Cited by 4Amyloidosis: Diagnosis, Treatment, OutcomesProtein Structure and DynamicsMultiple Myeloma Research and Treatments

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A conformational fingerprint for amyloidogenic light chains

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Abstract

Both immunoglobulin light-chain (LC) amyloidosis (AL) and multiple myeloma (MM) share the overproduction of a clonal LC. However, while LCs in MM remain soluble in circulation, AL LCs misfold into toxic-soluble species and amyloid fibrils that accumulate in organs, leading to distinct clinical manifestations. The significant sequence variability of LCs has hindered the understanding of the mechanisms driving LC aggregation. Nevertheless, emerging biochemical properties, including dimer stability, conformational dynamics, and proteolysis susceptibility, distinguish AL LCs from those in MM under native conditions. This study aimed to identify a 2 conformational fingerprint distinguishing AL from MM LCs. Using small-angle X-ray scattering (SAXS) under native conditions, we analyzed four AL and two MM LCs. We observed that AL LCs exhibited a slightly larger radius of gyration and greater deviations from X-ray crystallography-determined or predicted structures, reflecting enhanced conformational dynamics. SAXS data, integrated with molecular dynamics simulations, revealed a conformational ensemble where LCs adopt multiple states, with variable and constant domains either bent or straight. AL LCs displayed a distinct, low-populated, straight conformation (termed H state), which maximized solvent accessibility at the interface between constant and variable domains. Hydrogen-deuterium exchange mass spectrometry experimentally validated this H state. These findings reconcile diverse experimental observations and provide a precise structural target for future drug design efforts.

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Research works printed but not linked: 80

  1. Abraham, 2015, GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers, SoftwareX, 1–2, 19, 10.1016/j.softx.2015.06.001 · DOI · Paper page
  2. Absmeier, 2023, Antibodies gone bad - the molecular mechanism of light chain amyloidosis, The FEBS Journal, 290, 1398, 10.1111/febs.16390 · DOI
  3. Achour, 2020, Biochemical and biophysical comparison of human and mouse beta-2 microglobulin reveals the molecular determinants of low amyloid propensity, The FEBS Journal, 287, 546, 10.1111/febs.15046 · DOI
  4. Ahmed, 2021, Refinement of α-synuclein ensembles against SAXS data: comparison of force fields and methods, Frontiers in Molecular Biosciences, 8, 10.3389/fmolb.2021.654333 · DOI
  5. Al-Lazikani, 1997, Standard conformations for the canonical structures of immunoglobulins, Journal of Molecular Biology, 273, 927, 10.1006/jmbi.1997.1354 · DOI
  6. Ballabio, 2023, Accurate and efficient SAXS/SANS implementation including solvation layer effects suitable for molecular simulations, Journal of Chemical Theory and Computation, 19, 8401, 10.1021/acs.jctc.3c00864 · DOI · Paper page
  7. Blancas-Mejia, 2018, Immunoglobulin light chain amyloid aggregation, Chemical Communications, 54, 10664, 10.1039/c8cc04396e · DOI
  8. Blanchet, 2015, Versatile sample environments and automation for biological solution X-ray scattering experiments at the P12 beamline (PETRA III, DESY), Journal of Applied Crystallography, 48, 431, 10.1107/S160057671500254X · DOI
  9. Bonomi, 2016, Metainference: a Bayesian inference method for heterogeneous systems, Science Advances, 2, 10.1126/sciadv.1501177 · DOI
  10. Bonomi, 2016, Metadynamic metainference: enhanced sampling of the metainference ensemble using metadynamics, Scientific Reports, 6, 10.1038/srep31232 · DOI
  11. Bonomi, 2017, Integrative structural and dynamical biology with PLUMED-ISDB, Bioinformatics, 33, 3999, 10.1093/bioinformatics/btx529 · DOI
  12. Bonomi, 2019, Promoting transparency and reproducibility in enhanced molecular simulations, Nature Methods, 16, 670, 10.1038/s41592-019-0506-8 · DOI
  13. Bourne, 2002, Three-dimensional structure of an immunoglobulin light-chain dimer with amyloidogenic properties, Acta Crystallographica. Section D, Biological Crystallography, 58, 815, 10.1107/s0907444902004183 · DOI
  14. Branduardi, 2012, Metadynamics with adaptive gaussians, Journal of Chemical Theory and Computation, 8, 2247, 10.1021/ct3002464 · DOI
  15. Broggini, 2023, Nanobodies counteract the toxicity of an amyloidogenic light chain by stabilizing a partially open dimeric conformation, Journal of Molecular Biology, 435, 10.1016/j.jmb.2023.168320 · DOI
  16. Bussi, 2007, Canonical sampling through velocity rescaling, The Journal of Chemical Physics, 126, 10.1063/1.2408420 · DOI
  17. Camilloni, 2016, Rational design of mutations that change the aggregation rate of a protein while maintaining its native structure and stability, Scientific Reports, 6, 10.1038/srep25559 · DOI
  18. Cascino, 2022, Single-molecule real-time sequencing of the M protein: Toward personalized medicine in monoclonal gammopathies, American Journal of Hematology, 97, E389, 10.1002/ajh.26684 · DOI
  19. Chiu, 2019, Antibody structure and function: the basis for engineering therapeutics, Antibodies, 8, 10.3390/antib8040055 · DOI
  20. Comenzo, 2001, The tropism of organ involvement in primary systemic amyloidosis: contributions of Ig V(L) germ line gene use and clonal plasma cell burden, Blood, 98, 714, 10.1182/blood.v98.3.714 · DOI
  21. Dasari, 2015, Proteomic detection of immunoglobulin light chain variable region peptides from amyloidosis patient biopsies, Journal of Proteome Research, 14, 1957, 10.1021/acs.jproteome.5b00015 · DOI
  22. DeLano W. 2025. The pymol molecular graphics system. PyMol. 1.2. https://www.pymol.org/.
  23. Di Noia, 2007, Molecular mechanisms of antibody somatic hypermutation, Annual Review of Biochemistry, 76, 1, 10.1146/annurev.biochem.76.061705.090740 · DOI
  24. Garofalo, 2021, Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity, Nature Communications, 12, 10.1038/s41467-021-23880-9 · DOI
  25. Hopkins, 2015, Long-time-step molecular dynamics through hydrogen mass repartitioning, Journal of Chemical Theory and Computation, 11, 1864, 10.1021/ct5010406 · DOI
  26. Kazman, 2020, Fatal amyloid formation in a patient’s antibody light chain is caused by a single point mutation, eLife, 9, 10.7554/eLife.52300 · DOI
  27. Klimtchuk, 2023, Role of complementarity-determining regions 1 and 3 in pathologic amyloid formation by human immunoglobulin κ1 light chains, Amyloid, 30, 364, 10.1080/13506129.2023.2212397 · DOI
  28. Ko, 2019, Untying a Knotted SPOUT RNA methyltransferase by circular permutation results in a domain-swapped dimer, Structure, 27, 1224, 10.1016/j.str.2019.04.004 · DOI
  29. Kourelis, 2017, Clarifying immunoglobulin gene usage in systemic and localized immunoglobulin light-chain amyloidosis by mass spectrometry, Blood, 129, 299, 10.1182/blood-2016-10-743997 · DOI
  30. Lavatelli, 2020, Mass spectrometry characterization of light chain fragmentation sites in cardiac AL amyloidosis: insights into the timing of proteolysis, The Journal of Biological Chemistry, 295, 16572, 10.1074/jbc.RA120.013461 · DOI
  31. Le Marchand, 2018, Conformational dynamics in crystals reveal the molecular bases for D76N beta-2 microglobulin aggregation propensity, Nature Communications, 9, 10.1038/s41467-018-04078-y · DOI
  32. Löhr, 2017, Metadynamic metainference: convergence towards force field independent structural ensembles of a disordered peptide, The Journal of Chemical Physics, 146, 10.1063/1.4981211 · DOI
  33. Manalastas-Cantos, 2021, ATSAS 3.0: expanded functionality and new tools for small-angle scattering data analysis, Journal of Applied Crystallography, 54, 343, 10.1107/S1600576720013412 · DOI
  34. Maritan, 2020, Inherent biophysical properties modulate the toxicity of soluble amyloidogenic light chains, Journal of Molecular Biology, 432, 845, 10.1016/j.jmb.2019.12.015 · DOI
  35. Masson, 2019, Recommendations for performing, interpreting and reporting hydrogen deuterium exchange mass spectrometry (HDX-MS) experiments, Nature Methods, 16, 595, 10.1038/s41592-019-0459-y · DOI
  36. Mazzini, 2022, Protease-sensitive regions in amyloid light chains: what a common pattern of fragmentation across organs suggests about aggregation, The FEBS Journal, 289, 494, 10.1111/febs.16182 · DOI
  37. Merlini, 2018, Systemic immunoglobulin light chain amyloidosis, Nature Reviews. Disease Primers, 4, 10.1038/s41572-018-0034-3 · DOI
  38. Neudecker, 2012, Structure of an intermediate state in protein folding and aggregation, Science, 336, 362, 10.1126/science.1214203 · DOI
  39. Nokwe, 2015, The antibody light-chain linker is important for domain stability and amyloid formation, Journal of Molecular Biology, 427, 3572, 10.1016/j.jmb.2015.09.012 · DOI
  40. Oberti, 2017, Concurrent structural and biophysical traits link with immunoglobulin light chains amyloid propensity, Scientific Reports, 7, 10.1038/s41598-017-16953-7 · DOI
  41. Paissoni, 2020, Determination of protein structural ensembles by hybrid-resolution SAXS restrained molecular dynamics, Journal of Chemical Theory and Computation, 16, 2825, 10.1021/acs.jctc.9b01181 · DOI
  42. Paissoni, 2021, How to determine accurate conformational ensembles by metadynamics metainference: a chignolin study case, Frontiers in Molecular Biosciences, 8, 10.3389/fmolb.2021.694130 · DOI
  43. Parrinello, 1981, Polymorphic transitions in single crystals: a new molecular dynamics method, Journal of Applied Physics, 52, 7182, 10.1063/1.328693 · DOI
  44. Perfetti, 2012, The repertoire of λ light chains causing predominant amyloid heart involvement and identification of a preferentially involved germline gene, IGLV1-44, Blood, 119, 144, 10.1182/blood-2011-05-355784 · DOI
  45. Pernot, 2010, New beamline dedicated to solution scattering from biological macromolecules at the ESRF, Journal of Physics, 247, 10.1088/1742-6596/247/1/012009 · DOI
  46. Peterle, 2021, A conservative point mutation in a dynamic antigen-binding loop of human immunoglobulin λ6 light chain promotes pathologic amyloid formation, Journal of Molecular Biology, 433, 10.1016/j.jmb.2021.167310 · DOI
  47. Peterson, 2010, A single mutation promotes amyloidogenicity through A highly promiscuous dimer interface, Structure, 18, 563, 10.1016/j.str.2010.02.012 · DOI
  48. Pfaendtner, 2015, Efficient sampling of high-dimensional free-energy landscapes with parallel bias metadynamics, Journal of Chemical Theory and Computation, 11, 5062, 10.1021/acs.jctc.5b00846 · DOI
  49. Piana, 2015, Water dispersion interactions strongly influence simulated structural properties of disordered protein states, The Journal of Physical Chemistry. B, 119, 5113, 10.1021/jp508971m · DOI
  50. Piana, 2020, Development of a force field for the simulation of single-chain proteins and protein-protein complexes, Journal of Chemical Theory and Computation, 16, 2494, 10.1021/acs.jctc.9b00251 · DOI
  51. Poshusta, 2009, Mutations in specific structural regions of immunoglobulin light chains are associated with free light chain levels in patients with AL amyloidosis, PLOS ONE, 4, 10.1371/journal.pone.0005169 · DOI
  52. Pradhan, 2023, Mechanistic insights into the aggregation pathway of the patient-derived immunoglobulin light chain variable domain protein FOR005, Nature Communications, 14, 10.1038/s41467-023-39280-0 · DOI
  53. Puri, 2022, Impacts of cancer-associated mutations on the structure-activity relationship of BAP1, Journal of Molecular Biology, 434, 10.1016/j.jmb.2022.167553 · DOI
  54. Puri, 2022, Oxidation of catalytic cysteine of human deubiquitinase BAP1 triggers misfolding and aggregation in addition to functional loss, Biochemical and Biophysical Research Communications, 599, 57, 10.1016/j.bbrc.2022.02.029 · DOI
  55. Puri, 2023, The Cryo-EM STRUCTURE of renal amyloid fibril suggests structurally homogeneous multiorgan aggregation in AL Amyloidosis, Journal of Molecular Biology, 435, 10.1016/j.jmb.2023.168215 · DOI
  56. Puri, 2025, The critical role of the variable domain in driving proteotoxicity and aggregation in full-length light chains, Journal of Molecular Biology, 437, 10.1016/j.jmb.2025.168958 · DOI
  57. Radamaker, 2019, Cryo-EM structure of a light chain-derived amyloid fibril from a patient with systemic AL amyloidosis, Nature Communications, 10, 10.1038/s41467-019-09032-0 · DOI
  58. Radamaker, 2021, Cryo-EM reveals structural breaks in a patient-derived amyloid fibril from systemic AL amyloidosis, Nature Communications, 12, 10.1038/s41467-021-21126-2 · DOI
  59. Radamaker, 2021, Role of mutations and post-translational modifications in systemic AL amyloidosis studied by cryo-EM, Nature Communications, 12, 10.1038/s41467-021-26553-9 · DOI
  60. Rennella, 2019, Role of domain interactions in the aggregation of full-length immunoglobulin light chains, PNAS, 116, 854, 10.1073/pnas.1817538116 · DOI
  61. Rottenaicher, 2021, Molecular mechanism of amyloidogenic mutations in hypervariable regions of antibody light chains, The Journal of Biological Chemistry, 296, 10.1016/j.jbc.2021.100334 · DOI
  62. Rottenaicher, 2023, A constant domain mutation in A patient-derived antibody light chain reveals principles of AL amyloidosis, Communications Biology, 6, 10.1038/s42003-023-04574-y · DOI
  63. Saad, 2021, High conformational flexibility of the E2F1/DP1/DNA Complex, Journal of Molecular Biology, 433, 10.1016/j.jmb.2021.167119 · DOI
  64. Sala, 2020, Conformational stability and dynamics in crystals recapitulate protein behavior in solution, Biophysical Journal, 119, 978, 10.1016/j.bpj.2020.07.015 · DOI
  65. Schulte, 2024, Helical superstructures between amyloid and collagen in cardiac fibrils from a patient with AL amyloidosis, Nature Communications, 15, 10.1038/s41467-024-50686-2 · DOI
  66. Sun, 2023, Role of conformational dynamics in pathogenic protein aggregation, Current Opinion in Chemical Biology, 73, 10.1016/j.cbpa.2023.102280 · DOI
  67. Swuec, 2019, Cryo-EM structure of cardiac amyloid fibrils from an immunoglobulin light chain AL amyloidosis patient, Nature Communications, 10, 10.1038/s41467-019-09133-w · DOI
  68. Thomasen, 2022, Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins, Biochemical Society Transactions, 50, 541, 10.1042/BST20210499 · DOI
  69. Tribello, 2014, PLUMED 2: New feathers for an old bird, Computer Physics Communications, 185, 604, 10.1016/j.cpc.2013.09.018 · DOI
  70. Valentini, 2015, SASBDB, a repository for biological small-angle scattering data, Nucleic Acids Research, 43, D357, 10.1093/nar/gku1047 · DOI
  71. Visconti, 2019, Investigating the molecular basis of the aggregation propensity of the pathological D76N mutant of beta-2 microglobulin: role of the denatured state, International Journal of Molecular Sciences, 20, 10.3390/ijms20020396 · DOI
  72. Waterhouse, 2018, SWISS-MODEL: homology modelling of protein structures and complexes, Nucleic Acids Research, 46, W296, 10.1093/nar/gky427 · DOI
  73. Webb, 2016, Comparative Protein Structure Modeling Using MODELLER: Current Protocols in Bioinformatics 54, 10.1002/cpbi.3 · DOI
  74. Weber, 2018, The antibody light-chain linker regulates domain orientation and amyloidogenicity, Journal of Molecular Biology, 430, 4925, 10.1016/j.jmb.2018.10.024 · DOI
  75. Ballabio F. 2024. Immunoglobulin light chain H3. SASBDB. https://www.sasbdb.org/data/SASDVL4. SASDVL4.
  76. Ballabio F. 2024. Immunoglobulin light chain H7. SASBDB. https://www.sasbdb.org/data/SASDVM4. SASDVM4.
  77. Ballabio F. 2024. Immunoglobulin light chain H18. SASBDB. https://www.sasbdb.org/data/SASDVN4. SASDVN4.
  78. Ballabio F. 2024. Immunoglobulin light chain AL55. SASBDB. https://www.sasbdb.org/data/SASDVK4. SASDVK4.
  79. Ballabio F. 2024. Immunoglobulin light chain M7. SASBDB. https://www.sasbdb.org/data/SASDVP4. SASDVP4.
  80. Ballabio F. 2024. Immunoglobulin light chain M10. SASBDB. https://www.sasbdb.org/data/SASDVQ4. SASDVQ4.

Metadata

Authors
Paissoni, C., Puri, S., Broggini, L., Sriramoju, M. K., Maritan, M., Russo, R., Speranzini, V., Ballabio, F., Nuvolone, M., Merlini, G., Palladini, G., Hsu, S.-T. D., Ricagno, S., & Camilloni, C.
Affiliations
  • University of Milan (IT)
  • IRCCS Policlinico San Donato (IT)
  • Institute of Biological Chemistry, Academia Sinica (TW)
  • University of Pavia (IT)
  • Department of Bioscience, University of Milan
Corresponding author
Camilloni, Carlo
Venue
eLife
Published
2025-03-03
Volume
13
ISSN
2050-084X (ISSN-L)
OpenAlex
W4400603335
Cited by
4
References
1
Citations by year
2026: 2
FWCI
0.60
Type
journal article
Language
en
Open access
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
Funders
  • Ministero dell'Università e della Ricerca (PRIN 20207XLJB2)
  • Fondazione Cariplo (Telethon GJC23044)
  • Ministero della Salute (#GR-2018-12368387)
  • Fondazione AIRC per la ricerca sul cancro ETS (IG 2024 ID 30307)
  • Academia Sinica (AS-CDA-109- L08, AS-IV-114-L04)
  • National Science and Technology Council (113-2123-M-001-010-, 110-2113-M-001-050-MY3, 113-2811-M-001-110)
Topics
  • Health Sciences › Medicine › Internal Medicine › Amyloidosis: Diagnosis, Treatment, Outcomes
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Health Sciences › Medicine › Hematology › Multiple Myeloma Research and Treatments
Keywords
immunoglobulin light chain amyloidosis, multiple myeloma, amyloid fibrils, conformational dynamics, conformational ensembles, hydrogen-deuterium exchange, radius of gyration, solvent accessibility, small-angle X-ray scattering, molecular dynamics simulation, drug design targets

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