PubMed Health⌕ Search

Biomedical subjects

Ram Samudrala

Publications and source records attributed to Ram Samudrala.

At least 19 recordsLinked to original sources
PubMed2005

Structural insights into the cellular retinaldehyde-binding protein (CRALBP).

Cellular retinaldehyde-binding protein (CRALBP) is an essential protein in the human visual cycle without a known three-dimensional structure. Previous studies associate retinal pathologies to specific mutations in the CRALBP protein. Here we use homology modeling and molecular dynamics methods to investigate the structural mechanisms by which CRALBP functions in the visual cycle. We have constructed two conformations of CRALBP representing two states in the process of ligand association and dissociation. Notably, our homology models map the pathology-associated mutations either directly in or adjacent to the putative ligand-binding cavity. Furthermore, six novel residues have been identified to be crucial for the hinge movement of the lipid-exchange loop in CRALBP. We conclude that the binding and release of retinoid involve large conformational changes in the lipid-exchange loop at the entrance of the ligand-binding cavity.

Amino Acid Sequence↗
PubMed2005

Improvement in protein functional site prediction by distinguishing structural and functional constraints on protein family evolution using computational design.

The prediction of functional sites in newly solved protein structures is a challenge for computational structural biology. Most methods for approaching this problem use evolutionary conservation as the primary indicator of the location of functional sites. However, sequence conservation reflects not only evolutionary selection at functional sites to maintain protein function, but also selection throughout the protein to maintain the stability of the folded state. To disentangle sequence conservation due to protein functional constraints from sequence conservation due to protein structural constraints, we use all atom computational protein design methodology to predict sequence profiles expected under solely structural constraints, and to compute the free energy difference between the naturally occurring amino acid and the lowest free energy amino acid at each position. We show that functional sites are more likely than non-functional sites to have computed sequence profiles which differ significantly from the naturally occurring sequence profiles and to have residues with sub-optimal free energies, and that incorporation of these two measures improves sequence based prediction of protein functional sites. The combined sequence and structure based functional site prediction method has been implemented in a publicly available web server.

Algorithms↗
PubMed2005

Origin and evolution of new exons in rodents.

Gene number difference among organisms demonstrates that new gene origination is a fundamental biological process in evolution. Exon shuffling has been universally observed in the formation of new genes. Yet to be learned are the ways new exons originate and evolve, and how often new exons appear. To address these questions, we identified 2695 newly evolved exons in the mouse and rat by comparing the expressed sequences of 12,419 orthologous genes between human and mouse, using 743,856 pig ESTs as the outgroup. The new exon origination rate is about 2.71 x 10(-3) per gene per million years. These new exons have markedly accelerated rates both of nonsynonymous substitutions and of insertions/deletions (indels). A much higher proportion of new exons have K(a)/K(s) ratios >1 (where K(a) is the nonsynonymous substitution rate and K(s) is the synonymous substitution rate) than do the old exons shared by human and mouse, implying a role of positive selection in the rapid evolution. The majority of these new exons have sequences unique in the genome, suggesting that most new exons might originate through "exonization" of intronic sequences. Most of the new exons appear to be alternative exons that are expressed at low levels.

Alternative Splicing↗
PubMed2005

BIOVERSE: enhancements to the framework for structural, functional and contextual modeling of proteins and proteomes.

We have made a number of enhancements to the previously described Bioverse web server and computational biology framework (http://bioverse.compbio.washington.edu). In this update, we provide an overview of the new features available that include: (i) expansion of the number of organisms represented in the Bioverse and addition of new data sources and novel prediction techniques not available elsewhere, including network-based annotation; (ii) reengineering the database backend and supporting code resulting in significant speed, search and ease-of use improvements; and (iii) creation of a stateful and dynamic web application frontend to improve interface speed and usability. Integrated Java-based applications also allow dynamic visualization of real and predicted protein interaction networks.

Computer Graphics↗
PubMed2005

PROTINFO: new algorithms for enhanced protein structure predictions.

We describe new algorithms and modules for protein structure prediction available as part of the PROTINFO web server. The modules, comparative and de novo modelling, have significantly improved back-end algorithms that were rigorously evaluated at the sixth meeting on the Critical Assessment of Protein Structure Prediction methods. We were one of four server groups invited to make an oral presentation (only the best performing groups are asked to do so). These two modules allow a user to submit a protein sequence and return atomic coordinates representing the tertiary structure of that protein. The PROTINFO server is available at http://protinfo.compbio.washington.edu.

Algorithms↗
PubMed2005

Functional annotation from predicted protein interaction networks.

MOTIVATION: Progress in large-scale experimental determination of protein-protein interaction networks for several organisms has resulted in innovative methods of functional inference based on network connectivity. However, the amount of effort and resources required for the elucidation of experimental protein interaction networks is prohibitive. Previously we, and others, have developed techniques to predict protein interactions for novel genomes using computational methods and data generated from other genomes. RESULTS: We evaluated the performance of a network-based functional annotation method that makes use of our predicted protein interaction networks. We show that this approach performs equally well on experimentally derived and predicted interaction networks, for both manually and computationally assigned annotations. We applied the method to predicted protein interaction networks for over 50 organisms from all domains of life, providing annotations for many previously unannotated proteins and verifying existing low-confidence annotations. AVAILABILITY: Functional predictions for over 50 organisms are available at http://bioverse.compbio.washington.edu and datasets used for analysis at http://data.compbio.washington.edu/misc/downloads/nannotation_data/. SUPPLEMENTARY INFORMATION: A supplemental appendix gives additional details not in the main text. (http://data.compbio.washington.edu/misc/downloads/nannotation_data/supplement.pdf).

Chromosome Mapping↗
PubMed2005

FSSA: a novel method for identifying functional signatures from structural alignments.

MOTIVATION: It is commonly believed that sequence determines structure, which in turn determines function. However, the presence of many proteins with the same structural fold but different functions suggests that global structure and function do not always correlate well. RESULTS: We propose a method for accurate functional annotation, based on identification of functional signatures from structural alignments (FSSA) using the Structural Classification of Proteins (SCOP) database. The FSSA method is superior at function discrimination and classification compared with several methods that directly inherit functional annotation information from homology inference, such as Smith-Waterman, PSI-BLAST, hidden Markov models and structure comparison methods, for a large number of structural fold families. Our results indicate that the contributions of amino acid residue types and positions to structure and function are largely separable for proteins in multi-functional fold families.

Algorithms↗
PubMed2005

Virtual screening of HIV-1 protease inhibitors against human cytomegalovirus protease using docking and molecular dynamics.

The clearance of cytomegalovirus viraemia in HIV-1-infected patients may partly result from the inhibition of cytomegalovirus protease by HIV-1 protease inhibitors contained in highly active antiretroviral therapy. We used a computational method to calculate the binding affinity of six HIV-1 protease inhibitors to cytomegalovirus protease based on its X-ray crystallography structure. The calculations showed that amprenavir and indinavir occupy the substrate-binding site of the cytomegalovirus protease with high affinity, and may be implicated in alleviating cytomegalovirus infection.

AIDS-Related Opportunistic Infections↗
PubMed2005

Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach.

Emergence of drug resistance remains one of the most challenging issues in the treatment of HIV-1 infection. Here we focus on resistance to HIV-1 protease inhibitors (PIs) at a molecular level, which can be analysed genotypically or phenotypically. Genotypic assays are based on the analysis of mutations associated with reduced drug susceptibility, but are problematic because of the numerous mutations and mutational patterns that confer drug resistance. Phenotypic resistance or susceptibility can be experimentally evaluated by measuring the amount of free drug bound to HIV-1 protease molecules, but this procedure is expensive and time-consuming. To overcome these problems, we have developed a docking protocol that takes protein-inhibitor flexibility into account to predict phenotypic drug resistance. For six FDA-approved Pls and a total of 1792 HIV-1 protease sequence mutants, we used a combination of inhibitor flexible docking and molecular dynamics (MD) simulations to calculate protein-inhibitor binding energies. Prediction results were expressed as fold changes of the calculated inhibitory constant (Ki), and the samples predicted to have fold-increase in calculated Ki above the fixed cut-off were defined as drug resistant. Our combined docking and MD protocol achieved accuracies ranging from 72-83% in predicting resistance/susceptibility for five of the six drugs evaluated. Evaluating the method only on samples where our predictions concurred with established knowledge-based methods resulted in increased accuracies of 83-94% for the six drugs. The results suggest that a physics-based approach, which is readily applicable to any novel PI and/or mutant, can be used judiciously with knowledge-based approaches that require experimental training data to devise accurate models of HIV-1 Pl resistance prediction.

Binding Sites↗
PubMed2004

An enhanced Java graph applet interface for visualizing interactomes.

UNLABELLED: We have developed several new navigation features for a Java graph applet previously released for visualizing protein-protein interactions. This graph viewer can be used to navigate any molecular interactome dataset. We have successfully implemented this tool for exploring protein networks stored in the Bioverse interaction database. AVAILABILITY: http://bioverse.compbio.washington.edu/viewer CONTACT: ram@compbio.washington.edu.

Animals↗
PubMed2004

Improved protein structure selection using decoy-dependent discriminatory functions.

BACKGROUND: A key component in protein structure prediction is a scoring or discriminatory function that can distinguish near-native conformations from misfolded ones. Various types of scoring functions have been developed to accomplish this goal, but their performance is not adequate to solve the structure selection problem. In addition, there is poor correlation between the scores and the accuracy of the generated conformations. RESULTS: We present a simple and nonparametric formula to estimate the accuracy of predicted conformations (or decoys). This scoring function, called the density score function, evaluates decoy conformations by performing an all-against-all Calpha RMSD (Root Mean Square Deviation) calculation in a given decoy set. We tested the density score function on 83 decoy sets grouped by their generation methods (4state_reduced, fisa, fisa_casp3, lmds, lattice_ssfit, semfold and Rosetta). The density scores have correlations as high as 0.9 with the Calpha RMSDs of the decoy conformations, measured relative to the experimental conformation for each decoy. We previously developed a residue-specific all-atom probability discriminatory function (RAPDF), which compiles statistics from a database of experimentally determined conformations, to aid in structure selection. Here, we present a decoy-dependent discriminatory function called self-RAPDF, where we compiled the atom-atom contact probabilities from all the conformations in a decoy set instead of using an ensemble of native conformations, with a weighting scheme based on the density scores. The self-RAPDF has a higher correlation with Calpha RMSD than RAPDF for 76/83 decoy sets, and selects better near-native conformations for 62/83 decoy sets. Self-RAPDF may be useful not only for selecting near-native conformations from decoy sets, but also for fold simulations and protein structure refinement. CONCLUSIONS: Both the density score and the self-RAPDF functions are decoy-dependent scoring functions for improved protein structure selection. Their success indicates that information from the ensemble of decoy conformations can be used to derive statistical probabilities and facilitate the identification of near-native structures.

Computational Biology↗
PubMed2004

Genomic organization and sequence variation of the human integrin subunit alpha8 gene (ITGA8).

The integrin alpha8 is highly expressed during kidney and lung development. alpha8-deficient mice display abnormal renal development suggesting that alpha8 plays a critical role in organogenesis. Therefore, it would be of considerable interest to understand the genomic structure, localization and sequence variation of the alpha8 gene. Using FISH and genomic database analysis, we show that alpha8 gene maps to chromosome 10p13 and consists of >200 kbp organized into 30 exons. Examination of 47 individuals from two different ethnic groups (European and African descent) identified 286 varying sites. The diversity of alpha8 is comparable to that of other regions within the human genome. Eight of the varying sites were located in the coding regions: six resulted in nonsynonymous substitutions of which two lead to non-conservative changes in protein. None of the sites showed significant deviation from Hardy-Weinberg equilibrium. We mapped the coding region single nucleotide polymorphisms (SNPs) onto a model of the predicted alpha8 structure and found all the SNPs were located in the "calf" of the extracellular domain. In the European population, the linkage disequilibrium statistic D' showed three blocks of relatively non-recombinant regions in the alpha8 gene while the African population showed more evidence of recombination. The observed patterns of the linkage disequilibrium statistic R2 suggest that a large number of sites will need to be genotyped to ensure coverage of the entire gene for genetic association studies. Identification of the sequence variation will allow genetic association studies of alpha8 in kidney and lung disease.

Base Sequence↗
PubMed2004

Enhanced functional information from predicted protein networks.

Experimentally derived genome-wide protein interaction networks have been useful in the elucidation of functional information that is not evident from examining individual proteins but determination of these networks is complex and time consuming. To address this problem, several computational methods for predicting protein networks in novel genomes have been developed. A recent publication by Date and Marcotte describes the use of phylogenetic profiling for elucidating novel pathways in proteomes that have not been experimentally characterized. This method, in combination with other computational methods for generating protein-interaction networks, might help identify novel functional pathways and enhance functional annotation of individual proteins.

Energy Metabolism↗