PREDICTION BY A NEURAL-NETWORK OF OUTER-MEMBRANE BETA-STRAND PROTEIN TOPOLOGY

An artificial neural network (NN) was trained to predict the topology of bacterial outer membrane (OM) beta-strand proteins. Specifically, t he NN predicts the z-coordinate of Ca atoms in a coordinate frame with the outer membrane in the xy-plane, such that low z-values indicate p eriplasmic turns, medium z-values indicate transmembrane beta-strands, and high z-values indicate extracellular loops. To obtain a training set, seven OM proteins (porins) with structures known to high resoluti on were aligned with their pores along the z-axis. The relationship be tween Ca z-values and topology was thereby established. To predict the topology of other OM proteins, all seven porins were used for the tra ining set. Z-values (topologies) were predicted for two porins with hi therto unknown structure and for OM proteins not belonging to the pori n family, all with insignificant sequence homology to the training set . The results of topology prediction compare favorably with experiment al topology data.