Biblio

Found 19 results
Filters: Keyword is Computational Biology  [Clear All Filters]
2022
Martín M, Brunello FG, Modenutti CP, Nicola JP, Marti MA.  2022.  MotSASi: Functional short linear motifs (SLiMs) prediction based on genomic single nucleotide variants and structural data.. Biochimie. 197:59-73.
2021
Petrosino M, Novak L, Pasquo A, Chiaraluce R, Turina P, Capriotti E, Consalvi V.  2021.  Analysis and Interpretation of the Impact of Missense Variants in Cancer.. Int J Mol Sci. 22(11)
2020
Gonzalez TR, Martin KP, Barnes JE, Patel JSuresh, F Ytreberg M.  2020.  Assessment of software methods for estimating protein-protein relative binding affinities.. PLoS One. 15(12):e0240573.
2018
Khan NSaba, Verma R, Pradhan D, Nayek A, Bhuyan R, Sahu TKumar, Jain AKumar.  2018.  Analysis of interleukin 23 and 7G10 interactions for computational design of lead antibodies against immune-mediated inflammatory diseases.. J Recept Signal Transduct Res. 38(4):327-334.
oštarić NŠ, O'Reilly FJ, Giansanti P, Heck AJR, Gavin A-C, van Noort V.  2018.  Effects of Acetylation and Phosphorylation on Subunit Interactions in Three Large Eukaryotic Complexes.. Mol Cell Proteomics. 17(12):2387-2401.
2017
Xiong P, Zhang C, Zheng W, Zhang Y.  2017.  BindProfX: Assessing Mutation-Induced Binding Affinity Change by Protein Interface Profiles with Pseudo-Counts.. J Mol Biol. 429(3):426-434.
2016
Sulea T, Vivcharuk V, Corbeil CR, Deprez C, Purisima EO.  2016.  Assessment of Solvated Interaction Energy Function for Ranking Antibody-Antigen Binding Affinities.. J Chem Inf Model. 56(7):1292-303.
Huwe PJ, Xu Q, Shapovalov MV, Modi V, Andrake MD, Dunbrack RL.  2016.  Biological function derived from predicted structures in CASP11.. Proteins. 84 Suppl 1:370-91.
Van Durme J, De Baets G, Van Der Kant R, Ramakers M, Ganesan A, Wilkinson H, Gallardo R, Rousseau F, Schymkowitz J.  2016.  Solubis: a webserver to reduce protein aggregation through mutation.. Protein Eng Des Sel. 29(8):285-9.
2015
Liu Q, Ren J, Song J, Li J.  2015.  Co-Occurring Atomic Contacts for the Characterization of Protein Binding Hot Spots.. PLoS One. 10(12):e0144486.
Hashmi I, Shehu A.  2015.  idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.. J Comput Biol. 22(9):806-22.
Heselpoth RD, Yin Y, Moult J, Nelson DC.  2015.  Increasing the stability of the bacteriophage endolysin PlyC using rationale-based FoldX computational modeling.. Protein Eng Des Sel. 28(4):85-92.
2014
Liu Q, Hoi SCH, Kwoh CKeong, Wong L, Li J.  2014.  Integrating water exclusion theory into β contacts to predict binding free energy changes and binding hot spots.. BMC Bioinformatics. 15:57.
2007
Kiel C, Foglierini M, Kuemmerer N, Beltrao P, Serrano L.  2007.  A genome-wide Ras-effector interaction network.. J Mol Biol. 370(5):1020-32.
Tokuriki N, Stricher F, Schymkowitz J, Serrano L, Tawfik DS.  2007.  The stability effects of protein mutations appear to be universally distributed.. J Mol Biol. 369(5):1318-32.
2006
van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L, Quax WJ.  2006.  Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor.. Proc Natl Acad Sci U S A. 103(23):8634-9.
Musi V, Birdsall B, Fernandez-Ballester G, Guerrini R, Salvatori S, Serrano L, Pastore A.  2006.  New approaches to high-throughput structure characterization of SH3 complexes: the example of Myosin-3 and Myosin-5 SH3 domains from S. cerevisiae.. Protein Sci. 15(4):795-807.
Kiel C, Serrano L.  2006.  The ubiquitin domain superfold: structure-based sequence alignments and characterization of binding epitopes.. J Mol Biol. 355(4):821-44.
2005
Kiel C, Wohlgemuth S, Rousseau F, Schymkowitz J, Ferkinghoff-Borg J, Wittinghofer F, Serrano L.  2005.  Recognizing and defining true Ras binding domains II: in silico prediction based on homology modelling and energy calculations.. J Mol Biol. 348(3):759-75.