Hunting down zinc(II)-binding sites in proteins with distance matrices.

ABSTRACT:

Motivation

In recent years, high-throughput sequencing technologies have made available the genome sequences of a huge variety of organisms. However, the functional annotation of the encoded proteins often still relies on low-throughput and costly experimental studies. Bioinformatics approaches offer a promising alternative to accelerate this process. In this work, we focus on the binding of zinc(II) ions, which is needed for 5%-10% of any organism's proteins to achieve their physiologically relevant form.

Results

To implement a predictor of zinc(II)-binding sites in the 3D structures of proteins, we used a neural network, followed by a filter of the network output against the local structure of all known sites. The latter was implemented as a function comparing the distance

SUBMITTER: Laveglia V 

PROVIDER: S-EPMC10630175 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature