Appraisal of Pancreatic Lipase Inhibitory Potential of Ziziphus oenoplia (L.)Mill. Leaves by In Vitro and In Silico Approaches.

Pancreatic lipase is one of the crucial lipolytic enzymes of the gut that actively facilitates the digestion and absorption of the dietary triglycerides and cholesteryl esters. Although it has been deemed as one of the most reliable targets for the treatment of obesity and/or dyslipidemia, to date, orlistat is the only known FDA-approved, effective, oral pancreatic lipase inhibitor available for clinical use apart from the centrally acting antiobesity agents. However, it is known to be associated with adverse gastrointestinal and renal complications. In this study, we attempted to assess the antioxidant and porcine pancreatic lipase inhibitory potentials of Ziziphus oenoplia (L.)Mill. leaves through a systematic combination of in vitro and in silico approaches. Among the four different extracts including petroleum ether extract, ethyl acetate extract, ethanolic extract, and aqueous extract obtained through successive solvent extraction, the ethyl acetate extract has outperformed the other extracts and orderly displayed competent peroxide scavenging (IC50 value: 267.30 µg/mL) and porcine pancreatic lipase inhibitory (IC50 value: 444.44 µg/mL) potentials compared to the selected reference compounds: ascorbic acid (IC50 value: 251.50 µg/mL) and orlistat (IC50 value: 502.51 µg/mL) in the selected in vitro assay models. In addition, based on the molecular docking simulations of the six essential phytoconstituents of the leaves of Ziziphus oenoplia (L.)Mill. and their respective chemical analogues against the crystal structure of pancreatic lipase-colipase complex (PDB ID: 1LPB), four best-ranked molecules (PubChem CIDs: 15515703, 132582306, 11260294, and 44440845) have been proposed. Further, among these, the interaction potentials of the two top-ranked molecules (PubChem CIDs: 132582306 and 15515703) were analyzed through molecular dynamics (MD) simulations at a trajectory of 100 ns. Finally, absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters were theoretically predicted for all of the molecules using Swiss ADME and ADMET lab2.0. In conclusion, Ziziphus oenoplia (L.)Mill. leaves could become a prominent source for various potent bioactive compounds that may serve as prospective leads for the development of clinically cognizable pancreatic lipase inhibitors, provided their pharmacokinetic and in particular toxicity properties are thoroughly optimized.

Caseins: Versatility of Their Micellar Organization in Relation to the Functional and Nutritional Properties of Milk.

The milk of mammals is a complex fluid mixture of various proteins, minerals, lipids, and other micronutrients that play a critical role in providing nutrition and immunity to newborns. Casein proteins together with calcium phosphate form large colloidal particles, called casein micelles. Caseins and their micelles have received great scientific interest, but their versatility and role in the functional and nutritional properties of milk from different animal species are not fully understood. Caseins belong to a class of proteins that exhibit open and flexible conformations. Here, we discuss the key features that maintain the structures of the protein sequences in four selected animal species: cow, camel, human, and African elephant. The primary sequences of these proteins and their posttranslational modifications (phosphorylation and glycosylation) that determine their secondary structures have distinctively evolved in these different animal species, leading to differences in their structural, functional, and nutritional properties. The variability in the structures of milk caseins influence the properties of their dairy products, such as cheese and yogurt, as well as their digestibility and allergic properties. Such differences are beneficial to the development of different functionally improved casein molecules with variable biological and industrial utilities.

Shikimate Kinase Inhibitors: An Update on Promising Strategy against Mycobacterium tuberculosis.

Humanity has been battling with tuberculosis (TB) for a long period, and despite the availability of drugs well-known to act against the deadly microbe, the menace is still very far from reaching its end. Moreover, problems related to TB chemotherapy, such as lengthy treatment periods leading to poor patient compliance, increasing drug resistance, and association with another deadlier disease HIV-AIDS, make the situation alarming, thereby pressing the need for the discovery of new potent drugs urgently. Therefore, a drug target that is essential for survival and exclusive to M. tuberculosis presents a promising platform to explore novel molecules against the microorganism for better pathogen clearance with minimal toxicity. The shikimate pathway that leads to the synthesis of essential aromatic amino acids is one such attractive target. Shikimate kinase, the fifth enzyme of this pathway, converts shikimate to shikimate-3-phosphate by using ATP as a cosubstrate. Targeting shikimate kinase could be an effective strategy in light of its essentiality and absence of any homologue in mammals. This review discusses different strategies adopted for discovering novel compounds or scaffolds targeting M. tuberculosis shikimate kinase (MtSK) in vitro. The application of substrate analogues, their structure, and ligand-based approach for screening a library of anti-mycobacterial compounds, marine-derived molecules, and commercially available libraries have yielded promising MtSK inhibitors exhibiting micro-molar activities. To develop these leads into future drugs with minimum off-target effects on the host microenvironment, the molecules need to be structurally optimized for improved activities against enzymes and whole-cell organisms.

Type-2 diabetes mellitus-associated cancer risk: In pursuit of understanding the possible link.

BACKGROUND AND AIM: The insulin resistance-mediated abnormal gluconeogenesis when exceeds a given threshold culminates in type 2 diabetes mellitus (T2DM). This induces severe cellular oxidative stress that may eventually facilitate typical neoplastic transformations. This narrative review aims to portray some of the plausible key mechanistic links bridging T2DM and specific cancers. METHODS: A thorough literature search was conducted in the PubMedCentral database to retrieve information from various reputed biomedical reports/articles published from the year 2000. The information regarding the key biochemical signaling pathways mediating the carcinogenic transformation, especially in T2DM patients, was extensively excavated to systematically compile and present a narrative review. RESULTS: T2DM-associated insulin resistance is known to negatively influence certain crucial genetic and metabolic components (such as insulin/IGFs, PI-3K/Akt, AMPK, and AGEs/RAGE) that may eventually lead to neoplastic transformation. In particular, the risk of developing cancers like pancreatic, colorectal, breast, liver, endometrial, and bladder seems to be more significant in T2DM patients. CONCLUSION: Despite the fact that several studies have suggested a possible correlation between T2DM and cancer mortality, a more detailed research at both pre-clinical and clinical levels is still required so as to fully understand the intricate relationship and make a precise conclusion.

Computationally Decoding NudF Residues To Enhance the Yield of the DXP Pathway.

Terpenoids form a large pool of highly diverse organic compounds possessing several economically important properties, including nutritional, aromatic, and pharmacological properties. The 1-deoxy-d-xylulose 5-phosphate (DXP) pathway's end enzyme, nuclear distribution protein (NudF), interacting with isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), is critical for the synthesis of isoprenol/prenol/downstream compounds. The enzyme is yet to be thoroughly investigated to increase the overall yield of terpenoids in the Bacillus subtilis, which is widely used in industry and is generally regarded as a safe (GRAS) bacterium. The study aims to analyze the evolutionary conservation across the active site for mapping the key residues for mutagenesis studies. The 37-sequence data set, extracted from 103 Bacillus subtilis entries, shows a high phylogenetic divergence, and only six one-motif sequences ASB92783.1, ASB69297.1, ASB56714.1, AOR97677.1, AOL97023.1, and OAZ71765.1 show a monophyly relationship, unlike a complete polyphyly relationship between the other 31 three-motif sequences. Furthermore, only 47 of 179 residues of the representative sequence CUB50584.1 are observed to be significantly conserved. Docking analysis suggests a preferential bias of adenosine diphosphate (ADP)-ribose pyrophosphatase toward IPP, and a nearly threefold energetic difference is observed between IPP and DMAPP. The loops are hereby shown to play a regulatory role in guiding the promiscuity of NudF toward a specific ligand. Computational saturation mutagenesis of the seven hotspot residues identifies two key positions LYS78 and PHE116, orderly encoded within loop1 and loop7, majorly interacting with the ligands DMAPP and IPP, and their mutants K78I/K78L and PHE116D/PHE116E are found to stabilize the overall conformation. Molecular dynamics analysis shows that the IPP complex is significantly more stable than the DMAPP complex, and the NudF structure is very unstable. Besides showing a promiscuous binding of NudF with ligands, the analysis suggests its rate-limiting nature. The study would allow us to customize the metabolic load toward the synthesis of any of the downstream molecules. The findings would pave the way for the development of catalytically improved NudF mutants for the large-scale production of specific terpenoids with significant nutraceutical or commercial value.

Computational and Synthetic Biology Approaches for the Biosynthesis of Antiviral and Anticancer Terpenoids from Bacillus subtilis.

Recent advancements in medicinal research have identified several antiviral and anticancer terpenoids that are usually deployed as a source of flavor, fragrances and pharmaceuticals. Under the current COVID-19 pandemic conditions, natural therapeutics with the least side effects are the need of the hour to save the patients, especially, which are pre-affected with other medical complications. Although plants are the major sources of terpenoids; however, for the environmental concerns, the global interest has shifted to the biocatalytic production of molecules from microbial sources. The gram-positive bacterium Bacillus subtilis is a suitable host in this regard due to its GRAS (generally regarded as safe) status, ease in genetic manipulations and wide industrial acceptability. The B. subtilis synthesizes its terpenoid molecules from 1-deoxy-d-xylulose-5-phosphate (DXP) pathway, a common route in almost all microbial strains. Here, we summarize the computational and synthetic biology approaches to improve the production of terpenoid-based therapeutics from B. subtilis by utilizing DXP pathway. We focus on the in-silico approaches for screening the functionally improved enzyme-variants of the two crucial enzymes namely, the DXP synthase (DXS) and Farnesyl Pyrophosphate Synthase (FPPS). The approaches for engineering the active sites are subsequently explained. It will be helpful to construct the functionally improved enzymes for the high-yield production of terpenoid-based anticancer and antiviral metabolites, which would help to reduce the cost and improve the availability of such therapeutics for the humankind.

Probabilistic divergence of a template-based modelling methodology from the ideal protocol.

Protein structural information is essential for the detailed mapping of a functional protein network. For a higher modelling accuracy and quicker implementation, template-based algorithms have been extensively deployed and redefined. The methods only assess the predicted structure against its native state/template and do not estimate the accuracy for each modelling step. A divergence measure is therefore postulated to estimate the modelling accuracy against its theoretical optimal benchmark. By freezing the domain boundaries, the divergence measures are predicted for the most crucial steps of a modelling algorithm. To precisely refine the score using weighting constants, big data analysis could further be deployed.

Excavating the functionally crucial active-site residues of the DXS protein of Bacillus subtilis by exploring its closest homologues.

BACKGROUND: To achieve a high yield of terpenoid-based therapeutics, 1-deoxy-d-xylulose-5-phosphate (DXP) pathway has been significantly exploited for the production of downstream enzymes. The DXP synthase (DXS) enzyme, the initiator of this pathway, is pivotal for the convergence of carbon flux, and is computationally studied well for the industrially utilized generally regarded as safe (GRAS) bacterium Bacillus subtilis to decode its vital regions for aiding the construction of a functionally improved mutant library. RESULTS: For the 546 sequence dataset of DXS sequences, a representative set of 108 sequences is created, and it shows a significant evolutionary divergence across different species clubbed into 37 clades, whereas three clades are observed for the 76 sequence dataset of Bacillus subtilis. The DXS enzyme, sharing a statistically significant homology to transketolase, is shown to be evolutionarily too distant. By the mutual information-based co-evolutionary network and hotspot analysis, the most crucial loci within the active site are deciphered. The 650-residue representative structure displays a complete conservation of 114 loci, and only two co-evolving residues ASP154 and ILE371 are found to be the conserved ones. Lastly, P318D is predicted to be the top-ranked mutation causing the increase in the thermodynamic stability of 6OUW. CONCLUSION: The study excavates the vital functional, phylogenetic, and conserved residues across the active site of the DXS protein, the key rate-limiting controller of the entire pathway. It would aid to computationally understand the evolutionary landscape of this industrially useful enzyme and would allow us to widen its substrate repertoire to increase the enzymatic yield of unnatural molecules for in vivo and in vitro applications.

Decoding the vital segments in human ATP-dependent RNA helicase.

An analysis of the ATP-dependent RNA helicase using known functionally close analogs helps disclose the structural and functional information of the enzyme. The enzyme plays several interlinked biological functions and there is an urgent need to interpret its key active-site residues to infer function and establish role. The human protein q96c10.1 is annotated using tools such as interpro, go and cdd. The physicochemical properties are estimated using the tool protparam. We describe the enzyme protein model developed using modeller to identify active site residues. We used consurf to estimate the structural conservation and is evolutionary relationship is inferred using known close sequence homologs. The active site is predicted using castp and its topological flexibility is estimated through cabs-flex. The protein is annotated as a hydrolase using available data and ddx58 is found as its top-ranked interacting protein partner. We show that about 124 residues are found to be highly conserved among 259 homologs, clustered in 7 clades with the active-site showing low sequence conservation. It is further shown that only 9 loci among the 42 active-site residues are conserved with limited structural fluctuation from the wild type structure. Thus, we document various useful information linked to function, sequence similarity and phylogeny of the enzyme for annotation as potential helicase as designated by uniprot. Data shows limited degree of conserved sequence segments with topological flexibility unlike in other subfamily members of the protein.

Evaluation of specificity determinants in Mycobacterium tuberculosis σ/anti-σ factor interactions.

Extra Cytoplasmic Function (ECF) σ factor/regulatory protein (anti-σ factor) pairs govern environment mediated changes in gene expression in bacteria. The release of the ECF σ factor from an inactive σ/anti-σ factor complex is triggered by specific environmental stimuli. The free σ factor then associates with the RNA polymerase and drives the expression of genes in its target regulon. Multiple ECF σ/anti-σ pairs ensure calibrated changes in the expression profile by correlating diverse environmental stimuli with changes in the intracellular levels of different ECF σ factors. Specificity in σ/anti-σ factor interaction is thus essential for accurate signal transduction. Here we describe experiments to evaluate interactions between different M. tuberculosis σ and anti-σ proteins in vitro. The interaction parameters suggest that cross-talk between non-cognate σ/anti-σ pairs is likely. The sequence and conformational determinants that govern interaction specificity in a σ/anti-σ complex are not immediately evident due to substantial structural conservation. Sequence-structure analysis of all σ/anti-σ pairs suggest that conserved residues are not the primary determinants of σ/anti-σ interactions-a finding that suggests a potential route to set tolerance limits in interaction specificity. Non-specific σ/anti-σ interactions are likely to be biologically significant as it can contribute to heterogeneity in cellular responses in a bacterial population under less stringent requirements. This finding is relevant for synthetic biology approaches to engineer bacteria using σ/anti-σ transcription initiation modules for diverse applications in biotechnology.

Refined template selection and combination algorithm significantly improves template-based modeling accuracy.

In contrast to ab-initio protein modeling methodologies, comparative modeling is considered as the most popular and reliable algorithm to model protein structure. However, the selection of the best set of templates is still a major challenge. An effective template-ranking algorithm is developed to efficiently select only the reliable hits for predicting the protein structures. The algorithm employs the pairwise as well as multiple sequence alignments of template hits to rank and select the best possible set of templates. It captures several key sequences and structural information of template hits and converts into scores to effectively rank them. This selected set of templates is used to model a target. Modeling accuracy of the algorithm is tested and evaluated on TBM-HA domain containing CASP8, CASP9 and CASP10 targets. On an average, this template ranking and selection algorithm improves GDT-TS, GDT-HA and TM_Score by 3.531, 4.814 and 0.022, respectively. Further, it has been shown that the inclusion of structurally similar templates with ample conformational diversity is crucial for the modeling algorithm to maximally as well as reliably span the target sequence and construct its near-native model. The optimal model sampling also holds the key to predict the best possible target structure.

In Silico-Directed Evolution Using CADEE.

Recent years have seen an explosion of interest in both sequence- and structure-based approaches toward in silico-directed evolution. We recently developed a novel computational toolkit, CADEE, which facilitates the computer-aided directed evolution of enzymes. Our initial work (Amrein et al., IUCrJ 4:50-64, 2017) presented a pedagogical example of the application of CADEE to triosephosphate isomerase, to illustrate the CADEE workflow. In this contribution, we describe this workflow in detail, including code input/output snippets, in order to allow users to set up and execute CADEE simulations on any system of interest.

Quantitative proteomics analysis reveals the tolerance of wheat to salt stress in response to Enterobacter cloacae SBP-8.

Salinity stress adversely affects the plant growth and is a major constraint to agriculture. In the present study, we studied the role of plant growth promoting rhizobacterium (PGPR) Enterobacter cloacae SBP-8 possessing ACC deaminase activity on proteome profile of wheat (Triticum aestivum L.) under high salinity (200 mM NaCl) stress. The aim of study was to investigate the differential expressed protein in selected three (T-1, T-2, T-3) treatments and absolute quantification (MS/MS analysis) was used to detect statistically significant expressed proteins. In this study, we investigated the adaptation mechanisms of wheat seedlings exposed to high concentration of NaCl treatment (200 mM) for 15 days in response to bacterial inoculation based on proteomic data. The identified proteins were distributed in different cellular, biological and molecular functions. Under salt stress, proteins related to ion-transport, metabolic pathway, protein synthesis and defense responsive were increased to a certain extent. A broader comparison of the proteome of wheat plant under different treatments revealed that changes in some of the metabolic pathway may be involved in stress adaption in response to PGPR inoculation. Hierarchical cluster analysis identified the various up-regulated/down-regulated proteins into tested three treatments. Our results suggest that bacterial inoculation enhanced the ability of wheat plant to combat salt stress via regulation of transcription factors, promoting antioxidative activity, induction of defense enzymes, lignin biosynthesis, and acceleration of protein synthesis.

Protein structure prediction: challenging targets for CASP10.

Functional characterization of proteins being one of the major issues in molecular biology is still unsolved due to several resource and technical limitations of experimental structure determination methods. A suitable methodology for accurate prediction of protein confirmations simply from sequence is therefore emerging as the primary modeling goal of researchers today. Global blind protein structure prediction summit, entitled Critical Assessment of Structure Prediction (CASP), critically assesses the modeling methodologies, to track our algorithmic path development. But our success is still impeded by incompetent modeling methodologies and several key technical lacunas. There is still a great need to focus some key issues for bridging the major though considered trivial gaps, in the upcoming CASP to pave and demarcate our correct way of developing a consistently accurate prediction methodology in the near future. Major problems resulting in divergence of our predicted models from their actual native states are thus highlighted with suggested more stringent and reliable assessment considerations in the CASP test.