TY - JOUR
T1 - Present and future chanllenges and limitations in protein-Protein clocking
AU - Pons, Carles
AU - Grosdidier, Solène
AU - Solernou, Albert
AU - Pérez-Cano, Laura
AU - Fernández-Recio, Juan
PY - 2010
Y1 - 2010
N2 - The study of protein-protein interactions that are involved in essential life processes can largely benefit from the recent upraising of computational docking approaches. Predicting the structure of a protein-protein complex from their separate components is still a highly challenging task, but the field is rapidly improving. Recent advances in sampling algorithms and rigid-body scoring functions allow to produce, at least for some cases, high quality docking models that are perfectly suitable for biological and functional annotations, as it has been shown in the CAPRI blind tests. However, important challenges still remain in docking prediction. For example, in cases with significant mobility, such as multidomain proteins, fully unrestricted rigid-body docking approaches are clearly insufficient so they need to be combined with restraints derived from domaindomain linker residues, evolutionary information, or binding site predictions. Other challenging cases are weak or transient interactions, such as those between proteins involved in electron transfer, where the existence of alternative bound orientations and encounter complexes complicates the binding energy landscape. Docking methods also struggle when using in silico structural models for the interacting subunits. Bringing these challenges to a practical point of view, we have studied here the limitations of our docking and energy-based scoring approach, and have analyzed different parameters to overcome the limitations and improve the docking performance. For that, we have used the standard benchmark and some practical cases from CAPRI. Based on these results, we have devised a protocol to estimate the success of a given docking run.
AB - The study of protein-protein interactions that are involved in essential life processes can largely benefit from the recent upraising of computational docking approaches. Predicting the structure of a protein-protein complex from their separate components is still a highly challenging task, but the field is rapidly improving. Recent advances in sampling algorithms and rigid-body scoring functions allow to produce, at least for some cases, high quality docking models that are perfectly suitable for biological and functional annotations, as it has been shown in the CAPRI blind tests. However, important challenges still remain in docking prediction. For example, in cases with significant mobility, such as multidomain proteins, fully unrestricted rigid-body docking approaches are clearly insufficient so they need to be combined with restraints derived from domaindomain linker residues, evolutionary information, or binding site predictions. Other challenging cases are weak or transient interactions, such as those between proteins involved in electron transfer, where the existence of alternative bound orientations and encounter complexes complicates the binding energy landscape. Docking methods also struggle when using in silico structural models for the interacting subunits. Bringing these challenges to a practical point of view, we have studied here the limitations of our docking and energy-based scoring approach, and have analyzed different parameters to overcome the limitations and improve the docking performance. For that, we have used the standard benchmark and some practical cases from CAPRI. Based on these results, we have devised a protocol to estimate the success of a given docking run.
KW - CAPRI
KW - Desolvation
KW - Fast fourier transform
KW - Molecular recognition
KW - Protein-protein docking
UR - http://www.scopus.com/inward/record.url?scp=77949382951&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77949382951&partnerID=8YFLogxK
U2 - 10.1002/prot.22564
DO - 10.1002/prot.22564
M3 - Article
C2 - 19731373
AN - SCOPUS:77949382951
SN - 0887-3585
VL - 78
SP - 95
EP - 108
JO - Proteins: Structure, Function and Bioinformatics
JF - Proteins: Structure, Function and Bioinformatics
IS - 1
ER -