Error Tolerant NMR Backbone Resonance Assignment for Automated Structure Generation

Error tolerant backbone resonance assignment is the cornerstone of the NMR structure determination process. Although a variety of assignment approaches have been developed, none works well on noisy automatically picked peaks. We have designed an integer linear programming (ILP) based assignment system (IPASS) for this purpose. In order to reduce size of the problem, IPASS employs probabilistic spin system typing based on chemical shifts and secondary structure predictions. Furthermore, IPASS extracts connectivity information from the interresidue information and the (automatically picked) 15N-edited NOESY peaks which are then used to fix reliable fragments. When applied on fully automatically picked peaks for real proteins, IPASS achieves an average precision and recall of 78% and 67%, respectively. In contrast, the next best method, MARS, achieves an average precision and recall of 50% and 40%, respectively. The assignments generated by IPASS are then fed into a protein structure calculation system, FALCON-NMR, to fully automatically determine the 3D structures. The final models have backbone RMSDs of 1.25Å, 0.88Å, 1.49Å, and 0.67Å to the native structures for proteins TM1112, CASKIN, VRAR, and HACS1, respectively. Our data suggest that IPASS is the first program to fulfill all of the criteria for fully automated structure generation. IPASS will be available upon request, and the web server for IPASS is under construction. ? The authors wish it to be known that, in their opinion, the first three authors should be regarded as Joint First Authors. ?? All correspondence should be addressed to [email protected].