scholarly journals A computational approach to structural properties of glycoside hydrolase family 4 from bacteria.

2013 ◽  
Vol 60 (4) ◽  
Author(s):  
Dana Craciun ◽  
Beatrice Vlad-Oros ◽  
Nicoleta Filimon ◽  
Vasile Ostafe ◽  
Adriana Isvoran
Keyword(s):  
Protein Interactions ◽  
Thermotoga Maritima ◽  
Structural Characteristics ◽  
Specific Protein ◽  
Computational Approach ◽  
Glycoside Hydrolase Family ◽  
Protein Protein Interactions ◽  
Sequence Identity ◽  
Enzyme Family ◽  
Hydrolase Family

Structural bioinformatics approaches applied to the alpha- and beta-glycosidases from the GH4 enzyme family reveal that, despite low sequence identity, these enzymes possess quite similar global structural characteristics reflecting a common reaction mechanism. Locally, there are a few distinctive structural characteristics of GH4 alpha- and beta-glycosidases, namely, surface cavities with different geometric characteristics and two regions with highly dissimilar structural organizations and distinct physicochemical properties in the alpha- and beta-glucosidases from Thermotoga maritima. We suggest that these structurally dissimilar regions may be involved in specific protein-protein interactions and this hypothesis is sustained by the predicted distinct functional partners of the investigated proteins. Also, we predict that alpha- and beta-glycosidases from the GH4 enzyme family interact with difenoconazole, a fungicide, but there are different features of these interactions especially concerning the identified structurally distinct regions of the investigated proteins.

scholarly journals Modulating Glycoside Hydrolase Activity between Hydrolysis and Transfer Reactions Using an Evolutionary Approach

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6586
Author(s):  
Rodrigo A. Arreola-Barroso ◽  
Alexey Llopiz ◽  
Leticia Olvera ◽  
Gloria Saab-Rincón
Keyword(s):  
Glycoside Hydrolase ◽  
Thermotoga Maritima ◽  
Computational Approach ◽  
Glycoside Hydrolase Family ◽  
Structural Determinants ◽  
Dynamic Simulations ◽  
Reaction Specificity ◽  
Essential Contribution ◽  
Hydrolysis Of ◽  
Hydrolase Family

The proteins within the CAZy glycoside hydrolase family GH13 catalyze the hydrolysis of polysaccharides such as glycogen and starch. Many of these enzymes also perform transglycosylation in various degrees, ranging from secondary to predominant reactions. Identifying structural determinants associated with GH13 family reaction specificity is key to modifying and designing enzymes with increased specificity towards individual reactions for further applications in industrial, chemical, or biomedical fields. This work proposes a computational approach for decoding the determinant structural composition defining the reaction specificity. This method is based on the conservation of coevolving residues in spatial contacts associated with reaction specificity. To evaluate the algorithm, mutants of α-amylase (TmAmyA) and glucanotransferase (TmGTase) from Thermotoga maritima were constructed to modify the reaction specificity. The K98P/D99A/H222Q variant from TmAmyA doubled the transglycosydation/hydrolysis (T/H) ratio while the M279N variant from TmGTase increased the hydrolysis/transglycosidation ratio five-fold. Molecular dynamic simulations of the variants indicated changes in flexibility that can account for the modified T/H ratio. An essential contribution of the presented computational approach is its capacity to identify residues outside of the active center that affect the reaction specificity.

Structure, Function, Involvement in Diseases and Targeting of 14-3-3 Proteins: An Update

2018 ◽  
Vol 25 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Ylenia Cau ◽  
Daniela Valensin ◽  
Mattia Mori ◽  
Sara Draghi ◽  
Maurizio Botta
Keyword(s):  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Physiological Role ◽  
Specific Protein ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Partners ◽  
High Sequence Homology ◽  
Small Molecule Modulators

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.

Metallocluster transactions: dynamic protein interactions guide the biosynthesis of Fe–S clusters in bacteria

2018 ◽  
Vol 46 (6) ◽  
pp. 1593-1603 ◽  
Author(s):  
Chenkang Zheng ◽  
Patricia C. Dos Santos
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Specific Protein ◽  
Biological Synthesis ◽  
Cluster Assembly ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Cysteine Desulfurase ◽  
Wide Range ◽  
Domains Of Life

Iron–sulfur (Fe–S) clusters are ubiquitous cofactors present in all domains of life. The chemistries catalyzed by these inorganic cofactors are diverse and their associated enzymes are involved in many cellular processes. Despite the wide range of structures reported for Fe–S clusters inserted into proteins, the biological synthesis of all Fe–S clusters starts with the assembly of simple units of 2Fe–2S and 4Fe–4S clusters. Several systems have been associated with the formation of Fe–S clusters in bacteria with varying phylogenetic origins and number of biosynthetic and regulatory components. All systems, however, construct Fe–S clusters through a similar biosynthetic scheme involving three main steps: (1) sulfur activation by a cysteine desulfurase, (2) cluster assembly by a scaffold protein, and (3) guided delivery of Fe–S units to either final acceptors or biosynthetic enzymes involved in the formation of complex metalloclusters. Another unifying feature on the biological formation of Fe–S clusters in bacteria is that these systems are tightly regulated by a network of protein interactions. Thus, the formation of transient protein complexes among biosynthetic components allows for the direct transfer of reactive sulfur and Fe–S intermediates preventing oxygen damage and reactions with non-physiological targets. Recent studies revealed the importance of reciprocal signature sequence motifs that enable specific protein–protein interactions and consequently guide the transactions between physiological donors and acceptors. Such findings provide insights into strategies used by bacteria to regulate the flow of reactive intermediates and provide protein barcodes to uncover yet-unidentified cellular components involved in Fe–S metabolism.

scholarly journals A Computational Approach for Protein-Protein Interactions of Bacterial Surface Layer Protein with Human Erb3 and αIIB-β3 Receptors

2021 ◽  
Vol 12 (1) ◽  
pp. 420-430
Keyword(s):  
Surface Layer ◽  
Molecular Docking ◽  
Protein Interactions ◽  
Protein A ◽  
Computational Approach ◽  
Microbial Interactions ◽  
Protein Protein Interactions ◽  
Epithelial Surface ◽  
Surface Receptors ◽  
Surface Layer Protein

Host microbial interactions had significant factors in maintains homeostasis and immune-related activity. One such interaction made by Lactobacillus sp. with Surface layer proteins (Slps) had been studied through a computational approach. Erb3 and αIIB-β3, which are epithelial surface layer receptors, are subjected to interact with the Slp homology model. Both cell surface receptors were subjected to interact through computational docking, followed by molecular dynamics simulations through the coarse-grain method to explore the conformational stability. Through the implementation of the molecular docking for the surface layer protein A, we have shown the surface layer protein A, protein-protein interactions are higher in cellular receptors with epidermal growth factor receptor at an -34.45 ΔG and -51.19 ΔG through molecular docking with Erb3 and αIIB-β3. This study shows the unique interaction of Slp with the epithelial surface receptors like Erb3 and αIIB-β3, which are multipurpose applications in microbial-based drug therapeutics.

scholarly journals Bi-directional protein-protein interactions control liquid-liquid phase separation of PSD-95 and its interaction partners

2021 ◽  
Author(s):  
Nikolaj Riis Christensen ◽  
Christian Parsbæk Pedersen ◽  
Vita Sereikaite ◽  
Jannik Nedergaard Pedersen ◽  
Maria Vistrup-Parry ◽  
...  
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Protein Interactions ◽  
Postsynaptic Density ◽  
Specific Protein ◽  
Liquid Phase Separation ◽  
Protein Protein Interactions ◽  
New Perspective ◽  
Liquid Liquid Phase Separation

SUMMARYThe organization of the postsynaptic density (PSD), a protein-dense semi-membraneless organelle, is mediated by numerous specific protein-protein interactions (PPIs) which constitute a functional post-synapse. Postsynaptic density protein 95 (PSD-95) interacts with a manifold of proteins, including the C-terminal of transmembrane AMPA receptor (AMAPR) regulatory proteins (TARPs). Here, we uncover the minimal essential peptide responsible for the stargazin (TARP-γ2) mediated liquid-liquid phase separation (LLPS) formation of PSD-95 and other key protein constituents of the PSD. Furthermore, we find that pharmacological inhibitors of PSD-95 can facilitate formation of LLPS. We found that in some cases LLPS formation is dependent on multivalent interactions while in other cases short peptides carrying a high charge are sufficient to promote LLPS in complex systems. This study offers a new perspective on PSD-95 interactions and their role in LLPS formation, while also considering the role of affinity over multivalency in LLPS systems.

scholarly journals An Integrative Computational Approach for the Prediction of Human-Plasmodium Protein-Protein Interactions

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Kais Ghedira ◽  
Yosr Hamdi ◽  
Abir El Béji ◽  
Houcemeddine Othman
Keyword(s):  
Protein Interactions ◽  
Computational Approach ◽  
Protein Protein Interactions ◽  
Human Red Blood Cells ◽  
Pharmacological Targets ◽  
Host Pathogen ◽  
Human Proteins ◽  
Life Threatening ◽  
Similarity Method ◽  
Human Plasmodium

Host-pathogen molecular cross-talks are critical in determining the pathophysiology of a specific infection. Most of these cross-talks are mediated via protein-protein interactions between the host and the pathogen (HP-PPI). Thus, it is essential to know how some pathogens interact with their hosts to understand the mechanism of infections. Malaria is a life-threatening disease caused by an obligate intracellular parasite belonging to the Plasmodium genus, of which P. falciparum is the most prevalent. Several previous studies predicted human-plasmodium protein-protein interactions using computational methods have demonstrated their utility, accuracy, and efficiency to identify the interacting partners and therefore complementing experimental efforts to characterize host-pathogen interaction networks. To predict potential putative HP-PPIs, we use an integrative computational approach based on the combination of multiple OMICS-based methods including human red blood cells (RBC) and Plasmodium falciparum 3D7 strain expressed proteins, domain-domain based PPI, similarity of gene ontology terms, structure similarity method homology identification, and machine learning prediction. Our results reported a set of 716 protein interactions involving 302 human proteins and 130 Plasmodium proteins. This work provides a list of potential human-Plasmodium interacting proteins. These findings will contribute to better understand the mechanisms underlying the molecular determinism of malaria disease and potentially to identify candidate pharmacological targets.

scholarly journals Coevolution-based prediction of protein–protein interactions in polyketide biosynthetic assembly lines

2020 ◽  
Vol 36 (19) ◽  
pp. 4846-4853 ◽  
Author(s):  
Yan Wang ◽  
Miguel Correa Marrero ◽  
Marnix H Medema ◽  
Aalt D J van Dijk
Keyword(s):  
Protein Interactions ◽  
Antitumor Agents ◽  
Acyl Carrier Protein ◽  
Specific Protein ◽  
Combinatorial Biosynthesis ◽  
Supplementary Information ◽  
Protein Protein Interactions ◽  
Assembly Lines ◽  
Specific Order ◽  
Encoding Genes

Abstract Motivation Polyketide synthases (PKSs) are enzymes that generate diverse molecules of great pharmaceutical importance, including a range of clinically used antimicrobials and antitumor agents. Many polyketides are synthesized by cis-AT modular PKSs, which are organized in assembly lines, in which multiple enzymes line up in a specific order. This order is defined by specific protein–protein interactions (PPIs). The unique modular structure and catalyzing mechanism of these assembly lines makes their products predictable and also spurred combinatorial biosynthesis studies to produce novel polyketides using synthetic biology. However, predicting the interactions of PKSs, and thereby inferring the order of their assembly line, is still challenging, especially for cases in which this order is not reflected by the ordering of the PKS-encoding genes in the genome. Results Here, we introduce PKSpop, which uses a coevolution-based PPI algorithm to infer protein order in PKS assembly lines. Our method accurately predicts protein orders (93% accuracy). Additionally, we identify new residue pairs that are key in determining interaction specificity, and show that coevolution of N- and C-terminal docking domains of PKSs is significantly more predictive for PPIs than coevolution between ketosynthase and acyl carrier protein domains. Availability and implementation The code is available on http://www.bif.wur.nl/ (under ‘Software’). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Biochemical characterisation of four rhamnosidases from thermophilic bacteria of the genera Thermotoga, Caldicellulosiruptor and Thermoclostridium

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Melanie Baudrexl ◽  
Wolfgang H. Schwarz ◽  
Vladimir V. Zverlov ◽  
Wolfgang Liebl
Keyword(s):  
Thermophilic Bacteria ◽  
Thermotoga Maritima ◽  
Physiological Role ◽  
Structural Similarity ◽  
Glycoside Hydrolase Family ◽  
Thermotoga Neapolitana ◽  
Cobalt Nickel ◽  
Biochemical Characterisation ◽  
Hydrolase Family ◽  
Nickel Manganese

Abstract Carbohydrate active enzymes are classified in databases based on sequence and structural similarity. However, their function can vary considerably within a similarity-based enzyme family, which makes biochemical characterisation indispensable to unravel their physiological role and to arrive at a meaningful annotation of the corresponding genes. In this study, we biochemically characterised the four related enzymes Tm_Ram106B, Tn_Ram106B, Cb_Ram106B and Ts_Ram106B from the thermophilic bacteria Thermotoga maritima MSB8, Thermotoga neapolitana Z2706-MC24, Caldicellulosiruptor bescii DSM 6725 and Thermoclostridium stercorarium DSM 8532, respectively, as α-l-rhamnosidases. Cobalt, nickel, manganese and magnesium ions stimulated while EDTA and EGTA inhibited all four enzymes. The kinetic parameters such as Km, Vmax and kcat were about average compared to other rhamnosidases. The enzymes were inhibited by rhamnose, with half-maximal inhibitory concentrations (IC50) between 5 mM and 8 mM. The α-l-rhamnosidases removed the terminal rhamnose moiety from the rutinoside in naringin, a natural flavonone glycoside. The Thermotoga sp. enzymes displayed the highest optimum temperatures and thermostabilities of all rhamnosidases reported to date. The four thermophilic and divalent ion-dependent rhamnosidases are the first biochemically characterised orthologous enzymes recently assigned to glycoside hydrolase family 106.

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