Automated design of specificity in molecular recognition

Specific protein-protein interactions are crucial in signaling networks and for the assembly of multi-protein complexes, and represent a challenging goal for protein design. Optimizing interaction specificity requires both positive design, the stabilization of a desired interaction, and negative design, the destabilization of undesired interactions. Currently, no automated protein-design algorithms use explicit negative design to guide a sequence search. We describe a multi-state framework for engineering specificity that selects sequences maximizing the transfer free energy of a protein from a target conformation to a set of undesired competitor conformations. To test the multi-state framework, we engineered coiled-coil interfaces that direct the formation of either homodimers or heterodimers. The algorithm identified three specificity motifs that have not been observed in naturally occurring coiled coils. In all cases, experimental results confirm the predicted specificities.     

Rapid detection of CAA/CAG repeat polymorphism in the AIB1 gene using DHPLC

Denaturing high-performance liquid chromatography (DHPLC) has been used for rapid and accurate DNA mutation analysis; to extend the DNA fragment lengths analysis. Recently, polymorphism in polyglutamine-coding region of Amplified In Breast cancer gene 1 (AIB1) was analyzed as an independent genetic risk factor influencing breast cancer onset in carriers of mutation in breast cancer predisposing gene 1 (BRCA1). We have implemented efficient, cost-effective and rapid method for analysis of the AIB1 polyglutamine repeat polymorphism based on DHPLC analysis (WAVE system) of unlabeled PCR products. This strategy can be useful for genotyping of other trinucleotide repeat polymorphisms using DHPLC in medium/high throughput settings.     

Design of a partial PPARdelta agonist

Structure based ligand design was used in order to design a partial agonist for the PPARdelta receptor. The maximum activation in the transactivation assay was reduced from 87% to 39%. The crystal structure of the ligand binding domain of the PPARdelta receptor in complex with compound 2 was determined in order to understand the structural changes which gave rise to the decrease in maximum activation.     

A simple physical model for the prediction and design of protein-DNA interactions

Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.