Structure, dynamics, and interactions of jacalin. Insights from molecular dynamics simulations examined in conjunction with results of X-ray studies

Molecular dynamics simulations have been carried out on all the jacalin-carbohydrate complexes of known structure, models of unliganded molecules derived from the complexes and also models of relevant complexes where X-ray structures are not available. Results of the simulations and the available crystal structures involving jacalin permit delineation of the relatively rigid and flexible regions of the molecule and the dynamical variability of the hydrogen bonds involved in stabilizing the structure. Local flexibility appears to be related to solvent accessibility. Hydrogen bonds involving side chains and water bridges involving buried water molecules appear to be important in the stabilization of loop structures. The lectin-carbohydrate interactions observed in crystal structures, the average parameters pertaining to them derived from simulations, energetic contribution of the stacking residue estimated from quantum mechanical calculations, and the scatter of the locations of carbohydrate and carbohydrate-binding residues are consistent with the known thermodynamic parameters of jacalin-carbohydrate interactions. The simulations, along with X-ray results, provide a fuller picture of carbohydrate binding by jacalin than provided by crystallographic analysis alone. The simulations confirm that in the unliganded structures water molecules tend to occupy the positions occupied by carbohydrate oxygens in the lectin-carbohydrate complexes. Population distributions in simulations of the free lectin, the ligands, and the complexes indicate a combination of conformational selection and induced fit. Proteins 2009; 77:760-777.

Prediction of protein-protein interactions between Helicobacter pylori and a human host

A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro. Many of the predicted interactions could potentially occur between the pathogen and its human host during pathogenesis as we focused mainly on the H. pylori proteins that have a transmembrane region or are encoded in the pathogenic island and those which are known to be secreted into the human host. By applying the homology search approach to protein-protein interaction databases DIP and iPfam, we could predict in vitro interactions for a total of 623 H. pylori proteins with 6559 human proteins. The predicted interactions include 549 hypothetical proteins of as yet unknown function encoded in the H. pylori genome and 13 experimentally verified secreted proteins. We have recognized 833 interactions involving the extracellular domains of transmembrane proteins of H. pylori. Structural analysis of some of the examples reveals that the interaction predicted by us is consistent with the structural compatibility of binding partners. Examples of interactions with discernible biological relevance are discussed.

Influence of surface chemistry of mesoporous alumina with wide pore distribution on controlled drug release

The crucial role of the drug carrier surface chemical moeities on the uptake and in vitro release of drug is discussed here in a systematic manner. Mesoporous alumina with a wide pore size distribution (2-7 nm) functionalized with various hydrophilic and hydrophobic surface chemical groups was employed as the carrier for delivery of the model drug ibuprofen. Surface functionalization with hydrophobic groups resulted in low degree of drug loading (approximately 20%) and fast rate of release (85% over a period of 5 h) whereas hydrophilic groups resulted in a significantly higher drug payloads (21%-45%) and slower rate of release (12%-40% over a period of 5 h). Depending on the chemical moiety, the diffusion controlled (proportional to time(-0.5)) drug release was additionally observed to be dependent on the mode of arrangement of the functional groups on the alumina surface as well as on the pore characteristics of the matrix. For all mesoporous alumina systems the drug dosages were far lower than the maximum recommended therapeutic dosages (MRTD) for oral delivery. We envisage that the present study would aid in the design of delivery systems capable of sustained release of multiple drugs.

Titration calorimetric studies to elucidate the specificity of the interactions of polymyxin B with lipopolysaccharides and lipid A

Lipopolysaccharide (LPS), the major cell wall constituent of Gram-negative bacteria, evokes a multitude of biological effects in mammals including pyrogenicity and toxic shock syndrome. Polymyxin B (PmB), a polycationic cyclic peptide, is known to neutralize most of its activities. The nature of the interaction of PmB with LPS and lipid A was investigated by isothermal titration calorimetry. PmB binds to LPS as well as lipid A stoichiometrically and non-co-operatively with micromolar affinity. These interactions are driven primarily by a favourable change in entropy (delta S) and are endothermic in nature. These positive changes in enthalpies decrease with increasing temperature, yielding a heat capacity change, delta Cp, of -2385 J.mol-1.degree-1 for PmB-LPS interactions while the binding of PmB to lipid A displays a delta Cp of -2259 J.mol-1.degree-1. The negative heat capacity changes provide strong evidence for the role of hydrophobic interactions as the driving force for the association of PmB with LPS and lipid A. A correlation of the energetics of these interactions with analyses of the molecular models of PmB suggests that a cluster of solvent-exposed non-polar amino acid side-chains that line one surface of the molecule, together with a ring of positively charged residues on its other surface, are responsible for its strong and stoichiometric binding to LPS.

Multivalent ligand presentation as a central concept to study intricate carbohydrate-protein interactions

Studying the weak binding affinities between carbohydrates and proteins has been a central theme in sustained efforts to uncover intricate details of this class of biomolecular interaction. The amphiphilic nature of most carbohydrates, the competing nature of the surrounding water molecules to a given protein receptor site and the receptor binding site characteristics led to the realization that carbohydrates are required to exert favorable interactions, primarily through clustering of the ligands. The clustering of sugar ligands has been augmented using many different innovative molecular scaffolds. The synthesis of clustered ligands also facilitates fine-tuning of the spatial and topological proximities between the ligands, so as to allow the identification of optimal molecular features for significant binding affinity enhancements. The kinetic and thermodynamic parameters have been delineated in many instances, thereby allowing an ability to correlate the multivalent presentation and the observed ligand-receptor interaction profiles. This critical review presents various multivalent ligands, synthetic and semisynthetic, and mechanisms by which the weak binding affinities are overcome, and the ligand-receptor complexation leads to significantly enhanced binding affinities (157 references).

Purification of RNA polymerase from mycobacteria for optimized promoter-polymerase interactions

In vitro transcription analysis is important to understand the mechanism of transcription. Various assays for the analysis of initiation, elongation and termination form the basis for better understanding of the process. Purified RNA polymerase (RNAP) with high specific activity is necessary to carry out variety of these specific reactions. The RNAP purified from Mycobacterium smegmatis from exponential phase showed low promoter specificity in promoter-polymerase interaction studies. This is due to the presence of a large number of sigma factors during exponential phase and under-representation of sigma(A) required for house-keeping transcription. We describe an in vivo reconstitution of RNAP holoenzyme with sigma(A) and its purification, which resulted in holoenzyme with stoichiometric sigma(A) content. The reconstituted holoenzyme showed enhanced promoter-specific binding and promoter-specific-transcription activity compared to the enzyme isolated using standard procedure. Such in vivo reconstitution of stoichiometric holoenzyme could facilitate promoter-specific transcription assays, especially in organisms which encode a large number of sigma factors.

Theoretical Investigation on the Effect of Different Nitrogen Donors on Intramolecular Se center dot center dot center dot N Interactions

The effect of different donor nitrogen atoms on the strength and nature of intramolecular Se center dot center dot center dot N interactions is evaluated for organoselenium compounds having N,N-dimethylaminomethyl (dime), oxazoline (oxa) and pyridyl (py) substituents. Quantum chemical calculations on three series of compounds [2-(dime)C6H4SeX (1a-g), 2-(oxa)C6H4SeX (2a-g), 2- (py)C6H4SeX (3-ag); X=Cl, Br, OH, CN, SPh, SePh, CH3] at the B3LYP/6-31G(d) level show that the stability of different conformers depends on the strength of intramolecular nonbonded Se center dot center dot center dot N interactions. Natural bond orbital (NBO), NBO deletion and atoms in molecules (AIM) analyses suggest that the nature of the Se center dot center dot center dot N interaction is predominantly covalent and involves nN ->sigma*(Se-X) orbital interaction. In the three series of compounds, the strength of the Se center dot center dot center dot N interaction decreases in the order 3>2>1 for a particular X, and it decreases in the order Cl > Br > OH>SPh approximate to CN approximate to SePh>CH3 for all the three series 1-3. However, further analyses suggest that the differences in strength of Se center dot center dot center dot N interaction in 1-3 is predominantly determined by the distance between the Se and N atoms, which in turn is an outcome of specific structures of 1, 2 and 3, and the nature of the donor nitrogen atoms involved has very little effect on the strength of Se center dot center dot center dot N interaction. It is also observed that Se center dot center dot center dot N interaction becomes stronger in polar solvents such as CHCl3, as indicated by the shorter r(Se center dot center dot center dot N) and higher E-Se center dot center dot center dot N values in CHCl3 compared to those observed in the gas phase.

The Role of UPF0157 in the Folding of M-tuberculosis Dephosphocoenzyme A Kinase and the Regulation of the Latter by CTP

Background: Targeting the biosynthetic pathway of Coenzyme A (CoA) for drug development will compromise multiple cellular functions of the tubercular pathogen simultaneously. Structural divergence in the organization of the penultimate and final enzymes of CoA biosynthesis in the host and pathogen and the differences in their regulation mark out the final enzyme, dephosphocoenzyme A kinase (CoaE) as a potential drug target. Methodology/Principal Findings: We report here a complete biochemical and biophysical characterization of the M. tuberculosis CoaE, an enzyme essential for the pathogen's survival, elucidating for the first time the interactions of a dephosphocoenzyme A kinase with its substrates, dephosphocoenzyme A and ATP; its product, CoA and an intrinsic yet novel inhibitor, CTP, which helps modulate the enzyme's kinetic capabilities providing interesting insights into the regulation of CoaE activity. We show that the mycobacterial enzyme is almost 21 times more catalytically proficient than its counterparts in other prokaryotes. ITC measurements illustrate that the enzyme follows an ordered mechanism of substrate addition with DCoA as the leading substrate and ATP following in tow. Kinetic and ITC experiments demonstrate that though CTP binds strongly to the enzyme, it is unable to participate in DCoA phosphorylation. We report that CTP actually inhibits the enzyme by decreasing its Vmax. Not surprisingly, a structural homology search for the modeled mycobacterial CoaE picks up cytidylmonophosphate kinases, deoxycytidine kinases, and cytidylate kinases as close homologs. Docking of DCoA and CTP to CoaE shows that both ligands bind at the same site, their interactions being stabilized by 26 and 28 hydrogen bonds respectively. We have also assigned a role for the universal Unknown Protein Family 0157 (UPF0157) domain in the mycobacterial CoaE in the proper folding of the full length enzyme. Conclusions/Significance: In view of the evidence presented, it is imperative to assign a greater role to the last enzyme of Coenzyme A biosynthesis in metabolite flow regulation through this critical biosynthetic pathway.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Complex solitons in Bose-Einstein condensates with two- and three-body interactions

For the first time, we find the complex solitons for a quasi-one-dimensional Bose-Einstein condensate with two-and three-body interactions. These localized solutions are characterized by a power law behaviour. Both dark and right solitons can be excited in the experimentally allowed parameter domain, when two-and three-body interactions are,respectively, repulsive and attractive. The dark solitons travel with a constant speed, which is quite different from the Lieb mode, where profiles with different speeds, bounded above by sound velocity, can exist for specified interaction strengths. We also study the properties of these solitons in the presence of harmonic confinement with time-dependent nonlinearity and loss. The modulational instability and the Vakhitov-Kolokolov criterion of stability are also studied.

Interactions and turnover of the muscular dystrophy protein myotilin

The striated muscle sarcomere is a force generating and transducing unit as well as an important sensor of extracellular cues and a coordinator of cellular signals. The borders of individual sarcomeres are formed by the Z-disks. The Z-disk component myotilin interacts with Z-disk core structural proteins and with regulators of signaling cascades. Missense mutations in the gene encoding myotilin cause dominantly inherited muscle disorders, myotilinopathies, by an unknown mechanism. In this thesis the functions of myotilin were further characterized to clarify the molecular biological basis and the pathogenetic mechanisms of inherited muscle disorders, mainly caused by mutated myotilin. Myotilin has an important function in the assembly and maintenance of the Z-disks probably through its actin-organizing properties. Our results show that the Ig-domains of myotilin are needed for both binding and bundling actin and define the Ig domains as actin-binding modules. The disease-causing mutations appear not to change the interplay between actin and myotilin. Interactions between Z-disk proteins regulate muscle functions and disruption of these interactions results in muscle disorders. Mutations in Z-disk components myotilin, ZASP/Cypher and FATZ-2 (calsarcin-1/myozenin-2) are associated with myopathies. We showed that proteins from the myotilin and FATZ families interact via a novel and unique type of class III PDZ binding motif with the PDZ domains of ZASP and other Enigma family members and that the interactions can be modulated by phosphorylation. The morphological findings typical of myotilinopathies include Z-disk alterations and aggregation of dense filamentous material. The causes and mechanisms of protein aggregation in myotilinopathy patients are unknown, but impaired degradation might explain in part the abnormal protein accumulation. We showed that myotilin is degraded by the calcium-dependent, non-lysosomal cysteine protease calpain and by the proteasome pathway, and that wild type and mutant myotilin differ in their sensitivity to degradation. These studies identify the first functional difference between mutated and wild type myotilin. Furthermore, if degradation of myotilin is disturbed, it accumulates in cells in a manner resembling that seen in myotilinopathy patients. Based on the results, we propose a model where mutant myotilin escapes proteolytic breakdown and forms protein aggregates, leading to disruption of myofibrils and muscular dystrophy. In conclusion, the main results of this study demonstrate that myotilin is a Z-disk structural protein interacting with several Z-disk components. The turnover of myotilin is regulated by calpain and the ubiquitin proteasome system and mutations in myotilin seem to affect the degradation of myotilin, leading to protein accumulations in cells. These findings are important for understanding myotilin-linked muscle diseases and designing treatments for these disorders.

MIPS: metal interactions in protein structures

MIPS (metal interactions in protein structures) is a database of metals in the three-dimensional acromolecular structures available in the Protein Data Bank. Bound metal ions in proteins have both catalytic and structural functions. The proposed database serves as an open resource for the analysis and visualization of all metals and their interactions with macromolecular (protein and nucleic acid) structures. MIPS can be searched via a user-friendly interface, and the interactions between metals and protein molecules, and the geometric parameters, can be viewed in both textual and graphical format using the freely available graphics plug-in Jmol. MIPS is updated regularly, by means of programmed scripts to find metal-containing proteins from newly released protein structures. The database is useful for studying the properties of coordination between metals and protein molecules. It also helps to improve understanding of the relationship between macromolecular structure and function. This database is intended to serve the scientific community working in the areas of chemical and structural biology, and is freely available to all users, around the clock, at http://dicsoft2.physics.iisc.ernet.in/mips/.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.