Bioinformatics Vol. 18 no. 1 2002
Pages 167-174
© 2002 Oxford University Press
Prediction of 3D neighbours of molecular surface patches in proteins by artificial neural networks
1 Medical Faculty of the Humboldt University, (Charité) Institute of Biochemistry, Monbijoustr. 2A, Berlin D-10117, Germany
Received on March 13, 2001
; revised on September 4, 2001
; accepted on September 7, 2001
Motivation: Molecular Surface Patches (MSPs) of proteins are responsible for selective interactions between internal parts of one protein molecule or between protein and other molecules. The prediction of the neighbours of a distinct Secondary Structural Element (SSE) would be an important step for protein structure prediction.
Results: Based on a computational analysis of complementary molecular patches of SSEs, feed-forward Neural Networks (NNs) are trained on a large set of helices for predicting the neighbours of given MSPs. Accuracy of prediction is 96% if only two types of neighbours: solvent or ‘protein’ are considered, yet drops to 81% for three types of neighbours: (1) solvent, (2) helix/strand or (3) coil. Implications of the method for the prediction of protein structure and subunit interaction are discussed. As a special test case, the structurally equivalent helices of monomeric myoglobin and the homologous subunits of tetrameric haemoglobin are compared.
Availability: Programs are available on request from the authors.
Contact: dietmann{at}ebi.ac.uk; cornelius.froemmel{at}charite.de
* To whom correspondence should be addressed.
2 Present address: EMBL Qutstation EBI, Hinxton, Cambridge CB10 ISD, UK.