Conclusions

An effective loop-modeling procedure has been developed which uses probability grid Monte Carlo (PGMC) to search the conformational space of the loop backbone and its sidechains. Although this method is completely general, applicable to any loop conformation and sequence, it produces results comparable to methods requiring database matching or canonical structure matching. Modeling of the hypervariable loops of the immunoglobulins HyHEL-5 and McPC603 showed that most loops can be modeled to within 2 Å (backbone) or 3 Å (all-atom) rms deviations from the crystal structures. Additional energy terms using solvent-accessible surfaces or other solvation terms, may provide a means for improving the correlation between energy and rms fit to the crystal structure, thereby enabling backbone conformations to be regularly fit to near 1 Å or better. In addition, concurrent optimization of the sidechains of all six loops during Phase 2 should improve the packing of sidechains and the prediction of the shape of the antigen-binding site.

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