Protein language model identifies disordered, conserved motifs implicated in phase separation
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Abstract
Intrinsically disordered regions (IDRs) play a critical role in phase separation and are essential for the formation of membraneless organelles (MLOs). Mutations within IDRs can disrupt their multivalent interaction networks, altering phase behavior and contributing to various diseases. Therefore, examining the evolutionary constraints of IDRs provides valuable insights into the relationship between protein sequences and phase separation. In this study, we utilized the ESM2 protein language model to map the residue-level mutational tolerance landscapes of IDRs. Our findings reveal that IDRs, particularly those actively participating in phase separation, contain conserved amino acids. This conservation is evident through mutational constraints predicted by ESM2 and supported by direct analyses of multiple sequence alignments. These conserved, disordered amino acids include residues traditionally identified as ‘stickers’ as well as ‘spacers’ and frequently form continuous sequence motifs. The strong conservation, combined with their potential role in phase separation, suggests that these motifs may act as functional units under evolutionary selection to support stable MLO formation. Our findings underscore the insights into phase separation’s molecular grammar made possible through evolutionary analysis enabled by protein language models.
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“Mutations in IDRs can disrupt phase behavior, potentially leading to MLO dysfunction and contributing to diseases such as neurodegenerative disorders and cancer ( Alberti and Dormann, 2019 ; Zbinden et al., 2020 ; Rai et al., 2021 ; Das et al., 2020 ).”
Phase Transitions of Spindle-Associated Protein Regulate Spindle Apparatus Assembly
Jiang, H., Wang, S., Huang, Y., He, X.-N., Cui, H., Zhu, X.-L., & Zheng, Y.-X. (2015) · Cell · doi:10.1016/j.cell.2015.08.010 · Cited by 291 · cited 3× · see citing works
“…et al., 2023 ; Banani et al., 2017 ; Choi et al., 2020 ; Pappu et al., 2023 ; Ginell and Holehouse, 2023 ; Latham and Zhang, 2020 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022c ; Latham and Zhang, 2022b ; Latham et al., 2024 ; Liu et al., 2025 ; Lao and Zhang, 2024 ; Jiang et al., 2015 ).”
Brown, C. J., Johnson, A. K., Dunker, A., & Daughdrill, G. (2011) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2011.02.005 · Cited by 288 · cited 1× · see citing works
“In contrast, disordered residues (pLDDT ≤70) predominantly show high ESM2 scores (region II, ESM2 score ≥2.0), consistent with the rapid evolution and higher mutational tolerance typical of disordered proteins ( Brown et al., 2011 ; Liu and Huang, 2014 ; Forman-Kay and Mittag, 2013 ).”
InfluentialSchuster, B. S., Dignon, G., Tang, W.-S., Kelley, F., Ranganath, A. K., Jahnke, C., Simpkins, A. G., Regy, R. M., Hammer, D., Good, M., et al. (2020) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1101/2020.01.06.894576 · Cited by 276 · cited 4×
“…that these conserved amino acids encompass both ‘sticker’ and ‘spacer’ classifications, as defined in recent literature ( Jiang et al., 2015 ; Schuster et al., 2020 ; Yang et al., 2019 ; Tatavosian et al., 2019 ; Larson et al., 2017 ; DiRusso et al., 2023 ; Mitrea et al., 2018 ; Xiao et al.,…”
InfluentialFrom Sequence and Forces to Structure, Function, and Evolution of Intrinsically Disordered Proteins
Forman-Kay, J. D., & Mittag, T. (2013) · Structure · doi:10.1016/j.str.2013.08.001 · Cited by 259 · cited 1× · see citing works
“This distinction allows us to classify disordered regions into two types: ‘flexible disordered’ regions, which show high ESM2 scores and greater mutational tolerance, and ‘conserved disordered’ regions, which display low ESM2 scores, indicating varying levels of mutational constraint despite a lack…”
Thompson, J. D., Linard, B., Lecompte, O., & Poch, O. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018093 · Cited by 242 · cited 1× · see citing works
“…( Riley et al., 2023 ; Oldfield and Dunker, 2014 ; Brown et al., 2002 ; Huang and Sarai, 2012 ; Nunez-Castilla and Siltberg-Liberles, 2020 ; Thompson et al., 2011 ; Lange et al., 2016 ), though several studies have attempted alignment of disordered proteins with promising results ( Dasmeh…”
Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2
Alderson, T. R., Pritišanac, I., Kolarić, Đ., Moses, A. M., & Forman-Kay, J. D. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2304302120 · Cited by 240 · see citing works
Direct prediction of intrinsically disordered protein conformational properties from sequence
Lotthammer, J. M., Ginell, G. M., Griffith, D., Emenecker, R. J., & Holehouse, A. S. (2024) · Nature Methods · doi:10.1038/s41592-023-02159-5 · Cited by 228 · see citing works
Farag, M., Cohen, S. R., Borcherds, W., Bremer, A., Mittag, T., & Pappu, R. (2022) · Nature Communications · doi:10.1038/s41467-022-35370-7 · Cited by 220
Learning the molecular grammar of protein condensates from sequence determinants and embeddings
Saar, K., Morgunov, A., Qi, R.-Z., Arter, W. E., Krainer, G., Lee, A., & Knowles, T. (2021) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.2019053118 · Cited by 208 · cited 2× · see citing works
“…studies have sought to identify functionally relevant amino acid groups within IDRs ( Wang et al., 2018 ; Li et al., 2024 ; Latham and Zhang, 2021 ; Zhang et al., 2021 ; Saar et al., 2021 ; Liu et al., 2025 ; Schuster et al., 2020 ; Pak et al., 2016 ; Cohan et al., 2022 ; Dao et al., 2018 ).”
PhaSepDB: a database of liquid–liquid phase separation related proteins
You, K., Huang, Q., Yu, C., Shen, B., Sevilla, C., Shi, M.-L., Hermjakob, H., Chen, Y., & Li, T. (2019) · Nucleic Acids Res. · doi:10.1093/nar/gkz847 · Cited by 208 · cited 1× · see citing works
“For these proteins, experimentally verified segments have been identified, the deletion or mutation of which impairs phase separation ( Mészáros et al., 2020 ; You et al., 2020 ; Ning et al., 2020 ; Li et al., 2020 ; Orti et al., 2024 ; Figure 4B ).”
Regy, R. M., Thompson, J., Kim, Y. C., & Mittal, J. (2021) · Protein Science · doi:10.1002/pro.4094 · Cited by 205 · cited 1× · see citing works
“…; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022b ; Farag et…”
UDSMProt: universal deep sequence models for protein classification
Strodthoff, N., Wagner, P., Wenzel, M., & Samek, W. (2019) · bioRxiv · doi:10.1093/bioinformatics/btaa003 · Cited by 200 · cited 1× · see citing works
“Recent advances in protein language models ( Ofer et al., 2021 ; Rives et al., 2021 ; Elnaggar et al., 2021 ; Strodthoff et al., 2020 ; Alley et al., 2019 ; Brandes et al., 2022 ) provide alternative approaches for sequence analysis and information decoding.”
PhaSePro: the database of proteins driving liquid–liquid phase separation
Mészáros, B., Erdős, G., Szabó, B., Schád, É., Tantos, Á., Abukhairan, R., Horváth, T., Murvai, N., Kovács, O. P., Kovács, M., et al. (2019) · Nucleic Acids Res. · doi:10.1093/nar/gkz848 · Cited by 199 · cited 1× · see citing works
“For these proteins, experimentally verified segments have been identified, the deletion or mutation of which impairs phase separation ( Mészáros et al., 2020 ; You et al., 2020 ; Ning et al., 2020 ; Li et al., 2020 ; Orti et al., 2024 ; Figure 4B ).”
Expanding the molecular language of protein liquid-liquid phase separation
Rekhi, S., Garcia, C., Barai, M., Rizuan, A., Schuster, B. S., Kiick, K., & Mittal, J. (2023) · bioRxiv · doi:10.1038/s41557-024-01489-x · Cited by 198 · cited 1× · see citing works
“As a result, the absolute number of conserved residues may still be higher outside phase-separating regions.”
DrLLPS: a data resource of liquid–liquid phase separation in eukaryotes
Ning, W., Guo, Y.-P., Lin, S.-F., Mei, B., Wu, Y., Jiang, P.-R., Tan, X., Zhang, W., Chen, G.-W., Peng, D., et al. (2019) · Nucleic Acids Res. · doi:10.1093/nar/gkz1027 · Cited by 194 · cited 1× · see citing works
“For these proteins, experimentally verified segments have been identified, the deletion or mutation of which impairs phase separation ( Mészáros et al., 2020 ; You et al., 2020 ; Ning et al., 2020 ; Li et al., 2020 ; Orti et al., 2024 ; Figure 4B ).”
Simulation of FUS Protein Condensates with an Adapted Coarse-Grained Model
Benayad, Z., von Bülow, S., Stelzl, L., & Hummer, G. (2020) · bioRxiv · doi:10.1021/acs.jctc.0c01064 · Cited by 189 · cited 1× · see citing works
“…al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022b ; Farag et al., 2023 ; Lotthammer et al., 2024 ; Bülow et al., 2024 ; Zhang…”
The Hinge and Chromo Shadow Domain Impart Distinct Targeting of HP1-Like Proteins
Smothers, J., & Henikoff, S. (2001) · Molecular and Cellular Biology · doi:10.1128/mcb.21.7.2555-2569.2001 · Cited by 185 · cited 1× · see citing works
“Within the hinge domain, a conserved segment known as the KRK patch (highlighted in orange) ( Smothers and Henikoff, 2001 ; Badugu et al., 2005 ; Larson et al., 2017 ; Strom et al., 2021 ) shows low ESM2 scores, despite being disordered.”
Advantages of proteins being disordered
Liu, Z.-R., & Huang, Y.-Q. (2014) · Protein Science · doi:10.1002/pro.2443 · Cited by 182 · cited 1× · see citing works
“In contrast, disordered residues (pLDDT ≤70) predominantly show high ESM2 scores (region II, ESM2 score ≥2.0), consistent with the rapid evolution and higher mutational tolerance typical of disordered proteins ( Brown et al., 2011 ; Liu and Huang, 2014 ; Forman-Kay and Mittag, 2013 ).”
InfluentialLLPSDB: a database of proteins undergoing liquid–liquid phase separation in vitro
Li, Q., Peng, X., Li, Y.-Q., Tang, W.-Y., Zhu, J., Huang, J., Qi, Y., & Zhang, Z.-Q. (2019) · Nucleic Acids Res. · doi:10.1093/nar/gkz778 · Cited by 179 · cited 1× · see citing works
“For these proteins, experimentally verified segments have been identified, the deletion or mutation of which impairs phase separation ( Mészáros et al., 2020 ; You et al., 2020 ; Ning et al., 2020 ; Li et al., 2020 ; Orti et al., 2024 ; Figure 4B ).”
Константинович, Т. К., Kuznetsova, I. М., Fonin, A. V., Darling, A. L., Zaslavsky, B. Y., & Uversky, V. N. (2019) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2019.03.005 · Cited by 150 · cited 1× · see citing works
“Intrinsically disordered regions (IDRs), which lack well-defined tertiary structures yet exhibit unique structural disorder, frequently act as scaffolds within MLOs ( Borcherds et al., 2021 ; Hyman et al., 2014 ; Mittag and Pappu, 2022 ; Dignon et al., 2020 ; Turoverov et al., 2019 ).”
Conservation of protein structure over four billion years
Inglés-Prieto, Á., Ibarra-Molero, B., Delgado-Delgado, A., Perez-Jimenez, R., Fernandez, J. M., Gaucher, E., Sanchez-Ruiz, J., & Gavira, J. (2013) · Structure · doi:10.1016/j.str.2013.06.020 · Cited by 147 · see citing works
Farag, M., Borcherds, W., Bremer, A., Mittag, T., & Pappu, R. (2023) · Nature Communications · doi:10.1038/s41467-023-41274-x · Cited by 141 · cited 1× · see citing works
“Intrinsically disordered regions (IDRs), which lack well-defined tertiary structures yet exhibit unique structural disorder, frequently act as scaffolds within MLOs ( Borcherds et al., 2021 ; Hyman et al., 2014 ; Mittag and Pappu, 2022 ; Dignon et al., 2020 ; Turoverov et al., 2019 ).”
MobiDB: a comprehensive database of intrinsic protein disorder annotations
Domenico, T. D., Walsh, I., Martin, A. J. M., & Tosatto, S. (2012) · Bioinform. · doi:10.1093/bioinformatics/bts327 · Cited by 140 · see citing works
HP1α is a chromatin crosslinker that controls nuclear and mitotic chromosome mechanics
Strom, A. R., Biggs, R. J., Banigan, E., Wang, X.-T., Chiu, K., Herman, C., Collado, J., Yue, F., Politz, J. C. R., Tait, L. J., et al. (2020) · bioRxiv · doi:10.1101/2020.10.09.331900 · Cited by 133
Dynamic metastable long-living droplets formed by sticker-spacer proteins
Ranganathan, S., & Shakhnovich, E. (2020) · eLife · doi:10.7554/elife.56159 · Cited by 124 · cited 1× · see citing works
“Intrinsically disordered regions (IDRs), which lack well-defined tertiary structures yet exhibit unique structural disorder, frequently act as scaffolds within MLOs ( Borcherds et al., 2021 ; Hyman et al., 2014 ; Mittag and Pappu, 2022 ; Dignon et al., 2020 ; Turoverov et al., 2019 ).”
Simulation methods for liquid-liquid phase separation of disordered proteins
Dignon, G., Zheng, W.-W., & Mittal, J. (2019) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2019.03.004 · Cited by 113 · cited 1× · see citing works
“…; Zeng and Pappu, 2023 ; Schmit et al., 2020 ; Mittag and Pappu, 2022 ; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et…”
Uncovering non-random binary patterns within sequences of intrinsically disordered proteins
Cohan, M. C., Shinn, M. K., Lalmansingh, J. M., & Pappu, R. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.167373 · Cited by 107 · see citing works
Liquid–liquid phase separation of tau: From molecular biophysics to physiology and disease
Rai, S. K., Savastano, A., Singh, P., Mukhopadhyay, S., & Zweckstetter, M. (2021) · Protein Science · doi:10.1002/pro.4093 · Cited by 107 · cited 1× · see citing works
“Mutations in IDRs can disrupt phase behavior, potentially leading to MLO dysfunction and contributing to diseases such as neurodegenerative disorders and cancer ( Alberti and Dormann, 2019 ; Zbinden et al., 2020 ; Rai et al., 2021 ; Das et al., 2020 ).”
Hamill, S. J., Cota, E., Chothia, C., & Clarke, J. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3360 · Cited by 107 · cited 1× · see citing works
“…a dominant population with low ESM2 values (region a, ESM2 score ≤0.5), consistent with the established understanding that folded domains require structural and functional integrity and are thus more mutation sensitive ( Shakhnovich et al., 1996 ; Hamill et al., 2000 ; Ingles-Prieto et al., 2013 ).”
InfluentialPrediction of phase-separation propensities of disordered proteins from sequence
von Bülow, S., Tesei, G., Zaidi, F. K., Mittag, T., & Lindorff-Larsen, K. (2024) · bioRxiv · doi:10.1073/pnas.2417920122 · Cited by 94
Elnaggar, A., Ding, W., Jones, L., Gibbs, T., Fehér, T. B., Angerer, C., Severini, S., Matthes, F., & Rost, B. (2021) · arXiv.org · doi:10.48550/arxiv.2104.02443 · Cited by 86 · cited 1× · see citing works
“Recent advances in protein language models ( Ofer et al., 2021 ; Rives et al., 2021 ; Elnaggar et al., 2021 ; Strodthoff et al., 2020 ; Alley et al., 2019 ; Brandes et al., 2022 ) provide alternative approaches for sequence analysis and information decoding.”
Maximum Entropy Optimized Force Field for Intrinsically Disordered Proteins
Latham, A. P., & Zhang, B. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00932 · Cited by 84 · cited 2× · see citing works
“…; Schmit et al., 2020 ; Mittag and Pappu, 2022 ; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and…”
Self-citationConsistent Force Field Captures Homolog Resolved HP1 Phase Separation
Latham, A. P., & Zhang, B. (2021) · bioRxiv · doi:10.1101/2021.01.06.425600 · Cited by 77 · cited 3×
“…2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022b ; Farag et al., 2023 ;…”
Self-citationThe Convergence of Artificial Protein Polymers and Intrinsically Disordered Proteins
Dzuricky, M. J., Roberts, S., & Chilkoti, A. (2018) · Biochemistry · doi:10.1021/acs.biochem.8b00056 · Cited by 72 · cited 1× · see citing works
“…behaviors of conden-sates ( Brangwynne et al., 2015 ; Pappu et al., 2023 ; Zeng and Pappu, 2023 ; Schmit et al., 2020 ; Mittag and Pappu, 2022 ; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy…”
Badugu, R., Yoo, Y., Singh, P. B., & Kellum, R. (2005) · Chromosoma · doi:10.1007/s00412-004-0324-2 · Cited by 68 · cited 1× · see citing works
“Within the hinge domain, a conserved segment known as the KRK patch (highlighted in orange) ( Smothers and Henikoff, 2001 ; Badugu et al., 2005 ; Larson et al., 2017 ; Strom et al., 2021 ) shows low ESM2 scores, despite being disordered.”
Yang, Y.-R., Jones, H. B., Dao, T. P., & Castañeda, C. A. (2019) · Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.9b01024 · Cited by 67 · cited 2× · see citing works
“…evolutionarily conserved residues that contribute to phase separation ( Dasmeh et al., 2022 ; Ho and Huang, 2022 ; Jiang et al., 2015 ; Tatavosian et al., 2019 ; Schuster et al., 2020 ; Yang et al., 2019 ; Larson et al., 2017 ; DiRusso et al., 2023 ; Mitrea et al., 2016 ; Xiao et al., 2019 ).”
Tortora, M. M. C., Brennan, L. D., Karpen, G., & Jost, D. (2023) · bioRxiv · doi:10.1073/pnas.2211855120 · Cited by 62 · see citing works
Protein network structure enables switching between liquid and gel states
Schmit, J., Bouchard, J. J., Martin, E. W., & Mittag, T. (2019) · bioRxiv · doi:10.1101/754952 · Cited by 61 · cited 1×
“…focused on linking protein sequences to the phase behaviors of conden-sates ( Brangwynne et al., 2015 ; Pappu et al., 2023 ; Zeng and Pappu, 2023 ; Schmit et al., 2020 ; Mittag and Pappu, 2022 ; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ;…”
Amino acid homorepeats in proteins
Chavali, S., Singh, A., Santhanam, B., & Babu, M. (2020) · Nature Reviews Chemistry · doi:10.1038/s41570-020-0204-1 · Cited by 58 · cited 1× · see citing works
“In more folded domains, hydrophobic residues such as W and F are more conserved (see Figure 3— figure supplement 1 ), consistent with the characteristic conservation patterns of proteins across different disorder levels ( Yang et al., 2023 ; Chavali et al., 2020 ).”
Decoding the physical principles of two-component biomolecular phase separation
Zhang, Y.-J., Xu, B., Weiner, B. G., Meir, Y., & Wingreen, N. (2020) · bioRxiv · doi:10.1101/2020.08.24.264655 · Cited by 57 · cited 4×
“…1942 ; Huggins, 1942 ; Dignon et al., 2018 ; Dignon et al., 2019 ; Latham and Zhang, 2020 ; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022b ; Farag et al., 2023 ; Lotthammer et al.,…”
InfluentialSelf-citationCD-CODE: crowdsourcing condensate database and encyclopedia
Rostam, N., Ghosh, S., Chow, C. F. W., Hadarovich, A., Landerer, C., Ghosh, R., Moon, H., Hersemann, L., Mitrea, D. M., Klein, I. A., et al. (2023) · Nature Methods · doi:10.1038/s41592-023-01831-0 · Cited by 55
Towards Accurate Simulation of Coupling between Protein Secondary Structure and Phase Separation
Zhang, Y.-M., Li, S.-L., Gong, X., & Chen, J.-H. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.3c09195 · Cited by 53 · cited 3× · see citing works
“…et al., 2023 ; Banani et al., 2017 ; Choi et al., 2020 ; Pappu et al., 2023 ; Ginell and Holehouse, 2023 ; Latham and Zhang, 2020 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022c ; Latham and Zhang, 2022b ; Latham et al., 2024 ; Liu et al., 2025 ; Lao and Zhang, 2024 ; Jiang et al., 2015 ).”
Self-citationLu, A. X., Lu, A. X., Pritišanac, I., Zarin, T., Forman-Kay, J. D., & Moses, A. M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010238 · Cited by 51 · see citing works
Zeng, W., Dou, Y., Pan, L., Xu, L., & Peng, S. (2024) · Nature Communications · doi:10.1038/s41467-024-52293-7 · Cited by 49 · cited 1× · see citing works
“…Choi et al., 2020 ; Pappu et al., 2023 ; Wang et al., 2018 ; Prusty et al., 2018 ; Choi et al., 2019 ; Zhang et al., 2021 ), in which specific residues, termed ‘stickers’, drive strong, specific interactions, while ‘spacer’ regions act as flexible linkers with minimal nonspecific interactions (…”
Farahi, N., Lazar, T., Wodak, S. J., Tompa, P., & Pancsa, R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22063017 · Cited by 46 · cited 1× · see citing works
“…of MLO-hProt using a pLDDT score ≤70 and partitioned these regions into two categories: drivers (dMLO-hIDR), which actively drive phase separation, and clients (cMLO-hIDR), which are present in MLOs under certain conditions but do not promote phase separation themselves ( Farahi et al., 2021 ).”
Thermodynamics of Associative Polymer Blends
Prusty, D., Pryamitsyn, V., & de la Cruz, M. O. (2018) · Macromolecules · doi:10.1021/acs.macromol.8b00661 · Cited by 45 · cited 1×
“These studies support the ‘stickers- and-spacers’ framework ( Choi et al., 2020 ; Pappu et al., 2023 ; Wang et al., 2018 ; Prusty et al., 2018 ; Choi et al., 2019 ; Zhang et al., 2021 ), in which specific residues, termed ‘stickers’, drive strong, specific interactions, while ‘spacer’ regions act…”
An Introduction to the Stickers-and-Spacers Framework as Applied to Biomolecular Condensates.
Ginell, G., & Holehouse, A. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-2663-4_4 · Cited by 45 · see citing works
Developments in describing equilibrium phase transitions of multivalent associative macromolecules
Zeng, X.-Z., & Pappu, R. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102540 · Cited by 41
On the stability and layered organization of protein-DNA condensates
Latham, A. P., & Zhang, B. (2021) · bioRxiv · doi:10.1101/2021.08.22.457249 · Cited by 40
Self-citationLiu, S.-M., Wang, C., Latham, A. P., Ding, X.-Q., & Zhang, B. (2023) · bioRxiv · doi:10.1371/journal.pcbi.1011442 · Cited by 39 · cited 1× · see citing works
“These biomolecular condensates typically assemble through phase separation, dynamically recruiting reactants and releasing products to improve the efficiency and specificity of cellular processes ( Hyman et al., 2014 ; Feric et al., 2016 ; Pappu et al., 2023 ).”
Self-citationPredicting MoRFs in protein sequences using HMM profiles
Sharma, R., Kumar, S., Tsunoda, T., Patil, A., & Sharma, A. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1375-0 · Cited by 36 · cited 1× · see citing works
“We employed HHblits for homolog detection, a method particularly suited to disordered proteins as it effectively captures distant sequence similarities in highly divergent sequences ( Sharma et al., 2016 ; Jarnot et al., 2022 ; Peng et al., 2023 ).”
Predicting a Protein's Stability under a Million Mutations
Ouyang-Zhang, J., Diaz, D. J., Klivans, A. R., & Krähenbühl, P. (2023) · Neural Information Processing Systems · doi:10.52202/075280-3332 · Cited by 35 · see citing works
KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins
Lange, J., Wyrwicz, L., & Vriend, G. (2015) · Bioinform. · doi:10.1093/bioinformatics/btv663 · Cited by 35 · cited 1×
“…2023 ; Oldfield and Dunker, 2014 ; Brown et al., 2002 ; Huang and Sarai, 2012 ; Nunez-Castilla and Siltberg-Liberles, 2020 ; Thompson et al., 2011 ; Lange et al., 2016 ), though several studies have attempted alignment of disordered proteins with promising results ( Dasmeh et al., 2022 ; Lu et…”
Coarse-Grained Models to Study Protein–DNA Interactions and Liquid–Liquid Phase Separation
Kapoor, U., Kim, Y. C., & Mittal, J. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00525 · Cited by 34 · see citing works
Enhancing missense variant pathogenicity prediction with protein language models using VariPred
Lin, W., Wells, J., Wang, Z., Orengo, C., & Martin, A. C. R. (2024) · Scientific Reports · doi:10.1038/s41598-024-51489-7 · Cited by 34 · cited 1× · see citing works
“…framework ( Choi et al., 2020 ; Pappu et al., 2023 ; Wang et al., 2018 ; Prusty et al., 2018 ; Choi et al., 2019 ; Zhang et al., 2021 ), in which specific residues, termed ‘stickers’, drive strong, specific interactions, while ‘spacer’ regions act as flexible linkers with minimal nonspecific…”
Expert-guided protein language models enable accurate and blazingly fast fitness prediction
Marquet, C., Schlensok, J., Abakarova, M., Rost, B., & Laine, E. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae621 · Cited by 33 · see citing works
Gong, J.-T., Jiang, L., Chen, Y.-B., Zhang, Y., Li, X., Ma, Z.-Q., Fu, Z.-G., He, F., Sun, P.-P., Ren, Z.-L., et al. (2023) · Bioinform. · doi:10.1093/bioinformatics/btad646 · Cited by 33 · cited 2× · see citing works
“…; Joseph et al., 2021 ; Regy et al., 2021 ; Latham and Zhang, 2021 ; Tesei et al., 2021 ; Benayad et al., 2021 ; Latham and Zhang, 2022a ; Latham and Zhang, 2022b ; Farag et al., 2023 ; Lotthammer et al., 2024 ; Bülow et al., 2024 ; Zhang et al., 2024 ; Kapoor et al., 2024 ; Liu et al., 2023 ).”
Self-citationDecoding molecular mechanisms for loss-of-function variants in the human proteomePreprint
Cagiada, M., Jonsson, N., & Lindorff-Larsen, K. (2025) · bioRxiv · doi:10.1101/2024.05.21.595203 · Cited by 32 · see citing works
Molecular Determinants for the Layering and Coarsening of Biological Condensates
Latham, A. P., & Zhang, B. (2022) · Aggregate · doi:10.1002/agt2.306 · Cited by 28
Self-citationHuang, H., & Sarai, A. (2012) · Comput. Biol. Chem. · doi:10.1016/j.compbiolchem.2012.10.001 · Cited by 26 · cited 1× · see citing works
“…analysis of IDRs is challenging due to difficulties in sequence alignment ( Riley et al., 2023 ; Oldfield and Dunker, 2014 ; Brown et al., 2002 ; Huang and Sarai, 2012 ; Nunez-Castilla and Siltberg-Liberles, 2020 ; Thompson et al., 2011 ; Lange et al., 2016 ), though several studies have…”
Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset
Chu, S. K. S., & Siegel, J. B. (2023) · bioRxiv · doi:10.1101/2023.11.19.567747 · Cited by 25 · cited 3×
“…predicted by these models can be interpreted as proxies for evolutionary constraint or mutational tolerance ( Meier et al., 2024 ; Cagiada et al., 2024 ; Ouyang-Zhang et al., 2024 ; Lin et al., 2024 ; Saadat and Fellay, 2025 ; Chu et al., 2024 ; Marquet et al., 2024 ; Gong et al., 2023 ).”
Protein stability prediction by fine-tuning a protein language model on a mega-scale dataset
Chu, S. K. S., Narang, K., & Siegel, J. B. (2024) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1012248 · Cited by 24 · cited 1× · see citing works
“…( Choi et al., 2020 ; Pappu et al., 2023 ; Wang et al., 2018 ; Prusty et al., 2018 ; Choi et al., 2019 ; Zhang et al., 2021 ), in which specific residues, termed ‘stickers’, drive strong, specific interactions, while ‘spacer’ regions act as flexible linkers with minimal nonspecific…”
Peng, Z.-L., Li, Z., Meng, Q.-Z., Zhao, B., & Kurgan, L. (2022) · Briefings Bioinform. · doi:10.1093/bib/bbac502 · Cited by 24 · see citing works
Ho, W.-L., & Huang, J.-R. (2022) · Protein Science · doi:10.1002/pro.4317 · Cited by 24 · cited 1× · see citing works
“Substantial research has focused on linking protein sequences to the phase behaviors of conden-sates ( Brangwynne et al., 2015 ; Pappu et al., 2023 ; Zeng and Pappu, 2023 ; Schmit et al., 2020 ; Mittag and Pappu, 2022 ; Dzuricky et al., 2018 ; Flory, 1942 ; Huggins, 1942 ; Dignon et al., 2018 ;…”
Deep learning tools predict variants in disordered regions with lower sensitivity
Luppino, F., Lenz, S., Chow, C. F. W., & Toth-Petroczy, A. (2025) · BMC Genomics · doi:10.1186/s12864-025-11534-9 · Cited by 23 · see citing works
Towards predictive coarse-grained simulations of biomolecular condensates
Liu, S.-M., Wang, C.-Z., & Zhang, B. (2025) · Biochemistry · doi:10.1021/acs.biochem.4c00737 · Cited by 21 · see citing works
Self-citationRiley, A., Ashlock, D., & Graether, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0288388 · Cited by 21 · see citing works
Assessing variant effect predictors and disease mechanisms in intrinsically disordered proteins
Fawzy, M., & Marsh, J. A. (2025) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1013400 · Cited by 18 · see citing works
Microphase separation produces interfacial environment within diblock biomolecular condensatesPreprint
Latham, A. P., Zhu, L.-C., Sharon, D. A., Ye, S.-T., Willard, A. P., Zhang, X., & Zhang, B. (2023) · bioRxiv · doi:10.7554/elife.90750 · Cited by 18 · see citing works
Self-citationRegulation of zebrafish dorsoventral patterning by phase separation of RNA-binding protein Rbm14
Xiao, Y., Chen, J.-H., Wan, Y., Gao, Q., Jing, N.-H., Zheng, Y., & Zhu, X.-L. (2019) · Cell Discovery · doi:10.1038/s41421-019-0106-x · Cited by 17 · cited 2×
“…evolutionarily conserved residues that contribute to phase separation ( Dasmeh et al., 2022 ; Ho and Huang, 2022 ; Jiang et al., 2015 ; Tatavosian et al., 2019 ; Schuster et al., 2020 ; Yang et al., 2019 ; Larson et al., 2017 ; DiRusso et al., 2023 ; Mitrea et al., 2016 ; Xiao et al., 2019 ).”
Orti, F., Fernández, M., & Marino-Buslje, C. (2023) · bioRxiv · doi:10.1002/pro.4858 · Cited by 16
Ozawa, Y., Anbo, H., Ota, M., & Fukuchi, S. (2022) · Journal of Biochemistry (Tokyo) · doi:10.1093/jb/mvac106 · Cited by 16
Jarnot, P., Ziemska-Legiecka, J., Grynberg, M., & Gruca, A. (2022) · Briefings Bioinform. · doi:10.1093/bib/bbac299 · Cited by 16 · see citing works
Dasmeh, P., Doronin, R., & Wagner, A. (2021) · bioRxiv · doi:10.1101/2021.05.04.442641 · Cited by 13
Fine-tuning protein language models to understand the functional impact of missense variants
Saadat, A., & Fellay, J. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.05.022 · Cited by 10 · see citing works
Backbone Interactions and Secondary Structures in Phase Separation of Disordered Proteins
Li, S.-L., Zhang, Y.-M., & Chen, J.-H. (2024) · Biochemical Society Transactions · doi:10.1042/bst20230618 · Cited by 10 · see citing works
Self-citationDiRusso, C. J., DeMaria, A. M., Wong, J. M. Y., Wang, W., Jordanides, J. J., Whitty, A., Allen, K. N., & Gilmore, T. D. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.105396 · Cited by 9 · see citing works
HP1a promotes chromatin liquidity and drives spontaneous heterochromatin compartmentalizationPreprint
Brennan, L. D., Kim, H.-K., Colmenares, S., Ego, T., Ryu, J.-K., & Karpen, G. H. (2025) · bioRxiv · doi:10.1101/2024.10.18.618981 · Cited by 7 · see citing works
OpenNucleome for high resolution nuclear structural and dynamical modelingPreprint
Lao, Z.-H., Kamat, K., Jiang, Z.-L., & Zhang, B. (2023) · bioRxiv · doi:10.1101/2023.10.16.562451 · Cited by 7 · see citing works
Self-citationPrediction of Protein Half-lives from Amino Acid Sequences by Protein Language ModelsPreprint
Sagawa, T., Kanao, E., Ogata, K., Imami, K., & Ishihama, Y. (2024) · bioRxiv · doi:10.1101/2024.09.10.612367 · Cited by 6 · see citing works
Preserving condensate structure and composition by lowering sequence complexity
Sood, A., & Zhang, B. (2023) · bioRxiv · doi:10.1101/2023.11.29.569249 · Cited by 6 · cited 2×
“Additional information on MLO-hIDR candidate proteins and their biological roles is available in ( MLO-hIDR. csv). dMLO-IDR dataset.”
Self-citationAn Easy Protocol for Evolutionary Analysis of Intrinsically Disordered Proteins.
Nunez-Castilla, J., & Siltberg-Liberles, J. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0524-0_7 · Cited by 6 · see citing works
Prediction of folding patterns for intrinsic disordered protein
Yang, J., Cheng, W.-X., Wu, G., Sheng, S., & Zhang, P. (2023) · Scientific Reports · doi:10.1038/s41598-023-45969-5 · Cited by 4 · cited 1× · see citing works
“Conversely, hydrophobic residues like valine (V) and isoleucine (I) show higher ESM2 scores, suggesting they experience reduced evolutionary constraints.”
Unified protein force field for simulations of liquid-liquid phase separation
Latham, A. P., & Zhang, B. (2022) · Biophysical Journal · doi:10.1016/j.bpj.2021.11.969 · Cited by 4
Self-citation
Flagged first, then by citations
12 of the 149 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
MOFF2: A Transferable Coarse-Grained Protein Force Field for Predictive Condensate Simulations
Liu, S.-M., Zhang, Y.-M., Riveros, I., Wang, C.-Z., & Zhang, B. (2026) · bioRxiv · doi:10.64898/2026.06.10.731384 · Cited by 2
Self-citationZeng, X.-Y., Wang, T., Kulkarni, A., Lu, A., Ni, A., Xing, P., Zhao, J., Chen, S.-W., & Zhou, D. (2025) · doi:10.48550/arxiv.2507.02883 · Cited by 1
“This limitation is particularly consequential for applications that depend on dynamic and context-dependent interactions, including protein-protein interaction (PPI) prediction and phase separation [35].”
On the limits of marginal protein folding stability: methodological goals and drawbacks
Ferreiro, D., Zoni, V., & Arenas, M. (2026) · Journal of Molecular Modeling · doi:10.1007/s00894-026-07034-6
“Because PLMs are trained on millions of unannotated protein sequences using a masked-language-modeling objective, they inter-nalize statistical patterns of protein architecture, including residue-residue contacts and functional motifs [62].”
Zhang, Y.-M., Sood, A., Athreya, A., & Zhang, B. (2026) · Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.6c05200
Self-citationMOFF2: A Transferable Coarse-Grained Protein Force Field for Predictive Condensate Simulations.
Liu, S.-M., Zhang, Y.-M., Riveros, I., Wang, C.-Z., & Zhang, B. (2026) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6c01336
Self-citationEmergence of new function through evolutionary divergence of an intrinsically disordered regionPreprint
Elena-Real, C. A., Körber, A. M., Gatin-Fraudet, B., Kovinko, A., Motzny, K., Saiti, A., Lange, A., Broichhagen, J., & Milles, S. (2026) · bioRxiv · doi:10.64898/2026.08.25.746950
“4,5 While considerable progress has been made in understanding how distributed interaction motifs encode collective IDR behaviors such as phase separation, 6 –8 much less is known about how transient secondary structural elements evolve to generate new protein functions.”
Zhang, Y.-M., Sood, A., Athreya, A., & Zhang, B. (2026) · bioRxiv · doi:10.64898/2026.08.02.742325
Self-citationPatil, U., Boonchoosri, R., Benjakul, S., Jing, S. L., Kumar, P., & Singh, A. (2026) · Applied Food Research · doi:10.1016/j.afres.2026.102388
From prediction to discovery: AI as an observatory of physical organization in protein space
Zheng, Y., Zhang, Z., Wang, Y., Kang, W., Ren, W., & Tang, Q.-Y. (2026) · AI for Science · doi:10.1088/3050-287x/ae78ea
“Representation-based models have shown value for functional prediction and variant interpretation [72, 143], for disordered and phase-separating proteins [144], and for prioritizing sites or perturbations relevant to allostery, drug discovery, and protein engineering [80, 81, 85, 145].”
Yuan, Z.-L., Wang, B., Chen, Y.-L., Huang, H.-Q., Li, B.-H., Zahoor, A., Ren, L.-P., Du, M.-Z., Fang, R.-Q., & Ning, L. (2026) · Briefings Bioinform. · doi:10.1093/bib/bbag254
“This task reflects an important conceptual shift: rather than treating LLPS as a global protein property, it recognizes phase separation as an emergent outcome of localized sequence features and interaction motifs [ 118, 123].”
Khanna, Y., Hajdarević, A., Pirchner, J., Usluer, S., Rakhimbekova, A., Pritišanac, I., von Bülow, S., Lindorff-Larsen, K., & Madl, T. (2026) · bioRxiv · doi:10.64898/2026.04.13.717676
“Complementary approaches using protein language models and evolutionary conservation further highlight sequence-encoded motifs associated with phase separation and condensate formation [4].”
Wang, Y., Cai, M., Ma, Y., Wang, X., & Wei, K. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.07.717117
“Indeed, protein language models and deep generative frameworks successfully capture this evolutionary grammar and specific compositional motifs of IDP phase separation despite their extreme sensitivity to dynamic chemical environments [16–19].”
Intrinsic Disorder as a Biomimetic Design Paradigm
Puccinelli, T., & Bordin, J. R. (2026) · Biomimetics · doi:10.3390/biomimetics11040267
“In parallel, protein language models trained on large sequence databases are increasingly adapted to annotate disordered regions, identify functional motifs, and infer interaction propensities directly from sequence [73–75].”
- Authors
- Zhang, Y., Zheng, J., & Zhang, B.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Zhang, Bin
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2025-10-20
- Volume
- 14
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC12537011
- OpenAlex
- W4410139515
- Cited by
- 4
- References
- 149
- Citations by year
- 2026: 3 · 2025: 1
- Type
- posted content
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institute of General Medical Sciences (R35GM133580)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- intrinsically disordered regions, phase separation, biomolecular condensates, protein language models, ESM-2, mutational tolerance, evolutionary conservation, conserved motifs, multivalent interactions, protein sequence evolution
- MeSH terms
- Phase Separation, Amino Acid Sequence, Organelles, Conserved Sequence, Evolution, Molecular, Amino Acid Motifs, Intrinsically Disordered Proteins
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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