scholarly journals Peptide–Protein Interactions: From Drug Design to Supramolecular Biomaterials

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1219
Author(s):  
Andrea Caporale ◽  
Simone Adorinni ◽  
Doriano Lamba ◽  
Michele Saviano
Keyword(s):  
Secondary Structure ◽  
Protein Interactions ◽  
Self Assembly ◽  
Weak Interactions ◽  
New Drugs ◽  
Rational Approach ◽  
Biological Processes ◽  
Covalent Interaction ◽  
Self Recognition ◽  
Α Helix

The self-recognition and self-assembly of biomolecules are spontaneous processes that occur in Nature and allow the formation of ordered structures, at the nanoscale or even at the macroscale, under thermodynamic and kinetic equilibrium as a consequence of specific and local interactions. In particular, peptides and peptidomimetics play an elected role, as they may allow a rational approach to elucidate biological mechanisms to develop new drugs, biomaterials, catalysts, or semiconductors. The forces that rule self-recognition and self-assembly processes are weak interactions, such as hydrogen bonding, electrostatic attractions, and van der Waals forces, and they underlie the formation of the secondary structure (e.g., α-helix, β-sheet, polyproline II helix), which plays a key role in all biological processes. Here, we present recent and significant examples whereby design was successfully applied to attain the desired structural motifs toward function. These studies are important to understand the main interactions ruling the biological processes and the onset of many pathologies. The types of secondary structure adopted by peptides during self-assembly have a fundamental importance not only on the type of nano- or macro-structure formed but also on the properties of biomaterials, such as the types of interaction, encapsulation, non-covalent interaction, or covalent interaction, which are ultimately useful for applications in drug delivery.

Effect of Temperature and pH on the Secondary Structure and Denaturation Process of Jumbo Squid Hepatopancreas Cathepsin D.

2019 ◽  
Vol 26 (7) ◽  
pp. 532-541 ◽  
Author(s):  
Cadena-Cadena Francisco ◽  
Cárdenas-López José Luis ◽  
Ezquerra-Brauer Josafat Marina ◽  
Cinco-Moroyoqui Francisco Javier ◽  
López-Zavala Alonso Alexis ◽  
...  
Keyword(s):  
Circular Dichroism ◽  
Secondary Structure ◽  
Cathepsin D ◽  
Thermal Denaturation ◽  
Protein Denaturation ◽  
Marine Organisms ◽  
Effect Of Temperature ◽  
Jumbo Squid ◽  
Α Helix ◽  
Circular Dichroïsm

Background: Cathepsin D is a lysosomal enzyme that is found in all organisms acting in protein turnover, in humans it is present in some types of carcinomas, and it has a high activity in Parkinson's disease and a low activity in Alzheimer disease. In marine organisms, most of the research has been limited to corroborate the presence of this enzyme. It is known that cathepsin D of some marine organisms has a low thermostability and that it has the ability to have activity at very acidic pH. Cathepsin D of the Jumbo squid (Dosidicus gigas) hepatopancreas was purified and partially characterized. The secondary structure of these enzymes is highly conserved so the role of temperature and pH in the secondary structure and in protein denaturation is of great importance in the study of enzymes. The secondary structure of cathepsin D from jumbo squid hepatopancreas was determined by means of circular dichroism spectroscopy. Objective: In this article, our purpose was to determine the secondary structure of the enzyme and how it is affected by subjecting it to different temperature and pH conditions. Methods: Circular dichroism technique was used to measure the modifications of the secondary structure of cathepsin D when subjected to different treatments. The methodology consisted in dissecting the hepatopancreas of squid and freeze drying it. Then a crude extract was prepared by mixing 1: 1 hepatopancreas with assay buffer, the purification was in two steps; the first step consisted of using an ultrafiltration membrane with a molecular cut of 50 kDa, and the second step, a pepstatin agarose resin was used to purification the enzyme. Once the enzyme was purified, the purity was corroborated with SDS PAGE electrophoresis, isoelectric point and zymogram. Circular dichroism is carried out by placing the sample with a concentration of 0.125 mg / mL in a 3 mL quartz cell. The results were obtained in mdeg (millidegrees) and transformed to mean ellipticity per residue, using 111 g/mol molecular weight/residue as average. Secondary-structure estimation from the far-UV CD spectra was calculated using K2D Dichroweb software. Results: It was found that α helix decreases at temperatures above 50 °C and above pH 4. Heating the enzyme above 70°C maintains a low percentage of α helix and increases β sheet. Far-UV CD measurements of cathepsin D showed irreversible thermal denaturation. The process was strongly dependent on the heating rate, accompanied by a process of oligomerization of the protein that appears when the sample is heated, and maintained a certain time at this temperature. An amount typically between 3 and 4% α helix of their secondary structure remains unchanged. It is consistent with an unfolding process kinetically controlled due to the presence of an irreversible reaction. The secondary structure depends on pH, and a pH above 4 causes α helix structures to be modified. Conclusion: In conclusion, cathepsin D from jumbo squid hepatopancreas showed retaining up to 4% α helix at 80°C. The thermal denaturation of cathepsin D at pH 3.5 is under kinetic control and follows an irreversible model.

An Integrated Prediction Method for Identifying Protein-Protein Interactions

2020 ◽  
Vol 17 (4) ◽  
pp. 271-286
Author(s):  
Chang Xu ◽  
Limin Jiang ◽  
Zehua Zhang ◽  
Xuyao Yu ◽  
Renhai Chen ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Feature Vector ◽  
Prediction Method ◽  
Feature Representation ◽  
Protein Interaction Networks ◽  
Learning Approach ◽  
Biological Processes ◽  
Integrated Learning ◽  
Protein Protein Interactions ◽  
Training Process

Background: Protein-Protein Interactions (PPIs) play a key role in various biological processes. Many methods have been developed to predict protein-protein interactions and protein interaction networks. However, many existing applications are limited, because of relying on a large number of homology proteins and interaction marks. Methods: In this paper, we propose a novel integrated learning approach (RF-Ada-DF) with the sequence-based feature representation, for identifying protein-protein interactions. Our method firstly constructs a sequence-based feature vector to represent each pair of proteins, viaMultivariate Mutual Information (MMI) and Normalized Moreau-Broto Autocorrelation (NMBAC). Then, we feed the 638- dimentional features into an integrated learning model for judging interaction pairs and non-interaction pairs. Furthermore, this integrated model embeds Random Forest in AdaBoost framework and turns weak classifiers into a single strong classifier. Meanwhile, we also employ double fault detection in order to suppress over-adaptation during the training process. Results: To evaluate the performance of our method, we conduct several comprehensive tests for PPIs prediction. On the H. pyloridataset, our method achieves 88.16% accuracy and 87.68% sensitivity, the accuracy of our method is increased by 0.57%. On the S. cerevisiaedataset, our method achieves 95.77% accuracy and 93.36% sensitivity, the accuracy of our method is increased by 0.76%. On the Humandataset, our method achieves 98.16% accuracy and 96.80% sensitivity, the accuracy of our method is increased by 0.6%. Experiments show that our method achieves better results than other outstanding methods for sequence-based PPIs prediction. The datasets and codes are available at https://github.com/guofei-tju/RF-Ada-DF.git.

A Comparative Study of 1D Descriptors Supported CoMFA and CoMSIA QSAR Models to Gain Novel Insights into 1,2,4-Triazoles Acting As Antitubercular Agents

2020 ◽  
Vol 16 ◽  
Author(s):  
Rajdeep Ray ◽  
Gautham Shenoy ◽  
N V Ganesh Kumar Tummalapalli
Keyword(s):  
External Validation ◽  
Antitubercular Activity ◽  
New Drugs ◽  
Rational Approach ◽  
Antitubercular Drugs ◽  
Comfa Model ◽  
Qsar Models ◽  
Structural Insights ◽  
The Way

: Tuberculosis is one of the leading cause for deaths due to infectious disease worldwide. There is an urgent need for developing new drugs due to the rising incidents of drug resistance. Triazoles have previously been reported to show antitubercular activity. Various computational tools pave the way for a rational approach in understanding the structural importance of these compounds in inhibiting Mycobacterium tuberculosis growth. The aim of this study is to develop and compare two different QSAR models based on a set of previously reported molecules and use the best one for gaining structural insights in to the Triazole molecules. In the current study, two separate models were generated with CoMFA and CoMSIA descriptors respectively based on a dataset of triazole molecules showing antitubercular activity. Several one dimensional (1D) descriptors were added to each of the models and the validation results and the contour data generated from them were compared. The best model was studied to give a detailed understanding of the triazole molecules and their role in the antitubercular activity.The r2, q2, predicted r2 and SEP (Standard error of prediction) for the CoMFA model were 0.866, 0.573, 0.119 and 0.736 respectively and for the CoMSIA model the r2, q2, predicted r2 and SEP were calculated to be 0.998, 0.634, 0.013 and 0.869 respectively. Although both the QSAR models produced acceptable internal and external validation scores but the CoMSIA results were significantly better. The CoMSIA contours also provided a better match than CoMFA with most of the features of the active compound 30b. Hence, the CoMSIA model was chosen and its contours were explored for gaining structural insights on the triazole molecules. The CoMSIA contours helped us to understand the role of several atoms and groups of the triazole molecules in their biological activity. The possibilities for substitution in the triazole compounds that would enhance the activity were also analysed. Thus, this study paves the way for designing new antitubercular drugs in future.

scholarly journals Peptide-based inhibitors of protein–protein interactions: biophysical, structural and cellular consequences of introducing a constraint

2021 ◽  
Author(s):  
Hongshuang Wang ◽  
Robert S. Dawber ◽  
Peiyu Zhang ◽  
Martin Walko ◽  
Andrew J. Wilson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Α Helix ◽  
Cellular Behaviour

This review summarizes the influence of inserting constraints on biophysical, conformational, structural and cellular behaviour for peptides targeting α-helix mediated protein–protein interactions.

scholarly journals Structural relation matching: an algorithm to identify structural patterns into RNAs and their interactions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Michela Quadrini
Keyword(s):  
Hydrogen Bonding ◽  
Secondary Structure ◽  
Nucleotide Sequence ◽  
Thermus Thermophilus ◽  
Three Dimensional ◽  
Secondary Structures ◽  
Structural Effect ◽  
Biological Processes ◽  
Structural Pattern ◽  
Rna Molecules

Abstract RNA molecules play crucial roles in various biological processes. Their three-dimensional configurations determine the functions and, in turn, influences the interaction with other molecules. RNAs and their interaction structures, the so-called RNA–RNA interactions, can be abstracted in terms of secondary structures, i.e., a list of the nucleotide bases paired by hydrogen bonding within its nucleotide sequence. Each secondary structure, in turn, can be abstracted into cores and shadows. Both are determined by collapsing nucleotides and arcs properly. We formalize all of these abstractions as arc diagrams, whose arcs determine loops. A secondary structure, represented by an arc diagram, is pseudoknot-free if its arc diagram does not present any crossing among arcs otherwise, it is said pseudoknotted. In this study, we face the problem of identifying a given structural pattern into secondary structures or the associated cores or shadow of both RNAs and RNA–RNA interactions, characterized by arbitrary pseudoknots. These abstractions are mapped into a matrix, whose elements represent the relations among loops. Therefore, we face the problem of taking advantage of matrices and submatrices. The algorithms, implemented in Python, work in polynomial time. We test our approach on a set of 16S ribosomal RNAs with inhibitors of Thermus thermophilus, and we quantify the structural effect of the inhibitors.

Anion-Directed Self-Assembly of Coordination Polymer into Tunable Secondary Structure

2004 ◽  
Vol 126 (22) ◽  
pp. 7009-7014 ◽  
Author(s):  
Ho-Joong Kim ◽  
Wang-Cheol Zin ◽  
Myongsoo Lee
Keyword(s):  
Secondary Structure ◽  
Coordination Polymer ◽  
Self Assembly

scholarly journals NMR Experiments Shed New Light on Glycan Recognition by Human and Murine Norovirus Capsid Proteins

Viruses ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 416
Author(s):  
Robert Creutznacher ◽  
Thorben Maass ◽  
Patrick Ogrissek ◽  
Georg Wallmann ◽  
Clara Feldmann ◽  
...  
Keyword(s):  
Blood Group ◽  
Protein Interactions ◽  
Capsid Proteins ◽  
Blood Group Antigens ◽  
Biological Processes ◽  
Murine Norovirus ◽  
Human Norovirus ◽  
Head Groups ◽  
Significant Difference

Glycan–protein interactions are highly specific yet transient, rendering glycans ideal recognition signals in a variety of biological processes. In human norovirus (HuNoV) infection, histo-blood group antigens (HBGAs) play an essential but poorly understood role. For murine norovirus infection (MNV), sialylated glycolipids or glycoproteins appear to be important. It has also been suggested that HuNoV capsid proteins bind to sialylated ganglioside head groups. Here, we study the binding of HBGAs and sialoglycans to HuNoV and MNV capsid proteins using NMR experiments. Surprisingly, the experiments show that none of the norovirus P-domains bind to sialoglycans. Notably, MNV P-domains do not bind to any of the glycans studied, and MNV-1 infection of cells deficient in surface sialoglycans shows no significant difference compared to cells expressing respective glycans. These findings redefine glycan recognition by noroviruses, challenging present models of infection.

scholarly journals Fluorescent Parkin Cell-Based Assay Development for the Screening of Drugs against Parkinson Disease

2016 ◽  
Vol 22 (1) ◽  
pp. 67-76 ◽  
Author(s):  
Patricia Villacé ◽  
Rosa M. Mella ◽  
Meritxell Roura-Ferrer ◽  
María Valcárcel ◽  
Clarisa Salado ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Dopaminergic Neurons ◽  
Motor Impairment ◽  
Initial Response ◽  
Disease Type ◽  
New Drugs ◽  
Biological Processes ◽  
Mitochondrial Localization ◽  
Lead Identification

Parkinson disease (PD) is a prevalent neurodegenerative disease characterized by selective degeneration of dopaminergic neurons in the substantia nigra, causing tremor and motor impairment. Parkin protein, whose mutants are the cause of Parkinson disease type 2 (PARK2), has been mechanistically linked to the regulation of apoptosis and the turnover of damaged mitochondria. Several studies have implicated aberrant mitochondria as a key contributor to the development of PD. In the attempt to discover new drugs, high-content cell-based assays are becoming more important to mimic the nature of biological processes and their diversifications in diseases and will be essential for lead identification and the optimization of therapeutic candidates. We have developed a novel fluorescence cell-based assay for high-content screening to find compounds that can promote the mitochondrial localization of Parkin without severe mitochondrial damage induction. In this work, this model was used to screen a library of 1280 compounds. After the screening campaign, the positive compounds were chosen for further testing, based on the strength of the initial response and lack of cytotoxicity. These results indicated that this Parkin cell-based assay is a robust (Z′ > 0.5) and valid strategy to test potential candidates for preclinical studies.

scholarly journals Interactions between Integrase and Excisionase in the Phage Lambda Excisive Nucleoprotein Complex

2002 ◽  
Vol 184 (18) ◽  
pp. 5200-5203 ◽  
Author(s):  
Eun Hee Cho ◽  
Richard I. Gumport ◽  
Jeffrey F. Gardner
Keyword(s):  
Protein Interactions ◽  
Protein Protein Interactions ◽  
Mobility Shift ◽  
Host Chromosome ◽  
Amino Terminal ◽  
Nucleoprotein Complex ◽  
Carboxyl Terminal ◽  
Α Helix ◽  
Gel Mobility Shift ◽  
Amino Terminal Domain

ABSTRACT Bacteriophage lambda site-specific recombination comprises two overall reactions, integration into and excision from the host chromosome. Lambda integrase (Int) carries out both reactions. During excision, excisionase (Xis) helps Int to bind DNA and introduces a bend in the DNA that facilitates formation of the proper excisive nucleoprotein complex. The carboxyl-terminal α-helix of Xis is thought to interact with Int through direct protein-protein interactions. In this study, we used gel mobility shift assays to show that the amino-terminal domain of Int maintained cooperative interactions with Xis. This finding indicates that the amino-terminal arm-type DNA binding domain of Int interacts with Xis.

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