Biomedical subjects

Ivet Bahar

Publications and source records attributed to Ivet Bahar.

33 records · Page 2Linked to original sources

PubMed2004

Mining frequent patterns in protein structures: a study of protease families.

MOTIVATION: Analysis of protein sequence and structure databases usually reveal frequent patterns (FP) associated with biological function. Data mining techniques generally consider the physicochemical and structural properties of amino acids and their microenvironment in the folded structures. Dynamics is not usually considered, although proteins are not static, and their function relates to conformational mobility in many cases. RESULTS: This work describes a novel unsupervised learning approach to discover FPs in the protein families, based on biochemical, geometric and dynamic features. Without any prior knowledge of functional motifs, the method discovers the FPs for each type of amino acid and identifies the conserved residues in three protease subfamilies; chymotrypsin and subtilisin subfamilies of serine proteases and papain subfamily of cysteine proteases. The catalytic triad residues are distinguished by their strong spatial coupling (high interconnectivity) to other conserved residues. Although the spatial arrangements of the catalytic residues in the two subfamilies of serine proteases are similar, their FPs are found to be quite different. The present approach appears to be a promising tool for detecting functional patterns in rapidly growing structure databases and providing insights in to the relationship among protein structure, dynamics and function. AVAILABILITY: Available upon request from the authors.

Algorithms↗

PubMed2004

Discovery and characterization of novel small molecule inhibitors of human Cdc25B dual specificity phosphatase.

Cdc25A and Cdc25B dual-specificity phosphatases are key regulators of cell cycle transition and proliferation. They have oncogenic properties and are overexpressed in many human tumors. Because selective Cdc25 phosphatase inhibitors would be valuable biological tools and possible therapeutic agents, we have assayed a small molecule library for in vitro inhibition of Cdc25. We now report the identification of two new structurally distinct classes of Cdc25 inhibitors with cellular activity. The cyclopentaquinoline 3a,4,5,9b-tetrahydro-3H-cyclopenta[c]quinoline-4,8-dicarboxylic acid (5661118) and the naphthofurandione 3-benzoyl-naphtho[1,2-b]furan-4,5-dione (5169131) had in vitro IC50 values of 2.5 to 11 microM against recombinant Cdc25 and were less potent inhibitors of other phosphatases. Unlike 5661118, 5169131 caused reversible inhibition of Cdc25B and displayed competitive inhibitor kinetics. No growth inhibitory activity was seen with 5661118, whereas 10 to 30 microM 5169131 caused G1/S and G2/M arrest. We also found that 5169131 inhibited human PC-3 prostate and MDA-MB-435 breast cancer cell proliferation. Concentration-dependent Tyr15 hyperphosphorylation was seen on cyclin-dependent kinase with a 1-h 5169131 treatment, consistent with Cdc25 inhibition. Cells resistant to DNA toposiomerase II inhibitors were as sensitive to 5169131 as parental cells, indicating that this quinone compound does not inhibit topoisomerase II in vivo. Molecular modeling was used to predict a potential interaction site between the inhibitor and Cdc25B and to provide insights as to the molecular origins of the experimental observations. Based on its kinetic profile and cellular activity, we suggest that 5169131 could be an excellent tool for further studies on the cellular roles of Cdc25.

Cell Cycle↗

PubMed2004

Identification of core amino acids stabilizing rhodopsin.

Rhodopsin is the only G protein-coupled receptor (GPCR) whose 3D structure is known; therefore, it serves as a prototype for studies of the GPCR family of proteins. Rhodopsin dysfunction has been linked to misfolding, caused by chemical modifications that affect the naturally occurring disulfide bond between C110 and C187. Here, we identify the structural elements that stabilize rhodopsin by computational analysis of the rhodopsin structure and comparison with data from previous in vitro mutational studies. We simulate the thermal unfolding of rhodopsin by breaking the native-state hydrogen bonds sequentially in the order of their relative strength, using the recently developed Floppy Inclusion and Rigid Substructure Topography (FIRST) method [Jacobs, D. J., Rader, A. J., Kuhn, L. A. & Thorpe, M. F. (2001) Proteins 44, 150-165]. Residues most stable under thermal denaturation are part of a core, which is assumed to be important for the formation and stability of folded rhodopsin. This core includes the C110-C187 disulfide bond at the center of residues forming the interface between the transmembrane and the extracellular domains near the retinal binding pocket. Fast mode analysis of rhodopsin using the Gaussian network model also identifies the disulfide bond and the retinal ligand binding pocket to be the most rigid region in rhodopsin. Experiments confirm that 90% of the amino acids predicted by the FIRST method to be part of the core cause misfolding upon mutation. The observed high degree of conservation (78.9%) of this disulfide bond across all GPCR classes suggests that it is critical for the stability and function of GPCRs.

Amino Acid Sequence↗

PubMed2004

Global ribosome motions revealed with elastic network model.

The motions of large systems such as the ribosome are not fully accessible with conventional molecular simulations. A coarse-grained, less-than-atomic-detail model such as the anisotropic network model (ANM) is a convenient informative tool to study the cooperative motions of the ribosome. The motions of the small 30S subunit, the larger 50S subunit, and the entire 70S assembly of the two subunits have been analyzed using ANM. The lowest frequency collective modes predicted by ANM show that the 50S subunit and 30S subunit are strongly anti-correlated in the motion of the 70S assembly. A ratchet-like motion is observed that corresponds well to the experimentally reported ratchet motion. Other slow modes are also examined because of their potential links to the translocation steps in the ribosome. We identify several modes that may facilitate the E-tRNA exiting from the assembly. The A-site t-RNA and P-site t-RNA are found to be strongly coupled and positively correlated in these slow modes, suggesting that the translocations of these two t-RNAs occur simultaneously, while the motions of the E-site t-RNA are less correlated, and thus less likely to occur simultaneously. Overall the t-RNAs exhibit relatively large deformations. Animations of these slow modes of motion can be viewed at.

Anisotropy↗

PubMed2004

A sequence alignment-independent method for protein classification.

Annotation of the rapidly accumulating body of sequence data relies heavily on the detection of remote homologues and functional motifs in protein families. The most popular methods rely on sequence alignment. These include programs that use a scoring matrix to compare the probability of a potential alignment with random chance and programs that use curated multiple alignments to train profile hidden Markov models (HMMs). Related approaches depend on bootstrapping multiple alignments from a single sequence. However, alignment-based programs have limitations. They make the assumption that contiguity is conserved between homologous segments, which may not be true in genetic recombination or horizontal transfer. Alignments also become ambiguous when sequence similarity drops below 40%. This has kindled interest in classification methods that do not rely on alignment. An approach to classification without alignment based on the distribution of contiguous sequences of four amino acids (4-grams) was developed. Interest in 4-grams stemmed from the observation that almost all theoretically possible 4-grams (20(4)) occur in natural sequences and the majority of 4-grams are uniformly distributed. This implies that the probability of finding identical 4-grams by random chance in unrelated sequences is low. A Bayesian probabilistic model was developed to test this hypothesis. For each protein family in Pfam-A and PIR-PSD, a feature vector called a probe was constructed from the set of 4-grams that best characterised the family. In rigorous jackknife tests, unknown sequences from Pfam-A and PIR-PSD were compared with the probes for each family. A classification result was deemed a true positive if the probe match with the highest probability was in first place in a rank-ordered list. This was achieved in 70% of cases. Analysis of false positives suggested that the precision might approach 85% if selected families were clustered into subsets. Case studies indicated that the 4-grams in common between an unknown and the best matching probe correlated with functional motifs from PRINTS. The results showed that remote homologues and functional motifs could be identified from an analysis of 4-gram patterns.

Algorithms↗

PubMed2004

Inflammatory modulation of hepatocyte apoptosis by nitric oxide: in vivo, in vitro, and in silico studies.

Nitric oxide (NO*) and its reaction products are key players in the physiology and pathophysiology of inflammatory settings such as sepsis and shock. The consequences of the expression of inducible NO* synthase (iNOS, NOS-2) can be either protective or damaging to the liver. We have delineated two distinct hepatoprotective actions of NO*: the stimulation of cyclic guanosine monophosphate and the inhibition of caspases by S-nitrosation. In contrast, iNOS/NO* promotes hepatocyte death under conditions of severe redox stress, such as hemorrhagic shock or ischemia/reperfusion. Redox stress activates an unknown molecular switch that transforms NO*, which is hepatoprotective under resting conditions, into an agent that induces hepatocyte death. We hypothesize that the magnitude of the redox stress is a major determinant for the effects of NO* on cell survival by controlling the chemical fate of NO*. To address this hypothesis, we have carried out studies in relevant in vivo and in vitro settings. Moreover, we have constructed an initial mathematical model of caspase activation and coupled it to a model describing some of the reactions of NO* in hepatocytes. Our studies suggest that modulation of iron, oxygen, and superoxide may dictate whether NO* is hepatoprotective or hepatotoxic.

Animals↗

PubMed2004

Conformational changes in HIV-1 reverse transcriptase induced by nonnucleoside reverse transcriptase inhibitor binding.

Nonnucleoside reverse transcriptase inhibitors (NNRTI) are a group of small hydrophobic compounds with diverse structures that specifically inhibit HIV-1 reverse transcriptase (RT). NNRTIs interact with HIV-1 RT by binding to a single site on the p66 subunit of the p66/p51 heterodimeric enzyme, termed the NNRTI-binding pocket (NNRTI-BP). This binding interaction results in both short-range and long-range distortions of RT structure. In this article, we review the structural, computational and experimental evidence of the NNRTI-induced conformational changes in HIV-1 RT and relate them to the mechanism by which these compounds inhibit HIV-1 reverse transcription.

Anti-HIV Agents↗

PubMed2003

The origin and extent of coarse-grained regularities in protein internal packing.

Despite the suitability of various lattice geometries for coarse-grained modeling of proteins, the actual packing geometry of residues in folded structures has remained largely unexplored. A strong tendency to assume a regular packing geometry is shown here by optimally reorienting and superimposing clusters of neighboring residues from databank structures examined on a coarse-grained (single-site-per-residue) scale. The orientation function (or order parameter) of the examined coordination clusters with respect to fcc lattice directions is found to be 0.82. The observed geometry, which may be termed an incomplete distorted face-centered cubic (fcc) packing, is apparently favored by the drive to maximize packing density, in a fashion analogous to the way identical spheres pack densely and follow fcc geometry. About 2/3 of all residues obey this packing geometry, while the remainder occupy other context-dependent positions. The preferred coordination directions show relatively small variations over the various amino acid types, consistent with uniform residue viewpoint. Both the extremes of solvent-exposed and completely buried residue neighborhoods approximate the same generic packing, the only difference being in the numbers (and not the orientations) of coordination sites that are occupied (or left void for solvent occupancy). We observe the prevalence of a rather uniform (tight) residue packing density throughout the structure, including even the residues packed near solvent-exposed regions. The observed orientation distribution reveals an underlying, intrinsic orientation lattice for proteins.

Amino Acid Sequence↗

PubMed2003

Computing the transition state populations in simple protein models.

We describe the master equation method for computing the kinetics of protein folding. We illustrate the method using a simple Go model. Presently most models of two-state fast-folding protein folding kinetics invoke the classical idea of a transition state to explain why there is a single exponential decay in time. However, if proteins fold via funnel-shaped energy landscapes, as predicted by many theoretical studies, then it raises the question of what is the transition state. Is it a specific structure, or a small ensemble of structures, as is expected from classical transition state theory? Or is it more like the denatured states of proteins, a very broad ensemble? The answer that is usually obtained depends on the assumptions made about the transition state. The present method is a rigorous way to find transition states, without assumptions or approximations, even for very nonclassical shapes of energy landscapes. We illustrate the method here, showing how the transition states in two-state protein folding can be very broad ensembles.

Kinetics↗

PubMed2002

Inhibitor binding alters the directions of domain motions in HIV-1 reverse transcriptase.

Understanding the molecular mechanisms of HIV-1 reverse transcriptase (RT) action and drug inhibition is essential for designing effective antiretroviral therapies. Although comparisons of the different crystal forms of RT give insights into the flexibility of different domains, a direct computational assessment of the effect of inhibitor binding on the collective dynamics of RT is lacking. A structure-based approach is used here for exploring the dynamics of RT in unliganded and inhibitor-bound forms. Non-nucleoside RT inhibitors (NNRTI) are shown to interfere directly with the global hinge-bending mechanism that controls the cooperative motions of the p66 fingers and thumb subdomains. The net effect of nevirapine binding is to change the direction of domain movements rather than suppress their mobilities. The second generation NNRTI, efavirenz, on the other hand, shows the stronger effect of simultaneously reorienting domain motions and obstructing the p66 thumb fluctuations. A second hinge site controlling the global rotational reorientations of the RNase H domain is identified, which could serve as a target for potential inhibitors of RNase H activity.

Alkynes↗

PubMed2002

Dynamics of large proteins through hierarchical levels of coarse-grained structures.

Elastic network models have been successful in elucidating the largest scale collective motions of proteins. These models are based on a set of highly coupled springs, where only the close neighboring amino acids interact, without any residue specificity. Our objective here is to determine whether the equivalent cooperative motions can be obtained upon further coarse-graining of the protein structure along the backbone. The influenza virus hemagglutinin A (HA), composed of N = 1509 residues, is utilized for this analysis. Elastic network model calculations are performed for coarse-grained HA structures containing only N/2, N/10, N/20, and N/40 residues along the backbone. High correlations (>0.95) between residue fluctuations are obtained for the first dominant (slowest) mode of motion between the original model and the coarse-grained models. In the case of coarse-graining by a factor of 1/40, the slowest mode shape for HA is reconstructed for all residues by successively selecting different subsets of residues, shifting one residue at a time. The correlation for this reconstructed first mode shape with the original all-residue case is 0.73, while the computational time is reduced by about three orders of magnitude. The reduction in computational time will be much more significant for larger targeted structures. Thus, the dominant motions of protein structures are robust enough to be captured at extremely high levels of coarse-graining. And more importantly, the dynamics of extremely large complexes are now accessible with this new methodology.

Amino Acids↗

PubMed2002

Relating molecular flexibility to function: a case study of tubulin.

Microtubules (MT), along with a variety of associated motor proteins, are involved in a range of cellular functions including vesicle movement, chromosome segregation, and cell motility. MTs are assemblies of heterodimeric proteins, alpha beta-tubulins, the structure of which has been determined by electron crystallography of zinc-induced, pacilitaxel-stabilized tubulin sheets. These data provide a basis for examining relationships between structural features and protein function. Here, we study the fluctuation dynamics of the tubulin dimer with the aim of elucidating its functional motions relevant to substrate binding, polymerization/depolymerization and MT assembly. A coarse-grained model, harmonically constrained according to the crystal structure, is used to explore the global dynamics of the dimer. Our results identify six regions of collective motion, comprised of structurally close but discontinuous sequence fragments, observed only in the dimeric form, dimerization being a prerequisite for domain identification. Boundaries between regions of collective motions appear to act as linkages, found primarily within secondary-structure elements that lack sequence conservation, but are located at minima in the fluctuation curve, at positions of hydrophobic residues. Residue fluctuations within these domains identify the most mobile regions as loops involved in recognition of the adjacent regions. The least mobile regions are associated with nucleotide binding sites where lethal mutations occur. The functional coupling of motions between and within regions identifies three global motions: torsional and wobbling movements, en bloc, between the alpha- and beta-tubulin monomers, and stretching longitudinally. Further analysis finds the antitumor drug pacilitaxel (TaxotereR) to reduce flexibility in the M loop of the beta-tubulin monomer; an effect that may contribute to tightening lateral interactions between protofilaments assembled into MTs. Our analysis provides insights into relationships between intramolecular tubulin movements of MT organization and function.

Amino Acid Sequence↗

PubMed2002

Functional motions of influenza virus hemagglutinin: a structure-based analytical approach.

Influenza virus hemagglutinin (HA), a homotrimeric integral membrane glycoprotein essential for viral infection, is engaged in two biological functions: recognition of target cells' receptor proteins and fusion of viral and endosomal membranes, both requiring substantial conformational flexibility from the part of the glycoprotein. The different modes of collective motions underlying the functional mobility/adaptability of the protein are determined in the present study using an extension of the Gaussian network model (GNM) to treat concerted anisotropic motions. We determine the molecular mechanisms that may underlie HA function, along with the structural regions or residues whose mutations are expected to impede function. Good agreement between theoretically predicted fluctuations of individual residues and corresponding x-ray crystallographic temperature factors is found, which lends support to the GNM elucidation of the conformational dynamics of HA by focusing upon a subset of dominant modes. The lowest frequency mode indicates a global torsion of the HA trimer about its longitudinal axis, accompanied by a substantial mobility at the viral membrane connection. This mode is proposed to constitute the dominant molecular mechanism for the translocation and aggregation of HAs, and for the opening and dilation of the fusion pore. The second and third collective modes indicate a global bending, allowing for a large lateral surface exposure, which is likely to facilitate the close association of the viral and endosomal membranes before pore opening. The analysis of kinetically hot residues, in contrast, reveals a localization of energy centered around the HA2 residue Asp112, which apparently triggers the solvent exposure of the fusion peptide.

Anisotropy↗

PubMed2002

Fast-folding protein kinetics, hidden intermediates, and the sequential stabilization model.

Do two-state proteins fold by pathways or funnels? Native-state hydrogen exchange experiments show discrete nonnative structures in equilibrium with the native state. These could be called hidden intermediates (HI) because their populations are small at equilibrium, and they are not detected in kinetic experiments. HIs have been invoked as disproof of funnel models, because funnel pictures appear to indicate (1) no specific sequences of events in folding; (2) a continuum, rather than a discrete ladder, of structures; and (3) smooth landscapes. In the present study, we solve the exact dynamics of a simple model. We find, instead, that the present microscopic model is indeed consistent with HIs and transition states, but such states occur in parallel, rather than along the single pathway predicted by the sequential stabilization model. At the microscopic level, we observe a huge multiplicity of trajectories. But at the macroscopic level, we observe two pathways of specific sequences of events that are relatively traditional except that they are in parallel, so there is not a single reaction coordinate. Using singular value decomposition, we show an accurate representation of the shapes of the model energy landscapes. They are highly complex funnels.

Hydrogen-Ion Concentration↗

PubMedDate not supplied

An introduction to simulation and visualization of biological systems at multiple scales: a summer training program for interdisciplinary research.

Advances in biomedical research require a new generation of researchers having a strong background in both the life and physical sciences and a knowledge of computational, mathematical, and engineering tools for tackling biological problems. The NIH-NSF Bioengineering and Bioinformatics Summer Institute at the University of Pittsburgh (BBSI @ Pitt; www.ccbb.pitt.edu/bbsi) is a multi-institutional 10-week summer program hosted by the University of Pittsburgh, Duquesne University, the Pittsburgh Supercomputing Center, and Carnegie Mellon University, and is one of nine Institutes throughout the nation currently participating in the NIH-NSF program. Each BBSI focuses on a different area; the BBSI @ Pitt, entitled "Simulation and Computer Visualization of Biological Systems at Multiple Scales", focuses on computational and mathematical approaches to understanding the complex machinery of molecular-to-cellular systems at three levels, namely, molecular, subcellular (microphysiological), and cellular. We present here an overview of the BBSI @ Pitt, the objectives and focus of the program, and a description of the didactic training activities that distinguish it from other traditional summer research programs. Furthermore, we also report several challenges that have been identified in implementing such an interdisciplinary program that brings together students from diverse academic programs for a limited period of time. These challenges notwithstanding, presenting an integrative view of molecular-to-system analytical models has introduced these students to the field of computational biology and has allowed them to make an informed decision regarding their future career prospects.

Computational Biology↗