Prediction of protein coarse contact maps.
Prediction of topological representations of proteins that are geometrically invariants can contribute towards the solution of fundamental open problems in structural genomics like folding. In this paper we focus on coarse grained protein contact maps, a representation that describes the spatial neighborhood relation between secondary structure elements such as helices, beta sheets, and random coils. Our methodology is based on searching the graph space. The search algorithm is guided by an adaptive evaluation function computed by a specialized noncausal recursive connectionist architecture. The neural network is trained using candidate graphs generated during examples of successful searches. Our results demonstrate the viability of the approach for predicting coarse contact maps.
Vullo
Alessandro
A
Department of Systems and Computer Science, Università di Firenze, Via di Santa Marta 3, I-50139 Firenze Italy. vullo@dsi.unifi.it
Frasconi
Paolo
P
D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D001665:Binding Sites; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011485:Protein Binding; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000032:analysis* / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017386:Sequence Homology, Amino Acid; D013329:Structure-Activity Relationship
D000596:Amino Acids; D011506:Proteins