Modelling and Characterization of Glial Fibrillary Acidic Protein

Glial Fibrillary Acidic Protein (GFAP) is an intermediate-filament (IF) protein that maintains the astrocytes of the Central Nervous System in Human. This is differentially expressed during serological studies in inflamed condition such as Rheumatoid Arthritis (RA). Therefore, it is of interest to glean molecular insight using a model of GFAP (49.88 kDa) due to its crystallographic nonavailability. The present study has been taken into consideration to construct computational protein model using Modeller 9.11. The structural relevance of the protein was verified using Gromacs 4.5 followed by validation through PROCHECK, Verify 3D, WHAT-IF, ERRAT and PROVE for reliability. The constructed three dimensional (3D) model of GFAP protein had been scrutinized to reveal the associated functions by identifying ligand binding sites and active sites. Molecular level interaction study revealed five possible surface cavities as active sites. The model finds application in further computational analysis towards drug discovery in order to minimize the effect of inflammation.     

Comparative structural modeling and docking studies of oxalate oxidase: Possible implication in enzyme supplementation therapy for urolithiasis

In humans oxalate is end product of protein metabolism, with no enzyme present to act on it. In conditions of its enhanced endogenous synthesis or increased absorption from the diet, oxalate accumulation leads to hyperoxaluria which can further lead to a number of pathological conditions including urolithiasis. Urolithiasis has been a perplexing problem due to its high incidence and rate of recurrence after treatment like Extracorporeal-shock wave lithotripsy (ESWL). Hence other prophylactic treatment becomes necessary. One of the newer approaches of curing such metabolic disorders is the enzyme supplementation therapy. Oxalate oxidase (OxOx) is a commonly occurring enzyme in plants, bacteria and fungi that catalyses oxidative cleavage of oxalate to CO(2) with reduction of dioxygen to H(2)O(2). Present study, used Hordeum vulgare OxOx crystal structure (PDB ID 2ET1A) as a template for constructing 3D models of OxOx from Triticum aestivum, Arabidopsis thaliana, Sclerotiana sclerotiarum. Similarly Homology models for isoforms Ceriporiopsis subvermispora 336, C. subvermispora 422 were constructed by using template Bacillus subtilis oxalate decarboxylase (Oxdc) (PDB ID 2UY8A) by comparative modeling approach in SWISS MODEL, MODELLER, 3D JIGSAW and GENO 3D program server. Based on overall stereochemical quality (PROCHECK, PROSA, VARIFY 3D), best models were selected, energy minimized, refined and characterized for active site in BioMed CaChe V 6.1 workspace. Selected models were further studied for structure function relationship with substrate (oxalate) and its analogue (glycolate) by using docking approach. Calculated interaction energy between the oxalate and constructed enzyme indicated that homology models for OxOx of T. aestivum, A. thaliana and S. sclerotiarum, can account for better regio-specificity of this enzyme towards oxalate. That supports the interested metabolism and thus may further implement in enzyme supplementation therapy for urolithiasis.     

Homology modelling and molecular dynamics simulations of a protein serine/threonine phosphatase stp1 in Staphylococcus aureus N315: a potential drug target

The prevalence of methicillin-resistant Staphylococcus aureus and vanomycin intermediate S. aureus infections is on the rise, globally. This poses a huge challenge due to limited therapeutic options and the limited number of bacterial-specific drug targets available for due conservation with the human host. A serine/threonine phosphatase/kinase stp1/stk1 phospho-signalling system in S. aureus, which is just beginning to be understood, has been shown to be of importance in virulence and susceptibility to glycopeptide antibiotics. In this study, 3D structure of stp1 (clinical strain of S. aureus N315) was predicted using a homology modelling tool MODELLER. The validation of the predicted model was done using various tools such as PROCHECK, ERRAT, VERIFY-3D and ProSA. Molecular dynamics (MD) study was carried out using GROMACS to refine the least energy model generated from MODELLER9v11 and it was compared with the template. The template used was the crystal structure of serine/threonine phosphatase stp1 in Streptoccocus agalactiae (Protein Data Bank ID: 2PK0) with 38% identity with the query. Various validation tools showed the quality of the model generated using MODELLER. PROCHECK predicted 100% residues in the allowed region, ERRAT with overall quality factor of 76.47, VERIFY-3D with average score of >0.2 in 81.78% of residues, WHATIF with packaging quality score of > ? 5 for all residues and ProSA with Z-score of ? 7.02. MD simulation of the protein showed some fluctuations in the aqueous environment and changes in the ligand binding residues after simulation. The availability of the 3D-structural information of a viable drug target in S. aureus stp1 is expected to facilitate structure–activity relationship and interactions with proteins.     

In-silico comparative study of inhibitory mechanism of Plant Serine Proteinase Inhibitors

The nematodes like root-knot and cyst are plant-parasitic pest found in horticultural and agricultural crops. They do damages in the roots of plants as a result losses million tons of production. High cost of nematicides and environment safety concern has necessitated finding of some alternative methods. Under Integrated Pest Management (IPM) such problems are solving significantly by means of target gene inhibition, agrobacterium mediated transformation etc. One of this strategy use Plant Proteinase Inhibitors (PIs) gene which are used to control the proteolysis mechanism of Pest by inhibiting gut Serine Proteinase (SP). Present work investigates the utility of computer aided methods to study the mechanism of Protein-Protein interactions and thereby inhibition of Serine Proteinase by PIs. Hence 3D models of Serine Proteinase as well as Serine Proteinase Inhibitors (SPIs) generated using homology modeling. Validations of constructed models have been done by PROCHECK, VERIFY3D, ERRAT and PROSA. Prediction of Protein interacting surface patches and site specific protein docking was performed by using ZDOCK Server. Backbone refinement of output protein complexes was executed in Fiber Dock server. Interaction study between SP and SPIs complexes shows their comparative inhibition efficacy, measured in terms of number of hydrogen bonds, Van dar wall attraction and docking energy. This work reported that Vigna marina and Phaseolus oligospermus are having better inhibition efficiency in comparison to other inhibitors.     

Exploring the molecular basis for selective binding of Mycobacterium tuberculosis Asp kinase toward its natural substrates and feedback inhibitors: A docking and molecular dynamics study

Tuberculosis (TB) is still a major public health problem, compounded by the human immunodeficiency virus (HIV)-TB co-infection and recent emergence of multidrug-resistant (MDR) and extensively drug resistant (XDR)-TB. In this context, aspartokinase of mycobacterium tuberculosis has drawn attention for designing novel anti-TB drugs. Asp kinase is an enzyme responsible for the synthesis of 4-phospho-L-aspartate from L-aspartate and involved in the branched biosynthetic pathway leading to the synthesis of amino acids lysine, threonine, methionine and isoleucine. An intermediate of lysine biosynthetic branch, mesodiaminopimelate is also a component of the peptidoglycan which is a component of bacterial cell wall. To interfere with the production of all these amino acids and cell wall, it is possible to inhibit Asp kinase activity. This can be achieved using Asp kinase inhibitors. In order to design novel Asp kinase inhibitors as effective anti-TB drugs, it is necessary to have an understanding of the binding sites of Asp kinase. As no crystal structure of the enzyme has yet been published, we built a homology model of Asp kinase using the crystallized Asp kinase from M. Jannaschii, as template structures (2HMF and 3C1M). After the molecular dynamics refinement, the optimized homology model was assessed as a reliable structure by PROCHECK, ERRAT, WHAT-IF, PROSA2003 and VERIFY-3D. The results of molecular docking studies with natural substrates, products and feedback inhibitors are in agreement with the published data and showed that ACT domain plays an important role in binding to ligands. Based on the docking conformations, pharmacophore model can be developed by probing the common features of ligands. By analyzing the results, ACT domain architecture, certain key residues that are responsible for binding to feedback inhibitors and natural substrates were identified. This would be very helpful in understanding the blockade mechanism of Asp kinase and providing insights into rational design of novel Asp kinase inhibitors for M.tuberculosis.     

Structure of glutathione S-transferase of the filarial parasite Wuchereria bancrofti: a target for drug development against adult worm

A three dimensional structural model of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. The three dimensional X-ray crystal structure of porcine -class GST with PDB ID: 2gsr-A chain protein with 42% sequential and functional homology was used as the template. The model of wbGST built by MODELLER6v2 was analyzed by the PROCHECK programs. Ramachandran plot analysis showed that 93.5% of the residues are in the core region followed by 5.4 and 1.1% residues in the allowed and generously allowed regions, respectively. None of the non-glycine residues is in disallowed regions. The PROSA II z-score and the energy graph for the final model further confirmed the quality of the modeled structure. The computationally modeled three-dimensional (3D) structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668). 1SFM was used for docking with GST inhibitors by Hex4.2 macromolecular docking using spherical polar Fourier correlations.Figure: A three-dimensional (3D) structure of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. This modeled 3D structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668).     

来源于克雷伯氏菌的1,3-丙二醇氧化还原酶的同源建模

用Swiss—Model和Modeller对来源于Klebsiella pneumonide的1,3-丙二醇氧化还原酶（PDOR）进行三级结构建模,并对所得的6个目标模型进行评价和比较,从中选择最好的一个模型,预测了辅酶NADP＋和Fe2＋在PDOR结构空间的近似位置,并定位了与NADP^＋和Fe^2＋作用的相关残基。     

Inhibitory Potential of a Designed Peptide Inhibitor Based on Zymogen Structure of Trypsin from Spodoptera frugiperda: In Silico Insights

Spodoptera frugiperda (J.E. Smith) is an invasive pest in agriculture. It can potentially damage yield resulting severe crop losses and subsequently significant economic damage each year. S. frugiperda is predominantly managed using traditional chemical pesticides. Accordingly, sustainable alternatives such as digestive enzymes inhibitors can be used as an efficient pest management that protects the environment. This contribution aims to examine the pro-region of S. frugiperda trypsin as specific inhibitor of the pest protease enzyme. Structural modeling in conjunction with molecular docking simulations were conducted to design a peptide sequence with the best docking scores and strong binding energy to the target enzyme. The structural models of six pro-peptides were produced based on modification of 7-amino acids of the pro-region of S. frugiperda trypsin. VERIFY_3D, ERRAT, PROCHECK, PROSA and WHAT-IF scores validated the reliability of the predicted model of S. frugiperda trypsin. Molecular docking studies between the six designed inhibitor peptides and the predicted model structure at three different pH conditions were carried out. Data revealed that VPSNPQR at pH 11.0 with the best docking score, the lowest binding energy (ΔG) and dissociation constant (K_d) indicated a potent binding affinity towards S. frugiperda trypsin’s active site. Moreover, the peptide showed a weak potential for interaction with the human trypsin. The results indicated the importance of computational studies in design and selection of inhibitor peptides against target enzymes. Such inhibitors can be used for S. frugiperda control, which can be further applied in other pest management programs.

Graphical Abstract

Docking simulations between the pro-peptide inhibitor and Spodoptera frugiperda midgut trypsin confirmed the capacity of the designed pro-region in inhibiting the insect trypsin.

     

Sequence analysis and homology modeling of peroxidase from Medicago sativa

Plant peroxidases are one of the most extensively studied group of enzymes which find applications in the environment, health, pharmaceutical, chemical and biotechnological processes. Class III secretary peroxidase from alfalfa (Medicago sativa) has been characterized using bioinformatics approach Physiochemical properties and topology of alfalfa peroxidase were compared with that of soybean and horseradish peroxidase, two most popular commercially available peroxidase preparations. Lower value of instability index as predicted by ProtParam and presence of extra disulphide linkages as predicted by Cys_REC suggested alfalfa peroxidase to be more stable than either of the commercial preparations. Multiple Sequence Alignment (MSA) with other functionally similar proteins revealed the presence of highly conserved catalytic residues. Three dimensional model of alfalfa peroxidase was constructed based on the crystal structure of soybean peroxidase (PDB Id: 1FHF A) by homology modelling approach. The model was checked for stereo chemical quality by PROCHECH, VERIFY 3D, WHAT IF, ERRAT, 3D MATCH AND ProSA servers. The best model was selected, energy minimized and used to analyze structure function relationship with substrate hydrogen peroxide by Autodock 4.0. The enzyme substrate complex was viewed with Swiss PDB viewer and one residue ASP43 was found to stabilize the interaction by hydrogen bonds. The results of the study may be a guiding point for further investigations on alfalfa peroxidase.     

Exploring the structure of opioid receptors with homology modeling based on single and multiple templates and subsequent docking: A comparative study

Opioid receptors are the principal targets for opioids, which have been used as analgesics for centuries. Opioid receptors belong to the rhodopsin family of G-protein coupled receptors (GPCRs). In the absence of crystal structures of opioid receptors, 3D homology models have been reported with bovine rhodopsin as a template, though the sequence homology is low. Recently, it has been reported that use of multiple templates results in a better model for a target having low sequence identity with a single template. With the objective of carrying out a comparative study on the structural quality of the 3D models based on single and multiple templates, the homology models for opioid receptors (mu, delta and kappa) were generated using bovine rhodopsin as single template and the recently deposited crystal structures of squid rhodopsin, turkey β-1 and human β-2 adrenoreceptors along with bovine rhodopsin as multiple templates. In this paper we report the results of comparison between the refined 3D models based on multiple sequence alignment (MSA) and models built with bovine rhodopsin as template, using validation programs PROCHECK, PROSA, Verify 3D, Molprobity and docking studies. The results indicate that homology models of mu and kappa with multiple templates are better than those built with only bovine rhodopsin as template, whereas, in many aspects, the homology model of delta opioid receptor with single template is better with respect to the model based on multiple templates. Three nonselective ligands were docked to both the models of mu, delta and kappa opioid receptors using GOLD 3.1. The results of docking complied well with the pharamacophore, reported for nonspecific opioid ligands. The comparison of docking results for models with multiple templates and those with single template have been discussed in detail. Three selective ligands for each receptor were also docked. As the crystallographic structures are not yet known, this comparison will help in choosing better homology models of opioid receptors for studying ligand receptor interactions to design new potent opioid antagonists.     

In silico analysis of Myoglobin in Channa striata

Myoglobin is a cytoplasmic hemoprotein, expressed solely in cardiac myocytes and oxidative skeletal muscle fibers, that reversibly binds O₂ by its heme residue. Myoglobin is an essential oxygen-storage hemoprotein capable of facilitating oxygen transport and modulating nitric oxide homeostasis within cardiac and skeletal myocytes. Functionally, myoglobin is well accepted as an O₂- storage protein in muscle, capable of releasing O₂ during periods of hypoxia or anoxia. There is no evidence available regarding active sites, ligand binding sites, antigenic determinants and the ASA value of myoglobin in Channa striata. We further document the predicted active sites in the structural model with solvent exposed ASA residues. During this study, the model was built by CPH program and validated through PROCHECK, Verify 3D, ERRAT and ProSA for reliability. The active sites were predicted in the model with further ASA analysis of active site residues. The discussed information thus provides the predicted active sites, ligand binding sites, antigenic determinants and ASA values of myoglobin model in Channa striata.     

Probing the structure of Leishmania donovani chagasi DHFR-TS: comparative protein modeling and protein–ligand interaction studies

Dihydrofolate reductase (DHFR) has been used successfully as a drug target in the area of anti-bacterial, anti-cancer and anti-malarial therapy. It also acts as a drug target for Leishmaniasis. Inhibition of DHFR leads to cell death through lack of thymine (nucleotide metabolism). Although the crystal structures of Leishmania major and Trypanosoma cruzi DHFR-thymidylate synthase (TS) have been resolved, to date there is no three-dimensional (3D)-structural information on DHFR-TS of Leishmania donovani chagasi, which causes visceral leishmaniasis. Our aim in this study was to model the 3D structure of L. donovani chagasi DHFR-TS, and to investigate the structural requirements for its inhibition. In this paper we describe a highly refined homology model of L. donovani chagasi DHFR-TS based on available crystallographic structures by using the Homology module of Insight II. Structural refinement and minimization of the generated L. donovani chagasi DHFR-TS model employed the Discover 3 module of Insight II and molecular dynamic simulations. The model was further validated through use of the PROCHECK, Verify_3D, PROSA, PSQS and ERRAT programs, which confirm that the model is reliable. Superimposition of the model structure with the templates L. major A chain, L. major B chain And T. cruzi A chain showed root mean square deviations of 0.69 Å, 0.71 Å and 1.11 Å, respectively. Docking analysis of the L. donovani chagasi DHFR-TS model with methotrexate enabled us to identify specific residues, viz. Val156, Val30, Lys95, Lys75 and Arg97, within the L. donovani chagasi DHFR-TS binding pocket, that play an important role in ligand or substrate binding. Docking studies clearly indicated that these five residues are important determinants for binding as they have strong hydrogen bonding interactions with the ligand.     

Substrate docking and molecular dynamic simulation for prediction of fungal enzymes from Trichoderma species-assisted extraction of nanocellulose from oil palm leaves

Abstract

Fungi of the Trichoderma species are valued industrial enzymes in support of the ‘zero-waste’ technology to convert agro-industrial biomass into valuable products, i.e. nanocellulose (NC). In this study, an in silico approach using substrate docking and molecular dynamic (MD) simulation was used to predict the order of which the multilayers of cellulosic polymers, i.e. lignin, hemicellulose and cellulose in oil palm leaves (OPL) are degraded by fungal enzymes, endocellulase and exocellulase. The study aimed to establish the catalytic tendencies of the enzymes to optimally degrade the cellulosic components of OPL for high yield production of NC. Energy minimized endocellulase and exocellulase models revealed satisfactory scores of PROCHECK (90.0% and 91.2%), Verify3D (97.23% and 98.85%) and ERRAT (95.24% and 91.00%) assessments. Active site prediction by blind docking, COACH meta-server and multiple sequence alignment indicated the catalytic triads for endocellulase and exocellulase were Ser116–His205–Glu249 and Ser382–Arg124–Asp385, respectively. Binding energy of endocellulase docked with hemicellulose (?6.0 ? kcal mol^?1) was the most favourable followed by lignin (?5.6 ? kcal mol^?1) and cellulose (?4.4 ? kcal mol^?1). Exocellulase, contrarily, bonded favorably with lignin (?8.7 ? kcal mol^?1), closely followed by cellulose (?8.5 ? kcal mol^?1) and hemicellulose (?8.4 ? kcal mol^?1). MDs simulations showed that interactions of complexes, endocellulase–hemicellulose and the exocellulase–cellulose being the most stable. Thus, the findings of the study successfully identified the specific actions of sugar-acting enzymes for NC production.

Communicated by Ramaswamy H. Sarma     

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling,structure based pharmacophore,molecular docking,and molecular dynamics simulations

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.     

Homology modeling and assigned functional annotation of an uncharacterized antitoxin protein from Streptomyces xinghaiensis

Streptomyces xinghaiensis is a Gram-positive, aerobic and non-motile bacterium. The bacterial genome is known. Therefore, it is of interest to study the uncharacterized proteins in the genome. An uncharacterized protein (gi|518540893|86 residues) in the genome was selected for a comprehensive computational sequence-structure-function analysis using available data and tools. Subcellular localization of the targeted protein with conserved residues and assigned secondary structures is documented. Sequence homology search against the protein data bank (PDB) and non-redundant GenBank proteins using BLASTp showed different homologous proteins with known antitoxin function. A homology model of the target protein was developed using a known template (PDB ID: 3CTO:A) with 62% sequence similarity in HHpred after assessment using programs PROCHECK and QMEAN6. The predicted active site using CASTp is analyzed for assigned anti-toxin function. This information finds specific utility in annotating the said uncharacterized protein in the bacterial genome.     

Molecular docking studies of chloroquine and its derivatives against P23pro-zbd domain of chikungunya virus: Implication in designing of novel therapeutic strategies

The arthropod-transmitted chikungunya virus has emerged as an epidemic menace that causes debilitating polyarthritis. With this life-threatening impact on humans, the possible treatment requires to cure the viral infectivity. But, devoid of any vaccine against the chikungunya virus (CHIKV), there is a need to develop a novel chemotherapeutic strategy to treat this noxious infection. CHIKV carries highly compact P23^pro-zbd structure that possesses potential RNA-binding surface domains which extremely influences the use of RNA template during genome replication at the time of infection and pathogenesis. Therefore, computational approaches were used to explore the novel small molecule inhibitors targeting P23^pro-zbd domain. The tertiary structure was modeled and optimized using in silico approaches. The results obtained from PROCHECK (93.1% residues in favored regions), ERRAT (87.480 overall model quality) and ProSA (Z-score: −11.72) revealed the reliability of the proposed model. Interestingly, a previously reported inhibitor, chloroquine possesses good binding affinities with the target domain. In-depth analysis revealed that chloroquine derivatives such as didesethyl chloroquine hydroxyacetamide, cletoquine, hydroxychloroquine exhibited a better binding affinity. Notably, MD simulation analysis exhibited that Thr1312, Ala1355, Ala1356, Asn1357, Asp1364, Val1366, Cys1367, Ala1401, Gly1403, Ser1443, Tyr1444, Gly1445, Asn1459, and Thr1463 residues are the key amino acid responsible for stable ligand-protein interaction. The results obtained from this study provide new insights and advances the understanding to develop a new approach to consider effective and novel drug against chikungunya. However, a detailed in vivo study is required to explore its drug likeliness against this life-threatening disease.     

A comparative modeling and molecular docking study on Mycobacterium tuberculosis targets involved in peptidoglycan biosynthesis

An alarming rise of multidrug-resistant Mycobacterium tuberculosis strains and the continuous high global morbidity of tuberculosis have reinvigorated the need to identify novel targets to combat the disease. The enzymes that catalyze the biosynthesis of peptidoglycan in M. tuberculosis are essential and noteworthy therapeutic targets. In this study, the biochemical function and homology modeling of MurI, MurG, MraY, DapE, DapA, Alr, and Ddl enzymes of the CDC1551 M. tuberculosis strain involved in the biosynthesis of peptidoglycan cell wall are reported. Generation of the 3D structures was achieved with Modeller 9.13. To assess the structural quality of the obtained homology modeled targets, the models were validated using PROCHECK, PDBsum, QMEAN, and ERRAT scores. Molecular dynamics simulations were performed to calculate root mean square deviation (RMSD) and radius of gyration (Rg) of MurI and MurG target proteins and their corresponding templates. For further model validation, RMSD and Rg for selected targets/templates were investigated to compare the close proximity of their dynamic behavior in terms of protein stability and average distances. To identify the potential binding mode required for molecular docking, binding site information of all modeled targets was obtained using two prediction algorithms. A docking study was performed for MurI to determine the potential mode of interaction between the inhibitor and the active site residues. This study presents the first accounts of the 3D structural information for the selected M. tuberculosis targets involved in peptidoglycan biosynthesis.     

Evaluating protein structures determined by structural genomics consortia

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.     

Cα torsion angles as a flexible criterion to extract secrets from a molecular dynamics simulation

A multipolar, polarizable electrostatic method for future use in a novel force field is described. Quantum Chemical Topology (QCT) is used to partition the electron density of a chemical system into atoms, then the machine learning method Kriging is used to build models that relate the multipole moments of the atoms to the positions of their surrounding nuclei. The pilot system serine is used to study both the influence of the level of theory and the set of data generator methods used. The latter consists of: (i) sampling of protein structures deposited in the Protein Data Bank (PDB), or (ii) normal mode distortion along either (a) Cartesian coordinates, or (b) redundant internal coordinates. Wavefunctions for the sampled geometries were obtained at the HF/6-31G(d,p), B3LYP/apc-1, and MP2/cc-pVDZ levels of theory, prior to calculation of the atomic multipole moments by volume integration. The average absolute error (over an independent test set of conformations) in the total atom-atom electrostatic interaction energy of serine, using Kriging models built with the three data generator methods is 11.3 kJ mol^-1 (PDB), 8.2 kJ mol^-1 (Cartesian distortion), and 10.1 kJ mol^-1 (redundant internal distortion) at the HF/6-31G(d,p) level. At the B3LYP/apc-1 level, the respective errors are 7.7 kJ mol^-1, 6.7 kJ mol^-1, and 4.9 kJmol^-1, while at the MP2/cc-pVDZ level they are 6.5 kJ mol^-1, 5.3 kJ mol^-1, and 4.0 kJmol^-1. The ranges of geometries generated by the redundant internal coordinate distortion and by extraction from the PDB are much wider than the range generated by Cartesian distortion. The atomic multipole moment and electrostatic interaction energy predictions for the B3LYP/apc-1 and MP2/cc-pVDZ levels are similar, and both are better than the corresponding predictions at the HF/6-31G(d,p) level.     

Computational Analysis of N-acetyl transferase in Tribolium castaneum

N-acetyl transferase (NAT) is responsible to catalyze the transfer of acetyl groups to arylamines from acetyl-CoA. Aralkylamine Nacetyl transferase (AANAT), which belongs to GCN5-related N-acetyl transferase member, is a globular 23-kDa cytosolic protein that forms a reversible regulatory complex with 14-3-3 proteins, AANAT regulates the daily cycle of melatonin biosynthesis in mammals, making it an attractive target for therapeutic control of abnormal melatonin production in mood and sleep disorders. There is no evidence available regarding α and β subunits, active site and their ASA value in Dopamine N-acetyl transferase. Therefore, we describe the development of Dopamine N-acetyl transferase model in Tribolium castaneum. We further document the predicted active sites in the structural model with solvent exposed ASA residues. During this study, the model was built by CPH program and validated through PROCHECK, Verify 3D, ERRAT and ProSA for reliability. The active sites were predicted in the model with further ASA analysis of active site residues. The discussed information thus provides insight to the predicted active site and ASA values of Dopamine N-acetyl transferase model in Tribolium castaneum.