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1.  Computational Alanine Scanning with Linear Scaling Semi-Empirical Quantum Mechanical Methods 
Proteins  2010;78(10):2329-2337.
Alanine scanning is a powerful experimental tool for understanding the key interactions in protein-protein interfaces. Linear scaling semi-empirical quantum mechanical calculations are now sufficiently fast and robust to allow meaningful calculations on large systems such as proteins, RNA and DNA. In particular, they have proven useful in understanding protein-ligand interactions. Here we ask the question: can these linear scaling quantum mechanical methods developed for protein-ligand scoring be useful for computational alanine scanning? To answer this question, we assembled 15 protein-protein complexes with available crystal structures and sufficient alanine scanning data. In all, the data set contains ΔΔGs for 400 single point alanine mutations of these 15 complexes. We show that with only one adjusted parameter the quantum mechanics based methods out perform both buried accessible surface area and a potential of mean force and compare favorably to a variety of published empirical methods. Finally, we closely examined the outliers in the data set and discuss some of the challenges that arise from this examination.
PMCID: PMC2919288  PMID: 20544968
Protein-Protein interactions; linear scaling quantum mechanics; computational alanine scanning
2.  Outcome of a Workshop on Applications of Protein Models in Biomedical Research 
We describe the proceedings and conclusions from a “Workshop on Applications of Protein Models in Biomedical Research” that was held at University of California at San Francisco on 11 and 12 July, 2008. At the workshop, international scientists involved with structure modeling explored (i) how models are currently used in biomedical research, (ii) what the requirements and challenges for different applications are, and (iii) how the interaction between the computational and experimental research communities could be strengthened to advance the field.
PMCID: PMC2739730  PMID: 19217386

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