The use of the enzymatic hydrolysis of lignocellulose with subsequent fermentation to ethanol provides a green alternative for the production of transportation fuels. Because of its recalcitrant nature, the lignocellulosic biomass must be pretreated before enzymatic hydrolysis. However, the pretreatment often results in the formation of compounds that are inhibitory for the enzymes or fermenting organism. Although well recognized, little quantitative information on the inhibition of individual cellulase components by identified inhibitors is available.Trichoderma reesei cellobiohydrolases (CBHs) than cellobiose, which is one of the strongest inhibitors of these enzymes reported to date. Inhibition of endoglucanases (EGs) by IOS was weaker than that of CBHs. Most of the tested cellulases and hemicellulases were able to slowly degrade IOS and reduce the inhibitory power of the liquid fraction to some extent. The most efficient single enzyme component here was T. reesei EG TrCel7B. Although reduced by the enzyme treatment, the residual inhibitory power of IOS and the liquid fraction was strong enough to silence the major component of the T. reesei cellulase system, CBH TrCel7A.Strong cellulase inhibitors were separated from the liquid fraction of the hydrothermal pretreatment of wheat straw. HPLC and mass-spectroscopy analyses confirmed that the inhibitors were oligosaccharides  with a degree of polymerization from 7 to 16. The IOS are composed of a mixture of xylo- (XOS) and gluco-oligosaccharides (GOS). We propose that XOS and GOS are the fragments of the xylan backbone and mixed-linkage β-glucans, respectively. The IOS were approximately 100 times stronger inhibitors for The cellulase inhibitors described here may be responsible for the poor yields from the enzymatic conversion of the whole slurries from lignocellulose pretreatment under conditions that do not favor complete degradation of hemicellulose. Identification of the inhibitory compounds helps to design better enzyme mixtures for their degradation and to optimize the pretreatment regimes to minimize their formation. O and/or 3-O with arabinose (Ara), glucuronic acid, and acetic acid free) was measured from the inhibitory strength against TrCel7A on MUL using the previously quantified IC50 value of 0.31 μM and the equation for competitive inhibition in the conditions of [MUL] < <KM(MUL):The inhibition strength of cellulases measured on low-Mw model substrates does not necessarily reflect the inhibition strength on cellulose substrates . Therefoll known -40. Possvi and v0 are the initial rates of MUL hydrolysis measured in the presence and absence of IOS containing supernatants, respectively. Thus, what is measured here is the binding of the inhibitory strength against TrCel7A to cellulose. The distribution between the free and cellulose-bound inhibitory strength of IOS is shown in Figure 14C-BC, the maximum binding capacity of 42 μmol IOS g-1 cellulose with 15 μM half saturating [IOS]free was found. The binding capacity of IOS to the 14C-amorphous cellulose was approximately 4 times lower than that to 14C-BC , in the presence of IOS was followed  versus [IOS], where DIOS and DIOS=0 represent the degree of conversion of 14C-BC in the presence and absence of IOS, respectively  is the IC50 for cellobiose  was omitted from Equation 3 in the analysis of the data. Although TrCel6A was more resistant to IOS inhibition than TrCel7A, the IOS were also approximately 100 times stronger inhibitors than cellobiose for TrCel6A 8/(Xyl)9/(Xyl)10 in a 1/1/1 ratio)  glucose with a specific activity of 262 mCi mmol-1 was from Hartmann Analytic GmbH. The scintillation cocktail was from Merck.The LF was kindly provided by Jan Larsen from Inbicon . Glucose, MUL, MUG, pNPL, Novozyme®188, Celluclast®, and BSA were purchased from Sigma-Aldrich. The lichenase was from Megazyme . Cellobiose (≥ 99%) was from Fluka. D-[U-14C-BC was prepared by laboratory fermentation of the Gluconobacter xylinum strain ATCC 53582 in the presence of a [U-14C] glucose carbon source [14C-BC had a specific activity of 450,000 DPM mg-1. 14C-amorphous cellulose was prepared from 14C-bacterial microcrystalline cellulose by dissolution and regeneration from phosphoric acid [n source ,64. 14C-ric acid . The totTrCel7A, TrCel6A, TrCel7B, TrCel5A, and TrCel12A were purified from the culture filtrate of T. reesei QM 9414 as described previously [N188BG was purified from Novozyme®188 according to [TaXyn10A heterologously expressed in the T. reesei strain lacking the genes of four major cellulases was kindly provided by Terhi Puranen from Roal Oy . For purification of TaXyn10A, the above culture filtrate was heat treated in 50 mM sodium phosphate buffer with a pH of 6.0 for 2 h at 60°C to sediment the background T. reesei enzymes [TrXG (TrCel74A) and TrAXE were gifts from Matti Siika-aho from VTT . The lichenase (Megazyme) was used as purchased.eviously -68. N188rding to . The cul enzymes . Thermomg) and pressed through a 0.2 μm PVDF filter. SEC was performed using the ÄKTA Explorer chromatography system  at 4°C. The column was equilibrated and eluted with water at a flow rate of 0.5 ml min-1. The fractions (2.5 ml) were analyzed for the concentration of reducing groups using the modified BCA method [TrCel7A on MUL. The fractions from SEC were also analyzed by HPLC. HPLC was performed using a Prominex HPLC system (Shimadzu) equipped with an Aminex HPX-87P  column and a refractive index detector RID-10A (Shimadzu). The column temperature was kept at 80°C, the flow rate was 0.6 ml min-1, and the eluent was water. The fractions from HPLC (0.3 ml) were also collected and analyzed for the reducing groups and for the inhibitory strength against TrCel7A on MUL. Selected fractions from SEC were pooled, concentrated under reduced pressure, and purified on HPLC using the above-described conditions. HPLC fractions with retention times between 8–10 min were pooled, concentrated under reduced pressure, and stored at −18°C before use. This HPLC purified material is referred to as IOS throughout the study.Before its application to the SEC column (Toyopearl HW40-F), the LF was centrifuged  equipped with a nanoelectrospray ion source  using Proxeon medium nanospray needles. A 5 μl sample of IOS (100 μM) in 10 mM ammonium acetate (pH 5) was introduced into the LTQ Orbitrap mass spectrometer operating at a 180°C capillary temperature, a 105.0 V tube lens voltage, and a 1.0 kV needle voltage. Spectra (10 scans) were acquired in positive ion mode in profile (m/z 500 – 2000) with a resolution of 100000 FWHM.For deacetylation, IOS were incubated in 50 mM NaOH at 4°C overnight. The pH was adjusted to 6.0 by adding 0.5 M acetic acid. Deacetylated and neutralized IOS were purified by HPLC (see purification of IOS) before ESI-MS analysis.-1) at pH 5 and 35°C. The concentration of MUL was 5 μM and 20 μM in the case of experiments with TrCel7A and TrCel7B, respectively, and that of the inhibitor was varied as appropriate. Reactions were initiated by the addition of the enzyme to a final concentration of 10 nM and stopped by the addition of 1.0 M ammonium hydroxide . The released MU was quantified by the fluorescence using a Hitachi F-4500 fluorimeter with excitation and emission wavelengths set to 360 nm and 450 nm, respectively. The hydrolysis time was selected so that all rates of MU liberation correspond to the initial rates.All experiments were performed in 1.5 ml microcentrifuge tubes in 50 mM sodium acetate  at pH 5 and 35°C for 30 min. The concentration of 14C-BC and 14C-amorphous cellulose was 0.25 g l-1 and 0.5 g l-1, respectively. Cellulose was separated by centrifugation, and supernatants were analyzed for their inhibitory strength against TrCel7A on MUL, as described above. The concentration of IOS in the supernatant was calculated from the inhibitory strength and the IC50 value of 0.31 μM for IOS inhibition of TrCel7A using Equation 2. The concentration of IOS bound to cellulose was found as the difference between the total concentration of IOS and that in the supernatant.IOS (0–100 μM on a reducing groups basis) were incubated with -1) at 35°C. Inhibition of TrCel7A was assessed by following the synergistic hydrolysis of 14C-BC. For that, 14C-BC (0.25 g l-1) was pre-incubated (without stirring) with IOS at selected concentrations at 35°C for 30 min. Hydrolysis was initiated by the addition of the mixture of TrCel7A and TrCel5A to the final concentrations of 0.25 μM and 0.025 μM, respectively. In the case of experiments with no added IOS, the reaction mixtures were supplied with N188BG (0.06 μM). At selected times, 0.2 ml aliquots were withdrawn and added to 20 μl 1 M NaOH to stop the reaction. Residual cellulose was separated by centrifugation , and radioactivity in the supernatant was quantified using a liquid scintillation counter. The degree of cellulose degradation was found from the ratio of radioactivity in the supernatant to the total radioactivity in the hydrolysis mixture. In the case of the inhibition of TrCel6A, the same procedure and conditions were followed, except that TrCel5A was omitted.All experiments were performed in 50 mM sodium acetate buffer, pH 5.0, containing BSA (0.1 g l14C-amorphous cellulose. 14C-amorphous cellulose (0.5 g l-1) was pre-incubated (with shaking at 700 rpm) with IOS at selected concentrations at 35°C for 30 min. Hydrolysis was initiated by the addition of EG to a final concentration of 2.5 nM, 5.0 nM, and 50 nM for TrCel7B, TrCel5A, and TrCel12A, respectively. The rest of the procedure was identical to that described above for CBHs.IOS inhibition of EGs was assessed on -1) at 35°C. IOS (100 μM on a reducing groups basis) were treated with different enzymes for 2 h. Reactions were stopped by heating at 100°C for 20 min. Heat-inactivated enzymes were pelleted by centrifugation , and aliquots of supernatants were used to quantify the residual inhibitory power against TrCel7A on MUL (see inhibition of TrCel7A on MUL). Enzymes treated identically but without the presence of IOS were used for background measurements in the determination of the activity of TrCel7A on MUL. In the case of the treatment of the LF, the remaining solids in the LF were separated by centrifugation  and filtration through a 0.2 μm PVDF filter. The concentration of the LF in the enzymatic treatment was as provided (Table TrCel7A (21 μM), TrCel6A (7 μM), TrCel7B (3.5 μM), TrCel5A (3.5 μM), TrCel12A (3.5 μM), N188BG (1.75 μM), TaXyn10A (1.75 μM), TrAXE (0.1 μM), TrXG (0.1 μM), and lichenase (0.1 μM). Cellulase mixtures were loaded on an activity  or on a mg protein (for Thermomix) basis. In the case of the treatment of IOS with N188BG and TaXyn10A, a series with varying enzyme concentrations (between 1.0 nM and 1.75 μM) was also made.All of the experiments were performed in 50 mM sodium acetate buffer, pH 5.0, containing BSA (0.1 g lN188BG for 48 h before the inhibition studies. For the acid treatment, the LF was incubated with 2% sulfuric acid at 121°C for 20 min, followed by neutralization with NaOH before inhibition studies on 14C-BC (Figure In the case of the initial assessment of the inhibitory power of the LF (data in Figure 14C-labeled bacterial cellulose; CBH: Cellobiohydrolase; DIOS: Degree of conversion in the presence of IOS; DIOS=0: Degree of conversion in the absence of IOS; DM: Dry matter, DP, Degree of polymerization; EG: Endoglucanase; ESI-MS: Electrospray ionization mass spectroscopy; Glc: Glucose; GOS: Gluco-oligosaccharides; IOS: Inhibitory oligosaccharides; LF: Liquid fraction from hydrothermal pretreatment of wheat straw; MU: 4-methylumbelliferone; MUL: 4-methylumbelliferyl-β-lactoside; N188BG: β-glucosidase purified from Novozyme®188, pNPL, para-nitrophenole-β-lactoside; SEC: Size exclusion chromatography; TaXyn10A: Xylanase from Thermoascus aurantiacus; Tr: Trichoderma reesei; XG: Xyloglucanase; XOS: Xylo-oligosaccharides; Xyl: Xylose.Ac: Acetyl; Ara: Arabinose; AXE: Acetyl-xylan esterase, BSA, Bovine serum albumin; CB: Cellobiose; 14C-BC: The authors declare that they have no competing interests.All authors designed and performed the experiments. RK and PV wrote the paper. All authors read and approved the final manuscript.14C-celluloses in the absence and presence of IOS.Time courses of the hydrolysis of Click here for file


Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation.The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic  The desire to modulate protein function with small molecules that can be administered as drugs has led to a plethora of studies attempting to define and calculate the “druggability” of sites on a protein in vitro screening. More recently, quantitative predictors of cleft druggability have been devised et al. in silico screening starts with the selection of a single pocket from a single conformer.The search for suitable allosteric clefts requires consideration of functional relevance and druggability. Functional relevance is usually less obvious from structural snapshots for an allosteric site than an active site. It may be deduced experimentally by mutagenesis, or through observation of the binding site of known ligands. Druggability has traditionally been indirectly assessed by computational studies (docking) or 1-antitrypsin (A1AT), the archetypal member of the serpin (serine protease inhibitor) superfamily In this study we demonstrate how the approach of employing multiple protein conformers at the selection-of-pocket stage can be combined with predictions of druggability, to aid the identification of transient, novel druggable pockets often missed in single conformer approaches. Our study focuses upon αd (mean 1.01) We denote the eight top-ranking surface clefts identified by SiteMap Å3), and very hydrophobic  is small compared with the average volume of drug-binding sites , Lys380 (backbone oxygen O acts as donor to 7 ligands) and His269 (ND1 acts as donor to 4 ligands). Moreover two areas within the site are often occupied by hydrophobic rings. These findings can be used to build a pharmacophore template for further searches of additional ligand databases.Overall the sites identified by SiteMap analysis demonstrated specificity even when probed with small fragment compounds, that are intrinsically more likely than larger compounds to bind promiscuously in silico with relatively poor predicted binding energies , indicating poor potential for drug development. However, promisingly, low energy outliers in these distributions achieve scores in the range of −7.5 to −8.8 kcal/mol for each site  are considered unfavourable as leads for drug design we also considered the 10 best performing ligands in terms of their ligand efficiency for each site. Ligand efficiency is traditionally defined as the docking score divided by the number of heavy atoms, but here we are referring to the natural logarithm scaling of the ligand efficiency, a metric that the Schrödinger developers suggest gives a better fit to experimental data. Within these best ligand efficiency sets we then selected the ligand with the best overall docking score to avoid overcompensating for size at the expense of docking score. Some of these (‘best-efficient’) ligands conserved interactions that are important in the binding of the highest scoring ligand overall . Thus, within the I site, hydrogen bonding of a charged amine group to the backbone of Ser140 was seen with both the best-efficient (DrugBank ID: DB00610) and best-overall (DB07124) ligands. Similarly the aromatic ring of the most efficient ligand for the I site (DB03329) overlaps with the positions of all other aromatic rings in the top 10 scoring ligands.For a flexible protein, like A1AT, rigid receptor docking is likely to miss many ligands that require small structural rearrangements in order to fit some of the smaller sites. In this case, docking calculations that allow for induced fit are recommended. We experimented with the induced fit protocol mostly with the I site, as this is the smallest of all and more likely to benefit from such a protocol, whereby ligands are docked into sites in a soft mode (repulsive forces are very much reduced), then the protein and the ligand are allowed to relax, and finally the ligand is redocked to the relaxed conformer of the receptor. We found that the induced fit docking protocol dramatically changes the results for some ligands.d prediction in the nanomolar range  is a natural compound of mint oils that scores reasonably well  in the original docking trial (with the receptor kept rigid) and, more importantly, ranks eighth out of the 10,000 reported ligand poses. Following induced fit docking, this score improves dramatically to −8.5 kcal/mol, aided by a small rearrangement of His269, which results in an additional hydrogen bond to the ligand. Thymol is another interesting hit against site I. In preliminary docking experiments (without prior protein refinement in Glide) we observed that thymol was the fourth best scoring molecule against this site. Thymol is a natural product of thyme and a known protein binder ar range .Another interesting observation relating to the I site is that there seems to be a transient hydrophobic pocket next to the originally identified pocket, which, in some conformers, is merged with that site. This can allow larger ligands with two rings connected by a flexible linker to dock in a way that takes advantage of both hydrophobic patches. For example, when docking DrugBank entry DB07263 using the induced fit protocol, we can obtain the pose depicted in A small number of hits from our docking studies were assayed using thermal shift experiments (ThermoFluor). All compounds selected for testing had shown promising docking scores either using the induced fit protocol, or in preliminary docking studies using rigid receptor docking. in silico screens to identify the most promising target site on a protein, commonly based upon a single structural snapshot. Such pockets are of particular interest in cases where the protein target undergoes large conformational variations, as in the archetypal serpin A1AT. Here, we present an alternative methodology that characterizes more pockets, and simulates their solution behaviour in greater detail than a single conformer/single pocket approach.Transiently druggable pockets on the surface of proteins can be missed by in silico attempts to identify small molecules that can act as inhibitors of polymerisation have concentrated on what we refer to in this paper as the A site, a large cavity between the ß-sheet A and the D-helix in vitro, and increases secretion in a mammalian cell model of disease in silico research focusing on this site have led to ligands that blocked polymerisation of A1AT in vitroin silico screens.In this study we focused our efforts on identifying druggable pockets on the surface of native A1AT that could be the targets of inhibitors blocking polymerization. Previous We expected to see clues of the existence of alternative potentially druggable sites in the available crystal structures of A1AT. Indeed, crystal structures of A1AT allow us a glimpse of the variety of conformations sampled by this protein. This inherent flexibility, intimately linked to function, is dispersed across the whole protein in silico induced-fit type screening within high throughput studies, where keeping the number of residues that are allowed flexibility small is necessarily limited. We believe the combination of druggability and variability predictions could be very interesting for many proteins that are difficult targets due to their flexibility. We are currently pursuing an automated combination of these predictions in our laboratory.The variability of each pocket was further probed using Provar, a method recently developed in our lab. Provar allows us to highlight and readily visualize residues responsible for the variability of a protein pocket across an ensemble of conformers. This information allows us an insight into the origin of the pocket variability and can assist in vitro and in mammalian cells The conformers in which each pocket achieved its highest druggability score were selected for docking studies, employing the publicly available database of marketed and experimental drugs DrugBank. These docking experiments highlighted several low molecular weight ligands that scored well on individual sites and were specific for these sites. Promisingly, several of the docking scores of our best-scoring ligands at the novel targets are comparable to the docking score of compound “CG”, a molecule previously identified as an inhibitor of A1AT polymerization in vitro studies. A small but very hydrophobic site (site I) that is present in about one fifth of our in silico-produced conformers was initially identified by SiteMap in three crystal structures, carrying the Ala70Gly mutation. This mutation is known to increase the stability of the stressed state, oppose the propensity to polymerisation and retain the functionality of the protein, while inducing widespread changes in cavity sizes within A1AT. Further analysis showed that this site is present in all other crystallographic structures but it is not solvent accessible. Crucially it became solvent accessible in about one fifth of our conformers generated in silico from the wild type native structure 1qlp, indicating that transient solvent accessibility may be feasible in solution in the absence of mutations. Site I is therefore a potential ligand target site with some characteristics suggesting that ligand binding might induce local, stabilising conformational change. Support for this idea comes from mutagenesis studies that showed 13 mutations in the region of the I site (e.g. the space-filling mutation His269Tyr) increased stability, while preserving inhibitory function Our approach has also revealed sites that could become the focus of future The channel of interconnecting sites B,C and E is also potentially interesting as the druggability scores for these pockets are persistently high, and some of our best docking scores are results of docking ligands to these sites. However, the obvious caveat of docking to this site is that many of the ligands will interact with the RCL loop, thus potentially interfering with A1AT’s antiprotease function. Indeed, mutation experiments have shown that the sequence between Arg196 to Glu279 can carry 9 mutations that increase the stability of the A1AT, but in several cases also decrease functional activity in vitro observations of drug-like ligand binding. They do not guarantee in vitro binding affinity in a new system but provide a reasonable starting point for docking studies in silico and in vitro. Finally, our docking calculations are subject to many approximations. They should therefore be considered as a screening tool, based upon goodness of fit of certain ligands against each site, to enrich true positive hits among the ligand rankings.There are obvious caveats in the approach presented here. The conformers generated using CONCOORD may be artificially produced but appeared realistic when assessed for geometry and packing by the structure validation server PROSESS in silico hits targeted at the I site and assayed by ThermoFluor alter the melting temperature of A1AT. These data are consistent with an in vitro interaction and indicate that further experiments are warranted to pursue these ligands and I site targeting.In summary, we have presented a promising strategy that utilizes multiple protein conformer structures to identify both persistent and transiently druggable surface pockets. We have applied this approach to A1AT, whose conformational flexibility suggests that the usual one conformer/one pocket approach to screening is likely to be inadequate. We have found that pockets on the surface of A1AT show considerable variability across conformers, and we have also identified a new transient pocket with druggability potential. Some of our docking hits to this and other sites are at least as good or better than a previously identified promising lead. Finally, an unusually high proportion of a limited set of our A1AT structures were retrieved from the PDB using the SAS tool available in PDBsum One protein chain from each crystal structure in our dataset was prepared using the Protein Preparation Wizard protocol available in the Schrödinger suite . Ligands, waters and other co-crystallised agents were deleted and hydrogen atoms were added. The protassign script was used to optimise intramolecular contacts. The impref script was used to perform a restrained minimisation of the protein, with a maximum root mean square deviation (RMSD) of 0.30 Å.All structures were superimposed on the native wild type protein (1qlp) using the structalign utility from Schrödinger. The site recognition software SiteMap 2.3  was run on all 8 crystal structures to identify the top 10 ranked potential ligand-binding sites. SiteMap uses an algorithm analogous to the Goodford’s GRID algorithm The following physicochemical properties of the sites were calculated by the SiteMap program: size, volume, degree of enclosure/exposure, degree of contact, hydrophobic/-philic character, hydrophobic/-philic balance and hydrogen-bonding possibilities (acceptors/donors). In addition, SiteMap calculates two scores for each site. The SiteScore is defined as:n  =  the number of site points (capped at 100),e  =  enclosure,p  =  hydrophilicity of the site (capped at 1.0).n, e and p are defined as above, except that p is uncapped in this case. The developers of SiteMap suggest that a cut-off in the SiteScore of 0.80 can be used to differentiate between drug-binding and non-drug-binding sites, with scores higher than 1.0 being indicative of highly promising sites The druggability score, Dscore, is defined as:k was within 3.75 Å of the geometric centre of any site s  then site k was assigned the letter of the site s (i.e. the two sites were thought to coincide). This cut-off is strict and it was chosen after manual inspection of several cases where sites were very close to each other, but where it was still possible to discriminate between them. Sites C and E overlap in many conformers and in these cases they were assigned the label “C_E”. If the calculated distances for a new site were between 3.75 and 10 Å, the sites were inspected and assigned manually. If all distances were above 10 Å, the site was categorised as being new. Inspection of all “new” sites found in conformers of 1qlp led to approximately half of these sites being reassigned to one of the original nine sites (A to I). The remaining unassigned sites included mostly low-scoring sites, which were ignored in the present analysis.Nine sites were identified in our dataset of crystal structures of A1AT. These sites were labelled A to I. The geometric centre of each site as seen in the native wild type protein (1qlp), or, in the case of the I site, as seen in the structures bearing the Ala70 to Gly mutation , was calculated and it was used to identify sites in all other crystal structures and computationally produced conformers. This was done as follows: If the geometric centre of a site CONCOORD 2.0 http://prosess.ca. We have evaluated the quality of the CONCOORD conformers using the PROSESS server For each of the 100 CONCOORD conformers potential druggable sites were identified using SiteMap 2.3, as detailed previously. The SiteMap output files were then merged into single PDB files containing all predicted site sphere coordinates and were used as input to our in-house pocket variability visualisation method Provar. The Provar method is explained briefly here: For each conformation, residues within 3.75Å of any SiteMap sphere were considered as being pocket-lining and assigned a score of 1, all other residues were assigned a score of 0. These scores were summed across all conformations and divided by the number of conformers (100) to assign each residue a probability value representing the likelihood that it borders a predicted site. These values were written to the B-factor column of the PDB file (1qlp), and results were displayed using Chimera. Residue atoms and ribbons were rendered on a continuous colour scale from white  to red .Each of the nine sites (A to I) was used as a target for docking small molecules. For each site, the CONCOORD conformer that was selected to dock to was the one with the highest volume among the ones with the top five SiteScores as predicted by SiteMap. This selection was justified on the grounds that the highest SiteScore was not always associated with the largest cavity, but in rigid receptor docking a larger cavity, which allows more room for ligands to bind can potentially make up for the lack of side-chain flexibility during docking. Receptor grids were calculated with Glide , keeping default settings. The grid box was centred on the calculated geometric mean of the particular site. The box side lengths were set to the maximum value (14 Å).All ligand libraries used in this study were prepared using LigPrep . The preparation involved the generation of up to 32 stereoisomers (where these were not defined), tautomers, and protonation states corresponding to a pH of 7±2 (using epik), as well as an energy minimisation of the 3D structure using the OPLS2005 force field. The DrugBank 3.0 Glide with standard precision (SP) scoring was used for docking. Epik 2.0 state penalties were used in the final scoring. The highest scoring pose per ligand was kept and post-docking minimisation was switched on.−1 of the top 20 structures.A small number of molecules were selected for induced fit docking (IFD). All these molecules had shown promising Glide SP scores in preliminary docking trials, but some had poor scores following the inclusion of a protein preparation step. This suggested that IFD might be able to restore or even improve on the original scores, as it allows the protein side chains to optimise their position in the presence of the ligand. The IFD protocol  available within the Schrödinger suite was employed We applied the IFD protocol to a small selection of ligands docked in the I and C sites. This procedure was also applied to dock the CG compound http://cran.r-project.org/doc/FAQ/R-FAQ.html).All figures depicting A1AT, except −1 of A1AT, 1 mM of compound giving a final DMSO concentration of 5%, to which 1 µL SYPRO Orange (1:200 dilution) was added. Furthermore, the influence of DMSO and A1AT concentration on the thermal shift were analysed. The DMSO concentration was varied to 5%, 10% and 15% and the concentration of A1AT from 1 mg.mL−1 to 5 mg.mL−1. Each trial was repeated 6 times . The starting temperature for each run was 10°C increasing to 95°C in 0.5°C steps.The ThermoFluor  assay was performed using the iQ5 Real Time detection System (Bio-Rad – PCR Machine). Protein unfolding was monitored by measuring the fluorescence of the solvatochromic fluorescent dye SYPRO Orange, signalling unfolding of the protein. The compounds to be screened were dissolved in 100% dimethyl sulfoxide (DMSO) to give a stock solution of 20 mM. The assay was performed in 96- well plates, each well totalling a volume of 25 µL. Every assay had a final concentration of 1 mg.mLFigure S1Exploration of conformational space of A1AT using CONCOORD. CONCOORD-generated conformers from a native wild type A1AT structure ((PDB: 1qlp). (A) All 100 conformers used to analyse druggability of sites and their occurrence. (B) The 7 structures used for docking to sites A–I; colours for conformers are: white (site G), magenta (sites E and F), cyan (site I), yellow (sites A and C), red (site B), blue (site H), green (site D). (C) Three selected conformers depicting the extent to which structural variation was simulated.(TIF)Click here for additional data file.Figure S2A channel of interconnecting pockets on the surface of A1AT. (A) A channel of interconnecting surface pockets (blue spheres) defined by the RCL at the top and the H-helix at the bottom can be seen in several in silico produced A1AT conformers. (B) This channel is split up into separate sites in most conformers: B (cyan), E (fuchsia), I (yellow). These subsites themselves occasionally overlap as in the case shown here, e.g. site E can “spill into” the spaces usually occupied by sites I and B.(TIF)Click here for additional data file.Figure S3Site specificity of high-scoring fragment molecules. Red diamonds represent the docking scores for the top 5 scoring fragments for each of the sites A, BCE, D, FH, G, and I. The boxplots summarise the corresponding (merged) distributions of docking scores for the same five fragments docked to all other sites.(TIF)Click here for additional data file.Figure S4Thermal shift and melting temperature assays for A1AT incubated with selected ligands. Fluorescence-based (Thermofluor) thermal shift assay curves for A1AT incubated with small molecule ligands. Only ligands with significant thermal shifts are shown. Representative curves obtained in the presence of these ligands ) are shown in plots A to D . The mean ΔTm is shown for A1AT incubated with each ligand: (A) 5% DMSO control, (B) 4-nitrocatechol, (C) 2,6-diisopropylphenol, (D) thymol. (E) Mean melting temperatures and standard deviations for A1AT incubated with these three ligands (red) or 5% DMSO control (grey).(TIF)Click here for additional data file.Table S1Overall quality results for crystal structures and in silico conformers of A1AT selected for docking assessed by the PROSESS server (http://prossess.ca).(DOC)Click here for additional data file.Table S2Results for top-ranking fragments against each of the sites A–I on A1AT. The ZINC molecule identification codes and Glide SP docking score  for each of the five top-ranking fragments docked to sites on A1AT are listed. Results for sites B, C, E and F, H are merged.(DOC)Click here for additional data file.


Eight months after surgery, vertebral units with the screw rod constructs were collected. After CT scan, the soft and bony tissues around the screws were examined grossly and histologically. As a result, none of the screws broke during the endurance test stressing. The mean amount of abrasion wear was 0.0338 g. In the resected mini pig section, though zygapophyseal joints between fixed-head screws showed bony union, the amount of callus in the zygapophyseal joints connected with mobile-head screws was small, and joint space was confirmed by CT. No metalloses were noted around any of the screws. Novel screws were suggested to be highly durable and histologically safe.To prevent adjacent disc problems after spinal fusion, a pedicle screw with a mobile junction between the head and threaded shaft was newly developed. The threaded shaft of the screw has 10 degrees mobility in all directions, but its structure is to prevent abnormal translation and tilting. This screw was evaluated as follows: (1) endurance test: 10 Adjacent disc problems after spinal fusion have been considered unavoidable, and the overall annual incidence and predicted 10-year prevalence of further surgery are 2.5% and 22.2%, respectively  and variThe new pedicle screw is manufactured, which is made of titanium alloy and has a mobile polyaxial structure at the junction between the head and threaded shaft . BecauseDimples were made on the contact surface of the thread shaft at the junction of the screw to contain the abrasion wear generated after implantation Figures  and 2. T6 times, and the room temperature was adjusted to 25°C. Three screws were similarly tested, whether breakage occurred or not, and the amounts of abrasion powder were evaluated. The amount of abrasion wear was calculated by weighing the screw before and after the fatigue test. After durability testing, the screws were washed with acetone and weighed on an electronic balance AW320 (Simadzu). Three screws with no dimples on the contact surface were similarly tested.The mobile head of the novel pedicle screw was fixed in a servo-type fatigue tester from Shimadzu Corporation , and rotational stress was applied with a motor at an angle of ±5° relative to the threaded shaft, displacement of ±2.2 mm, and frequency of 5 Hz. The stress was applied 10Two 6-month-old domestic minipigs weighing 100 kg were anesthetized and screws were inserted into the bilateral pedicles at L3, L4, and L5 under fluoroscopic guidance. In one minipig, novel screws with a mobile head were inserted at L3, and conventional screws with a fixed head  were inserted at L4 and L5. In the other minipig, conventional screws with a fixed head were inserted at L3 and L4, and novel screws with a mobile head were inserted at L5 . The insNone of the screws tested broke in the predetermined number of trials. The mean amount of abrasion wear, determined by weighing before and after the fatigue test, was 0.0338 g , which wNo gross metalloses were noted around any of the screws . Bony unTo solve the problem of adjacent spinal segment disorder after spinal fixation, surgical procedures to treat spinal instability that preserve intervertebral mobility without fusion of vertebral segments have been developed –6. While


The responses of neurons in sensory cortex depend on the summation of excitatory and inhibitory synaptic inputs. How the excitatory and inhibitory inputs scale with stimulus depends on the network architecture, which ranges from the lateral inhibitory configuration where excitatory inputs are more narrowly tuned than inhibitory inputs, to the co-tuned configuration where both are tuned equally. The underlying circuitry that gives rise to lateral inhibition and co-tuning is yet unclear. Using large-scale network simulations with experimentally determined connectivity patterns and simulations with rate models, we show that the spatial extent of the input determined the configuration: there was a smooth transition from lateral inhibition with narrow input to co-tuning with broad input. The transition from lateral inhibition to co-tuning was accompanied by shifts in overall gain (reduced), output firing pattern (from tonic to phasic) and rate-level functions . The results suggest that a single cortical network architecture could account for the extended range of experimentally observed response types between the extremes of lateral inhibitory versus co-tuned configurations. The cerebral cortex contains a network of electrically active cells (neurons) interconnected by synapses, which may be excitatory (tending to increase activity) or inhibitory. Network activity, i.e., the ensemble of activity patterns of the individual cells, is driven by input from the sense organs, and creates an internal representation of features of the outside world. In auditory cortex, sound frequency (pitch) is encoded by the physical location of activity in the network. Thus, connections among cells at various distances may blur or sharpen the frequency representation. Recent work in living animals has yielded conflicting results: sharpening of responses via lateral inhibition in some cases, versus balanced excitation and inhibition (co-tuning) in others. It was previously unknown whether a single cortical network architecture could account for this spectrum of findings. Here, computer simulations based on experimental data reveal that this is indeed the case. Varying input to the network causes smooth transitions between lateral inhibition and co-tuning, accompanied by changes in the strength and timing of the responses. Diverse input-dependent response patterns in a single network may be a general mechanism enabling the brain to process a wide range of sensory information under various conditions. The firing properties and receptive fields of neurons in sensory cortex are heterogeneous and can vary both quantitatively and qualitatively with changing stimuli. The diverse responses are well exemplified in the primary auditory cortex (A1), where firing ranges from phasic (only at stimulus onset) to tonic  input onto inhibitory versus excitatory cells, or broader spread of intracortical inhibition versus excitation. Canonical circuits typically consist of excitatory pyramidal (P) cells and fast-spiking (FS) interneurons. In layers 2/3 and 4, both P and FS cells receive direct thalamic inputs in vivo.Here, we performed simulations in a large network model and with rate models to determine how the excitatory and inhibitory drive to P cells changes with stimulus. The patterns of connections and synaptic properties between excitatory P and FS inhibitory cells were based on experimental data. The simulations indicated that the same network generated both lateral inhibition and co-tuning: shifting between them is accomplished simply by changing the spatial distribution of the thalamic input. Therefore, a single, hardwired network potentially is consistent with many of the diverse response patterns previously reported The broad goal was to build a detailed model of the pattern of stimulus-driven cortical activity. For simplicity, the parameters of the model were taken from published Neurons in sensory cortex are connected to their neighbors with a relatively low probability. The connection rates decrease with distance between cells, as the local axonal and dendritic arborizations are confined within several hundred µm of the soma. In cortical layers 2/3 and 4, the thalamorecipient layers of auditory cortex, our experimental data on connection probability versus distance between somata for each connection type  were fitted with a Gaussian function . The radU and recτ, Supporting A, The synaptic and intrinsic membrane properties were also based on experimental data The intrinsic membrane properties of P and FS cells used in the simulations are listed in max each neuron can receive and by the standard deviation σ ; i.e., the thalamic afferents were maximally active here because the stimulus was assumed to represent the preferred frequency for the center cell. The amplitudes, time course, and short-term dynamics of thalamic inputs were adjusted separately for the P and FS populations . For simplicity, each input was modeled as a sequence of spikes arriving at a specified frequency . The FS inhibitory component rose steeply owing to the FS cells' high frequency firing responses to input.Each synaptic component increased with the number, Nc inputs . The excmax constant, widening the thalamic input from σ = 40 µm  shows that the network shifted progressively from the lateral inhibitory configuration (Winh/Wexc >1) to the co-tuned configuration (Winh/Wexc ∼1) (max (A plot of the ratio of the inhibitory to excitatory profile widths (WWexc ∼1) . These c∼1) , S2(x)) separated by different distances  to both excitatory and inhibitory cells was inherited directly from, and was therefore identical to, thalI (inhI) to excitatory cells involved several steps since the inhibitory cells must be activated. First, thalI was transformed with a threshold-linear function  of thalI changed. Plotting the ratio of the widths of excI and inhI (inh/wexcw) as a function of Nmax  and σ  revealed the regimes  followed by a regime where excI was slightly wider than inhI. With increasing Nmax , the ratio was initially less than one but grew as the inhibitory cells became more active. Taking a slice through the inh/wexcw surface  toward larger  σ values.For simplicity, the analyses assumed that the thalamic afferents were distributed equally to excitatory and inhibitory cells. Whether or not the P and FS cells have the same tuning properties in intact animals is unclear. To determine the effects of unequal tuning, the relative widths of thalamic inputs to P and FS were varied . The shimax  and σ. In the LIN regime (σ = 40 µm), firing was confined to a narrow band . The simulations also do not consider other types of interneurons and potentially important inputs from other cortical areas. Many of these issues can be circumvented if only the synaptic events and firing within the first 50 ms after the stimulus are considered. In the auditory system, as noted above, brief tone pips (25–50 ms) are often used to characterize the tuning and firing properties of neurons. As argued in the In addition, the model while incorporating many of the measured parameters is necessarily incomplete because several parameters - notably the spatiotemporal profile of thalamic inputs to P and FS, and sources of noise under  results –S5. Thein vivo whole-cell recordings from the auditory system of mice and rats in vivo experiments thus far have been with anesthetized animals. The evoked responses in awake animals are markedly different in vivo studies in anaesthetized animals using brief stimuli. However, the transition between lateral inhibition and co-tuning persists in the presence of background noise . There is some experimental support for this finding in auditory cortex A second implication of the model is that the magnitude of inhibition increases in parallel with the spread of thalamic input  and 6C. A third implication is that the thalamocortical terminal field widths will determine whether a cortical area is biased towards co-tuning or lateral inhibition. In rodent somatosensory and primate visual cortices, the spatial distribution of thalamic axons varies 6 fold in the thalamorecipient layers Fourth, whether the network is biased toward lateral inhibition or co-tuning will also depend on the dendritic and axonal arborizations of FS cells Finally, the fact that the relation between excitation and inhibition is malleable in a single network potentially provides a mechanism for modulating the response of the network to a variety of inputs and behavioral states. Recently, for example, the magnitudes of feedforward and lateral inputs in visual cortex were found to be modulated by stimulus contrast 3 and network was assumed to correspond to a volume (x by y by h) of 1185×1185×200 µm before compression to 2 dimensions (1185×1185 µm). In 2 dimensions, the probability that a reference neuron at x0, y0 is connected to its neighbors xi, yj is given by:d represents radial distance A represents peak probability, and σ represents spread of connectivity (see 2 goodness-of-fit tests).The network was a 2 dimensional sheet of 160×160 P and 32×32 of inhibitory FS cells . The denThe neurons were adaptive exponential integrate and fire units aEIF; . The aEIsyn, was described with an alpha function:The postsynaptic conductance, gin) of inputs and frequency Fin of each input to the network were Gaussian distributed in space (max = 25–150) firing at the maximum specified rate (Fmax = 50 Hz):The thalamic inputs to the network were drawn randomly from a set of simulated spike trains , inset. in space  so that ctr and yctr are the center of the network. Nin and Fin were adjusted so that the evoked firing rates of the P and FS cells were in the midrange of their respective F/I curves. The spike trains were used to calculate the composite synaptic currents generated in each P and FS neuron. Representative synaptic conductances and associated firing are shown in The evoked firing was quantified by calculating the number of spikes that occur within a 50 ms time window after the onset of the stimulus. This corresponded approximately to the peak of the post-stimulus time histogram (PSTH) compiled from the spike trains .inh(x)) and that of the thalamic synaptic inputs  to the excitatory and inhibitory cells are each Gaussian:The simplified network shown in inh and σthal are the standard deviations of the inhibitory to excitatory connection profile and the thalamic input, respectively. The spatial profiles of the excitatory (Iexc) and inhibitory input (Iinh) were calculated as described in exc, Finh,F in Hz) in terms of position (x) and time:The simulations in exc, τinhτ  is the Gaussian connectivity profile , wiw were the corresponding average unitary synaptic strengths S, was modeled as a Naka-Rushton function:in pA/Hz , and P, using an iterative search procedure.θ, and n  were fitFigure S1Effects of background noise. Simulations were performed with the network shown in A, dot rasters showing firing of P (top) and FS (bottom), cell populations. Injected noise amplitude was 1 nA (+/− standard deviation). B, Temporal profiles of synaptic conductances to P cells at the center of the network from thalamus (gray), neighboring P cells (cyan), and FS cells (red). C, Normalized spatial conductance profiles of composite excitatory (black) and inhibitory inputs (red) to P cell population for σ = 40 (top) and 110 µm (bottom). D, ratio of excitatory to inhibitory spatial halfwidths vs s for 3 noise levels.(TIF)Click here for additional data file.Figure S2Effects of background firing. Simulations were performed using steady-state values of synaptic depression/facilitation, assuming all neurons were firing spontaneously at different frequencies prior to the arrival of the stimulus. A, Spatial profiles of composite excitatory (black) and inhibitory (red) conductances evoked in P cells for input σ of 40 µm (left) and 110 µm (right). B, ratio of excitatory to inhibitory spatial halfwidths vs background firing rate for σ = 40 µm (circles) and 110 µm (squares).(TIF)Click here for additional data file.Figure S3Role of FS excitability in LIN-CON transition.A, simulations with FS cells with lowered threshold (−52 mV). i, dot rasters of P cell cells evoked with σ = 40 µm. Bottom shows poststimulus time histgram. ii, normalized spatial profile of excitatory (black) and inhibitory conductances evoked in P cells with σ = 40 µm (left) and σ = 110 µm (right). B, FS threshold set at −47 mV as in the main text. C, FS threshold set at -37 mV.(TIF)Click here for additional data file.Figure S4Role of FS threshold in LIN-CON transition.A, calculation of spatial profile of excitatory and inhibitory input to P cells is as in B, without the threshold, the surface describing the ratio of excitatory to inhibitory widths approaches 1 asymptotically as σ increases.(TIF)Click here for additional data file.Figure S5Effects of differences in spatial inputs to excitatory and inhibitory cells.A–C, changes in the ratio of inhibitory to escitatory widths surface as the thalamic input to inhibitory cells was made broader than that to excitatory cells. See Supporting (TIF)Click here for additional data file.Figure S6Transition between lateral inhibition and co-tuning with non-Gaussian connectivity schemes. A, left, plots of ratio of widths of inhibitory to excitatory current to P cells (Winh/Wexc) versus input width (σ), for Nmax = 10, 20, or 30, in the rate-based model  and broad input . B, corresponding data for connectivity based on a quadratic model; C, binomially distributed connectivity.(TIF)Click here for additional data file.Table S1Parameters of adaptive exponential integrate-and-fire cells.(PDF)Click here for additional data file.Table S2Parameters governing dynamic properties of EPSPs and IPSPs.(PDF)Click here for additional data file.Table S3Network parameters for the firing rate model.(PDF)Click here for additional data file.Table S4Unitary response amplitudes for the firing rate model.(PDF)Click here for additional data file.Text S1Additional methods and results.(PDF)Click here for additional data file.


Brugia malayi (Bm-Aspin) makes it interesting to study because of the fact that the filarial parasite never encounters the host digestive system. Here, the aspartic protease inhibition kinetics of Bm-Aspin and its NMR structural characteristics have been investigated. The overall aim of this study is to explain the inhibition and binding properties of Bm-Aspin from its structural point of view. UV-spectroscopy and multi-dimensional NMR are the experiments that have been performed to understand the kinetic and structural properties of Bm-Aspin respectively. The human aspartic proteases that are considered for this study are pepsin, renin, cathepsin-E and cathepsin-D. The results of this analysis performed with the specific substrate [Phe-Ala-Ala-Phe (4-NO2)-Phe-Val-Leu (4-pyridylmethyl) ester] against aspartic proteases suggest that Bm-Aspin inhibits the activities of all four human aspartic proteases. The kinetics studies indicate that Bm-Aspin follows a competitive mode of inhibition for pepsin and cathepsin-E, non-competitive for renin and mixed mode for cathepsin-D. The triple resonance NMR experiments on Bm-Aspin suggested the feasibility of carrying out NMR studies to obtain its solution structure. The NMR titration studies on the interactions of Bm-Aspin with the proteases indicate that it undergoes fast-exchange phenomena among themselves. In addition to this, the chemical shift perturbations for some of the residues of Bm-Aspin observed from 15N-HSQC spectra upon the addition of saturated amounts of aspartic proteases suggest the binding between Bm-Aspin and human aspartic proteases. They also provide information on the variations in the intensities and mode of binding between the proteases duly corroborating with the results from the protease inhibition assay method.The presence of aspartic protease inhibitor in filarial parasite  Brugia malayi was identified and the recombinant protein was biochemically characterized. Aspins get fast gaining importance in the fields like medicine, agriculture and biotechnology. Hence, in this study, the inhibition ability of filarial Aspin against human aspartic proteases is attempted from structural biology point of view. This new knowledge may contribute to a better overall understanding of the mechanism that explains the versatility of human filarial parasite. Since filariasis is more often considered as the disease of poor countries, fight against filariasis is also a fight against poverty.Filariasis is a parasitic infectious tropical disease caused by thread like filarial nematodes. These worms occupy the lymph nodes and in chronic cases they lead to the disease “elephantiasis.” Over 120 million people have already been affected by it, and 40 million are seriously disfigured by this disease. These parasites in human, adopt numerous strategies to hamper the host immune system which can facilitate its survival. The ability of the parasite to modulate the host immune system is a concept which explains the versatility of human filarial parasites. One such interesting concept to understand is the secretion of protease inhibitors by filarial parasites. Recently, an Aspin from parasite  Wuchereria bancrofti, Brugia malayi or Brugia timori that affects 120 million people in 73 countries and another 1100 million people are at the risk of contracting this dreadful disease Lymphatic filariasis is a mosquito borne infection caused by Though the mass drug administration was initiated as a preventive measure, it had only a limited ability During the process of infection, all stages of the parasite are constantly exposed to various human proteases. It is interesting to understand how filarial parasites successfully evade or counteract the harmful effects produced by the various human proteases. Under this scenario, several lines of studies suggest that filarial parasites have evolved mechanism to neutralize the harmful effects produced by the human proteases. For example, filarial parasites produce three types of classical protease inhibitors viz., serine protease inhibitors (serpins), cysteine protease inhibitors (cystatins) and aspartic protease inhibitors (aspins) to overcome the harmful effects produced by the human proteases.taeniaformisBrugia malayi. The suggested function of serpins and cystatins was to contribute to the longevity of the parasite in the blood stream. Despite the pivotal role of Aspins in host pathogenesis, immune regulation and diagnostic marker The first evidence of protease inhibitors in parasite survival was Taeniaestatin from a non-filarial parasite Taenia Brugia malayi, termed as pepsin inhibitor homolog compared to the amino acid composition of PI-3 from Ascaris SuumIn this context, an Aspin from As these aspartic proteases are believed to play a key role in various physiological activities, understanding the aspartic protease inhibitory mechanism of Bm-Aspin becomes imperative to study its role in parasite survival and its immune evasion strategies. However, lack of Bm-Aspin three dimensional structure limit the ability of understanding aspartic protease inhibition mechanism. In order to unravel the structure-based protease inhibition mechanism, Bm-Aspin's, aspartic protease inhibition kinetics and solution structure determination has been initiated and presented in this study. This work happens to be the first report describing the feasibility of solution structure determination of filarial Aspin and understand its protease inhibitory efficiency from structural biology point of view.Ascaris Suum PI-3 and was believed to follow similar kind of pepsin inhibition. Hence pH 5.6 was considered. The sample conditions and the methods that were chosen to study the protease inhibition by Bm-Aspin were similar to those used by Abu-erreish and Peanasky to study the pepsin inhibition by PI-3 from Ascaris Suum2)-Phe-Val-Leu (4-pyridylmethyl) ester, the specific substrate for aspartic proteases from a stock of 1 mg/ml, was added The aspartic proteases pepsin, renin, cathepsin-E, and cathepsin-D purchased from Sigma, USA and the lab purified Bm-Aspin were used for the assays. Equimolar concentrations of Bm-Aspin and the proteases were mixed and incubated in 100 mM sodium acetate buffer at pH 5.6 for 10 min at 37°C separately. Bm-Aspin initially termed as “pepsin inhibitor homologue” The kinetics of aspartic protease inhibition by Bm-Aspin was determined by the UV- spectroscopic method mK value for Bm-Aspin was determined by linear regression method from plots of 1/V vs. 1/S, utilizing substrate concentrations of 7–80 µM. Three fixed concentrations of Bm-Aspin as explained above were used to determine the inhibition constant (iK) against six concentrations of substrate. Assays were carried out in triplicates and the kinetic constants for Bm-Aspin against the human aspartic proteases were determined using Graphpad Prism 2.0 .The In order to show the activity of the protease and its inhibition by Bm-Aspin under NMR conditions, the effects of SDS and pH on the protease were studied. We have performed protease activity assays using Casein Agar plate and also by the UV spectroscopic method. The inhibition by Bm-Aspin has also been looked at these conditions. Fine punch holes were made on Casein agar plate as described by Cheseseman 15N minimal medium using 15NH4Cl as the sole nitrogen source. The purification and the refolding protocols are the same that have been described earlier 2O (v/v). This NMR study was initially performed without any detergents and the resultant spectrum suggests the possibility of aggregation. Then the following chemicals/detergents were used to figure out the best one that helps to avoid aggregation: 0.5 M urea and 1% glycerol, 100 mM n-Dodecyl β-D-Maltopyranoside (DDM), 1% n-octyl-β-D-glucoside (OG), 1% triton-×100 and 100 mM SDS. The final goal is to obtain the most suitable condition for Bm-Aspin that could provide good quality NMR spectra. There after the protein sample for the NMR experiment was refolded and concentrated in the presence of the above mentioned detergents each time, respectively.The plasmid containing Bm-Aspin was expressed in 15N HSQC spectrum was acquired for Bm-Aspin at 298 K. Data was collected on the Bruker Avance III 700 MHz spectrometer available at Claflin University. The NMR experiments were recorded with the carrier position of 4.678 ppm for 1H and 117 ppm for 15N. All chemical shifts were referenced to internal D2O. The triple resonance NMR experiments like HNCO, HN(CO)CA, HNCA, CBCA(CO)NH and HNCACB on a uniformly 13C, 15N labeled Bm-Aspin were carried out as mentioned above. The data acquired were processed using NMRPipe 15N-HSQC spectra were collected by titrating with progressive additions of human aspartic proteases  to 15N-labeled Bm-Aspin to attain molar ratios of 0∶1, 0.1∶1, 0.5∶1 and 1∶1 respectively.2)-Phe-Val-Leu (4-pyridylmethyl) ester, successful inhibitions of all four proteases were observed.Inhibition effect of Bm-Aspin on the human aspartic proteases was examined . When asProtease digestion was observed in Casein agar plate by 5 µg of pepsin and 5 µg of pepsin preincubated (for 10 min at 37°C) with 100 mM SDS at both pH 5.6 and 7.0 . EncouraiK) for pepsin, renin, cathepsin-E and cathepsin-D inhibition by Bm-Aspin was found to be: 2.1 (±0.7) nM, 2.9 (±0.9) nM, 4.3 (±0.2) nM, and 6.5 (±0.6) nM respectively. The data clearly indicate the strength of inhibition among the four different proteases with Bm-Aspin.The double inverse Lineweaver-Burk plots depicted the inhibition of pepsin, renin, cathepsin-E and cathepsin-D by Bm-Aspin  possess appreciable peak movement indicating their involvement in the interaction phenomena. All the spectra are having the same trend in their protease interaction shifts with pepsin producing more appreciable shifts. The general inhibition characteristics that have been observed from the kinetic and inhibition assay methods are in perfect agreement with the NMR titration method, duly confirming the results. A visual look at the overlaid spectra clearly confirms the strong inhibitory characteristics of pepsin compared to the rest. There is strong evidence about the involvement of the C-terminal residues in the interaction process of all the proteases. Additionally, for pepsin, some glycines from the N-terminal domain are found to be affected as compared to the rest of the proteases, which could attribute to the more inhibitory nature of pepsin. From the binding studies of Bm-Aspin with the aspartic proteases, we have observed that there are five residues  of the C-terminal domain that are commonly affected in all the four aspartic proteases interactions. This provides an information that the same kind of interaction mode is followed in all the four protease interactions. Three of the N-terminal domain residues  are appreciably affected in interacting with Pepsin and Renin and they are smaller for CatD and CatE. These sites could be the aiding factor for the two former proteases to have higher activities compared to the latter two. These residue specificities for the proteases clearly indicate that they are the genuine interacting sites. As the HSQC spectrum has more peak overlaps, for simplicity, only the residues A213, I214, and Y215 that are having appreciable shifts when interacting with pepsin are shown here as an example.  and bound (Bm-Aspin+protease complex) states, respectively. The bar diagram has been drawn using the radial shifts data obtained for the earlier mentioned 10 residues, when each of the four proteases used and is as shown in Ascaris Suum inhibitor, PI-3. Hence, it is quite obvious to expect the role of Bm-Aspin C-terminal domain in the inhibitory actions against the aspartic proteases.On comparing the aspartic protease interactions with Bm-Aspin at their saturated conditions, the saturated sample spectra for each of the four proteases were overlaid on each other. Again, the same three residues considered in the previous example have been shown here . The peaBrugia malayi Aspin inhibits the important human aspartic proteases Filarial parasites while gaining entry into the mammalian host are exposed to a variety of hostile factors including human proteases. To circumvent the harmful effects of these proteases, parasites have evolved several counter attacking mechanisms. For example, filarial parasites are known to secrete serpins, cystatins, and aspins to neutralize the human proteases thereby contributing to the longevity of the parasite in the blood stream. Though the functional characterizations of serpins and cystatins have been reported Determination of inhibition constant for pepsin inhibition activity of Bm-Aspin was reported with Casein as a substrate in our previous studies Kinetic studies of Bm-Aspin were performed to find out its mode of protease inhibition. Our data clearly indicates that the protease inhibition by Bm-Aspin was found to be competitive for pepsin and cathepsin-E, non-competitive for renin and mixed for cathepsin-D. Similar trend of linear competitive inhibition was observed with Pepsin when Casein was used as a substrate Ascaris suum that infects the pigs Ascaris suum inhibitor, PI-3, was found to be ineffective against renin and cathepsin-D and in contrast an appreciable influence on all the four aspartic proteases was evident with Bm-Aspin. The role of PI-3 N-terminal end residues was discussed in the case of PI-3 - pepsin crystal structure complex The mode of pepsin and cathepsin-E inhibition by Bm-Aspin was found to be comparable to that of an Aspin, PI-3 from the non-filarial nematode iK) values determined by linear regression of 1/V vs 1/S plot suggests that renin, cathepsin-E and cathpesin-D inhibition by Bm-Aspin are 0.8, 2.2 and 4.4 times less specific than that of pepsin. This correlates with our previous iso-thermal calorimetric titration experiment results indicating that the preference of protease inhibition by Bm-Aspin is in the following order: pepsin>rennin>cathepsin-E>cathepsin-D The inhibition constant CA, HNCA, CBCA(CO)NH and HNCACB were carried out at 298 K on a uniformly double 15N edited NOESY spectra. The usage of CBCA (CO) NH/HNCACB was found to be extremely useful not only for the improved resolution in the carbon dimension, but more importantly, it provided the phase information which will be used in the assignment process. The initial assignment was simple with the easier identification of Glycine residues and its connectivity with the other easily identifiable Ala, Ser and Thr residues. Nearly 15 residue-stretches with sequential residue connectivity have been identified and assigned. The complete backbone and side-chain assignments for the other residues of Bm-Aspin is in progress and will soon be communicated elsewhere.The peak overlaps in the HSQC spectrum of Bm-Aspin with a large number of amide peaks make its resonance assignment extremely challenging. The backbone assignment of Bm-Aspin was initiated by establishing the neighboring residue connectivity using pairs of triple resonance spectra, HNCA and HNCOCA; HNCACB and CBCA(CO)NH. The sequential NMR spin system connectivities have been achieved by both intra- and inter-residue cross-peaks of Cβ and Cα respectively. Any ambiguities were resolved by going through the Before performing the NMR titration analysis between Bm-Aspin and human aspartic proteases, activity of pepsin in the above mentioned conditions (100 mM SDS and pH 7.0) was carried out. From these studies, it was clearly demonstrated that 100 mM SDS has no effect on pepsin activity and on the inhibitory activity of Bm-Aspin. The observation of protease digestion by pepsin at both pH 5.6 and 7.0 indicate a higher activity for pH 5.6, which is in agreement with earlier studies carried out on pH stability of pepsin The preliminary residue assignment of Bm-Aspin has been useful in the analysis of the Bm-Aspin interactions with the proteases. Our results clearly demonstrate that Bm-Aspin interacts with human aspartic proteases supporting our earlier results. The chemical shift perturbations were observed in the HSQC experiments upon the addition of aspartic proteases to Bm-Aspin. These observations provide the direct experimental proof that the Bm-Aspin contains the binding sites for human aspartic proteases. As expected, based on the displacement observed from the chemical shift perturbations in the HSQC of Bm-Aspin upon the addition of aspartic proteases, the inhibition slows down in the order of pepsin>renin>cathepsin-E>cathepsin-D. Similar findings were observed previously, when Bm-Aspin inhibition kinetic studies were carried out using UV-spectroscopy, suggesting the authentication of the experiments performed and the results obtained. However the detailed mechanism of protease inhibition by Bm-Aspin and its role in parasite survival can only be addressed further by structure-function studies with the determination of the solution structure of Bm-Aspin which would be initiated on completion of the assignment process.15N HSQC spectra of Bm-Aspin upon the addition of aspartic proteases, suggesting the possibilities of identifying the binding sites of human aspartic proteases on Bm-Aspin. This work happens to be the first attempt on the solution NMR studies of the protein involved in human lymphatic filariasis. Considering the physiological role played by these human aspartic proteases, understanding the protease inhibition mechanism of Bm-Aspin will be interesting to speculate Bm-Aspin, as an important drug target for human lymphatic filariasis. For which, the high resolution 3D structure determinations of Bm-Aspin in apo-form by solution NMR and the complex with human pepsin by X-ray crystallography methods are well underway in our laboratories. These high resolution structures will be instrumental in our understanding of the structure/function and mechanism of aspartic protease inhibition.We report here the aspartic protease inhibition kinetic studies and feasibility to conduct the solution NMR based structural studies on Bm-Aspin. Aspartic protease inhibition assay carried out using the specific substrate suggested that Bm-Aspin inhibits the important human aspartic proteases supporting our earlier published data. Inhibition kinetic studies suggest that, Bm-Aspin follows competitive mode of inhibition for pepsin and cathepsin-E, non-competitive for renin, and mixed for cathepsin-D. The triple resonance NMR experiments conducted on Bm-Aspin with SDS detergent suggested the feasibility to carry out the NMR based structural studies. The activities of pepsin at pH 7.0 and in the presence of 100 mM SDS suggests that all the titrations carried out are in the biologically relevant form. The chemical shift perturbations were observed in the


Here, utilizing a novel combination of outdoor experimental icing, manual measurements and terrestrial laser scanning (TLS), we perform the first in situ measurements of ice accretion on branches at differing heights in a tree crown and with increasing duration of exposure. We found that TLS can reproduce both branch and iced branch diameters with high fidelity, but some TLS instruments do not detect ice. Contrary to the expectations of ice accretion models, radial accretion varied sharply within tree crowns. Initially, radial ice accretion was similar throughout the crown, but after 6.5 hours of irrigation (second scanning) radial ice accretion was much greater on upper branches than on lower (∼factor of 3). The slope of the change in radial ice accretion along branches increased with duration of exposure and was significantly greater at the second scanning compared to the first. We conclude that outdoor icing experiments coupled with the use of TLS provide a robust basis for evaluation of models of ice accretion and breakage in tree crowns, facilitating estimation of the limiting breaking stress of branches by accurate measurements of ice loads.In the eastern hardwood forests of North America ice storms are an important disturbance event. Ice storms strongly influence community dynamics as well as urban infrastructure via catastrophic branch failure; further, the severity and frequency of ice storms are likely to increase with climate change. However, despite a long-standing interest into the effects of freezing rain on forests, the process of ice accretion and thus ice loading on branches remains poorly understood. This is because a number of challenges have prevented  Ice storms are one of the most frequent and severe natural disturbances in the deciduous forests of northeastern North America and thus play a central role in forest dynamics. Developing when warm moist air passes over a colder ground-level air mass in situ measurements of ice on branches, including: 1) measuring branches in tall canopies, 2) limitations to travel during and immediately after events 3) the unpredictability of ice storm events, and (4) the fact that the advancing warm front quickly arrives at the local ground level and melts the ice.The often extraordinary effects of ice storms on trees have drawn the attention of researchers for more than a century. Early studies described crown damage from icing qualitatively In a recent paper, an experimental approach to studying the effects of freezing rain was tested One expects a bias towards the interception of freezing rain at branch tips, causing them to accumulate ice at a greater rate and leading to a positive feedback; i.e. dependence of the radial ice accumulation rate on branch (plus ice) diameter so that the icing rate decreases from branch tip toward the bole Given the difficulties associated with accessing the crowns of large mature trees, as well as the challenge of recording data on crown structure in 3D by hand, researchers have sought to utilize methods of remote sensing, such as terrestrial laser scanning (TLS) to measure various aspects of tree crown structure, including branch diameter and geometry Acer platanoides L. in the city of Montreal. To our knowledge, this is the first study to successfully quantify in situ ice accretion on branches, as well as the first to employ TLS to measure ice accretion. Specifically, our goals were to: 1) evaluate the feasibility of experimental icing, 2) test the method of using TLS to capture ice accretion and structural changes in tree crowns, and 3) test the hypothesis that radial ice accretion on branches varies with diameter (distance from branch tip) and with crown position. A subsequent paper will use this data set to test models of accretion and breakage.We argue that both an experimental approach rooted in TLS and the development of mechanistic models of accretion and breakage will lead to better prediction of the inter-specific effects of ice storms on eastern deciduous forests. Here we present the first results from an experimental outdoor icing of a mature A. platanoides, is the most common urban tree in eastern North America . The individual studied was typical for urban A. platanoides street trees, and was situated on a flat site with wide spacing (∼6 m) between neighbouring trees. Permission to utilize the field site and conduct the experiment was granted by The City of Montréal and The Canada Lands Company. Due to the lack of competition the lower crown was much more fully developed than with a forest tree. A one story building was situated ∼5 m to the northeast since the tree was planted, but was demolished a few years prior to the experiment. Tree age was determined from ring counts to be 43 years, diameter at breast height was 35 cm, height was ∼9 m and crown diameter was ∼5 m.This study was conducted in the city of Montréal, Québec, Canada. The study species, Simulation of freezing rain will be influenced by variables such as expected air temperature and its diel variation, water droplet size, falling time, area to cover, flow rate and source water temperature. In this study, our goal was to simulate a “realistic” freezing rain event on branches. This meant that we needed to avoid the formation of icicles . We also sought to create a uniform pattern of rain over an area several meters wider than the crown itself.m away from the experimental tree. We irrigated from a scaffolding tower equal to the height of the tree  converts to 6.15 mm h−1 and ∼40 mm of precipitation for the duration of the experiment. The diameter range of water droplets produced was 0.9 mm–2.8 mm and the mean droplet size was 2 mm. This was determined from dusting Whatmans #2 filter paper with methylene blue and exposing the papers to one timed cycle of the oscillating sprinkler. Diameters of the water droplet stains (n = 103) were measured using the program ImageJ Developing an irrigation system required testing methods and observing the shape of ice on branches and the propensity for the water nozzles to freeze at temperatures ranging from −5°C to −20°C. After a series of small-scale outdoor trials in January, we tested two possible irrigation systems on a neighbouring tree ∼15The experiment was deliberately conducted over two relatively calm days  from February 22–23, 2011. For this paper, we only utilize the data for the first day of icing. On that day there was a gentle breeze (3–5 m/s) and temperature ranged from a low of −15°C to a high of −6°C. Fire hoses carried the source water 30 m from a hydrant to the site, where a 1/2” reducer was used to connect to plastic poly vinyl piping and then to the sprinkler. The experimental irrigation began at 9∶30 and ended at 16∶00 Table 1.We conducted trials to test the abilities of different TLS devices to detect ice on branches using an ILRIS-3D  and a Z+F laser scanner . On a cold day in January a ∼3 m long section of branch was supported at a 45 degree angle by a ladder. An initial ice-free scan of the branch was made. Then a fine mist of water was sprayed on the branch from a garden hose with a misting setting. After an accumulation of 5–10 mm radial ice accretion on branch tips the scene was scanned and the data inspected to determine if the ice coating was detectable. Both, ILRIS and Z+F scans were taken at about 10 m from the branch with medium resolution settings.Table S1). Prior to icing and several times during the experiment, the study tree was scanned from three positions separated by ∼120 degrees, each at a distance comprised between 12 and 17 m. We used the high resolution setting and the time to complete a scan was approximately 3 minutes. The multiple scans for the same scanning interval . In some cases targets were obscured due to safety fencing (prohibiting registration in the Z+F software) so fixed points (i.e. intersections of scaffold beams) were used as reference points for scan registration in Pointstream (http://www.arius3d.com/pointstream/). Registration quality was assessed using the alignment of immovable objects in the scans such as the scaffolding, slices of large diameter branches and the main stem.Then, during the experiment, we generated two data sets on ice accretion. The first comprised manual measurements that served as validation data, and the second was produced from TLS. Collection of 3D point clouds was acquired using the Z+F device with settings allowing a beam size of 5 mm at 10 m and a distance of 0.34 mm between points at 10 m  starting at the tips of branches. The locations of these measurements were marked by hanging numbered aluminum tags at the point of measurement, using thin wire, so the same point could be re-measured after icing. Two caliper measurements were made at each point along the branches, perpendicular to each other, with the first being parallel to the ground. This was done at the first scanning of the tree, prior to the onset of irrigation.In addition to measurements on branches, ice accretion was measured on eight wooden dowels (2.54 cm diameter) positioned parallel to and 1 m above the ground. Four of these wooden dowels were located beneath the crown, halfway between the drip line and the trunk to obtain an estimate of the through-fall intercepted by the canopy. The other four were placed ∼2 m beyond the furthest extant of the canopy. Dowel thickness was measured with calipers after the first and second scanning Table 1., an open source Python and VTK-based software tool for the reconstruction and modeling of botanical trees from point cloud data (e.g. acquired from TLS devices), to fit a series of cylinders to the 3D point data for each branch (details of the reconstruction process available at http://cjauvin.github.com/pylidar/markers.html). Based on the PypeTree reconstructions, measurement markers (i.e. spheres with a position and radius) are generated at evenly spaced interpolated intervals . Measurement marker radius is then adjusted if the limits of the markers are smaller or exceed the boundaries of the point cloud at any given location on a branch  as the standard measure of ice accretion from freezing rain, where Req is the radius of ice added to a cylinder if the ice was distributed uniformly around the cylinder circumference; i.e. it is the mean added radius. Measurements of Req were made by randomly collecting samples of ice-covered broken branch elements. For some larger samples branch diameter was determined from the curvature in the ice. Samples were placed in a freezer on-site. Measurements on the geometry were made later along each branch, with Req calculated as:D is the diameter (cm) and L is the length of the branch element (cm), V is the volume of the melted ice (milliliters) and −3) Studies of icing on cables and towers use the eq) were related to caliper measurements of ice radial thickness using linear regression. Finally, multiple linear regression was used to related radial ice accretion to distance from branch tips (and to branch diameter), position in the tree crown and time during the day of data collection. All statistical analyses were conducted in R v.2.15.2 (http://www.r-project.org/).To assess the ability of TLS to capture branch architecture and ice accretion, we used linear regression to relate caliper measurements to estimates of branch diameter from measurement markers in PypeTree. Similarly, measurements of equivalent radial ice thickness .Freezing rain produced radial ice accretion averaging 30 mm on branch tips in the upper crown and 7 mm on tips in the lower crown Table 1.2 = 0.94). Forcing the x-intercept to zero reduced the bias, leading to a slope of 0.97; for which the 95% confidence interval included 1 (2 = 0.98).The Z+F Imager but not the ILRIS-3D was capable of detecting the ice coating the branches. Estimates of branch and ice diameters produced from measurements of point clouds from TLS closely matched those obtained using a caliper in the field, but with a slight bias toward over-estimation and under-estimation at small and large diameters respectively Fig. 4A.2 = 0.92). Setting the x-intercept to zero brought the value of the slope to 0.97 and the 95% confidence interval still included 1 (2 = 0.98).For the wooden dowels TLS slightly under-estimated diameter at higher values but the slope and intercept did not differ from 1 or 0 significantly  but not at the first scanning interval  covering a sufficiently large area of ground with a uniform pattern of drops, b) accessing a source of water during freezing weather, c) producing drops of an appropriate size for the temperature, that freeze soon after contact with trees, and d) producing high enough flow rates so that the equipment does not freeze, or using heating elements or an alternative.eq from this study and from another recent experimental study. For example, in the present study there was a strong relationship between Req and caliper measurements, whereas in the only previous experimental icing study we are aware of the relationship between caliper measurements and Req appeared to be weaker–unfortunately, differences in data presentation prevent direct comparison; see −1 volume) to spray water up through a gap in the canopy resulted in less regular ice formation Diel variation in temperature causes significant difficulties for the design of irrigation systems for simulating freezing rain. This is because the risk of equipment freezing increases as water flow decreases, but high rates of water input will lead to excessive flow on the branches at warmer (but still sub-zero) temperatures, creating icicles and other structures that are not commonly observed during natural glaze events and are more difficult to describe with simple geometric shapes (i.e. cylinders). This aspect of irrigation system design may be reflected in the comparison of Rin situ measurements in the crown–branches shed ice when they finally snap, again when they may interact with other crown elements as they fall and once again finally when they strike the ground.TLS provided a novel and accurate method for measuring ice accretion in tree crowns Table 3,http://www.optech.ca/pdf/ILRIS_LR_SpecSheet_110304_Web.pdf, accessed 12/12/2012), utilizes a class 3 laser, has a wavelength closer to visible (1064 nm), and is promoted based on its abilities in detecting snow and ice. We note that operating TLS devices in extreme weather (below −20°C and above 45°C) is not recommended and may represent logistical challenges. One solution is to scan from a vehicle when possible, and we imagine that other methods of protecting the instrument from extreme cold temperatures could be employed.In our initial tests we found that not all TLS devices were able to detect ice. For example, ice accumulated on our test branch did not return a signal when we used the ILRIS-3D (no data in scan files). However, as demonstrated here it is certainly not a limitation of TLS in general. Other devices, such as the Z+F employed in the current study, provide a strong signal from ice and snow. This is surely related to the contrasting wavelengths used in both devices as well as to different beam power. Indeed, the ILRIS-3D uses a short wavelength in the infrared range (1535 nm), while the Z+F laser operates in the visible range. Ice and water energy absorption increases significantly in the infrared range while it is very low in the visible Irrigation was continued during the scanning process, which required three scan positions separated by ∼120 degrees to prevent ice from forming in water lines. As a result of this limitation we observed some change in the deflection of branches (near tips) in the three different scans, undoubtedly caused by ice loading. This primarily affected branch tips because of their greater flexibility and the apical concentration of stress. However, in most cases, the point cloud density for the side profile of the branch was very similar in at least two scans, and ultimately provided accurate measurements of the diameters of branches with ice compared to measurements made with a caliper in the field  along a vertical path through the canopy. To develop this conceptual model of ice accretion for tree crowns, one could adapt ray-tracing light models from existing functional-structural models, but simply fix the angle of approach (i.e. raindrops as photons that stick to branches instead of scattering). Alternatively, one could also employ voxel-based analysis and attempt to relate variation in ice accretion on branches with counts of voxels along transects through the canopy. Finally, the data generated on ice accretion and branch allometry in the present study will permit detailed modeling of the stresses on branches with additional information on material properties Click here for additional data file.Table S2Registration reports for the alignment of the TLS scans from the Z+F laser scanner.(DOCX)Click here for additional data file.