MENSAdb: a thorough structural analysis of membrane protein dimers

Abstract Membrane proteins (MPs) are key players in a variety of different cellular processes and constitute the target of around 60% of all Food and Drug Administration–approved drugs. Despite their importance, there is still a massive lack of relevant structural, biochemical and mechanistic information mainly due to their localization within the lipid bilayer. To help fulfil this gap, we developed the MEmbrane protein dimer Novel Structure Analyser database (MENSAdb). This interactive web application summarizes the evolutionary and physicochemical properties of dimeric MPs to expand the available knowledge on the fundamental principles underlying their formation. Currently, MENSAdb contains features of 167 unique MPs (63% homo- and 37% heterodimers) and brings insights into the conservation of residues, accessible solvent area descriptors, average B-factors, intermolecular contacts at 2.5 Å and 4.0 Å distance cut-offs, hydrophobic contacts, hydrogen bonds, salt bridges, π–π stacking, T-stacking and cation–π interactions. The regular update and organization of all these data into a unique platform will allow a broad community of researchers to collect and analyse a large number of features efficiently, thus facilitating their use in the development of prediction models associated with MPs. Database URL: http://www.moreiralab.com/resources/mensadb.

[1]  Alan M. Jones,et al.  Saltational evolution of the heterotrimeric G protein signaling mechanisms in the plant kingdom , 2016, Science Signaling.

[2]  David J Weber,et al.  Structure of the STRA6 receptor for retinol uptake , 2016, Science.

[3]  Jie Liang,et al.  Detecting remote homologues using scoring matrices calculated from the estimation of amino acid substitution rates of beta-barrel membrane proteins , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Raquel Norel,et al.  Protein interface conservation across structure space , 2010, Proceedings of the National Academy of Sciences.

[5]  Kay Diederichs,et al.  Structure of the sucrose-specific porin ScrY from Salmonella typhimurium and its complex with sucrose , 1998, Nature Structural Biology.

[6]  F. Pucci,et al.  A comprehensive computational study of amino acid interactions in membrane proteins , 2019, Scientific Reports.

[7]  Qi Wang,et al.  Drug Target Protein-Protein Interaction Networks: A Systematic Perspective , 2017, BioMed research international.

[8]  J. Martins,et al.  Solvent‐accessible surface area: How well can be applied to hot‐spot detection? , 2014, Proteins.

[9]  M. Natália D. S. Cordeiro,et al.  Solvent Accessible Surface Area-Based Hot-Spot Detection Methods for Protein-Protein and Protein-Nucleic Acid Interfaces , 2015, J. Chem. Inf. Model..

[10]  J. M. Perez-Aguilar,et al.  Computational design of membrane proteins. , 2012, Structure.

[11]  P. Bourne,et al.  Exploiting sequence and structure homologs to identify protein–protein binding sites , 2005, Proteins.

[12]  Alexandre M J J Bonvin,et al.  SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots , 2017, Scientific Reports.

[13]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[14]  Gert Vriend,et al.  A series of PDB related databases for everyday needs , 2010, Nucleic Acids Res..

[15]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[16]  Irina S. Moreira,et al.  A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces , 2016, International journal of molecular sciences.

[17]  J M Thornton,et al.  Protein-protein interactions: a review of protein dimer structures. , 1995, Progress in biophysics and molecular biology.

[18]  J. Janin,et al.  Changes in protein structure at the interface accompanying complex formation , 2015, IUCrJ.

[19]  Wenchao Jiang,et al.  Identifying protein–protein interaction sites in transient complexes with temperature factor, sequence profile and accessible surface area , 2009, Amino Acids.

[20]  Robert Fredriksson,et al.  Mapping the human membrane proteome : a majority of the human membrane proteins can be classified according to function and evolutionary origin , 2015 .

[21]  Dmitrij Frishman,et al.  Residue co-evolution helps predict interaction sites in α-helical membrane proteins. , 2019, Journal of structural biology.

[22]  Andrew J. Bordner,et al.  Predicting protein-protein binding sites in membrane proteins , 2009, BMC Bioinformatics.

[23]  William F. DeGrado,et al.  Experimental and computational evaluation of forces directing the association of transmembrane helices. , 2009, Journal of the American Chemical Society.

[24]  Hwee Tong Tan,et al.  Membrane proteins and membrane proteomics , 2008, Proteomics.

[25]  Sven Rahmann,et al.  Non-symmetric score matrices and the detection of homologous transmembrane proteins , 2001, ISMB.

[26]  Hui-Ling Huang,et al.  Propensity Scores for Prediction and Characterization of Bioluminescent Proteins from Sequences , 2014, PloS one.

[27]  M. Sansom,et al.  Amino acid distributions in integral membrane protein structures. , 2001, Biochimica et biophysica acta.

[28]  Panagiotis I. Koukos,et al.  Structural Characterization of Membrane Protein Dimers. , 2019, Methods in molecular biology.

[29]  H. Yin,et al.  Drugging Membrane Protein Interactions. , 2016, Annual review of biomedical engineering.

[30]  S. G. Patching,et al.  Comprehensive analysis of the numbers, lengths and amino acid compositions of transmembrane helices in prokaryotic, eukaryotic and viral integral membrane proteins of high-resolution structure , 2018, Journal of biomolecular structure & dynamics.

[31]  J Andrew McCammon,et al.  BINANA: a novel algorithm for ligand-binding characterization. , 2011, Journal of molecular graphics & modelling.

[32]  G. Sciara,et al.  Structural basis for catalysis in a CDP-alcohol phosphotransferase , 2014, Nature Communications.

[33]  J. Fernández-Recio,et al.  Hot-spot analysis for drug discovery targeting protein-protein interactions , 2018, Expert opinion on drug discovery.

[34]  R. Garavito,et al.  Crystal structures of translocator protein (TSPO) and mutant mimic of a human polymorphism , 2015, Science.

[35]  Ilan Samish,et al.  The membrane- and soluble-protein helix-helix interactome: similar geometry via different interactions. , 2015, Structure.

[36]  Andrei L Lomize,et al.  The role of hydrophobic interactions in positioning of peripheral proteins in membranes , 2007, BMC Structural Biology.

[37]  Guoli Wang,et al.  PISCES: a protein sequence culling server , 2003, Bioinform..

[38]  David J Weber,et al.  Solution structure of zinc- and calcium-bound rat S100B as determined by nuclear magnetic resonance spectroscopy. , 2005, Biochemistry.

[39]  Jianhua Lin,et al.  Divergence measures based on the Shannon entropy , 1991, IEEE Trans. Inf. Theory.

[40]  Laurence Lins,et al.  Analysis of accessible surface of residues in proteins , 2003, Protein science : a publication of the Protein Society.

[41]  Bartek Wilczynski,et al.  Biopython: freely available Python tools for computational molecular biology and bioinformatics , 2009, Bioinform..

[42]  Joshua A. Kritzer,et al.  Comprehensive Analysis of Loops at Protein-Protein Interfaces for Macrocycle Design , 2014, Nature chemical biology.

[43]  Daniel R. Caffrey,et al.  Are protein–protein interfaces more conserved in sequence than the rest of the protein surface? , 2004, Protein science : a publication of the Protein Society.

[44]  A. Barabasi,et al.  Drug—target network , 2007, Nature Biotechnology.

[45]  Julie C. Mitchell,et al.  KFC Server: interactive forecasting of protein interaction hot spots , 2008, Nucleic Acids Res..

[46]  Jose M. Duarte,et al.  An analysis of oligomerization interfaces in transmembrane proteins , 2013, BMC Structural Biology.

[47]  So Iwata,et al.  Molecular Basis of Proton Motive Force Generation: Structure of Formate Dehydrogenase-N , 2002, Science.

[48]  H. Tajmir-Riahi,et al.  Effect of hydrophobicity on protein–protein interactions , 2015 .

[49]  Zhe Zhang,et al.  On the role of electrostatics in protein–protein interactions , 2011, Physical biology.

[50]  B. Rost,et al.  Conservation and prediction of solvent accessibility in protein families , 1994, Proteins.

[51]  Jeffrey L. Mendenhall,et al.  Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking , 2019, Computational and structural biotechnology journal.

[52]  R. Doolittle,et al.  A simple method for displaying the hydropathic character of a protein. , 1982, Journal of molecular biology.

[53]  Mona Singh,et al.  Predicting functionally important residues from sequence conservation , 2007, Bioinform..

[54]  W. Delano The PyMOL Molecular Graphics System , 2002 .

[55]  Markus Eilers,et al.  Comparison of Helix Interactions in Membrane and Soluble α-Bundle Proteins , 2002 .

[56]  Jack D. Dunitz,et al.  Atomic Dispacement Parameter Nomenclature. Report of a Subcommittee on Atomic Displacement Parameter Nomenclature , 1996 .

[57]  S. White,et al.  Biophysical dissection of membrane proteins , 2009, Nature.

[58]  Vasant Honavar,et al.  Characterization of Protein–Protein Interfaces , 2008, The protein journal.

[59]  Pedro A Fernandes,et al.  Hot spots—A review of the protein–protein interface determinant amino‐acid residues , 2007, Proteins.

[60]  John P. Overington,et al.  How many drug targets are there? , 2006, Nature Reviews Drug Discovery.

[61]  K Schulten,et al.  VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.

[62]  E. Koonin,et al.  Crystal Structure of a Hedgehog Autoprocessing Domain: Homology between Hedgehog and Self-Splicing Proteins , 1997, Cell.

[63]  Yu-Yen Ou,et al.  Bioinformatics approaches for functional annotation of membrane proteins , 2014, Briefings Bioinform..