Protein and Peptide Letters - Volume 26, Issue 8, 2019

Amyloids are highly ordered beta sheet rich stable protein aggregates, which have been found to play a significant role in the onset of several degenerative diseases such as Alzheimer’s disease, Huntington’s disease, Parkinson’s disease, Type II diabetes mellitus and so on. Aggregation of proteins leading to amyloid fibril formation via intermediate(s), is thought to be a nucleated condensation polymerization process associated with many pathological conditions. There has been extensive research to identify inhibitors of these disease oriented aggregation processes. In recent times, quantum dots, with their unique physico-chemical properties have grabbed the attention of scientific community due to its applications in medical sciences. Quantum dots are nano-particles usually made of semiconductor materials which emit fluorescence upon radiation. The wavelength of fluorescence emission varies with changes in size of quantum dots. Several studies have reported significant inhibitory effects of these quantum dots towards amyloidogenesis, thereby presenting themselves as promising candidates against amyloidosis. Further, studies have also revealed amyloid detection capacity of quantum dots with sensitivity and specificity better than conventional probes. In the current review, we will discuss the various effects of quantum dots on protein aggregation pathways, their mechanism of actions and their potentials as effective therapeutics against amyloidosis.

Antimicrobial Peptides (AMPs) are short amphipathic biological molecules generally with less than 100 amino acids. AMPs not only present high bioactivities against bacteria, fungi or protists-induced infections, but also play important roles in anticancer activity, immune response and inflammation regulation. AMPs are classified as ribosomally synthesized, non-ribosomally synthesized and post-translationally modified, non-ribosomally synthesized ones and several synthetic or semisynthetic peptides according to their synthesis with or without the involvement of ribosomes. The molecular characterization and bioactivity action mechanisms are summarized for several ribosomally synthesized AMPs and main non-ribosomally synthesized members (cyclopeptides, lipopeptides, glycopeptides, lipoglycopeptides). We also analyze challenges and new strategies to overcome drug resistance and application limitations for AMP discovery. In conclusion, the growing novel small molecular AMPs have huge therapeutic potentials of antibacterial, antiviral, anticancer and immunoregulatory bioactivities through new techniquesdriven drug discovery strategy including bioinformatics prediction, de novo rational design and biosynthesis.

The most recent decade was described by a developing awareness about the seriousness of dementia in the field of age-related people. Among the dementias, Alzheimer's assumes a plentiful role as a result of its amazingly high rate and casualty. A few pharmacological procedures have been attempted yet at the same time now, Alzheimer continues being an untreatable malady. The collection of Aβ in the brain is an early poisonous occasion in the pathogenesis of Alzheimer's disease, which is the most widely recognized type of dementia correlated with plaques and tangles within the brain. However, the mechanism of the intraneuronal direction of BACE1 is poorly understood. AD is caused by mutations in one of the genes that encoding APP, presenilins 1 and 2. Most of the mutations in these genes increase Aβ42 production. Numerous receptors are associated with initiating Aβ transport and clearance. Among them, RAGE is an influx transport receptor that binds soluble Aβ and mediates pathophysiological cellular responses. RAGE additionally intervenes the vehicle of plasma Aβ over the blood-brain barrier. LRP-1 functions as a clearance receptor for Aβ at the blood-brain barrier. The regulation of beta-secretase movement is being explored as a potential restorative focus for treating AD.

Post-translational modifications often regulate protein functioning. Covalent attachment of long chain fatty acids to cysteine residues via a thioester linkage (known as protein palmitoylation or S-acylation) affects protein trafficking, protein-protein and protein-membrane interactions. This post-translational modification is coupled to membrane fusion or virus assembly and may affect viral replication in vitro and thus also virus pathogenesis in vivo. In this review we outline modern methods to study S-acylation of viral proteins and to characterize palmitoylproteomes of virus infected cells. The palmitoylation site predictor CSS-palm is critically tested against the Class I enveloped virus proteins. We further focus on identifying the S-acylation sites directly within acyl-peptides and the specific fatty acid (e.g, palmitate, stearate) bound to them using MALDI-TOF MS-based approaches. The fatty acid heterogeneity/ selectivity issue attracts now more attention since the recently published 3D-structures of two DHHC-acyl-transferases gave a hint how this might be achieved.

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

Background: Human proteome contains a plethora of short linear peptide motifs that is crucial for signaling and other cellular processes. These motifs are difficult to identify due to lack of systematic approach for their detection. Objectives: Here we demonstrate the use of peptide phage display in combination with high throughput next generation sequencing to identify enriched peptide sequences through biopanning process against polo box domain (PBD) of mitotic polo like kinase 1 (Plk1). Methods: Purified recombinant Plk1 and two unrelated controls namely B-lymphocyte antigen (CD20) and fluorescent protein (mCherry) were subjected to peptide phage display analysis. Bacterially-propagated phage DNA was amplified by PCR using triplet bar coded primers to tag the pool from each amplicon. Results: Proteomic peptide phage display along with next generation sequencing and Bioinformatics analysis demonstrated several known and putative novel interactions which were potentially related to Plk1-PBD. With our strategy, we were able to identify and characterize several Plk1-PBD binding peptides, as well as define more precisely, consensus sequences. Conclusion: We believe that this information could provide valuable tools for exploring novel interaction involved in Plk1 signaling as well as to choose peptides for Plk1 specific drug development.