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Conrad C. Huang

Researcher at University of California, San Francisco

Publications -  64
Citations -  48439

Conrad C. Huang is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Haplotype & PharmGKB. The author has an hindex of 36, co-authored 63 publications receiving 36712 citations. Previous affiliations of Conrad C. Huang include University of California, Berkeley.

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MINRMS: an efficient algorithm for determining protein structure similarity using root-mean-squared-distance.

TL;DR: A heuristic for limiting the search space for structure alignment comparisons between two proteins, and an algorithm for finding minimal root-mean-squared-distance (RMSD) alignments as a function of the number of matching residue pairs within this limited search space are described.
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Computational investigations of structural changes resulting from point mutations in a collagen‐like peptide

TL;DR: The results demonstrate that molecular dynamics can be used to reproduce the experimental structures of collagen-like peptides, and demonstrate the feasibility of using the AMBER-94 molecular mechanical force field, which was parameterized to model nucleic acids and globular proteins, for fibril proteins.
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RRDistMaps: a UCSF Chimera tool for viewing and comparing protein distance maps.

TL;DR: A UCSF Chimera tool, RRDistMaps, to compute generalized contact maps in order to analyze pairwise variations in intramolecular contacts, and contains the unique features of identifying long-range residue motion and aligning sequences to simultaneously compare distance maps.
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Functional effects of protein sequence polymorphisms in the organic cation/ergothioneine transporter OCTN1 (SLC22A4).

TL;DR: The common OCTN1-L503F variant may explain a significant amount of population variation in the pharmacokinetics of OCTn1 substrate drugs, and provide a rational tool for studying the importance of ergothioneine in humans in vivo.
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Computed free energy differences between point mutations in a collagen-like peptide.

TL;DR: The sum of the calculated individual residues' free energy can accurately model the experimental free energy for the whole peptide, and the results demonstrate that each mutation does not contribute equally to the free energy.