Protein-protein interaction network-based detection of functionally similar proteins within species

Engineered polymer nanoparticles incorporating l-amino acid groups as affinity reagents for fibrinogen

Synthetic polymer hydrogel nanoparticles (NPs) were developed to function as abiotic affinity reagents for fibrinogen. These NPs were made using both temperature-sensitive N-isopropyl acrylamide (NIPAm) and l-amino acid monomers. Five kinds of l-amino acids were acryloylated to obtain functional monomers: l-phenylalanine (Phe) and l-leucine (Leu) with hydrophobic side chains, l-glutamic acid (Glu) with negative charges, and l-lysine (Lys) and l-arginine (Arg) with positive charges. After incubating the NPs with fibrinogen, γ-globulin, and human serum albumin (HSA) respectively, the NPs that incorporated N-acryloyl-Arg monomers (AArg@NPs) showed the strongest and most specific binding affinity to fibrinogen, when compared with γ-globulin and HSA. Additionally, the fibrinogen-AArg binding model had the best docking scores, and this may be due to the interaction of positively charged AArg@NPs and the negatively charged fibrinogen D domain and the hydrophobic interaction between them. The specific adsorption of AArg@NPs to fibrinogen was also confirmed by the immunoprecipitation assay, as the AArg@NPs selectively trapped the fibrinogen from a human plasma protein mixture. AArg@NPs had a strong selectivity for, and specificity to, fibrinogen and may be developed as a potential human fibrinogen-specific affinity reagent.

Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction

Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.

Enter the Dragon: The Dynamic and Multifunctional Evolution of Anguimorpha Lizard Venoms

While snake venoms have been the subject of intense study, comparatively little work has been done on lizard venoms. In this study, we have examined the structural and functional diversification of anguimorph lizard venoms and associated toxins, and related these results to dentition and predatory ecology. Venom composition was shown to be highly variable across the 20 species of Heloderma, Lanthanotus, and Varanus included in our study. While kallikrein enzymes were ubiquitous, they were also a particularly multifunctional toxin type, with differential activities on enzyme substrates and also ability to degrade alpha or beta chains of fibrinogen that reflects structural variability. Examination of other toxin types also revealed similar variability in their presence and activity levels. The high level of venom chemistry variation in varanid lizards compared to that of helodermatid lizards suggests that venom may be subject to different selection pressures in these two families. These results not only contribute to our understanding of venom evolution but also reveal anguimorph lizard venoms to be rich sources of novel bioactive molecules with potential as drug design and development lead compounds.