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Comparative Modeling (comparative + modeling)

Distribution by Scientific Domains

Chemistry	100%

Selected Abstracts

Prediction of the Candida antarctica Lipase A Protein Structure by Comparative Modeling and Site-Directed Mutagenesis

CHEMBIOCHEM, Issue 12 2007
Alex Kasrayan Dr.
Abstract A number of model structures of the CalA suggested by comparative modeling were tested by site-directed mutagenesis. Enzyme variants were created where amino acids predicted to play key roles for the lipase activity in the different models were replaced by an inert amino acid (alanine). The results from activity measurements of the overproduced and purified mutant enzymes indicate a structure where the active site consists of amino acid residues Ser184, His366, and Asp334 and in which there is no lid. This model can be used for future targeted modifications of the enzyme to obtain new substrate acceptance, better thermostability, and higher enantioselectivity. [source]

Evolutionary constraints on structural similarity in orthologs and paralogs,

PROTEIN SCIENCE, Issue 6 2009
Mark E. Peterson
Abstract Although a quantitative relationship between sequence similarity and structural similarity has long been established, little is known about the impact of orthology on the relationship between protein sequence and structure. Among homologs, orthologs (derived by speciation) more frequently have similar functions than paralogs (derived by duplication). Here, we hypothesize that an orthologous pair will tend to exhibit greater structural similarity than a paralogous pair at the same level of sequence similarity. To test this hypothesis, we used 284,459 pairwise structure-based alignments of 12,634 unique domains from SCOP as well as orthology and paralogy assignments from OrthoMCL DB. We divided the comparisons by sequence identity and determined whether the sequence-structure relationship differed between the orthologs and paralogs. We found that at levels of sequence identity between 30 and 70%, orthologous domain pairs indeed tend to be significantly more structurally similar than paralogous pairs at the same level of sequence identity. An even larger difference is found when comparing ligand binding residues instead of whole domains. These differences between orthologs and paralogs are expected to be useful for selecting template structures in comparative modeling and target proteins in structural genomics. [source]

Host,pathogen protein interactions predicted by comparative modeling

PROTEIN SCIENCE, Issue 12 2007
Fred P. Davis
Abstract Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host,pathogen interactions involve protein,protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host,pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for "neglected" human diseases. The method was assessed by (1) comparison to a set of known host,pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host,pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host,pathogen protein interactions. [source]

Structural conservation in the major facilitator superfamily as revealed by comparative modeling

PROTEIN SCIENCE, Issue 7 2004
Eyal Vardy
Abstract The structures of membrane transporters are still mostly unsolved. Only recently, the first two high-resolution structures of transporters of the major facilitator superfamily (MFS) were published. Despite the low sequence similarity of the two proteins involved, lactose permease and glycerol-3-phosphate transporter, the reported structures are highly similar. This leads to the hypothesis that all members of the MFS share a similar structure, regardless of their low sequence identity. To test this hypothesis, we generated models of two other members of the MFS, the Tn10-encoded metal-tetracycline/H+ antiporter (TetAB) and the rat vesicular monoamine transporter (rVMAT2). The models are based on the two MFS structures and on experimental data. The models for both proteins are in good agreement with the data available and support the notion of a shared fold for all MFS proteins. [source]

In search for more accurate alignments in the twilight zone

PROTEIN SCIENCE, Issue 7 2002
Lukasz Jaroszewski
Abstract A major bottleneck in comparative modeling is the alignment quality; this is especially true for proteins whose distant relationships could be reliably recognized only by recent advances in fold recognition. The best algorithms excel in recognizing distant homologs but often produce incorrect alignments for over 50% of protein pairs in large fold-prediction benchmarks. The alignments obtained by sequence,sequence or sequence,structure matching algorithms differ significantly from the structural alignments. To study this problem, we developed a simplified method to explicitly enumerate all possible alignments for a pair of proteins. This allowed us to estimate the number of significantly different alignments for a given scoring method that score better than the structural alignment. Using several examples of distantly related proteins, we show that for standard sequence,sequence alignment methods, the number of significantly different alignments is usually large, often about 1010 alternatives. This distance decreases when the alignment method is improved, but the number is still too large for the brute force enumeration approach. More effective strategies were needed, so we evaluated and compared two well-known approaches for searching the space of suboptimal alignments. We combined their best features and produced a hybrid method, which yielded alignments that surpassed the original alignments for about 50% of protein pairs with minimal computational effort. [source]

Modeling of loops in protein structures

PROTEIN SCIENCE, Issue 9 2000
András Fiser
Abstract Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4,, 8,, and 12,residue loop predictions, respectively, had <2 Å RMSD error for the mainchain N, Ca, C, and O atoms; the average accuracies were 0.59 6 0.05, 1.16 6 0.10, and 2.61 6 0.16 Å, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 Å, the average loop prediction error increased by 180, 25, and 3% for 4,, 8,, and 12,residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling. [source]