Hydrophobic, hydrophilic, and charged amino acid networks within protein

Laponite nanoclays for the sustained delivery of therapeutic proteins

Protein therapeutics hold immense promise for treating a wide array of diseases. However, their efficacy is often compromised by rapid degradation and clearance. The synthetic smectite clay Laponite emerges as a promising candidate for their sustained delivery. Despite its unique properties allow to load and release proteins mitigating burst release and extending their effects, precise control over Laponite-protein interactions remains challenging since it depends on a complex interplay of factors whose implication is not fully understood yet. The aim of this review article is to shed light on this issue, providing a comprehensive discussion of the factors influencing protein loading and release, including the physicochemical properties of the nanoclay and proteins, pH, dispersion buffer, clay/protein concentration and Laponite degradation. Furthermore, we thoroughly revise the array of bioactive proteins that have been delivered from formulations containing the nanoclay, highlighting Laponite-polymer nanocomposite hydrogels, a promising avenue currently under extensive investigation.

Revealing the interaction between alpha-chymotrypsin and eugenol: An integrated multi-spectral and dynamic simulation approach

The study aims to explore the effects of Eugenol (EUG) as an antioxidant on α-Chymotrypsin (α-Chy) and its interaction mechanism, with potential implications for new therapy development. The interaction between EUG and α-Chy was demonstrated through ultraviolet (UV) spectroscopy, which resulted in a shift in absorption with docking energies of -22.76 kJ/mol. An increase in fluorescence intensity indicated that the Trp residues moved to a less polar environment, which is consistent with the changes in accessible surface area (ASA) values. The presence of EUG led to a decrease in α-helix, β-turn, and random coil structures as shown by circular dichroism (CD) and Fourier-transform infrared (FTIR) analysis. Additionally, there was a slight increase in β-sheet structures, indicating a decrease in enzyme stability. However, tests for thermal stability showed a decrease in folding upon the introduction of EUG, which contradicted the results obtained from molecular dynamics (MD) simulations. The docking studies revealed that EUG forms hydrogen bonds and van der Waals forces with the enzyme, indicating the interaction mechanism. Kinetic studies confirmed that EUG acts as a mixed inhibitor. However, further research involving live organisms is necessary to fully understand its potential.

Electric field modulated configuration and orientation of aqueous molecule chains

Understanding how external electric fields (EFs) impact the properties of aqueous molecules is crucial for various applications in chemistry, biology, and engineering. In this paper, we present a study utilizing molecular dynamics simulation to explore how direct-current (DC) and alternative-current (AC) EFs affect hydrophobic (n-triacontane) and hydrophilic (PEG-10) oligomer chains. Through a machine learning approach, we extract a 2-dimensional free energy (FE) landscape of these molecules, revealing that electric fields modulate the FE landscape to favor stretched configurations and enhance the alignment of the chain with the electric field. Our observations indicate that DC EFs have a more prominent impact on modulation compared to AC EFs and that EFs have a stronger effect on hydrophobic chains than on hydrophilic oligomers. We analyze the orientation of water dipole moments and hydrogen bonds, finding that EFs align water molecules and induce more directional hydrogen bond networks, forming 1D water structures. This favors the stretched configuration and alignment of the studied oligomers simultaneously, as it minimizes the disruption of 1D structures. This research deepens our understanding of the mechanisms by which electric fields modulate molecular properties and could guide the broader application of EFs to control other aqueous molecules, such as proteins or biomolecules.

Exploring α-synuclein stability under the external electrostatic field: Effect of repeat unit

Parkinson's disease (PD) is a category of neurodegenerative disorders (ND) that currently lack comprehensive and definitive treatment strategies. The etiology of PD can be attributed to the presence and aggregation of a protein known as α-synuclein. Researchers have observed that the application of an external electrostatic field holds the potential to induce the separation of the fibrous structures into peptides. To comprehend this phenomenon, our investigation involved simulations conducted on the α-synuclein peptides through the application of Molecular Dynamics (MD) simulation techniques under the influence of a 0.1 V/nm electric field. The results obtained from the MD simulations revealed that in the presence of external electric field, the monomer and oligomeric forms of α-synuclein are experienced significant conformational changes which could prevent them from further aggregation. However, as the number of peptide units in the model system increases, forming trimers and tetramers, the stability against the electric field also increases. This enhanced stability in larger aggregates indicates a critical threshold in α-synuclein assembly where the electric field's effectiveness in disrupting the aggregation diminishes. Therefore, our findings suggest that early diagnosis and intervention could be crucial in preventing PD progression. When α-synuclein predominantly exists in its monomeric or dimeric form, applying even a lower electric field could effectively disrupt the initial aggregation process. Inhibition of α-synuclein fibril formation at early stages might serve as a viable solution to combat PD by halting the formation of more stable and pathogenic α-synuclein fibrils.

Molecular Dynamics Simulation of Kir6.2 Variants Reveals Potential Association with Diabetes Mellitus

Diabetes mellitus (DM) represents a problem for the healthcare system worldwide. DM has very serious complications such as blindness, kidney failure, and cardiovascular disease. In addition to the very bad socioeconomic impacts, it influences patients and their families and communities. The global costs of DM and its complications are huge and expected to rise by the year 2030. DM is caused by genetic and environmental risk factors. Genetic testing will aid in early diagnosis and identification of susceptible individuals or populations using ATP-sensitive potassium (KATP) channels present in different tissues such as the pancreas, myocardium, myocytes, and nervous tissues. The channels respond to different concentrations of blood sugar, stimulation by hormones, or ischemic conditions. In pancreatic cells, they regulate the secretion of insulin and glucagon. Mutations in the KCNJ11 gene that encodes the Kir6.2 protein (a major constituent of KATP channels) were reported to be associated with Type 2 DM, neonatal diabetes mellitus (NDM), and maturity-onset diabetes of the young (MODY). Kir6.2 harbors binding sites for ATP and phosphatidylinositol 4,5-diphosphate (PIP2). The ATP inhibits the KATP channel, while the (PIP2) activates it. A Kir6.2 mutation at tyrosine330 (Y330) was demonstrated to reduce ATP inhibition and predisposes to NDM. In this study, we examined the effect of mutations on the Kir6.2 structure using bioinformatics tools and molecular dynamic simulations (SIFT, PolyPhen, SNAP2, PANTHER, PhD&SNP, SNP&Go, I-Mutant, MuPro, MutPred, ConSurf, HOPE, and GROMACS). Our results indicated that M199R, R201H, R206H, and Y330H mutations influence Kir6.2 structure and function and therefore may cause DM. We conclude that MD simulations are useful techniques to predict the effects of mutations on protein structure. In addition, the M199R, R201H, R206H, and Y330H variant in the Kir6.2 protein may be associated with DM. These results require further verification in protein-protein interactions, Kir6.2 function, and case-control studies.

Revisiting structural organization of proteins at high temperature from a network perspective

Interactions between distantly placed amino acids in the primary chain (long-range) play a very crucial role in the formation and stabilization of the tertiary structure of a protein, while interactions between closely placed amino acids in the primary chain (short-range) mostly stabilize the secondary structures. Every protein needs to maintain marginal stability in order to perform its physiological functions in its native environment. The requirements for this stability in mesophilic and thermophilic proteins are different. Thermophilic proteins need to form more interactions as well as more stable interactions to survive in the extreme environment, they live in. Here, we aim to find out how the interacting amino acids in three-dimensional space are positioned in the primary chains in thermophilic and mesophilic. How does this arrangement help thermophiles to maintain their structural integrity at high temperatures? Working on a dataset of 1560 orthologous pairs we perceive that thermophiles are not only enriched with long-range interactions, they feature bigger connected clusters and higher network densities compared to their mesophilic orthologs, at higher interaction strengths between the amino acids. Moreover, we have observed the enrichment of different types of interactions at different secondary structural regions.

Excavation, identification and structure-activity relationship of heat-stable umami peptides in the processing of Wuding chicken

Umami peptides from different stages of Wuding chicken processing were discovered, isolated, and purified using ultrafiltration membrane, gel filtration chromatography, and reversed-phase high-performance liquid chromatography, and the binding mechanism was explored. Twelve umami peptides were found by nano-scale liquid chromatography-tandem mass spectrometry, three of which (HLEEEIK, LDDALR, and ELY) existed throughout the processing step. The umami score and the frequency of active fragments of umami were highest for LEEEL, followed by EEF. The main active sites between umami peptide and receptor T1R1/T1R3 were Tyr262, Glu325, and Glu292, and hydrophobic interaction and hydrogen bonding were the main forces, and bitter amino acids were also important components of umami peptides. It was found for the first time that heat-stable umami peptides exist in Wuding chickens, which provides a basis for the identification and screening of umami peptides in local chickens, and also helps to study the structure-activity relationship of umami peptides.

Identification, Characterization, and Receptor Binding Mechanism of New Umami Peptides from Traditional Fermented Soybean Paste (Dajiang)

Dajiang, a traditional Chinese condiment, is made from fermented soybeans. It is highly popular among consumers as a result of its delicious umami flavor, which mainly originates from umami peptides. To examine the mechanism of umami taste in Dajiang, we selected Dajiang samples with strong umami taste and subjected them to purification and identification analysis using ethanol precipitation, gel chromatography, reversed-phase high-performance liquid chromatography, and ultraperformance liquid chromatography-tandem mass spectrometry. Subsequently, on the basis of toxicity and umami prediction analysis, we screened, synthesized, and characterized three novel bean umami peptides in Dajiang: TLGGPTTL, 758.4174 Da; GALEQILQ, 870.4811 Da; and HSISDLQ, 911.4713 Da. Their sensory threshold values were 0.25, 0.40, and 0.17 mmol/L, respectively. Furthermore, molecular docking results showed that hydrogen-bonding and hydrophobic interactions are important interaction forces in the binding of umami peptide to taste receptors. Ser147 and Glu148 of the T1R3 taste receptor are important amino acid residues for binding of the three umami peptides. This study uncovers the mechanism of umami-peptide-driven flavor in fermented soybean products.

Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review

In recent years, the widespread application of artificial intelligence algorithms in protein structure, function prediction, and de novo protein design has significantly accelerated the process of intelligent protein design and led to many noteworthy achievements. This advancement in protein intelligent design holds great potential to accelerate the development of new drugs, enhance the efficiency of biocatalysts, and even create entirely new biomaterials. Protein characterization is the key to the performance of intelligent protein design. However, there is no consensus on the most suitable characterization method for intelligent protein design tasks. This review describes the methods, characteristics, and representative applications of traditional descriptors, sequence-based and structure-based protein characterization. It discusses their advantages, disadvantages, and scope of application. It is hoped that this could help researchers to better understand the limitations and application scenarios of these methods, and provide valuable references for choosing appropriate protein characterization techniques for related research in the field, so as to better carry out protein research.

In Silico Investigation of AKT2 Gene and Protein Abnormalities Reveals Potential Association with Insulin Resistance and Type 2 Diabetes

Type 2 diabetes (T2D) develops from insulin resistance (IR) and the dysfunction of pancreatic beta cells. The AKT2 protein is very important for the protein signaling pathway, and the non-synonymous SNP (nsSNPs) in AKT2 gene may be associated with T2D. nsSNPs can result in alterations in protein stability, enzymatic activity, or binding specificity. The objective of this study was to investigate the effect of nsSNPs on the AKT2 protein structure and function that may result in the induction of IR and T2D. The study identified 20 variants that were considered to be the most deleterious based on a range of analytical tools included (SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, and I-Mut). Two mutations, p.A179T and p.L183Q, were selected for further investigation based on their location within the protein as determined by PyMol. The results indicated that mutations, p.A179T and p.L183Q alter the protein stability and functional characteristics, which could potentially affect its function. In order to conduct a more in-depth analysis of these effects, a molecular dynamics simulation was performed for wildtype AKT2 and the two mutants (p.A179T and p.L183Q). The simulation evaluated various parameters, including temperature, pressure, density, RMSD, RMSF, SASA, and Region, over a period of 100 ps. According to the simulation results, the wildtype AKT2 protein demonstrated higher stability in comparison to the mutant variants. The mutations p.A179T and p.L183Q were found to cause a reduction in both protein stability and functionality. These findings underscore the significance of the effects of nsSNPs (mutations p.A179T and p.L183Q) on the structure and function of AKT2 that may lead to IR and T2D. Nevertheless, they require further verifications in future protein functional, protein-protein interaction, and large-scale case-control studies. When verified, these results will help in the identification and stratification of individuals who are at risk of IR and T2D for the purpose of prevention and treatment.

In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson's disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case-control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.

Understanding the helical stability of charged peptides

Cationic helical peptides play a crucial role in applications such as anti-microbial and anticancer activity. The activity of these peptides directly correlates with their helicity. In this study, we have performed extensive all-atom molecular dynamics simulations of 25 Lysine-Leucine co-polypeptide sequences of varying charge density ( λ ) and patterns. Our findings showed that, an increase in the charge density on the peptide leads to a gradual decrease in the helicity up to a critical charge density λ c . Beyond λ c _, a complete helix to coil transition was observed. The decrease in the helicity is correlated with the increased number of water molecules in first solvation shell, solvent-exposed surface area, and a higher value of the radius of gyration of the peptide.

Identification and characterization of proteins that form the inner core Ixodes scapularis tick attachment cement layer

Ixodes scapularis long-term blood feeding behavior is facilitated by a tick secreted bio adhesive (tick cement) that attaches tick mouthparts to skin tissue and prevents the host from dislodging the attached tick. Understanding tick cement formation is highly sought after as its disruption will prevent tick feeding. This study describes proteins that form the inner core layer of I. scapularis tick cement as disrupting these proteins will likely stop formation of the outer cortical layer. The inner core cement layer completes formation by 24 h of tick attachment. Thus, we used laser-capture microdissection to isolate cement from cryosections of 6 h and 24 h tick attachment sites and to distinguish between early and late inner core cement proteins. LC-MS/MS analysis identified 138 tick cement proteins (TCPs) of which 37 and 35 were unique in cement of 6 and 24 h attached ticks respectively. We grouped TCPs in 14 functional categories: cuticular protein (16%), tick specific proteins of unknown function, cytoskeletal proteins, and enzymes (13% each), enzymes (10%), antioxidant, glycine rich, scaffolding, heat shock, histone, histamine binding, proteases and protease inhibitors, and miscellaneous (3-6% each). Gene ontology analysis confirm that TCPs are enriched for bio adhesive properties. Our data offer insights into tick cement bonding patterns and set the foundation for understanding the molecular basis of I. scapularis tick cement formation.

Spray-Drying Hen Eggs: Effects of the Egg Yolk to Egg White Ratio and Sucrose Addition on the Physicochemical, Functional, and Nutritional Properties of Dried Products and on Their Amino Acid Profiles

Manufactured egg powders can be formulated to produce food products that vary in their properties. The present study aims to determine the effect of egg white content on the physicochemical characteristics and on the functionality and nutritional value of dried whole egg (WE), egg white (W), and an egg yolk/white mixture in a 1:3 ratio (M1:3). These fresh egg products were spray-dried using sucrose—an agent recognized for its effect of protecting the protein in the egg during the drying process. Experiments were conducted in a laboratory-scale spray dryer, operated under controlled conditions, with an air inlet temperature of 120 °C. In the dried products, water activity, water solubility index, color, and pH were affected significantly as a function of the fresh egg component ratio and the added sucrose. The wettability and dispersibility in water of egg powder were improved when sucrose was added to the WE. The water-holding capacity was highest in dried egg white, and higher in the M1:3 mixture without sucrose added than in the WE with 5% sucrose. The results suggest that modifying the ratio of fresh egg yolk to egg white could lend some control over the protein and fat contents of dried egg products and over their functional properties.

Inferring Retinal Degeneration-Related Genes Based on Xgboost

Retinal Degeneration (RD) is an inherited retinal disease characterized by degeneration of rods and cones photoreceptor cells and degeneration of retinal pigment epithelial cells. The age of onset and disease progression of RD are related to genes and environment. At present, research has discovered five genes closely related to RD. They are RHO, PDE6B, MERTK, RLBP1, RPGR, and researchers have developed corresponding gene therapy methods. Gene therapy uses vectors to transfer therapeutic genes, genetically modify target cells, and correct or replace disease-causing RD genes. Therefore, identifying the pathogenic genes of RD will play an important role in the development of treatment methods for the disease. However, the traditional methods of identifying RD-related genes are mostly based on animal experiments, and currently only a small number of RD-related genes have been identified. With the increase of biological data, Xgboost is purposed in this article to identify RP-related genes. Xgboost adds a regular term to control the complexity of the model, hence using Xgboost to find out true RD-related genes from complex and massive genes is suitable. The problem of overfitting can be avoided to some extent. To verify the power of Xgboost to identify RD-related genes, we did 10-cross validation and compared with three traditional methods: Random Forest, Back Propagation network, Support Vector Machine. The accuracy of Xgboost is 99.13% and AUC is much higher than other three methods. Therefore, this article can provide technical support for efficient identification of RD-related genes and help researchers have a deeper the understanding of the genetic characteristics of RD.

Humans and machines in biomedical knowledge curation: hypertrophic cardiomyopathy molecular mechanisms' representation

Background

Biomedical knowledge is dispersed in scientific literature and is growing constantly. Curation is the extraction of knowledge from unstructured data into a computable form and could be done manually or automatically. Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease, with genotype–phenotype associations still incompletely understood. We compared human- and machine-curated HCM molecular mechanisms’ models and examined the performance of different machine approaches for that task.

Results

We created six models representing HCM molecular mechanisms using different approaches and made them publicly available, analyzed them as networks, and tried to explain the models’ differences by the analysis of factors that affect the quality of machine-curated models (query constraints and reading systems’ performance). A result of this work is also the Interactive HCM map, the only publicly available knowledge resource dedicated to HCM. Sizes and topological parameters of the networks differed notably, and a low consensus was found in terms of centrality measures between networks. Consensus about the most important nodes was achieved only with respect to one element (calcium). Models with a reduced level of noise were generated and cooperatively working elements were detected. REACH and TRIPS reading systems showed much higher accuracy than Sparser, but at the cost of extraction performance. TRIPS proved to be the best single reading system for text segments about HCM, in terms of the compromise between accuracy and extraction performance.

Conclusions

Different approaches in curation can produce models of the same disease with diverse characteristics, and they give rise to utterly different conclusions in subsequent analysis. The final purpose of the model should direct the choice of curation techniques. Manual curation represents the gold standard for information extraction in biomedical research and is most suitable when only high-quality elements for models are required. Automated curation provides more substance, but high level of noise is expected. Different curation strategies can reduce the level of human input needed. Biomedical knowledge would benefit overwhelmingly, especially as to its rapid growth, if computers were to be able to assist in analysis on a larger scale.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13040-021-00279-2.

Characteristics of gelatin from skin and bone of snakehead (Channa striata) extracted with different temperature and time

This study aimed to determine the physicochemical properties of the skin and bone of snakehead fish as a potential source of gelatin through extraction at different temperatures and times compared to commercial gelatin. Extraction of skin and bones of wild snakehead fish (Channa striata) at different temperatures (50, 60, 70 ºC) and time (12,18, 24 hours). The pre-treatment process used a 0.1 M Ca (OH) 2 (1:6 w/v) immersion solution for 1 h and continued with 0.05 M citric acid (1:6 b/v) for 5 h. Before pre-treatment, the minerals of bones were degreased with 3% HCL solution for 24 hours. The results of the analysis showed that the differences in raw materials, temperature, and extraction time had a significant effect (p <0.05), as well as interactions among treatments (p <0.05) on the yield and gel strength. The yield of skin and bone tended to increase with extending extraction temperature and time, while the highest gelatin strength was found at 60 °C for 12 hours on the skin and 24 hours for the bone. The best gelatin was accomplished based on the highest performance of gel strength on skin and bones and compared to bovine commercial gelatin. The amino acids of the three types of gelatin showed higher levels of glycine and proline than other types of amino acids. Based on the total residues of each amino acid, skin gelatin and bone gelatin showed more dominant hydrophobic properties than hydrophilic properties, in contrast to bovine commercial gelatin. The three types of gelatin showed diverse chemical compositions, emulsion activity index, emulsion stability, water resistance, and fat binding capacity, which was reflected to be closely related to the source of the raw material and its amino acid content. The FTIR results showed that the extracted snakehead fish skin and bones have the potentiality to be used as gelatin equivalent to a commercial one

Type II c-Met inhibitors: molecular insight into crucial interactions for effective inhibition

The c-Met tyrosine kinase plays an important role in human cancers. Preclinical studies demonstrated that c-Met is over-expressed, mutated and amplified in a variety of human tumor types and design of more potent c-Met inhibitors is a priority. In this study, 14 molecular dynamics simulations of potent type II c-Met inhibitors were run to resolve the critical interactions responsible for high affinity of ligands towards c-Met considering the essential flexibility of protein-ligand interactions. Residues Phe1223 and Tyr1159, involved in pi-pi interactions were recognized as the most effective residues in the ligand binding in terms of binding free energies. Hydrogen bond interaction with Met1160 was also found necessary for effective type II ligand binding to c-Met.

Identification of benzamide inhibitors of histone deacetylase 1 from Babesia and Theileria species via high-throughput virtual screening and molecular dynamics simulations

Theileria and Babesia species are eukaryotic protozoan parasites classified under the order Piroplasmida of the phylum Apicomplexa. Tick vectors transmit these microorganisms in tropical and subtropical regions to a wide range of animals, including ruminants, causing fatal and life-threatening diseases such as bovine babesiosis and theileriosis. Resistance to commercially available drugs requires the search for new drug candidates. Histone deacetylase (HDAC) has a potential to be utilized as a drug target; therefore, it may be considered as an effective alternative. Previous studies revealed that HDAC inhibitors, identified for human use, show promising anti-parasitic effects. We have herein focused on the class I HDAC enzyme, HDAC1, of the Babesia and Theileria species to discover potential benzamide inhibitors by following a streamlined workflow of computer-aided drug design methodology. Molecular docking and molecular dynamics simulations revealed that benzamide derivatives stably interacted with the HDAC1 active site in both parasites as hypothesized. Furthermore, specific residue insertions at the entry point of the active site cleft of parasitic HDAC1 could enable ways to design parasite-specific drugs without adversely affecting host enzymes.

Characterizing Hydropathy of Amino Acid Side Chain in a Protein Environment by Investigating the Structural Changes of Water Molecules Network

Assessing the hydropathy properties of molecules, like proteins and chemical compounds, has a crucial role in many fields of computational biology, such as drug design, biomolecular interaction, and folding prediction. Over the past decades, many descriptors were devised to evaluate the hydrophobicity of side chains. In this field, recently we likewise have developed a computational method, based on molecular dynamics data, for the investigation of the hydrophilicity and hydrophobicity features of the 20 natural amino acids, analyzing the changes occurring in the hydrogen bond network of water molecules surrounding each given compound. The local environment of each residue is complex and depends on the chemical nature of the side chain and the location in the protein. Here, we characterize the solvation properties of each amino acid side chain in the protein environment by considering its spatial reorganization in the protein local structure, so that the computational evaluation of differences in terms of hydropathy profiles in different structural and dynamical conditions can be brought to bear. A set of atomistic molecular dynamics simulations have been used to characterize the dynamic hydrogen bond network at the interface between protein and solvent, from which we map out the local hydrophobicity and hydrophilicity of amino acid residues.

Characterizing genomic variants and mutations in SARS-CoV-2 proteins from Indian isolates

SARS-CoV-2 is mutating and creating divergent variants by altering the composition of essential constituent proteins. Pharmacologically, it is crucial to understand the diverse mechanism of mutations for stable vaccine or anti-viral drug design. Our current study concentrates on all the constituent proteins of 469 SARS-CoV-2 genome samples, derived from Indian patients. However, the study may easily be extended to the samples across the globe.

We perform clustering analysis towards identifying unique variants in each of the SARS-CoV-2 proteins. A total of 536 mutated positions within the coding regions of SARS-CoV-2 proteins are detected among the identified variants from Indian isolates. We quantify mutations by focusing on the unique variants of each SARS-CoV-2 protein. We report the average number of mutation per variant, percentage of mutated positions, synonymous and non-synonymous mutations, mutations occurring in three codon positions and so on. Our study reveals the most susceptible six (06) proteins, which are ORF1ab, Spike (S), Nucleocapsid (N), ORF3a, ORF7a, and ORF8. Several non-synonymous substitutions are observed to be unique in different SARS-CoV-2 proteins. A total of 57 possible deleterious amino acid substitutions are predicted, which may impact on the protein functions. Several mutations show a large decrease in protein stability and are observed in putative functional domains of the proteins that might have some role in disease pathogenesis. We observe a good number of physicochemical property change during above deleterious substitutions.

Exploring the candidates for a new protein folding - cross-α amyloid - in available protein databases

Amyloid fibrils are formed from the assembly of soluble proteins and are responsible for many diseases. They are known to have a cross-β structure, where the fibril runs perpendicular to the β-sheets. A new type of tertiary structure formed by the aggregation of peptides in their α-helical form, in naturally occurring as well as synthetic peptides, termed cross-α amyloid has been reported recently. We have studied the interactions responsible for the formation of these cross-α amyloids and proposed a model to determine the peptides that could form these structures. Eight such peptides obtained using the model have been shown to form a cross-α structure using molecular dynamics simulations. The formation of a cross-α structure from eight copies of a randomly chosen peptide and its stability over a microsecond simulation have been demonstrated. A software named Cross-Alpha-Det has been developed that can determine whether a protein can form a cross-α structure from its secondary structure.

Effect of bacterial nanocellulose binding on the bactericidal activity of bovine lactoferrin

Bovine lactoferrin (bLF) has been extensively described as a wide spectrum antimicrobial protein. bLF bactericidal activity has been mainly attributed to two different mechanisms: environmental iron depletion and cell membrane destabilization. Due to its antimicrobial properties, bLF has been included in the formulation nutraceutical food products and edible active packages. This work comprises the experimental evidence of the requirement of bLF unrestricted mobility ("free bLF") to effectively perform its bactericidal action. To assess the unrestricted and restricted bLF activity, a nontoxic matrix of bacterial nanocellulose (BNC) was used as carrier, and as an anchoring scaffold, respectively. Therefore, BNC was functionalized with bLF through two different methodologies: (i) bLF was embedded within the three-dimensional structure of BNC and; (ii) bLF was covalently bounded to the nanofibrils of BNC. bLF efficiency was tested against two bacteria isolated from clinical specimens, Escherichia coli and Staphylococcus aureus. bLF concentration after covalent binding to BNC was two-fold higher in comparison to the embedding method. Nevertheless, only the embedded bLF exhibited a significant bactericidal activity, due to bLF ability to permeate the BNC matrix and execute its bactericidal action.

Multimodal Role of Amino Acids in Microbial Control and Drug Development

Amino acids are ubiquitous vital biomolecules found in all kinds of living organisms including those in the microbial world. They are utilised as nutrients and control many biological functions in microorganisms such as cell division, cell wall formation, cell growth and metabolism, intermicrobial communication (quorum sensing), and microbial-host interactions. Amino acids in the form of enzymes also play a key role in enabling microbes to resist antimicrobial drugs. Antimicrobial resistance (AMR) and microbial biofilms are posing a great threat to the world's human and animal population and are of prime concern to scientists and medical professionals. Although amino acids play an important role in the development of microbial resistance, they also offer a solution to the very same problem i.e., amino acids have been used to develop antimicrobial peptides as they are highly effective and less prone to microbial resistance. Other important applications of amino acids include their role as anti-biofilm agents, drug excipients, drug solubility enhancers, and drug adjuvants. This review aims to explore the emerging paradigm of amino acids as potential therapeutic moieties.

Network Connectivity, Centrality and Fragmentation in the Greek-Key Protein Topology

Understanding and computationally predicting the protein folding process remains one of the most challenging scientific problems and has uniquely garnered the interdisciplinary efforts of researchers from both the biological, chemical, physical and computational disciplines. Previous studies have demonstrated the importance of long-range interactions in guiding the native structure. However, predicting how the native long-range interaction network forms to generate a specific topology from among all other conformations remains unresolved. The present research study conducts an exploratory study to identify amino acids and long-range interactions that have the potential to play a key role in building and maintaining the protein topology. Towards this end, the application of network science is utilized and developed to analyze the structures of a group of proteins that share a common Greek-key topology but differ in sequence, secondary structure and function. We investigate the idea that the residues with high betweeness centrality score are potentially significant in maintaining the protein network and in governing the Greek-key topology. This hypothesis is tested by two different computational methods: through a fragmentation test and by the analysis of diameter impacts. In summary, we find a subset of selected residues in similar geographical positions in all model proteins, which demonstrates the role of these specific residues and regions in governing the Greek-key topology from a network perspective.

Simulated Epidemics in 3D Protein Structures to Detect Functional Properties

The outcome of an epidemic is closely related to the network of interactions between individuals. Likewise, protein functions depend on the 3D arrangement of their residues and the underlying energetic interaction network. Borrowing ideas from the theoretical framework that has been developed to address the spreading of real diseases, we study for the first time the diffusion of a fictitious epidemic inside the protein nonbonded interaction network, aiming to study network features and properties. Our approach allows us to probe the overall stability and the capability of propagating information in complex 3D structures, proving to be very efficient in addressing different problems, from the assessment of thermal stability to the identification of functional sites.

Structural and conformational changes induced by missense variants in the zinc finger domains of GATA3 involved in breast cancer

Breast cancer (BC) is the main cancer in women having multiple receptor based tumour subtypes. Large scale genome sequencing studies of BC have identified several genes among which GATA3 is reported as a highly mutated gene followed by TP53 and PIK3CA. GATA3 is a crucial transcription factor, and was initially identified as a DNA-binding protein involved in the regulation of immune cell functions. Different missense mutations in the region of the DNA-binding domain of GATA3 are associated with BC and other neoplastic disorders. In this study, computational based approaches have been exploited to reveal associations of various mutations on structure, stability, conformation and function of GATA3. Our findings have suggested that, all analysed missense mutations were deleterious and highly pathogenic in nature. A molecular dynamics simulation study showed that all mutations led to structural destabilisation by reducing protein globularity and flexibility, by altering secondary structural configuration and decreasing protein ligand stability. Essential dynamics analysis indicated that mutations in GATA3 decreased protein mobility and increased its conformational instability. Furthermore, residue network analysis showed that the mutations affected the signal transduction of important residues that potentially influenced GATA3-DNA binding. The present study highlights the importance of different variants of GATA3 which have potential impact on neoplastic progression in breast cancer and may facilitate development of precise and personalized therapeutics.

Mutations in the N- and C-finger domains of GATA3 lead to breast cancer.

Quantitative description and classification of protein structures by a novel robust amino acid network: interaction selective network (ISN)

To quantitatively categorize protein structures, we developed a quantitative coarse-grained model of protein structures with a novel amino acid network, the interaction selective network (ISN), characterized by the links based on interactions in both the main and side chains. We found that the ISN is a novel robust network model to show the higher classification probability in the plots of average vertex degree (k) versus average clustering coefficient (C), both of which are typical network parameters for protein structures, and successfully distinguished between “all-α” and “all-β” proteins. On the other hand, one of the typical conventional networks, the α-carbon network (CAN), was found to be less robust than the ISN, and another typical network, atomic distance network (ADN), failed to distinguish between these two protein structures. Considering that the links in the CAN and ADN are defined by the interactions only between the main chain atoms and by the distance of the closest atom pair between the two amino acid residues, respectively, we can conclude that reflecting structural information from both secondary and tertiary structures in the network parameters improves the quantitative evaluation and robustness in network models, resulting in a quantitative and more robust description of three-dimensional protein structures in the ISN.

Is it possible for short peptide composed of positively- and negatively-charged "hydrophilic" amino acid residue-clusters to form metastable "hydrophobic" packing?

We theoretically and experimentally analyzed a conformational ensemble of a small, characteristic polypeptide consisting of positively- and negatively-charged amino acid residue clusters, (Lys)9(Glu)9(Lys)9, designed based on the supercoiled DNA-recognition (SDR) domain, with the capability of preferentially binding to supercoiled DNA. Advanced molecular dynamics (MD) simulations coupled with a generalized ensemble technique revealed that substantial amounts of ordered, helical structures were present at the boundaries of the Lys and Glu segments in the obtained conformational ensemble. In fact, the helical content of the peptide calculated from our MD simulations was consistent with that estimated from our experimental analysis employing circular dichroism (CD) spectroscopy. The statistical analysis of the structural ensemble revealed the metastable hydrophobic contact clusters, which were stabilized by closely cohesive residue contacts, formed through "hybrid" hydrophobic (methylene groups) and electrostatic (salt bridges) residue contacts. Both short-range and long-range residue contacts were involved in the metastable hydrophobic clusters, constituting the aforementioned local helical conformations and the compact entire structures, respectively. A significant helical propensity was also found in the (Lys)n and (Glu)m boundaries of other conventional protein structures deposited in the Protein Data Bank (PDB), thus indicating the generality of this conformational trend that has been identified herein.

A Protocol To Characterize Peptide-Based Drug Delivery Systems for miRNAs

Micro RNA (miRNA)-based medicines have attracted attention as new therapeutic strategies to treat genetic diseases and metabolic and immunological disorders. MiRNAs have emerged as key mediators of metabolic processes fulfilling regulatory functions in maintaining physiological conditions, while altered miRNA expression profiles are often associated with genetic diseases. However, naked miRNAs exhibit poor enzymatic stability, biomembrane permeation, and cellular uptake. To overcome these limitations, the development of appropriate drug delivery systems (DDS) is necessary. Herein, a DDS is characterized being assembled from miRNA-27a (negative regulator in fat metabolism) and the amphipathic N-TER peptide. Dynamic light scattering (DLS), electrophoretic light scattering, and atomic force microscopy (AFM) are used to investigate physicochemical properties (i.e., size, shape, and charge) of the DDS. Although surface charges should provide decent stabilization, the AFM results confirm a state of agglomeration, which is also suggested by DLS. Furthermore, AFM studies reveal adhesion on hydrophilic as well as hydrophobic substrates, which is related to the amphipathic properties of the N-TER peptide. Physicochemical properties of DDS are important parameters, which have an impact on cell internalization/uptake and have to be taken into account for in vitro studies to develop a successful peptide-based DDS for miRNA replacement therapy in metabolic diseases, such as obesity and others.

Bioinformatics analysis of aflatoxins produced by Aspregillus sp. in basic consumer grain (corn and rice) in Saudi Arabia

The food contaminants by aflatoxins are inevitable even when all precautions and good agricultural practices are applied. Samples of white rice and corn (yellow, red) grains were collected from different local markets and houses. Three Aspergillus flavus strain isolated were identified using molecular characterization of AFLR (aflR) toxin gene. DNA genome of the three A. flavus isolates (namely A. flavus _ YC; A. flavus _ RC; A. flavus _ Rice) which corresponds to isolates from, yellow corn, red corn and white rice respectively were used as a template for PCR to amplify Aspergillus flavus AFLR (aflR) toxin gene. Partially sequenced was amplified using a specific primer set to confirm its identity, phylogenetic relationships between the three isolates as well as determination of the corresponding antigenic determinants. The epitope prediction analysis demonstrated that there were 1, 2, 3 and 4 epitopes whose score were equal 1 in A. flavus _ YC; A. flavus _ RC; A. flavus _ Rice, respectively. Interestingly, there were great dissimilarity in the epitope sequences among the three isolates except in RLQEGGDDAAGIPA, SPPPPVETQGLGGD, RPSESLPSARSEQG and PAHNTYSTPHAHTQ were found to be similar between all isolates. This work articulates that the molecular identification and characterization of three A. flavus using Aspergillus flavus AFLR (aflR) toxin gene and the unique antigenic determinants that could be used for design of a broad-spectrum antibody for rapid detection of A. flavus in foods and support quality system of food safety.

Anti-cancer effect of GV1001 for prostate cancer: function as a ligand of GnRHR

GV1001, a 16-amino acid fragment of the human telomerase reverse transcriptase catalytic subunit (hTERT), has been developed as an injectable formulation of cancer vaccine. Here, we revealed for the first time that GV1001 is a novel ligand for gonadotropin-releasing hormone receptor (GnRHR). The docking prediction for GV1001 against GnRHR showed high binding affinity. Binding of GV1001 to GnRHR stimulated the Gαs-coupled cAMP signaling pathway and antagonized Gαq-coupled Ca2+ release by leuprolide acetate (LA), a GnRHR agonist. Repeated injection of GV1001 attenuated both serum testosterone level and seminal vesicle weight via desensitization of hypothalamic-pituitary-gonadal (HPG) axis. We then tested whether GV1001 has an inhibitory effect on tumor growth of LNCaP cells, androgen receptor-positive human prostate cancer (PCa) cells. GV1001 significantly inhibited tumor growth and induced apoptosis in LNCaP-implanted xenografts. Interestingly, mRNA expressions of matrix metalloproteinase 2 and matrix metalloproteinase 9 were suppressed by GV1001, but not by LA. Moreover, GV1001 significantly inhibited the proliferation and migration of PCa cells and induced apoptosis in a concentration-dependent manner. Our findings suggest that GV1001 functions as a biased GnRHR ligand to selectively stimulate the Gαs/cAMP pathway, with anti-proliferative and anti-migratory effects on human PCa.

Identification of Residues in Lassa Virus Glycoprotein Subunit 2 That Are Critical for Protein Function

Lassa virus (LASV) is an Old World arenavirus, endemic to West Africa, capable of causing hemorrhagic fever. Currently, there are no approved vaccines or effective antivirals for LASV. However, thorough understanding of the LASV glycoprotein and entry into host cells could accelerate therapeutic design. LASV entry is a two-step process involving the viral glycoprotein (GP). First, the GP subunit 1 (GP1) binds to the cell surface receptor and the viral particle is engulfed into an endosome. Next, the drop in pH triggers GP rearrangements, which ultimately leads to the GP subunit 2 (GP2) forming a six-helix-bundle (6HB). The process of GP2 forming 6HB fuses the lysosomal membrane with the LASV envelope, allowing the LASV genome to enter the host cell. The aim of this study was to identify residues in GP2 that are crucial for LASV entry. To achieve this, we performed alanine scanning mutagenesis on GP2 residues. We tested these mutant GPs for efficient GP1-GP2 cleavage, cell-to-cell membrane fusion, and transduction into cells expressing α-dystroglycan and secondary LASV receptors. In total, we identified seven GP2 mutants that were cleaved efficiently but were unable to effectively transduce cells: GP-L280A, GP-L285A/I286A, GP-I323A, GP-L394A, GP-I403A, GP-L415A, and GP-R422A. Therefore, the data suggest these residues are critical for GP2 function in LASV entry.

Understanding contact patterns of protein structures from protein contact map and investigation of unique patterns in the globin-like folded domains

Proteins are biochemical compounds made up of one or more polypeptides in a specific order, typically folded into a functionally active form. Proteins are categorized into four different structural classes according to the topology of α-helices and β-strands. In this study, we modeled these four structural classes as an undirected network depicting amino acids as nodes and interaction between them as edges. Results infer that basic protein classes can be easily recognized as well as distinguished by utilizing protein contact maps (PCM). Toward studying the globin-like fold, the helix-loop-helix region contacts were seen to be of a unique pattern, and these remained in all the folds. Further, the averaged diagonal contacts were analyzed and identified those contacts in α/β proteins were higher in comparison with the other class. Interesting, we noticed that anti-parallel beta sheets were dominant in all-β and α + β classes that lead to similar diagonal patterns. Network properties of all four basic classes were analyzed and found to possess small-world property. Findings infer that PCM may assist classify protein structure classes and it also helps in evaluating the predicted protein structures.

Poly(N-isopropylacrylamide-co-2-((diethylamino)methyl)-4-formyl-6-methoxyphenyl acrylate) Environmental Functional Copolymers: Synthesis, Characterizations, and Grafting with Amino Acids

Vanillin was used to synthesize a new derivative with an active aldehyde group and response to pH. It is named 2-((diethylamino) methyl)-4-formyl-6-methoxyphenyl acrylate, abbreviated to DEAMVA. The chemical structures were evaluated by ¹H, 13C nuclear magnetic resonance (NMR), infrared (IR), and UV-Vis-spectroscopy, and all results demonstrated good statement. In order to achieve the dual responsive behavior thermo-pH with functionality, free radical polymerization of N-isopropylacrylamide with DEAMVA in different molar ratios (5, 10, 15 mol%) has been used, with azobisisobutyronitrile (AIBN) as the initiator. The chemical structure of the polymers was investigated by ¹H NMR and IR. The dual responsive functional copolymer was exposed to a grafted process with tryptophan and tyrosine, both of which were also evaluated by ¹HNMR and IR. Copolymers before and after grafting were physically investigated by size exclusion chromatography (SEC) for estimation of the molecular weight, the glass transition temperature by differential scanning calorimeter (DSC) and scanning electron microscope (SEM) for the surface morphology. The phase separation or lower critical solution temperature (LCST) (Tc) of the polymer solution was determined not only by a turbidity method using the change in the transmittance with temperature, but also by micro-DSC. The conversion to an amino acid-grafted polymer was detected through Beer's law for the absorption of the ⁻CH=N- imine group by UV-Vis-Spectroscopy.

Identification and Analysis of OVATE Family Members from Genome of the Early Land Plants Provide Insights into Evolutionary History of OFP Family and Function

Mosses, liverworts, hornworts and lycophytes represent transition stages between the aquatic to terrestrial/land plants. Several morphological and adaptive novelties driven by genomic components including emergence and expansion of new or existing gene families have played a critical role during and after the transition, and contributed towards successful colonization of terrestrial ecosystems. It is crucial to decipher the evolutionary transitions and natural selection on the gene structure and function to understand the emergence of phenotypic and adaptive diversity. Plants at the "transition zone", between aquatic and terrestrial ecosystem, are also the most vulnerable because of climate change and may contain clues for successful mitigation of the challenges of climate change. Identification and comparative analyses of such genetic elements and gene families are few in mosses, liverworts, hornworts and lycophytes. Ovate family proteins (OFPs) are plant-specific transcriptional repressors and are acknowledged for their roles in important growth and developmental processes in land plants, and information about the functional aspects of OFPs in early land plants is fragmentary. As a first step towards addressing this gap, a comprehensive in silico analysis was carried out utilizing publicly available genome sequences of Marchantia polymorpha (Mp), Physcomitrella patens (Pp), Selaginella moellendorffii (Sm) and Sphagnum fallax (Sf). Our analysis led to the identification of 4 MpOFPs, 19 PpOFPs, 6 SmOFPs and 3 SfOFPs. Cross-genera analysis revealed a drastic change in the structure and physiochemical properties in OFPs suggesting functional diversification and genomic plasticity during the evolutionary course. Knowledge gained from this comparative analysis will form the framework towards deciphering and dissection of their developmental and adaptive role/s in early land plants and could provide insights into evolutionary strategies adapted by land plants.

Node-Weighted Amino Acid Network Strategy for Characterization and Identification of Protein Functional Residues

The study of functional residues (FRs) is essential for understanding protein functions and biological processes. The amino acid network (AAN) has become an emerging paradigm for studying FRs during the past decade. Current AAN models ignore the heterogeneity of nodes and treat amino acids in the AAN as the same. However, the properties of each amino acid node are of fundamental importance. We here proposed a node-weighted AAN strategy termed the node-weighted amino acid contact energy network (NACEN) to characterize and predict three types of FRs, namely, hot spots, catalytic residues, and allosteric residues. We first constructed NACENs with their nodes weighted based on structural, sequence, physicochemical, and dynamical properties of the amino acids and then characterized the FRs with the NACEN parameters. We finally built machine learning predictors to identify each type of FR. The results revealed that residues characterized with NACEN parameters are more distinguishable between FRs and non-FRs than those with unweighted network ones. With few features for classification, NACEN yields comparable performance for FR identification and provides residue level prediction for allosteric regulation. The proposed strategy can be easily implemented to other functional residue identification. An R package is also provided for NACEN construction and analysis at http://sysbio.suda.edu.cn/NACEN/index.html .

Mutations close to a hub residue affect the distant active site of a GH1 β-glucosidase

The tertiary structure of proteins has been represented as a network, in which residues are nodes and their contacts are edges. Protein structure networks contain residues, called hubs or central, which are essential to form short connection pathways between any pair of nodes. Hence hub residues may effectively spread structural perturbations through the protein. To test whether modifications nearby to hub residues could affect the enzyme active site, mutations were introduced in the β-glycosidase Sfβgly (PDB-ID: 5CG0) directed to residues that form an α-helix (260–265) and a β-strand (335–337) close to one of its main hub residues, F251, which is approximately 14 Å from the Sfβgly active site. Replacement of residues A263 and A264, which side-chains project from the α-helix towards F251, decreased the rate of substrate hydrolysis. Mutation A263F was shown to weaken noncovalent interactions involved in transition state stabilization within the Sfβgly active site. Mutations placed on the opposite side of the same α-helix did not show these effects. Consistently, replacement of V336, which side-chain protrudes from a β-strand face towards F251, inactivated Sfβgly. Next to V336, mutation S337F also caused a decrease in noncovalent interactions involved in transition state stabilization. Therefore, we suggest that mutations A263F, A264F, V336F and S337F may directly perturb the position of the hub F251, which could propagate these perturbations into the Sfβgly active site through short connection pathways along the protein network.

Genetic stability of foot-and-mouth disease virus during long-term infections in natural hosts

Foot-and-mouth disease (FMD) is a severe infection caused by a picornavirus that affects livestock and wildlife. Persistence in ruminants is a well-documented feature of Foot-and-mouth disease virus (FMDV) pathogenesis and a major concern for disease control. Persistently infected animals harbor virus for extended periods, providing a unique opportunity to study within-host virus evolution. This study investigated the genetic dynamics of FMDV during persistent infections of naturally infected Asian buffalo. Using next-generation sequencing (NGS) we obtained 21 near complete FMDV genome sequences from 12 sub-clinically infected buffalo over a period of one year. Four animals yielded only one virus isolate and one yielded two isolates of different serotype suggesting a serial infection. Seven persistently infected animals yielded more than one virus of the same serotype showing a long-term intra-host viral genetic divergence at the consensus level of less than 2.5%. Quasi-species analysis showed few nucleotide variants and non-synonymous substitutions of progeny virus despite intra-host persistence of up to 152 days. Phylogenetic analyses of serotype Asia-1 VP1 sequences clustered all viruses from persistent animals with Group VII viruses circulating in Pakistan in 2011, but distinct from those circulating on 2008–2009. Furthermore, signature amino acid (aa) substitutions were found in the antigenically relevant VP1 of persistent viruses compared with viruses from 2008–2009. Intra-host purifying selective pressure was observed, with few codons in structural proteins undergoing positive selection. However, FMD persistent viruses did not show a clear pattern of antigenic selection. Our findings provide insight into the evolutionary dynamics of FMDV populations within naturally occurring subclinical and persistent infections that may have implications to vaccination strategies in the region.

SubVis: an interactive R package for exploring the effects of multiple substitution matrices on pairwise sequence alignment

Understanding how proteins mutate is critical to solving a host of biological problems. Mutations occur when an amino acid is substituted for another in a protein sequence. The set of likelihoods for amino acid substitutions is stored in a matrix and input to alignment algorithms. The quality of the resulting alignment is used to assess the similarity of two or more sequences and can vary according to assumptions modeled by the substitution matrix. Substitution strategies with minor parameter variations are often grouped together in families. For example, the BLOSUM and PAM matrix families are commonly used because they provide a standard, predefined way of modeling substitutions. However, researchers often do not know if a given matrix family or any individual matrix within a family is the most suitable. Furthermore, predefined matrix families may inaccurately reflect a particular hypothesis that a researcher wishes to model or otherwise result in unsatisfactory alignments. In these cases, the ability to compare the effects of one or more custom matrices may be needed. This laborious process is often performed manually because the ability to simultaneously load multiple matrices and then compare their effects on alignments is not readily available in current software tools. This paper presents SubVis, an interactive R package for loading and applying multiple substitution matrices to pairwise alignments. Users can simultaneously explore alignments resulting from multiple predefined and custom substitution matrices. SubVis utilizes several of the alignment functions found in R, a common language among protein scientists. Functions are tied together with the Shiny platform which allows the modification of input parameters. Information regarding alignment quality and individual amino acid substitutions is displayed with the JavaScript language which provides interactive visualizations for revealing both high-level and low-level alignment information.

Transiently disordered tails accelerate folding of globular proteins

Numerous biological proteins exhibit intrinsic disorder at their termini, which are associated with multifarious functional roles. Here, we show the surprising result that an increased percentage of terminal short transiently disordered regions with enhanced flexibility (TstDREF) is associated with accelerated folding rates of globular proteins. Evolutionary conservation of predicted disorder at TstDREFs and drastic alteration of folding rates upon point-mutations suggest critical regulatory role(s) of TstDREFs in shaping the folding kinetics. TstDREFs are associated with long-range intramolecular interactions and the percentage of native secondary structural elements physically contacted by TstDREFs exhibit another surprising positive correlation with folding kinetics. These results allow us to infer probable molecular mechanisms behind the TstDREF-mediated regulation of folding kinetics that challenge protein biochemists to assess by direct experimental testing.

In silico analysis of Shiga toxins (Stxs) to identify new potential vaccine targets for Shiga toxin-producing Escherichia coli

Shiga toxins belong to a family of structurally and functionally related toxins serving as the main virulence factors for pathogenicity of the Shiga toxin-producing Escherichia coli (STEC) associating with Hemolytic uremic syndrome (HUS). At present, there is no effective treatment or prevention for HUS. The aim of the present study was to find conserved regions within the amino acid sequences of Stx1, Stx2 (Shiga toxin) and their variants. In this regard, In-silico identification of conformational continuous B cell and T-cell epitopes was performed in order to introduce new potential vaccine candidates. 93-100% Homology was observed in Stx1 and its variants. In Stx2 and its variants, 69-100% homology was shown. By sequence alignment with Stx1 and Stx2, 54% homology was detected. T-cell epitope identification in Stx1A and Stx2A epitopes with highest binding affinity for each HLA (human leukocyte antigen) was demonstrated with 100% identity among all Stxs. B-cell epitope prediction was resulted in finding of four common epitopes between Stxs. In silico analysis of Stxs was resulted to identification of new peptide targets that could be used in development of new epitope vaccine candidates or in immunodiagnostic tests.

Modular Organization of Residue-Level Contacts Shapes the Selection Pressure on Individual Amino Acid Sites of Ribosomal Proteins

Understanding the molecular evolution of macromolecular complexes in the light of their structure, assembly, and stability is of central importance. Here, we address how the modular organization of native molecular contacts shapes the selection pressure on individual residue sites of ribosomal complexes. The bacterial ribosomal complex is represented as a residue contact network where nodes represent amino acid/nucleotide residues and edges represent their van der Waals interactions. We find statistically overrepresented native amino acid-nucleotide contacts (OaantC, one amino acid contacts one or multiple nucleotides, internucleotide contacts are disregarded). Contact number is defined as the number of nucleotides contacted. Involvement of individual amino acids in OaantCs with smaller contact numbers is more random, whereas only a few amino acids significantly contribute to OaantCs with higher contact numbers. An investigation of structure, stability, and assembly of bacterial ribosome depicts the involvement of these OaantCs in diverse biophysical interactions stabilizing the complex, including high-affinity protein-RNA contacts, interprotein cooperativity, intersubunit bridge, packing of multiple ribosomal RNA domains, etc. Amino acid-nucleotide constituents of OaantCs with higher contact numbers are generally associated with significantly slower substitution rates compared with that of OaantCs with smaller contact numbers. This evolutionary rate heterogeneity emerges from the strong purifying selection pressure that conserves the respective amino acid physicochemical properties relevant to the stabilizing interaction with OaantC nucleotides. An analysis of relative molecular orientations of OaantC residues and their interaction energetics provides the biophysical ground of purifying selection conserving OaantC amino acid physicochemical properties.