Biomolecular structure prediction at a low resolution using a neural network and the double-iterated kalman filter technique
✍ Scribed by Ruth Pachter; Steven B. Fairchild; James A. Lupo; W. Wade Adams
- Publisher
- Wiley (John Wiley & Sons)
- Year
- 1998
- Tongue
- English
- Weight
- 737 KB
- Volume
- 39
- Category
- Article
- ISSN
- 0006-3525
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✦ Synopsis
We report the application of an integrated computational approach for biomolectilar structure determination at a low resolution. In particitlar, a neural network is trained to predict the spatial proximity of C-alpha atoms that are less than a given threshold apart, whereas a Kalman filter algorithm is employed to outline the biomolecular.fidd, with a constraints set that includes these pairwise atomic distances, and the distances and angles that define the structure as it is known from the protein 's sequence. The resultsfor Crambin demonstrate that this integrated approach is iuefii1,ji)r molecular structure prediction at a low resolution and may also complement existing experimental distunce datu,for a protein structure determination. 0 I996 John Wiley & Sons, Inc.