Amino Acid Residues In Proteins Research Articles

Mass Spectrometry-Based Platforms for Protein Lipoxidation Profiling.

Lipid peroxidation, occurring through enzymatic or non-enzymatic processes, generates lipid-derived electrophiles (LDEs), which can covalently modify nucleophilic amino acid residues in proteins, a process known as protein lipoxidation. This modification can alter protein structure and function, either causing damage or regulating signalling pathways. Identifying the protein targets and specific lipoxidation sites provide important clues for unveiling the oxidative stress-related protein interaction network and molecular mechanisms of related diseases. In this review, we present a detailed overview of recent advances in protein LDE modification profiling, with a focus on mass spectrometry (MS)-based chemoproteomic platforms for global protein lipoxidation profiling.

Two amino acid pairs in the Gc Glycoprotein of Severe Fever with Thrombocytopenia Syndrome Virus responsible for the enhanced virulence

Severe fever with thrombocytopenia syndrome (SFTS) is a significant public health concern, with a high fatality rate in humans and cats. In this study, we explored the genetic determinants that contribute to the different virulence of SFTS virus (SFTSV) based on Tk-F123 and Ng-F264 strains isolated from cats. Tk-F123 was 100% lethal in type I interferon receptor-knockout mice, whereas Ng-F264 exhibited no fatality. We identified a pair of amino acid residues in the Gc protein, glycine and serine, at residues 581 and 934, respectively, derived from Tk-F123, leading to a fatal infection. Those in Ng-F264 were arginine and asparagine. These results suggest that this pair of residues affects the Gc protein function and regulates SFTSV virulence. Our findings provide useful clues for the elucidation of viral pathogenicity and the development of effective live-attenuated vaccines and antiviral strategies.

Comparative Study of Docking Tools for Evaluation of Potential Copper Metallodrugs and Their Interaction with TMPRSS2

COVID-19 has caused over seven million deaths globally due to its high transmission rate. The virus responsible for the disease requires a transmembrane protease serine type II (TMPRSS2-7MEQ) to infiltrate host cells and has been linked to several cancers, particularly prostate cancer. To investigate COVID-19 potential therapies, a series of Casiopeina-like copper complexes containing 1,10-Phenanthroline and amino acids were investigated as TMPRSS2 inhibitors. The molecular structures of twelve Phenanthroline copper complexes were calculated, and their global reactivity indices were analyzed using DFT and conceptual DFT methods. Three molecular docking algorithms were employed to identify the most effective inhibitors by examining their interactions with amino acid residues in the target protein’s catalytic activity triad (Asp345, His296, and Ser441). All complexes are docked above the catalytic site, blocking the interaction with substrates. The Phenanthroline complexes showed better interactions than the Bipyridine complexes, likely due to increased hydrophobic contacts. Analogs’ cationic nature and amino acids’ basic side chains bring them near the active site by interacting with Asp435. The top complexes in this study contain Ornithine, Lysine, and Arginine, making them promising alternatives for researching new drugs for COVID-19 and cancers like prostate cancer.

Determining structural sites of the IGPD protein family from patterns in property based correlation matrices

Abstract We use the statistical approach of random matrix and network theory to tackle the problem of identifying the important motifs responsible for the crucial functioning of the IGPD protein family. This addresses directly the question of patterns of interaction between amino acid residues (based on properties) in proteins that contribute to protein function. We use the mathematical tools of inverse participation ratio and Shannon entropy to determine the locations of the important groups of correlated amino acid positions which gives us the structural sites of the IGPD protein. These tools isolate the smallest eigenvalues/outliers corresponding to eigenmodes as the most localized which give the crucial sites for the family. We also create the threshold network of the IGPD protein and find that at certain threshold, similar sites emerge from the network analysis which in addition gives us the strongest connected sites. This strengthens our method of finding the structural and functional sites. As a bonus we find these important sites also match with experiments.

Modeling Of the Structure of the tRolC Protein of Nicotiana tabacum and Its Functional Relation to Other Proteins

The trolC gene is a homologue of the rolC oncogene of Agrobacterium rhizogenes and most likely got into Nicotiana tabacum genome during horizontal gene transfer. This gene is quite conserved and is expressed in young organs, but its functions, like the agrobacterium rolC gene, remain unknown. The putative structure of the tRolC protein of Nicotiana tabacum, predicted using the I-TASSER service, was analyzed in the study. The presence of amino acid residues in the tRolC protein of the active center and binding site, as well as a protein-binding and ARTT loop, similar in structure to protein 6b of Agrobacterium vitis, indicates that they perform similar biological functions. Based on the data, a hypothesis was put forward about the presence of ADP-ribosyltransferase activity in the tRolC protein, which allows it to influence the growth and stress tolerance, as well as the biosynthesis of secondary metabolites by influencing the regulation of gene expression through interaction with transcription factors, RNA interference, or the manifestation of histone-like activity.

Preparation and characterization of novel antioxidant peptides from protein hydrolysate of Ophiocordyceps gracilis

Ophiocordyceps gracilis is a type of fungus commonly utilized in both health food and Chinese medicine. Herein, we prepared antioxidant hydrolysate from O. gracilis, and isolated and purified the prepared hydrolysate to obtain O. gracilis peptides-4–3–1 (OGP-4–3–1) grade with the highest scavenging activity on DPPH, ABTS and hydroxyl radicals. Three new peptides with high antioxidant capacity were identified as LFNHF, PLDRHPF and YPFLRPL, respectively. The three peptides can reduce the proportion of senescent cells conveying positive expression of senescence-associated-β-galactosidase (SA-β-Gal) and increase survival pace of H2O2-induced human hepatocellular carcinomas (HepG2 cells), and the protective effects on cellular against senescence might be related to their increase in the activities of antioxidant enzymes, as well as the decrease in the concentration of malondialdehyde (MDA) and reactive oxygen species (ROS). The molecular docking results indicated that they could form durable hydrophobic and hydrogen bonds with critical amino acid residues of the Kelch-like ECH-associated protein 1 (Keap1), which could potentially modulate pathway of nuclear factor erythroid 2-related factor 2 (Nrf2) in conjunction with Keap1. In conclusion, the current research offers a theoretical foundation for the further development of the anti-aging effect of OGP, which has a broad application prospect in the fields of functional food and cosmetics.

Molecular genotyping and subgenotyping of duck circovirus at duck farms in Thailand.

Ducks worldwide are infected with duck circovirus (DuCV), which causes feather abnormality, emaciation, and poor growth performance. DuCV is similar to other circoviruses that induce immunosuppression due to the occurrence of the bursae of Fabricius (BF) and spleen atrophies. In Thailand, retarded ducks with feather losses were submitted for disease investigation. The ducks presented low body weight gain, had small BF and spleens, and were consistent with duck-infected DuCV. Our study investigated the possibility of DuCV infection in duck flocks in Thailand. We also analyzed the genetic characteristics of the virus. BF and spleen samples were collected from affected meat and layer ducks from six farms thought to have been infected with DuCV. These tissues were then subjected to histopathological examination and molecular identification using conventional polymerase chain reaction and nucleotide sequencing. To identify DuCV, phylogenetic trees were generated using MEGA version X software. Samples of tissues or swabs were collected to determine whether coinfections with bacteria and viruses existed. Phylogenetic analysis using the entire genome (1995-1996 bp) and cap gene (762 bp) revealed that the DuCV isolates circulating in Thailand belonged to DuCV genotype I, which was further subdivided into two sub-genotypes: sub-genotype I b and an unclassified sub-genotype based on reference sub-genotypes. Thai isolates have variations in 10 amino acid residues in the capsid protein. Ducks infected with Thai DuCV were also coinfected with Riemerella anatipestifer, Escherichia coli, Pasteurella multocida, duck viral enteritis, and duck Tembusu virus, which is consistent with previous DuCV infection studies. Six DuCVs from ducks who were previously found to have feather loss, were underweight, had growth retardation, and had poor body condition were identified in this study as belonging to genotype I and constituting at least two sub-genotypes. Due to the immunosuppressive effects of DuCV, coinfection of bacterial and viral pathogens was typically observed in Thai DuCV-infected ducks.

Unveiling crucial amino acid residues in the red clover necrotic mosaic virus movement protein for dynamic subcellular localization and viral cell-to-cell movement

Emerging evidence suggests that the localization of viral movement proteins (MPs) to both plasmodesmata (PD) and viral replication complexes (VRCs) is the key to viral cell-to-cell movement. However, the molecular mechanism that establishes the subcellular localization of MPs is not fully understood. Here, we investigated the PD localization pathway of red clover necrotic mosaic virus (RCNMV) MP and the functional regions of MP that are crucial for MP localization to PD and VRCs. Disruption analysis of the transport pathway suggested that RCNMV MP does not rely on the ER-Golgi pathway or the cytoskeleton for the localization to the PD. Furthermore, mutagenesis analysis identified amino acid residues within the alpha helix regions responsible for localization to the PD or VRCs. These α-helix regions were also essential for efficient viral cell-to-cell movement, highlighting the importance of these dynamic localization of the MPs for viral infection.

Whole-genome sequence analysis of canine parvovirus reveals replacement with a novel CPV-2c strain throughout India.

Canine parvovirus (CPV) infection causes severe gastroenteritis in canines, with high mortality in puppies. This virus evolved from feline panleukopenia virus by altering its transferrin receptor (TfR), followed by the emergence of CPV-2 variants in subsequent years with altered immunodominant amino acid residues in the VP2 protein. While previous studies have focused on the VP2 gene, there have been fewer studies on non-structural protein (NS1 and NS2) genes. In the present study, CPV genome sequences from clinical samples collected from canines throughout India in 2023, previous Indian CPV isolates from 2009-2019, and the current Indian CPV vaccine strain were compared. The study showed that the CPV-2c (N426E) variant had almost completely replaced the previously dominant CPV-2a variant (N426) in India. The Q370R mutation of VP2 was the most common change in the recent CPV-2c strain (CPV-2c 370Arg variant). Phylogenetic analysis showed the existence of three clades among the recent CPV-2c strains, and sequence analysis identified several new sites of positive selection in the VP1 (N-terminus), VP2, NS1, and NS2 protein-encoding genes in recent CPV strains, indicating the emergence of new CPV-2c variants with varied antigenic and replication properties. The predominant 'CPV-2c 370Arg variants' were grouped with the Chinese and Nigerian CPV-2c strains but were separate from the CPV vaccine strain and earlier isolates from our repository. VP2 epitope analysis predicted nine amino acid variations (including two new variations) in four potential linear B-cell epitopes in the CPV-2c 370Arg variants that might make vaccine failure more likely. This pan-Indian study lays the foundation for further research concerning the dynamics of virus evolution and understanding genetic mutations.

Computational investigation of novel synthetic analogs of C-1′β substituted remdesivir against RNA-dependent RNA-polymerase of SARS-CoV-2

Remdesivir, a C-nucleotide prodrug binds to the viral RNA-dependent-RNA polymerase (RdRp) and inhibits the viral replication by terminating RNA transcription prematurely. It is reported in literature that interaction between the C-1’β–CN moiety of Remdesivir (RDV) and the Ser861 residue in RdRp enzyme, causes a delayed chain termination during the RNA replication process and is one of the important aspect of its mechanism of action. In the pursuance of increasing the biological activity of RDV and enhancing the SAR studies, against RNA viruses, we have designed its fourteen C1’β substituted analogs, 10 –23 bearing 4/5-membered heterocyclic rings. The docking and 100 ns molecular dynamics (MD) simulations of 10-23 to the RdRp protein (PDB ID: 7L1F) revealed important interactions between 2’,3’-diol, oxo group of phosphoramidate, nitrogen residues of heterocyclic rings of synthetic molecules with Arg555, Arg553, Ser759, Cys622, Asn691, Asp623 amino acid residues of protein. The docking score of 2-ethylbutyl ((S)-(((2R,3S,4R,5R)-5-(4-aminopyrrolo[2,1-f][1,2,4]triazin-7-yl)-3,4-dihydroxy-5-(1H-1,2,3-triazol-4-yl)tetrahydrofuran-2-yl)methoxy)(phenoxy)phosphoryl)-L-alaninate, 11 was found to be the higher than RDV among 14 new compounds i.e. -5.20 kcal/mol. Out of 3 compounds, 10, 12 and 13 submitted for MD simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis, trifluoro-oxadiazole derivative, 13 showed higher binding energy as compared to Remdesivir. The predicted ADMET properties of 14 compounds showed their potential for being drug candidates. The present study suggests that substitution at the C1’β position by 4/5-membered rings plays an important role in the interactions between nucleoside/tide and target protein.

Non-Medical Applications of Inorganic Medicines. A Switch Based on Mechanistic Knowledge.

Metals have been used in medicine for centuries. However, it was not until much later that the effects of inorganic drugs could be rationalized from a mechanistic point of view. Today, thanks to the technologies available, this approach has been functionally developed and implemented. It has been found that there is probably no single biological target for the pharmacological effects of most inorganic drugs. Herein, we present an overview of some integrated and multi-technique approaches to elucidate the molecular interactions underlying the biological effects of metallodrugs. On this premise, selected examples are used to illustrate how the information obtained on metal-based drugs and their respective mechanisms can become relevant for applications in fields other than medicine. For example, some well-known metallodrugs, which have been shown to bind specific amino acid residues of proteins, can be used to solve problems related to protein structure elucidation in crystallographic studies. Diruthenium tetraacetate can be used to catalyze the conversion of hydroxylamines to nitrones with a high selectivity when bound to lysozyme. Finally, a case study is presented in which an unprecedented palladium/arsenic-mediated catalytic cycle for nitrile hydration was discovered thanks to previous studies on the solution chemistry of the anticancer compound arsenoplatin-1 (AP-1).

Computational Design of a Novel Inhibitor Against COVID

Background: In recent years, in silico computational approaches have tremendously guided computational medicinal chemists and research scientists to analyze protein structures, kinetics, functions, and molecular interactions of the administered drugs. Objective: This study aimed to identify a novel inhibitor against SARS-CoV-2 using human CD26 and modeled spike protein through suitable in silico approaches. Methods: In this work, molecular docking and molecular dynamics simulation experiments were conducted to gain insights into the binding affinity and stability, respectively. The docked complex of CD26 with modeled spike protein showed higher binding affinity than the complex of CD26 with resolved spike protein due to the existence of strong interactions with the crucial amino acid residues of the target proteins. Results: The results of the molecular dynamics simulation demonstrated that CD26 with the modeled spike protein docked complex showed good stability when compared with the resolved protein. Conclusion: From this computational finding, it was also suggested that the structure was stable and would rapidly guide the discovery of potential inhibitors against COVID-19.

Proton Transfer Kinetics in Histidine Side Chains Determined by pH-Dependent Multi-Nuclear NMR Relaxation.

Histidine is a key amino-acid residue in proteins with unique properties engendered by its imidazole side chain that can exist in three different states: two different neutral tautomeric forms and a protonated, positively charged one with a pKa value close to physiological pH. Commonly, two or all three states coexist and interchange rapidly, enabling histidine to act as both donor and acceptor of hydrogen bonds, coordinate metal ions, and engage in acid/base catalysis. Understanding the exchange dynamics among the three states is critical for assessing histidine's mechanistic role in catalysis, where the rate of proton exchange and interconversion among tautomers might be rate limiting for turnover. Here, we determine the exchange kinetics of histidine residues with pKa values representative of the accessible range from 5 to 9 by measuring pH-dependent 15N, 13C, and 1H transverse relaxation rate constants for 5 nuclei in each imidazole. Proton exchange between the imidazole and the solvent is mediated by hydronium ions at acidic and neutral pH, whereas hydroxide mediated exchange becomes the dominant mechanism at basic pH. Proton transfer is very fast and reaches the diffusion limit for pKa values near neutral pH. We identify a direct pathway between the two tautomeric forms, likely mediated by a bridging water molecule or, in the case of high pH, hydroxide ion. For histidines with pKa 7, we determine all rate constants (lifetimes) involving protonation over the entire pH range. Our approach should enable critical insights into enzymatic acid/base catalyzed reactions involving histidines in proteins.

Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Its Variants Omicron, BA.5, EG.5, and JN.1 for Viral Infectivity, Virulence and Immune Escape.

Semi-covariance has attracted significant attention in recent years and is increasingly employed to elucidate statistical phenomena exhibiting fluctuations, such as the similarity or difference in charge patterns of spike proteins among coronaviruses. In this study, by examining values above and below the average/mean based on the positive and negative charge patterns of amino acid residues in the spike proteins of SARS-CoV-2 and its current circulating variants, the proposed methods offer profound insights into the nonlinear evolving trends in those viral spike proteins. Our study indicates that the charge span value can predict the infectivity of the virus and the charge density can estimate the virulence of the virus, and both predicated infectivity and virulence appear to be associated with the capability of viral immune escape. This semi-covariance coefficient analysis may be used not only to predict the infectivity, virulence and capability of immune escape for coronaviruses but also to analyze the functionality of other viral proteins. This study improves our understanding of the trend of viral evolution in terms of viral infectivity, virulence or the capability of immune escape, which remains further validated by more future studies and statistical data.

HLA Mismatches Identified by a Novel Algorithm Predict Risk of Antibody-mediated Rejection From De Novo Donor-specific Antibodies.

The development of de novo donor-specific antibodies (dnDSA) and antibody-mediated rejection (AMR) remains a barrier to long-term graft and patient survival. Most dnDSA are directed against mismatched donor HLA-DQ antigens. Here, we describe a novel algorithm, which we have termed categorical amino acid mismatched epitope, to evaluate HLA-DQ mismatches. In this algorithm, amino acid residues of HLA-DQ protein were categorized into 4 groups based on their chemical characteristics. The likelihood of categorically mismatched peptides presented by the recipient's HLA-DRB1 was expressed as a normalized value, %Rank score. Categorical HLA-DQ mismatches were analyzed in 386 heart transplant recipients who were mismatched with their donors at the HLA-DQB1 locus. We found that the presence of DQB1 mismatches with %Rank score ≤1 was associated with the development of dnDSA (P = 0.002). Furthermore, dnDSA increased the risk of AMR only in recipients who had DQ mismatches with %Rank score ≤1 (hazard ratio = 5.8), but the freedom from AMR was comparable between recipients with dnDSA and those without dnDSA if %Rank scores of DQ mismatching were >1. These results suggest that HLA-DQ mismatches evaluated by the categorical amino acid mismatched epitope algorithm can stratify the risk of development of dnDSA and AMR in heart transplant recipients.

2'-O-Alkyl-N 3-Methyluridine Functionalized Passenger Strand Improves RNAi Activity by Modulating the Thermal Stability.

Herein, we have demonstrated that the siRNA activity could be enhanced by incorporating the guide strand in the RISC complex through thermodynamic asymmetry caused by m3U-based destabilizing modifications. A nuclease stability study revealed that 2'-OMe-m3U and 2'-OEt-m3U modifications slightly improved the half-lives of siRNA strands in human serum. In the in vitro gene silencing assay, 2'-OMe-m3U modification at the 3'-overhang and cleavage site of the passenger strand in anti-renilla and anti-Bcl-2 siRNA duplexes were well-tolerated and exhibited improved gene silencing activity. However, gene silencing activity was attenuated when these modifications were incorporated at position 3 in the seed region of the antisense strand. The molecular modeling studies using these modifications at the seed region with the MID domain of hAGO2 explained that the 2'-alkoxy group makes steric interactions with the amino acid residues of the hAGO2 protein.

Data-driven probabilistic definition of the low energy conformational states of protein residues.

Protein dynamics and related conformational changes are essential for their function but difficult to characterise and interpret. Amino acids in a protein behave according to their local energy landscape, which is determined by their local structural context and environmental conditions. The lowest energy state for a given residue can correspond to sharply defined conformations, e.g.in a stable helix, or can cover a wide range of conformations, e.g.in intrinsically disordered regions. A good definition of such low energy states is therefore important to describe the behaviour of a residue and how it changes with its environment. We propose a data-driven probabilistic definition of six low energy conformational states typically accessible for amino acid residues in proteins. This definition is based on solution NMR information of 1322 proteins through a combined analysis of structure ensembles with interpreted chemical shifts. We further introduce a conformational state variability parameter that captures, based on an ensemble of protein structures from molecular dynamics or other methods, how often a residue moves between these conformational states. The approach enables a different perspective on the local conformational behaviour of proteins that is complementary to their static interpretation from single structure models.

Protein-Chlorogenic Acid Interactions: Mechanisms, Characteristics, and Potential Food Applications.

The interactions between proteins and chlorogenic acid (CGA) have gained significant attention in recent years, not only as a promising approach to modify the structural and techno-functional properties of proteins but also to enhance their bioactive potential in food systems. These interactions can be divided into covalent (chemical or irreversible) and non-covalent (physical or reversible) linkages. Mechanistically, CGA forms covalent bonds with nucleophilic amino acid residues of proteins by alkaline, free radical, and enzymatic approaches, leading to changes in protein structure and functionality, such as solubility, emulsification properties, and antioxidant activity. In addition, the protein-CGA complexes can be obtained by hydrogen bonds, hydrophobic and electrostatic interactions, and van der Waals forces, each offering unique advantages and outcomes. This review highlights the mechanism of these interactions and their importance in modifying the structural, functional, nutritional, and physiological attributes of animal- and plant-based proteins. Moreover, the potential applications of these protein-CGA conjugates/complexes are explored in various food systems, such as beverages, films and coatings, emulsion-based delivery systems, and so on. Overall, this literature review provides an in-depth overview of protein-CGA interactions, offering valuable insights for future research to develop novel protein-based food and non-food products with improved nutritional and functional characteristics.

Reactivity-Tunable Fluorescent Platform for Selective and Biocompatible Modification of Cysteine or Lysine.

Chemoselective modification of specific residues within a given protein poses a significant challenge, as the microenvironment of amino acid residues in proteins is variable. Developing a universal molecular platform with tunable chemical warheads can provide powerful tools for precisely labeling specific amino acids in proteins. Cysteine and lysine are hot targets for chemoselective modification, but current cysteine/lysine-selective warheads face challenges due to cross-reactivity and unstable reaction products. In this study, a versatile fluorescent platform is developed for highly selective modification of cysteine/lysine under biocompatible conditions. Chloro- or phenoxy-substituted NBSe derivatives effectively labeled cysteine residues in the cellular proteome with high specificity. This finding also led to the development of phenoxy-NBSe phototheragnostic for the diagnosis and activatable photodynamic therapy of GSH-overexpressed cancer cells. Conversely, alkoxy-NBSe derivatives are engineered to selectively react with lysine residues in the cellular environment, exhibiting excellent anti-interfering ability against thiols. Leveraging a proximity-driven approach, alkoxy-NBSe probes are successfully designed to demonstrate their utility in bioimaging of lysine deacetylase activity. This study also achieves integrating a small photosensitizer into lysine residues of proteins in a regioselective manner, achieving photoablation of cancer cells activated by overexpressed proteins.

Structure-based network analysis predicts pathogenic variants in human proteins associated with inherited retinal disease.

Advances in gene sequencing technologies have accelerated the identification of genetic variants, but better tools are needed to understand which are causal of disease. This would be particularly useful in fields where gene therapy is a potential therapeutic modality for a disease-causing variant such as inherited retinal disease (IRD). Here, we apply structure-based network analysis (SBNA), which has been successfully utilized to identify variant-constrained amino acid residues in viral proteins, to identify residues that may cause IRD if subject to missense mutation. SBNA is based entirely on structural first principles and is not fit to specific outcome data, which makes it distinct from other contemporary missense prediction tools. In 4 well-studied human disease-associated proteins (BRCA1, HRAS, PTEN, and ERK2) with high-quality structural data, we find that SBNA scores correlate strongly with deep mutagenesis data. When applied to 47 IRD genes with available high-quality crystal structure data, SBNA scores reliably identified disease-causing variants according to phenotype definitions from the ClinVar database. Finally, we applied this approach to 63 patients at Massachusetts Eye and Ear (MEE) with IRD but for whom no genetic cause had been identified. Untrained models built using SBNA scores and BLOSUM62 scores for IRD-associated genes successfully predicted the pathogenicity of novel variants (AUC = 0.851), allowing us to identify likely causative disease variants in 40 IRD patients. Model performance was further augmented by incorporating orthogonal data from EVE scores (AUC = 0.927), which are based on evolutionary multiple sequence alignments. In conclusion, SBNA can used to successfully identify variants as causal of disease in human proteins and may help predict variants causative of IRD in an unbiased fashion.