Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Assigned and unassigned distance geometry: applications to biological molecules and nanostructures

  • Invited Survey
  • Published:
4OR Aims and scope Submit manuscript

Abstract

Considering geometry based on the concept of distance, the results found by Menger and Blumenthal originated a body of knowledge called distance geometry. This survey covers some recent developments for assigned and unassigned distance geometry and focuses on two main applications: determination of three-dimensional conformations of biological molecules and nanostructures.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Almeida FCL, Moraes AH, Gomes-Neto F (2013) An overview on protein structure determination by NMR. In: Mucherino A et al (eds) Historical and future perspectives of the use of distance geometry methods, pp 377–412

  • Berger B, Kleinberg J, Leighton T (2011) Reconstructing a three-dimensional model with arbitrary errors. J Assoc Comput Mach 50:212–235

    Google Scholar 

  • Billinge SJL (2010) Viewpoint: the nanostructure problem. Physics 3:25

    Article  Google Scholar 

  • Billinge SJL, Kanatzidis MG (2004) Beyond crystallography: the study of disorder, nanocrystallinity and crystallographically challenged materials with pair distribution functions. Chem Commun 7:749–760

    Article  Google Scholar 

  • Billinge SJL, Levin I (2007) The problem with determining atomic structure at the nanoscale. Science 316(5824):561–565

    Article  Google Scholar 

  • Blumenthal LM (1953) Theory and applications of distance geometry. Oxford University Press, Oxford

    Google Scholar 

  • Bouchevreau B, Martineau C, Mellot-Draznieks C, Tuel A, Suchomel MR, Trebosc J, Lafon O, Amoureux JP, Taulelle F (2013) An NMR-driven crystallography strategy to overcome the computability limit of powder structure determination: A layered aluminophosphate case. Int J Comput Geom Appl 19:5009–5013

    Google Scholar 

  • Boutin M, Kemper G (2007) Which point configurations are determined by the distribution of their pairwise distances. Int J Comput Geom Appl 17(1):31–43

    Article  Google Scholar 

  • Brunger AT, Adams PD, Clore GM, DeLano WL, Gros P, Grosse-Kunstleve RW, Jiang JS, Kuszewski J, Nilges M, Pannu NS, Read RJ, Rice LM, Simonson T, Warren GL (1998) Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr Sect D Biol Crystallogr 54(595):905–921

    Article  Google Scholar 

  • Carvalho RS, Lavor C, Protti F (2008) Extending the geometric build-up algorithm for the molecular distance geometry problem. Inf Process Lett 108:234–237

    Article  Google Scholar 

  • Cassioli A, Bardiaux B, Bouvier G, Mucherino A, Alves R, Liberti L, Nilges M, Lavor C, Malliavin TE (2015a) An algorithm to enumerate all possible protein conformations verifying a set of distance restraints. BMC Bioinform 16:23

    Article  Google Scholar 

  • Cassioli A, Gunluk O, Lavor C, Liberti L (2015b) Discretization vertex orders in distance geometry. Discrete Appl Math 197:27–41

    Article  Google Scholar 

  • Clore GM, Gronenborn AM (1997) New methods of structure refinement for macromolecular structure determination by NMR. Proc Natl Acad Sci 95:5891–5898

    Article  Google Scholar 

  • Connelly R (1991) On generic global rigidity. DIMACS Ser Discrete Math Theor Comput Sci 4:147–155

    Google Scholar 

  • Connelly R (2005) Generic global rigidity. Discrete Comput Geom 33:549–563

    Article  Google Scholar 

  • Connelly R (2013) Generic global rigidity of body-bar frameworks. J Comb Theory Ser B 103:689–705

    Article  Google Scholar 

  • Costa V, Mucherino A, Lavor C, Cassioli A, Carvalho L, Maculan N (2014) Discretization orders for protein side chains. J Glob Optim 60:333–349

    Article  Google Scholar 

  • Crippen GM, Havel TF (1988) Distance geometry and molecular conformation. Research Studies Press, Baldock

    Google Scholar 

  • Dokmanic I, Parhizkar R, Ranieri J, Vetterli M (2015) Euclidean distance matrices: essential theory, algorithms, and applications. IEEE Signal Process Mag 32(6):12–30

    Article  Google Scholar 

  • Dong Q, Wu Z (2002) A linear-time algorithm for solving the molecular distance geometry problem with exact interatomic distances. J Glob Optim 22:365–375

    Article  Google Scholar 

  • Duxbury PM, Granlund L, Gujarathi SR, Juhas P, Billinge SJL (2016) The unassigned distance geometry problem. Discrete Appl Math 204:117–132

    Article  Google Scholar 

  • Egami T, Billinge SJL (2012) Underneath the Bragg peaks: structural analysis of complex materials, 2nd edn. Pergamon Press, Oxford

    Google Scholar 

  • Eren T, Goldenberg DK, Whiteley W, Yang YR, Morse AS, Anderson BDO, Belhumeur PN (2004) Rigidity, computation and randomization in network localization. In: 23rd annual joint conference of the IEEE computer and communications societies, vol 4, pp 2673–2684

  • Evrard G, Pusztai L (2005) Reverse Monte Carlo modelling of the structure of disordered materials with RMC++: a new implementation of the algorithm in C++. J Phys Condens Matter 17:S1–S13

    Article  Google Scholar 

  • Farrow CL, Juhas P, Liu JW, Bryndin D, Boz̈in ES, Bloch J, Proffen T, Billinge SJL (2007) PDFfit2 and PDFgui: computer programs for studying nanostructure in crystals. J Phys Condens Matter 19(33):335219

    Article  Google Scholar 

  • Gaffney KJ, Chapman HN (2007) Imaging atomic structure and dynamics with ultrafast X-ray scattering. Science 36(5830):1444–1448

    Article  Google Scholar 

  • Gommes CJ, Jiao Y, Torquato S (2012) Microstructural degeneracy associated with a two-point correlation function and its information contents. Phys Rev E 85:051140

    Article  Google Scholar 

  • Gonçalves D, Mucherino A (2014) Discretization orders and efficient computation of Cartesian coordinates for distance geometry. Optim Lett 8:2111–2125

    Article  Google Scholar 

  • Gonçalves DS, Mucherino A, Lavor C (2014) An adaptive branching scheme for the branch & prune algorithm applied to distance geometry. In: IEEE conference proceedings, federated conference on computer science and information systems (FedCSIS 14), workshop on computational optimization (WCO14), Warsaw, Poland, pp 463–469

  • Gortler S, Healy A, Thurston D (2010) Characterizing generic global rigidity. Am J Math 132(4):897–939

    Article  Google Scholar 

  • Graver J, Servatius B, Servatius H (1993) Combinatorial rigidity. American Mathematical Society, issue 2 of graduate studies in mathematics

  • Guerry P, Herrmann T (2011) Advances in automated NMR protein structure determination. Q Rev Biophys 44(3):257–309

    Article  Google Scholar 

  • Gujarathi SR, Farrow CL, Glosser C, Granlund L, Duxbury PM (2014) Ab-initio reconstruction of complex Euclidean networks in two dimensions. Phys Rev 89:053311

    Google Scholar 

  • Hendrickson B (1992) Conditions for unique graph realizations. SIAM J Comput 21:65–84

    Article  Google Scholar 

  • Hendrickson B (1995) The molecule problem: exploiting structure in global optimization. SIAM J Optim 5(4):835–857

    Article  Google Scholar 

  • Jackson B, Jordan T (2005) Connected rigidity matroids and unique realization graphs. J Comb Theory Ser B 94:1–29

    Article  Google Scholar 

  • Jacobs DJ, Hendrickson B (1997) An algorithm for two-dimensional rigidity percolation: the pebble game. J Comput Phys 137:346–365

    Article  Google Scholar 

  • Jacobs DJ, Thorpe MF (1995) Generic rigidity percolation: the pebble game. Phys Rev Lett 75(22):4051–4054

    Article  Google Scholar 

  • Jaganathan K, Hassibi B (2013) Reconstruction of integers from pairwise distances. In: ICASSP, pp 5974–5978

  • Jain PC, Trigunayat GC (1977) Resolution of ambiguities in Zhdanov notation: actual examples of homometric structures. Acta Crystallogr A33:257–260

    Article  Google Scholar 

  • Juhás P, Cherba DM, Duxbury PM, Punch WF, Billinge SJL (2006) Ab initio determination of solid-state nanostructure. Nature 440(7084):655–658

    Article  Google Scholar 

  • Juhás P, Granlund L, Duxbury PM, Punch WF, Billinge SJL (2008) The LIGA algorithm for ab initio determination of nanostructure. Acta Crystallogr Sect A Found Crystallogr 64(Pt 6):631–640

    Article  Google Scholar 

  • Juhas P, Granlund L, Gujarathi SR, Duxbury PM, Billinge SJL (2010) Crystal structure solution from experimentally determined atomic pair distribution functions. J Appl Crystallogr 43:623–629

    Article  Google Scholar 

  • Laman G (1970) On graphs and rigidity of plane skeletal structures. J Eng Math 4:331–340

    Article  Google Scholar 

  • Lavor C, Mucherino A, Liberti L, Maculan N (2011) On the computation of protein backbones by using artificial backbones of hydrogens. J Glob Optim 50:329–344

    Article  Google Scholar 

  • Lavor C, Lee J, Lee-St.John A, Liberti L, Mucherino A, Sviridenko M (2012a) Discretization orders for distance geometry problems. Optim Lett 6(4):783–796

    Article  Google Scholar 

  • Lavor C, Liberti L, Maculan N, Mucherino A (2012b) The discretizable molecular distance geometry problem. Comput Optim Appl 52:115–146

    Article  Google Scholar 

  • Lavor C, Liberti L, Mucherino A (2013) The interval BP algorithm for the discretizable molecular distance geometry problem with interval data. J Glob Optim 56:855–871

    Article  Google Scholar 

  • Lavor C, Alves R, Figueiredo W, Petraglia A, Maculan N (2015) Clifford algebra and the discretizable molecular distance geometry problem. Adv Appl Clifford Algebras 25:925–942

    Article  Google Scholar 

  • Liberti L, Lavor C (2015) Six mathematical gems from the history of distance geometry. Int Trans Oper Res. doi:10.1111/itor.12170

  • Liberti L, Lavor C, Mucherino A (2013) In Mucherino A et al (eds) The discretizable molecular distance geometry problem seems easier on proteins, pp 47–60

  • Liberti L, Lavor C, Maculan N, Mucherino A (2014a) Euclidean distance geometry and applications. SIAM Rev 56(1):3–69

    Article  Google Scholar 

  • Liberti L, Masson B, Lee J, Lavor C, Mucherino A (2014b) On the number of realizations of certain Henneberg graphs arising in protein conformation. Discrete Appl Math 165:213–232

    Article  Google Scholar 

  • Lovász L, Yemini Y (1982) On generic rigidity in the plane. SIAM J Algorithms Discrete Math 3:91–98

    Article  Google Scholar 

  • McGreevy RL, Pusztai L (1988) Reverse Monte Carlo simulation: a new technique for the determination of disordered structures. Mol Simul 1:359–367

    Article  Google Scholar 

  • Menger K (1928) Dimension theorie. Teubner, Berlin

    Google Scholar 

  • Moukarzel C (1996) An efficient algorithm for testing the generic rigidity of graphs in the plane. J Phys A Math Gen 29:8079–8098

    Article  Google Scholar 

  • Moukarzel C, Duxbury PM (1995) Stressed backbone and elasticity of random central-force system. Phys Rev Lett 75(22):4055–4058

    Article  Google Scholar 

  • Mucherino A (2013) On the identification of discretization orders for distance geometry with intervals. In: Nielsen F, Barbaresco F (eds) Proceedings of geometric science of information (GSI 13). Lecture Notes in Computer Science, vol 8085, Paris, France, pp 231–238

  • Mucherino A (2015) A pseudo de bruijn graph representation for discretization orders for distance geometry. In: Ortuño F, Rojas I (eds) Lecture Notes in Computer Science, vol 9043, Lecture Notes in Bioinformatics series, Proceedings of the 3rd international work-conference on bioinformatics and biomedical engineering (IWBBIO15), Granada, Spain, pp 514–523

  • Mucherino A, Lavor C, Malliavin T, Liberti L, Nilges M, Maculan N (2011) Influence of pruning devices on the solution of molecular distance geometry problems. In: Pardalos PM, Rebennack S (eds) Lecture Notes in Computer Science, vol 6630, Proceedings of the 10th international symposium on experimental algorithms (SEA11), Crete, Greece, pp 206–217

  • Mucherino A, Lavor C, Liberti L (2012) The discretizable distance geometry problem. Optim Lett 6:1671–1686

    Article  Google Scholar 

  • Mucherino A, Lavor C, Liberti L, Maculan N (eds) (2013) Distance geometry: theory, methods, and applications. Springer, Berlin

    Google Scholar 

  • Mucherino A, de Freitas R, Lavor C (2015) Distance geometry and applications. Spec Issue Discrete Appl Math 197:1–144

    Article  Google Scholar 

  • Nilges M, O’Donoghue SI (1998) Ambiguous NOEs and automated NOE assignment. Prog Nucl Magn Reson Spectrosc 32(2):107–139

    Article  Google Scholar 

  • Patterson AL (1944) Ambiguities in the X-ray analysis of crystal structures. Phys Rev 65:195–201

    Article  Google Scholar 

  • Rader AJ, Hespenheide BM, Kuhn LA, Thorpe MF (2002) Protein unfolding: rigidity lost. PNAS 99:3540–3545

    Article  Google Scholar 

  • Saxe J (1979) Embeddability of weighted graphs in k-space is strongly NP-hard. In: Conference in communications control and computing, pp 480–489

  • Schneider MN, Seibald M, Lagally P, Oeckler O (2010) Ambiguities in the structure determination of antimony tellurides arising from almost homometric structure models and stacking disorder. J Appl Cryst 43:1011–1020

    Google Scholar 

  • Senechal M (2008) A point set puzzle revisited. Eur J Comb 29:1933–1944

    Article  Google Scholar 

  • Sivia DS (2011) Elementary scattering theory. Oxford University Press, Oxford

    Book  Google Scholar 

  • Skiena S, Smith W, Lemke P (1990) Reconstructing sets from interpoint distances. In Sixth ACM symposium on computational geometry, pp 332–339

  • Tay TS (1984) Rigidity of multi-graphs I: linking rigid bodies in n-space. J Comb Theory Ser B 36:95–112

    Article  Google Scholar 

  • Thorpe MF, Duxbury PM (eds) (1999) Rigidity theory and applications. Kluwer Academic, Dordrecht

    Google Scholar 

  • Tucker MG, Keen DA, Dove MT, Goodwin AL, Huie Q (2007) RMCProfile: reverse Monte Carlo for polycrystalline materialss. J Phys Condens Matter 19:335218

    Article  Google Scholar 

  • Voller Z, Wu Z (2013) Distance geometry methods for protein structure determination, pp 139–159. In Mucherino et al. (2013)

  • Whiteley W (2005) Counting out to the flexibility of molecules. Phys Biol 2:S116–S126

    Article  Google Scholar 

  • Wu D, Wu Z (2007) An updated geometric build-up algorithm for solving the molecular distance geometry problems with sparse data. J Glob Optim 37:661–672

    Article  Google Scholar 

  • Wuthrich K (1989) The development of nuclear magnetic resonance spectroscopy as a technique for protein structure determination. Acc Chem Res 22(1):36–44

    Article  Google Scholar 

Download references

Acknowledgments

Support for work at Michigan State University by the MSU foundation is gratefully acknowledged. Collaborations with Pavol Juhas, Luke Granlund, Saurabh Gujarathi, Chris Farrow and Connor Glosser are much appreciated. PMD, CL and AM would like to thank Leo Liberti for interesting and motivating discussions. AM was supported by a grant of University of Rennes 1 for the development of international collaborations. PMD and CL were financially supported by the Brazilian research agencies FAPESP and CNPq. Work in the Billinge group was supported by the US National Science foundation DMREF program through grant: DMR-1534910.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Douglas S. Gonçalves.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Billinge, S.J.L., Duxbury, P.M., Gonçalves, D.S. et al. Assigned and unassigned distance geometry: applications to biological molecules and nanostructures. 4OR-Q J Oper Res 14, 337–376 (2016). https://doi.org/10.1007/s10288-016-0314-2

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10288-016-0314-2

Keywords

Mathematics Subject Classification