Ensembles of Hydrophobicity Scales as Potent Classifiers for Chimeric Virus-Like Particle Solubility – An Amino Acid Sequence-Based Machine Learning Approach

Virus-like particles (VLPs) are protein-based nanoscale structures that show high potential as immunotherapeutics or cargo delivery vehicles. Chimeric VLPs are decorated with foreign peptides resulting in structures that confer immune responses against the displayed epitope. However, insertion of foreign sequences often results in insoluble proteins, calling for methods capable of assessing a VLP candidate’s solubility in silico. The prediction of VLP solubility requires a model that can identify critical hydrophobicity-related parameters, distinguishing between VLP-forming aggregation and aggregation leading to insoluble virus protein clusters. Therefore, we developed and implemented a soft ensemble vote classifier (sEVC) framework based on chimeric hepatitis B core antigen (HBcAg) amino acid sequences and 91 publicly available hydrophobicity scales. Based on each hydrophobicity scale, an individual decision tree was induced as classifier in the sEVC. An embedded feature selection algorithm and stratified sampling proved beneficial for model construction. With a learning experiment, model performance in the space of model training set size and number of included classifiers in the sEVC was explored. Additionally, seven models were created from training data of 24–384 chimeric HBcAg constructs, which were validated by 100-fold Monte Carlo cross-validation. The models predicted external test sets of 184–544 chimeric HBcAg constructs. Best models showed a Matthew’s correlation coefficient of >0.6 on the validation and the external test set. Feature selection was evaluated for classifiers with best and worst performance in the chimeric HBcAg VLP solubility scenario. Analysis of the associated hydrophobicity scales allowed for retrieval of biological information related to the mechanistic backgrounds of VLP solubility, suggesting a special role of arginine for VLP assembly and solubility. In the future, the developed sEVC could further be applied to hydrophobicity-related problems in other domains, such as monoclonal antibodies

Optimization of a Soft Ensemble Vote Classifier for the Prediction of Chimeric Virus-Like Particle Solubility and Other Biophysical Properties

Chimeric virus-like particles (cVLPs) are protein-based nanostructures applied as investigational vaccines against infectious diseases, cancer, and immunological disorders. Low solubility of cVLP vaccine candidates is a challenge that can prevent development of these very substances. Solubility of cVLPs is typically assessed empirically, leading to high time and material requirements. Prediction of cVLP solubility in silico can aid in reducing this effort. Protein aggregation by hydrophobic interaction is an important factor driving protein insolubility. In this article, a recently developed soft ensemble vote classifier (sEVC) for the prediction of cVLP solubility was used based on 91 literature amino acid hydrophobicity scales. Optimization algorithms were developed to boost model performance, and the model was redesigned as a regression tool for ammonium sulfate concentration required for cVLP precipitation. The present dataset consists of 568 cVLPs, created by insertion of 71 different peptide sequences using eight different insertion strategies. Two optimization algorithms were developed that (I) modified the sEVC with regard to systematic misclassification based on the different insertion strategies, and (II) modified the amino acid hydrophobicity scale tables to improve classification. The second algorithm was additionally used to synthesize scales from random vectors. Compared to the unmodified model, Matthew’s Correlation Coefficient (MCC), and accuracy of the test set predictions could be elevated from 0.63 and 0.81 to 0.77 and 0.88, respectively, for the best models. This improved performance compared to literature scales was suggested to be due to a decreased correlation between synthesized scales. In these, tryptophan was identified as the most hydrophobic amino acid, i.e., the amino acid most problematic for cVLP solubility, supported by previous literature findings. As a case study, the sEVC was redesigned as a regression tool and applied to determine ammonium sulfate concentrations for the precipitation of cVLPs. This was evaluated with a small dataset of ten cVLPs resulting in an R$^{2}$ of 0.69. In summary, we propose optimization algorithms that improve sEVC model performance for the prediction of cVLP solubility, allow for the synthesis of amino acid scale tables, and further evaluate the sEVC as regression tool to predict cVLP-precipitating ammonium sulfate concentrations

Enhanced stability of a chimeric hepatitis B core antigen virus-like-particle (HBcAg-VLP) by a C-terminal linker-hexahistidine-peptide

Abstract Background Virus-like-particles (VLPs) are attractive nanoparticulate scaffolds for broad applications in material/biological sciences and medicine. Prior their functionalization, specific adaptations have to be carried out. These adjustments frequently lead to disordered particles, but the particle integrity is an essential factor for the VLP suitability. Therefore, major requirements for particle stabilization exist. The objective of this study was to evaluate novel stabilizing elements for functionalized chimeric hepatitis B virus core antigen virus-like particles (HBcAg-VLP), with beneficial characteristics for vaccine development, imaging or delivery. Results The effects of a carboxy-terminal polyhistidine-peptide and an intradimer disulfide-bridge on the stability of preclinically approved chimeric HBcAg-VLPs were assessed. We purified recombinant chimeric HBcAg-VLPs bearing different modified C-termini and compared their physical and chemical particle stability by quantitative protein-biochemical and biophysical techniques. We observed lower chemical resistance of T = 3- compared to T = 4-VLP (triangulation number) capsids and profound impairment of accessibility of hexahistidine-peptides in assembled VLPs. Histidines attached to the C-terminus were associated with superior mechanical and/or chemical particle stability depending on the number of histidine moieties. A molecular modeling approach based on cryo-electron microscopy and biolayer interferometry revealed the underlying structural mechanism for the strengthening of the integrity of VLPs. Interactions triggering capsid stabilization occur on a highly conserved residue on the basis of HBcAg-monomers as well as on hexahistidine-peptides of adjacent monomers. This new stabilization mechanism appears to mimic an evolutionary conserved stabilization concept for hepadnavirus core proteins. Conclusions These findings establish the genetically simply transferable C-terminal polyhistidine-peptide as a general stabilizing element for chimeric HBcAg-VLPs to increase their suitability

Pathogenesis of POLR1C-dependent type 3 treacher collins syndrome revealed by a zebrafish model

[[abstract]]Treacher Collins Syndrome (TCS) is a rare congenital birth disorder (1 in 50,000 live births) characterized by severe craniofacial defects, including the downward slanting palpebral fissures, hypoplasia of the facial bones, and cleft palate (CP). Over 90% of patients with TCS have a mutation in the TCOF1 gene. However, some patients exhibit mutations in two new causative genes, POLR1C and POLR1D, which encode subunits of RNA polymerases I and III, that affect ribosome biogenesis. In this study, we examine the role of POLR1C in TCS using zebrafish as a model system. Our data confirmed that polr1c is highly expressed in the facial region, and dysfunction of this gene by knockdown or knock-out resulted in mis-expression of neural crest cells during early development that leads to TCS phenotype. Next generation sequencing and bioinformatics analysis of the polr1c mutants further demonstrated the up-regulated p53 pathway and predicted skeletal disorders. Lastly, we partially rescued the TCS facial phenotype in the background of p53 mutants, which supported the hypothesis that POLR1C-dependent type 3 TCS is associated with the p53 pathway