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Statistical Survey of Chemical and Geometric Patterns on Protein Surfaces as a Blueprint for Protein-mimicking Nanoparticles
Open accessPreprint — published as 10.1002/sstr.202400086
Abstract
Despite recent breakthroughs in understanding how protein sequence relates to structure and function, considerably less attention has been paid to the general features of protein surfaces beyond those regions involved in binding and catalysis. This paper provides a systematic survey of the universe of protein surfaces and quantifies the sizes, shapes, and curvatures of the positively/negatively charged and hydrophobic/hydrophilic surface patches as well as correlations between such patches. It then compares these statistics with the metrics characterizing nanoparticles functionalized with ligands terminated with positively and negatively charged ligands. These particles are of particular interest because they are also surface-patchy and have been shown to exhibit both antibiotic and anticancer activities – via selective interactions against various cellular structures – prompting loose analogies to proteins. Our analyses support such analogies in several respects (e.g., patterns of charged protrusions and hydrophobic niches similar to those observed in proteins), although there are also significant differences. Looking forward, this work provides a blueprint for the rational design of synthetic nanoobjects with further enhanced mimicry of proteins’ surface properties.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Research works printed but not linked: 130
- 2019, The Pfam Protein Families Database in 2019, Nucleic Acids Res, 47, 427, 10.1093/nar/gky995 · DOI · Paper page
- 10.1186/1479-7364-4-3-207 · DOI
- 10.1093/nar/gkaa1100 · DOI · Paper page
- 10.1093/nar/28.1.235 · DOI · Paper page
- 2020, The SCOP Database in 2020: Expanded Classification of Representative Family and Superfamily Domains of Known Protein Structures, Nucleic Acids Res, 48, 376, 10.1093/nar/gkz1064 · DOI
- Kessel, A. ; Ben-Tal, N. Introduction to Proteins: Structure, Function, and Motion; CRC Press, 2010. · DOI
- 10.1088/1742-5468/ad1be7 · DOI
- 10.1038/75556 · DOI · Paper page
- 10.1126/science.abj8754 · DOI · Paper page
- 10.1103/PhysRevLett.131.218401 · DOI · Paper page
- Mcbride, J. M. ; Tlusty, T. AI-Predicted Protein Deformation Encodes Energy Landscape Perturbation. ArXiv Prepr. ArXiv231118222 2023. · DOI
- 10.1038/nature19946 · DOI · Paper page
- 10.1017/S0033583500005746 · DOI
- 10.1002/pro.5560070905 · DOI · Paper page
- 2006, CASTp: Computed Atlas of Surface Topography of Proteins with Structural and Topographical Mapping of Functionally Annotated Residues, Nucleic Acids Res, 34, 116, 10.1093/nar/gkl282 · DOI · Paper page
- 10.1007/s10930-007-9108-x · DOI
- 10.1038/nrd.2016.29 · DOI · Paper page
- 2021, Structural motifs in protein cores and at protein–protein interfaces are different, Protein Sci, 30, 381, 10.1002/pro.3996 · DOI
- 10.1038/nature05981 · DOI
- 2020, Deciphering Interaction Fingerprints from Protein Molecular Surfaces Using Geometric Deep Learning, Nat Methods, 17, 184, 10.1038/s41592-019-0666-6 · DOI
- 10.1093/molbev/msac217 · DOI
- 10.1073/pnas.0802460105 · DOI
- 2014, A Sequence-Specific Transcription Activator Motif and Powerful Synthetic Variants That Bind Mediator Using a Fuzzy Protein Interface, Proc Natl Acad Sci, 111, 3506
- 10.1016/j.febslet.2015.07.022 · DOI
- 10.1021/acs.jpclett.9b00099 · DOI
- 10.1073/pnas.1917569117 · DOI
- Ulmschneider, M. B. ; Sansom, M. S. P. Amino acid distributions in integral membrane protein structures. Biochim Biophys Acta - Biomembr 1512, 1–14. · DOI
- 2020, Protein Electrostatics: From Computational and Structural Analysis to Discovery of Functional Fingerprints and Biotechnological Design, Comput Struct Biotechnol J, 18, 1774, 10.1016/j.csbj.2020.06.029 · DOI
- 2018, Large-Scale Aggregation Analysis of Eukaryotic Proteins Reveals an Involvement of Intrinsically Disordered Regions in Protein Folding, Sci Rep, 8, 678, 10.1038/s41598-017-18977-5 · DOI
- Hebditch, M. ; Warwicker, J. Web-Based Display of Protein Surface and pH-Dependent Properties for Assessing the Developability of Biotherapeutics. Sci Rep 1969, 9. · DOI
- 2020, Effect of Protein Surface Charge Distribution on Protein–Polyelectrolyte Complexation, Biomacromolecules, 21, 3026, 10.1021/acs.biomac.0c00346 · DOI
- 10.1073/pnas.79.10.3236 · DOI
- 10.1016/j.tibs.2016.08.013 · DOI
- 10.1021/acs.chemrev.8b00753 · DOI
- 10.1016/j.sbi.2019.11.004 · DOI
- 10.1371/journal.pone.0000468 · DOI
- 10.1016/j.cell.2013.03.032 · DOI · Paper page
- 10.1016/j.molcel.2010.10.020 · DOI
- 10.3389/fimmu.2019.00133 · DOI
- 10.1073/pnas.81.1.140 · DOI
- 10.1002/bip.360250913 · DOI
- 10.1002/bip.360330107 · DOI
- 1995, Computation of the Dipole Moments of Proteins, Biophys J, 69, 1344, 10.1016/S0006-3495(95)80001-9 · DOI
- 10.1002/pro.5560050821 · DOI
- 1996, Hydrophobic Patches on the Surfaces of Protein Structures, Proteins Struct Funct Bioinforma, 25, 389, 10.1002/(SICI)1097-0134(199607)25:3<389::AID-PROT10>3.0.CO;2-E · DOI
- 1999, Spatial Sign-Alternating Charge Clusters in Globular Proteins, Protein Eng Sel, 12, 101, 10.1093/protein/12.2.101 · DOI
- Nicolau, D. V. ; Paszek, E. ; Fulga, F. ; Nicolau, D. V. Protein Molecular Surface Mapped at Different Geometrical Resolutions. PLoS One 2013, 8. · DOI
- 10.1371/journal.pone.0089680 · DOI · Paper page
- 10.1016/j.ijpharm.2010.02.025 · DOI
- 2016, Electrostatic Titrations Reveal Surface Compositions of Mixed, On-Nanoparticle Monolayers Comprising Positively and Negatively Charged Ligands, J Phys Chem C, 120, 4139, 10.1021/acs.jpcc.5b12599 · DOI
- 2013, Controlled pH Stability and Adjustable Cellular Uptake of Mixed-Charge Nanoparticles, J Am Chem Soc, 2, 1
- 2020, pH-Responsive Nanoparticles for Selective Interactions with Cells, Organelles, and Bacteria. Acc. Mater Res, 1, 188, 10.1021/accountsmr.0c00041 · DOI
- 2016, Self-Assembly of like-Charged Nanoparticles into Microscopic Crystals, Nanoscale, 8, 157, 10.1039/C5NR06983A · DOI
- 2016, Engineering Gram Selectivity of Mixed-Charge Gold Nanoparticles by Tuning the Balance of Surface Charges, Angew Chem. Int Ed, 55, 8610, 10.1002/anie.201602965 · DOI
- 2020, Targeted Crystallization of Mixed-Charge Nanoparticles in Lysosomes Induces Selective Death of Cancer Cells, Nat Nanotechnol, 15, 331, 10.1038/s41565-020-0643-3 · DOI
- 1999, Asparagine and Glutamine: Using Hydrogen Atom Contacts in the Choice of Side-Chain Amide orientation11Edited by J, Thornton J Mol Biol, 285, 1735
- 10.1093/nar/gkm276 · DOI
- 10.1002/(SICI)1097-0282(199603)38:3<305::AID-BIP4>3.0.CO;2-Y · DOI
- 10.1002/pro.3280 · DOI
- 10.1016/S0022-2836(03)00021-4 · DOI
- 10.1016/0022-2836(82)90515-0 · DOI
- Rego, N. B. ; Xi, E. ; Patel, A. J. Identifying Hydrophobic Protein Patches to Inform Protein Interaction Interfaces. Proc Natl Acad Sci 2021, 118. · DOI
- 10.1073/pnas.1910225116 · DOI
- 10.1016/j.bpj.2021.11.024 · DOI
- 10.1093/nar/gkaa1100 · DOI · Paper page
- 10.1038/s41598-018-28948-z · DOI
- 10.1093/molbev/msw046 · DOI
- 10.1007/BF01386390 · DOI
- Allen, M. P. ; Tildesley, D. J. Computer Simulation of Liquids, Second edition.; Oxford University Press: Oxford, 2017. · DOI · Paper page
- 10.1016/j.softx.2015.06.001 · DOI · Paper page
- 10.1093/nar/gkab1061 · DOI · Paper page
- 10.1021/acscatal.8b01323 · DOI
- 10.1002/jcc.20161 · DOI
- 10.1021/ja00124a002 · DOI
- 10.1021/jp801931d · DOI
- 10.1002/jcc.20290 · DOI · Paper page
- 10.1110/ps.03431704 · DOI
- 10.1016/0022-2836(87)90038-6 · DOI
- 10.1002/jmr.534 · DOI
- 10.1073/pnas.95.11.5942 · DOI
- 10.1371/journal.pcbi.1006858 · DOI
- 10.1016/0263-7855(83)80001-0 · DOI
- 2009, Size, Shape, and Flexibility of Proteins and DNA, J Chem Phys, 131, 165104, 10.1063/1.3251769 · DOI
- 2014, How round is a protein? Exploring protein structures for globularity using conformal mapping, Front Mol Biosci, 1, 26
- 10.1021/jp037128y · DOI
- 2019, Evolutionary Drivers of Protein Shape, Sci Rep, 9, 11873, 10.1038/s41598-019-47337-8 · DOI
- 10.1021/ja108154a · DOI
- 10.1016/j.trechm.2019.02.006 · DOI
- 10.1021/jacs.1c03939 · DOI
- 10.1039/D1SC05933E · DOI
- 10.1002/adma.202201562 · DOI
- 10.1021/jacs.2c06848 · DOI
- 2021, On-Nanoparticle Gating Units Render an Ordinary Catalyst Substrate- And Site-Selective, J Am Chem Soc, 143, 1807, 10.1021/jacs.0c09408 · DOI
- 10.1039/D2NR06341G · DOI
- 10.1038/nmat1116 · DOI
- 10.1103/PhysRevLett.99.226106 · DOI
- 10.1038/s41467-018-03699-7 · DOI
- 10.1146/annurev-biochem-060614-033955 · DOI · Paper page
- 10.1146/annurev-biochem-060208-092442 · DOI
- 10.1002/smll.200900358 · DOI
- 2002, Thermal Stability of Self-Assembled Monolayers: Influence of Lateral Hydrogen Bonding, J Phys Chem B, 106, 10401, 10.1021/jp0200526 · DOI
- 2012, Measuring the Activation Energy of Thiol Desorption Using Lateral Force Microscopy, Scanning, 34, 200, 10.1002/sca.20293 · DOI
- 10.1007/s00018-011-0852-x · DOI
- 10.1021/ja406089c · DOI
- 10.1002/marc.201900096 · DOI
- 10.1021/acs.chemrev.0c00428 · DOI
- 10.1021/acs.macromol.0c02826 · DOI
- 10.1016/j.jcis.2021.09.080 · DOI
- 10.1103/RevModPhys.91.031001 · DOI
- 10.1073/pnas.1716215115 · DOI
- 10.1073/pnas.1609462113 · DOI
- 2017, Physical Model of the Genotype-to-Phenotype Map of Proteins, Phys Rev X, 7, 021037
- 10.1098/rsta.2015.0070 · DOI
- 10.1002/bies.202100062 · DOI
- 10.1038/nrg2662 · DOI · Paper page
- 10.1016/j.plrev.2010.06.002 · DOI
- 10.1016/j.jtbi.2007.07.029 · DOI
- 10.1126/sciadv.abf1410 · DOI
- 10.1021/acs.chemrev.7b00194 · DOI
- 10.1002/smll.201101882 · DOI
- 10.1073/pnas.2403049121 · DOI
- 10.1515/BC.2000.109 · DOI
- 10.1126/science.1250494 · DOI · Paper page
- 10.1016/j.tibs.2015.07.009 · DOI
- 10.1073/pnas.0805135105 · DOI
- 10.1002/wnan.1788 · DOI
- 10.2147/IJN.S36111 · DOI
- 2014, Fabrication of Corona-Free Nanoparticles with Tunable Hydrophobicity, ACS Nano, 8, 6748, 10.1021/nn5006478 · DOI
- 2016, Striped Gold Nanoparticles: New Insights from Molecular Dynamics Simulations, J Chem Phys, 144, 244710, 10.1063/1.4954980 · DOI
- 2011, Nanoscale Phase Segregation of Mixed Thiolates on Gold Nanoparticles, Angew Chem. - Int Ed, 50, 10554, 10.1002/anie.201102882 · DOI
Metadata
- Authors
- McBride, J. M., Koshevarnikov, A., Siek, M., Grzybowski, B. A., & Tlusty, T.
- Affiliations
- Institute for Basic Science (KR)
- Institute of Organic Chemistry (PL)
- Corresponding author
- McBride, John M.
- Grzybowski, Bartosz A.
- Tlusty, Tsvi
- Venue
- Small Structures
- Publisher
- openRxiv
- Published
- 2024-07-19
- Volume
- 5
- Issue
- 9
- ISSN
- 2688-4062 (ISSN-L)
- OpenAlex
- W4401870761
- Cited by
- 4
- References
- 1
- Citations by year
- 2026: 1 · 2025: 3
- FWCI
- 0.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Small Structures (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Korea Basic Science Institute (IBS-R020)
- Institute for Basic Science (IBS-R-020, IBS-R-020-D1, R020-D1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Keywords
- protein surface, surface patches, hydrophobic patch, surface curvature, nanoparticle functionalization, ligand-functionalized nanoparticles, antibiotic activity, anticancer activity
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