The DOI matches its Crossref record; 360 of the 361 references it cites were found in a registry or an index.
Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning
Open accessAbstract
Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
In the citing paper
“AlphaFold, which predicts single ranked structures for a protein sequence, is unable to address directly allosteric mechanisms, which are based on the populations of conformational states in the ensembles.”
From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [107]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Items 201–360 of 360
Allostery through the computational microscope: cAMP activation of a canonical signalling domain
Malmstrom, R. D., Kornev, A. P., Taylor, S. S., & Amaro, R. E. (2015) · Nature Communications · doi:10.1038/ncomms8588 · Cited by 99
Inhibitors and chemical probes for molecular chaperone networks
Gestwicki, J. E., & Shao, H. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.tm118.002813 · Cited by 99
Src Kinase Conformational Activation: Thermodynamics, Pathways, and Mechanisms
Yang, S., & Roux, B. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000047 · Cited by 98
Structures of Large Protein Complexes Determined by Nuclear Magnetic Resonance Spectroscopy
Huang, C., & Kalodimos, C. G. (2017) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-070816-033701 · Cited by 96
Stetz, G., & Verkhivker, G. M. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005299 · Cited by 95
Self-citationQuantifying allosteric effects in proteins
Ming, D., & Wall, M. E. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20440 · Cited by 91
Cowan‐Jacob, S. W., Jahnke, W., & Knapp, S. (2014) · Future Medicinal Chemistry · doi:10.4155/fmc.13.216 · Cited by 90
Complexity and simplicity of ligand–macromolecule interactions: the energy landscape perspective
Verkhivker, G. M., Bouzida, D., Gehlhaar, D. K., Rejto, P. A., Freer, S. T., & Rose, P. W. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00310-x · Cited by 90
Self-citationAdvances in NMR Methods To Map Allosteric Sites: From Models to Translation
Boulton, S., & Melacini, G. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00718 · Cited by 90
Ferraro, M., D’Annessa, I., Moroni, E., Morra, G., Paladino, A., Rinaldi, S., Compostella, F., & Colombo, G. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b00825 · Cited by 90
Locking the Active Conformation of c-Src Kinase through the Phosphorylation of the Activation Loop
Meng, Y., & Roux, B. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.10.001 · Cited by 89
Binding Leverage as a Molecular Basis for Allosteric Regulation
Mitternacht, S., & Berezovsky, I. N. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002148 · Cited by 89
The Projection Analysis of NMR Chemical Shifts Reveals Extended EPAC Autoinhibition Determinants
Selvaratnam, R., VanSchouwen, B., Fogolari, F., Mazhab‐Jafari, M. T., Das, R., & Melacini, G. (2012) · Biophysical Journal · doi:10.1016/j.bpj.2011.12.030 · Cited by 89
Morra, G., Neves, M. A. C., Plescia, C. J., Tsustsumi, S., Neckers, L., Verkhivker, G. M., Altieri, D. C., & Colombo, G. (2010) · Journal of Chemical Theory and Computation · doi:10.1021/ct100334n · Cited by 87
Self-citationDelineation of the allosteric mechanism of a cytidylyltransferase exhibiting negative cooperativity.
Stevens, S. Y., Sanker, S., Kent, C., & Zuiderweg, E. R. P. (2001) · Nature Structural Biology · doi:10.1038/nsb1101-947 · Cited by 85
Liang, Z. T., Verkhivker, G. M., & Hu, G. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz029 · Cited by 85
Self-citationSchulze, J. O., Saladino, G., Busschots, K., Neimanis, S., Süß, E., Odadzic, D., Zeuzem, S., Hindie, V., Herbrand, A. K., Lisa, M., et al. (2016) · Cell chemical biology · doi:10.1016/j.chembiol.2016.06.017 · Cited by 84
Allosteric Communication Networks in Proteins Revealed through Pocket Crosstalk Analysis
Sala, G. L., Decherchi, S., Vivo, M. D., & Rocchia, W. (2017) · ACS Central Science · doi:10.1021/acscentsci.7b00211 · Cited by 84
Exploiting protein flexibility to predict the location of allosteric sites
Panjkovich, A., & Daura, X. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-273 · Cited by 83
A systematic protocol for the characterization of Hsp90 modulators
Matts, R. L., Brandt, G. E. L., Lu, Y., Dixit, A., Mollapour, M., Wang, S., Donnelly, A. C., Neckers, L. Μ., Verkhivker, G. M., & Blagg, B. S. J. (2010) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2010.10.029 · Cited by 83
Self-citationGhosh, A., & Vishveshwara, S. (2008) · Biochemistry · doi:10.1021/bi8007559 · Cited by 83
Understanding ligand-based modulation of the Hsp90 molecular chaperone dynamics at atomic resolution
Colombo, G., Morra, G., Meli, M., & Verkhivker, G. M. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0802879105 · Cited by 83
Self-citationDixit, A., & Verkhivker, G. M. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002179 · Cited by 83
Self-citationLisi, G. P., & Loria, J. P. (2017) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.08.002 · Cited by 83
Tracing an allosteric pathway regulating the activity of the HslV protease
Shi, L., & Kay, L. E. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1318476111 · Cited by 82
Flow graphs: Interweaving dynamics and structure
Lambiotte, R., Sinatra, R., Delvenne, J., Evans, T., Barahona, M., & Latora, V. (2011) · Physical Review E · doi:10.1103/physreve.84.017102 · Cited by 82
Hacisuleyman, A., & Erman, B. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005319 · Cited by 82
Allosteric cross-talk in chromatin can mediate drug-drug synergy
Adhireksan, Z., Palermo, G., Riedel, T., Ma, Z., Muhammad, R., Röthlisberger, U., Dyson, P. J., & Davey, C. A. (2017) · Nature Communications · doi:10.1038/ncomms14860 · Cited by 82
Pérez‐Hernández, G., & Noé, F. (2016) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b00738 · Cited by 79
Rational Design of Allosteric and Selective Inhibitors of the Molecular Chaperone TRAP1
Sànchez‐Martìn, C., Moroni, E., Ferraro, M., Laquatra, C., Cannino, G., Masgras, I., Negro, A., Quadrelli, P., Rasola, A., & Colombo, G. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107531 · Cited by 79
Allostery Wiring Diagrams in the Transitions that Drive the GroEL Reaction Cycle
Tehver, R., Chen, J., & Thirumalai, D. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.12.032 · Cited by 78
NMR Methods to Study Dynamic Allostery
Grutsch, S., Brüschweiler, S., & Tollinger, M. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004620 · Cited by 78
Encoding dynamics for multiscale community detection: Markov time sweeping for the map equation
Schaub, M. T., Lambiotte, R., & Barahona, M. (2012) · Physical Review E · doi:10.1103/physreve.86.026112 · Cited by 76
Estimating the resolution limit of the map equation in community detection
Kawamoto, T., & Rosvall, M. (2015) · Physical Review E · doi:10.1103/physreve.91.012809 · Cited by 76
Tyrosine Kinase Activation and Conformational Flexibility: Lessons from Src-Family Tyrosine Kinases
Meng, Y., Pond, M. P., & Roux, B. (2017) · Accounts of Chemical Research · doi:10.1021/acs.accounts.7b00012 · Cited by 76
Jiang, Y., & Kalodimos, C. G. (2017) · Journal of Molecular Biology · doi:10.1016/j.jmb.2017.07.007 · Cited by 76
The power of deep learning to ligand-based novel drug discovery
Baskin, I. I. (2020) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2020.1745183 · Cited by 76
Chemical shift-based methods in NMR structure determination
Nerli, S., McShan, A. C., & Sgourakis, N. G. (2018) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2018.03.002 · Cited by 74
Dixit, A., & Verkhivker, G. M. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000487 · Cited by 73
Self-citationIntegrative structural and dynamical biology with PLUMED-ISDB
Bonomi, M., & Camilloni, C. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx529 · Cited by 73
Zimmerman, M. I., Porter, J. R., Sun, X., Silva, R. R., & Bowman, G. R. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00500 · Cited by 73
Kaya, C., Armutlulu, A., Ekesan, Ş., & Haliloǧlu, T. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt284 · Cited by 72
Allostery without conformation change: modelling protein dynamics at multiple scales
McLeish, T. C. B., Rodgers, T. L., & Wilson, M. R. (2013) · Physical Biology · doi:10.1088/1478-3975/10/5/056004 · Cited by 72
Calculation of 15 N NMR chemical shifts: Recent advances and perspectives
Krivdin, L. B. (2017) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2017.08.001 · Cited by 71
Allosteric Communication in Cysteinyl tRNA Synthetase
Ghosh, A., Sakaguchi, R., Liu, C., Vishveshwara, S., & Hou, Y. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.246702 · Cited by 69
Time-resolved observation of protein allosteric communication
Buchenberg, S., Sittel, F., & Stock, G. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707694114 · Cited by 69
Kalbitzer, H. R., Rosnizeck, I. C., Munte, C. E., Narayanan, S. P., Kropf, V., & Spoerner, M. (2013) · Angewandte Chemie International Edition · doi:10.1002/anie.201305741 · Cited by 68
A Tool Set to Map Allosteric Networks through the NMR Chemical Shift Covariance Analysis
Boulton, S., Akimoto, M., Selvaratnam, R., Bashiri, A., & Melacini, G. (2014) · Scientific Reports · doi:10.1038/srep07306 · Cited by 67
Sattin, S., Tao, J., Vettoretti, G., Moroni, E., Pennati, M., Lopergolo, A., Morelli, L., Bugatti, A., Zuehlke, A. D., Moses, M., et al. (2015) · Chemistry - A European Journal · doi:10.1002/chem.201502211 · Cited by 67
Atomic view of the energy landscape in the allosteric regulation of Abl kinase
Saleh, T., Rossi, P., & Kalodimos, C. G. (2017) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3470 · Cited by 67
Coevolution in defining the functional specificity
Chakrabarti, S., & Panchenko, A. R. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22239 · Cited by 66
Hacisuleyman, A., & Erman, B. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25272 · Cited by 66
The multifaceted allosteric regulation of Aurora kinase A
Levinson, N. M. (2018) · Biochemical Journal · doi:10.1042/bcj20170771 · Cited by 65
Kuzmanic, A., Sutto, L., Saladino, G., Nebreda, Á. R., Gervasio, F. L., & Orozco, M. (2017) · eLife · doi:10.7554/elife.22175 · Cited by 64
A dynamic mechanism for allosteric activation of Aurora kinase A by activation loop phosphorylation
Ruff, E. F., Muretta, J. M., Thompson, A. R., Lake, E. W., Cyphers, S., Albanese, S. K., Hanson, S. M., Behr, J. M., Thomas, D. D., Chodera, J. D., et al. (2018) · eLife · doi:10.7554/elife.32766 · Cited by 64
Cembran, A., Kim, J., Gao, J., & Veglia, G. (2014) · Physical Chemistry Chemical Physics · doi:10.1039/c4cp00110a · Cited by 63
Csermely, P., Sandhu, K. S., Hazai, E., Hoksza, Z., Kiss, H., Miozzo, F., Veres, D. V., Piazza, F., & Nussinov, R. (2011) · Nature Precedings · doi:10.2174/138920312799277992 · Cited by 63
The allosteric communication pathways in KIX domain of CBP
Palazzesi, F., Barducci, A., Tollinger, M., & Parrinello, M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313548110 · Cited by 62
Lin, Y.-L., & Roux, B. (2013) · Journal of the American Chemical Society · doi:10.1021/ja405939x · Cited by 62
Structural and Functional Roles of Coevolved Sites in Proteins
Chakrabarti, S., & Panchenko, A. R. (2010) · PLoS ONE · doi:10.1371/journal.pone.0008591 · Cited by 61
Tse, A., & Verkhivker, G. M. (2015) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00240 · Cited by 58
Self-citationA non-equilibrium approach to allosteric communication
Stock, G., & Hamm, P. M. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0187 · Cited by 58
Bhattacharyya, M., & Vishveshwara, S. (2011) · Biochemistry · doi:10.1021/bi200306u · Cited by 57
Using higher-order Markov models to reveal flow-based communities in networks
Salnikov, V., Schaub, M. T., & Lambiotte, R. (2016) · Scientific Reports · doi:10.1038/srep23194 · Cited by 57
Agajanian, S., Odeyemi, O., & Verkhivker, G. M. (2019) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2019.00044 · Cited by 57
Self-citationThe Energy Landscape Analysis of Cancer Mutations in Protein Kinases
Dixit, A., & Verkhivker, G. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026071 · Cited by 56
Self-citationComputational approaches to detect allosteric pathways in transmembrane molecular machines
Stolzenberg, S., Michino, M., Levine, M. V., Weinstein, H., & Shi, L. (2016) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2016.01.010 · Cited by 56
Paladino, A., Woodford, M. R., Backe, S. J., Sager, R., Kancherla, P., Daneshvar, M., Chen, V. Z., Bourboulia, D., Ahanin, E. F., Prodromou, C., et al. (2020) · Chemistry - A European Journal · doi:10.1002/chem.202000615 · Cited by 56
Molecular Mechanism of Allosteric Communication in Hsp70 Revealed by Molecular Dynamics Simulations
Chiappori, F., Ivan Merelli, A., Colombo, G., Milanesi, L., & Morra, G. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002844 · Cited by 54
Interactions in Native Binding Sites Cause a Large Change in Protein Dynamics
Ming, D., & Wall, M. E. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.01.097 · Cited by 54
A Mechanistic Understanding of Allosteric Immune Escape Pathways in the HIV-1 Envelope Glycoprotein
Sethi, A., Jianhui, T., Derdeyn, C. A., Korber, B., & Gnanakaran, S. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003046 · Cited by 54
Dixit, A., & Verkhivker, G. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037605 · Cited by 53
Self-citationLin, Y.-L., Meng, Y., Huang, L., & Roux, B. (2014) · Journal of the American Chemical Society · doi:10.1021/ja504146x · Cited by 52
Generative adversarial networks with decoder–encoder output noises
Zhong, G., Gao, W. J., Liu, Y., Yang, Y., Wang, D., & Huang, K. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.04.005 · Cited by 52
Allosteric Pathways in the PPARγ-RXRα nuclear receptor complex
Ricci, C. G., Silveira, R. L., Rivalta, I., Batista, V. S., & Skaf, M. S. (2016) · Scientific Reports · doi:10.1038/srep19940 · Cited by 51
The Activation of c-Src Tyrosine Kinase: Conformational Transition Pathway and Free Energy Landscape
Fajer, M., Meng, Y., & Roux, B. (2016) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.6b08409 · Cited by 51
Separating Dipolar and Chemical Exchange Magnetization Transfer Processes in 1 H‐CEST
Yuwen, T., Sekhar, A., & Kay, L. E. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201610759 · Cited by 51
Measuring hydrogen exchange rates in invisible protein excited states
Long, D., Bouvignies, G., & Kay, L. E. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405011111 · Cited by 50
Atomistic Kinetic Model for Population Shift and Allostery in Biomolecules
Long, D., & Brüschweiler, R. (2011) · Journal of the American Chemical Society · doi:10.1021/ja208813t · Cited by 48
NMR reveals novel mechanisms of protein activity regulation
Kalodimos, C. G. (2011) · Protein Science · doi:10.1002/pro.614 · Cited by 48
Grebner, C., Matter, H., Plowright, A. T., & Heßler, G. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.9b02044 · Cited by 47
Stetz, G., & Verkhivker, G. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143752 · Cited by 46
Self-citationStetz, G., & Verkhivker, G. M. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00755 · Cited by 45
Self-citationTsuchiya, Y., Taneishi, K., & Yonezawa, Y. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00426 · Cited by 45
Toledano, D. T., Fernández-Gallego, M. P., & Lozano-Díez, A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205355 · Cited by 44
Chiappori, F., Merelli, I., Milanesi, L., Colombo, G., & Morra, G. (2016) · Scientific Reports · doi:10.1038/srep23474 · Cited by 43
Astl, L., & Verkhivker, G. M. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00119 · Cited by 43
Self-citationKimanius, D., Pettersson, I., Schluckebier, G., Lindahl, E. R., & Andersson, M. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00299 · Cited by 40
James, K. A., & Verkhivker, G. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113488 · Cited by 40
Self-citationDesign of Allosteric Stimulators of the Hsp90 ATPase as New Anticancer Leads
D’Annessa, I., Sattin, S., Tao, J., Pennati, M., Sànchez‐Martìn, C., Moroni, E., Rasola, A., Zaffaroni, N., Agard, D. A., Bernardi, A., et al. (2017) · Chemistry - A European Journal · doi:10.1002/chem.201700169 · Cited by 40
Applications of NMR and computational methodologies to study protein dynamics
Narayanan, C., Bafna, K., Roux, L. D., Agarwal, P. K., & Doucet, N. (2017) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2017.05.002 · Cited by 40
Protein function and allostery: a dynamic relationship
Kalodimos, C. G. (2012) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.06319.x · Cited by 39
Combining Metadynamics and Integrated Tempering Sampling
Yang, Y., Niu, H., & Parrinello, M. (2018) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.8b03005 · Cited by 39
Tse, A., & Verkhivker, G. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130203 · Cited by 38
Self-citationAguilar, D., Oliva, B., & Marino‐Buslje, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041430 · Cited by 37
Structure-Functional Prediction and Analysis of Cancer Mutation Effects in Protein Kinases
Dixit, A., & Verkhivker, G. M. (2014) · Computational and Mathematical Methods in Medicine · doi:10.1155/2014/653487 · Cited by 37
Self-citationRecognition of protein allosteric states and residues: Machine learning approaches
Zhou, H.-Y., Dong, Z., & Tao, P. (2018) · Journal of Computational Chemistry · doi:10.1002/jcc.25218 · Cited by 36
Self-citationCharacterization of low-lying excited states of proteins by high-pressure NMR
Williamson, M. P., & Kitahara, R. (2018) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2018.10.014 · Cited by 35
How do dynamic cellular signals travel long distances?
Nussinov, R. (2011) · Molecular BioSystems · doi:10.1039/c1mb05205e · Cited by 34
Munte, C. E., Erlach, M. B., Kremer, W., Koehler, J., & Kalbitzer, H. R. (2013) · Angewandte Chemie International Edition · doi:10.1002/anie.201301537 · Cited by 34
Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery
Kalescky, R. J. B., Zhou, H.-Y., Liu, J., & Tao, P. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004893 · Cited by 34
Self-citationUnraveling the meaning of chemical shifts in protein NMR
Berjanskii, M. V., & Wishart, D. S. (2017) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2017.07.005 · Cited by 34
Identifying Key Residues for Protein Allostery through Rigid Residue Scan
Kalescky, R. J. B., Liu, J., & Tao, P. (2014) · The Journal of Physical Chemistry A · doi:10.1021/jp5083455 · Cited by 33
Self-citationDevelopment of Phenyl Cyclohexylcarboxamides as a Novel Class of Hsp90 C‐terminal Inhibitors
Garg, G., Forsberg, L. K., Zhao, H., & Blagg, B. S. J. (2017) · Chemistry - A European Journal · doi:10.1002/chem.201703206 · Cited by 33
Ito, S. (2016) · Scientific Reports · doi:10.1038/srep36831 · Cited by 32
Czemeres, J., Buse, K., & Verkhivker, G. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0190267 · Cited by 32
Self-citationRinaldi, S., Assimon, V. A., Young, Z. T., Morra, G., Shao, H., Taylor, I. R., Gestwicki, J. E., & Colombo, G. (2018) · ACS Chemical Biology · doi:10.1021/acschembio.8b00712 · Cited by 32
Amor, B., Yaliraki, S. N., Woscholski, R., & Barahona, M. (2014) · Molecular BioSystems · doi:10.1039/c4mb00088a · Cited by 31
Markov models for the elucidation of allosteric regulation
Sengupta, U., & Strodel, B. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0178 · Cited by 31
Paladino, A., Morra, G., & Colombo, G. (2015) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5b00270 · Cited by 30
Curiosity‐driven recommendation strategy for adaptive learning via deep reinforcement learning
Han, R., Chen, K., & Tan, C. (2020) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12199 · Cited by 30
Xia, J., Deng, N.-J., & Levy, R. M. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp400797y · Cited by 29
Statistical Model Selection for Markov Models of Biomolecular Dynamics
McGibbon, R. T., Schwantes, C. R., & Pande, V. S. (2014) · The Journal of Physical Chemistry B · doi:10.1021/jp411822r · Cited by 29
Random network behaviour of protein structures
Brinda, K. V., Vishveshwara, S., & Vishveshwara, S. (2009) · Molecular BioSystems · doi:10.1039/b903019k · Cited by 27
Hu, S., Ferraro, M., Thomas, A. P., Chung, J. M., Yoon, N. G., Seol, J.-H., Kim, S., Kim, H., An, M. Y., Ok, H., et al. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.9b01420 · Cited by 27
NMR Characterization of Information Flow and Allosteric Communities in the MAP Kinase p38γ
Aoto, P. C., Martin, B. T., & Wright, P. E. (2016) · Scientific Reports · doi:10.1038/srep28655 · Cited by 26
Garg, G., Zhao, H., & Blagg, B. S. J. (2016) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2016.11.030 · Cited by 26
Conformational Entropy as Collective Variable for Proteins
Palazzesi, F., Valsson, Ó., & Parrinello, M. (2017) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.7b01770 · Cited by 26
Boulton, S., Selvaratnam, R., Ahmed, R., & Melacini, G. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7386-6_18 · Cited by 26
Brotzakis, Z. F., & Parrinello, M. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00827 · Cited by 26
MSMExplorer: visualizing Markov state models for biomolecule folding simulations
Cronkite-Ratcliff, B., & Pande, V. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt051 · Cited by 25
Stetz, G., & Verkhivker, G. M. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.7b00638 · Cited by 23
Self-citationZhou, H.-Y., Dong, Z., Verkhivker, G. M., Zoltowski, B. D., & Tao, P. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006801 · Cited by 23
Self-citationMachine Learning Classification Model for Functional Binding Modes of TEM-1 β-Lactamase
Wang, F., Shen, L., Zhou, H.-Y., Wang, S., Wang, X., & Tao, P. (2019) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2019.00047 · Cited by 23
Self-citationVerkhivker, G. M., Dixit, A., Morra, G., & Colombo, G. (2009) · Current Topics in Medicinal Chemistry · doi:10.2174/156802609789895700 · Cited by 22
Self-citationDarmon, D. M., & Rapp, P. E. (2017) · Physical review. E · doi:10.1103/physreve.96.022121 · Cited by 22
Hansia, P., Ghosh, A., & Vishveshwara, S. (2009) · Molecular BioSystems · doi:10.1039/b903807h · Cited by 21
Li, C., Ma, N., Wang, Y., Wang, Y., & Chen, G. (2014) · The Journal of Physical Chemistry B · doi:10.1021/jp411111g · Cited by 21
Vasantha Kumar, M. V., Noor, R. E., Davis, R. E., Zhang, Z., Sipavicius, E., Keramisanou, D., Blagg, B. S. J., & Gelis, I. (2018) · MedChemComm · doi:10.1039/c8md00151k · Cited by 21
Astl, L., & Verkhivker, G. M. (2019) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2019.07.008 · Cited by 21
Self-citationVerkhivker, G. M. (2018) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2018.04.008 · Cited by 20
Self-citationAgajanian, S., Odeyemi, O., Bischoff, N., Ratra, S., & Verkhivker, G. M. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00414 · Cited by 20
Self-citationProbing Protein Allostery as a Residue-Specific Concept via Residue Response Maps
Hayatshahi, H. S., Ahuactzin-Garcia, E., Tao, P., Wang, S., & Liu, J. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00447 · Cited by 20
Self-citationThe Role and Promise of Artificial Intelligence in Medical Toxicology
Chary, M. A., Manini, A. F., Boyer, E. W., & Burns, M. M. (2020) · Journal of Medical Toxicology · doi:10.1007/s13181-020-00769-5 · Cited by 20
Allosteric signalling in the outer membrane translocation domain of PapC usher
Farabella, I., Pham, T., Henderson, N. S., Geibel, S., Phan, G., Thanassi, D. G., Delcour, A. H., Waksman, G., & Topf, M. (2014) · eLife · doi:10.7554/elife.03532 · Cited by 18
Novobiocin Analogues That Inhibit the MAPK Pathway
Hall, J. A., Seedarala, S., Zhao, H., Garg, G., Ghosh, S., & Blagg, B. S. J. (2016) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b01354 · Cited by 18
Stetz, G., Tse, A., & Verkhivker, G. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0186089 · Cited by 18
Self-citationZaiter, S. S., Huo, Y., Tiew, F. Y., Gestwicki, J. E., & McAlpine, S. R. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b01436 · Cited by 18
Astl, L., Tse, A., & Verkhivker, G. M. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-8719-7_9 · Cited by 18
Self-citationNMR studies of protein structure and dynamics – A look backwards and forwards
Kay, L. E. (2011) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2011.08.010 · Cited by 17
Software for Building Markov State Models
Bowman, G. R., & Noé, F. (2013) · Advances in experimental medicine and biology · doi:10.1007/978-94-007-7606-7_11 · Cited by 16
Predicting allostery and microbial drug resistance with molecular simulations
Cortina, G. A., & Kasson, P. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.09.001 · Cited by 16
Using Chemical Shifts to Determine Structural Changes in Proteins upon Complex Formation
Cavalli, A., Montalvão, R. W., & Vendruscolo, M. (2011) · The Journal of Physical Chemistry B · doi:10.1021/jp202647q · Cited by 15
A Tutorial on Building Markov State Models with MSMBuilder and Coarse-Graining Them with BACE
Bowman, G. R. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-658-0_8 · Cited by 15
Dynamical important residue network (DIRN): network inference via conformational change
Li, Q., Luo, R., & Chen, H. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz298 · Cited by 15
Understanding Protein Folding Using Markov State Models
Pande, V. S. (2013) · Advances in experimental medicine and biology · doi:10.1007/978-94-007-7606-7_8 · Cited by 14
Application of Hidden Markov Models in Biomolecular Simulations
Shukla, S., Shamsi, Z., Moffett, A. S., Selvam, B., & Shukla, D. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6753-7_3 · Cited by 13
Revealing Hidden Conformational Space of LOV Protein VIVID Through Rigid Residue Scan Simulations
Zhou, H.-Y., Zoltowski, B. D., & Tao, P. (2017) · Scientific Reports · doi:10.1038/srep46626 · Cited by 13
Self-citationThe impact of long-distance mutations on the Ω-loop conformation in TEM type β-lactamases
Shcherbinin, D., Veselovsky, A. V., Rubtsova, M. Y., Григоренко, В. Г., & Egorov, A. M. (2019) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2019.1634642 · Cited by 12
REDAN: relative entropy-based dynamical allosteric network model
Zhou, H., & Tao, P. (2018) · Molecular Physics · doi:10.1080/00268976.2018.1543904 · Cited by 11
Self-citationComputational Modeling of the Hsp90 Interactions with Cochaperones and Small-Molecule Inhibitors
Verkhivker, G. M. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7477-1_19 · Cited by 10
Self-citationAnsari, S. M., Coletta, A., Skeby, K. K., Sørensen, J., Schiøtt, B., & Palmer, D. S. (2016) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.6b07491 · Cited by 9
Directed kinetic transition network model
Zhou, H.-Y., Wang, F., Bennett, D. I. G., & Tao, P. (2019) · The Journal of Chemical Physics · doi:10.1063/1.5110896 · Cited by 8
Self-citationLawless, N., Blacklock, K. M., Berrigan, E., & Verkhivker, G. M. (2013) · Pharmaceuticals · doi:10.3390/ph6111407 · Cited by 7
Self-citationTse, A., & Verkhivker, G. M. (2015) · Molecular BioSystems · doi:10.1039/c5mb00246j · Cited by 7
Self-citationDynamics Sampling in Transition Pathway Space
Zhou, H.-Y., & Tao, P. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00606 · Cited by 7
Self-citationVerkhivker, G. M. (2014) · Israel Journal of Chemistry · doi:10.1002/ijch.201300143 · Cited by 4
Self-citationAuthor response: Allosteric signalling in the outer membrane translocation domain of PapC usher
Farabella, I., Pham, T., Henderson, N. S., Geibel, S., Phan, G., Thanassi, D. G., Delcour, A. H., Waksman, G., & Topf, M. (2014) · eLife · doi:10.7554/elife.03532.020 · Cited by 1
Ruff, E. F., Muretta, J. M., Thompson, A. R., Lake, E. W., Cyphers, S., Albanese, S. K., Hanson, S. M., Behr, J. M., Thomas, D. D., Chodera, J. D., et al. (2018) · eLife · doi:10.7554/elife.32766.019 · Cited by 1
Kuzmanic, A., Sutto, L., Saladino, G., Nebreda, Á. R., Gervasio, F. L., & Orozco, M. (2017) · eLife · doi:10.7554/elife.22175.024 · Cited by 1
Flagged first, then by citations
1 of the 361 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Verkhivker, 2016, Dissecting allosteric regulatory mechanisms of the Hsp90 chaperone interactions with the protein kinase clients: Integrating structural bioinformatics with multiscale atomistic simulations and biophysical experiments, Abst. Pap. Am. Chem. Soc., 251, 2
Cited by
Sorted by citations
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190
Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs
Nussinov, R., Zhang, M., Maloney, R., Liu, Y., Tsai, C.-J., & Jang, H. (2022) · Journal of Molecular Biology · doi:10.1016/j.jmb.2022.167569 · Cited by 66
Machine learning approaches in predicting allosteric sites
Nerín-Fonz, F., & Cournia, Z. (2024) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2024.102774 · Cited by 62
Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development
Nam, K., Shao, Y., Major, D. T., & Wolf‐Watz, M. (2024) · ACS Omega · doi:10.1021/acsomega.3c09084 · Cited by 57
New Insights into the Cooperativity and Dynamics of Dimeric Enzymes
Chen, K.-W., Sun, T., & Wu, Y. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00042 · Cited by 46
Metadata
- Authors
- Verkhivker, G. M., Agajanian, S., Hu, G., & Tao, P.
- Affiliations
- Chapman University (US)
- Soochow University (CN)
- Southern Methodist University (US)
- Corresponding author
- Verkhivker, Gennady M.
- Venue
- Frontiers in Molecular Biosciences
- Publisher
- Frontiers Media SA
- Published
- 2020-07-09
- Volume
- 7
- Pages
- 136-136
- ISSN
- 2296-889X (ISSN-L)
- PMC
- PMC7363947
- OpenAlex
- W3041792613
- Cited by
- 76
- References
- 361
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 15 · 2023: 13 · 2022: 15 · 2021: 10 · 2020: 4
- FWCI
- 1.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Molecular Biosciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Chapman University Digital Commons (Chapman University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Chapman University
- National Institute of General Medical Sciences (R15GM122013)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- allosteric regulation, allosteric proteins, allosteric modulators, multiscale modeling, Markov model, protein-protein interaction network, information theory, deep learning, deep reinforcement learning, allosteric mechanism
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
