Prediction of hypervariable CDR-H3 loop structures in antibodies.

Abstract

The structure of the most variable antibody hypervariable loop, CDR-H3, has been predicted from amino acid sequence alone. In contrast to other approaches predictions are made for loop lengths up to 17 residues. The predictions have been achieved using artificial neural networks which are trained on a large set of loops from the Brookhaven Protein Databank which have structures similar to CDR-H3. The loop structures are described by the two backbone dihedral angles phi and psi for each residue. For 21 CDR-H3 loops unique to the neural network, the prediction of dihedral angles leads to an average root mean square deviation in the Cartesian coordinates of 2.65 A. The present method, when combined with existing modelling protocols, provides an important addition to the structural prediction of the complementarity determining regions of antibodies.