Improving the performance of rosetta using multiple sequence alignment information and global measures of hydrophobic core formation

We have developed a method that combines the ROSETTA de novo protein folding and refinement protocol with distance constraints derived from homologous structures to build homology models that are frequently more accurate than their templates. We test this method by building complete-chain models for a benchmark set of 22 proteins, each with 1 or 2 candidate templates, for a total of 39 test cases. We use structure-based and sequence-based alignments for each of the test cases. All atoms, including hydrogens, are represented explicitly. The resulting models contain approximately the same number of atomic overlaps as experimentally determined crystal structures and maintain good stereochemistry. The most accurate models can be identified by their energies, and in 22 of 39 cases a model that is more accurate than the template over aligned regions is one of the 10 lowest-energy models.fragment assembly ͉ structure prediction B uilding accurate 3D structural models for protein sequences of unknown structure is a challenging, unsolved problem in contemporary biology, and its solution would provide insight into a broad range of biological systems. Large-scale genomic sequencing efforts are providing increasing numbers of sequences, but the number of experimentally determined structures remains small by comparison. The goal of homology modeling methods is to match these query sequences with known template structures and construct accurate 3D models of the proteins.This task involves four steps: identifying suitable templates, aligning the query sequence to the templates, building the model for the query sequence by using information from the templates, and evaluating the models. Several methods are available to perform these steps and appear to perform similarly when used optimally (see refs. 1 and 2 for a description of several current methods). Although these methods have been useful, in most cases the final model is not more structurally similar to the query structure than the parent template (3, 4). In addition, many homology-modeling methods introduce physically unrealistic properties into the models in efforts to substitute the query sequence onto a nonnative backbone (2). The fixed backbone of the template is not always able to accommodate the side chains of the query sequence, particularly at buried positions, resulting in poor stereochemistry or atomic overlaps. Although the overall topology of the query structure can be derived from its homologs assuming a reasonably confident alignment, the atomic details of a homology model are of equal interest. Accurate modeling of side-chain and loop conformations is necessary in modeling and manipulating small molecule interactions, protein-protein and protein-nucleic acid interactions, and protein function.A useful homology model is one that can provide more information about a protein of interest than any homologous structures. The positions of the query sequence that are aligned to a template can be modeled by simply copying coordinates for the backbone atoms or by us...

show abstract

“…Cluster analysis was carried out as described in ref. 22, by using a clustering threshold of between 1 and 3 Å.…”

Section: Methodsmentioning

confidence: 99%

Physically realistic homology models built with rosetta can be more accurate than their templates

Misura

Chivian

Rohl

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

150

132

View full text Add to dashboard Cite

show abstract

“…We see previously that a sequence profile derived from multiple sequence alignments matches the prototype sequence well. This implies that information about multiple homologous sequences can help improve protein structure prediction as shown for both secondary structure prediction (52) and tertiary structure prediction (53)(54)(55).…”

Section: Implications For Protein Structure Prediction and Sequence Dmentioning

confidence: 99%

Roles of mutation and recombination in the evolution of protein thermodynamics

Xia

Levitt

2002

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

We present a comprehensive study of the evolutionary origin of the thermodynamic behavior of proteins. With the use of a simplified model, we exhaustively enumerate the space of all sequences and the space of all structures, simulate the evolutionary relationship between sequences and structures, and characterize the steady-state sequence distribution for all structures in terms of several thermodynamic variables. We assess the effects of two major forces of evolution: mutation and recombination. Three simplifications are made. First, a two-dimensional lattice model is used to represent protein sequences and structures. Second, proteins undergo neutral evolution so that the fitness landscape has a flat allowed region inside of which all sequences are equally fit. Third, we ignore otherwise important factors such as finite population size and evolutionary time. Two scenarios emerge from our study. The first occurs when evolution is dominated by mutation events. Even though the prototype sequence that is most mutationally robust is preferred by evolution, the preference is not strong enough to offset the huge size of sequence space. Most native sequences are located near the boundary of the fitness region and are marginally compatible with the native structure. The second scenario occurs when evolution is dominated by recombination events. Now evolutionary preference for prototype sequence is strong enough to overcome the size of sequence space so that most native sequences are located near the center of sequence-structure compatibility. We conclude that the relative frequency of mutation and recombination events is a major determinant of how optimal protein sequences are for their structures. U nderstanding the relationship between protein sequences and structures is a central theme in modern molecular biology. Such an understanding can be partially achieved by predicting the folded structure from the amino acid sequence, and by predicting the compatible sequences from a known structure, using physical principles or protein-specific knowledge. However, a better understanding requires a global view of the space of all sequences and the space of all structures and its dynamics as a result of evolution. Because proteins are building blocks of life and a direct result of evolution, it is crucial to understand how evolution shapes the global relationship between protein sequences and structures by simulating the process of evolution in a direct way.Molecular evolution is often simulated as an adaptive walk over a fitness landscape (1) of connected network of all sequences (2). Simulation of molecular evolution has been used to study RNA sequence-secondary structure relationship (3, 4). Simple tractable models such as lattice and spin-glass models are often used to understand physical principles of protein folding (5-7), because these models are often simple enough to allow for precise statistical mechanical characterization, yet are able to capture the dominant forces in protein folding (8). Recently, simple tractable...

show abstract

“…I-sites generates a fragment library, and with it, Rosetta searches conformational space using the Monte Carlo fragment insertion method. 19,22,23 …”

Section: Methodsmentioning

confidence: 99%

Predicting interresidue contacts using templates and pathways

Shao

Bystroff

2003

Proteins

View full text Add to dashboard Cite

We present a novel method, HMMSTR-CM, for protein contact map predictions. Contact potentials were calculated by using HMMSTR, a hidden Markov model for local sequence structure correlations. Targets were aligned against protein templates using a Bayesian method, and contact maps were generated by using these alignments. Contact potentials then were used to evaluate these templates. An ab initio method based on the target contact potentials using a rule-based strategy to model the protein-folding pathway was developed. Fold recognition and ab initio methods were combined to produce accurate, protein-like contact maps. Pathways sometimes led to an unambiguous prediction of topology, even without using templates. The results on CASP5 targets are discussed. Also included is a brief update on the quality of fully automated ab initio predictions using the I-sites server. Proteins 2003;53:497-502.

show abstract

Improving the performance of rosetta using multiple sequence alignment information and global measures of hydrophobic core formation

Cited by 86 publications

References 30 publications

Physically realistic homology models built with rosetta can be more accurate than their templates

Physically realistic homology models built with rosetta can be more accurate than their templates

Roles of mutation and recombination in the evolution of protein thermodynamics

Predicting interresidue contacts using templates and pathways

Contact Info

Product

Resources

About