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QM/MM dynamics of chymotrypsin

From EverybodyWiki Bios & Wiki

Chymotrypsin is a prime example of a serine protease, a type of enzyme that catalyzes the breakdown of peptide bonds. [1][2][3] The chemical reaction, which involves bond breaking and forming in a vast protein environment, is ideal for study utilizing Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics. [4][5][6] This hybrid technique is especially useful for researching enzyme catalysis because it provides for a thorough, atomistic description of bond-breaking and bond-forming events (managed by QM) inside the complicated electrostatic and steric/dynamic environment of the protein and solvent (managed by MM). [7] The use of QM/MM dynamics simulation on chymotrypsin has proved useful in confirming and improving the suggested catalytic mechanism, offering insights that would be difficult or impossible to get through experimental means alone. [8][9][10]

File:Chymotrypsin.png
Chymotrypsin

Background

The Catalytic reaction Mechanism

Chymotrypsin catalyzes the hydrolysis of peptide bonds, specifically at the carboxyl end of aromatic amino acids such as phenylalanine, tyrosine, and tryptophan.[11][12] The widely accepted catalytic mechanism involves a catalytic triad (Ser195, His57, Asp102)[13] and proceeds through a two-step process (acylation and deacylation) involving an acyl-enzyme intermediate:[14][15] In acylation, the Ser195 attacks the carbonyl carbon of the substrate, creating a tetrahedral intermediate. This intermediate is stabilized by hydrogen bonds from the oxyanion hole and then collapses, releasing the amine part of the substrate while covalently attaching the acyl portion to Ser195.[16] In deacylation, His57 activates a water molecule, which attacks the acyl-enzyme carbonyl to form a second tetrahedral intermediate. This intermediate then collapses, releasing the carboxylic acid product and restoring the free serine at the active site. [17] Therefore, the introduction of QM/MM molecular dynamics simulation has allowed for a deeper understanding of how enzyme structure and dynamics contribute to catalysis.[18][19]

Principles of QM/MM Molecular Dynamics Simulation

QM/MM is a multi-scale computational technique that splits a large molecular system into two regions to balance the computational efficiency with chemical accuracy: [20]

QM region: In QM/MM, only the directly reactive part of the system is treated quantum‑mechanically, typically the catalytic triad (Ser195, His57, Asp102) together with the scissile peptide bond of the substrate, where bonds are broken and formed using high‑level methods such as DFT or semi‑empirical QM. [21]

MM region: In QM/MM simulations, the remainder of the system, most of the protein, surrounding water, and counterions, is treated with faster, empirical MM force fields such as CHARMM, AMBER, or OPLS.[22]

Molecular Dynamics (MD): The simulation can investigate the dynamic (time-dependent) behavior of the system at biologically relevant temperatures by coupling QM/MM with MD (QM/MM/MD). [23][24] This is crucial for calculating the reaction free energy profile and identifying the thermal fluctuations that facilitate catalysis. [25] The dynamics are often performed using Born–Oppenheimer or Car–Parrinello molecular dynamics methods. [26][27][28][29]

CHARMM-GUI can be used to generate both MD and QM/MM protocols by interactively building complex systems and preparing their input files with well-established, reproducible simulation workflows for state-of-the-art molecular simulations using widely used simulation packages such as CHARMM, NAMD, GROMACS, AMBER, LAMMPS, and OpenMM. [30]. To perform the QM/MM calculation in CHARMM-GUI, first prepare the chymotrypsin topology using the PDB Reader & Manipulator → Solution Builder (for the enzyme in water), and then use the QM/MM Interfacer to define and set up the QM/MM region. [31][32]

1. Acylation Phase (First Hydrolysis Step)

During the acylation phase, Ser195 (activated by His57) attacks the substrate carbonyl (nucleophilic attack) to form a high‑energy first transition state (TS1) and then a stabilized tetrahedral intermediate (INT1) in the oxyanion hole. INT1 collapses as His57 donates a proton to the leaving group nitrogen, cleaving the peptide bond, releasing the C‑terminal product, and leaving a covalent acyl‑enzyme intermediate on Ser195.[1]

Step Molecular Event Modeled by QM/MM Key Energetic Feature
Nucleophilic Attack The Oγ of Ser 195, activated by proton transfer to His 57, performs a nucleophilic attack on the carbonyl carbon (C) of the substrate. Transition State 1 (TS1):The rate determining step of the reaction.
Tetrahedral Intermediate 1 (TI1) The carbonyl O atom becomes negatively charged (the oxy-anion). The QM/MM calculation shows the crucial stabilization of this charge by N-H groups in the oxyanion hole (primarily from Gly 193 and Ser 195 backbone amides). Intermediate 1 (INT1): A meta-stable, relatively low-energy state due to oxyanion stabilization.
Peptide Bond Cleavage The protonated His 57 acts as a general acid, transferring its proton to the leaving group (the N atom of the peptide bond), facilitating the release of the C-terminal product. Acyl-Enzyme: The final stable covalent intermediate before the second half of the reaction.

2. Deacylation Phase (Second Hydrolysis Step)

In the deacylation phase, His57 activates a water molecule to attack the acyl-enzyme, forming a second tetrahedral intermediate (TI2) stabilized in the oxyanion hole through TS2. TI2 then collapses, releasing the N-terminal product and regenerating active Ser195-OH.


This is the hydrolysis of the acyl-enzyme intermediate and the regeneration of the active enzyme.[2]

Step Molecular Event Modeled by QM/MM Key Energetic Feature
Water Activation A water molecule (H2O) enters the active site, and a proton is extracted by the His 57 residue, forming a potent hydroxide nucleophile (OH-). Transition State 2 (TS2): The nucleophilic attack of the water/hydroxide on the acyl-enzyme.
Tetrahedral Intermediate 2 (TI2) Formation of the second oxyanion intermediate, again stabilized by the oxyanion hole. Intermediate 2 (INT2): Second meta-stable state.
Enzyme Regeneration The final intermediate collapses, regenerating the active Ser 195-OH and releasing the final product (the N-terminal fragment, now with a carboxylate group). Enzyme Regeneration: Return to the original, resting state of the enzyme.

Key Applications and Insights

QM/MM dynamics simulations have been applied to chymotrypsin to address several fundamental questions about its function:

1. Energetics and Reaction Pathway

Free Energy Profiles (potential of mean force): QM/MM calculations provide the most accurate theoretical values for the activation energy(ΔG‡) of the key reaction steps. Studies on chymotrypsin generally find that the acylation step is the rate-limiting step for good substrates, but the energy barrier for the formation of the tetrahedral intermediate is significantly lower than that for the uncatalyzed reaction, highlighting the power of enzymatic transition state stabilization.[33][34]

2. The Nature of the Transition State and Oxyanion Hole

QM/MM studies have provided atomic-level detail of the transition state structures. A key finding is the critical role of the oxyanion hole (primarily backbone amides of Gly193 and Ser195) in stabilizing the negatively charged oxyanion that develops on the substrate's carbonyl oxygen in the tetrahedral intermediate and transition states.[35] The simulations quantify the strong hydrogen-bonding interactions that provide this stabilization, significantly lowering the reaction barrier.[36][37]

3. The Role of the Catalytic Triad

The simulations have visualized the proton transfer events within the catalytic triad (Ser195-His57-Asp102). They support a "charge-relay" mechanism where Asp102 orientates and polarizes His57, which in turn acts as a general base to deprotonate Ser195, enhancing its nucleophilicity. The dynamics show that this proton transfer is coupled with the nucleophilic attack and is facilitated by the protein environment.[38][39]

4. Substrate Specificity and Solvent Effects

By simulating chymotrypsin with different substrates, QM/MM dynamics can elucidate the structural basis for its specificity. The simulations show how the enzyme's S1 binding pocket optimally accommodates large, hydrophobic side chains. Furthermore, the treatment of the MM environment includes the dynamic effects of solvent water and the protein's flexibility, demonstrating how the active site is pre-organized and shielded from bulk solvent to facilitate the reaction.[40][41]

These studies have confirmed that electrostatic preorganization and active-site flexibility are key contributors to chymotrypsin’s catalytic power.

Significance

The study of chymotrypsin using QM/MM dynamics stands as a landmark achievement in computational biochemistry. [42][43]

  • Provided a dynamic, atomistic validation of a mechanism previously inferred from static crystal structures and kinetics.
  • Quantified the energetic contributions of key catalytic strategies, such as transition state stabilization and general base catalysis.
  • Established QM/MM as a powerful and now standard tool for investigating enzyme mechanisms, paving the way for its application to countless other enzymatic systems.

Limitations and Challenges

Despite its success, QM/MM dynamics face several challenges:[44][45]

  • Computational cost: QM calculations are expensive for large systems.
  • QM region selection: The boundary between QM and MM regions must be chosen carefully.
  • Sampling limitations: Conventional molecular dynamics timescales may not capture rare catalytic events.
  • Continued improvements in algorithms and computational power are enabling longer and more accurate QM/MM simulations of enzyme catalysis.

See also

References

  1. ↑ "ENZYME - 3.4.21.1 chymotrypsin". enzyme.expasy.org. Retrieved 2025-11-28.
  2. ↑ Hedstrom, Lizbeth (2002-12-01). "Serine Protease Mechanism and Specificity". Chemical Reviews. 102 (12): 4501–4524. doi:10.1021/cr000033x. ISSN 0009-2665. PMID 12475199.
  3. ↑ Patra, Animesh; Samanta, Nirnay; Das, Dipak Kumar; Mitra, Rajib Kumar (2017-02-23). "Enhanced Catalytic Activity of α-Chymotrypsin in Cationic Surfactant Solutions: The Component Specificity Revisited". The Journal of Physical Chemistry B. 121 (7): 1457–1465. Bibcode:2017JPCB..121.1457P. doi:10.1021/acs.jpcb.6b10472. ISSN 1520-6106. PMID 28151666.
  4. ↑ Gisdon, Florian J.; Bombarda, Elisa; Ullmann, G. Matthias (2022-06-09). "Serine and Cysteine Peptidases: So Similar, Yet Different. How the Active-Site Electrostatics Facilitates Different Reaction Mechanisms". The Journal of Physical Chemistry B. 126 (22): 4035–4048. Bibcode:2022JPCB..126.4035G. doi:10.1021/acs.jpcb.2c01484. ISSN 1520-6106. PMID 35609250 Check |pmid= value (help).
  5. ↑ "QM/MM", Wikipedia, 2025-10-24, retrieved 2025-11-28
  6. ↑ Nutho, Bodee; Mulholland, Adrian J.; Rungrotmongkol, Thanyada (2019-04-04). "Quantum Mechanics/Molecular Mechanics (QM/MM) Calculations Support a Concerted Reaction Mechanism for the Zika Virus NS2B/NS3 Serine Protease with Its Substrate". The Journal of Physical Chemistry B. 123 (13): 2889–2903. Bibcode:2019JPCB..123.2889N. doi:10.1021/acs.jpcb.9b02157. ISSN 1520-6106. PMID 30845796.
  7. ↑ Liao, Rong-Zhen; Thiel, Walter (2012-10-09). "Comparison of QM-Only and QM/MM Models for the Mechanism of Tungsten-Dependent Acetylene Hydratase". Journal of Chemical Theory and Computation. 8 (10): 3793–3803. Bibcode:2012JCTC....8.3793L. doi:10.1021/ct3000684. ISSN 1549-9618. PMID 26593020.
  8. ↑ Kalita, Surajit; Shaik, Sason; Dubey, Kshatresh Dutta (2021-11-10). "MD simulations and QM/MM calculations reveal the key mechanistic elements which are responsible for the efficient C–H amination reaction performed by a bioengineered P450 enzyme". Chemical Science. 12 (43): 14507–14518. doi:10.1039/D1SC03489H. ISSN 2041-6539. PMC 8580044 Check |pmc= value (help). PMID 34881002 Check |pmid= value (help).
  9. ↑ Ilter, Metehan; Escorcia, Andrés M.; Schulze-Niemand, Eric; Naumann, Michael; Stein, Matthias (2025-01-27). "Activation and Reactivity of the Deubiquitinylase OTU Cezanne-2 from MD Simulations and QM/MM Calculations". Journal of Chemical Information and Modeling. 65 (2): 921–936. doi:10.1021/acs.jcim.4c01964. ISSN 1549-9596. PMC 11776055 Check |pmc= value (help). PMID 39782030 Check |pmid= value (help).
  10. ↑ Moritsugu, Kei; Ekimoto, Toru; Ikeguchi, Mitsunori; Kidera, Akinori (2023-01-09). "Binding and Unbinding Pathways of Peptide Substrates on the SARS-CoV-2 3CL Protease". Journal of Chemical Information and Modeling. 63 (1): 240–250. doi:10.1021/acs.jcim.2c00946. ISSN 1549-9596. PMID 36539353 Check |pmid= value (help).
  11. ↑ Dawson, John (2021-01-04). "The Catalytic Mechanism of Chymotrypsin & Measuring Activity".
  12. ↑ Gutfreund, H.; Sturtevant, J. M. (October 1956). "The mechanism of chymotrypsin-catalyzed reactions". Proceedings of the National Academy of Sciences. 42 (10): 719–728. Bibcode:1956PNAS...42..719G. doi:10.1073/pnas.42.10.719. PMC 528322. PMID 16589938.
  13. ↑ Malde, Alpeshkumar K.; Hill, Timothy A.; Iyer, Abishek; Fairlie, David P. (2019-09-11). "Crystal Structures of Protein-Bound Cyclic Peptides". Chemical Reviews. 119 (17): 9861–9914. doi:10.1021/acs.chemrev.8b00807. hdl:10072/389842. ISSN 0009-2665. PMID 31046237.
  14. ↑ Amorim, Vitor Martins de Freitas; Soares, Eduardo Pereira; Ferrari, Anielle Salviano de Almeida; Merighi, Davi Gabriel Salustiano; de Souza, Robson Francisco; Guzzo, Cristiane Rodrigues; Souza, Anacleto Silva de (2024-05-24). "3-Chymotrypsin-like Protease (3CLpro) of SARS-CoV-2: Validation as a Molecular Target, Proposal of a Novel Catalytic Mechanism, and Inhibitors in Preclinical and Clinical Trials". Viruses. 16 (6): 844. doi:10.3390/v16060844. ISSN 1999-4915. PMC 11209289 Check |pmc= value (help). PMID 38932137 Check |pmid= value (help).
  15. ↑ Lima, M. C. P.; Seabra, G. M. (2016-11-09). "Reaction mechanism of the dengue virus serine protease: a QM/MM study". Physical Chemistry Chemical Physics. 18 (44): 30288–30296. Bibcode:2016PCCP...1830288L. doi:10.1039/C6CP03209E. ISSN 1463-9084. PMID 27341353.
  16. ↑ Topf, Maya; Várnai, Peter; Richards, W. Graham (2002-12-01). "Ab Initio QM/MM Dynamics Simulation of the Tetrahedral Intermediate of Serine Proteases:  Insights into the Active Site Hydrogen-Bonding Network". Journal of the American Chemical Society. 124 (49): 14780–14788. doi:10.1021/ja026219q. ISSN 0002-7863.
  17. ↑ Topf, Maya; Várnai, Peter; Richards, W. Graham (2002-12-01). "Ab Initio QM/MM Dynamics Simulation of the Tetrahedral Intermediate of Serine Proteases:  Insights into the Active Site Hydrogen-Bonding Network". Journal of the American Chemical Society. 124 (49): 14780–14788. doi:10.1021/ja026219q. ISSN 0002-7863.
  18. ↑ Ishida, Toyokazu; Kato, Shigeki (2003-10-01). "Theoretical Perspectives on the Reaction Mechanism of Serine Proteases: The Reaction Free Energy Profiles of the Acylation Process". Journal of the American Chemical Society. 125 (39): 12035–12048. Bibcode:2003JAChS.12512035I. doi:10.1021/ja021369m. ISSN 0002-7863. PMID 14505425.
  19. ↑ Molina, Pablo A.; Sikorski, R. Steven; Jensen, Jan H. (2003-04-01). "NMR chemical shifts in the low-pH form of a-chymotrypsin. A QM/MM and ONIOM-NMR study". Theoretical Chemistry Accounts: Theory, Computation, and Modeling (Theoretica Chimica Acta). 109 (3): 100–107. doi:10.1007/s00214-002-0415-1. ISSN 1432-881X.
  20. ↑ Molani, Farzad; Webb, Simon; Cho, Art E. (2023-05-08). "Combining QM/MM Calculations with Classical Mining Minima to Predict Protein–Ligand Binding Free Energy". Journal of Chemical Information and Modeling. 63 (9): 2728–2734. doi:10.1021/acs.jcim.2c01637. ISSN 1549-9596. PMID 37079618 Check |pmid= value (help).
  21. ↑ Díaz-Cervantes, Erik; Robles, Juvencio; Solà, Miquel; Swart, Marcel (2023-03-15). "The peptide bond rupture mechanism in the serine proteases: an in silico study based on sequential scale models". Physical Chemistry Chemical Physics. 25 (11): 8043–8049. Bibcode:2023PCCP...25.8043D. doi:10.1039/D2CP04872H. ISSN 1463-9084. PMID 36876585 Check |pmid= value (help).
  22. ↑ Jerves, Carola; Neves, Rui P. P.; Silva, Saulo L. da; Ramos, Maria J.; Fernandes, Pedro A. (2023-12-18). "Rate-enhancing PETase mutations determined through DFT/MM molecular dynamics simulations". New Journal of Chemistry. 48 (1): 45–54. doi:10.1039/D3NJ04204A. ISSN 1369-9261.
  23. ↑ van der Kamp, Marc W.; Begum, Jaida (2024), "QM / MM for Structure-Based Drug Design: Techniques and Applications", Computational Drug Discovery, John Wiley & Sons, Ltd, pp. 119–156, doi:10.1002/9783527840748.ch6, ISBN 978-3-527-84074-8, retrieved 2025-11-28
  24. ↑ Zhu, Lijuan; Yang, Wei; Meng, Yan Yan; Xiao, Xiuchan; Guo, Yanzhi; Pu, Xuemei; Li, Menglong (2012-03-15). "Effects of Organic Solvent and Crystal Water on γ-Chymotrypsin in Acetonitrile Media: Observations from Molecular Dynamics Simulation and DFT Calculation". The Journal of Physical Chemistry B. 116 (10): 3292–3304. Bibcode:2012JPCB..116.3292Z. doi:10.1021/jp3002405. ISSN 1520-6106. PMID 22320259.
  25. ↑ Platero-Rochart, Daniel; Krivobokova, Tatyana; Gastegger, Michael; Reibnegger, Gilbert; Sánchez-Murcia, Pedro A. (2023-08-14). "Prediction of Enzyme Catalysis by Computing Reaction Energy Barriers via Steered QM/MM Molecular Dynamics Simulations and Machine Learning". Journal of Chemical Information and Modeling. 63 (15): 4623–4632. doi:10.1021/acs.jcim.3c00772. ISSN 1549-9596. PMC 10430765 Check |pmc= value (help). PMID 37479222 Check |pmid= value (help).
  26. ↑ Niklasson, Anders M. N.; Negre, Christian F. A. (2023-04-21). "Shadow energy functionals and potentials in Born–Oppenheimer molecular dynamics". The Journal of Chemical Physics. 158 (15). arXiv:2302.06703. Bibcode:2023JChPh.158o4105N. doi:10.1063/5.0146431. ISSN 0021-9606. PMID 37093997 Check |pmid= value (help). Unknown parameter |article-number= ignored (help)
  27. ↑ Tangney, Paul (2006-01-28). "On the theory underlying the Car-Parrinello method and the role of the fictitious mass parameter". The Journal of Chemical Physics. 124 (4). arXiv:cond-mat/0601130. Bibcode:2006JChPh.124d4111T. doi:10.1063/1.2162893. ISSN 0021-9606. PMID 16460153. Unknown parameter |article-number= ignored (help)
  28. ↑ Neves, Rui P. P.; Fernandes, Pedro A.; Ramos, Maria J. (2022-08-08). "Role of Enzyme and Active Site Conformational Dynamics in the Catalysis by α-Amylase Explored with QM/MM Molecular Dynamics". Journal of Chemical Information and Modeling. 62 (15): 3638–3650. doi:10.1021/acs.jcim.2c00691. ISSN 1549-9596. PMC 9778734 Check |pmc= value (help). PMID 35880954 Check |pmid= value (help).
  29. ↑ Brigitta, Elsässer; Peter, Goettig (January 2021). "Mechanisms of Proteolytic Enzymes and Their Inhibition in QM/MM Studies". International Journal of Molecular Sciences. 22 (6). doi:10.3390/ijm (inactive 29 November 2025). ISSN 1422-0067. Archived from the original on 2024-12-03. Retrieved 2025-11-28. Unknown parameter |url-status= ignored (help)
  30. ↑ Lee, Jumin; Cheng, Xi; Swails, Jason M.; Yeom, Min Sun; Eastman, Peter K.; Lemkul, Justin A.; Wei, Shuai; Buckner, Joshua; Jeong, Jong Cheol; Qi, Yifei; Jo, Sunhwan; Pande, Vijay S.; Case, David A.; Brooks, Charles L. III; MacKerell, Alexander D. Jr. (2016-01-12). "CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field". Journal of Chemical Theory and Computation. 12 (1): 405–413. Bibcode:2016JCTC...12..405L. doi:10.1021/acs.jctc.5b00935. ISSN 1549-9618. PMC 4712441. PMID 26631602.
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  32. ↑ Jo, Sunhwan; Cheng, Xi; Islam, Shahidul M.; Huang, Lei; Rui, Huan; Zhu, Allen; Lee, Hui Sun; Qi, Yifei; Han, Wei; Vanommeslaeghe, Kenno; MacKerell, Alexander D.; Roux, Benoît; Im, Wonpil (2014-01-01), CHARMM-GUI PDB Manipulator for Advanced Modeling and Simulations of Proteins Containing Nonstandard Residues, Advances in Protein Chemistry and Structural Biology, 96, Academic Press, pp. 235–265, doi:10.1016/bs.apcsb.2014.06.002, ISBN 978-0-12-800013-7, PMC 4739825, PMID 25443960
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  40. ↑ Hudáky, Péter; Perczel, András (2006). "A self-stabilized model of the chymotrypsin catalytic pocket. The energy profile of the overall catalytic cycle". Proteins: Structure, Function, and Bioinformatics. 62 (3): 749–759. doi:10.1002/prot.20827. ISSN 1097-0134. PMID 16358328.
  41. ↑ Wehrhan, Leon; Leppkes, Jakob; Dimos, Nicole; Loll, Bernhard; Koksch, Beate; Keller, Bettina G. (2022-12-08). "Water Network in the Binding Pocket of Fluorinated BPTI–Trypsin Complexes─Insights from Simulation and Experiment". The Journal of Physical Chemistry B. 126 (48): 9985–9999. Bibcode:2022JPCB..126.9985W. doi:10.1021/acs.jpcb.2c05496. ISSN 1520-6106. PMID 36409613 Check |pmid= value (help).
  42. ↑ Vennelakanti, Vyshnavi; Nazemi, Azadeh; Mehmood, Rimsha; Steeves, Adam H.; Kulik, Heather J. (2022-02-01). "Harder, better, faster, stronger: Large-scale QM and QM/MM for predictive modeling in enzymes and proteins". Current Opinion in Structural Biology. 72: 9–17. arXiv:2105.12873. doi:10.1016/j.sbi.2021.07.004. ISSN 0959-440X.
  43. ↑ Raghavan, Bharath; Paulikat, Mirko; Ahmad, Katya; Callea, Lara; Rizzi, Andrea; Ippoliti, Emiliano; Mandelli, Davide; Bonati, Laura; De Vivo, Marco; Carloni, Paolo (2023-06-26). "Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations". Journal of Chemical Information and Modeling. 63 (12): 3647–3658. doi:10.1021/acs.jcim.3c00557. ISSN 1549-9596. PMC 10302481 Check |pmc= value (help). PMID 37319347 Check |pmid= value (help).
  44. ↑ Zlobin, Alexander; Belyaeva, Julia; Golovin, Andrey (2023-01-23). "Challenges in Protein QM/MM Simulations with Intra-Backbone Link Atoms". Journal of Chemical Information and Modeling. 63 (2): 546–560. doi:10.1021/acs.jcim.2c01071. ISSN 1549-9596. PMID 36633836 Check |pmid= value (help).
  45. ↑ Lu, Xiya; Fang, Dong; Ito, Shingo; Okamoto, Yuko; Ovchinnikov, Victor; Cui, Qiang (2016-09-01). "QM/MM free energy simulations: recent progress and challenges". Molecular Simulation. 42 (13): 1056–1078. doi:10.1080/08927022.2015.1132317. ISSN 0892-7022. PMC 4993472. PMID 27563170.

Category: Computational chemistry, Molecular dynamics



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