The seminar will be a journal club, in which students take turns presenting papers from the literature. Everyone is expected to read all the papers, and to present one or two (depending on how many students take the course). We may also have presentations of original research, both by UCSC researchers and by visitors.
I will post a list of papers that we might want to read here, as I think of them. I welcome suggestions for other papers to read!
I have no particular bias for subject area this quarter, and welcome suggestions from students about papers relevant to their own interests.
Abstract: We explore the ability of a simple simulated annealing procedure to assemble native-like structures from fragments of unrelated protein structures with similar local sequences using Bayesian scoring functions. Environment and residue pair specific contributions to the scoring functions appear as the first two terms in a series expansion for the residue probability distributions in the protein database; the decoupling of the distance and environment dependencies of the distributions resolves the major problems with current database-derived scoring functions noted by Thomas and Dill. The simulated annealing procedure rapidly and frequently generates native-like structures for small helical proteins and better than random structures for small beta sheet containing proteins. Most of the simulated structures have native-like solvent accessibility and secondary structure patterns, and thus ensembles of these structures provide a particularly challenging set of decoys for evaluating scoring functions. We investigate the effects of multiple sequence information and different types of conformational constraints on the overall performance of the method, and the ability of a variety of recently developed scoring functions to recognize the native-like conformations in the ensembles of simulated structures.
Simons KT, Ruczinski I, Kooperberg C, Fox BA, Bystroff C, Baker D
Improved recognition of native-like protein structures using a
combination of sequence-dependent and sequence-independent features of
proteins
PROTEINS-STRUCTURE FUNCTION AND GENETICS
34: (1) 82-95 JAN 1 1999
Abstract:
We describe the development of a scoring function based on the decomposition P(structure\sequence) proportional to P(sequence\structure) *P(structure), which outperforms previous scoring functions in correctly identifying native-like protein structures in large ensembles of compact decoys. The first term captures sequence-dependent features of protein structures, such as the burial of hydrophobic residues in the core, the second term, universal sequence-independent features, such as the assembly of beta-strands into beta-sheets. The efficacies of a wide variety of sequence-dependent and sequence-independent features of protein structures for recognizing native-like structures were systematically evaluated using ensembles of similar to 30,000 compact conformations with fixed secondary structure for each of 17 small protein domains. The best results were obtained using a core scoring function with P(sequence\structure) parameterized similarly to our previous work (Simons et al., J Mol Biol 1997;268:209-225] and P(structure) focused on secondary structure packing preferences; while several additional features had some discriminately power on their own, they did not provide any additional discriminatory power when combined with the core scoring function. Our results, on both the training set and the independent decoy set of Park and Levitt (J Mol Biol 1996;258:367-392), suggest that this scoring function should contribute to the prediction of tertiary structure from knowledge of sequence and secondary structure.
This paper makes an argument for hydrogen bonding being as important as hydrophobicity in stabilizing proteins.
We will probably not have time to cover the opposing viewpoint
in the following paper (if someone else could cover it a different
week), that would be great:
Dominant Forces in Protein Folding.
Dill, KA. Biochemistry 29:7133-7155, 1990.
This paper makes a strong argument that burial of hydrophobics is the main driving force for protein folding, and is the classic paper that the Pace et al. paper is responding to.
Falicov, A; Cohen, FE.
A surface of minimum area metric for the structural comparison of
proteins.
Journal of Molecular Biology, 1996 May 24, 258(5):871-92.
Use of a Nanoscale Pore To Read and Characterize DNA, RNA and Other Encoded Linear Polymers
Single molecules of DNA or RNA can be detected as they are driven through a nanoscale pore by an applied electric field. During translocation, nucleotides within the polynucleotide must pass through the channel pore in sequential, single-file order because the limiting diameter of the pore can accommodate only one strand of DNA or RNA at a time. We have shown that a nanopore can rapidly discriminate between pyrimidine, purine, and abasic segments along DNA or RNA molecules. The detector is also very sensitive to secondary structure including base-pairs within DNA hairpins. Nanopore detection and characterization of single molecules represents a new method for directly reading information encoded in biological and synthetic linear polymers, and is a necessary first step towards direct sequencing of individual DNA and RNA molecules.