Abstract
BackgroundThe prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model structures from a variety of alternatives that would correspond to a functional protein.ResultsUsing a large collection of protein-like decoy models, a score was devised that selected those with predicted functional site residues that formed a cluster. When tested on a variety of small α/β/α type proteins, including enzymes and non-enzymes, those that corresponded to the native fold were ranked highly. This performance held also for a selection of larger α/β/α proteins that played no part in the development of the method.ConclusionThe use of predicted site positions provides a useful filter to discriminate native-like protein models from non-native models. The method can be applied to any collection of models and should provide a useful aid to all modelling methods from ab initio to homology based approaches.
Highlights
The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites
We have shown that consideration of the requirement of proteins to form a functional site, either enzymic or binding, can be used to select the correct protein fold from a large number of well constructed decoy models
Our method uses only sequence data to do this in combination with the model structures and involves no information derived from the known structures
Summary
The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. With the increasing numbers of known structures, many recent methods have turned to the use of structure-based sequence alignment (threading) [1,2] or fragment assembly [3], including various hybrid combinations [4] Some of these methods are referred to as ab initio, they all rely on having a database of known structures and are better classed as de novo to distinguish them from a pure physico-chemical approach. With a view to using such information to constrain predictions, attempts were made to predict active site residues from a multiple sequence alignment [9] This approach relies on finding residues that are conserved for no apparent structural reason and some recent methods com-
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
