arXiv subjects

Homayoun Valafar

Publications and source records attributed to Homayoun Valafar.

40 records · Page 3Linked to original sources

arXiv2019

PDBMine: A Reformulation of the Protein Data Bank to Facilitate Structural Data Mining

Large scale initiatives such as the Human Genome Project, Structural Genomics, and individual research teams have provided large deposits of genomic and proteomic data. The transfer of data to knowledge has become one of the existing challenges, which is a consequence of capturing data in databases that are optimally designed for archiving and not mining. In this research, we have targeted the Protein Databank (PDB) and demonstrated a transformation of its content, named PDBMine, that reduces storage space by an order of magnitude, and allows for powerful mining in relation to the topic of protein structure determination. We have demonstrated the utility of PDBMine in exploring the prevalence of dimeric and trimeric amino acid sequences and provided a mechanism of predicting protein structure.

cs.DB↗

arXiv2019

Using Residual Dipolar Couplings from Two Alignment Media to Detect Structural Homology

The method of Probability Density Profile Analysis has been introduced previously as a tool to find the best match between a set of experimentally generated Residual Dipolar Couplings and a set of known protein structures. While it proved effective on small databases in identifying protein fold families, and for picking the best result from computational protein folding tool ROBETTA, for larger data sets, more data is required. Here, the method of 2-D Probability Density Profile Analysis is presented which incorporates paired RDC data from 2 alignment media for N-H vectors. The method was tested using synthetic RDC data generated with +/-1 Hz error. The results show that the addition of information from a second alignment medium makes 2-D PDPA a much more effective tool that is able to identify a structure from a database of 600 protein fold family representatives.

q-bio.BM↗

arXiv2019

Aligning Multiple Protein Structures using Biochemical and Biophysical Properties

Aligning multiple protein structures can yield valuable information about structural similarities among related proteins, as well as provide insight into evolutionary relationships between proteins in a family. We have developed an algorithm (msTALI) for aligning multiple protein structures using biochemical and biophysical properties, including torsion angles, secondary structure, hydrophobicity, and surface accessibility. The algorithm is a progressive alignment algorithm motivated by popular techniques from multiple sequence alignment. It has demonstrated success in aligning the major structural regions of a set of proteins from the s/r kinase family. The algorithm was also successful at aligning functional residues of these proteins. In addition, the algorithm was also successful in aligning seven members of the acyl carrier protein family, including both experimentally derived as well as computationally modeled structures.

q-bio.BM↗

arXiv2019

Protein Fold Family Recognition From Unassigned Residual Dipolar Coupling Data

Despite many advances in computational modeling of protein structures, these methods have not been widely utilized by experimental structural biologists. Two major obstacles are preventing the transition from a purely-experimental to a purely-computational mode of protein structure determination. The first problem is that most computational methods need a large library of computed structures that span a large variety of protein fold families, while structural genomics initiatives have slowed in their ability to provide novel protein folds in recent years. The second problem is an unwillingness to trust computational models that have no experimental backing. In this paper we test a potential solution to these problems that we have called Probability Density Profile Analysis (PDPA) that utilizes unassigned residual dipolar coupling data that are relatively cheap to acquire from NMR experiments.

q-bio.BM↗