Challenges in protein docking
Open accessAbstract
Current developments in protein docking aim at improvement of applicability, accuracy and utility of modeling macromolecular complexes. The challenges include the need for greater emphasis on protein docking to molecules of different types, proper accounting for conformational flexibility upon binding, new promising methodologies based on residue co-evolution and deep learning, affinity prediction, and further development of fully automated docking servers. Importantly, new developments increasingly focus on realistic modeling of protein interactions in vivo, including crowded environment inside a cell, which involves multiple transient encounters, and propagating the system in time. This opinion paper offers the author's perspective on these challenges in structural modeling of protein interactions and the future of protein docking.
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Written from the paper’s full text.
TL;DR
This opinion paper surveys challenges in protein docking, covering static versus dynamic modeling, docking to non-protein molecules, conformational flexibility and refinement, co-evolution and deep learning, affinity prediction, automated servers, and realistic in vivo interactome modeling. It argues that structure-based dynamic whole-cell modeling at molecular/atomic resolution is the ultimate strategic goal of protein docking.
Key findings
- Protein-protein docking is fairly advanced toward “solving” the problem at coarse-grained resolution for traditional equilibrium complexes of soluble globular proteins, partly because rigid-body approximation reduces the global search to six coordinates and global fold often determines the docking solution. Other molecule types and membrane protein-protein interactions lag, due to non-protein conformational flexibility and the need for atomic-level accuracy.
- Conformational flexibility remains a challenge: conformational selection allows precomputed ensembles to be docked with limited search, but adequate ensemble determination is often complicated and induced fit can contribute; local refinement, especially backbone conformational changes, remains difficult.
- Co-evolution and deep learning have greatly advanced individual protein structure prediction but not protein assembly modeling; obstacles include distinguishing inter-molecular from intra-molecular co-evolutionary information and a perceived lack of sufficient sequence data on protein-protein or protein-other molecule interfaces.
- Docking scores correlate with interaction energy but too loosely to distinguish weakly/non-interacting from strongly interacting pairs by absolute score values; exploring intermolecular energy landscapes from docking output may help. Automated docking servers lag behind protein structure prediction, and dynamic in vivo crowded interactome modeling is an open-ended long-term proposition.
Methods
- This is an opinion paper offering the author’s perspective on challenges in structural modeling of protein interactions and the future of protein docking.
- It synthesizes prior literature and references rather than presenting new experimental data, benchmarks, or quantitative analyses.
- No primary dataset, sample, or statistical analysis is reported; the text refers to conceptual figures but gives no numerical results.
Limitations
- The paper states that dynamic whole-cell modeling is an open-ended long-term proposition due to its extreme scale and complexity, and that deep learning for docking faces a perceived lack of sufficient interface sequence data.
- The paper states that automated text mining for docking constraints faces copyright restrictions and is hindered by the still limited amount of open-access publications.
- Evident from the text: as an opinion paper, it does not provide original data, systematic benchmarking, or quantitative validation of the challenges discussed.
Model-written summary. Check it against the paper before relying on it.
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Cites
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Claims the paper makes
0 of 30 cited sources checked · 0 supported · 0 flagged
- Findingreasoning
A similar advancement in structural modeling of protein assemblies has not occurred yet.
“A similar advancement in structural modeling of protein assemblies has not occurred yet.”
Quote in the paperNot a substantial claim - Findingreasoning
Automated hands-off generation of such data is often non-trivial.
“Automated hands-off generation of such data is often non-trivial.”
Quote in the paperSubstantial claim - Findingreasoning
Local conformational adjustment (refinement) remains a challenge.
“In addition to the global flexibility, the local conformational adjustment (refinement) remains a challenge.”
Quote in the paperSubstantial claim- Rests on an assumption: Proteins, as well as other macromolecules, change conformation upon binding.
- Findingreasoning
The docking community still lags behind in the development of fully automated modeling servers.
“However, in that regard, the docking community still lags behind.”
Quote in the paperSubstantial claim - Findingcitation
Despite significant progress, the local refinement problem remains a challenge, especially in cases of conformational changes in the backbone.
“However, despite significant progress in this direction [26–29], the problem remains a challenge, especially in cases of conformational changes in the backbone.”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [26] Dauzhenka T, Kundrotas PJ, Vakser IA: Computational feasibility of an exhaustive search of side-chain conformations in protein-protein docking. J. Comput. Chem. 2018, 39: 2012– 2021. 30226647 PMC6186188 source
Not checked in the free run.
- cites [27] Schindler CEM, de Beauchene IC, de Vries SJ, Zacharias M: Protein-protein and peptide-protein docking and refinement using ATTRACT in CAPRI. Proteins 2017, 85: 391– 398. 27785830 source
Not checked in the free run.
- cites [28] Roy Burman SS, Yovanno RA, Gray JJ: Flexible backbone assembly and refinement of symmetrical homomeric complexes. Structure 2019, 27: 1041– 1051. 31006588 PMC6719319 source
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- Findingcitation
Studies have shown that exploration of the intermolecular energy landscapes based on the docking output is helpful in distinguishing interacting and non-interacting proteins.
“Since these landscapes should be different for strongly and weakly interacting proteins, studies have shown that exploration of the intermolecular energy landscapes based on the docking output is helpful in distinguishing interacting and non-interacting proteins [45,46].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [45] Yueh C, Hall DR, Xia B, Padhorny D, Kozakov D, Vajda S: ClusPro-DC: Dimer classification by the Cluspro server for protein-protein docking. J. Mol. Biol. 2017, 429: 372– 381. 27771482 PMC5538892 source
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- cites [46] Vakser IA: Low-resolution docking: Prediction of complexes for underdetermined structures. Biopolymers 1996, 39: 455– 464. 8756522 source
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- Findingreasoning
The correlation of docking scores with the actual energy of association is strong enough to reflect the intermolecular energy landscape.
“Still, the correlation of the docking scores with the actual energy of association is strong enough to reflect the intermolecular energy landscape.”
Quote in the paperSubstantial claim - Findingnone given
The current obstacle for applying co-evolution to docking is that it is not clear how to distinguish inter-molecular co-evolutionary information from intra-molecular one.
“The current obstacle for applying this approach to docking is that it is not clear how to distinguish the ínter-molecular co-evolutionary information, needed for docking, from the intra-molecular one, which is not directly relevant to docking.”
Quote in the paperSubstantial claim - Findingreasoning
Docking algorithms have not been specifically designed for or capable of distinguishing interacting and non-interacting proteins.
“Docking algorithms have not been specifically designed for or capable of distinguishing interacting and non-interacting proteins.”
Quote in the paperSubstantial claim - Findingreasoning
The issue with some leading publicly available docking servers is that an important part of the prediction protocols is based on data which serves as constraints for docking and is supposed to be supplied by the user.
“The issue with some leading publicly available docking servers is that an important part of the prediction protocols is based on data which serves as constraints for docking and is supposed to be supplied by the user.”
Quote in the paperSubstantial claim - Interpretationreasoning
Global conformational flexibility of the non-protein component (peptides, RNA, lipids) is an important natural obstacle in docking to other types of molecules.
“an important “natural” obstacle is the global conformational flexibility of the non-protein component, in cases of peptides, RNA and lipids.”
Quote in the paperSubstantial claim - Premisecitation
The rise of comparative modeling of protein-protein complexes (template-based docking), based on the rapid expansion of PDB, makes the availability of templates for docking procedures routine.
“The rise of the comparative modeling of protein-protein complexes (template-based docking), based on the rapid expansion of PDB, makes the availability of templates for docking procedures routine [12,13].”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [12] Kundrotas PJ, Zhu Z, Janin J, Vakser IA: Templates are available to model nearly all complexes of structurally characterized proteins. Proc. Natl. Acad. Sci. USA 2012, 109: 9438– 9441 22645367 PMC3386081 source
Not checked in the free run.
- cites [13] Lensink MF, Brysbaert G, Nadzirin N, Velankar S, Chaleil R, Gerguri T, Bates P, Laine E, Carbone A, Grudinin S,: Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment. Proteins 2019, 87: 1200– 1221. 31612567 PMC7274794 • •The paper presents the results of the most recent community-wide protein assembly prediction conducted jointly by the protein structure prediction (CASP) and prediction of protein interactions (CAPRI) challenges. The paper summarizes comparative evaluation of the results by a broad spectrum of participating groups, and as such reflects the state- source
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- Premisereasoning
Proteins in general are well-suited for the rigid body docking approximation due to the uniqueness or limited variety of their global fold.
“Whereas the basic motivation for that is the centrality of the protein-protein interactions in molecular mechanisms, an important pragmatic consideration for this focus is that proteins in general, due to the uniqueness or limited variety of their global fold (at least for the non-intrinsically disordered protein types) are well-suited for the rigid body docking approximation.”
Quote in the paperSubstantial claim - Interpretationreasoning
Progress in docking to other types of molecules and in membrane protein-protein interactions might be less obvious compared to the soluble globular protein-protein case.
“the progress there might be less obvious compared to the soluble globular protein-protein case.”
Quote in the paperNot a substantial claim - Premisecitation
Protein shape, reflecting the protein fold, to a large extent determines the docking solution, even at coarse-grained representation.
“Another important consideration is that the protein shape, reflecting the protein fold, to a large extent determines the docking solution, even at coarse-grained representation [11].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] Vakser IA: Low-resolution structural modeling of protein interactome. Curr. Opin. Struct. Biol. 2013, 23: 198– 205 23294579 PMC3676717 source
Not checked in the free run.
- Interpretationreasoning
In cases where conformational flexibility is less of a problem, such as protein-protein complexes in membranes and protein-DNA complexes, the dimensionality of the docking space may actually be less than that for soluble protein-protein complexes.
“In cases where the conformational flexibility is less of a problem, such as protein-protein complexes in membranes and protein-DNA complexes, the dimensionality of the docking space may actually be less than that for the soluble protein-protein complexes.”
Quote in the paperNot a substantial claim - Premisecitation
In recent years, there has been major progress in utilizing residue co-evolution information for predicting structures of individual proteins, based on rapid growth of experimental data and new ideas, combined with deep learning.
“In recent years, there has been major progress in utilizing the residue co-evolution information for predicting structures of individual proteins, based on the rapid growth of experimental data on proteins and new ideas on how to use it, combined with spectacular advances in computer science (deep learning) [30–33].”
Quote in the paperNot a substantial claim0 of 4 sources checked- cites [30] Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, Qin C, Zídek A, Nelson AWR, Bridgland A,: Improved protein structure prediction using potentials from deep learning. Nature 2020, 577: 706– 710. 31942072 • • The paper presents a deep-learning system that provides accurate predictions of the inter-residue distances and can be used to construct a protein-specific potential that represents the protein structure. The method was used for protein structure prediction, showing superior performance in the community-wide assessment of predictive methodologies. source
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- cites [31] Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J: Critical assessment of methods of protein structure prediction (CASP)-Round XIII. Proteins 2019, 87: 1011– 1020. 31589781 PMC6927249 source
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- cites [32] Anishchenko I, Ovchinnikov S, Kamisetty H, Baker D: Origins of coevolution between residues distant in protein 3D structures. Proc. Natl. Acad. Sci. USA 2017, 114: 9122– 9127. 28784799 PMC5576787 source
Not checked in the free run.
- cites [33] Ovchinnikov S, Park H, Varghese N, Huang PS, Pavlopoulos GA, Kim DE, Kamisetty H, Kyrpides NC, Baker D: Protein structure determination using metagenome sequence data. Science 2017, 355: 294– 298. 28104891 PMC5493203 source
Not checked in the free run.
- Rests on an assumption: Co-evolution of residues is correlated with their position in protein structure.
- Premisereasoning
Docking traditionally addresses only predicting the mode of interaction, given the fact of interaction obtained by other means, not predicting the fact of interaction.
“Docking traditionally addresses only the second problem.”
Quote in the paperSubstantial claim - Interpretationreasoning
Co-evolution data can be useful for structure prediction algorithms.
“Thus, the co-evolution data can be useful for structure prediction algorithms.”
Quote in the paperNot a substantial claim- Rests on an assumption: Co-evolution of residues is correlated with their position in protein structure.
- Interpretationreasoning
Precomputing the conformational ensemble and docking separate conformers should solve the docking problem in a number of cases.
“That, in principle, should solve the problem in a number of cases.”
Quote in the paperNot a substantial claim- Rests on an assumption: Proteins, as well as other macromolecules, change conformation upon binding.
- Premisecitation
Global flexibility is an important consideration for docking approaches.
“While the global flexibility (multiplicity of conformations of the overall structure), may not be a problem for a number of protein docking cases (see above), in general, it is an important consideration for the docking approaches [20].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [20] Ozdemir ES, Nussinov R, Gursoy A, Keskin O: Developments in integrative modeling with dynamical interfaces. Curr. Opin. Struct. Biol. 2019, 56: 11– 17. 30439586 source
Not checked in the free run.
- Rests on an assumption: Proteins, as well as other macromolecules, change conformation upon binding.
- Classified as probably not a substantial claim. 8
- May combine two claims. 10
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Findingnone givenAnother problem is a perceived lack of sufficient amount of sequence data on protein-protein (and/or protein-other molecules) interfaces needed for deep learning.
“The other problem is a perceived lack of sufficient amount of sequence data on protein-protein (and/or protein-other molecules) interfaces needed for the deep learning.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Findingnone givenFirst steps on the long path to whole-cell modeling are already being made by the community.
“However, first steps on this long path are already being made by the community.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationAutomated procedures like text mining of publicly available online publications face copyright restrictions and are hindered by still limited amount of open-access publications.
“Such automated procedures, like text mining of publicly available online publications [47] face copyright restrictions and are hindered by still limited amount of open-access publications.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [47] Badal VD, Kundrotas PJ, Vakser IA: Natural language processing in text mining for structural modeling of protein complexes. BMC Bioinformatics 2018, 19: 84. 29506465 PMC5838950 source
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationOther types of molecules interacting with proteins, as well as protein-protein interactions in membranes, have been studied extensively through the years.
“While other types of molecules interacting with proteins, as well as protein-protein interactions in membranes, have been studied extensively through the years [14–18]”
Quote in the paperNot a substantial claim0 of 5 sources checked- cites [14] Nithin C, Ghosh P, Bujnicki JM: Bioinformatics tools and benchmarks for computational docking and 3D structure prediction of RNA-protein complexes. Genes 2018, 9: 432. PMC6162694 30149645 source
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- cites [15] Si J, Zhao R, Wu R: An overview of the prediction of protein DNA-binding sites. Int. J. Mol. Sci. 2015, 16: 5194– 5215. 25756377 PMC4394471 source
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- cites [16] Hurwitz N, Schneidman-Duhovny D, Wolfson HJ: Memdock: An alpha-helical membrane protein docking algorithm. Bioinformatics 2016, 32: 2444– 2450. 27153621 source
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- cites [17] Koukos PI, Faro I, van Noort CW, Bonvin AMJJ: A membrane protein complex docking benchmark. J. Mol. Biol. 2018, 430: 5246– 5256. 30414967 source
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- cites [18] Ciemny M, Kurcinski M, Kamel K, Kolinski A, Alam N, Schueler-Furman O, Kmiecik S: Protein-peptide docking: Opportunities and challenges. Drug. Discov. Today 2018, 23: 1530– 1537. 29733895 source
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May combine two claims.
InterpretationcitationSuch flexibility limits the applicability of structure-alignment-based comparative docking and significantly increases the dimensionality of the docking search space by adding the multiplicity of internal degrees of freedom of the non-protein component.
“Such flexibility limits the applicability of the powerful structure-alignment-based comparative docking [19] and significantly increases the dimensionality of the docking search space by adding the multiplicity of the internal degrees of freedom of the non-protein component.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [19] Chakravarty D, McElfresh GW, Kundrotas PJ, Vakser IA: How to choose templates for modeling of protein complexes: Insights from benchmarking template-based docking. Proteins 2020, doi: 10.1002/prot.25875. PMC7375009 31994759 • Docking utilizing structure similarity of target protein monomers to template protein-protein complexes significantly expands structural coverage of the interactome. The paper presents a comprehensive comparative benchmarking study of the template-based docking utilizing different template detectiont methods. source
Not checked in the free run.
May combine two claims.
PremisereasoningThe rigid body docking approximation allows exclusion of internal degrees of freedom, reducing the global search space to six coordinates of a two rigid-bodies system.
“Such approximation is extremely important for the docking protocols because it allows one to exclude the enormous multitude of the internal degrees of freedom of the interacting molecules, reducing the global search space to only six coordinates of a two rigid-bodies system.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Interpretationnone givenFor many biological applications, the approximate docking prediction from the global search may suffice, but in a number of cases atomic resolution of the predicted match is required.
“Although for many biological applications, the approximate docking prediction from the global search may suffice (e.g. prediction of the binding interfaces for functional assessment, etc.), in a number of cases the atomic resolution of the predicted match is required (e.g. inhibition of interaction, affinity assessment, etc.).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSuch servers are common in prediction of individual protein structures.
“Such servers are common in prediction of individual protein structures [31].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [31] Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J: Critical assessment of methods of protein structure prediction (CASP)-Round XIII. Proteins 2019, 87: 1011– 1020. 31589781 PMC6927249 source
Not checked in the free run.
May combine two claims.
InterpretationreasoningOften the determination of the adequate conformational ensemble is complicated (e.g., for inherently flexible molecules like peptides, lipids) and/or the binding involves a significant contribution of induced fit mechanisms.
“However, often the determination of the adequate conformational ensemble is complicated (e.g. for inherently flexible molecules, like peptides, lipids, etc.) and/or the binding involves a significant contribution of the induced fit mechanisms.”
Quote in the paperSubstantial claim- Rests on an assumption: Proteins, as well as other macromolecules, change conformation upon binding.
May combine two claims.
PremisecitationEvidence points to the conformational selection binding mechanism, which allows one to precompute the conformational ensemble of the interacting molecule(s) and dock the separate conformers with limited conformational search.
“In a long-standing debate between the proponents of the “induced-fit” and the “conformational selection” binding mechanisms [21–23], the evidence pointing to the latter allows one to precompute the conformational ensemble of the interacting molecule(s) and dock the separate conformers with limited conformational search [24,25].”
Quote in the paperNot a substantial claim0 of 5 sources checked- cites [21] Ruvinsky AM, Kirys T, Tuzikov AV, Vakser IA: Ensemble-based characterization of unbound and bound states on protein energy landscape. Protein Sci. 2013, 22: 734– 744. 23526684 PMC3690713 source
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- cites [22] Csermely P, Palotai R, Nussinov R: Induced fit, conformational selection and independent dynamic segments: An extended view of binding events. Trends Biochem. Sci. 2010, 35: 539– 546. 20541943 PMC3018770 source
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- cites [23] Greives N, Zhou HX: Both protein dynamics and ligand concentration can shift the binding mechanism between conformational selection and induced fit. Proc. Natl. Acad. Sci. USA 2014, 111: 10197– 10202. 24982141 PMC4104862 source
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- cites [24] Marze NA, Burman SSR, Sheffler W, Gray JJ: Efficient flexible backbone protein-protein docking for challenging targets. Bioinformatics 2018, 34: 3461– 3469. 29718115 PMC6184633 source
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- cites [25] Kurkcuoglu Z, Bonvin AMJJ: Pre- and post-docking sampling of conformational changes using ClustENM and HADDOCK for protein-protein and protein-DNA systems. Proteins 2020, 88: 292– 306. 31441121 PMC6973081 source
Not checked in the free run.
- Rests on an assumption: Proteins, as well as other macromolecules, change conformation upon binding.
Probably not a substantial claim: may not pass S4 (based).
Premisenone givenExperimentally and computationally determined atomic resolution data currently provide snapshots of the molecules in the cellular environment.
“The experimentally and computationally determined atomic resolution data currently provide snapshots of the molecules in the cellular environment.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningIn membrane and protein-DNA cases, the recognition factors are smaller in scale than in soluble protein-protein complexes and require atomic-level prediction accuracy.
“However, the problem in these cases is that the recognition factors are smaller in scale than in the soluble protein-protein complexes (where coarse-grained representation determined by the global fold often suffices for a meaningful prediction) and require atomic-level prediction accuracy.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationMany modeling techniques needed for a first-pass approximation (e.g., coarse-graining) already exist, requiring proper scaling-up and integration into a self-consistent system.
“Arguably, many modeling techniques needed for a first-pass approximation (e.g. coarse-graining [56–58]) already exist, requiring “just” proper scaling-up and integration into a self-consistent system.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [56] Vakser IA, Matar OG, Lam CF: A systematic study of low-resolution recognition in protein-protein complexes. Proc. Natl. Acad. Sci. USA 1999, 96: 8477– 8482. 10411900 PMC17541 source
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- cites [57] Pak AJ, Voth GA: Advances in coarse-grained modeling of macromolecular complexes. Curr. Opin. Struct. Biol. 2018, 52: 119– 126. 30508766 PMC6296860 source
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- cites [58] Hafner AE, Krausser J, Saric A: Minimal coarse-grained models for molecular self-organisation in biology. Curr. Opin. Struct. Biol. 2019, 58: 43– 52. 31226513 source
Not checked in the free run.
May combine two claims.
PremisereasoningProtein-protein translational degrees of freedom in membranes are largely constrained in two dimensions by the membrane, and movement of proteins interacting with DNA may be modeled by sliding them along the one-dimensional DNA chain until they recognize the intended patch of nucleotides.
“Protein-protein translational degrees of freedom in membranes are largely constrained in two dimensions by the membrane, and movement of proteins interacting with DNA may be modeled by sliding them along the one-dimensional DNA chain until they recognize the intended patch of nucleotides.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
PremisereasoningThe local conformational search involves fewer degrees of freedom than the global one, and as such is more tractable.
“The local conformational search involves less degrees of freedom than the global one, and as such is more tractable.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Proteins, as well as other macromolecules, change conformation upon binding.
“Proteins, as well as other macromolecules, change conformation upon binding.”
The paper relies on this without support.
Co-evolution of residues is correlated with their position in protein structure.
“Co-evolution of residues is correlated with their position in protein structure.”
The authors state this as an assumption.
The fact of interaction is determined by (a) co-localization and (b) the strength of interaction.
“Assuming that the fact of interaction is determined by (a) co-localization and (b) the strength of interaction”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Accurate modeling of low-affinity interactions is a recognized challenge for docking methods.
“Accurate modeling of low-affinity interactions is a recognized challenge for docking methods.240”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [240]
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Self-citationTemplates are available to model nearly all complexes of structurally characterized proteins
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- Authors
- Vakser, I. A.
- Affiliations
- University of Kansas (US)
- Corresponding author
- Vakser, Ilya A
- ORCID
- Vakser, Ilya A
- Venue
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 64
- Pages
- 160-165
- ISSN
- 0959-440X (ISSN-L)
- PMC
- PMC7666046
- OpenAlex
- W3081286612
- Cited by
- 62
- References
- 58
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 6 · 2023: 7 · 2022: 24 · 2021: 4 · 2020: 2
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Opinion in Structural Biology (acceptedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- protein docking, macromolecular complexes, conformational flexibility, deep learning, binding affinity prediction, time propagation
- MeSH terms
- Protein Binding, Proteins, Molecular Docking Simulation
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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