Biomedical subjects

Ruben Abagyan

Publications and source records attributed to Ruben Abagyan.

At least 37 records · Page 2Linked to original sources

PubMed2005

METLIN: a metabolite mass spectral database.

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.

Biomarkers↗

PubMed2004

Predictions of protein flexibility: first-order measures.

The normal modes of a molecule are utilized, in conjunction with classical conformal vector field theory, to define a function that measures the capability of the molecule to deform at each of its residues. An efficient algorithm is presented to calculate the local chain deformability from the set of normal modes of vibration. This is done by considering each mode as an off-grid sample of a deformation vector field. Predictions of deformability are compared with experimental data in the form of dihedral angle differences between two conformations of ten kinases by using a modified correlation function. Deformability calculations correlate well with experimental results and validate the applicability of this method to protein flexibility predictions.

Chemistry, Physical↗

PubMed2004

Determinants of retinoid X receptor transcriptional antagonism.

The synthesis and bioactivity of the retinoid X receptor (RXR) antagonist 4-[(3'-n-butyl-5',6',7',8'-tetrahydro-5',5',8',8'-tetramethyl-2'-naphthalenyl)(cyclopropylidene)methyl]benzoic acid and several heteroatom-substituted analogues are described. Ligand design was based on the scaffold of the 3'-methyl RXR-selective agonist analogue and reports that 3'-n-propyl and longer n-alkyl groups conferred RXR antagonism. The transcriptional antagonism of the 3'-n-butyl analogue was demonstrated by its blockade of retinoic acid receptor (RAR) beta expression induced by the RXRalpha/peroxisome proliferator-activated receptor (PPAR) gamma heterodimer complexed with an RXRalpha agonist plus the PPARgamma agonist ciglitazone and the inhibition of 9-cis-RA-induced coactivator SRC-1a recruitment to RXRalpha. Receptor-ligand docking studies using full-atom flexible ligand and flexible receptor suggested that binding of the antagonist to the RXRalpha antagonist conformation was favored because the salt bridge that formed between the retinoid carboxylate and the RXRalpha helix H5 arginine-321 was far stronger than that formed on its binding to the agonist conformation. The antagonist also blocked activation of RAR subtypes alpha and beta by 9-cis-RA but not that of RARgamma.

Benzoates↗

PubMed2004

Long chain amines and long chain ammonium salts as novel inhibitors of dynamin GTPase activity.

We examined a number of ligands with the view of inhibiting the GTPase activity of dynamin. Dynamin contains a pleckstrin homology (PH) domain that interacts with lipids. We report a series of simple lipid-like molecules that display moderate inhibitory activity. Inhibitory activity is linked to chain length and quaternarization of the terminal amine. A change in the counterion, Cl versus Br or I, had little effect on potency. However, introduction of a hydrophobic collar proximal to the charged site was beneficial to dynamin GTPase inhibitory action. The most potent compound was myristoyl trimethyl ammonium bromide (MTMAB, IC(50) 3.15 microM).

Amines↗

PubMed2004

SAD--a normalized structural alignment database: improving sequence-structure alignments.

MOTIVATION: We present a structural alignment database that is specifically targeted for use in derivation and optimization of sequence-structure alignment algorithms for homology modeling. We have paid attention to ensure that fold-space is properly sampled, that the structures involved in alignments are of significant resolution (better than 2.5 A) and the alignments are accurate and reliable. RESULTS: Alignments have been taken from the HOMSTRAD, BAliBASE and SCOP-based Gerstein databases along with alignments generated by a global structural alignment method described here. In order to discriminate between equivalent alignments from these different sources, we have developed a novel scoring function, Contact Alignment Quality score, which evaluates trial alignments by their statistical significance combined with their ability to reproduce conserved three-dimensional residue contacts. The resulting non-redundant, unbiased database contains 1927 alignments from across fold-space with high-resolution structures and a wide range of sequence identities. AVAILABILITY: The database can be interactively queried either over the web at http://abagyan.scripps.edu/lab/web/sad/show.cgi or by using MySQL, and is also available to download over the web.

Algorithms↗

PubMed2004

Identification of protein-protein interaction sites from docking energy landscapes.

Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.

Binding Sites↗

PubMed2004

Comprehensive identification of "druggable" protein ligand binding sites.

We have developed a new computational algorithm for de novo identification of protein-ligand binding pockets and performed a large-scale validation of the algorithm on two systematically collected datasets from all crystallographic structures in the Protein Data Bank (PDB). This algorithm, called DrugSite, takes a three-dimensional protein structure as input and returns the location, volume and shape of the putative small molecule binding sites by using a physical potential and without any knowledge about a potential ligand molecule. We validated this method using 17,126 binding sites from complexes and apo-structures from the PDB. Out of 5,616 binding sites from protein-ligand complexes, 98.8% were identified by predicted pockets. In proteins having known binding sites, 80.9% were predicted by the largest predicted pocket and 92.7% by the first two. The average ratio of predicted contact area to the total surface area of the protein was 4.7% for the predicted pockets. In only 1.2% of the cases, no "pocket density" was found at the ligand location. Further, 98.6% of 11,510 binding sites collected from apo-structures were predicted. The algorithm is accurate and fast enough to predict protein-ligand binding sites of uncharacterized protein structures, suggest new allosteric druggable pockets, evaluate druggability of protein-protein interfaces and prioritize molecular targets by druggability. Furthermore, the known and the predicted binding pockets for the proteome of a particular organism can be clustered into a "pocketome", that can be used for rapid evaluation of possible binding partners of a given chemical compound.

Algorithms↗

PubMed2003

Nuclear hormone receptor targeted virtual screening.

Virtual library screening (VLS) is emerging as a valuable drug lead discovery tool. ICM-VLS implementation of this technology was evaluated on a benchmark set of nuclear hormone receptors (NRs), an important therapeutic target family. Over 5000 structurally diverse compounds, including 78 known NR ligands, were screened against 18 crystal structures and one computer model of 10 NR ligand binding domains in their active or inactive states. The results confirm the ability of the VLS method to generate highly focused subsets of the input chemical library, enriched 33- to 100-fold for all but one receptor studied. However, receptor flexibility remains to be fully addressed, and the choice of the specific conformation used for screening may determine the success of the exercise. We observe that for a particular ligand VLS can often identify the correct target within the receptor family, although the technology is unable to reliably discriminate between the closely related receptor isoforms. Additionally, our results suggest that VLS may be applied successfully without an experimental structure of the receptor by using a homology model. These data represent a realistic snapshot of the state-of-the-art of NR-targeted VLS and define the recent progress and the remaining limitations of the technology.

Crystallography, X-Ray↗

PubMed2003

ICM-DISCO docking by global energy optimization with fully flexible side-chains.

The ICM-DISCO (Docking and Interface Side-Chain Optimization) protein-protein-docking method is a direct stochastic global energy optimization from multiple starting positions of the ligand. The first step is performed by docking of a rigid all-atom ligand molecule to a set of soft receptor potentials precalculated on a 0.5 A grid from realistic solvent-corrected force-field energies. This step finds the correct solution as the lowest energy conformation in almost 100% of the cases in which interfaces do not change on binding. The second step is needed to deal with the induced changes and includes the global optimization of the interface side-chains of up to 400 best solutions. The CAPRI predictions were performed fully automatically with this method. Available experimental information was included as a filtering step to favor expected docking surfaces. In three of the seven proposed targets, the ICM-DISCO method found a good solution (>50% of correct contacts) within the five submitted models. The procedure is global and fully automated. We demonstrate that the algorithm handles the induced changes of surface side-chains but is less successful if the backbone undergoes large-scale rearrangements.

Algorithms↗

PubMed2003

Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking.

Treatment of hyperthyroidism, a common clinical condition that can have serious manifestations in the elderly, has remained essentially unchanged for >30 years. Directly antagonizing the effect of the thyroid hormone at the receptor level may be a significant improvement for the treatment of hyperthyroid patients. We built a computer model of the thyroid hormone receptor (TR) ligand-binding domain in its predicted antagonist-bound conformation and used a virtual screening algorithm to select 100 TR antagonist candidates out of a library of >250,000 compounds. We were able to obtain 75 of the compounds selected in silico and studied their ability to act as antagonists by using cultured cells that express TR. Fourteen of these compounds were found to antagonize the effect of T3 on TR with IC50s ranging from 1.5 to 30 microM. A small virtual library of compounds, derived from the highest affinity antagonist (1-850) that could be rapidly synthesized, was generated. A second round of virtual screening identified new compounds with predicted increased antagonist activity. These second generation compounds were synthesized, and their ability to act as TR antagonists was confirmed by transfection and receptor binding experiments. The extreme structural diversity of the antagonist compounds shows how receptor-based virtual screening can identify diverse chemistries that comply with the structural rules of TR antagonism.

Drug Design↗

PubMed2003

ICFF: a new method to incorporate implicit flexibility into an internal coordinate force field.

We introduce a new method to accurately "project" a Cartesian force field onto an internal coordinate molecular model with fixed-bond geometry. The algorithm automatically generates the Internal Coordinate Force Field (ICFF), which is a close approximation of the "source" Cartesian force field. The ICFF method reduces the number of free variables in a model by at least 10-fold and facilitates the fast convergence of geometry optimizations, an advantage that is critical for many applications such as the docking of flexible ligands or conformational modeling of macromolecules. Although covalent geometry is fixed in an ICFF model, implicit flexibility is incorporated into the force field parameters in the following two ways. First, we formulate an empirical torsion energy term in ICFF as a sixfold Fourier series and develop a procedure to calculate the Fourier coefficients from the conformational energy profiles of the fully flexible Cartesian model. The ICFF torsion parameters thus represent not only torsion component of the source force field, but also bond bending, bond stretching, and "1-4" van der Waals interactions. Second, we use a soft polynomial repulsion function for "1-5" and "1-6" interactions to mimic the flexibility of bonds, connecting these atoms. Also, we suggest a way to use a local part of the Cartesian force field to automatically generate fixed covalent geometries, compatible with the ICFF energy function. Here, we present an implementation of the ICFF algorithm, which employs the MMFF94s Cartesian force field as a "source." Extensive benchmarking of ICFF with a representative set of organic molecules demonstrates that the implicit flexibility model accurately reproduces MMFF94s equilibrium conformational energy differences (RMSD approximately 0.64 kcal) and, most importantly, detailed torsion energy profiles (RMSD approximately 0.37 kcal). This accuracy is characteristic of the method, because all the ICFF parameters (except one scaling factor in the "1-5,1-6" repulsion term) are derived directly from the source Cartesian force field and do not depend on any particular molecular set. In contrast, the rigid geometry model with the MMFF94s energy function yields highly biased estimations in this test with the RMSD exceeding 1.2 kcal for the equilibrium energy comparisons and approximately 3.4 kcal for the torsion energy profiles.

Journal Article↗

PubMed2003

Comparative study of several algorithms for flexible ligand docking.

We have performed a comparative assessment of several programs for flexible molecular docking: DOCK 4.0, FlexX 1.8, AutoDock 3.0, GOLD 1.2 and ICM 2.8. This was accomplished using two different studies: docking experiments on a data set of 37 protein-ligand complexes and screening a library containing 10,037 entries against 11 different proteins. The docking accuracy of the methods was judged based on the corresponding rank-one solutions. We have found that the fraction of molecules docked with acceptable accuracy is 0.47, 0.31, 0.35, 0.52 and 0.93 for, respectively, AutoDock, DOCK, FlexX, GOLD and ICM. Thus ICM provided the highest accuracy in ligand docking against these receptors. The results from the other programs are found to be less accurate and of approximately the same quality. A speed comparison demonstrated that FlexX was the fastest and AutoDock was the slowest among the tested docking programs. The database screening was performed using DOCK, FlexX and ICM. ICM was able to identify the original ligands within the top 1% of the total library in 17 cases. The corresponding number for DOCK and FlexX was 7 and 8, respectively. We have estimated that in virtual database screening, 50% of the potentially active compounds will be found among approximately 1.5% of the top scoring solutions found with ICM and among approximately 9% of the top scoring solutions produced by DOCK and FlexX.

Algorithms↗

PubMed2003

The transthyretin-related protein family.

A number of proteins related to the homotetrameric transport protein transthyretin (TTR) forms a highly conserved protein family, which we present in an integrated analysis of data from different sources combined with an initial biochemical characterization. Homologues of the transthyretin-related protein (TRP) can be found in a wide range of species including bacteria, plants and animals, whereas transthyretins have so far only been identified in vertebrates. A multiple sequence alignment of 49 TRP sequences from 47 species to TTR suggests that the tertiary and quaternary features of the three-dimensional structure are most likely preserved. Interestingly, while some of the TRP orthologues show as little as 30% identity, the residues at the putative ligand-binding site are almost entirely conserved. RT/PCR analysis in Caenorhabditis elegans confirms that one TRP gene is transcribed, spliced and predominantly expressed in the worm, which suggests that at least one of the two C. elegans TRP genes encodes a functional protein. We used double-stranded RNA-mediated interference techniques in order to determine the loss-of-function phenotype for the two TRP genes in C. elegans but detected no apparent phenotype. The cloning and initial characterization of purified TRP from Escherichia coli reveals that, while still forming a homotetramer, this protein does not recognize thyroid hormones that are the natural ligands of TTR. The ligand for TRP is not known; however, genomic data support a functional role involving purine catabolism especially linked to urate oxidase (uricase) activity.

Amino Acid Sequence↗

PubMed2003

Algorithms for high-density oligonucleotide array.

As a global gene expression-monitoring tool, high-density oligonucleotide arrays (HDAs), accelerate biological and drug discovery processes. Computational considerations affect several key issues, from array design and accurate gene expression level determination to various aspects of the biological analysis of cell functions and gene networks. This review highlights recent progress in ideas and algorithms that are specific to HDAs. Replacing a large number of specific 'mismatch' oligonucleotides by a small number of general noise control oligonucleotides and using dynamic probe-to-gene mapping were some of the ideas proposed. Several novel mismatch-free probe-to-gene condensation algorithms have demonstrated the ability to take advantage of such designs, and provide higher density and equivalent or better calculation accuracy than previous algorithms. Algorithms to be developed in the future should significantly increase both the quality and quantity of information revealed by a single array; therefore, a single array containing the whole mammalian genome or even multiple genomes could soon become a standard tool.

Algorithms↗

PubMed2002

Excess polymorphisms in genes for membrane proteins in Plasmodium falciparum.

The detection of single-nucleotide polymorphisms in pathogenic microorganisms has normally been carried out by trial and error. Here we show that DNA hybridization with high-density oligonucleotide arrays provides rapid and convenient detection of single-nucleotide polymorphisms in Plasmodium falciparum, despite its exceptionally high adenine-thymine (AT) content (82%). A disproportionate number of polymorphisms are found in genes encoding proteins associated with the cell membrane. These genes are targets for only 22% of the oligonucleotide probes but account for 69% of the polymorphisms. Genetic variation is also enriched in subtelomeric regions, which account for 22% of the chromosome but 76% of the polymorphisms.

Animals↗

PubMed2002

Match-only integral distribution (MOID) algorithm for high-density oligonucleotide array analysis.

BACKGROUND: High-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics. RESULTS: A new algorithm, Match-Only Integral Distribution (MOID), was developed to analyze high-density oligonucleotide arrays. Using known data from both spiking experiments and no-change experiments performed with Affymetrix GeneChip arrays, MOID and the Affymetrix algorithm implemented in Microarray Suite 4.0 (MAS4) were compared. While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4. There are two main features that distinguish MOID from MAS4. First, MOID uses continuous P values for the likelihood of gene presence, while MAS4 resorts to discrete absolute calls. Secondly, MOID uses heuristic confidence intervals for both gene expression levels and fold change values, while MAS4 categorizes the significance of gene expression level changes into discrete fold change calls. CONCLUSIONS: The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

Algorithms↗

PubMed2002

Structural model of nicotinic acetylcholine receptor isotypes bound to acetylcholine and nicotine.

BACKGROUND: Nicotine is a psychoactive drug presenting a diverse array of biological activities, some positive, such as enhancement of cognitive performances, others negative, such as addiction liability. Ligands that discriminate between the different isotypes of nicotinic acetylcholine receptors (nAChRs) could present improved pharmacology and toxicity profile. RESULTS: Based on the recent crystal structure of a soluble acetylcholine binding protein from snails, we have built atomic models of acetylcholine and nicotine bound to the pocket of four different human nAChR subtypes. The structures of the docked ligands correlate with available biochemical data, and reveal that the determinants for isotype selectivity are relying essentially on four residues, providing diversity of the ligand binding pocket both in terms of Van der Waals boundary, and electrostatic potential. We used our models to screen in silico a large compound database and identify a new ligand candidate that could display subtype selectivity. CONCLUSION: The nAChR-agonist models should be useful for the design of nAChR agonists with diverse specificity profiles.

Acetylcholine↗

PubMed2002

Soft protein-protein docking in internal coordinates.

The association of two biological macromolecules is a fundamental biological phenomenon and an unsolved theoretical problem. Docking methods for ab initio prediction of association of two independently determined protein structures usually fail when they are applied to a large set of complexes, mostly because of inaccuracies in the scoring function and/or difficulties on simulating the rearrangement of the interface residues on binding. In this work we present an efficient pseudo-Brownian rigid-body docking procedure followed by Biased Probability Monte Carlo Minimization of the ligand interacting side-chains. The use of a soft interaction energy function precalculated on a grid, instead of the explicit energy, drastically increased the speed of the procedure. The method was tested on a benchmark of 24 protein-protein complexes in which the three-dimensional structures of their subunits (bound and free) were available. The rank of the near-native conformation in a list of candidate docking solutions was <20 in 85% of complexes with no major backbone motion on binding. Among them, as many as 7 out of 11 (64%) protease-inhibitor complexes can be successfully predicted as the highest rank conformations. The presented method can be further refined to include the binding site predictions and applied to the structures generated by the structural proteomics projects. All scripts are available on the Web.

Algorithms↗