%0 Journal Article %1 Moal2013Scoring %A Moal, Iain H. %A Moretti, Rocco %A Baker, David %A Fernández-Recio, Juan %D 2013 %J Current opinion in structural biology %K high-throughput protein-protein-interactions %N 6 %P 862--867 %R 10.1016/j.sbi.2013.06.017 %T Scoring functions for protein-protein interactions. %U http://dx.doi.org/10.1016/j.sbi.2013.06.017 %V 23 %X The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright \copyright 2013 Elsevier Ltd. All rights reserved.

@article{Moal2013Scoring, abstract = {The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright {\copyright} 2013 Elsevier Ltd. All rights reserved.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Moal, Iain H. and Moretti, Rocco and Baker, David and Fern\'{a}ndez-Recio, Juan}, biburl = {https://www.bibsonomy.org/bibtex/2df6b5a4de820aff67cd287bc1fcb7937/karthikraman}, citeulike-article-id = {13427826}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.sbi.2013.06.017}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/23871100}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=23871100}, doi = {10.1016/j.sbi.2013.06.017}, interhash = {8949211b4aa31b8e5e636fb3ef8eb647}, intrahash = {df6b5a4de820aff67cd287bc1fcb7937}, issn = {1879-033X}, journal = {Current opinion in structural biology}, keywords = {high-throughput protein-protein-interactions}, month = dec, number = 6, pages = {862--867}, pmid = {23871100}, posted-at = {2014-11-13 18:32:00}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Scoring functions for protein-protein interactions.}, url = {http://dx.doi.org/10.1016/j.sbi.2013.06.017}, volume = 23, year = 2013 }