Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features.

ABSTRACT: Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the prote

SUBMITTER: Xiao W 

PROVIDER: S-EPMC9550495 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature