Biomedical subjects

R Samudrala

Publications and source records attributed to R Samudrala.

7 recordsLinked to original sources

PubMed1998

A graph-theoretic algorithm for comparative modeling of protein structure.

The interconnected nature of interactions in protein structures appears to be the major hurdle in preventing the construction of accurate comparative models. We present an algorithm that uses graph theory to handle this problem. Each possible conformation of a residue in an amino acid sequence is represented using the notion of a node in a graph. Each node is given a weight based on the degree of the interaction between its side-chain atoms and the local main-chain atoms. Edges are then drawn between pairs of residue conformations/nodes that are consistent with each other (i.e. clash-free and satisfying geometrical constraints). The edges are weighted based on the interactions between the atoms of the two nodes. Once the entire graph is constructed, all the maximal sets of completely connected nodes (cliques) are found using a clique-finding algorithm. The cliques with the best weights represent the optimal combinations of the various main-chain and side-chain possibilities, taking the respective environments into account. The algorithm is used in a comparative modeling scenario to build side-chains, regions of main chain, and mix and match between different homologs in a context-sensitive manner. The predictive power of this method is assessed by applying it to cases where the experimental structure is not known in advance.

Algorithms↗

PubMed1998

An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction.

We present a formalism to compute the probability of an amino acid sequence conformation being native-like, given a set of pairwise atom-atom distances. The formalism is used to derive three discriminatory functions with different types of representations for the atom-atom contacts observed in a database of protein structures. These functions include two virtual atom representations and one all-heavy atom representation. When applied to six different decoy sets containing a range of correct and incorrect conformations of amino acid sequences, the all-atom distance-dependent discriminatory function is able to identify correct from incorrect more often than the discriminatory functions using approximate representations. We illustrate the importance of using a detailed atomic description for obtaining the most accurate discrimination, and the necessity for testing discriminatory functions against a wide variety of decoys. The discriminatory function is also shown to be capable of capturing the fine details of atom-atom preferences. These results suggest that the all-atom distance-dependent discriminatory function will be useful for protein structure prediction and model refinement.

Models, Theoretical↗

PubMed1998

Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures.

For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-Calpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 A.

Computer Simulation↗

PubMed1998

Determinants of side chain conformational preferences in protein structures.

A discriminatory function based on a statistical analysis of atomic contacts in protein structures is used for selecting side chain rotamers given a peptide main chain. The function allows us to rank different possible side chain conformations on the basis of contacts between side chain atoms and atoms in the environment. We compare the differences in constructing side chain conformations using contacts with only the local main chain, using the entire main chain, and by building pairs of side chains simultaneously with local main chain information. Using only the local main chain allows us to construct side chains with approximately 75% of the chi1 angles within 30 degrees of the experimental value, and an average side chain atom r.m.s.d. of 1.72 A in a set of 10 proteins. The results of constructing side chains for the 10 proteins are compared with the results of other side chain building methods previously published. The comparison shows similar accuracies. An advantage of the present method is that it can be used to select a small number of likely side chain conformations for each residue, thus permitting limited combinatorial searches for building multiple protein side chains simultaneously.

Amino Acid Sequence↗

PubMed1997

Handling context-sensitivity in protein structures using graph theory: bona fide prediction.

We constructed five comparative models in a blind manner for the second meeting on the Critical Assessment of protein Structure Prediction methods (CASP2). The method used is based on a novel graph-theoretic clique-finding approach, and attempts to address the problem of interconnected structural changes in the comparative modeling of protein structures. We discuss briefly how the method is used for protein structure prediction, and detail how it performs in the blind tests. We find that compared to CASP1, significant improvements in building insertions and deletions and sidechain conformations have been achieved.

Amino Acid Sequence↗

PubMed1995

Confronting the problem of interconnected structural changes in the comparative modeling of proteins.

Comparative models of three proteins have been built using a variety of computational methods, heavily supplemented by visual inspection. We consider the accuracy obtained to be worse than expected. A careful analysis of the models shows that a major reason for the poor results is the interconnectedness of the structural differences between the target proteins and the template structures they were modeled from. Side chain conformations are often determined by details of the structure remote in the sequence, and can be influenced by relatively small main chain changes. Almost all of the regions of substantial main chain conformational change interact with at least one other such region, so that they often cannot be modeled independently. Visual inspection is sometimes effective in correcting errors in sequence alignment and in spotting when an alternative template structure is more appropriate. We expect some improvements in the near future through the development of structure-based sequence alignment tools, side chain interconnectedness rotamer choice algorithms, and a better understanding of the context sensitivity of conformational features.

Amino Acid Sequence↗

PubMed1990

Congenital neuroblastoma: evaluation with multimodality imaging.

The authors retrospectively evaluated 12 patients with congenital (neonatal) neuroblastoma to assess the utility of newer imaging modalities. Findings at prenatal ultrasound (US), performed in four patients, were nonspecific (hydramnios and hydrops fetalis) in two and consistent with a suprarenal mass (one solid, one cystic) in the other two. Postnatal US helped accurately detect adrenal tumors (solid or complex, with one exception) but was less accurate in the diagnosis of metastatic disease to the liver. Computed tomography accurately depicted all primary tumors and liver metastases. Magnetic resonance (MR) imaging helped establish the correct diagnosis in three patients. This study again confirmed the benign course of neonatal neuroblastoma, with 50% of the patients classified with stage IV-S disease and two deaths occurring in the series, both due to complications. Therefore, aggressive diagnostic imaging is less desirable, and US is therefore very useful, despite its limitations. The prenatal detection and solid appearance of a suprarenal mass makes the diagnosis of neuroblastoma very likely, as does the presence of liver lesions. In the absence of these characteristic findings, US should be repeated to exclude adrenal hemorrhage. MR imaging seems to be a good alternative in some instances.

Adrenal Gland Neoplasms↗