Effect of hydrophobicity on protein–protein interactions

The investigation of the interaction determination between carbendazim and elastase, using both in vitro and in silico methods

Pesticides, including fungicides, are one of the important groups of environmental toxins that affect human and animal health. Studies have shown that these compounds are considered chemical pollutants. Carbendazim is a systemic fungicide. Unfortunately, excessive use of carbendazim has caused environmental pollution all over the world. In this study, the effect of carbendazim on the enzyme elastase (secreted from the endocrine gland of the pancreas) has been investigated. In a study, the performance and reaction of carbendazim with elastase were investigated using spectroscopic techniques. The stability and structure of elastase enzymes were studied under the influence of carbendazim. The results of fluorescence emission and UV-visible absorption spectrum showed that in the presence of carbendazim, there is an increase in UV-Vis absorption and a decrease in the intensity of the intrinsic fluorescence emission in the protein spectrum. Additionally, a decrease in the thermal stability of elastase was observed in the presence of carbendazim. The stability and structure of elastase enzyme were investigated in the presence of carbendazim. The results revealed that the UV-Vis absorption increased due to the presence of carbendazim, as indicated by the hyperchromic spectrum at 220 and 280 nm peaks. Additionally, the intrinsic fluorescence emission in the protein spectrum decreased with increasing carbendazim concentration at three different temperatures (298, 303, and 313 K). Moreover, the study demonstrated that the TM decreased from 2.59 to 4.58 with the increase of carbendazim, suggesting a decrease in the stability of the elastase structure in response to the elevated carbendazim concentration. According to the results of the research, the interaction between elastase and carbendazim has occurred, and changes have been made in the enzyme under the influence of carbendazim. The formation of the complex between elastase and carbendazim was consistent with the results obtained from molecular simulation and confirmed the thermodynamic data.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

Systematic identification and repurposing of FDA-approved drugs as antibacterial agents against Streptococcus pyogenes: In silico and in vitro studies

Streptococcus pyogenes (Group A Streptococcus - GAS) is a human pathogen causing wide range of infections and toxin-mediated diseases in human beings of all age groups with fatality of 10-30 %. The limited success of antibiotics and the non-availability of vaccines makes GAS a global burden. The multi-subunit RNA polymerase (RNAP) is a validated bacterial therapeutic target as it is involved in transcription and can arrest growth. Of the five subunits of this enzyme complex, the β-subunit (RpoC) has attracted specific attention as a drug target, particularly in the switch region. Here we attempt to repurpose non-antimicrobial drugs to act as RpoC inhibitors against S. pyogenes. In this study, 1826 FDA approved drugs have been identified through high-throughput virtual screening. Free Energy Perturbation (FEP) based binding free energy calculations have been performed at the final step of the virtual screening funnel to ensure high accuracy in silico results. Three compounds identified have been tested for susceptibility of S. pyogenes MTCC 442 strain and two antibiotic-resistant clinical isolates of S. pyogenes using microdilution assay. Among the three, two drugs Amlodipine Besylate (Amd) and Ranitidine hydrochloride (Rnt) have shown inhibition against all the tested strains and its mechanism of interaction with RpoC has been studied. The docked complexes were analyzed to understand the binding mode of the drugs to the target. Classical Molecular Dynamics studies for RpoC-Rnt complex and the two stable conformations of RpoC-Amd complex was carried out. Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (RoG) and Solvent Accessible Surface Area (SASA) of the complexes were plotted and studied. The thermodynamic parameters of protein-drug were experimentally determined using Isothermal Titration Calorimetry (ITC). Infrared spectroscopic studies and Fluorescence quenching studies provided insights into the secondary structural changes in RpoC on binding to the drugs.

Manipulating Physicochemical Properties of Biosensor Platform with Polysuccinimide-Silica Nanocomposite for Enhanced Protein Detection

As point-of-care testing (POCT) is becoming the new paradigm of medical diagnostics, there is a growing need to develop reliable POCT devices that can be conveniently operated in a minimally invasive manner. However, the clinical potential of POCT diagnostics is yet to be realized, mainly due to the limited and inconsistent amount of collected samples on these devices, undermining their accuracy. This study proposes a new biosensing platform modified with a functional polysuccinimide (PSI)-silica nanoparticle (SNP) composite system that can substantially increase the protein conjugation efficiency by modulating physicochemical interaction with proteins by several hundred percent from an unmodified device. The efficacy of this PSI-SNP system is further validated by applying it on the surface of a microneedle array (MN), which has emerged as a promising POCT device capable of accessing interstitial fluid through minimal penetration of the skin. This PSI-SNP MN is demonstrated to detect a wide array of proteins with high sensitivity on par with conventional whole serum analysis, validated by in vivo animal testing, effectively displaying broad applicability in biomedical engineering.

Antibody designing against IIIabc junction (JIIIabc) of HCV IRES through affinity maturation; RNA-Antibody docking and interaction analysis

Hepatitis C virus is a single-stranded RNA based virus which can cause chronic HCV and hepatocellular carcinoma. HCV genotype 3a has relatively higher rate of fibrosis progression, prevalence of steatosis and incidence of HCC. Despite HCVs variation in genomic sequence, the 5' untranslated region containing internal ribosome entry site (IRES) is highly conserved among all genotypes. It is responsible for translation and initiation of the viral protein. In present study, IRES was targeted by designing variants of reported antigen binding fragment (Fab) through affinity maturation approach. Affinity maturation strategy allowed the rational antibody designing with better biophysical properties and antibody-antigen binding interactions. Complementarity determining regions of reported Fab (wild type) were assessed and docked with IRES. Best generated model of Fab was selected and subjected to alanine scanning Three sets of insilico mutations for variants (V) designing were selected; single (1-71), double (a-j) and triple (I-X). Redocking of IRES-Fab variants consequently enabled the discovery of three variants exhibiting better docking score as compared to the wild type Fab. V1, V39 and V4 exhibited docking scores of -446.51, -446.52 and-446.29 kcal/mol respectively which is better as compared to the wild type Fab that exhibited the docking score of -351.23 kcal/mol. Variants exhibiting better docking score were screened for aggregation propensity by assessing the aggregation prone regions in Fab structure. Total A3D scores of wild type Fab, V1, V4 and V39 were predicted as -315.325, -312.727, -316.967 and -317.545 respectively. It is manifested that solubility of V4 and V39 is comparable to wild type Fab. In future, development and invitro assessment of these promising Fab HCV3 variants is aimed.

The role of surface activity on the amyloid fibrillation pathway of bovine serum albumin upon interaction with glyphosate

As an active ingredient in its derivative products, glyphosate has emerged as the most widespread herbicide in recent decades. Bovine serum albumin (BSA) as a carrier protein may be adversely affected by structural changes due to binding affinity with glyphosate, which may lead to dysfunctionality or metabolic disorders. This study aimed to investigate the interaction of glyphosate with BSA and its thermal fibrillation pathway employing techniques such as dynamic surface tension, fluorescence quenching, ThT binding, circular dichroism spectroscopy, and reactive oxygen species (ROS) measurement, as well as molecular dynamics (MD) studies. The adsorption dynamic analysis suggested hydrophobic moiety at higher concentrations of glyphosate upon interaction with BSA. MD results suggested a slight fluctuation due to glyphosate interaction with protein molecules. The carboxy group presented in glyphosate made a hydrogen bond with the hydroxyl group of TYR¹⁴⁷. The fluorescence quenching and diffusion studies approved BSA's increased unfolding and hydrophobicity resulting from glyphosate interaction, which would induce fibrillation/aggregation, according to our fibrillation kinetics data. The surface activity of glyphosate at higher concentrations and its approved involvement in structural changes of BSA through hydrogen bonding may raise concerns about its potential side effect on farm animals and the food cycle.

MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

Protein-protein interactions play a ubiquitous role in biological function. Knowledge of the three-dimensional (3D) structures of the complexes they form is essential for understanding the structural basis of those interactions and how they orchestrate key cellular processes. Computational docking has become an indispensable alternative to the expensive and time-consuming experimental approaches for determining the 3D structures of protein complexes. Despite recent progress, identifying near-native models from a large set of conformations sampled by docking-the so-called scoring problem-still has considerable room for improvement. We present MetaScore, a new machine-learning-based approach to improve the scoring of docked conformations. MetaScore utilizes a random forest (RF) classifier trained to distinguish near-native from non-native conformations using their protein-protein interfacial features. The features include physicochemical properties, energy terms, interaction-propensity-based features, geometric properties, interface topology features, evolutionary conservation, and also scores produced by traditional scoring functions (SFs). MetaScore scores docked conformations by simply averaging the score produced by the RF classifier with that produced by any traditional SF. We demonstrate that (i) MetaScore consistently outperforms each of the nine traditional SFs included in this work in terms of success rate and hit rate evaluated over conformations ranked among the top 10; (ii) an ensemble method, MetaScore-Ensemble, that combines 10 variants of MetaScore obtained by combining the RF score with each of the traditional SFs outperforms each of the MetaScore variants. We conclude that the performance of traditional SFs can be improved upon by using machine learning to judiciously leverage protein-protein interfacial features and by using ensemble methods to combine multiple scoring functions.

The effect of putrescine on the lysozyme activity and structure: Spectroscopic approaches and molecular dynamic simulation

The present research addressed the influence of polyamine (putrescine) on the compound as well as function of lysozyme; accordingly, UV- Visible, fluorescence spectroscopy and simulation method were applied to fulfill this goal. Lysozyme's structural variability was examined at various putrescine ‌concentrations; also, the putrescine binding to lysozyme was addressed using spectrofluorescence, circular dichroism (CD) and UV-Vis measurements. The obtained results indicated that with raising the putrescine concentration, the intrinsic quenching fluorescence of lysozyme was decreased based on the static mechanism. Analysis of thermodynamic parameters also indicated that van der Waals as well as hydrogen bond forces served a fundamental role in determining the resulting stability; this was in agreement with modeling studies. Measurement of UV absorption spectroscopy, fluorescence spectroscopy, and circular dichroism spectroscopy also demonstrated that lysozyme's second and tertiary structures were altered in a putrescine concentration-dependent manner. Putrescine inhibited lysozyme's enzymatic activity, displaying its affinity with the lysozyme's active site. Further, molecular simulation conducted revealed that putrescine could have spontaneous binding to lysozyme, changing its structure, thus further emphasizing the experimental results.

Modeling the MreB-CbtA Interaction to Facilitate the Prediction and Design of Candidate Antibacterial Peptides

Protein-protein interactions (PPIs) have emerged as promising targets for PPI modulators as alternative drugs because they are essential for most biochemical processes in living organisms. In recent years, a spotlight has been put on the development of peptide-based PPI inhibitors as the next-generation therapeutics to combat antimicrobial resistance taking cognizance of protein-based PPI-modulators that interact with target proteins to inhibit function. Although protein-based PPI inhibitors are not effective therapeutic agents because of their high molecular weights, they could serve as sources for peptide-based pharmaceutics if the target-inhibitor complex is accessible and well characterized. The Escherichia coli (E. coli) toxin protein, CbtA, has been identified as a protein-based PPI modulator that binds to the bacterial actin homolog MreB leading to the perturbation of its polymerization dynamics; and consequently has been suggested to have antibacterial properties. Unfortunately, however, the three-dimensional structures of CbtA and the MreB-CbtA complex are currently not available to facilitate the optimization process of the pharmacological properties of CbtA. In this study, computer modeling strategies were used to predict key MreB-CbtA interactions to facilitate the design of antiMreB peptide candidates. A model of the E. coli CbtA was built using the trRosetta software and its stability was assessed through molecular dynamics (MD) simulations. The modeling and simulations data pointed to a model with reasonable quality and stability. Also, the HADDOCK software was used to predict a possible MreB-CbtA complex, which was characterized through MD simulations and compared with MreB-MreB dimmer. The results suggest that CbtA inhibits MreB through the competitive mechanism whereby CbtA competes with MreB monomers for the interprotofilament interface leading to interference with double protofilament formation. Additionally, by using the antiBP software to predict antibacterial peptides in CbtA, and the MreB-CbtA complex as the reference structure to determine important interactions and contacts, candidate antiMreB peptides were suggested. The peptide sequences could be useful in a rational antimicrobial peptide hybridization strategy to design novel antibiotics. All-inclusive, the data reveal the molecular basis of MreB inhibition by CbtA and can be incorporated in the design/development of the next-generation antibacterial peptides targeting MreB.

ZmPPR26, a DYW-type pentatricopeptide repeat protein, is required for C-to-U RNA editing at atpA-1148 in maize chloroplasts

Pentatricopeptide repeat (PPR) proteins are involved in the C-to-U RNA editing of organellar transcripts. The maize genome contains over 600 PPR proteins and few have been found to function in the C-to-U RNA editing in chloroplasts. Here, we report the function of ZmPPR26 in the C-to-U RNA editing and chloroplast biogenesis in maize. ZmPPR26 encodes a DYW-type PPR protein targeted to chloroplasts. The zmppr26 mutant exhibits albino seedling-lethal phenotype. Loss of function of ZmPPR26 abolishes the editing at atpA-1148 site, and decreases the editing at ndhF-62, rpl20-308, rpl2-2, rpoC2-2774, petB-668, rps8-182, and ndhA-50 sites. Overexpression of ZmPPR26 in zmppr26 restores the editing efficiency and rescues the albino seedling-lethal phenotype. Abolished editing at atpA-1148 causes a Leu to Ser change at AtpA-383 that leads to a reduction in the abundance of chloroplast ATP synthase in zmppr26. The accumulation of photosynthetic complexes are also markedly reduced in zmppr26, providing an explanation for the albino seedling-lethal phenotype. These results indicate that ZmPPR26 is required for the editing at atpA-1148 and is important for editing at the other seven sites in maize chloroplasts. The editing at atpA-1148 is critical for AtpA function, assembly of ATP synthase complex, and chloroplast biogenesis in maize.

MENSAdb: a thorough structural analysis of membrane protein dimers

Membrane proteins (MPs) are key players in a variety of different cellular processes and constitute the target of around 60% of all Food and Drug Administration-approved drugs. Despite their importance, there is still a massive lack of relevant structural, biochemical and mechanistic information mainly due to their localization within the lipid bilayer. To help fulfil this gap, we developed the MEmbrane protein dimer Novel Structure Analyser database (MENSAdb). This interactive web application summarizes the evolutionary and physicochemical properties of dimeric MPs to expand the available knowledge on the fundamental principles underlying their formation. Currently, MENSAdb contains features of 167 unique MPs (63% homo- and 37% heterodimers) and brings insights into the conservation of residues, accessible solvent area descriptors, average B-factors, intermolecular contacts at 2.5 Å and 4.0 Å distance cut-offs, hydrophobic contacts, hydrogen bonds, salt bridges, π-π stacking, T-stacking and cation-π interactions. The regular update and organization of all these data into a unique platform will allow a broad community of researchers to collect and analyse a large number of features efficiently, thus facilitating their use in the development of prediction models associated with MPs. Database URL: http://www.moreiralab.com/resources/mensadb.

Identification of monoclonal antibody variants involved in aggregate formation - Part 2: Hydrophobicity variants

Monoclonal antibodies (mAbs) are valuable tools both in therapy and in diagnostic. Their tendency to aggregate is a serious concern. Since a mAb drug substance (DS) is composed of different variants, it is important for manufacturers to know the behavior and stability not only of the mAb as a whole, but also of the variants contained in the product. We present a method to separate hydrophobicity variants of a mAb and subsequently analyzed these variants for stability and aggregation propensity. We identified a potentially aggregation prone hydrophilic variant which is interrelated with another previously identified aggregation prone acidic charge variant. Additionally, we assessed the risk posed by the aggregation prone variant to the DS by spiking hydrophobicity variants into DS and did not observe an enhanced aggregation propensity. Thus we present an approach to separate, characterize and analyze the criticality of aggregation prone variants in protein DS which is a step forward to further assure drug safety.

Targeting SARS-CoV-2 RBD Interface: a Supervised Computational Data-Driven Approach to Identify Potential Modulators

Coronavirus disease 2019 (COVID-19) has spread out as a pandemic threat affecting over 2 million people. The infectious process initiates via binding of SARS-CoV-2 Spike (S) glycoprotein to host angiotensin-converting enzyme 2 (ACE2). The interaction is mediated by the receptor-binding domain (RBD) of S glycoprotein, promoting host receptor recognition and binding to ACE2 peptidase domain (PD), thus representing a promising target for therapeutic intervention. Herein, we present a computational study aimed at identifying small molecules potentially able to target RBD. Although targeting PPI remains a challenge in drug discovery, our investigation highlights that interaction between SARS-CoV-2 RBD and ACE2 PD might be prone to small molecule modulation, due to the hydrophilic nature of the bi-molecular recognition process and the presence of druggable hot spots. The fundamental objective is to identify, and provide to the international scientific community, hit molecules potentially suitable to enter the drug discovery process, preclinical validation and development.

Anammox bacteria enrichment and denitrification in moving bed biofilm reactors packed with different buoyant carriers: Performances and mechanisms

Anaerobic ammonium oxidation (anammox) is recognized as the most cost-effective process for nitrogen removal from wastewater. In this study, effects of polyethylene plastics, nonwoven fabric, granular activated carbon (GAC) and polyurethane sponge as buoyant carriers were evaluated in lab-scale moving bed biofilm reactors (MBBRs). The overall performance of MBBRs with four types of carriers from priority to inferiority was noticed as, GAC, nonwoven fabrics, polyurethane sponge and polyethylene plastics under the same packing ratio of 20 v% and an average carrier size of 4 × 4 × 4 mm. The hydrophobic surface of GAC could selectively adsorb hydrophobic protein and favor anammox bacteria attachment, which contributed to achieving a total nitrogen removal rate of 0.40 kg-N/(m³·d) in 60 days. In conclusion, our results provide compelling evidence for achieving effective anammox process in an MBBR with GAC carriers and would benefit towards accomplishing a stable partial nitritation-anammox process in the future.

Annexin B12 Trimer Formation is Governed by a Network of Protein-Protein and Protein-Lipid Interactions

Membrane protein oligomerization mediates a wide range of biological events including signal transduction, viral infection and membrane curvature induction. However, the relative contributions of protein-protein and protein-membrane interactions to protein oligomerization remain poorly understood. Here, we used the Ca²⁺-dependent membrane-binding protein ANXB12 as a model system to determine the relative contributions of protein-protein and protein-membrane interactions toward trimer formation. Using an EPR-based detection method, we find that some protein-protein interactions are essential for trimer formation. Surprisingly, these interactions are largely hydrophobic, and they do not include the previously identified salt bridges, which are less important. Interfering with membrane interaction by mutating selected Ca²⁺-ligands or by introducing Lys residues in the membrane-binding loops had variable, strongly position-dependent effects on trimer formation. The strongest effect was observed for the E226Q/E105Q mutant, which almost fully abolished trimer formation without preventing membrane interaction. These results indicate that lipids engage in specific, trimer-stabilizing interactions that go beyond simply providing a concentration-enhancing surface. The finding that protein-membrane interactions are just as important as protein-protein interactions in ANXB12 trimer formation raises the possibility that the formation of specific lipid contacts could be a more widely used driving force for membrane-mediated oligomerization of proteins in general.

Application and biomolecular study of functionalized folic acid-dendrimer nanoparticles in drug delivery

We determined the loading efficacy of folic acid - PAMAM - G3 and folic acid - PAMAM - G4 nanoparticles with doxorubicin (Dox), tamoxifen (Tam) and tetracycline (Tet) in aqueous solution at pH 7.2. Thermodynamic parameters ΔH⁰ -16 to -4 (kJ mol^-1), ΔS⁰ 31 to -0.3 (J mol^-1K^-1) and ΔG⁰ -14 to -11 (kJ mol^-1) showed drug folic acid-PAMAM bindings are via ionic, H-bonding and van der Waals interactions. As acid - PAMAM size increased the stability and loading efficacy of drug-polymer conjugates were increased. The order of stability for drug-nanoparticles was doxorubicin > tetracycline > tamoxifen. TEM analysis showed major polymer morphological changes, upon drug encapsulation. Folic acid-PAMAM conjugates are effective drug delivery tools in vitro. Communicated by Ramaswamy H. Sarma.

Prediction of Protein-Protein Interaction Sites Using Convolutional Neural Network and Improved Data Sets

Protein-protein interaction (PPI) sites play a key role in the formation of protein complexes, which is the basis of a variety of biological processes. Experimental methods to solve PPI sites are expensive and time-consuming, which has led to the development of different kinds of prediction algorithms. We propose a convolutional neural network for PPI site prediction and use residue binding propensity to improve the positive samples. Our method obtains a remarkable result of the area under the curve (AUC) = 0.912 on the improved data set. In addition, it yields much better results on samples with high binding propensity than on randomly selected samples. This suggests that there are considerable false-positive PPI sites in the positive samples defined by the distance between residue atoms.

Solvent Screening in Zwitterions Analyzed with the Fragment Molecular Orbital Method

Based on induced solvent charges, a new model of solvent screening is developed in the framework of the fragment molecular orbital combined with the polarizable continuum model. The developed model is applied to analyze interactions in a prototypical zwitterionic system, sodium chloride in water, and it is shown that the large underestimation of the interaction in the original solvent screening based on local charges is successfully corrected. The model is also applied to a complex of the Trp-cage (PDB: 1L2Y ) miniprotein with an anionic ligand, and the physical factors determined protein-ligand binding in solution are unraveled.

Pattern to Knowledge: Deep Knowledge-Directed Machine Learning for Residue-Residue Interaction Prediction

Residue-residue close contact (R2R-C) data procured from three-dimensional protein-protein interaction (PPI) experiments is currently used for predicting residue-residue interaction (R2R-I) in PPI. However, due to complex physiochemical environments, R2R-I incidences, facilitated by multiple factors, are usually entangled in the source environment and masked in the acquired data. Here we present a novel method, P2K (Pattern to Knowledge), to disentangle R2R-I patterns and render much succinct discriminative information expressed in different specific R2R-I statistical/functional spaces. Since such knowledge is not visible in the data acquired, we refer to it as deep knowledge. Leveraging the deep knowledge discovered to construct machine learning models for sequence-based R2R-I prediction, without trial-and-error combination of the features over external knowledge of sequences, our R2R-I predictor was validated for its effectiveness under stringent leave-one-complex-out-alone cross-validation in a benchmark dataset, and was surprisingly demonstrated to perform better than an existing sequence-based R2R-I predictor by 28% (p: 1.9E-08). P2K is accessible via our web server on https://p2k.uwaterloo.ca .

Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features

Protein-protein interactions (PPIs) play important roles in various aspects of the structural and functional organization of cells; thus, detecting PPIs is one of the most important issues in current molecular biology. Although much effort has been devoted to using high-throughput techniques to identify protein-protein interactions, the experimental methods are both time-consuming and costly. In addition, they yield high rates of false positive and false negative results. In addition, most of the proposed computational methods are limited in information about protein homology or the interaction marks of the protein partners. In this paper, we report a computational method only using the information from protein sequences. The main improvements come from novel protein sequence representation by combing the continuous and discrete wavelet transforms and from adopting weighted sparse representation-based classifier (WSRC). The proposed method was used to predict PPIs from three different datasets: yeast, human and H. pylori. In addition, we employed the prediction model trained on the PPIs dataset of yeast to predict the PPIs of six datasets of other species. To further evaluate the performance of the prediction model, we compared WSRC with the state-of-the-art support vector machine classifier. When predicting PPIs of yeast, humans and H. pylori dataset, we obtained high average prediction accuracies of 97.38%, 98.92% and 93.93% respectively. In the cross-species experiments, most of the prediction accuracies are over 94%. These promising results show that the proposed method is indeed capable of obtaining higher performance in PPIs detection.

Cathepsin-Mediated Cleavage of Peptides from Peptide Amphiphiles Leads to Enhanced Intracellular Peptide Accumulation

Peptides synthesized in the likeness of their native interaction domain(s) are natural choices to target protein-protein interactions (PPIs) due to their fidelity of orthostatic contact points between binding partners. Despite therapeutic promise, intracellular delivery of biofunctional peptides at concentrations necessary for efficacy remains a formidable challenge. Peptide amphiphiles (PAs) provide a facile method of intracellular delivery and stabilization of bioactive peptides. PAs consisting of biofunctional peptide headgroups linked to hydrophobic alkyl lipid-like tails prevent peptide hydrolysis and proteolysis in circulation, and PA monomers are internalized via endocytosis. However, endocytotic sequestration and steric hindrance from the lipid tail are two major mechanisms that limit PA efficacy to target intracellular PPIs. To address these problems, we have constructed a PA platform consisting of cathepsin-B cleavable PAs in which a selective p53-based inhibitory peptide is cleaved from its lipid tail within endosomes, allowing for intracellular peptide accumulation and extracellular recycling of the lipid moiety. We monitor for cleavage and follow individual PA components in real time using a Förster resonance energy transfer (FRET)-based tracking system. Using this platform, we provide a better understanding and quantification of cellular internalization, trafficking, and endosomal cleavage of PAs and of the ultimate fates of each component.

PEG and mPEG-anthracene conjugate with trypsin and trypsin inhibitor: hydrophobic and hydrophilic contacts

The conjugation of trypsin (try) and trypsin inhibitor (tryi) with poly(ethylene glycol) (PEG) and methoxypoly(ethylene glycol) anthracene (mPEG-anthracene) was investigated in aqueous solution, using multiple spectroscopic methods, thermodynamic analysis, and molecular modeling. Thermodynamic parameters ΔS, ΔH, and ΔG showed protein-PEG bindings occur via H-bonding and van der Waals contacts with trypsin inhibitor forming more stable conjugate than trypsin. As polymer size increased more stable PEG-protein conjugate formed, while hydrophobic mPEG-anthracene forms less stable protein complexes. Modeling showed the presence of several H-bonding contacts between polymer and amino acids that stabilize protein-polymer conjugation. Polymer complexation induces more perturbations of trypsin inhibitor structure than trypsin with reduction of protein alpha-helix and major increase in random structures, indicating protein structural destabilization.

tRNA conjugation with folic acid-chitosan conjugates

The conjugation of tRNA with folic acid-chitosan conjugates was studied, using multiple spectroscopic methods and transmission electron microscopy (TEM). Thermodynamic analysis ΔH -14 to -10 (KJMol^-1) and ΔS 14 to -1 (JMol^-1, K^-1) showed tRNA-folic acid-chitosan bindings occur via H-bonding, hydrophobic and van der Waals contacts. The loading efficacy and the stability of tRNA conjugates were enhanced as folic acid-chitosan size increased. TEM analysis showed major tRNA morphological changes, upon folic acid-chitosan conjugation. No alteration of tRNA conformation was observed on conjugate formation. Folic acid-chitosan conjugates can deliver tRNA in vitro.

Customised nucleic acid libraries for enhanced aptamer selection and performance

Aptamers are short single-stranded oligo(deoxy)nucleotides that are selected to bind to target molecules with high affinity and specificity. Because of their sophisticated characteristics and versatile applicability, aptamers are thought to become universal molecular probes in biotechnological and therapeutic applications. However, the variety of possible interactions with a putative target molecule is limited by the chemical repertoire of the natural nucleobases. Consequently, many desired targets are not addressable by aptamers. This obstacle is overcome by broadening the chemical diversity of aptamers, mainly achieved by nucleobase-modifications and the introduction of novel bases or base pairs. We discuss these achievements and the characteristics of the respective modified aptamers, reflected by SOMAmers (slow off-rate modified aptamers), clickmers, and aptamers bearing an expanded genetic alphabet.

Aggregation of trypsin and trypsin inhibitor by Al cation

Al cation may trigger protein structural changes such as aggregation and fibrillation, causing neurodegenerative diseases. We report the effect of Al cation on the solution structures of trypsin (try) and trypsin inhibitor (tryi), using thermodynamic analysis, UV-Visible, Fourier transform infrared (FTIR) spectroscopic methods and atomic force microscopy (AFM). Thermodynamic parameters showed Al-protein bindings occur via H-bonding and van der Waals contacts for trypsin and trypsin inhibitor. AFM showed that Al cations are able to force trypsin into larger or more robust aggregates than trypsin inhibitor, with trypsin 5±1 SE (n=52) proteins per aggregate and for trypsin inhibitor 8.3±0.7 SE (n=118). Thioflavin T test showed no major protein fibrillation in the presence of Al cation. Al complexation induced more alterations of trypsin inhibitor conformation than trypsin.

Electrostatic potentials of the S-locus F-box proteins contribute to the pollen S specificity in self-incompatibility in Petunia hybrida

Self-incompatibility (SI) is a self/non-self discrimination system found widely in angiosperms and, in many species, is controlled by a single polymorphic S-locus. In the Solanaceae, Rosaceae and Plantaginaceae, the S-locus encodes a single S-RNase and a cluster of S-locus F-box (SLF) proteins to control the pistil and pollen expression of SI, respectively. Previous studies have shown that their cytosolic interactions determine their recognition specificity, but the physical force between their interactions remains unclear. In this study, we show that the electrostatic potentials of SLF contribute to the pollen S specificity through a physical mechanism of 'like charges repel and unlike charges attract' between SLFs and S-RNases in Petunia hybrida. Strikingly, the alteration of a single C-terminal amino acid of SLF reversed its surface electrostatic potentials and subsequently the pollen S specificity. Collectively, our results reveal that the electrostatic potentials act as a major physical force between cytosolic SLFs and S-RNases, providing a mechanistic insight into the self/non-self discrimination between cytosolic proteins in angiosperms.

Protein conjugation with PAMAM nanoparticles: Microscopic and thermodynamic analysis

PAMAM dendrimers form strong protein conjugates that are used in drug delivery systems. We report the thermodynamic and binding analysis of polyamidoamine (PAMAM-G4) conjugation with human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (b-LG) in aqueous solution at physiological pH. Hydrophobicity played a major role in PAMAM-protein interactions with more hydrophobic b-LG forming stronger polymer-protein conjugates. Thermodynamic parameters showed PAMAM-protein bindings occur via hydrophobic and H-bonding contacts for b-LG, while van der waals and H-bonding interactions prevail in HSA and BSA-polymer conjugates. The protein loading efficacy was 45-55%. PAMAM complexation induced major alterations of protein conformation. TEM images show major polymer morphological changes upon protein conjugation.

Conjugation of biogenic and synthetic polyamines with serum proteins: A comprehensive review

We have reviewed the conjugation of biogenic polyamines spermine (spm), spermidine (spmd) and synthetic polyamines 3,7,11,15-tetrazaheptadecane.4HCl (BE-333) and 3,7,11,15,19-pentazahenicosane.5HCl (BE-3333) with human serum albumin (HSA), bovine serum albumin (BSA) and milk beta-lactoglobulin (b-LG) in aqueous solution at physiological pH. The results of multiple spectroscopic methods and molecular modeling were analysed here and correlations between polyamine binding mode and protein structural changes were estabilished. Polyamine-protein bindings are mainly via hydrophilic and H-bonding contacts. BSA forms more stable conjugates than HSA and b-LG. Biogenic polyamines form more stable complexes than synthetic polyamines except in the case of b-LG, where the protein shows more hydrophobic character than HSA and BSA. The loading efficacies were 40-52%. Modeling showed the presence of several H-bonding systems, which stabilized polyamine-protein conjugates. Polyamine conjugation induced major alterations of serum protein conformations. The potential application of serum proteins in delivery of polyamines is evaluated here.

Design strategies to address the effect of hydrophobic epitope on stability and in vitro assembly of modular virus-like particle

Virus-like particles (VLPs) and capsomere subunits have shown promising potential as safe and effective vaccine candidates. They can serve as platforms for the display of foreign epitopes on their surfaces in a modular architecture. Depending on the physicochemical properties of the antigenic modules, modularization may affect the expression, solubility and stability of capsomeres, and VLP assembly. In this study, three module designs of a rotavirus hydrophobic peptide (RV10) were synthesized using synthetic biology. Among the three synthetic modules, modularization of the murine polyomavirus VP1 with a single copy of RV10 flanked by long linkers and charged residues resulted in the expression of stable modular capsomeres. Further employing the approach of module titration of RV10 modules on each capsomere via Escherichia coli co-expression of unmodified VP1 and modular VP1-RV10 successfully translated purified modular capomeres into modular VLPs when assembled in vitro. Our results demonstrate that tailoring the physicochemical properties of modules to enhance modular capsomeres stability is achievable through synthetic biology designs. Combined with module titration strategy to avoid steric hindrance to intercapsomere interactions, this allows bioprocessing of bacterially produced in vitro assembled modular VLPs.

Lysozyme Photochemistry as a Function of Temperature. The Protective Effect of Nanoparticles on Lysozyme Photostability

The presence of aromatic residues and their close spatial proximity to disulphide bridges makes hen egg white lysozyme labile to UV excitation. UVB induced photo-oxidation of tryptophan and tyrosine residues leads to photochemical products, such as, kynurenine, N-formylkynurenine and dityrosine and to the disruption of disulphide bridges in proteins. We here report that lysozyme UV induced photochemistry is modulated by temperature, excitation power, illumination time, excitation wavelength and by the presence of plasmonic quencher surfaces, such as gold, and by the presence of natural fluorescence quenchers, such as hyaluronic acid and oleic acid. We show evidence that the photo-oxidation effects triggered by 295 nm at 20°C are reversible and non-reversible at 10°C, 25°C and 30°C. This paper provides evidence that the 295 nm damage threshold of lysozyme lies between 0.1 μW and 0.3 μW. Protein conformational changes induced by temperature and UV light have been detected upon monitoring changes in the fluorescence emission spectra of lysozyme tryptophan residues and SYPRO® Orange. Lysozyme has been conjugated onto gold nanoparticles, coated with hyaluronic acid and oleic acid (HAOA). Steady state and time resolved fluorescence studies of free and conjugated lysozyme onto HAOA gold nanoparticles reveals that the presence of the polymer decreased the rate of the observed photochemical reactions and induced a preference for short fluorescence decay lifetimes. Size and surface charge of the HAOA gold nanoparticles have been determined by dynamic light scattering and zeta potential measurements. TEM analysis of the particles confirms the presence of a gold core surrounded by a HAOA matrix. We conclude that HAOA gold nanoparticles may efficiently protect lysozyme from the photochemical effects of UVB light and this nanocarrier could be potentially applied to other proteins with clinical relevance. In addition, this study confirms that the temperature plays a critical role in the photochemical pathways a protein enters upon UV excitation.