Relationship between Protein Digestibility and the Proteolysis of Legume Proteins during Seed Germination.

Legume seed protein is an important source of nutrition, but generally it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defenses against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defense or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species- and strain-dependent. Further research is needed to highlight which changes contribute most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry-identified peptide breakdown products.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery.

BACKGROUND: Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. OBJECTIVE: The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. METHOD: This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. RESULTS: This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. CONCLUSION: The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Structural Events in a Bacterial Uniporter Leading to Translocation of Glucose to the Cytosol.

Among classes of sugar transporters, there exists a comparatively new family of transporters named SWEET transporters (semi-SWEETS in bacteria) that are uniport transmembrane proteins. It is hypothesized that sugar is transported from the extracellular side (via outward-open state) to intracellular side (inward-open state) through intermediate occluded state (both extracellular and intracellular gates closed). In our study, extensive unbiased all-atom molecular dynamics simulations were carried out with the outward-open and inward-open conformations to study this transition mechanism. We find that after 100 ns, the outward-open structure without sugar bound starts changing to the occluded form leading to closure of extracellular gates stabilized by electrostatic and hydrophobic interactions. Further simulations (up to 7 µs) have led to a transition toward the inward-open form and suggest that there exists more than one intermediate occluded conformation. We have also performed 5-µs simulations on the glucose-docked structure to identify the putative substrate-bound translocation pathway. Glucose binds to semi-SWEET with strong hydrogen bonds to Asn66 and Trp50. Comparative simulations of substrate bound, and unbound forms suggested that glucose, the putative substrate, facilitates relatively rapid conformational transitions. For the first time, we captured the release of glucose to the cytosol, in this family of transporters. We find that prior to release of glucose, the glucose forms interactions with polar residues near the intracellular gate which may facilitate its release. The distance between the residues Asn31 and Gly34 of the other protomer was found to play a decisive role in the transport of glucose to the cytoplasmic side.

Enhanced basepair dynamics pre-disposes protein-assisted flips of key bases in DNA strand separation during transcription initiation.

Localized separation of strands of duplex DNA is a necessary step in many DNA-dependent processes, including transcription and replication. Little is known about how these strand separations occur. The strand-separated E.coli RNA polymerase-promoter open-complex structure showed four bases of the non-template strand, the master base -11A, -7, -6 and +2, in a flipped state and inserted into protein pockets. To explore whether any property of these bases in the duplex state pre-disposes them to flipping, NMR studies were performed on a wild-type promoter in the duplex state. Measurement of relaxation times indicates that a limited number of base pairs, including the flipped ones, have faster opening rates than the rest. Molecular dynamics studies also show an inherently high dynamic character of the -11A:T base pair in the wild-type strand-paired state. In order to explore the role of the RNA polymerase in the flipping process, we have used 2-aminopurine as a fluorescent probe. Slower kinetics of the increase of 2-aminopurine fluorescence was observed with RNA polymerases containing several mutant σ70s. This may be interpreted as the protein playing an important role in enhancing the flipping rate. These results suggest that flipping of -11A, and perhaps other flipped bases observed in the open-complex, is facilitated by its inherent proclivity to open-up with further assistance from the protein, thus leading to a strand-open state. Other DNA-based processes that require strand-separation may use similar pathways for strand separation. We conclude that not only basepair stability, but also dynamics may play an important role in the strand-separation.

Identification of novel hits as highly prospective dual agonists for mu and kappa opioid receptors: an integrated in silico approach.

Opioid agonists are used clinically for the treatment of acute and chronic pain, however, their clinical use is limited due to the presence of undesired side effects. Dual agonists, simultaneously targeting mu and kappa opioid receptors, show fewer side effects than that of selective agonists. In the present work, 2D- and 3D- Quantitative Structure Activity Relationship studies were performed on a series of aminomorphinan derivatives as dual agonists, using a wide range of descriptors. The aim of the study was to identify the structural requirements for the activity of these compounds towards mu and kappa opioid receptors and using the models, with best external predictability, for predicting the activities of new hits obtained from shape based virtual screening of drug like compounds from ZINC database. Genetic algorithm-based GFA and G/PLS techniques were used to derive the 2D-QSAR models. Common feature-based pharmacophore was used for aligning the compounds for 3D-QSAR. All the models were validated both internally and externally using statistical metrics. The coverage estimation of the models was carried out with applicability domain calculation. Six enriched hits were identified as novel prospective dual agonist based on good Blood Brain Barrier permeability and their activities towards mu and kappa opioid receptors, predicted by the best QSAR models. The known potent dual agonist, cyclorphan, and two highly prospective dual agonists were docked to both the receptors and binding free energies were calculated using MMGBSA. Molecular dynamics studies were performed on the docked complexes with both the receptors to establish stability of the complexes.

Aristolochic acid and its derivatives as inhibitors of snake venom L-amino acid oxidase.

Snake venom L-amino acid oxidase (LAAO) exerts toxicity by inducing hemorrhage, pneumorrhagia, pulmonary edema, cardiac edema, liver cell necrosis etc. Being well conserved, inhibitors of the enzyme may be synthesized using the template of the substrate, substrate binding site and features of the catalytic site of the enzyme. Previous findings showed that aristolochic acid (AA), a major constituent of Aristolochia indica, inhibits Russell's viper venom LAAO enzyme activity since, AA interacts with DNA and causes genotoxicity, derivatives of this compound were synthesized by replacing the nitro group to reduce toxicity while retaining the inhibitory potency. The interactions of AA and its derivatives with LAAO were followed by inhibition kinetics and surface plasmon resonance. Similar interactions with DNA were followed by absorption spectroscopy and atomic force microscopy. LAAO-induced cytotoxicity was evaluated by generation of reactive oxygen species (ROS), cell viability assays, confocal and epifluorescence microscopy. The hydroxyl (AA-OH) and chloro (AA-Cl) derivatives acted as inhibitors of LAAO but did not interact with DNA. The derivatives significantly reduced LAAO-induced ROS generation and cytotoxicity in human embryonic kidney (HEK 293) and hepatoma (HepG2) cell lines. Confocal images indicated that AA, AA-OH and AA-Cl interfered with the binding of LAAO to the cell membrane. AA-OH and AA-Cl significantly inhibited LAAO activity and reduced LAAO-induced cytotoxicity.

Molecular Simulations of Mixed Lipid Bilayers with Sphingomyelin, Glycerophospholipids, and Cholesterol.

The highly diversified composition of lipid bilayers across living cells is crucial for many biological processes. Lipid bilayers mainly consist of phosphatidylcholines (PC), phosphatidylethanolamines (PE), sphingomyelin (SM), and cholesterol, with eukaryotic membranes containing high percentage of sphingomyelin and cholesterol. In this study, we have modeled bilayers with different concentration of PC, PE, and SM to understand the changes in bilayer properties with varied SM concentrations. In addition, membrane models with 33% cholesterol have been simulated to understand the influence of cholesterol. To quantitatively access the structure and dynamics of membranes, deuterium order parameters (SCD), mass density profiles, lipid relaxation times, clustering analysis, and radial distribution functions are calculated. The SCDs compare favorably with past NMR experiments and increase with an increase in SM content. The surface area calculations showed that on addition of 50% palmitoyl-SM (PSM) surface area decreases (60.0 ± 0.6 Å2) from that of pure POPC (64.7 Å2), which is further lowered in the presence of cholesterol (44.4 ± 0.2 Å2). The lipid axial relaxation time decreases with increase in concentration of glycerophospholipids. The accuracy of these lipid membranes allows for future studies with more complex lipid mixtures containing SM to represent the diversity of lipids in natural membranes.

Interplay of Specific Trans- and Juxtamembrane Interfaces in Plexin A3 Dimerization and Signal Transduction.

Plexins are transmembrane proteins that serve as guidance receptors during angiogenesis, lymphangiogenesis, neuronal development, and zebrafish fin regeneration, with a putative role in cancer metastasis. Receptor dimerization or clustering, induced by extracellular ligand binding but modulated in part by the plexin transmembrane (TM) and juxtamembrane (JM) domains, is thought to drive plexin activity. Previous studies indicate that isolated plexin TM domains interact through a conserved, small-x3-small packing motif, and the cytosolic JM region interacts through a hydrophobic heptad repeat; however, the roles and interplay of these regions in plexin signal transduction remain unclear. Using an integrated experimental and simulation approach, we find disruption of the small-x3-small motifs in the Danio rerio Plexin A3 TM domain enhances dimerization of the TM-JM domain by enhancing JM-mediated dimerization. Furthermore, mutations of the cytosolic JM heptad repeat that disrupt dimerization do so even in the presence of TM domain mutations. However, mutations to the small-x3-small TM interfaces also disrupt Plexin A3 signaling in a zebrafish axonal guidance assay, indicating the importance of this TM interface in signal transduction. Collectively, our experimental and simulation results demonstrate that multiple TM and JM interfaces exist in the Plexin A3 homodimer, and these interfaces independently regulate dimerization that is important in Plexin A3 signal transduction.

Capturing state-dependent dynamic events of GABAA-receptors: a microscopic look into the structural and functional insights.

The γ-amino butyric acid type A receptors (GABAA-Rs) are the key players in the mammalian brain that meditate fast inhibitory neurotransmission events. The structural integrity of these ligand-gated ion channel controls chloride ion permeability, which in turn monitors important pharmacological functions. Despite ample studies on GABAA-Rs, there was a need for a study on full-length receptor structures, devoted to track structure-function correlations based on their dynamic behavior consideration. We have employed molecular dynamics simulations accompanied by other biophysical methods to shed light on sequential and unaddressed questions like How GABAA-R structure facilitates the entry of GABA molecules at its two orthosteric binding sites? After entry, what structural features and changes monitor site-wise GABA binding differences? In the same context, what are the roles and responsibilities of loops such as C and F? On physiologically relevant time scales, how open to close state transition occurs? How salt bridges such as E155-R207 and E153-R207 maintain state-dependent C-loop structures? In an attempt, our simulation study unravels the complete course of GABA binding-unbinding pathway. This provides us with the relevant understanding of state-dependent dynamic events of GABAA-Rs.

Indirect read-out of the promoter DNA by RNA polymerase in the closed complex.

Transcription is initiated when RNA polymerase recognizes the duplex promoter DNA in the closed complex. Due to its transient nature, the closed complex has not been well characterized. How the initial promoter recognition occurs may offer important clues to regulation of transcription initiation. In this article, we have carried out single-base pair substitution experiments on two Escherichia coli promoters belonging to two different classes, the -35 and the extended -10, under conditions which stabilize the closed complex. Single-base pair substitution experiments indicate modest base-specific effects on the stability of the closed complex of both promoters. Mutations of base pairs in the -10 region affect the closed complexes of two promoters differently, suggesting different modes of interaction of the RNA polymerase and the promoter in the two closed complexes. Two residues on σ(70) which have been suggested to play important role in promoter recognition, Q437 and R436, were mutated and found to have different effects on the closed-complex stability. DNA circular dichroism (CD) and FRET suggest that the promoter DNA in the closed complex is distorted. Modeling suggests two different orientations of the recognition helix of the RNA polymerase in the closed complex. We propose that the RNA polymerase recognizes the sequence dependent conformation of the promoter DNA in the closed complex.

Modeling the closed and open state conformations of the GABA(A) ion channel--plausible structural insights for channel gating.

Recent disclosure of high resolution crystal structures of Gloeobacter violaceus (GLIC) in open state and Erwinia chrysanthemii (ELIC) in closed state provides newer avenues to advance our knowledge and understanding of the physiologically and pharmacologically important ionotropic GABA(A) ion channel. The present modeling study envisions understanding the complex molecular transitions involved in ionic conductance, which were not evident in earlier disclosed homology models. In particular, emphasis was put on understanding the structural basis of gating, gating transition from the closed to the open state on an atomic scale. Homology modeling of two different physiological states of GABA(A) was carried out using their respective templates. The ability of induced fit docking in breaking the critical inter residue salt bridge (Glu155ß(2) and Arg207ß(2)) upon endogenous GABA docking reflects the perceived side chain rearrangements that occur at the orthosteric site and consolidate the quality of the model. Biophysical calculations like electrostatic mapping, pore radius calculation, ion solvation profile, and normal-mode analysis (NMA) were undertaken to address pertinent questions like the following: How the change in state of the ion channel alters the electrostatic environment across the lumen; How accessible is the Cl(-) ion in the open state and closed state; What structural changes regulate channel gating. A "Twist to Turn" global motion evinced at the quaternary level accompanied by tilting and rotation of the M2 helices along the membrane normal rationalizes the structural transition involved in gating. This perceived global motion hints toward a conserved gating mechanism among pLGIC. To paraphrase, this modeling study proves to be a reliable framework for understanding the structure function relationship of the hitherto unresolved GABA(A) ion channel. The modeled structures presented herein not only reveal the structurally distinct conformational states of the GABA(A) ion channel but also explain the biophysical difference between the respective states.

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

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

Combinatorial library enumeration and lead hopping using comparative interaction fingerprint analysis and classical 2D QSAR methods for seeking novel GABA(A) alpha(3) modulators.

Selective modulators of GABA(A) alpha(3) (gamma amino butyric acid alpha(3)) receptor are known to alleviate the side effects associated with nonspecific modulators. A follow up study was undertaken on a series of functionally selective phthalazines with an ideological credo of identifying more potent isofunctional chemotypes. A bioisosteric database enumerated using the combichem approach endorsed mining in a lead-like chemical space. Primary screening of the massive library was undertaken using the "Miscreen" toolkit, which uses sophisticated bayesian statistics for calculating bioactivity score. The resulting subset, thus, obtained was mined using a novel proteo-chemometric method that integrates molecular docking and QSAR formalism termed CoIFA (comparative interaction fingerprint analysis). CoIFA encodes protein-ligand interaction terms as propensity values based on a statistical inference to construct categorical QSAR models that assist in decision making during virtual screening. In the absence of an experimentally resolved structure of GABA(A) alpha(3) receptor, standard comparative modeling techniques were employed to construct a homology model of GABA(A) alpha(3) receptor. A typical docking study was then carried out on the modeled structure, and the interaction fingerprints generated based on the docked binding mode were used to derive propensity values for the interacting atom pairs that served as pseudo-energy variables to generate a CoIFA model. The classification accuracy of the CoIFA model was validated using different metrics derived from a confusion matrix. Further predictive lead mining was carried out using a consensus two-dimensional QSAR approach, which offers a better predictive protocol compared to the arbitrary choice of a single QSAR model. The predictive ability of the generated model was validated using different statistical metrics, and similarity-based coverage estimation was carried out to define applicability boundaries. Few analogs designed using the concept of bioisosterism were found to be promising and could be considered for synthesis and subsequent screening.

A study of interface roughness of heteromeric obligate and non-obligate protein-protein complexes.

A number of studies aimed to distinguish the structural patterns at the interfaces of obligate and non-obligate protein-protein complexes. These studies revealed better geometric complementarity of protomers in obligate complexes over non-obligates. We showed that protein surface roughness can be used to explain this observation. Using smoothened atomic fractal dimension (SAFD) as a descriptor, this work investigates the role of interface roughness in the molecular recognition of these two types of protein-protein complexes. We studied 52 obligate and 62 nonobligate heteromeric high quality crystal structures from benchmark data sets. We found that distribution of interface roughness values obligate and non-obligates are quite similar. However, we observed a distinct preference for obligate protomers to complex with chains having similar roughness. The roughness pairing is correlated in obligates only. The later indicates, an increase/decrease of roughness in one chain causes a proportional change in roughness in its binding partner. Based on these observations we proposed that similar and correlated roughness pairing leads to more interdigitation and contacts at the interface leading to better geometric fit in obligates. We propose that roughness information can find useful application in improving machine learning based complex type classifiers and filtering protein-protein docking solutions.