Modeling covalent-modifier drugs.
Abstract
In this review, we present a summary of how computer modeling has been used in the development of covalent-modifier drugs. Covalent-modifier drugs bind by forming a chemical bond with their target. This covalent binding can improve the selectivity of the drug for a target with complementary reactivity and result in increased binding affinities due to the strength of the covalent bond formed. In some cases, this results in irreversible inhibition of the target, but some targeted covalent inhibitor (TCI) drugs bind covalently but reversibly. Computer modeling is widely used in drug discovery, but different computational methods must be used to model covalent modifiers because of the chemical bonds formed. Structural and bioinformatic analysis has identified sites of modification that could yield selectivity for a chosen target. Docking methods, which are used to rank binding poses of large sets of inhibitors, have been augmented to support the formation of protein-ligand bonds and are now capable of predicting the binding pose of covalent modifiers accurately. The pK a's of amino acids can be calculated in order to assess their reactivity towards electrophiles. QM/MM methods have been used to model the reaction mechanisms of covalent modification. The continued development of these tools will allow computation to aid in the development of new covalent-modifier drugs. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Due to increasing interest in covalent drugs, many non-covalent docking programs have developed covalent versions and some new docking programs focused on covalent ligands have been developed.
“Due to the increasing interest in covalent drugs, many non-covalent docking programs have developed covalent versions and some new docking programs focused on covalent ligands have been developed (Kumalo et al., 2015; Awoonor-Williams et al., 2017; De Cesco et al., 2017).”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Awoonor-Williams et al., 2017
Cites
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · see citing works
Scalable molecular dynamics with NAMD
Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20289 · Cited by 16,914 · see citing works
Targeting cancer with small molecule kinase inhibitors
Zhang, J., Yang, P. L., & Gray, N. S. (2008) · Nature reviews. Cancer · doi:10.1038/nrc2559 · Cited by 2,586 · see citing works
A hierarchical approach to all‐atom protein loop prediction
Jacobson, M. P., Pincus, D. L., Rapp, C. S., Day, T., Honig, B. H., Shaw, D. E., & Friesner, R. A. (2004) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10613 · Cited by 2,541 · see citing works
Insights into Current Limitations of Density Functional Theory
Cohen, A. J., Mori-Sánchez, P., & Yang, W. (2008) · Science · doi:10.1126/science.1158722 · Cited by 2,527 · see citing works
Comprehensive analysis of kinase inhibitor selectivity
Davis, M. I., Hunt, J. P., Herrgard, S., Ciceri, P., Wodicka, L. M., Pallares, G., Hocker, M., Treiber, D. K., & Zarrinkar, P. P. (2011) · Nature Biotechnology · doi:10.1038/nbt.1990 · Cited by 2,409 · see citing works
Computational Methods in Drug Discovery
Sliwoski, G. R., Kothiwale, S., Meiler, J., & Lowe, E. W. (2013) · Pharmacological Reviews · doi:10.1124/pr.112.007336 · Cited by 2,226 · see citing works
The resurgence of covalent drugs
Singh, J., Petter, R. C., Baillie, T. A., & Whitty, A. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3410 · Cited by 1,873 · see citing works
Drug-target residence time and its implications for lead optimization
Copeland, R. A., Pompliano, D. L., & Meek, T. D. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2082 · Cited by 1,464 · see citing works
Wang, L., Wu, Y., Deng, Y., Kim, B., Pierce, L., Krilov, G., Lupyan, D., Robinson, S., Dahlgren, M. K., Greenwood, J., et al. (2015) · Journal of the American Chemical Society · doi:10.1021/ja512751q · Cited by 1,313 · see citing works
On the Role of the Crystal Environment in Determining Protein Side-chain Conformations
Jacobson, M. P., Friesner, R. A., Xiang, Z., & Honig, B. H. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00470-9 · Cited by 1,289 · see citing works
Irreversible Inhibitors of Serine, Cysteine, and Threonine Proteases
Powers, J. C., Asgian, J. L., Ekici, Ö. D., & James, K. E. (2002) · Chemical Reviews · doi:10.1021/cr010182v · Cited by 1,090 · see citing works
pKa's of ionizable groups in proteins: atomic detail from a continuum electrostatic model
Bashford, D., & Karplus, M. (1990) · Biochemistry · doi:10.1021/bi00496a010 · Cited by 1,089 · see citing works
Sherwood, P., de Vries, A. H., Guest, M. F., Schreckenbach, G., Catlow, C. R. A., French, S., Sokol, A. A., Bromley, S. T., Thiel, W., Turner, A. J., et al. (2003) · Journal of Molecular Structure THEOCHEM · doi:10.1016/s0166-1280(03)00285-9 · Cited by 1,058 · see citing works
Proteome-wide covalent ligand discovery in native biological systems
Backus, K. M., Correia, B. E., Lum, K. M., Forli, S., Horning, B. D., González-Páez, G. E., Chatterjee, S., Lanning, B. R., Teijaro, J. R., Olson, A. J., et al. (2016) · Nature · doi:10.1038/nature18002 · Cited by 940 · see citing works
The maximal affinity of ligands
Kuntz, I. D., Chen, K., Sharp, K. A., & Kollman, P. A. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.18.9997 · Cited by 859 · see citing works
The drug–target residence time model: a 10-year retrospective
Copeland, R. A. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2015.18 · Cited by 726 · see citing works
Mannhold, R., Poda, G. I., Ostermann, C., & Tetko, I. V. (2008) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.21494 · Cited by 663 · see citing works
Developing Irreversible Inhibitors of the Protein Kinase Cysteinome
Liu, Q., Sabnis, Y. A., Zhao, Z., Zhang, T., Buhrlage, S. J., Jones, L. H., & Gray, N. S. (2013) · Chemistry & Biology · doi:10.1016/j.chembiol.2012.12.006 · Cited by 662 · see citing works
Calculation of absolute protein–ligand binding free energy from computer simulations
Woo, H.-J., & Roux, B. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0409005102 · Cited by 661 · see citing works
Jackson, P. A., Widen, J. C., Harki, D. A., & Brummond, K. M. (2017) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.6b00788 · Cited by 588 · see citing works
Targeted Covalent Inhibitors for Drug Design
Baillie, T. A. (2016) · Angewandte Chemie International Edition · doi:10.1002/anie.201601091 · Cited by 578 · see citing works
Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review
Cheng, T., Li, Q., Zhou, Z., Wang, Y., & Bryant, S. H. (2012) · The AAPS Journal · doi:10.1208/s12248-012-9322-0 · Cited by 575 · see citing works
Alchemical free energy methods for drug discovery: Progress and challenges
Chodera, J., Mobley, D., Shirts, M., Dixon, R. W., Branson, K., & Pande, V. (2011) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2011.01.011 · Cited by 545 · see citing works
Bauer, R. A. (2015) · Drug Discovery Today · doi:10.1016/j.drudis.2015.05.005 · Cited by 534 · see citing works
C hem S hell—a modular software package for QM / MM simulations
Metz, S., Kästner, J., Sokol, A. A., Keal, T. W., & Sherwood, P. (2013) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1163 · Cited by 531 · see citing works
Structural Bioinformatics-Based Design of Selective, Irreversible Kinase Inhibitors
Cohen, M. S., Zhang, C., Shokat, K. M., & Taunton, J. (2005) · Science · doi:10.1126/science1108367 · Cited by 509 · see citing works
Reversible targeting of noncatalytic cysteines with chemically tuned electrophiles
Serafimova, I. M., Pufall, M. A., Krishnan, S., Duda, K., Cohen, M. S., Maglathlin, R. L., McFarland, J. M., Miller, R. M., Frödin, M., & Taunton, J. (2012) · Nature Chemical Biology · doi:10.1038/nchembio.925 · Cited by 496 · see citing works
Docking Covalent Inhibitors: A Parameter Free Approach To Pose Prediction and Scoring
Zhu, K., Borrelli, K., Greenwood, J., Day, T., Abel, R., Farid, R., & Harder, E. D. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci500118s · Cited by 445 · see citing works
Ligand and Target Discovery by Fragment-Based Screening in Human Cells
Parker, C. G., Galmozzi, A., Wang, Y., Correia, B. E., Sasaki, K., Joslyn, C. M., Kim, A. S., Cavallaro, C. L., Lawrence, R. M., Johnson, S. R., et al. (2017) · Cell · doi:10.1016/j.cell.2016.12.029 · Cited by 439 · see citing works
Prolonged and tunable residence time using reversible covalent kinase inhibitors
Bradshaw, J. M., McFarland, J. M., Paavilainen, V. O., Bisconte, A. R., Tam, D., Phan, V. T., Romanov, S., Finkle, D., Shu, J., Patel, V. P., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1817 · Cited by 428 · see citing works
Relationship Between the Occurrence of Cysteine in Proteins and the Complexity of Organisms
Miseta, A., & Csutora, P. (2000) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a026406 · Cited by 401 · see citing works
Strategies for Discovering and Derisking Covalent, Irreversible Enzyme Inhibitors
Johnson, D. S., Weerapana, E., & Cravatt, B. F. (2010) · Future Medicinal Chemistry · doi:10.4155/fmc.10.21 · Cited by 387 · see citing works
The implementation of a fast and accurate QM/MM potential method in Amber
Walker, R. C., Crowley, M. F., & Case, D. (2008) · Journal of Computational Chemistry · doi:10.1002/jcc.20857 · Cited by 377 · see citing works
pK values of the ionizable groups of proteins
Thurlkill, R. L., Grimsley, G. R., Scholtz, J. M., & Pace, C. N. (2006) · Protein Science · doi:10.1110/ps.051840806 · Cited by 369 · see citing works
Wang, J., Deng, Y., & Roux, B. (2006) · Biophysical Journal · doi:10.1529/biophysj.106.084301 · Cited by 355 · see citing works
Challenges and advances in computational docking: 2009 in review
Yuriev, E., Agostino, M., & Ramsland, P. A. (2010) · Journal of Molecular Recognition · doi:10.1002/jmr.1077 · Cited by 350 · see citing works
Covalent Modifiers: An Orthogonal Approach to Drug Design
Potashman, M. H., & Duggan, M. E. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm8008597 · Cited by 348 · see citing works
Irreversible Protein Kinase Inhibitors: Balancing the Benefits and Risks
Barf, T., & Kaptein, A. (2012) · Journal of Medicinal Chemistry · doi:10.1021/jm3003203 · Cited by 331 · see citing works
Delocalization Error and “Functional Tuning” in Kohn–Sham Calculations of Molecular Properties
Autschbach, J., & Srebro‐Hooper, M. (2014) · Accounts of Chemical Research · doi:10.1021/ar500171t · Cited by 295 · see citing works
A 21st century revisionist's view at a turning point in enzymology
Nagel, Z. D., & Klinman, J. P. (2009) · Nature Chemical Biology · doi:10.1038/nchembio.204 · Cited by 294 · see citing works
Schwartz, P. A., Kuzmic, P., Solowiej, J., Bergqvist, S., Bolanos, B., Almaden, C., Nagata, A., Ryan, K., Feng, J., Dalvie, D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313733111 · Cited by 281 · see citing works
Covalent docking of large libraries for the discovery of chemical probes
London, N., Miller, R. M., Krishnan, S., Uchida, K., Irwin, J. J., Eidam, O., Gibold, L., Cimermančič, P., Bonnet, R., Shoichet, B. K., et al. (2014) · Nature Chemical Biology · doi:10.1038/nchembio.1666 · Cited by 274 · see citing works
Progress in the prediction of p K a values in proteins
Alexov, E. G., Mehler, E. L., Baker, N., Baptista, A. M., Huang, Y. G., Milletti, F., Nielsen, J. E., Farrell, D., Carstensen, T., Olsson, M. H. M., et al. (2011) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.23189 · Cited by 269 · see citing works
Krishnan, S., Miller, R. M., Tian, B., Mullins, R. D., Jacobson, M. P., & Taunton, J. (2014) · Journal of the American Chemical Society · doi:10.1021/ja505194w · Cited by 267 · see citing works
Michel, J., & Essex, J. (2010) · J. Comput. Aided Mol. Des. · doi:10.1007/s10822-010-9363-3 · Cited by 254 · see citing works
Proton binding to proteins: pK(a) calculations with explicit and implicit solvent models.
Simonson, T., Carlsson, J., & Case, D. (2004) · Journal of the American Chemical Society · doi:10.1021/ja039788m · Cited by 247 · see citing works
Covalent docking using autodock: two-point attractor and flexible side chain methods.
Bianco, G., Forli, S., Goodsell, D. S., & Olson, A. J. (2016) · Protein Science · doi:10.1002/pro.2733 · Cited by 246 · see citing works
Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds
Lee, C. T., Comer, J. R., Herndon, C., Leung, N., Pavlova, À., Swift, R. V., Tung, C., Rowley, C. N., Amaro, R. E., Chipot, C. J., et al. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00022 · Cited by 234 · see citing works
Corbeil, C. R., Englebienne, P., & Moitessier, N. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci6002637 · Cited by 215 · see citing works
Scholz, C., Knorr, S., Hamacher, K., & Schmidt, B. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci500681r · Cited by 206 · see citing works
Leproult, É., Barluenga, S., Moras, D., Wurtz, J., & Winssinger, N. (2011) · Journal of Medicinal Chemistry · doi:10.1021/jm101396q · Cited by 196 · see citing works
Delocalization errors in density functionals and implications for main-group thermochemistry
Johnson, E. R., Mori‐Sánchez, P., Cohen, A. J., & Yang, W. (2008) · The Journal of Chemical Physics · doi:10.1063/1.3021474 · Cited by 190 · see citing works
Keap Calm, and Carry on Covalently
Wilson, A. J., Kerns, J. K., Callahan, J. F., & Moody, C. J. (2013) · Journal of Medicinal Chemistry · doi:10.1021/jm400224q · Cited by 171 · see citing works
Drug discovery for a new generation of covalent drugs
Kalgutkar, A. S. S., & Dalvie, D. (2012) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2012.688744 · Cited by 169 · see citing works
Jöst, C., Nitsche, C., Scholz, T., Roux, L., & Klein, C. D. P. (2014) · Journal of Medicinal Chemistry · doi:10.1021/jm5006918 · Cited by 167 · see citing works
Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls
Kumalo, H., Bhakat, S., & Soliman, M. (2015) · Molecules · doi:10.3390/molecules20021984 · Cited by 158 · see citing works
Structure-Based Virtual Screening Approach for Discovery of Covalently Bound Ligands
Warshaviak, D. T., Golan, G., Borrelli, K. W., Zhu, K., & Kalid, O. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci500175r · Cited by 155 · see citing works
Krenske, E. H., Petter, R. C., & Houk, K. N. (2016) · The Journal of Organic Chemistry · doi:10.1021/acs.joc.6b02188 · Cited by 152 · see citing works
Molecular simulation of nonfacilitated membrane permeation
Awoonor‐Williams, E., & Rowley, C. N. (2015) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2015.12.014 · Cited by 142 · see citing works
Ouyang, X., Zhou, S., Su, C. T. T., Ge, Z., Li, R., & Kwoh, C. K. (2013) · Journal of Computational Chemistry · doi:10.1002/jcc.23136 · Cited by 134 · see citing works
Determining Cysteines Available for Covalent Inhibition Across the Human Kinome
Zhao, Z., Liu, Q., Bliven, S. E., Xie, L., & Bourne, P. E. (2017) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.6b01815 · Cited by 126 · see citing works
Evaluation of Methods for the Calculation of the p K a of Cysteine Residues in Proteins
Awoonor‐Williams, E., & Rowley, C. N. (2016) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b00631 · Cited by 115 · see citing works
The Importance of Being Inconsistent
Wasserman, A., Nafziger, J., Jiang, K., Kim, M. C., Sim, E., & Burke, K. (2017) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-052516-044957 · Cited by 114 · see citing works
Olsson, M. H. M., Mavri, J., & Warshel, A. (2006) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2006.1880 · Cited by 108 · see citing works
Corbeil, C. R., & Moitessier, N. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci8004176 · Cited by 107 · see citing works
A Classical Enzyme Active Center Motif Lacks Catalytic Competence until Modulated Electrostatically
Pinitglang, S., Watts, A. B., Patel, M., Reid, J. D., Noble, M. A., Gul, S., Bokth, A., Naeem, A., Patel, H., Thomas, E. W., et al. (1997) · Biochemistry · doi:10.1021/bi9705974 · Cited by 99 · see citing works
Ma, S., Devi-Kesavan, L. S., & Gao, J. (2007) · Journal of the American Chemical Society · doi:10.1021/ja074222+ · Cited by 92 · see citing works
Quantum Chemical-Based Protocol for the Rational Design of Covalent Inhibitors
Schirmeister, T., Kesselring, J., Jung, S., Schneider, T. H., Weickert, A., Becker, J., Lee, W., Bamberger, D., Wich, P. R., Distler, U., et al. (2016) · Journal of the American Chemical Society · doi:10.1021/jacs.6b03052 · Cited by 89 · see citing works
Krenske, E. H., Petter, R. C., Zhu, Z., & Houk, K. N. (2011) · The Journal of Organic Chemistry · doi:10.1021/jo200761w · Cited by 86 · see citing works
Reversible Michael Additions: Covalent Inhibitors and Prodrugs
Johansson, M. H. (2012) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/13895575112091330 · Cited by 85 · see citing works
Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods
Moitessier, N., Pottel, J., Therrien, É., Englebienne, P., Liu, Z., Tomberg, A., & Corbeil, C. R. (2016) · Accounts of Chemical Research · doi:10.1021/acs.accounts.6b00185 · Cited by 77 · see citing works
Range-Separated DFT Functionals are Necessary to Model Thio-Michael Additions
Smith, J. M. B., Jami‐Alahmadi, Y., & Rowley, C. N. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct400773k · Cited by 75 · see citing works
Tóth, L. F., Muszbek, L., & Komáromi, I. (2013) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2012.12.013 · Cited by 67 · see citing works
Riahi, S., & Rowley, C. N. (2014) · Journal of Computational Chemistry · doi:10.1002/jcc.23716 · Cited by 67 · see citing works
Mladenović, M., Fink, R. F., Thiel, W., Schirmeister, T., & Engels, B. (2008) · Journal of the American Chemical Society · doi:10.1021/ja711043x · Cited by 66 · see citing works
Aziridide‐Based Inhibitors of Cathepsin L: Synthesis, Inhibition Activity, and Docking Studies
Vičík, R., Busemann, M., Gelhaus, C., Stiefl, N., Scheiber, J., Schmitz, W., Schulz, F., Mladenović, M., Engels, B., Leippe, M., et al. (2006) · ChemMedChem · doi:10.1002/cmdc.200600106 · Cited by 58 · see citing works
Cesco, S. D., Deslandes, S., Therrien, É., Levan, D., Cueto, M., Schmidt, R., Cantin, L., Mittermaier, A., Juillerat‐Jeanneret, L., & Moitessier, N. (2012) · Journal of Medicinal Chemistry · doi:10.1021/jm3002839 · Cited by 55 · see citing works
Paasche, A., Schirmeister, T., & Engels, B. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct301082y · Cited by 52 · see citing works
Ai, Y.-B., Yu, L.-L., Tan, X., Chai, X., & Liu, S. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00334 · Cited by 52 · see citing works
Wu, S., Luo, H., Wang, H., Zhao, W., Hu, Q., & Yang, Y. (2016) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2016.08.109 · Cited by 52 · see citing works
Dipeptidyl Nitroalkenes as Potent Reversible Inhibitors of Cysteine Proteases Rhodesain and Cruzain
Latorre, A., Schirmeister, T., Kesselring, J., Jung, S., Johé, P., Hellmich, U. A., Heilos, A., Engels, B., Krauth‐Siegel, R. L., Dirdjaja, N., et al. (2016) · ACS Medicinal Chemistry Letters · doi:10.1021/acsmedchemlett.6b00276 · Cited by 51 · see citing works
Lawandi, J., Toumieux, S., Seyer, V., Campbell, P. D., Thielges, S., Juillerat‐Jeanneret, L., & Moitessier, N. (2009) · Journal of Medicinal Chemistry · doi:10.1021/jm901013a · Cited by 49 · see citing works
Fanfrlík, J., Brahmkshatriya, P. S., Řezáč, J., Jílková, A., Horn, M., Mares, M. A., Hobza, P., & Lepšı́k, M. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp409604n · Cited by 47 · see citing works
Mladenović, M., Junold, K., Fink, R. F., Thiel, W., Schirmeister, T., & Engels, B. (2008) · The Journal of Physical Chemistry B · doi:10.1021/jp711287c · Cited by 45 · see citing works
Mladenović, M., Ansorg, K., Fink, R. F., Thiel, W., Schirmeister, T., & Engels, B. (2008) · The Journal of Physical Chemistry B · doi:10.1021/jp803895f · Cited by 44 · see citing works
Zhao, Z., Xie, L., Xie, L., & Bourne, P. E. (2016) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b02041 · Cited by 42 · see citing works
Vičík, R., Helten, H., Schirmeister, T., & Engels, B. (2006) · ChemMedChem · doi:10.1002/cmdc.200600081 · Cited by 40 · see citing works
Mladenović, M., Schirmeister, T., Thiel, S., Thiel, W., & Engels, B. (2006) · ChemMedChem · doi:10.1002/cmdc.200600159 · Cited by 38 · see citing works
Schirmeister, T., Schmitz, J., Jung, S., Schmenger, T., Krauth‐Siegel, R. L., & Gütschow, M. (2016) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2016.11.036 · Cited by 38 · see citing works
Mechanistic Insights into Cyclooxygenase Irreversible Inactivation by Aspirin
Tosco, P., & Lazzarato, L. (2009) · ChemMedChem · doi:10.1002/cmdc.200800438 · Cited by 36 · see citing works
CovalentDock Cloud: a web server for automated covalent docking
Ouyang, X., Zhou, S., Ge, Z., Li, R., & Kwoh, C. K. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt406 · Cited by 31 · see citing works
The mechanism of papain inhibition by peptidyl aldehydes
Shokhen, M., Khazanov, N., & Albeck, A. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22939 · Cited by 26 · see citing works
Automated computational screening of the thiol reactivity of substituted alkenes
Smith, J. M. B., & Rowley, C. N. (2015) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-015-9857-0 · Cited by 25 · see citing works
Mariaule, G., Cesco, S. D., Airaghi, F., Kurian, J., Schiavini, P., Rocheleau, S., Huskić, I., Auclair, K., Mittermaier, A., & Moitessier, N. (2015) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b01296 · Cited by 25 · see citing works
Unsupervised guided docking of covalently bound ligands
Fradera, X., Kaur, J., & Mestres, J. (2004) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-004-5291-4 · Cited by 24 · see citing works
Rational Design of Improved Aziridine-Based Inhibitors of Cysteine Proteases
Buback, V., Mladenović, M., Engels, B., & Schirmeister, T. (2009) · The Journal of Physical Chemistry B · doi:10.1021/jp810549n · Cited by 23 · see citing works
Arafet, K., Ferrer, S., Martı́, S., & Moliner, V. (2014) · Biochemistry · doi:10.1021/bi500060h · Cited by 22 · see citing works
An explicit-solvent conformation search method using open software
Gaalswyk, K., & Rowley, C. N. (2016) · PeerJ · doi:10.7717/peerj.2088 · Cited by 13 · see citing works
A computational workflow for the design of irreversible inhibitors of protein kinases
Río, A. D., Sgobba, M., Parenti, M. D., Degliesposti, G., Forestiero, R., Percivalle, C., Conte, P., Freccero, M., & Rastelli, G. (2010) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-010-9324-x · Cited by 11 · see citing works
Flagged first, then by citations
1 of the 101 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Structure-based design of targeted covalent inhibitors
Lonsdale, R., & Ward, R. A. (2018) · Chemical Society Reviews · doi:10.1039/c7cs00220c · Cited by 344 · see citing works
Guedes, I. A., Pereira, F. S. S., & Dardenne, L. E. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.01089 · Cited by 331 · see citing works
Fibroblast Growth Factor Receptors (FGFRs): Structures and Small Molecule Inhibitors
Dai, S., Zhou, Z. M., Chen, Z., Xu, G., & Chen, Y. (2019) · Cells · doi:10.3390/cells8060614 · Cited by 297 · see citing works
Covalent Inhibition in Drug Discovery
Ghosh, A. K., Samanta, I., Mondal, A., & Liu, W. R. (2019) · ChemMedChem · doi:10.1002/cmdc.201900107 · Cited by 265 · see citing works
Progress with covalent small-molecule kinase inhibitors
Zhao, Z., & Bourne, P. E. (2018) · Drug Discovery Today · doi:10.1016/j.drudis.2018.01.035 · Cited by 200 · see citing works
Monica, G. L., Bono, A., Lauria, A., & Martorana, A. (2022) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.2c01005 · Cited by 168 · see citing works
Arafet, K., Serrano-Aparicio, N., Lodola, A., Mulholland, A. J., González, F. V., Świderek, K., & Moliner, V. (2020) · Chemical Science · doi:10.1039/d0sc06195f · Cited by 138 · see citing works
Acoplamiento Molecular: Avances Recientes y Retos
Prieto-Martínez, F. D., Arciniega, M., & Medina‐Franco, J. L. (2018) · TIP Revista Especializada en Ciencias Químico-Biológicas · doi:10.22201/fesz.23958723e.2018.0.143 · Cited by 126 · see citing works
Nitriles: an attractive approach to the development of covalent inhibitors
Bonatto, V., Lameiro, R. F., Rocho, F. D. R., Lameira, J., Leitão, A., & Montanari, C. A. (2022) · RSC Medicinal Chemistry · doi:10.1039/d2md00204c · Cited by 119 · see citing works
Polarisable force fields: what do they add in biomolecular simulations?
Inakollu, V. S. S., Geerke, D. P., Rowley, C. N., & Yu, H. B. (2020) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2019.12.012 · Cited by 88 · see citing works
The expanding repertoire of covalent warheads for drug discovery
Mehta, N. V., & Degani, M. S. (2023) · Drug Discovery Today · doi:10.1016/j.drudis.2023.103799 · Cited by 72 · see citing works
Development of covalent inhibitors: Principle, design, and application in cancer
Zheng, L., Li, Y., Wu, D., Xiao, H., Zheng, S., Wang, G., & Sun, Q. (2023) · MedComm – Oncology · doi:10.1002/mog2.56 · Cited by 71 · see citing works
Docking of Covalent Ligands: Challenges and Approaches
Sotriffer, C. (2018) · Molecular Informatics · doi:10.1002/minf.201800062 · Cited by 61 · see citing works
Can Relative Binding Free Energy Predict Selectivity of Reversible Covalent Inhibitors?
Chatterjee, P., Botello‐Smith, W. M., Zhang, H., Qian, L., Alsamarah, A., Kent, D., Lacroix, J. J., Baudry, M., & Luo, Y. (2017) · Journal of the American Chemical Society · doi:10.1021/jacs.7b08938 · Cited by 61 · see citing works
Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease
Pavlova, À., Lynch, D. L., Daidone, I., Polzi, L. Z., Smith, M. D., Chipot, C. J., Kneller, D. W., Kovalevsky, A. Y., Coates, L., Golosov, A. A., et al. (2020) · Chemical Science · doi:10.1039/d0sc04942e · Cited by 59 · see citing works
Silva, L. R., Guimarães, A. S., do Nascimento, J., Nascimento, I. J. D. S., da Silva, E. B., McKerrow, J. H., Cardoso, S. H., & da Silva‐Júnior, E. F. (2021) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2021.116213 · Cited by 57 · see citing works
How Reactive are Druggable Cysteines in Protein Kinases?
Awoonor‐Williams, E., & Rowley, C. N. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00454 · Cited by 57 · see citing works
Drug design targeting active posttranslational modification protein isoforms
Meng, F., Liang, Z. T., Zhao, K., & Luo, C. (2020) · Medicinal Research Reviews · doi:10.1002/med.21774 · Cited by 56 · see citing works
Voice, A. T., Tresadern, G., Twidale, R. M., van Vlijmen, H., & Mulholland, A. J. (2021) · Chemical Science · doi:10.1039/d0sc06122k · Cited by 55 · see citing works
Ranking Reversible Covalent Drugs: From Free Energy Perturbation to Fragment Docking
Zhang, H., Jiang, W., Chatterjee, P., & Luo, Y. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00959 · Cited by 51 · see citing works
Reactivity of Covalent Fragments and Their Role in Fragment Based Drug Discovery
McAulay, K., Bilsland, A. E., & Bon, M. (2022) · Pharmaceuticals · doi:10.3390/ph15111366 · Cited by 50 · see citing works
Bum‐Erdene, K., Liu, D., González-Gutiérrez, G., Ghozayel, M. K., Xu, D. D., & Meroueh, S. O. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1913654117 · Cited by 49 · see citing works
Quantum Chemical Methods for Modeling Covalent Modification of Biological Thiols
Awoonor‐Williams, E., Isley, W. C., Dale, S. G., Johnson, E. R., Yu, H. B., Becke, A. D., Roux, B., & Rowley, C. N. (2019) · Journal of Computational Chemistry · doi:10.1002/jcc.26064 · Cited by 49 · see citing works
Petri, L., Egyed, A., Bajusz, D., Imre, T., Hetényi, A., Martinek, T. A., Ábrányi‐Balogh, P., & Keserű, G. M. (2020) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2020.112836 · Cited by 49 · see citing works
Silva, J. R. A., Cianni, L., de Araújo, D. G. P. G., Batista, P. H. J., Vita, D. D., Rosini, F., Leitão, A., Lameira, J., & Montanari, C. A. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b01138 · Cited by 47 · see citing works
Awoonor‐Williams, E., & Abu‐Saleh, A. A. A. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d1cp00266j · Cited by 46 · see citing works
The role of quantum chemistry in covalent inhibitor design
Mihalovits, L. M., Ferenczy, G. G., & Keserű, G. M. (2021) · International Journal of Quantum Chemistry · doi:10.1002/qua.26768 · Cited by 45 · see citing works
Harris, R. C., Liu, R., & Shen, J. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.0c00258 · Cited by 45 · see citing works
CHARMM-GUI PDB Reader and Manipulator: Covalent Ligand Modeling and Simulation
Kong, L., Park, S., & Im, W. (2024) · Journal of Molecular Biology · doi:10.1016/j.jmb.2024.168554 · Cited by 45 · see citing works
Covalent binders in drug discovery
Vasudevan, A., Argiriadi, M. A., Baranczak, A., Friedman, M., Gavrilyuk, J. I., Hobson, A. D., Hulce, J. J., Osman, S., & Wilson, N. S. (2019) · Progress in medicinal chemistry · doi:10.1016/bs.pmch.2018.12.002 · Cited by 42 · see citing works
Bianco, G., Goodsell, D. S., & Forli, S. (2020) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2020.10.005 · Cited by 39 · see citing works
Reversible Covalent Inhibition─Desired Covalent Adduct Formation by Mass Action
Patel, D., Huma, Z. E., & Duncan, D. (2024) · ACS Chemical Biology · doi:10.1021/acschembio.3c00805 · Cited by 40 · see citing works
Mohapatra, P. K., Chopdar, K. S., Dash, G. C., Mohanty, A. K., & Raval, M. K. (2021) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2021.2007170 · Cited by 40 · see citing works
Structure-Based Engineering of Irreversible Inhibitors against Histone Lysine Demethylase KDM5A
Horton, J. R., Woodcock, C. B., Chen, Q., Liu, X., Zhang, X., Shanks, J. R., Rai, G., Mott, B. T., Jansen, D. J., Kales, S. C., et al. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b01219 · Cited by 37 · see citing works
Awoonor‐Williams, E., & Rowley, C. N. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c00897 · Cited by 36 · see citing works
Lameira, J., Bonatto, V., Cianni, L., Rocho, F. D. R., Leitão, A., & Montanari, C. A. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp04820k · Cited by 35 · see citing works
Structural characterization of dicyanopyridine containing DNMT1-selective, non-nucleoside inhibitors
Horton, J. R., Pathuri, S., Wong, K., Ren, R., Rueda, L., Fosbenner, D. T., Heerding, D. A., McCabe, M. T., Pappalardi, M. B., Zhang, X., et al. (2022) · Structure · doi:10.1016/j.str.2022.03.009 · Cited by 34 · see citing works
Polzi, L. Z., Smith, M. D., Chipot, C. J., Gumbart, J. C., Lynch, D. L., Pavlova, À., Smith, J. C., & Daidone, I. (2021) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.1c00425 · Cited by 32 · see citing works
Mechanistic aspects of thiol additions to Michael acceptors: Insights from computations
Roseli, R. B., Keto, A. B., & Krenske, E. H. (2022) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1636 · Cited by 32 · see citing works
Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors
da Costa, C. H. S., Bonatto, V., dos Santos, A. M., Lameira, J., Leitão, A., & Montanari, C. A. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00847 · Cited by 28 · see citing works
Benchmarking In Silico Tools for Cysteine p K a Prediction
Awoonor‐Williams, E., Golosov, A. A., & Horn̆ák, V. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00004 · Cited by 28 · see citing works
The hydration structure of methylthiolate from QM/MM molecular dynamics
Awoonor‐Williams, E., & Rowley, C. N. (2018) · The Journal of Chemical Physics · doi:10.1063/1.5038010 · Cited by 23 · see citing works
Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations
Lodola, A., Callegari, D., Scalvini, L., Rivara, S., & Mor, M. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0282-9_19 · Cited by 22 · see citing works
User-Friendly Quantum Mechanics: Applications for Drug Discovery
Kotev, M. I., Sarrat, L., & Gonzalez, C. D. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0282-9_15 · Cited by 22 · see citing works
Meden, A., Knez, D., Brazzolotto, X., Modeste, F., Perdih, A., Pišlar, A. H., Zorman, M., Zorović, M., Denic, M., Pajk, S., et al. (2022) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2022.115048 · Cited by 22 · see citing works
Covalent-Allosteric Inhibitors: Do We Get the Best of Both Worlds?
Tao, H., Yang, B., Farhangian, A., Xu, K., Li, T., Zhang, Z., & Li, J. (2025) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.4c02760 · Cited by 21 · see citing works
Khan, S., Bjij, I., Olotu, F. A., Agoni, C., Adeniji, E. A., & Soliman, M. E. S. (2018) · Future Medicinal Chemistry · doi:10.4155/fmc-2017-0304 · Cited by 20 · see citing works
Mechanism-Based and Computational-Driven Covalent Drug Design
Luo, Y. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c01278 · Cited by 20 · see citing works
Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease
Pavlova, À., Lynch, D. L., Diadone, I., Polzi, L. Z., Smith, M. D., Chipot, C. J., Kneller, D. W., Kovalevsky, A. Y., Coates, L., Velez‐Vega, C., et al. (2021) · The Novartis Repository (Novartis) · Cited by 19 · see citing works
Limitations of Ligand-Only Approaches for Predicting the Reactivity of Covalent Inhibitors
Voice, A. T., Tresadern, G., van Vlijmen, H., & Mulholland, A. J. (2019) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b00404 · Cited by 19 · see citing works
Drug repurposing for schistosomiasis: molecular docking and dynamics investigations
Ezebuo, F. C., & Uzochukwu, I. C. (2020) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2020.1820382 · Cited by 18 · see citing works
Inhibition of metabolic cooperation in Chinese hamster cells by organochlorine pesticides.
Kurata, M., Hirose, K., & Umeda, M. (1982) · PubMed · Cited by 18 · see citing works
Exploiting Cysteine Residues of SLC Membrane Transporters as Targets for Drugs
Scalise, M., Console, L., Galluccio, M., Pochini, L., Tonazzi, A., Giangregorio, N., & Indiveri, C. (2019) · SLAS DISCOVERY · doi:10.1177/2472555219856601 · Cited by 15 · see citing works
Bai, M., Dai, J., Hu, W., Li, C., Cui, H., & Lin, L. (2023) · Food Bioscience · doi:10.1016/j.fbio.2023.103137 · Cited by 13 · see citing works
Reimer, B. M., Awoonor‐Williams, E., Golosov, A. A., & Horn̆ák, V. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01281 · Cited by 13 · see citing works
Stein, A., Thomopoulou, P. H. N., Frias, C., Pütz, S. M., Varela, P. F., Wilke, N. L., Mariappan, A., Neudörfl, J., Fedorov, A. Y., Gopalakrishnan, J., et al. (2022) · ACS Omega · doi:10.1021/acsomega.1c04659 · Cited by 13 · see citing works
Arafet, K., Royo, S., Schirmeister, T., Barthels, F., González, F. V., & Moliner, V. (2023) · ACS Catalysis · doi:10.1021/acscatal.3c01035 · Cited by 11 · see citing works
Discovery of nonnucleoside inhibitors of polymerase from infectious pancreatic necrosis virus (IPNV)
Belló-Pérez, M., Falcó, A., Galiano, V., Coll, J. M., Pérez, L., & Encinar, J. A. (2018) · Drug Design Development and Therapy · doi:10.2147/dddt.s171087 · Cited by 11 · see citing works
Calculating the Energy Profile of an Enzymatic Reaction on a Quantum Computer
Ettenhuber, P., Hansen, M. B., Poier, P. P., Shaik, I., Rasmussen, S. E., Madsen, N. K., Majland, M., Jensen, F., Olsen, L., & Zinner, N. T. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5c00022 · Cited by 10 · see citing works
Janero, D. R., Korde, A., & Makriyannis, A. (2017) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2017.06.022 · Cited by 10 · see citing works
Reversible Covalent Reaction of Levosimendan with Cardiac Troponin C in Vitro and in Situ
Klein, B. A., Reiz, B., Robertson, I. M., Irving, M., Li, L., Sun, Y., & Sykes, B. D. (2018) · Biochemistry · doi:10.1021/acs.biochem.8b00109 · Cited by 10 · see citing works
Awoonor‐Williams, E., & Abu‐Saleh, A. A. A. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c00310 · Cited by 8 · see citing works
Graph neural networks for identifying protein-reactive compounds
Gil, V., & Rowley, C. N. (2024) · Digital Discovery · doi:10.1039/d4dd00038b · Cited by 8 · see citing works
Awoonor‐Williams, E. (2022) · Physical Chemistry Chemical Physics · doi:10.1039/d2cp03080b · Cited by 8 · see citing works
Xu, L., & Coote, M. L. (2022) · Annual reports in computational chemistry · doi:10.1016/bs.arcc.2022.09.001 · Cited by 7 · see citing works
Danilack, A. D., Dickson, C. J., Soylu, C., Fortunato, M., Rodde, S., Münkler, H., Horn̆ák, V., & Duca, J. S. (2024) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-024-00560-6 · Cited by 7 · see citing works
Self‐Immolation of a Bacterial Dehydratase Enzyme by its Epoxide Product
Lence, E., Maneiro, M., Sanz‐Gaitero, M., van Raaij, M. J., Thompson, P., Hawkins, A. R., & González‐Bello, C. (2020) · Chemistry - A European Journal · doi:10.1002/chem.202000759 · Cited by 7 · see citing works
Measuring and predicting warhead and residue reactivity
Awoonor‐Williams, E., Kennedy, J., & Rowley, C. N. (2020) · Annual reports in medicinal chemistry · doi:10.1016/bs.armc.2020.09.001 · Cited by 7 · see citing works
Adeniji, E. A., Olotu, F. A., & Soliman, M. E. S. (2018) · Anti-Cancer Agents in Medicinal Chemistry · doi:10.2174/1871520618666180718110231 · Cited by 7 · see citing works
Yuan, X., Hou, Y., Qin, N., Xiang, L., Jiang, Z., & Bao, X. (2025) · Food & Function · doi:10.1039/d4fo04478a · Cited by 6 · see citing works
Kinetic Modeling of Covalent Inhibition: Effects of Rapidly Fluctuating Intermediate States
Ghaby, K., & Roux, B. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00952 · Cited by 6 · see citing works
Free Energy Perturbation and Free-Energy Calculations Applied to Drug Design
Antunes, D., Santos, L. H., Guimarães, A. C. R., & Caffarena, E. R. (2024) · Computer-aided drug discovery and design · doi:10.1007/978-3-031-76718-0_10 · Cited by 5 · see citing works
Road Map for the Structure-Based Design of Selective Covalent HCV NS3/4A Protease Inhibitors
Shunmugam, L., Ramharack, P., & Soliman, M. E. S. (2017) · The Protein Journal · doi:10.1007/s10930-017-9736-8 · Cited by 5 · see citing works
Polzi, L. Z., Smith, M. D., Chipot, C. J., Gumbart, J. C., Lynch, D. L., Pavlova, A., Smith, J. C., & Daidone, I. (2020) · ChemRxiv · doi:10.26434/chemrxiv.13200227 · Cited by 5 · see citing works
Effect of a primer containing Artemisinin on dentin endogenous MMPs and resin bond durability
Ding, Y., Li, Q., Tang, W., Pan, Y., Nie, R., & Meng, X. (2023) · International Journal of Adhesion and Adhesives · doi:10.1016/j.ijadhadh.2023.103340 · Cited by 4 · see citing works
Hou, H.-P., Liu, X., Liu, W., Zhang, P., & Zhou, B. (2025) · Medical Oncology · doi:10.1007/s12032-025-02699-0 · Cited by 3 · see citing works
Targeting protein–protein interactions with reversible covalent modalities: Non‐cysteine chemistries
Basu, R., & Fletcher, S. (2026) · British Journal of Pharmacology · doi:10.1111/bph.70377 · Cited by 3 · see citing works
Thermodynamic characterisation of covalent ligand binding
Hertzman, R., Lavie, M., Nadir, A., Gabizon, R., & London, N. (2026) · British Journal of Pharmacology · doi:10.1111/bph.70574 · Cited by 2 · see citing works
Gayatri, S. K., Chhabra, V., Kumar, H., & Sobhia, M. E. (2022) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2022.2129453 · Cited by 2 · see citing works
Sirtuin 3 as a promising target in disease therapy: Model action and drug discovery
Yu, D. (2025) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2025.117929 · Cited by 2 · see citing works
Targeting enzymes with covalent warheads: Beyond cysteine
Patel, D., Sharma, A., & Duncan, D. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29808-0.00064-9 · Cited by 1 · see citing works
Molecular Dynamics-Guided Design and Chemoproteomic Profiling of Covalent Kinase Activity Probes
Chakraborty, P., Carlos, A. J., Thomas, T., Ghaby, K., Fathi, S., Sharma, M., Nguyen, N. K., Farmwald, M., Blachowicz, L., Alcyone, E., et al. (2026) · Journal of the American Chemical Society · doi:10.1021/jacs.5c18691 · Cited by 1 · see citing works
Computational support of structure-based targeted covalent inhibitor design
Abel, R., & Friesner, R. A. (2021) · Annual reports in medicinal chemistry · doi:10.1016/bs.armc.2021.01.001 · Cited by 1 · see citing works
Modeling Covalent Protein-Ligand Interactions
Ward, R. A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11519-3
Meden, A., Knez, D., Brazzolotto, X., Modeste, F., Perdih, A., Pišlar, A. H., Zorman, M., Denic, M., Pajk, S., Nachon, F., et al. (2022) · ChemRxiv · doi:10.26434/chemrxiv-2022-msbb4
Molecular Dynamics-Guided Design and Chemoproteomic Profiling of Covalent Kinase Activity ProbesPreprint
Chakraborty, P., Carlos, A. J., Thomas, T., Ghaby, K., Fathi, S., Sharma, M., Nguyen, N. K., Farmwald, M., Blachowicz, L., Yu, S., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.17.683178
Kanwal, S., Saeed, A., Tahir, A., Shah, M. R., Hussain, F., Yaqoob, M., Zheng, H., Ikram, M., Hassan, A., & Rashid, U. (2026) · Bioorganic Chemistry · doi:10.1016/j.bioorg.2026.109664
CHARMM-GUI Covalent Ligand Docker as a Web-Based Molecular Docking Platform for Covalent Ligands
Kong, L., Suh, D., & Im, W. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c02343
BindingDB Entry 50023438: Covalent-Allosteric Inhibitors: Do We Get the Best of Both Worlds?
BindingDB (2026) · UC San Diego · doi:10.7270/q2h136xb
- Authors
- Awoonor-Williams, E., Walsh, A. G., & Rowley, C. N.
- Affiliations
- Memorial University of Newfoundland (CA)
- Corresponding author
- Rowley, Christopher N.
- Venue
- Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 1865
- Issue
- 11
- Pages
- 1664-1675
- ISSN
- 1570-9639 (ISSN-L)
- OpenAlex
- W2598528124
- Cited by
- 90
- References
- 101
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 7 · 2023: 6 · 2022: 11 · 2021: 10 · 2020: 16 · 2019: 9 · 2018: 12 · 2017: 3
- FWCI
- 1.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- NSERC of Canada (418505-2012)
- Memorial University
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
- Physical Sciences › Chemistry › Organic Chemistry › Click Chemistry and Applications
- Keywords
- targeted covalent inhibitors, covalent binding, protein-ligand docking, binding pose prediction, pKa prediction, QM/MM, drug selectivity, irreversible inhibition
- MeSH terms
- Adenine, Models, Molecular, Penicillins, Piperidines, Pyrazoles, Pyrimidines, Drug Discovery
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
