SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids.

Tumor-homing peptides (THPs) are small peptides that can recognize and bind cancer cells specifically. To gain a better understanding of THPs' functional mechanisms, the accurate identification and characterization of THPs is required. Although some computational methods for in silico THP identification have been proposed, a major drawback is their lack of model interpretability. In this study, we propose a new, simple and easily interpretable computational approach (called SCMTHP) for identifying and analyzing tumor-homing activities of peptides via the use of a scoring card method (SCM). To improve the predictability and interpretability of our predictor, we generated propensity scores of 20 amino acids as THPs. Finally, informative physicochemical properties were used for providing insights on characteristics giving rise to the bioactivity of THPs via the use of SCMTHP-derived propensity scores. Benchmarking experiments from independent test indicated that SCMTHP could achieve comparable performance to state-of-the-art method with accuracies of 0.827 and 0.798, respectively, when evaluated on two benchmark datasets consisting of Main and Small datasets. Furthermore, SCMTHP was found to outperform several well-known machine learning-based classifiers (e.g., decision tree, k-nearest neighbor, multi-layer perceptron, naive Bayes and partial least squares regression) as indicated by both 10-fold cross-validation and independent tests. Finally, the SCMTHP web server was established and made freely available online. SCMTHP is expected to be a useful tool for rapid and accurate identification of THPs and for providing better understanding on THP biophysical and biochemical properties

Activity, structural features and in silico digestion of antidiabetic peptides

Funding This research was funded by the grant PID2020-114137RB-I00 funded by MCIN/AEI/10.13039/501100011033Food antidiabetic peptides inhibit the enzymes involved in the regulation of the glycemic index (e.g. a-amylase, a-glucosidase and dipeptidyl peptidase-IV (DPP-IV)). This work reviews the antidiabetic peptide sequences reported in the literature, with activity confirmed by using synthetic peptides, and critically discusses their structural features. Moreover, it provides an overview of the potency of in silico analysis tools to predict the in vitro antidiabetic activity of DPP-IV-inhibitory peptides. In addition, the potential degradation of the most active peptides during digestion was evaluated in silico. Therefore, this work advances our understanding on the structure-activity relationship of antidiabetic peptides and provides new insights on their stability during digestion.MCIN/AEI/10.13039/501100011033: PID2020-114137RB-I0

Bioinformatics Tool for Prediction of Protein Solubility

Abychom dosáhli levnější a efektivnější výroby proteinů, musíme být schopni predikovat, zda budou proteiny rozpustné. V této práci se zabýváme vytvořením bioinformatických datových sad na základě databází Target Track a eSol, testováním příznaků používaných v existujících nástrojích zabývajících se rozpustností proteinů a tvorbou nového prediktoru. Přestože se nám nedaří vytvořit efektivní nástroj na predikci rozpustnosti proteinů, zjišťujeme, že ve většině případů staré příznaky na nové datové sadě nekorelují s rozpustností proteinů tak silně, jako tomu je u starších a menších datových sad.To achieve cheaper and more efficient protein production, we must be able to predict protein solubility. In this thesis, we describe creation of bioinformatic data sets based on Target Track and eSol databases, we test the features used in existing protein solubility prediction tools and create a new predictor. Even though we fail to create an effective prediction tool we find out that in most cases the old features tested on the new data do not correlate with protein solubility as strongly as others repot in older and smaller datasets.

Bacterial inclusion bodies are industrially exploitable amyloids

Altres ajuts: CERCA Programme/Generalitat de CatalunyaUnderstanding the structure, functionalities and biology of functional amyloids is an issue of emerging interest. Inclusion bodies, namely protein clusters formed in recombinant bacteria during protein production processes, have emerged as unanticipated, highly tunable models for the scrutiny of the physiology and architecture of functional amyloids. Based on an amyloidal skeleton combined with varying amounts of native or native-like protein forms, bacterial inclusion bodies exhibit an unusual arrangement that confers mechanical stability, biological activity and conditional protein release, being thus exploitable as versatile biomaterials. The applicability of inclusion bodies in biotechnology as enriched sources of protein and reusable catalysts, and in biomedicine as biocompatible topographies, nanopills or mimetics of endocrine secretory granules has been largely validated. Beyond these uses, the dissection of how recombinant bacteria manage the aggregation of functional protein species into structures of highly variable complexity offers insights about unsuspected connections between protein quality (conformational status compatible with functionality) and cell physiology

Bacterial inclusion bodies are industrially exploitable amyloids

Understanding the structure, functionalities and biology of functional amyloids is an issue of emerging interest. Inclusion bodies, namely protein clusters formed in recombinant bacteria during protein production processes, have emerged as unanticipated, highly tunable models for the scrutiny of the physiology and architecture of functional amyloids. Based on an amyloidal skeleton combined with varying amounts of native or native-like protein forms, bacterial inclusion bodies exhibit an unusual arrangement that confers mechanical stability, biological activity and conditional protein release, being thus exploitable as versatile biomaterials. The applicability of inclusion bodies in biotechnology as enriched sources of protein and reusable catalysts, and in biomedicine as biocompatible topographies, nanopills or mimetics of endocrine secretory granules has been largely validated. Beyond these uses, the dissection of how recombinant bacteria manage the aggregation of functional protein species into structures of highly variable complexity offers insights about unsuspected connections between protein quality (conformational status compatible with functionality) and cell physiology.info:eu-repo/semantics/acceptedVersio