Mangrovimonas sp. strain CR14 is a halophilic bacterium affiliated with family Flavobacteriaceae which was successfully isolated from mangrove soil samples obtained from Tanjung Piai National Park, Johor. The whole genome of strain CR14 was sequenced on an Illumina HiSeq 2500 platform (2 × 150 bp paired end). Herein, we report the genome sequence of Mangrovimonas sp. strain CR14 in which its assembled genome consisted 20 contigs with a total size of 3,590,195 bp, 3209 coding sequences, and an average 36.08% G + C content. Genome annotation and gene mining revealed that this bacterium demonstrated proteolytic activity which could be potentially applied in detergent industry. This whole-genome shotgun data of Mangrovimonas sp. strain CR14 has been deposited at DDBJ/ENA/GenBank under the accession JAAFZY000000000. The version described in this paper is version JAAFZY010000000.
A halo-thermophilic bacterium, Roseithermus sacchariphilus strain RA (previously known as Rhodothermaceae bacterium RA), was isolated from a hot spring in Langkawi, Malaysia. A complete genome analysis showed that the bacterium harbors 57 glycoside hydrolases (GHs), including a multi-domain xylanase (XynRA2). The full-length XynRA2 of 813 amino acids comprises a family 4_9 carbohydrate-binding module (CBM4_9), a family 10 glycoside hydrolase catalytic domain (GH10), and a C-terminal domain (CTD) for type IX secretion system (T9SS). This study aims to describe the biochemical properties of XynRA2 and the effects of CBM truncation on this xylanase. XynRA2 and its CBM-truncated variant (XynRA2ΔCBM) was expressed, purified, and characterized. The purified XynRA2 and XynRA2ΔCBM had an identical optimum temperature at 70 °C, but different optimum pHs of 8.5 and 6.0 respectively. Furthermore, XynRA2 retained 94% and 71% of activity at 4.0 M and 5.0 M NaCl respectively, whereas XynRA2ΔCBM showed a lower activity (79% and 54%). XynRA2 exhibited a turnover rate (kcat) of 24.8 s-1, but this was reduced by 40% for XynRA2ΔCBM. Both the xylanases hydrolyzed beechwood xylan predominantly into xylobiose, and oat-spelt xylan into a mixture of xylo-oligosaccharides (XOs). Collectively, this work suggested CBM4_9 of XynRA2 has a role in enzyme performance.
Halogenated compounds are recalcitrant environmental pollutants prevalent in agricultural fields, waste waters and industrial by-products, but they can be degraded by dehalogenase-containing microbes. Notably, 2-haloalkanoic acid dehalogenases are employed to resolve optically active chloropropionates, as exemplified by the d-specific dehalogenase from Rhizobium sp. RCI (DehD), which acts on d-2-chloropropionate but not on its l-enantiomer. The catalytic residues of this dehalogenase responsible for its affinity toward d-2-chloropropionate have not been experimentally determined, although its three-dimensional crystal structure has been solved. For this study, we performed in silico docking and molecular dynamic simulations of complexes formed by this dehalogenase and d- or l-2-chloropropionate. Arg134 of the enzyme plays the key role in the stereospecific binding and Arg16 is in a position that would allow it to activate a water molecule for hydrolytic attack on the d-2-chloropropionate chiral carbon for release of the halide ion to yield l-2-hydroxypropionate. We propose that within the DehD active site, the NH group of Arg134 can form a hydrogen bond with the carboxylate of d-2-chloropropionate with a strength of ∼4 kcal/mol that may act as an acid-base catalyst, whereas, when l-2-chloropropionate is present, this bond cannot be formed. The significance of the present work is vital for rational design of this dehalogenase in order to confirm the involvement of Arg16 and Arg134 residues implicated in hydrolysis and binding of d-2-chloropropionate in the active site of d-specific dehalogenase from Rhizobium sp. RC1.
Currently, there is no three-dimensional structure of D-specific dehalogenase (DehD) in the protein database. We modeled DehD using ab initio technique, performed molecular dynamics (MD) simulation and docking of D-2-chloropropionate (D-2CP), D-2-bromopropionate (D-2BP), monochloroacetate (MCA), monobromoacetate (MBA), 2,2-dichloropropionate (2,2-DCP), d,l-2,3-dichloropropionate (d,l-2,3-DCP), and 3-chloropropionate (3-CP) into the DehD active site. The sequences of DehD and D-2-haloacid dehalogenase (HadD) from Pseudomonas putida AJ1 have 15% sequence similarity. The model had 80% of the amino acid residues in the most favored region when compared to the crystal structure of DehI from Pseudomonas putida PP3. Docking analysis revealed that Arg107, Arg134 and Tyr135 interacted with D-2CP, and Glu20 activated the water molecule for hydrolytic dehalogenation. Single residue substitutions at 25-30 °C showed that polar residues of DehD were stable when substituted with nonpolar residues and showed a decrease in activity within the same temperature range. The molecular dynamics simulation of DehD and its variants showed that in R134A variant, Arg107 interacted with D-2CP, while in Y135A, Gln221 and Arg231 interacted with D-2CP. It is our emphatic belief that the new model will be useful for the rational design of DehDs with enhanced potentials.
The D-2-haloacid dehalogenase of D-specific dehalogenase (DehD) from Rhizobium sp. RC1 catalyses the hydrolytic dehalogenation of D-haloalkanoic acids, inverting the substrate-product configuration and thereby forming the corresponding L-hydroxyalkanoic acids. Our investigations were focused on DehD mutants: R134A and Y135A. We examined the possible interactions between these mutants with haloalkanoic acids and characterized the key catalytic residues in the wild-type dehalogenase, to design dehalogenase enzyme(s) with improved potential for dehalogenation of a wider range of substrates. Three natural substrates of wild-type DehD, specifically, monochloroacetate, monobromoacetate and D,L-2,3-dichloropropionate, and eight other non-natural haloalkanoic acids substrates of DehD, namely, L-2-chloropropionate; L-2-bromopropionate; 2,2-dichloropropionate; dichloroacetate; dibromoacetate; trichloroacetate; tribromoacetate; and 3-chloropropionate, were docked into the active site of the DehD mutants R134A and Y135A, which produced altered catalytic functions. The mutants interacted strongly with substrates that wild-type DehD does not interact with or degrade. The interaction was particularly enhanced with 3-chloropropionate, in addition to monobromoacetate, monochloroacetate and D,L-2,3-dichloropropionate. In summary, DehD variants R134A and Y135A demonstrated increased propensity for binding haloalkanoic acid and were non-stereospecific towards halogenated substrates. The improved characteristics in these mutants suggest that their functionality could be further exploited and harnessed in bioremediations and biotechnological applications.
Managing education and research during pandemics has increased in importance since the onset of epidemics such as avian flu, SARS and now CoViD-19. Successful management in times of crisis ensures business continuity and institutional survival, making preparedness preceding an impending pandemic essential. Institutions of higher education (IHEs) must maintain balance between academic continuity and preventing morbidity during a pandemic crisis. To date, however, no general pandemic preparedness frameworks exist for IHEs. The aim of this paper is to report on the development of a Haddon matrix framework for IHE pandemic preparedness based on a scoping literature review of past IHE responses including pre-, during and post-pandemic phases. First, a review of previous global responses by IHEs during past pandemics was carried out. The review findings were then collated into a new IHE-centric Haddon matrix for pandemic preparedness. The content of the matrix is then illustrated through the documented responses of Malaysian universities during the early stages of the COVID-19 pandemic. The resulting IHE Haddon matrix can be used by universities as a general guide to identify preparedness gaps and intervention opportunities for business continuity during pandemics.
Previous molecular dynamic simulations have reported elongation of the existing beta-sheet in prion proteins. Detailed examination has shown that these elongations do not extend beyond the proline residues flanking these beta-sheets. In addition, proline has also been suggested to possess a possible structural role in preserving protein interaction sites by preventing invasion of neighboring secondary structures. In this work, we have studied the possible structural role of the flanking proline residues by simulating mutant structures with alternate substitution of the proline residues with valine. Simulations showed a directional inhibition of elongation, with the elongation progressing in the direction of valine including evident inhibition of elongation by existing proline residues. This suggests that the flanking proline residues in prion proteins may have a containment role and would confine the beta-sheet within a specific length.
The cluster-based compound selection is used in the lead identification process of drug discovery and design. Many clustering methods have been used for chemical databases, but there is no clustering method that can obtain the best results under all circumstances. However, little attention has been focused on the use of combination methods for chemical structure clustering, which is known as consensus clustering. Recently, consensus clustering has been used in many areas including bioinformatics, machine learning and information theory. This process can improve the robustness, stability, consistency and novelty of clustering. For chemical databases, different consensus clustering methods have been used including the co-association matrix-based, graph-based, hypergraph-based and voting-based methods. In this paper, a weighted cumulative voting-based aggregation algorithm (W-CVAA) was developed. The MDL Drug Data Report (MDDR) benchmark chemical dataset was used in the experiments and represented by the AlogP and ECPF_4 descriptors. The results from the clustering methods were evaluated by the ability of the clustering to separate biologically active molecules in each cluster from inactive ones using different criteria, and the effectiveness of the consensus clustering was compared to that of Ward's method, which is the current standard clustering method in chemoinformatics. This study indicated that weighted voting-based consensus clustering can overcome the limitations of the existing voting-based methods and improve the effectiveness of combining multiple clusterings of chemical structures.
Elucidation of the sperm-egg interaction at the molecular level is one of the unresolved problems in sexual reproduction, and understanding the molecular mechanism is crucial in solving problems in infertility and failed in vitro fertilization (IVF). Many molecular interactions in the form of protein-protein interactions (PPIs) mediate the sperm-egg membrane interaction. Due to the complexity of the problem such as difficulties in analyzing in vivo membrane PPIs, many efforts have failed to comprehensively elucidate the fusion mechanism and the molecular interactions that mediate sperm-egg membrane fusion. The main purpose of this study was to reveal possible protein interactions and associated molecular function during sperm-egg interaction using a protein interaction network approach. Different databases have been used to construct the human sperm-egg interaction network. The constructed network revealed new interactions. These included CD151 and CD9 in human oocyte that interact with CD49 in sperm, and CD49 and ITGA4 in sperm that interact with CD63 and CD81, respectively, in the oocyte. These results showed that the different integrins in sperm may be involved in human sperm-egg interaction. It was also suggested that sperm ADAM2 plays a role as a protein candidate involved in sperm-egg membrane interaction by interacting with CD9 in the oocyte. Interleukin-4 receptor activity, receptor signaling protein tyrosine kinase activity, and manganese ion transmembrane transport activity are the major molecular functions in sperm-egg interaction protein network. The disease association analysis indicated that sperm-egg interaction defects are also reflected in other disease networks such as cardiovascular, hematological, and breast cancer diseases. By analyzing the network, we identified the major molecular functions and disease association genes in sperm-egg interaction protein. Further experimental studies will be required to confirm the significance of these new computationally resolved interactions and the genetic links between sperm-egg interaction abnormalities and the associated disease.
Sperm-egg interaction defect is a significant cause of in-vitro fertilization failure for infertile cases. Numerous molecular interactions in the form of protein-protein interactions mediate the sperm-egg membrane interaction process. Recent studies have demonstrated that in addition to experimental techniques, computational methods, namely protein interaction network approach, can address protein-protein interactions between human sperm and egg. Up to now, no drugs have been detected to treat sperm-egg interaction disorder, and the initial step in drug discovery research is finding out essential proteins or drug targets for a biological process. The main purpose of this study is to identify putative drug targets for human sperm-egg interaction deficiency and consider if the detected essential proteins are targets for any known drugs using protein-protein interaction network and ingenuity pathway analysis.
Proteins can interact in various ways, ranging from direct physical relationships to indirect interactions in a formation of protein-protein interaction network. Diagnosis of the protein connections is critical to identify various cellular pathways. Today constructing and analyzing the protein interaction network is being developed as a powerful approach to create network pharmacology toward detecting unknown genes and proteins associated with diseases. Discovery drug targets regarding therapeutic decisions are exciting outcomes of studying disease networks. Protein connections may be identified by experimental and recent new computational approaches. Due to difficulties in analyzing in-vivo proteins interactions, many researchers have encouraged improving computational methods to design protein interaction network. In this review, the experimental and computational approaches and also advantages and disadvantages of these methods regarding the identification of new interactions in a molecular mechanism have been reviewed. Systematic analysis of complex biological systems including network pharmacology and disease network has also been discussed in this review.
Non-obstructive azoospermia is a severe infertility factor. Currently, the etiology of this condition remains elusive with several possible molecular pathway disruptions identified in the post-meiotic spermatozoa. In the presented study, in order to identify all possible candidate genes associated with azoospermia and to map their relationship, we present the first protein-protein interaction network related to azoospermia and analyze the complex effects of the related genes systematically. Using Online Mendelian Inheritance in Man, the Human Protein Reference Database and Cytoscape, we created a novel network consisting of 209 protein nodes and 737 interactions. Mathematical analysis identified three proteins, ar, dazap2, and esr1, as hub nodes and a bottleneck protein within the network. We also identified new candidate genes, CREBBP and BCAR1, which may play a role in azoospermia. The gene ontology analysis suggests a genetic link between azoospermia and liver disease. The KEGG analysis also showed 45 statistically important pathways with 31 proteins associated with colorectal, pancreatic, chronic myeloid leukemia and prostate cancer. Two new genes and associated diseases are promising for further experimental validation.
Complete elucidation of fertilization process at molecular level is one of the unresolved challenges in sexual reproduction studies, and understanding the molecular mechanism is crucial in overcoming difficulties in infertility and unsuccessful in vitro fertilization. Sperm-oocyte interaction is one of the most remarkable events in fertilization process, and deficiency in protein-protein interactions which mediate this interaction is a major cause of unexplained infertility. Due to detection of how the various defects of sperm-oocyte interaction can affect fertilization failure, different experimental methods have been applied. This review summarizes the current understanding of sperm-egg interaction mechanism during fertilization and also accumulates the different types of sperm-egg interaction abnormalities and their association with infertility. Several detection approaches regarding sperm-egg protein interactions and the associated defects are reviewed in this paper.
Xylitol is a high-value low-calorie sweetener used as sugar substitute in food and pharmaceutical industry. Xylitol phosphate dehydrogenase (XPDH) catalyses the conversion of d-xylulose 5-phosphate (XU5P) and d-ribulose 5-phosphate (RU5P) to xylitol and ribitol respectively in the presence of nicotinamide adenine dinucleotide hydride (NADH). Although these enzymes have been shown to produce xylitol and ribitol, there is an incomplete understanding of the mechanism of the catalytic events of these reactions and the detailed mechanism has yet to be elucidated. The main goal of this work is to analyse the conformational changes of XPDH-bound ligands such as zinc, NADH, XU5P, and RU5P to elucidate the key amino acids involved in the substrate binding. In silico modelling, comparative molecular dynamics simulations, interaction analysis and conformational study were carried out on three XPDH enzymes of the Medium-chain dehydrogenase (MDR) family in order to elucidate the atomistic details of conformational transition, especially on the open and closed state of XPDH. The analysis also revealed the possible mechanism of substrate specificity that are responsible in the catalyse hydride transfer are the residues His58 and Ser39 which would act as the proton donor for reduction of XU5P and RU5P respectively. The structural comparison and MD simulations displayed a significant difference in the conformational dynamics of the catalytic and coenzyme loops between Apo and XPDH-complexes and highlight the contribution of newly found triad residues. This study would assist future mutagenesis study and enzyme modification work to increase the catalysis efficiency of xylitol production in the industry.
A novel α-amylase was isolated successfully from Glaciozyma antarctica PI12 using DNA walking and reverse transcription-polymerase chain reaction (RT-PCR) methods. The structure of this psychrophilic α-amylase (AmyPI12) from G. antarctica PI12 has yet to be studied in detail. A 3D model of AmyPI12 was built using a homology modelling approach to search for a suitable template and to generate an optimum target-template alignment, followed by model building using MODELLER9.9. Analysis of the AmyPI12 model revealed the presence of binding sites for a conserved calcium ion (CaI), non-conserved calcium ions (CaII and CaIII) and a sodium ion (Na). Compared with its template-the thermostable α-amylase from Bacillus stearothermophilus (BSTA)-the binding of CaII, CaIII and Na ions in AmyPI12 was observed to be looser, which suggests that the low stability of AmyPI12 allows the protein to work at different temperature scales. The AmyPI12 amino acid sequence and model were compared with thermophilic α-amylases from Bacillus species that provided the highest structural similarities with AmyPI12. These comparative studies will enable identification of possible determinants of cold adaptation.
The structure of psychrophilic chitinase (CHI II) from Glaciozyma antarctica PI12 has yet to be studied in detail. Due to its low sequence identity (<30 %), the structural prediction of CHI II is a challenge. A 3D model of CHI II was built by first using a threading approach to search for a suitable template and to generate an optimum target-template alignment, followed by model building using MODELLER9v7. Analysis of the catalytic insertion domain structure in CHI II revealed an increase in the number of aromatic residues and longer loops compared to mesophilic and thermophilic chitinases. A molecular dynamics simulation was used to examine the stability of the CHI II structure at 273, 288 and 300 K. Structural analysis of the substrate-binding cleft revealed a few exposed aromatic residues. Substitutions of certain amino acids in the surface and loop regions of CHI II conferred an increased flexibility to the enzyme, allowing for an adaptation to cold temperatures. A substrate binding comparison of CHI II with the mesophilic chitinase from Coccidioides immitis, 1D2K, suggested that the psychrophilic adaptation and catalytic activity at low temperatures were achieved through a reduction in the number of salt bridges, fewer hydrogen bonds and an increase in the exposure of the hydrophobic side chains to the solvent.
Here, we present a novel psychrophilic β-glucanase from Glaciozyma antarctica PI12 yeast that has been structurally modeled and analyzed in detail. To our knowledge, this is the first attempt to model a psychrophilic laminarinase from yeast. Because of the low sequence identity (<40%), a threading method was applied to predict a 3D structure of the enzyme using the MODELLER9v12 program. The results of a comparative study using other mesophilic, thermophilic, and hyperthermophilic laminarinases indicated several amino acid substitutions on the surface of psychrophilic laminarinase that totally increased the flexibility of its structure for efficient catalytic reactions at low temperatures. Whereas several structural factors in the overall structure can explain the weak thermal stability, this research suggests that the psychrophilic adaptation and catalytic activity at low temperatures were achieved through existence of longer loops and shorter or broken helices and strands, an increase in the number of aromatic and hydrophobic residues, a reduction in the number of hydrogen bonds and salt bridges, a higher total solvent accessible surface area, and an increase in the exposure of the hydrophobic side chains to the solvent. The results of comparative molecular dynamics simulation and principal component analysis confirmed the above strategies adopted by psychrophilic laminarinase to increase its catalytic efficiency and structural flexibility to be active at cold temperature.
The structure of a novel psychrophilic β-mannanase enzyme from Glaciozyma antarctica PI12 yeast has been modelled and analysed in detail. To our knowledge, this is the first attempt to model a psychrophilic β-mannanase from yeast. To this end, a 3D structure of the enzyme was first predicted using a threading method because of the low sequence identity (<30%) using MODELLER9v12 and simulated using GROMACS at varying low temperatures for structure refinement. Comparisons with mesophilic and thermophilic mannanases revealed that the psychrophilic mannanase contains longer loops and shorter helices, increases in the number of aromatic and hydrophobic residues, reductions in the number of hydrogen bonds and salt bridges and numerous amino acid substitutions on the surface that increased the flexibility and its efficiency for catalytic reactions at low temperatures.