Unusual commonality in active site structural features of substrate promiscuous and specialist enzymes.

Enzyme promiscuity is the ability of (some) enzymes to perform alternate reactions or catalyze non-cognate substrate(s). The latter is referred to as substrate promiscuity, widely studied for its biotechnological applications and understanding enzyme evolution. Insights into the structural basis of substrate promiscuity would greatly benefit the design and engineering of enzymes. Previous studies on some enzymes have suggested that flexibility, hydrophobicity, and active site protonation state could play an important role in enzyme promiscuity. However, it is not known yet whether substrate promiscuous enzymes have distinctive structural characteristics compared to specialist enzymes, which are specific for a substrate. In pursuit to address this, we have systematically compared substrate/catalytic binding site structural features of substrate promiscuous with those of specialist enzymes. For this, we have carefully constructed dataset of substrate promiscuous and specialist enzymes. On careful analysis, surprisingly, we found that substrate promiscuous and specialist enzymes are similar in various binding/catalytic site structural features such as flexibility, surface area, hydrophobicity, depth, and secondary structures. Recent studies have also alluded that promiscuity is widespread among enzymes. Based on these observations, we propose that substrate promiscuity could be defined as a continuum feature that varies from narrow (specialist) to broad range of substrate preferences. Moreover, diversity of conformational states of an enzyme accessible for ligand binding may possibly regulate its substrate preferences.

Disulphide bond restrains the C-terminal region of thermostable direct hemolysin during folding to promote oligomerization.

Pore-forming toxins (PFTs) are typically produced as water-soluble monomers, which upon interacting with target cells assemble into transmembrane oligomeric pores. Vibrio parahaemolyticus thermostable direct hemolysin (TDH) is an atypical PFT that exists as a tetramer in solution, prior to membrane binding. The TDH structure highlights a core ß-sandwich domain similar to those found in the eukaryotic actinoporin family of PFTs. However, the TDH structure harbors an extended C-terminal region (CTR) that is not documented in the actinoporins. This CTR remains tethered to the ß-sandwich domain through an intra-molecular disulphide bond. Part of the CTR is positioned at the inter-protomer interface in the TDH tetramer. Here we show that the truncation, as well as mutation, of the CTR compromise tetrameric assembly, and the membrane-damaging activity of TDH. Our study also reveals that intra-protomer disulphide bond formation during the folding/assembly process of TDH restrains the CTR to mediate its participation in the formation of inter-protomer contact, thus facilitating TDH oligomerization. However, once tetramerization is achieved, disruption of the disulphide bond does not affect oligomeric assembly. Our study provides critical insights regarding the regulation of the oligomerization mechanism of TDH, which has not been previously documented in the PFT family.

CSmetaPred: a consensus method for prediction of catalytic residues.

BACKGROUND: Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. RESULTS: Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic residues at lower (better) ranked positions, which can facilitate and expedite their experimental characterization. CONCLUSIONS: The benchmarking studies showed that employing meta-approach in combining residue-level scores derived from well-known catalytic residue predictors can improve prediction accuracy as well as provide improved ranked positions of known catalytic residues. Hence, such predictions can assist experimentalist to prioritize residues for mutational studies in their efforts to characterize catalytic residues. Both meta-predictors are available as webserver at: http://14.139.227.206/csmetapred/ .

XTMS: pathway design in an eXTended metabolic space.

As metabolic engineering and synthetic biology progress toward reaching the goal of a more sustainable use of biological resources, the need of increasing the number of value-added chemicals that can be produced in industrial organisms becomes more imperative. Exploring, however, the vast possibility of pathways amenable to engineering through heterologous genes expression in a chassis organism is complex and unattainable manually. Here, we present XTMS, a web-based pathway analysis platform available at http://xtms.issb.genopole.fr, which provides full access to the set of pathways that can be imported into a chassis organism such as Escherichia coli through the application of an Extended Metabolic Space modeling framework. The XTMS approach consists on determining the set of biochemical transformations that can potentially be processed in vivo as modeled by molecular signatures, a specific coding system for derivation of reaction rules for metabolic reactions and enumeration of all the corresponding substrates and products. Most promising routes are described in terms of metabolite exchange, maximum allowable pathway yield, toxicity and enzyme efficiency. By answering such critical design points, XTMS not only paves the road toward the rationalization of metabolic engineering, but also opens new processing possibilities for non-natural metabolites and novel enzymatic transformations.

Curcumin Inhibits Membrane-Damaging Pore-Forming Function of the ß-Barrel Pore-Forming Toxin Vibrio cholerae Cytolysin.

Vibrio cholerae cytolysin (VCC) is a ß-barrel pore-forming toxin (ß-PFT). Upon encountering the target cells, VCC forms heptameric ß-barrel pores and permeabilizes the cell membranes. Structure-function mechanisms of VCC have been extensively studied in the past. However, the existence of any natural inhibitor for VCC has not been reported yet. In the present study, we show that curcumin can compromise the membrane-damaging activity of VCC. Curcumin is known to modulate a wide variety of biological processes and functions. However, the application of curcumin in the physiological scenario often gets limited due to its extremely poor solubility in the aqueous environment. Interestingly, we find that VCC can associate with the insoluble fraction of curcumin in the aqueous medium and thus gets separated from the solution phase. This, in turn, reduces the availability of VCC to attack the target membranes and thus blocks the membrane-damaging action of the toxin. We also observe that the soluble aqueous extract of curcumin, generated by the heat treatment, compromises the pore-forming activity of VCC. Interestingly, in the presence of such soluble extract of curcumin, VCC binds to the target membranes and forms the oligomeric assembly. However, such oligomers appear to be non-functional, devoid of the pore-forming activity. The ability of curcumin to bind to VCC and neutralize its membrane-damaging activity suggests that curcumin has the potential to act as an inhibitor of this potent bacterial ß-PFT.

An inquiry-based approach in large undergraduate labs: Learning, by doing it the "wrong" way.

Undergraduate laboratory courses, owing to their larger sizes and shorter time slots, are often conducted in highly structured modes. However, this approach is known to interfere with students' engagement in the experiments. To enhance students' engagement, we propose an alternative mode of running laboratory courses by creating some "disorder" in a previously adopted structure. After performing an experiment in the right way, the students were asked to repeat the experiment but with a variation at certain steps leading to the experiment being done the "wrong" way. Although this approach led to fewer experiments being conducted in a semester, it significantly enhanced the students' involvement. This was also reflected in the students' feedback. The majority of students preferred repeating an experiment with a variant protocol than performing a new experiment. Although we have tested this inquiry-based approach only for an undergraduate laboratory course in molecular biology, we believe such an approach could also be extended to undergraduate laboratory courses of other subjects.

Unraveling the structural landscape of intra-chain domain interfaces: Implication in the evolution of domain-domain interactions.

Intra-chain domain interactions are known to play a significant role in the function and stability of multidomain proteins. These interactions are mediated through a physical interaction at domain-domain interfaces (DDIs). With a motivation to understand evolution of interfaces, we have investigated similarities among DDIs. Even though interfaces of protein-protein interactions (PPIs) have been previously studied by structurally aligning interfaces, similar analyses have not yet been performed on DDIs of either multidomain proteins or PPIs. For studying the structural landscape of DDIs, we have used iAlign to structurally align intra-chain domain interfaces of domains. The interface alignment of spatially constrained domains (due to inter-domain linkers) showed that ~88% of these could identify a structural matching interface having similar C-alpha geometry and contact pattern despite that aligned domain pairs are not structurally related. Moreover, the mean interface similarity score (IS-score) is 0.307, which is higher compared to the average random IS-score (0.207) suggesting domain interfaces are not random. The structural space of DDIs is highly connected as ~84% of all possible directed edges among interfaces are found to have at most path length of 8 when 0.26 is IS-score threshold. At this threshold, ~83% of interfaces form the largest strongly connected component. Thus, suggesting that structural space of intra-chain domain interfaces is degenerate and highly connected, as has been found in PPI interfaces. Interestingly, searching for structural neighbors of inter-chain interfaces among intra-chain interfaces showed that ~86% could find a statistically significant match to intra-chain interface with a mean IS-score of 0.311. This implies that domain interfaces are degenerate whether formed within a protein or between proteins. The interface degeneracy is most likely due to limited possible ways of packing secondary structures. In principle, interface similarities can be exploited to accurately model domain interfaces in structure prediction of multidomain proteins.

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score.

BACKGROUND: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. RESULTS: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TM-align, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr-TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. CONCLUSION: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr-TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/.

Enhanced functional and structural domain assignments using remote similarity detection procedures for proteins encoded in the genome of Mycobacterium tuberculosis H37Rv.

The sequencing of the Mycobacterium tuberculosis (MTB) H37Rv genome has facilitated deeper insights into the biology of MTB, yet the functions of many MTB proteins are unknown. We have used sensitive profile-based search procedures to assign functional and structural domains to infer functions of gene products encoded in MTB. These domain assignments have been made using a compendium of sequence and structural domain families. Functions are predicted for 78 % of the encoded gene products. For 69 % of these, functions can be inferred by domain assignments. The functions for the rest are deduced from their homology to proteins of known function. Superfamily relationships between families of unknown and known structures have increased structural information by approximately 11%. Remote similarity detection methods have enabled domain assignments for 1325 'hypothetical proteins'. The most populated families in MTB are involved in lipid metabolism, entry and survival of the bacillus in host. Interestingly, for 353 proteins, which we refer to as MTB-specific, no homologues have been identified. Numerous, previously unannotated, hypothetical proteins have been assigned domains and some of these could perhaps be the possible chemotherapeutic targets. MTB-specific proteins might include factors responsible for virulence. Importantly, these assignments could be valuable for experimental endeavors. The detailed results are publicly available at http://hodgkin.mbu.iisc.ernet.in/~dots.

TASSER-Lite: an automated tool for protein comparative modeling.

This study involves the development of a rapid comparative modeling tool for homologous sequences by extension of the TASSER methodology, developed for tertiary structure prediction. This comparative modeling procedure was validated on a representative benchmark set of proteins in the Protein Data Bank composed of 901 single domain proteins (41-200 residues) having sequence identities between 35-90% with respect to the template. Using a Monte Carlo search scheme with the length of runs optimized for weakly/nonhomologous proteins, TASSER often provides appreciable improvement in structure quality over the initial template. However, on average, this requires approximately 29 h of CPU time per sequence. Since homologous proteins are unlikely to require the extent of conformational search as weakly/nonhomologous proteins, TASSER's parameters were optimized to reduce the required CPU time to approximately 17 min, while retaining TASSER's ability to improve structure quality. Using this optimized TASSER (TASSER-Lite), we find an average improvement in the aligned region of approximately 10% in root mean-square deviation from native over the initial template. Comparison of TASSER-Lite with the widely used comparative modeling tool MODELLER showed that TASSER-Lite yields final models that are closer to the native. TASSER-Lite is provided on the web at (http://cssb.biology.gatech.edu/skolnick/webservice/tasserlite/index.html).

Proteomics analysis of carbon-starved Mycobacterium smegmatis: induction of Dps-like protein.

Mycobacterium tuberculosis is a globally successful pathogen, infecting more than one third of total world's population. These bacteria have the remarkable ability to persist in the host for long periods of time unrecognized by the immune system and then to re-emerge later in life causing the disease. The physiology of such persistent or dormant bacilli is not very well characterized. Some evidence suggests that the dormant bacilli survive in a nutrient-deprived state that is similar to the stationary phase of the bacteria with respect to gene expression and physiology. Under this assumption we have studied the survival of Mycobacterium smegmatis in carbon starvation conditions as a model for mycobacterial persistence. M.smegmatis, being a fast-growing strain, serves as a good model to study starvation responses. Using the two-dimensional electrophoresis-based proteomics approach, we identified a protein which was found to be expressed preferentially under starvation conditions. This protein is homologous to a family of proteins called Dps (DNA binding Protein from Starved cells) that are known to protect DNA under various kinds of environmental stresses and its existence has, so far, not been reported in mycobacteria. Upon expression and purification of this protein, we observed that it has non-specific DNA-binding ability. Formation of a cage-like dodecamer structure is a characteristic feature of Dps. Using comparative modelling we were able to show that Dps from M.smegmatis could form a dodecamer structure similar to the crystal structure of Dps from Escherichia coli.