Homology modelling: a review about the method on hand of the diabetic antigen GAD 65 structure prediction

Insight into the Molecular Mechanism for the Discrepant Inhibition of Microcystins (MCLR, LA, LF, LW, LY) on Protein Phosphatase 2A

Microcystins (MCs) exhibit diversified inhibition effects on protein phosphatases (PPs) due to their structural differences. To fully evaluate the potential mechanism for the discrepant inhibition effects, the five most frequent MCs with varying residues at position Z4 were selected as the tested toxins. Their inhibition sequence on PP2A was detected as follows: MCLR > MCLW > MCLA > MCLF > MCLY. Combined with homology modeling and molecular docking technology, the major interaction parameters between the MCs and PP2A were obtained. The correlation analysis for the major interaction parameters and inhibition effects showed that the hydrophobicity of Z4 had an important influence on the interaction of the MCs to PP2A. The introduction of hydrophobic Z4 directly weakened hydrogen bonds Z4→Pro213 and Z4←Arg214, indirectly weakened hydrogen bonds Adda5←Asn117, Glu6←Arg89, and MeAsp3←Arg89, but indirectly enhanced ionic bonds Glu6←Arg89, Glu6-Mn12+, and Glu6-Mn22+. In this way, the combination of the MCs with PP2A was blocked, and thus, the interactions between PP2A and the Mn2+ ions (in the catalytic center) were further affected; metal bonds Asp85-Mn12+ and Asp85-Mn22+ were weakened, while metal bond His241-Mn12+ was enhanced. As a result, the interactions in the catalytic center were inhibited to varying degrees, resulting in the reduced toxicity of MCs.

Structure prediction and functional analyses of a thermostable lipase obtained from Shewanella putrefaciens

Previous experimental studies on thermostable lipase from Shewanella putrefaciens suggested the maximum activity at higher temperatures, but with little information on its conformational profile. In this study, the three-dimensional structure of lipase was predicted and a 60 ns molecular dynamics (MD) simulation was carried out at temperatures ranging from 300 to 400 K to better understand its thermostable nature at the molecular level. MD simulations were performed in order to predict the optimal activity of thermostable lipase. The results suggested strong conformational temperature dependence. The thermostable lipase maintained its bio-active conformation at 350 K during the 60 ns MD simulations.

What can we learn from the microbial ecological interactions associated with polymicrobial diseases?

Periodontal diseases in humans and animals are model polymicrobial diseases which are associated with a shift in the microbial community structure and function; there is therefore a need to investigate these diseases from a microbial ecological perspective. This review highlights three important areas of microbial ecological investigation of polymicrobial diseases and the lessons that could be learnt: (1) identification of disease-associated microbes and the implications for choice of anti-infective treatment; (2) the implications associated with vaccine design and development and (3) application of the dynamics of microbial interaction in the discovery of novel anti-infective agents. This review emphasises the need to invigorate microbial ecological approaches to the study of periodontal diseases and other polymicrobial diseases for greater understanding of the ecological interactions between and within the biotic and abiotic factors of the environment.

Serine protease identification (in vitro) and molecular structure predictions (in silico) from a phytopathogenic fungus, Alternaria solani

Serine proteases are involved in an enormous number of biological processes. The present study aims at characterizing three-dimensional (3D) molecular architecture of serine proteases from early blight pathogen, Alternaria solani that are hypothesized to be markers of phytopathogenicity. A serine protease was purified to homogeneity and MALDI-TOF-MS/MS analysis revealed that protease produced by A. solani belongs to alkaline serine proteases (AsP). AsP is made up of 403 amino acid residues with molecular weight of 42.1 kDa (Isoelectric point - 6.51) and its molecular formula was C1859 H2930 N516 O595 S4 . AsP structure model was built based on its comparative homology with serine protease using the program, MODELER. AsP had 16 β-sheets and 10 α-helices, with Ser(350) (G347-G357), Asp(158) (D158-H169), and His(193) (H193-G203) in separate turn/coil structures. Biological metal binding region situated near 6th-helix and His(193) residue is responsible for metal binding site. Also, calcium ion (Ca(2+)) is coordinated by the carboxyl groups of Lys(84), Ile(85), Lys(86), Asp(87), Phe(88), Ala(89), Ala(90) (K84-A90) for first Ca(2+) binding site and carbonyl oxygen atom of Lys(244), Gly(245), Arg(246), Thr(247), Lys(248), Lys(249), and Ala(250) (K244-A250), for second Ca(2+) binding site. Moreover, Ramachandran plot analysis of protein residues falling into most favored secondary structures were determined (83.3%). The predicted molecular 3D structural model was further verified using PROCHECK, ERRAT, and VADAR servers to confirm the geometry and stereo-chemical parameters of the molecular structural design. The functional analysis of AsP 3D molecular structure predictions familiar in the current study may provide a new perspective in the understanding and identification of antifungal protease inhibitor designing.

Space constrained homology modelling: the paradigm of the RNA-dependent RNA polymerase of dengue (type II) virus

Protein structure is more conserved than sequence in nature. In this direction we developed a novel methodology that significantly improves conventional homology modelling when sequence identity is low, by taking into consideration 3D structural features of the template, such as size and shape. Herein, our new homology modelling approach was applied to the homology modelling of the RNA-dependent RNA polymerase (RdRp) of dengue (type II) virus. The RdRp of dengue was chosen due to the low sequence similarity shared between the dengue virus polymerase and the available templates, while purposely avoiding to use the actual X-ray structure that is available for the dengue RdRp. The novel approach takes advantage of 3D space corresponding to protein shape and size by creating a 3D scaffold of the template structure. The dengue polymerase model built by the novel approach exhibited all features of RNA-dependent RNA polymerases and was almost identical to the X-ray structure of the dengue RdRp, as opposed to the model built by conventional homology modelling. Therefore, we propose that the space-aided homology modelling approach can be of a more general use to homology modelling of enzymes sharing low sequence similarity with the template structures.

Modelling and enhanced molecular dynamics to steer structure-based drug discovery

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes.

Dynamic changes in the secondary structure of ECE-1 and XCE account for their different substrate specificities

Background

X-converting enzyme (XCE) involved in nervous control of respiration, is a member of the M13 family of zinc peptidases, for which no natural substrate has been identified yet. In contrast, it’s well characterized homologue endothelin-converting enzyme-1 (ECE-1) showed broad substrate specificity and acts as endopeptidase as well as dipeptidase. To explore the structural differences between XCE and ECE-1, homology model of XCE was built using the complex structure of ECE-1 with phosphoramidon (pdb-id: 3DWB) as template. Phosphoramidon was docked into the binding site of XCE whereas phosphate oxygen of the inhibitor was used as water molecule to design the apo forms of both enzymes. Molecular dynamics simulation of both enzymes was performed to analyze the dynamic nature of their active site residues in the absence and presence of the inhibitor.

Results

Homology model of XCE explained the role of non-conserved residues of its S2’ subsite. Molecular dynamics (MD) simulations identified the flexible transitions of F149/I150, N566/N571, W714/W719, and R145/R723 residues of ECE-1/XCE for the strong binding of the inhibitor. Secondary structure calculations using DSSP method reveals the folding of R145/R723 residue of ECE-1/XCE into β-sheet structure while unfolding of the S2’ subsite residues in aECE-1 and sustained compact folding of that of aXCE. The results evaluated are in good agreement with available experimental data, thus providing detailed molecular models which can explain the structural and specificities differences between both zinc peptidases.

Conclusions

Secondary structure changes of both enzymes during the simulation time revealed the importance of β-sheet structure of R145/R723 for its binding with the terminal carboxylate group of the inhibitor. Unfolding of the α-helix comprising the S2’ subsite residues in aECE-1 correlate well with its endopeptidase activity while their compact folding in aXCE may account for the inactivity of the enzyme towards large C-terminal containing substrates.