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Biomedical subjects

Ruben Abagyan

Publications and source records attributed to Ruben Abagyan.

At least 19 recordsLinked to original sources
PubMed2006

Assay principle for modulators of protein-protein interactions and its application to non-ATP-competitive ligands targeting protein kinase A.

Targeting sites that modulate protein-protein interactions represents an ongoing challenge for drug discovery. We have devised an assay principle, named ligand-regulated competition (LiReC), in an effort to find non-ATP competitive small-molecule regulators for type Ialpha cAMP-dependent Protein kinase (PKA-Ialpha), a protein complex that is implicated in disease. Our assay based on the LiReC principle utilizes a competitive fluorescent peptide probe to assess the integrity of the PKA-Ialpha complex upon introduction of an allosteric ligand. The developed fluorescence polarization method screens for small molecules that specifically protect (antagonists) or conversely activate (agonists) this protein complex. In high-throughput format, various cyclic nucleotide-derived agonists and antagonists are successfully detected with high precision. Furthermore, assay performance (Z'-factors above 0.7) far exceeds the minimum requirement for small-molecule screening. To identify compounds that operate through novel modes of action, our method shields the ATP-binding site and purposely excludes ATP-competitive ligands. These proof-of-principle experiments highlight the potential of the LiReC technique and suggest its application to other protein complexes, thereby providing a novel approach to identify and characterize modulators (small molecules, proteins, peptides, or nucleic acids) of protein-protein systems.

Adenosine Triphosphate↗
PubMed2006

ADP_EM: fast exhaustive multi-resolution docking for high-throughput coverage.

MOTIVATION: Efficient fitting tools are needed to take advantage of a fast growth of atomic models of protein domains from crystallography or comparative modeling, and low-resolution density maps of larger molecular assemblies. Here, we report a novel fitting algorithm for the exhaustive and fast overlay of partial high-resolution models into a low-resolution density map. The method incorporates a fast rotational search based on spherical harmonics (SH) combined with a simple translational scanning. RESULTS: This novel combination makes it possible to accurately dock atomic structures into low-resolution electron-density maps in times ranging from seconds to a few minutes. The high-efficiency achieved with simulated and experimental test cases preserves the exhaustiveness needed in these heterogeneous-resolution merging tools. The results demonstrate its efficiency, robustness and high-throughput coverage. AVAILABILITY: http://sbg.cib.csic.es/Software/ADP_EM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗
PubMed2006

Weighted quality estimates in machine learning.

MOTIVATION: Machine learning methods such as neural networks, support vector machines, and other classification and regression methods rely on iterative optimization of the model quality in the space of the parameters of the method. Model quality measures (accuracies, correlations, etc.) are frequently overly optimistic because the training sets are dominated by particular families and subfamilies. To overcome the bias, the dataset is usually reduced by filtering out closely related objects. However, such filtering uses fixed similarity thresholds and ignores a part of the training information. RESULTS: We suggested a novel approach to calculate prediction model quality based on assigning to each data point inverse density weights derived from the postulated distance metric. We demonstrated that our new weighted measures estimate the model generalization better and are consistent with the machine learning theory. The Vapnik-Chervonenkis theorem was reformulated and applied to derive the space-uniform error estimates. Two examples were used to illustrate the advantages of the inverse density weighting. First, we demonstrated on a set with a built-in bias that the unweighted cross-validation procedure leads to an overly optimistic quality estimate, while the density-weighted quality estimates are more realistic. Second, an analytical equation for weighted quality estimates was used to derive an SVM model for signal peptide prediction using a full set of known signal peptides, instead of the usual filtered subset.

Algorithms↗
PubMed2006

Defining the CD59-C9 binding interaction.

CD59 is a membrane glycoprotein that regulates formation of the cytolytic membrane attack complex (MAC or C5b-9) on host cell membranes. It functions by binding to C8 (alpha chain) and C9 after their structural rearrangement during MAC assembly. Previous studies indicated that the CD59 binding site in C9 was located within a 25-residue disulfide-bonded loop, and in C8alpha was located within a 51-residue sequence that overlaps the CD59 binding region of C9. By peptide screens and the use of peptides in binding assays, functional assays, and computer modeling and docking studies, we have identified a 6-residue sequence of human C9, spanning residues 365-371, as the primary CD59 recognition domain involved in CD59-mediated regulation of MAC formation. The data also indicate that both C8alpha and C9 bind to a similar or overlapping site on CD59. Furthermore, data from CD59-peptide docking models are consistent with the C9 binding site on CD59 located at a hydrophobic pocket, putatively identified previously by CD59 mutational and modeling studies.

Binding Sites↗
PubMed2006

Ab initio prediction of peptide-MHC binding geometry for diverse class I MHC allotypes.

Since determining the crystallographic structure of all peptide-MHC complexes is infeasible, an accurate prediction of the conformation is a critical computational problem. These models can be useful for determining binding energetics, predicting the structures of specific ternary complexes with T-cell receptors, and designing new molecules interacting with these complexes. The main difficulties are (1) adequate sampling of the large number of conformational degrees of freedom for the flexible peptide, (2) predicting subtle changes in the MHC interface geometry upon binding, and (3) building models for numerous MHC allotypes without known structures. Whereas previous studies have approached the sampling problem by dividing the conformational variables into different sets and predicting them separately, we have refined the Biased-Probability Monte Carlo docking protocol in internal coordinates to optimize a physical energy function for all peptide variables simultaneously. We also imitated the induced fit by docking into a more permissive smooth grid representation of the MHC followed by refinement and reranking using an all-atom MHC model. Our method was tested by a comparison of the results of cross-docking 14 peptides into HLA-A*0201 and 9 peptides into H-2K(b) as well as docking peptides into homology models for five different HLA allotypes with a comprehensive set of experimental structures. The surprisingly accurate prediction (0.75 A backbone RMSD) for cross-docking of a highly flexible decapeptide, dissimilar to the original bound peptide, as well as docking predictions using homology models for two allotypes with low average backbone RMSDs of less than 1.0 A illustrate the method's effectiveness. Finally, energy terms calculated using the predicted structures were combined with supervised learning on a large data set to classify peptides as either HLA-A*0201 binders or nonbinders. In contrast with sequence-based prediction methods, this model was also able to predict the binding affinity for peptides to a different MHC allotype (H-2K(b)), not used for training, with comparable prediction accuracy.

Binding Sites↗
PubMed2006

XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps.edu/download/.

Algorithms↗
PubMed2006

Discovery of bioactive small-molecule inhibitor of poly adp-ribose polymerase: implications for energy-deficient cells.

Poly (ADP-ribose) polymerase (PARP1) is a nuclear protein that, when overactivated by oxidative stress-induced DNA damage, ADP ribosylates target proteins leading to dramatic cellular ATP depletion. We have discovered a biologically active small-molecule inhibitor of PARP1. The discovered compound inhibited PARP1 enzymatic activity in vitro and prevented ATP loss and cell death in a surrogate model of oxidative stress in vivo. We also investigated a new use for PARP1 inhibitors in energy-deficient cells by using Huntington's disease as a model. Our results showed that insult with the oxidant hydrogen peroxide depleted cellular ATP in mutant cells below the threshold of viability. The protective role of PARP1 inhibitors against oxidative stress has been shown in this model system.

Adenosine Triphosphate↗
PubMed2006

The liganding of glycolipid transfer protein is controlled by glycolipid acyl structure.

Glycosphingolipids (GSLs) play major roles in cellular growth and development. Mammalian glycolipid transfer proteins (GLTPs) are potential regulators of cell processes mediated by GSLs and display a unique architecture among lipid binding/transfer proteins. The GLTP fold represents a novel membrane targeting/interaction domain among peripheral proteins. Here we report crystal structures of human GLTP bound to GSLs of diverse acyl chain length, unsaturation, and sugar composition. Structural comparisons show a highly conserved anchoring of galactosyl- and lactosyl-amide headgroups by the GLTP recognition center. By contrast, acyl chain chemical structure and occupancy of the hydrophobic tunnel dictate partitioning between sphingosine-in and newly-observed sphingosine-out ligand-binding modes. The structural insights, combined with computed interaction propensity distributions, suggest a concerted sequence of events mediated by GLTP conformational changes during GSL transfer to and/or from membranes, as well as during GSL presentation and/or transfer to other proteins.

Base Sequence↗
PubMed2005

Small molecule inhibitors of dynamin I GTPase activity: development of dimeric tyrphostins.

Dynamin I is a GTPase enzyme required for endocytosis and is an excellent target for the design of potential endocytosis inhibitors. Screening of a library of tyrphostins, in our laboratory, against the GTPase activity of dynamin I gave rise to a microM potent lead, 2-cyano-3-(3,4-dihydroxyphenyl)thioacrylamide (1, IC50 70 microM). Our initial investigations suggested that only the dimeric form of 1 displayed dynamin I GTPase inhibitory activity. Subsequent synthetic iterations were based on dimeric analogues and afforded a number of small molecules, low microM potent, inhibitors of dynamin I GTPase, in particular, symmetrical analogues with a minimum of two free phenolic -OHs: catechol-acrylamide (9) (IC50= 5.1 +/- 0.6 microM), its 3,4,5-trihydroxy congener (10) (IC50= 1.7 +/- 0.2 microM), and the corresponding 3-methyl ether (11) (IC50= 9 +/- 3 microM). Increasing the length of the central alkyl spacer from ethyl to propyl (22-24) afforded essentially identical activity with IC50's of 1.7 +/- 0.2, 1.7 +/- 0.2, and 5 +/- 1 microM, respectively. No decrease in activity was noted until the introduction of a hexyl spacer. Our studies highlight the requirement for two free amido NHs with neither the mono-N-methyl (86) nor the bis-N-methyl (87) analogues inhibiting dynamin I GTPase. A similar effect was noted for the removal of the nitrile moieties. However, modest potency was observed with the corresponding ester analogues of 9-11: ethyl ester (90), propyl ester (91), and butyl ester (92), with IC50's of 42 +/- 3, 38 +/- 2, and 61 +/- 2 microM, respectively. Our studies reveal the most potent and promising dynamin I GTPase inhibitor in this series as (22), which is also known as BisT.

Animals↗
PubMed2005

Surrogate data--a secure way to share corporate data.

The privacy of chemical structure is of paramount importance for the industrial sector, in particular for the pharmaceutical industry. At the same time, companies handle large amounts of physico-chemical and biological data that could be shared in order to improve our molecular understanding of pharmacokinetic and toxicological properties, which could lead to improved predictivity and shorten the development time for drugs, in particular in the early phases of drug discovery. The current study provides some theoretical limits on the information required to produce reverse engineering of molecules from generated descriptors and demonstrates that the information content of molecules can be as low as less than one bit per atom. Thus theoretically just one descriptor can be used to completely disclose the molecular structure. Instead of sharing descriptors, we propose to share surrogate data. The sharing of surrogate data is nothing else but sharing of reliably predicted molecules. The use of surrogate data can provide the same information as the original set. We consider the practical application of this idea to predict lipophilicity of chemical compounds and we demonstrate that surrogate and real (original) data provides similar prediction ability. Thus, our proposed strategy makes it possible not only to share descriptors, but also complete collections of surrogate molecules without the danger of disclosing the underlying molecular structures.

Chemical Engineering↗
PubMed2005

Statistical analysis and prediction of protein-protein interfaces.

Predicting protein-protein interfaces from a three-dimensional structure is a key task of computational structural proteomics. In contrast to geometrically distinct small molecule binding sites, protein-protein interface are notoriously difficult to predict. We generated a large nonredundant data set of 1494 true protein-protein interfaces using biological symmetry annotation where necessary. The data set was carefully analyzed and a Support Vector Machine was trained on a combination of a new robust evolutionary conservation signal with the local surface properties to predict protein-protein interfaces. Fivefold cross validation verifies the high sensitivity and selectivity of the model. As much as 97% of the predicted patches had an overlap with the true interface patch while only 22% of the surface residues were included in an average predicted patch. The model allowed the identification of potential new interfaces and the correction of mislabeled oligomeric states.

Animals↗
PubMed2005

Insights into the human CD59 complement binding interface toward engineering new therapeutics.

CD59 is a 77-amino acid membrane glycoprotein that plays an important role in regulating the terminal pathway of complement by inhibiting formation of the cytolytic membrane attack complex (MAC or C5b-9). The MAC is formed by the self assembly of C5b, C6, C7, C8, and multiple C9 molecules, with CD59 functioning by binding C5b-8 and C5b-9 in the assembling complex. We performed a scanning alanine mutagenesis screen of residues 16-57, a region previously identified to contain the C8/C9 binding interface. We have also created an improved NMR model from previously published data for structural understanding of CD59. Based on the scanning mutagenesis data, refined models, and additional site-specific mutations, we identified a binding interface that is much broader than previously thought. In addition to identifying substitutions that decreased CD59 activity, a surprising number of substitutions significantly enhanced CD59 activity. Because CD59 has significant therapeutic potential for the treatment of various inflammatory conditions, we investigated further the ability to enhance CD59 activity by additional mutagenesis studies. Based on the enhanced activity of membrane-bound mutant CD59 molecules, clinically relevant soluble mutant CD59-based proteins were prepared and shown to have up to a 3-fold increase in complement inhibitory activity.

Alanine↗
PubMed2005

Improving CAPRI predictions: optimized desolvation for rigid-body docking.

The ICM Docking and Interface Side-Chain Optimization (ICM-DISCO) showed promising predictive results during the first CAPRI experiment by successfully finding medium- or high-accuracy models in 3 of the 7 targets. A key factor was the ability to recognize near-native rigid-body geometries in a relatively low number of alternative docking poses, together with the successful refinement of the rigid-body docking interfaces. Since then, we have focused on improving the scoring function to optimally discriminate the near-native rigid-body conformations. For that, we have defined a new desolvation descriptor for rigid-body docking, based on atomic solvation parameters (ASPs) derived from octanol-water transfer experiments. This and other new approaches have been gradually incorporated into our docking procedure during our participation on the second CAPRI experiment. Overall, we produced reasonable models for 8 of the 9 official targets. Especially encouraging were those cases in which a homology model of 1 of the subunits had to be used during the docking simulations. And not less gratifying has been the successful prediction of antibody-antigen targets in a completely automatic, unrestrained fashion. In summary, our success rate (89%) shows a consistent improvement over the previous CAPRI rounds, and suggests that a correct desolvation description is key for improved protein-protein docking predictions.

Algorithms↗
PubMed2005

Pocketome via comprehensive identification and classification of ligand binding envelopes.

We developed a new computational algorithm for the accurate identification of ligand binding envelopes rather than surface binding sites. We performed a large scale classification of the identified envelopes according to their shape and physicochemical properties. The predicting algorithm, called PocketFinder, uses a transformation of the Lennard-Jones potential calculated from a three-dimensional protein structure and does not require any knowledge about a potential ligand molecule. We validated this algorithm using two systematically collected data sets of ligand binding pockets from complexed (bound) and uncomplexed (apo) structures from the Protein Data Bank, 5616 and 11,510, respectively. As many as 96.8% of experimental binding sites were predicted at better than 50% overlap level. Furthermore 95.0% of the asserted sites from the apo receptors were predicted at the same level. We demonstrate that conformational differences between the apo and bound pockets do not dramatically affect the prediction results. The algorithm can be used to predict ligand binding pockets of uncharacterized protein structures, suggest new allosteric pockets, evaluate feasibility of protein-protein interaction inhibition, and prioritize molecular targets. Finally the data base of the known and predicted binding pockets for the human proteome structures, the human pocketome, was collected and classified. The pocketome can be used for rapid evaluation of possible binding partners of a given chemical compound.

Algorithms↗
PubMed2005

REVCOM: a robust Bayesian method for evolutionary rate estimation.

MOTIVATION: Evolutionary conservation estimated from a multiple sequence alignment is a powerful indicator of the functional significance of a residue and helps to predict active sites, ligand binding sites, and protein interaction interfaces. Many algorithms that calculate conservation work well, provided an accurate and balanced alignment is used. However, such a strong dependence on the alignment makes the results highly variable. We attempted to improve the conservation prediction algorithm by making it more robust and less sensitive to (1) local alignment errors, (2) overrepresentation of sequences in some branches and (3) occasional presence of unrelated sequences. RESULTS: A novel method is presented for robust constrained Bayesian estimation of evolutionary rates that avoids overfitting independent rates and satisfies the above requirements. The method is evaluated and compared with an entropy-based conservation measure on a set of 1494 protein interfaces. We demonstrated that approximately 62% of the analyzed protein interfaces are more conserved than the remaining surface at the 5% significance level. A consistent method to incorporate alignment reliability is proposed and demonstrated to reduce arbitrary variation of calculated rates upon inclusion of distantly related or unrelated sequences into the alignment.

Algorithms↗
PubMed2005

Optimal docking area: a new method for predicting protein-protein interaction sites.

Understanding energetics and mechanism of protein-protein association remains one of the biggest theoretical problems in structural biology. It is assumed that desolvation must play an essential role during the association process, and indeed protein-protein interfaces in obligate complexes have been found to be highly hydrophobic. However, the identification of protein interaction sites from surface analysis of proteins involved in non-obligate protein-protein complexes is more challenging. Here we present Optimal Docking Area (ODA), a new fast and accurate method of analyzing a protein surface in search of areas with favorable energy change when buried upon protein-protein association. The method identifies continuous surface patches with optimal docking desolvation energy based on atomic solvation parameters adjusted for protein-protein docking. The procedure has been validated on the unbound structures of a total of 66 non-homologous proteins involved in non-obligate protein-protein hetero-complexes of known structure. Optimal docking areas with significant low-docking surface energy were found in around half of the proteins. The 'ODA hot spots' detected in X-ray unbound structures were correctly located in the known protein-protein binding sites in 80% of the cases. The role of these low-surface-energy areas during complex formation is discussed. Burial of these regions during protein-protein association may favor the complexed configurations with near-native interfaces but otherwise arbitrary orientations, thus driving the formation of an encounter complex. The patch prediction procedure is freely accessible at http://www.molsoft.com/oda and can be easily scaled up for predictions in structural proteomics.

Binding Sites↗
PubMed2005

Druggability of SCF ubiquitin ligase-protein interfaces.

The unique mechanism of the SCF ubiquitin ligase poses a challenge to drug discovery. A central enzymatic small molecule-binding active site is not evident in this multisubunit protein enzyme, as is the case with kinases or proteases. Instead, the SCF ligase seems to accomplish ubiquitylation through a series of cooperative movements dependent on the protein interfaces between its components and its substrate. Activity-modulating small molecules, therefore, need to interact with these protein interfaces. The three-dimensional structure of these interfaces may be the key asset in determining their suitability for small molecule binding. Computational tools and a systematic approach described in detail here can assess the "druggability" of an SCF ligase before the investment of effort in high-throughput screening (HTS), structure-based drug design (SBBD), or virtual library screening (VLS).

Binding Sites↗