humbling challenge, as past experience has shown. In order for nanobiology to reach its full potential, we must devise a means to alter the properties of nanoparticles, as expressed in the human body, in a predictable manner. Computer-aided methods are the natural option to speed up the development of these technologies. Yet, the procedures for annotation and simulation of nanoparticle properties must be developed and their limitations understood before computational methods can be fully exploited. In this review we will compare the state of development of nanoscale simulations in the biological sciences to that of the computer-aided drug design efforts in the past, tracing a historical parallel between both disciplines. From this comparison, lessons can be learned and bottlenecks identified, helping to speed up the development of computer-aided nanobiodevice design tools.

Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools.

A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.