1
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Gupta AK, Maier S, Thapa B, Raghavachari K. Toward Post-Hartree-Fock Accuracy for Protein-Ligand Affinities Using the Molecules-in-Molecules Fragmentation-Based Method. J Chem Theory Comput 2024; 20:2774-2785. [PMID: 38530869 DOI: 10.1021/acs.jctc.3c01293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
The complexity and size of large molecular systems, such as protein-ligand complexes, pose computational challenges for accurate post-Hartree-Fock calculations. This study delivers a thorough benchmarking of the Molecules-in-Molecules (MIM) method, presenting a clear and accessible strategy for layer/theory selections in post-Hartree-Fock computations on substantial molecular systems, notably protein-ligand complexes. An approach is articulated, enabling augmented computational efficiency by strategically canceling out common subsystem energy terms between complexes and proteins within the supermolecular equation. Employing DLPNO-based post-Hartree-Fock methods in conjunction with the three-layer MIM method (MIM3), this study demonstrates the achievement of protein-ligand binding energies with remarkable accuracy (errors <1 kcal mol-1), while significantly reducing computational costs. Furthermore, noteworthy correlations between theoretically computed interaction energies and their experimental equivalents were observed, with R2 values of approximately 0.90 and 0.78 for CDK2 and BZT-ITK sets, respectively, thus validating the efficacy of the MIM method in calculating binding energies. By highlighting the crucial role of diffuse or small Pople-style basis sets in the middle layer for reducing energy errors, this work provides valuable insights and practical methodologies for interaction energy computations in large molecular complexes and opens avenues for their application across a diverse range of molecular systems.
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Affiliation(s)
- Ankur K Gupta
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Sarah Maier
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Bishnu Thapa
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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2
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Chandy SK, Raghavachari K. MIM-ML: A Novel Quantum Chemical Fragment-Based Random Forest Model for Accurate Prediction of NMR Chemical Shifts of Nucleic Acids. J Chem Theory Comput 2023; 19:6632-6642. [PMID: 37703522 DOI: 10.1021/acs.jctc.3c00563] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
We developed a random forest machine learning (ML) model for the prediction of 1H and 13C NMR chemical shifts of nucleic acids. Our ML model is trained entirely on reproducing computed chemical shifts obtained previously on 10 nucleic acids using a Molecules-in-Molecules (MIM) fragment-based density functional theory (DFT) protocol including microsolvation effects. Our ML model includes structural descriptors as well as electronic descriptors from an inexpensive low-level semiempirical calculation (GFN2-xTB) and trained on a relatively small number of DFT chemical shifts (2080 1H chemical shifts and 1780 13C chemical shifts on the 10 nucleic acids). The ML model is then used to make chemical shift predictions on 8 new nucleic acids ranging in size from 600 to 900 atoms and compared directly to experimental data. Though no experimental data was used in the training, the performance of our model is excellent (mean absolute deviation of 0.34 ppm for 1H chemical shifts and 2.52 ppm for 13C chemical shifts for the test set), despite having some nonstandard structures. A simple analysis suggests that both structural and electronic descriptors are critical for achieving reliable predictions. This is the first attempt to combine ML from fragment-based DFT calculations to predict experimental chemical shifts accurately, making the MIM-ML model a valuable tool for NMR predictions of nucleic acids.
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Affiliation(s)
- Sruthy K Chandy
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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3
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Wang X, Wang Y, Guo M, Wang X, Li Y, Zhang JZH. Assessment of an Electrostatic Energy-Based Charge Model for Modeling the Electrostatic Interactions in Water Solvent. J Chem Theory Comput 2023; 19:6294-6312. [PMID: 37656610 DOI: 10.1021/acs.jctc.3c00467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/03/2023]
Abstract
The protein force field based on the restrained electrostatic potential (RESP) charges has limitations in accurately describing hydrogen bonding interactions in proteins. To address this issue, we propose an alternative approach called the electrostatic energy-based charges (EEC) model, which shows improved performance in describing electrostatic interactions (EIs) of hydrogen bonds in proteins. In this study, we further investigate the performance of the EEC model in modeling EIs in water solvent. Our findings demonstrate that the fixed EEC model can effectively reproduce the quantum mechanics/molecular mechanics (QM/MM)-calculated EIs between a water molecule and various water solvent environments. However, to achieve the same level of computational accuracy, the electrostatic potential (ESP) charge model needs to fluctuate according to the electrostatic environment. Our analysis indicates that the requirement for charge adjustments depends on the specific mathematical and physical representation of EIs as a function of the environment for deriving charges. By comparing with widely used empirical water models calibrated to reproduce experimental properties, we confirm that the performance of the EEC model in reproducing QM/MM EIs is similar to that of general purpose TIP4P-like water models such as TIP4P-Ew and TIP4P/2005. When comparing the computed 10,000 distinct EI values within the range of -40 to 0 kcal/mol with the QM/MM results calculated at the MP2/aug-cc-pVQZ/TIP3P level, we noticed that the mean unsigned error (MUE) for the EEC model is merely 0.487 kcal/mol, which is remarkably similar to the MUE values of the TIP4P-Ew (0.63 kcal/mol) and TIP4P/2005 (0.579 kcal/mol) models. However, both the RESP method and the TIP3P model exhibit a tendency to overestimate the EIs, as evidenced by their higher MUE values of 1.761 and 1.293 kcal/mol, respectively. EEC-based molecular dynamics simulations have demonstrated that, when combined with appropriate van der Waals parameters, the EEC model can closely reproduce oxygen-oxygen radial distribution function and density of water, showing a remarkable similarity to the well-established TIP4P-like empirical water models. Our results demonstrate that the EEC model has the potential to build force fields with comparable accuracy to more sophisticated empirical TIP4P-like water models.
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Affiliation(s)
- Xianwei Wang
- College of Science, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
| | - Yiying Wang
- College of Science, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
| | - Man Guo
- College of Science, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
| | - Xuechao Wang
- College of Science, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China
| | - Yang Li
- College of Information Science and Engineering, Shandong Agricultural University, Tai'an, Shandong 271018, China
| | - John Z H Zhang
- Shenzhen Institute of Synthetic Biology, Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
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4
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Wych DC, Wall ME. Molecular-dynamics simulations of macromolecular diffraction, part I: Preparation of protein crystal simulations. Methods Enzymol 2023; 688:87-114. [PMID: 37748833 DOI: 10.1016/bs.mie.2023.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
Molecular-dynamics (MD) simulations of protein crystals enable the prediction of structural and dynamical features of both the protein and the solvent components of macromolecular crystals, which can be validated against diffraction data from X-ray crystallographic experiments. The simulations have been useful for studying and predicting both Bragg and diffuse scattering in protein crystallography; however, the preparation is not yet automated and includes choices and tradeoffs that can impact the results. Here we examine some of the intricacies and consequences of the choices involved in setting up MD simulations of protein crystals for the study of diffraction data, and provide a recipe for preparing the simulations, packaged in an accompanying Jupyter notebook. This article and the accompanying notebook are intended to serve as practical resources for researchers wishing to put these models to work.
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Affiliation(s)
- David C Wych
- Computer, Computational and Statistical Sciences Division, Los Alamos, NM, United States; Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM, United States
| | - Michael E Wall
- Computer, Computational and Statistical Sciences Division, Los Alamos, NM, United States.
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5
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Kříž K, Schmidt L, Andersson AT, Walz MM, van der Spoel D. An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation. J Chem Inf Model 2023; 63:412-431. [PMID: 36630710 PMCID: PMC9875315 DOI: 10.1021/acs.jcim.2c01127] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Indexed: 01/12/2023]
Abstract
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchmarks. While such benchmarks are rather common in the fields of quantum chemistry, this is not the case for empirical FFs. That is, few benchmarks are reused to evaluate FFs, and development teams rather use their own training and test sets. Here we present an overview of currently available tests and benchmarks for computational chemistry, focusing on organic compounds, including halogens and common ions, as FFs for these are the most common ones. We argue that many of the benchmark data sets from quantum chemistry can in fact be reused for evaluating FFs, but new gas phase data is still needed for compounds containing phosphorus and sulfur in different valence states. In addition, more nonequilibrium interaction energies and forces, as well as molecular properties such as electrostatic potentials around compounds, would be beneficial. For the condensed phases there is a large body of experimental data available, and tools to utilize these data in an automated fashion are under development. If FF developers, as well as researchers in artificial intelligence, would adopt a number of these data sets, it would become easier to compare the relative strengths and weaknesses of different models and to, eventually, restore the balance in the force.
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Affiliation(s)
- Kristian Kříž
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Lisa Schmidt
- Faculty
of Biosciences, University of Heidelberg, Heidelberg69117, Germany
| | - Alfred T. Andersson
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Marie-Madeleine Walz
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - David van der Spoel
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
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6
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Gonçalves YMH, Horta BAC. gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration. J Chem Theory Comput 2023; 19:605-618. [PMID: 36634285 DOI: 10.1021/acs.jctc.2c00955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.
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Affiliation(s)
- Yan M H Gonçalves
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
- Peers Consulting & Technology, Av. Ibirapuera, 1753-18° andar, Moema, São Paulo, São Paulo 04029-90, Brazil
| | - Bruno A C Horta
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
- Peers Consulting & Technology, Av. Ibirapuera, 1753-18° andar, Moema, São Paulo, São Paulo 04029-90, Brazil
- Laboratory of Applied Intelligence, University of Vale do Itajaí, Itajaí, Santa Catarina 88302-901, Brazil
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7
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Chandy SK, Raghavachari K. Accurate and Cost-Effective NMR Chemical Shift Predictions for Nucleic Acids Using a Molecules-in-Molecules Fragmentation-Based Method. J Chem Theory Comput 2023; 19:544-561. [PMID: 36630261 DOI: 10.1021/acs.jctc.2c00967] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We have developed, implemented, and assessed an efficient protocol for the prediction of NMR chemical shifts of large nucleic acids using our molecules-in-molecules (MIM) fragment-based quantum chemical approach. To assess the performance of our approach, MIM-NMR calculations are calibrated on a test set of three nucleic acids, where the structure is derived from solution-phase NMR studies. For DNA systems with multiple conformers, the one-layer MIM method with trimer fragments (MIM1trimer) is benchmarked to get the lowest energy structure, with an average error of only 0.80 kcal/mol with respect to unfragmented full molecule calculations. The MIMI-NMRdimer calibration with respect to unfragmented full molecule calculations shows a mean absolute deviation (MAD) of 0.06 and 0.11 ppm, respectively, for 1H and 13C nuclei, but the performance with respect to experimental NMR chemical shifts is comparable to the more expensive MIM1-NMR and MIM2-NMR methods with trimer subsystems. To compare with the experimental chemical shifts, a standard protocol is derived using DNA systems with Protein Data Bank (PDB) IDs 1SY8, 1K2K, and 1KR8. The effect of structural minimizations is employed using a hybrid mechanics/semiempirical approach and used for computations in solution with implicit and explicit-implicit solvation models in our MIM1-NMRdimer methodology. To demonstrate the applicability of our protocol, we tested it on seven nucleic acids, including structures with nonstandard residues, heteroatom substitutions (F and B atoms), and side chain mutations with a size ranging from ∼300 to 1100 atoms. The major improvement for predicted MIM1-NMRdimer calculations is obtained from structural minimizations and implicit solvation effects. A significant improvement with the explicit-implicit solvation model is observed only for two smaller nucleic acid systems (1KR8 and 7NBK), where the expensive first solvation shell is replaced by the microsolvation model, in which a single water molecule is added for each solvent-exposed amino and imino protons, along with the implicit solvation. Overall, our target accuracy of ∼0.2-0.3 ppm for 1H and ∼2-3 ppm for 13C has been achieved for large nucleic acids. The proposed MIM-NMR approach is accurate and cost-effective (linear scaling with system size), and it can aid in the structural assignments of a wide range of complex biomolecules.
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Affiliation(s)
- Sruthy K Chandy
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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8
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Pantiora P, Furlan V, Matiadis D, Mavroidi B, Perperopoulou F, Papageorgiou AC, Sagnou M, Bren U, Pelecanou M, Labrou NE. Monocarbonyl Curcumin Analogues as Potent Inhibitors against Human Glutathione Transferase P1-1. Antioxidants (Basel) 2022; 12:antiox12010063. [PMID: 36670925 PMCID: PMC9854774 DOI: 10.3390/antiox12010063] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/14/2022] [Accepted: 12/22/2022] [Indexed: 12/31/2022] Open
Abstract
The isoenzyme of human glutathione transferase P1-1 (hGSTP1-1) is involved in multi-drug resistance (MDR) mechanisms in numerous cancer cell lines. In the present study, the inhibition potency of two curcuminoids and eleven monocarbonyl curcumin analogues against hGSTP1-1 was investigated. Demethoxycurcumin (Curcumin II) and three of the monocarbonyl curcumin analogues exhibited the highest inhibitory activity towards hGSTP1-1 with IC50 values ranging between 5.45 ± 1.08 and 37.72 ± 1.02 μM. Kinetic inhibition studies of the most potent inhibitors demonstrated that they function as non-competitive/mixed-type inhibitors. These compounds were also evaluated for their toxicity against the prostate cancer cells DU-145. Interestingly, the strongest hGSTP1-1 inhibitor, (DM96), exhibited the highest cytotoxicity with an IC50 of 8.60 ± 1.07 μΜ, while the IC50 values of the rest of the compounds ranged between 44.59-48.52 μΜ. Structural analysis employing molecular docking, molecular dynamics (MD) simulations, and binding-free-energy calculations was performed to study the four most potent curcumin analogues as hGSTP1-1 inhibitors. According to the obtained computational results, DM96 exhibited the lowest binding free energy, which is in agreement with the experimental data. All studied curcumin analogues were found to form hydrophobic interactions with the residue Gln52, as well as hydrogen bonds with the nearby residues Gln65 and Asn67. Additional hydrophobic interactions with the residues Phe9 and Val36 as well as π-π stacking interaction with Phe9 contributed to the superior inhibitory activity of DM96. The van der Waals component through shape complementarity was found to play the most important role in DM96-inhibitory activity. Overall, our results revealed that the monocarbonyl curcumin derivative DM96 acts as a strong hGSTP1-1 inhibitor, exerts high prostate cancer cell cytotoxicity, and may, therefore, be exploited for the suppression and chemosensitization of cancer cells. This study provides new insights into the development of safe and effective GST-targeted cancer chemosensitizers.
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Affiliation(s)
- Panagiota Pantiora
- Laboratory of Enzyme Technology, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, 75 Iera Odos Street, GR-11855 Athens, Greece
- Institute of Biosciences & Applications, NCSR “Demokritos”, 15310 Athens, Greece
| | - Veronika Furlan
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia
| | - Dimitris Matiadis
- Institute of Biosciences & Applications, NCSR “Demokritos”, 15310 Athens, Greece
| | - Barbara Mavroidi
- Institute of Biosciences & Applications, NCSR “Demokritos”, 15310 Athens, Greece
| | - Fereniki Perperopoulou
- Laboratory of Enzyme Technology, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, 75 Iera Odos Street, GR-11855 Athens, Greece
| | | | - Marina Sagnou
- Institute of Biosciences & Applications, NCSR “Demokritos”, 15310 Athens, Greece
| | - Urban Bren
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000 Koper, Slovenia
- Institute of Environmental Protection and Sensors, Beloruska Ulica 7, SI-2000 Maribor, Slovenia
| | - Maria Pelecanou
- Institute of Biosciences & Applications, NCSR “Demokritos”, 15310 Athens, Greece
| | - Nikolaos E. Labrou
- Laboratory of Enzyme Technology, Department of Biotechnology, School of Applied Biology and Biotechnology, Agricultural University of Athens, 75 Iera Odos Street, GR-11855 Athens, Greece
- Correspondence: ; Tel./Fax: +30-2105294208
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9
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González D, Macaya L, Castillo-Orellana C, Verstraelen T, Vogt-Geisse S, Vöhringer-Martinez E. Nonbonded Force Field Parameters from Minimal Basis Iterative Stockholder Partitioning of the Molecular Electron Density Improve CB7 Host-Guest Affinity Predictions. J Chem Inf Model 2022; 62:4162-4174. [PMID: 35959540 DOI: 10.1021/acs.jcim.2c00316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.
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Affiliation(s)
- Duván González
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Luis Macaya
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Carlos Castillo-Orellana
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Toon Verstraelen
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark-Zwijnnarde 46, B-9052 Ghent, Belgium
| | - Stefan Vogt-Geisse
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Esteban Vöhringer-Martinez
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
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10
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Monteleone S, Fedorov DG, Townsend-Nicholson A, Southey M, Bodkin M, Heifetz A. Hotspot Identification and Drug Design of Protein-Protein Interaction Modulators Using the Fragment Molecular Orbital Method. J Chem Inf Model 2022; 62:3784-3799. [PMID: 35939049 DOI: 10.1021/acs.jcim.2c00457] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Protein-protein interactions (PPIs) are essential for the function of many proteins. Aberrant PPIs have the potential to lead to disease, making PPIs promising targets for drug discovery. There are over 64,000 PPIs in the human interactome reference database; however, to date, very few PPI modulators have been approved for clinical use. Further development of PPI-specific therapeutics is highly dependent on the availability of structural data and the existence of reliable computational tools to explore the interface between two interacting proteins. The fragment molecular orbital (FMO) quantum mechanics method offers comprehensive and computationally inexpensive means of identifying the strength (in kcal/mol) and the chemical nature (electrostatic or hydrophobic) of the molecular interactions taking place at the protein-protein interface. We have integrated FMO and PPI exploration (FMO-PPI) to identify the residues that are critical for protein-protein binding (hotspots). To validate this approach, we have applied FMO-PPI to a dataset of protein-protein complexes representing several different protein subfamilies and obtained FMO-PPI results that are in agreement with published mutagenesis data. We observed that critical PPIs can be divided into three major categories: interactions between residues of two proteins (intermolecular), interactions between residues within the same protein (intramolecular), and interactions between residues of two proteins that are mediated by water molecules (water bridges). We extended our findings by demonstrating how this information obtained by FMO-PPI can be utilized to support the structure-based drug design of PPI modulators (SBDD-PPI).
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Affiliation(s)
- Stefania Monteleone
- Evotec UK Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4RZ, United Kingdom
| | - Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
| | - Andrea Townsend-Nicholson
- Institute of Structural & Molecular Biology, Research Department of Structural & Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, United Kingdom
| | - Michelle Southey
- Evotec UK Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4RZ, United Kingdom
| | - Michael Bodkin
- Evotec UK Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4RZ, United Kingdom
| | - Alexander Heifetz
- Evotec UK Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire OX14 4RZ, United Kingdom
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11
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Lang EJM, Baker EG, Woolfson DN, Mulholland AJ. Generalized Born Implicit Solvent Models Do Not Reproduce Secondary Structures of De Novo Designed Glu/Lys Peptides. J Chem Theory Comput 2022; 18:4070-4076. [PMID: 35687842 PMCID: PMC9281390 DOI: 10.1021/acs.jctc.1c01172] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
![]()
We test a range of
standard generalized Born (GB) models and protein
force fields for a set of five experimentally characterized, designed
peptides comprising alternating blocks of glutamate and lysine, which
have been shown to differ significantly in α-helical content.
Sixty-five combinations of force fields and GB models are evaluated
in >800 μs of molecular dynamics simulations. GB models generally
do not reproduce the experimentally observed α-helical content,
and none perform well for all five peptides. These results illustrate
that these models are not usefully predictive in this context. These
peptides provide a useful test set for simulation methods.
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Affiliation(s)
- Eric J M Lang
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K.,School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K.,BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, U.K
| | - Emily G Baker
- School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K.,BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, U.K
| | - Derek N Woolfson
- School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K.,BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, U.K.,School of Biochemistry, University of Bristol, Medical Sciences Building, University Walk, Bristol BS8 1TD, U.K
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K.,School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, U.K
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12
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Camacho-Zarco AR, Schnapka V, Guseva S, Abyzov A, Adamski W, Milles S, Jensen MR, Zidek L, Salvi N, Blackledge M. NMR Provides Unique Insight into the Functional Dynamics and Interactions of Intrinsically Disordered Proteins. Chem Rev 2022; 122:9331-9356. [PMID: 35446534 PMCID: PMC9136928 DOI: 10.1021/acs.chemrev.1c01023] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
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Intrinsically disordered
proteins are ubiquitous throughout all
known proteomes, playing essential roles in all aspects of cellular
and extracellular biochemistry. To understand their function, it is
necessary to determine their structural and dynamic behavior and to
describe the physical chemistry of their interaction trajectories.
Nuclear magnetic resonance is perfectly adapted to this task, providing
ensemble averaged structural and dynamic parameters that report on
each assigned resonance in the molecule, unveiling otherwise inaccessible
insight into the reaction kinetics and thermodynamics that are essential
for function. In this review, we describe recent applications of NMR-based
approaches to understanding the conformational energy landscape, the
nature and time scales of local and long-range dynamics and how they
depend on the environment, even in the cell. Finally, we illustrate
the ability of NMR to uncover the mechanistic basis of functional
disordered molecular assemblies that are important for human health.
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Affiliation(s)
| | - Vincent Schnapka
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Serafima Guseva
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Anton Abyzov
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Wiktor Adamski
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | - Sigrid Milles
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
| | | | - Lukas Zidek
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 5, 82500 Brno, Czech Republic.,Central European Institute of Technology, Masaryk University, Kamenice 5, 82500 Brno, Czech Republic
| | - Nicola Salvi
- Université Grenoble Alpes, CEA, CNRS, IBS, 38000 Grenoble, France
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13
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Yang D, Gronenborn AM, Chong LT. Development and Validation of Fluorinated, Aromatic Amino Acid Parameters for Use with the AMBER ff15ipq Protein Force Field. J Phys Chem A 2022; 126:2286-2297. [PMID: 35352936 PMCID: PMC9014858 DOI: 10.1021/acs.jpca.2c00255] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/15/2022] [Indexed: 12/27/2022]
Abstract
We developed force field parameters for fluorinated, aromatic amino acids enabling molecular dynamics (MD) simulations of fluorinated proteins. These parameters are tailored to the AMBER ff15ipq protein force field and enable the modeling of 4, 5, 6, and 7F-tryptophan, 3F- and 3,5F-tyrosine, and 4F- or 4-CF3-phenylalanine. The parameters include 181 unique atomic charges derived using the implicitly polarized charge (IPolQ) scheme in the presence of SPC/Eb explicit water molecules and 9 unique bond, angle, or torsion terms. Our simulations of benchmark peptides and proteins maintain expected conformational propensities on the μs time scale. In addition, we have developed an open-source Python program to calculate fluorine relaxation rates from MD simulations. The extracted relaxation rates from protein simulations are in good agreement with experimental values determined by 19F NMR. Collectively, our results illustrate the power and robustness of the IPolQ lineage of force fields for modeling the structure and dynamics of fluorine-containing proteins at the atomic level.
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Affiliation(s)
- Darian
T. Yang
- Molecular
Biophysics and Structural Biology Graduate Program, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, Pennsylvania 15260, United States
- Department
of Structural Biology, University of Pittsburgh
School of Medicine, Pittsburgh, Pennsylvania 15260, United States
- Department
of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Angela M. Gronenborn
- Department
of Structural Biology, University of Pittsburgh
School of Medicine, Pittsburgh, Pennsylvania 15260, United States
- Department
of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Lillian T. Chong
- Department
of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
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14
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Polêto MD, Lemkul JA. Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields. Commun Chem 2022; 5:10.1038/s42004-022-00653-z. [PMID: 35382231 PMCID: PMC8979544 DOI: 10.1038/s42004-022-00653-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/21/2022] [Indexed: 01/27/2023] Open
Abstract
The development of accurate protein force fields has been the cornerstone of molecular simulations for the past 50 years. During this period, many lessons have been learned regarding the use of experimental target data and parameter fitting procedures. Here, we review recent advances in protein force field development. We discuss the recent emergence of polarizable force fields and the role of electronic polarization and areas in which additive force fields fall short. The use of automated fitting methods and the inclusion of additional experimental solution data during parametrization is discussed as a means to highlight possible routes to improve the accuracy of force fields even further.
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Affiliation(s)
- Marcelo D. Polêto
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
| | - Justin A. Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
- Center for Drug Discovery, Virginia Tech, Blacksburg, VA 24061 United States
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15
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ElGamacy M. Accelerating therapeutic protein design. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2022; 130:85-118. [PMID: 35534117 DOI: 10.1016/bs.apcsb.2022.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein structures provide for defined microenvironments that can support complex pharmacological functions, otherwise unachievable by small molecules. The advent of therapeutic proteins has thus greatly broadened the range of manageable disorders. Leveraging the knowledge and recent advances in de novo protein design methods has the prospect of revolutionizing how protein drugs are discovered and developed. This review lays out the main challenges facing therapeutic proteins discovery and development, and how present and future advancements of protein design can accelerate the protein drug pipelines.
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Affiliation(s)
- Mohammad ElGamacy
- University Hospital Tübingen, Division of Translational Oncology, Tübingen, Germany; Max Planck Institute for Biology, Tübingen, Germany.
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16
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Kognole AA, Lee J, Park SJ, Jo S, Chatterjee P, Lemkul JA, Huang J, MacKerell AD, Im W. CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field. J Comput Chem 2021; 43:359-375. [PMID: 34874077 DOI: 10.1002/jcc.26795] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 11/10/2021] [Accepted: 11/25/2021] [Indexed: 12/18/2022]
Abstract
Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.
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Affiliation(s)
- Abhishek A Kognole
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Jumin Lee
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
| | - Sang-Jun Park
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
| | - Sunhwan Jo
- Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois, USA
| | - Payal Chatterjee
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Justin A Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, Virginia, USA
| | - Jing Huang
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Zhejiang, Hangzhou, China
| | - Alexander D MacKerell
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Wonpil Im
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
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17
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Qiu Y, Smith DGA, Boothroyd S, Jang H, Hahn DF, Wagner J, Bannan CC, Gokey T, Lim VT, Stern CD, Rizzi A, Tjanaka B, Tresadern G, Lucas X, Shirts MR, Gilson MK, Chodera JD, Bayly CI, Mobley DL, Wang LP. Development and Benchmarking of Open Force Field v1.0.0-the Parsley Small-Molecule Force Field. J Chem Theory Comput 2021; 17:6262-6280. [PMID: 34551262 PMCID: PMC8511297 DOI: 10.1021/acs.jctc.1c00571] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of the specification. Parameters are optimized with the ForceBalance tool, based on reference quantum chemical data that include torsion potential energy profiles, optimized gas-phase structures, and vibrational frequencies. These quantum reference data are computed and are maintained with QCArchive, an open-source and freely available distributed computing and database software ecosystem. In this initial application of the method, we present essentially a full optimization of all valence parameters and report tests of the resulting force field against compounds and data types outside the training set. These tests show improvements in optimized geometries and conformational energetics and demonstrate that Parsley's accuracy for liquid properties is similar to that of other general force fields, as is accuracy on binding free energies. We find that this initial Parsley force field affords accuracy similar to that of other general force fields when used to calculate relative binding free energies spanning 199 protein-ligand systems. Additionally, the resulting infrastructure allows us to rapidly optimize an entirely new force field with minimal human intervention.
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Affiliation(s)
- Yudong Qiu
- Chemistry Department, The University of California at Davis, Davis, California 95616, United States
| | - Daniel G A Smith
- The Molecular Sciences Software Institute (MolSSI), Blacksburg, Virginia 24060, United States
| | - Simon Boothroyd
- Computational & Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | - Hyesu Jang
- Chemistry Department, The University of California at Davis, Davis, California 95616, United States
| | - David F Hahn
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - Jeffrey Wagner
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
| | - Caitlin C Bannan
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
- Skaggs School of Pharmacy and Pharmaceutical Sciences, The University of California at San Diego, La Jolla, California 92093, United States
| | - Trevor Gokey
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
| | - Victoria T Lim
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
| | - Chaya D Stern
- Computational & Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | - Andrea Rizzi
- Computational & Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
- Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York 10065, United States
| | - Bryon Tjanaka
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
| | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - Xavier Lucas
- F. Hoffmann-La Roche AG, Basel 4070, Switzerland
| | - Michael R Shirts
- Chemical & Biological Engineering Department, The University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Michael K Gilson
- Skaggs School of Pharmacy and Pharmaceutical Sciences, The University of California at San Diego, La Jolla, California 92093, United States
| | - John D Chodera
- Computational & Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States
| | | | - David L Mobley
- Chemistry Department, The University of California at Irvine, Irvine, California 92617, United States
| | - Lee-Ping Wang
- Chemistry Department, The University of California at Davis, Davis, California 95616, United States
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18
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González D, Macaya L, Vöhringer-Martinez E. Molecular Environment-Specific Atomic Charges Improve Binding Affinity Predictions of SAMPL5 Host-Guest Systems. J Chem Inf Model 2021; 61:4462-4474. [PMID: 34464129 DOI: 10.1021/acs.jcim.1c00655] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Host-guest systems are widely used in benchmarks as model systems to improve computational methods for absolute binding free energy predictions. Recent advances in sampling algorithms for alchemical free energy calculations and the increase in computational power have made their binding affinity prediction primarily dependent on the quality of the force field. Here, we propose a new methodology to derive the atomic charges of host-guest systems based on quantum mechanics/molecular mechanics calculations and minimal basis iterative stockholder (MBIS) partitioning of the polarized electron density. A newly developed interface between the OpenMM and ORCA software packages provides D-MBIS charges that represent the guest's average electrostatic interactions in the hosts or the solvent. The simulation workflow also calculates the average energy required to polarize the guest in the bound and unbound state. Alchemical free energy calculations using the general Amber force field parameters with D-MBIS charges improve the binding affinity prediction of six guests bound to two octa acid hosts compared to the AM1-BCC charge set after correction with the average energetic polarization cost. This correction originates from the difference in potential energy that is required to polarize the guest in the bound and unbound state and contributes significantly to the binding affinity of anionic guests.
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Affiliation(s)
- Duván González
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Luis Macaya
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
| | - Esteban Vöhringer-Martinez
- Departamento de Físico-Química, Facultad de Ciencias Químicas, Universidad de Concepción, 4070386 Concepción, Chile
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19
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P. Oliveira M, Hünenberger PH. Systematic optimization of a fragment-based force field against experimental pure-liquid properties considering large compound families: application to oxygen and nitrogen compounds. Phys Chem Chem Phys 2021; 23:17774-17793. [PMID: 34350931 PMCID: PMC8386690 DOI: 10.1039/d1cp02001c] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/30/2021] [Indexed: 12/04/2022]
Abstract
The CombiFF approach is a workflow for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. One peculiarity of this approach is that it relies on an electronegativity-equalization scheme to account for induction effects within molecules, with values of the atomic hardness and electronegativity as electrostatic parameters, rather than the partial charges themselves. In a previous article [M. P. Oliveira, M. Andrey, S. R. Rieder, L. Kern, D. F. Hahn, S. Riniker, B. A. C. Horta and P. H. Hünenberger, J. Chem. Theory. Comput. 2020, 16, 7525], CombiFF was introduced and applied to calibrate a GROMOS-compatible united-atom force field for the saturated acyclic (halo-)alkane family. Here, this scheme is employed for the construction of a corresponding force field for saturated acyclic compounds encompassing eight common chemical functional groups involving oxygen and/or nitrogen atoms, namely: ether, aldehyde, ketone, ester, alcohol, carboxylic acid, amine, and amide. Monofunctional as well as homo-polyfunctional compounds are considered. A total of 1712 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 1175 molecules are used for the calibration (339 molecules) and validation (836 molecules) of the 102 non-bonded interaction parameters of the force field. Using initial parameter values based on the GROMOS 2016H66 parameter set, convergence is reached after five iterations. Given access to one processor per simulated system, this operation only requires a few days of wall-clock computing time. After optimization, the root-mean-square deviations from experiment are 29.9 (22.4) kg m-3 for ρliq and 4.1 (5.5) kJ mol-1 for ΔHvap for the calibration (validation) set. Thus, a very good level of agreement with experiment is achieved in terms of these two properties, although the errors are inhomogeneously distributed across the different chemical functional groups.
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Affiliation(s)
- Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 5503
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 5503
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20
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Bin Faheem A, Kim JY, Bae SE, Lee KK. Efficient parameterization of intermolecular force fields for molecular dynamics simulations via genetic algorithms. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.116579] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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21
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Furlan V, Bren U. Insight into Inhibitory Mechanism of PDE4D by Dietary Polyphenols Using Molecular Dynamics Simulations and Free Energy Calculations. Biomolecules 2021; 11:biom11030479. [PMID: 33806914 PMCID: PMC8004924 DOI: 10.3390/biom11030479] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 03/19/2021] [Accepted: 03/21/2021] [Indexed: 12/11/2022] Open
Abstract
Phosphodiesterase 4 (PDE4), mainly present in immune, epithelial, and brain cells, represents a family of key enzymes for the degradation of cyclic adenosine monophosphate (cAMP), which modulates inflammatory response. In recent years, the inhibition of PDE4 has been proven to be an effective therapeutic strategy for the treatment of neurological disorders. PDE4D constitutes a high-interest therapeutic target primarily for the treatment of Alzheimer’s disease, as it is highly involved in neuroinflammation, learning ability, and memory dysfunctions. In the present study, a thorough computational investigation consisting of molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations based on the linear response approximation (LRA) method was performed to study dietary polyphenols as potential PDE4D inhibitors. The obtained results revealed that curcumin, 6-gingerol, capsaicin, and resveratrol represent potential PDE4D inhibitors; however, the predicted binding free energies of 6-gingerol, capsaicin, and resveratrol were less negative than in the case of curcumin, which exhibited the highest inhibitory potency in comparison with a positive control rolipram. Our results also revealed that the electrostatic component through hydrogen bonding represents the main driving force for the binding and inhibitory activity of curcumin, 6-gingerol, and resveratrol, while the van der Waals component through shape complementarity plays the most important role in capsaicin’s inhibitory activity. All investigated compounds form hydrophobic interactions with residues Gln376 and Asn602 as well as hydrogen bonds with nearby residues Asp438, Met439, and Ser440. The binding mode of the studied natural compounds is consequently very similar; however, it significantly differs from the binding of known PDE4 inhibitors. The uncovered molecular inhibitory mechanisms of four investigated natural polyphenols, curcumin, 6-gingerol, capsaicin, and resveratrol, form the basis for the design of novel PDE4D inhibitors for the treatment of Alzheimer’s disease with a potentially wider therapeutic window and fewer adverse side effects.
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Affiliation(s)
- Veronika Furlan
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia;
| | - Urban Bren
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia;
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000 Koper, Slovenia
- Correspondence: ; Tel.: +386-2-229-4421
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22
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Yuan Y, Ma Z, Wang F. Development and Validation of a DFT-Based Force Field for a Hydrated Homoalanine Polypeptide. J Phys Chem B 2021; 125:1568-1581. [PMID: 33555880 PMCID: PMC7899179 DOI: 10.1021/acs.jpcb.0c11618] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A new force field has been created for simulating hydrated alanine polypeptides using the adaptive force matching (AFM) method. Only density functional theory calculations using the Perdew-Burke-Ernzerhof exchange-correlation functional and the D3 dispersion correction were used to fit the force field. The new force field, AFM2020, predicts NMR scalar coupling constants for hydrated homopolymeric alanine in better agreements with experimental data than several other models including those fitted directly to such data. For Ala7, the new force field shows about 15% helical conformations, 20% conformation in the β basin, and 65% polyproline II. The predicted helical population of short hydrated alanine is higher than previous estimates based on the same experimental data. Gas-phase simulations indicate that the force field developed by AFM solution-phase data is likely to produce a reasonable conformation distribution when hydration water is no longer present, such as the interior of a protein.
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Affiliation(s)
- Ying Yuan
- Department of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, United States
| | - Zhonghua Ma
- Department of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, United States
| | - Feng Wang
- Department of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, United States
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23
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Gopal SM, Wingbermühle S, Schnatwinkel J, Juber S, Herrmann C, Schäfer LV. Conformational Preferences of an Intrinsically Disordered Protein Domain: A Case Study for Modern Force Fields. J Phys Chem B 2021; 125:24-35. [PMID: 33382616 DOI: 10.1021/acs.jpcb.0c08702] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular simulations of intrinsically disordered proteins (IDPs) are challenging because they require sampling a very large number of relevant conformations, corresponding to a multitude of shallow minima in a flat free energy landscape. However, in the presence of a binding partner, the free energy landscape of an IDP can be dominated by few deep minima. This characteristic imposes high demands on the accuracy of the force field used to describe the molecular interactions. Here, as a model system for an IDP that is unstructured in solution but folds upon binding to a structured interaction partner, the transactivation domain of c-Myb was studied both in the unbound (free) form and when bound to the KIX domain. Six modern biomolecular force fields were systematically tested and compared in terms of their ability to describe the structural ensemble of the IDP. The protein force field/water model combinations included in this study are AMBER ff99SB-disp with its corresponding water model that was derived from TIP4P-D, CHARMM36m with TIP3P, ff15ipq with SPC/Eb, ff99SB*-ILDNP with TIP3P and TIP4P-D, and FB15 with TIP3P-FB water. Comparing the results from REST2-enhanced sampling simulations with experimental CD spectra and secondary chemical shifts reveals that the ff99SB-disp force field can realistically capture the broad and mildly helical structural ensemble of free c-Myb. The structural ensembles yielded by CHARMM36m, ff99SB*-ILDNP together with TIP4P-D water, and FB15 are also mildly helical; however, each of these force fields can be assigned a specific subset of c-Myb residues for which the simulations could not reproduce the experimental secondary chemical shifts. In addition, microsecond-timescale MD simulations of the KIX/c-Myb complex show that most force fields used preserve a stable helix fold of c-Myb in the complex. Still, all force fields predict a KIX/c-Myb complex interface that differs slightly from the structures provided by NMR because several NOE-derived distances between KIX and c-Myb were exceeded in the simulations. Taken together, the ff99SB-disp force field in the first place but also CHARMM36m, ff99SB*-ILDNP together with TIP4P-D water, and FB15 can be suitable choices for future simulation studies of the coupled folding and binding mechanism of the KIX/c-Myb complex and potentially also other IDPs.
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Affiliation(s)
- Srinivasa M Gopal
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Sebastian Wingbermühle
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Jan Schnatwinkel
- Physical Chemistry I, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Selina Juber
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Christian Herrmann
- Physical Chemistry I, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Lars V Schäfer
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
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24
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Amezcua M, El Khoury L, Mobley DL. SAMPL7 Host-Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations. J Comput Aided Mol Des 2021; 35:1-35. [PMID: 33392951 PMCID: PMC8121194 DOI: 10.1007/s10822-020-00363-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/24/2020] [Indexed: 12/15/2022]
Abstract
The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges have thus frequently included a component focusing on host-guest binding, which removes some of these challenges while still focusing on molecular recognition. Here, we report on the results of the SAMPL7 blind prediction challenge for host-guest affinity prediction. In this study, we focused on three different host-guest categories-a familiar deep cavity cavitand series which has been featured in several prior challenges (where we examine binding of a series of guests to two hosts), a new series of cyclodextrin derivatives which are monofunctionalized around the rim to add amino acid-like functionality (where we examine binding of two guests to a series of hosts), and binding of a series of guests to a new acyclic TrimerTrip host which is related to previous cucurbituril hosts. Many predictions used methods based on molecular simulations, and overall success was mixed, though several methods stood out. As in SAMPL6, we find that one strategy for achieving reasonable accuracy here was to make empirical corrections to binding predictions based on previous data for host categories which have been studied well before, though this can be of limited value when new systems are included. Additionally, we found that alchemical free energy methods using the AMOEBA polarizable force field had considerable success for the two host categories in which they participated. The new TrimerTrip system was also found to introduce some sampling problems, because multiple conformations may be relevant to binding and interconvert only slowly. Overall, results in this challenge tentatively suggest that further investigation of polarizable force fields for these challenges may be warranted.
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Affiliation(s)
- Martin Amezcua
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA
| | - Léa El Khoury
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA
| | - David L Mobley
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA.
- Department of Chemistry, University of California, Irvine, CA, 92697, USA.
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25
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Chandy SK, Thapa B, Raghavachari K. Accurate and cost-effective NMR chemical shift predictions for proteins using a molecules-in-molecules fragmentation-based method. Phys Chem Chem Phys 2020; 22:27781-27799. [PMID: 33244526 DOI: 10.1039/d0cp05064d] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We have developed an efficient protocol using our two-layer Molecules-in-Molecules (MIM2) fragmentation-based quantum chemical method for the prediction of NMR chemical shifts of large biomolecules. To investigate the performance of our fragmentation approach and demonstrate its applicability, MIM-NMR calculations are first calibrated on a test set of six proteins. The MIM2-NMR method yields a mean absolute deviation (MAD) from unfragmented full molecule calculations of 0.01 ppm for 1H and 0.06 ppm for 13C chemical shifts. Thus, the errors from fragmentation are only about 3% of our target accuracy of ∼0.3 ppm for 1H and 2-3 ppm for 13C chemical shifts. To compare with experimental chemical shifts, a standard protocol is first derived using two smaller proteins 2LHY (176 atoms) and 2LI1 (146 atoms) for obtaining an appropriate protein structure for NMR chemical shift calculations. The effect of the solvent environment on the calculated NMR chemical shifts is incorporated through implicit, explicit, or explicit-implicit solvation models. The expensive first solvation shell calculations are replaced by a micro-solvation model in which only the immediate interaction between the protein and the explicit solvation environment is considered. A single explicit water molecule for each amine and amide proton is found to be sufficient to yield accurate results for 1H chemical shifts. The 1H and 13C NMR chemical shifts calculated using our protocol give excellent agreement with experiments for two larger proteins, 2MC5 (the helical part with 265 atoms) and 3UMK (33 residue slice with 547 atoms). Overall, our target accuracy of ∼0.3 ppm for 1H and ∼2-3 ppm for 13C has been achieved for the larger proteins. The proposed MIM-NMR method is accurate and computationally cost-effective and should be applicable to study a wide range of large proteins.
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Affiliation(s)
- Sruthy K Chandy
- Department of Chemistry, Indiana University, Bloomington, Indiana, USA.
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26
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Oliveira MP, Andrey M, Rieder SR, Kern L, Hahn DF, Riniker S, Horta BAC, Hünenberger PH. Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes. J Chem Theory Comput 2020; 16:7525-7555. [DOI: 10.1021/acs.jctc.0c00683] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Maurice Andrey
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Salomé R. Rieder
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Leyla Kern
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - David F. Hahn
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Sereina Riniker
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Bruno A. C. Horta
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Honggerberg, HCI, CH-8093 Zürich, Switzerland
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27
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Kashefolgheta S, Oliveira MP, Rieder SR, Horta BAC, Acree WE, Hünenberger PH. Evaluating Classical Force Fields against Experimental Cross-Solvation Free Energies. J Chem Theory Comput 2020; 16:7556-7580. [DOI: 10.1021/acs.jctc.0c00688] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Sadra Kashefolgheta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Salomé R. Rieder
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Bruno A. C. Horta
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
| | - William E. Acree
- Department of Chemistry, University of North Texas, 1155 Union Circle Drive #305070, Denton, Texas 76203, United States
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
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28
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Bogetti AT, Piston HE, Leung JMG, Cabalteja CC, Yang DT, DeGrave AJ, Debiec KT, Cerutti DS, Case DA, Horne WS, Chong LT. A twist in the road less traveled: The AMBER ff15ipq-m force field for protein mimetics. J Chem Phys 2020; 153:064101. [PMID: 35287464 PMCID: PMC7419161 DOI: 10.1063/5.0019054] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 07/19/2020] [Indexed: 12/17/2022] Open
Abstract
We present a new force field, AMBER ff15ipq-m, for simulations of protein mimetics in applications from therapeutics to biomaterials. This force field is an expansion of the AMBER ff15ipq force field that was developed for canonical proteins and enables the modeling of four classes of artificial backbone units that are commonly used alongside natural α residues in blended or "heterogeneous" backbones: chirality-reversed D-α-residues, the Cα-methylated α-residue Aib, homologated β-residues (β3) bearing proteinogenic side chains, and two cyclic β residues (βcyc; APC and ACPC). The ff15ipq-m force field includes 472 unique atomic charges and 148 unique torsion terms. Consistent with the AMBER IPolQ lineage of force fields, the charges were derived using the Implicitly Polarized Charge (IPolQ) scheme in the presence of explicit solvent. To our knowledge, no general force field reported to date models the combination of artificial building blocks examined here. In addition, we have derived Karplus coefficients for the calculation of backbone amide J-coupling constants for β3Ala and ACPC β residues. The AMBER ff15ipq-m force field reproduces experimentally observed J-coupling constants in simple tetrapeptides and maintains the expected conformational propensities in reported structures of proteins/peptides containing the artificial building blocks of interest-all on the μs timescale. These encouraging results demonstrate the power and robustness of the IPolQ lineage of force fields in modeling the structure and dynamics of natural proteins as well as mimetics with protein-inspired artificial backbones in atomic detail.
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Affiliation(s)
- Anthony T. Bogetti
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - Hannah E. Piston
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - Jeremy M. G. Leung
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - Darian T. Yang
- Molecular Biophysics and Structural Biology Graduate Program, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, Pennsylvania 15260, USA
| | - Alex J. DeGrave
- School of Computer Science and Engineering, University of Washington, Seattle, Washington 98115, USA
| | | | - David S. Cerutti
- Department of Chemistry and Chemical Biology, Rutgers University, New Brunswick, New Jersey 008854, USA
| | - David A. Case
- Department of Chemistry and Chemical Biology, Rutgers University, New Brunswick, New Jersey 008854, USA
| | - W. Seth Horne
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - Lillian T. Chong
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
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29
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Bradshaw RT, Dziedzic J, Skylaris CK, Essex JW. The Role of Electrostatics in Enzymes: Do Biomolecular Force Fields Reflect Protein Electric Fields? J Chem Inf Model 2020; 60:3131-3144. [DOI: 10.1021/acs.jcim.0c00217] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Richard T. Bradshaw
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
| | - Jacek Dziedzic
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
- Faculty of Applied Physics and Mathematics, Gdańsk University of Technology, 80-233 Gdańsk, Poland
| | - Chris-Kriton Skylaris
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
| | - Jonathan W. Essex
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
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30
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Moreau CA, Quadt KA, Piirainen H, Kumar H, Bhargav SP, Strauss L, Tolia NH, Wade RC, Spatz JP, Kursula I, Frischknecht F. A function of profilin in force generation during malaria parasite motility that is independent of actin binding. J Cell Sci 2020; 134:jcs233775. [PMID: 32034083 DOI: 10.1242/jcs.233775] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 01/06/2020] [Indexed: 01/20/2023] Open
Abstract
During transmission of malaria-causing parasites from mosquito to mammal, Plasmodium sporozoites migrate at high speed within the skin to access the bloodstream and infect the liver. This unusual gliding motility is based on retrograde flow of membrane proteins and highly dynamic actin filaments that provide short tracks for a myosin motor. Using laser tweezers and parasite mutants, we previously suggested that actin filaments form macromolecular complexes with plasma membrane-spanning adhesins to generate force during migration. Mutations in the actin-binding region of profilin, a near ubiquitous actin-binding protein, revealed that loss of actin binding also correlates with loss of force production and motility. Here, we show that different mutations in profilin, that do not affect actin binding in vitro, still generate lower force during Plasmodium sporozoite migration. Lower force generation inversely correlates with increased retrograde flow suggesting that, like in mammalian cells, the slow down of flow to generate force is the key underlying principle governing Plasmodium gliding motility.
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Affiliation(s)
- Catherine A Moreau
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
| | - Katharina A Quadt
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
- Department of Cellular Biophysics, Max Planck Institute for Medical Research and Laboratory of Biophysical Chemistry, Heidelberg University, Jahnstrasse 29, 69120 Heidelberg, Germany
| | - Henni Piirainen
- Biocenter Oulu and Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7, 90220 Oulu, Finland
| | - Hirdesh Kumar
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
- Department of Molecular Microbiology, Washington University School of Medicine, St Louis, MO 63110, USA
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance and Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Saligram P Bhargav
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
- Biocenter Oulu and Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7, 90220 Oulu, Finland
| | - Léanne Strauss
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
| | - Niraj H Tolia
- Department of Molecular Microbiology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Rebecca C Wade
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance and Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
- Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany
| | - Joachim P Spatz
- Department of Cellular Biophysics, Max Planck Institute for Medical Research and Laboratory of Biophysical Chemistry, Heidelberg University, Jahnstrasse 29, 69120 Heidelberg, Germany
| | - Inari Kursula
- Biocenter Oulu and Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7, 90220 Oulu, Finland
- Department of Biomedicine, University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
| | - Friedrich Frischknecht
- Integrative Parasitology, Center for Infectious Diseases, Heidelberg University Medical School, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany
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31
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Heifetz A, Morao I, Babu MM, James T, Southey MWY, Fedorov DG, Aldeghi M, Bodkin MJ, Townsend-Nicholson A. Characterizing Interhelical Interactions of G-Protein Coupled Receptors with the Fragment Molecular Orbital Method. J Chem Theory Comput 2020; 16:2814-2824. [PMID: 32096994 PMCID: PMC7161079 DOI: 10.1021/acs.jctc.9b01136] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
G-protein coupled receptors (GPCRs) are the largest superfamily of membrane proteins, regulating almost every aspect of cellular activity and serving as key targets for drug discovery. We have identified an accurate and reliable computational method to characterize the strength and chemical nature of the interhelical interactions between the residues of transmembrane (TM) domains during different receptor activation states, something that cannot be characterized solely by visual inspection of structural information. Using the fragment molecular orbital (FMO) quantum mechanics method to analyze 35 crystal structures representing different branches of the class A GPCR family, we have identified 69 topologically equivalent TM residues that form a consensus network of 51 inter-TM interactions, providing novel results that are consistent with and help to rationalize experimental data. This discovery establishes a comprehensive picture of how defined molecular forces govern specific interhelical interactions which, in turn, support the structural stability, ligand binding, and activation of GPCRs.
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Affiliation(s)
- Alexander Heifetz
- Evotec
(U.K.) Ltd., 114 Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
- Institute
of Structural & Molecular Biology, Research Department of Structural
& Molecular Biology, Division of Biosciences, University College London, London, WC1E 6BT, United Kingdom
- E-mail: (A.H.)
| | - Inaki Morao
- Evotec
(U.K.) Ltd., 114 Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
- E-mail: (I.M.)
| | - M. Madan Babu
- MRC
Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Tim James
- Evotec
(U.K.) Ltd., 114 Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
| | | | - Dmitri G. Fedorov
- CD-FMat,
National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
| | - Matteo Aldeghi
- Department
of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
| | - Michael J. Bodkin
- Evotec
(U.K.) Ltd., 114 Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
| | - Andrea Townsend-Nicholson
- Institute
of Structural & Molecular Biology, Research Department of Structural
& Molecular Biology, Division of Biosciences, University College London, London, WC1E 6BT, United Kingdom
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32
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Weber R, McCullagh M. The Role of Hydrophobicity in the Stability and pH-Switchability of (RXDX) 4 and Coumarin-(RXDX) 4 Conjugate β-Sheets. J Phys Chem B 2020; 124:1723-1732. [PMID: 32045245 DOI: 10.1021/acs.jpcb.0c00048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
pH-Switchable, self-assembling materials are of interest in biological imaging and sensing applications. Here we propose that combining the pH-switchability of RXDX (X = Ala, Val, Leu, Ile, Phe) peptides and the optical properties of coumarin creates an ideal candidate for these materials. This suggestion is tested with a thorough set of all-atom molecular dynamics simulations. We first investigate the dependence of pH-switchabiliy on the identity of the hydrophobic residue, X, in the bare (RXDX)4 systems. Increasing the hydrophobicity stabilizes the fiber which, in turn, reduces the pH-switchabilty of the system. This behavior is found to be somewhat transferable to systems in which a single hydrophobic residue is replaced with a coumarin containing amino acid. In this case, conjugates with X = Ala are found to be unstable at both pHs, while conjugates with X = Val, Leu, Ile, and Phe are found to form stable β-sheets at least at neutral pH. The coumarin-(RFDF)4 conjugate is found to have the largest relative entropy value of 0.884 ± 0.001 between neutral and acidic coumarin ordering distributions. Thus, we posit that coumarin-(RFDF)4 containing peptide sequences are ideal candidates for pH-sensing bioelectronic materials.
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Affiliation(s)
- Ryan Weber
- Department of Chemistry, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Martin McCullagh
- Department of Chemistry, Oklahoma State University, Stillwater, Oklahoma 74074, United States
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33
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Kelly BD, Smith WR. Alchemical Hydration Free-Energy Calculations Using Molecular Dynamics with Explicit Polarization and Induced Polarity Decoupling: An On–the–Fly Polarization Approach. J Chem Theory Comput 2020; 16:1146-1161. [DOI: 10.1021/acs.jctc.9b01139] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Braden D. Kelly
- Department of Mathematics and Statistics, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - William R. Smith
- Department of Mathematics and Statistics, University of Guelph, Guelph, ON N1G 2W1, Canada
- Department of Chemical Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
- Faculty of Science, Ontario Tech University, Oshawa, ON L1H 7K4, Canada
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34
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Tian C, Kasavajhala K, Belfon KAA, Raguette L, Huang H, Migues AN, Bickel J, Wang Y, Pincay J, Wu Q, Simmerling C. ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution. J Chem Theory Comput 2019; 16:528-552. [PMID: 31714766 DOI: 10.1021/acs.jctc.9b00591] [Citation(s) in RCA: 780] [Impact Index Per Article: 156.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.
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Affiliation(s)
- Chuan Tian
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Koushik Kasavajhala
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Kellon A A Belfon
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Lauren Raguette
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - He Huang
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Angela N Migues
- Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - John Bickel
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Yuzhang Wang
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Jorge Pincay
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States
| | - Qin Wu
- Center for Functional Nanomaterials , Brookhaven National Laboratory , Upton , New York 11973 , United States
| | - Carlos Simmerling
- Department of Chemistry , Stony Brook University , Stony Brook , New York 11794 , United States.,Laufer Center for Physical and Quantitative Biology , Stony Brook University , Stony Brook , New York 11794 , United States
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35
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Allen AA, Robertson MJ, Payne MC, Cole DJ. Development and Validation of the Quantum Mechanical Bespoke Protein Force Field. ACS OMEGA 2019; 4:14537-14550. [PMID: 31528808 PMCID: PMC6740169 DOI: 10.1021/acsomega.9b01769] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 07/30/2019] [Indexed: 06/10/2023]
Abstract
Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus, they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the quantum mechanical bespoke (QUBE) force field by deriving nonbonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are rederived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE nonbonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, is tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained, and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific nonbonded force field parameters is a promising approach for next-generation simulations of biological molecules.
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Affiliation(s)
- Alice
E. A. Allen
- TCM
Group, Cavendish Laboratory, 19 JJ Thomson Ave, Cambridge CB3 0HE, United Kingdom
| | - Michael J. Robertson
- Department of Molecular and Cellular Physiology and Department of Structural Biology Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, United States
| | - Michael C. Payne
- TCM
Group, Cavendish Laboratory, 19 JJ Thomson Ave, Cambridge CB3 0HE, United Kingdom
| | - Daniel J. Cole
- School
of Natural and Environmental Sciences, Newcastle
University, Newcastle
upon Tyne NE1 7RU, United
Kingdom
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36
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Machado MR, Barrera EE, Klein F, Sóñora M, Silva S, Pantano S. The SIRAH 2.0 Force Field: Altius, Fortius, Citius. J Chem Theory Comput 2019; 15:2719-2733. [PMID: 30810317 DOI: 10.1021/acs.jctc.9b00006] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
A new version of the coarse-grained (CG) SIRAH force field for proteins has been developed. Modifications to bonded and non-bonded interactions on the existing molecular topologies significantly ameliorate the structural description and flexibility of a non-redundant set of proteins. The SIRAH 2.0 force field has also been ported to the popular simulation package AMBER, which along with the former implementation in GROMACS expands significantly the potential range of users and performance of this CG force field on CPU/GPU codes. As a non-trivial example of its application, we undertook the structural and dynamical analysis of the most abundant and conserved calcium-binding protein, calmodulin (CaM). CaM is composed of two calcium-binding motifs called EF-hands, which in the presence of calcium specifically recognize a cognate peptide by embracing it. CG simulations of CaM bound to four calcium ions in the presence or absence of a binding peptide (holo and apo forms, respectively) resulted in good and stable ion coordination. The simulation of the holo form starting from an experimental structure sampled near-native conformations, retrieving quasi-atomistic precision. Removing the binding peptide enabled the EF-hands to perform large reciprocal movements, comparable to those observed in NMR structures. On the other hand, the isolated peptide starting from the helical conformation experienced spontaneous unfolding, in agreement with previous experimental data. However, repositioning the peptide in the neighborhood of one EF-hand not only prevented the peptide from unfolding but also drove CaM to a fully bound conformation, with both EF-hands embracing the cognate peptide, resembling the experimental holo structure. Therefore, SIRAH 2.0 shows the capacity to handle a number of structurally and dynamically challenging situations, including metal ion coordination, unbiased conformational sampling, and specific protein-peptide recognition.
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Affiliation(s)
- Matías R Machado
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
| | - Exequiel E Barrera
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
| | - Florencia Klein
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
| | - Martín Sóñora
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
| | - Steffano Silva
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
| | - Sergio Pantano
- Biomolecular Simulations Group , Institut Pasteur de Montevideo , Mataojo 2020 , CP 11400 Montevideo , Uruguay
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37
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Du S, Fu H, Shao X, Chipot C, Cai W. Addressing Polarization Phenomena in Molecular Machines Containing Transition Metal Ions with an Additive Force Field. J Chem Theory Comput 2019; 15:1841-1847. [DOI: 10.1021/acs.jctc.8b00972] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Affiliation(s)
- Shuangli Du
- Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China
| | - Haohao Fu
- Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China
- Tianjin Key Laboratory of Biosensing and Molecular Recognition, Tianjin 300071, China
- State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin 300071, China
| | - Christophe Chipot
- LPCT, UMR 7019 Université de Lorraine CNRS, F-54506 Vandœuvre-lès-Nancy, France
- Laboratoire International Associé CNRS and University of Illinois at Urbana−Champaign, F-54506 Vandœuvre-lès-Nancy, France
- Department of Physics, University of Illinois at Urbana−Champaign, 1110 West Green Street, Urbana, Illinois 61801, United States
| | - Wensheng Cai
- Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China
- Tianjin Key Laboratory of Biosensing and Molecular Recognition, Tianjin 300071, China
- Collaborative Innovation Center of Chemical Science and Engineering, Tianjin 300071, China
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38
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Abstract
All-atom, classical force fields for protein molecular dynamics (MD) simulations currently occupy a sweet spot in the universe of computational models, sufficiently detailed to be of predictive value in many cases, yet also simple enough that some biologically relevant time scales (microseconds or more) can now be sampled via specialized hardware or enhanced sampling methods. However, due to their long evolutionary history, there is now a myriad of force field branches in current use, which can make it hard for those entering the simulation field to know which would be the best set of parameters for a given application. In this chapter, I try to give an overview of the historical motivation for the different force fields available, suggestions for how to determine the most appropriate model and what to do if the results are in conflict with experimental evidence.
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Affiliation(s)
- Robert B Best
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
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Shao Q, Yang L, Zhu W. Selective enhanced sampling in dihedral energy facilitates overcoming the dihedral energy increase in protein folding and accelerates the searching for protein native structure. Phys Chem Chem Phys 2019; 21:10423-10435. [DOI: 10.1039/c9cp00615j] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A dihedral-energy-based selective enhanced sampling method (D-SITSMD) is presented with improved capabilities for searching a protein's natively folded structure and for providing the underlying folding pathway.
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Affiliation(s)
- Qiang Shao
- Drug Discovery and Design Center
- CAS Key Laboratory of Receptor Research
- Shanghai Institute of Materia Medica
- Chinese Academy of Sciences
- Shanghai
| | - Lijiang Yang
- Beijing National Laboratory for Molecular Sciences
- Beijing
- China
- Institute of Theoretical and Computational Chemistry
- College of Chemistry and Molecular Engineering, and Biodynamic Optical Imaging Center
| | - Weiliang Zhu
- Drug Discovery and Design Center
- CAS Key Laboratory of Receptor Research
- Shanghai Institute of Materia Medica
- Chinese Academy of Sciences
- Shanghai
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40
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Abstract
Accurate and reliable calculation of protein-ligand binding free energy is of central importance in computational biophysics and structure-based drug design. Among the various methods to calculate protein-ligand binding affinities, alchemical free energy perturbation (FEP) calculations performed by way of explicitly solvated molecular dynamics simulations (FEP/MD) provide a thermodynamically rigorous and complete description of the binding event and should in turn yield highly accurate predictions. Although the original theory of FEP was proposed more than 60 years ago, subsequent applications of FEP to compute protein-ligand binding free energies in the context of drug discovery projects over much of that time period was sporadic and generally unsuccessful. This was mainly due to the limited accuracy of the available force fields, inadequate sampling of the protein-ligand conformational space, complexity of simulation set up and analysis, and the large computational resources required to pursue such calculations. Over the past few years, there have been advances in computing power, classical force field accuracy, enhanced sampling algorithms, and simulation setup. This has led to newer FEP implementations such as the FEP+ technology developed by Schrödinger Inc., which has enabled accurate and reliable calculations of protein-ligand binding free energies and positioned free energy calculations to play a guiding role in small-molecule drug discovery. In this chapter, we outline the methodological advances in FEP+, including the OPLS3 force fields, the REST2 (Replica Exchange with Solute Tempering) enhanced sampling, the incorporation of REST2 sampling with conventional FEP (Free Energy Perturbation) through FEP/REST, and the advanced simulation setup and data analysis. The validation of FEP+ method in retrospective studies and the prospective applications in drug discovery projects are also discussed. We then present the recent extension of FEP+ method to handle challenging perturbations, including core-hopping transformations, macrocycle modifications, and reversible covalent inhibitor optimization. The limitations and pitfalls of the current FEP+ methodology and the best practices in real applications are also examined.
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Shao Q, Zhu W. Assessing AMBER force fields for protein folding in an implicit solvent. Phys Chem Chem Phys 2018; 20:7206-7216. [PMID: 29480910 DOI: 10.1039/c7cp08010g] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Molecular dynamics (MD) simulation implemented with a state-of-the-art protein force field and implicit solvent model is an attractive approach to investigate protein folding, one of the most perplexing problems in molecular biology. But how well can force fields developed independently of implicit solvent models work together in reproducing diverse protein native structures and measuring the corresponding folding thermodynamics is not always clear. In this work, we performed enhanced sampling MD simulations to assess the ability of six AMBER force fields (FF99SBildn, FF99SBnmr, FF12SB, FF14ipq, FF14SB, and FF14SBonlysc) as coupled with a recently improved pair-wise GB-Neck2 model in modeling the folding of two helical and two β-sheet peptides. Whilst most of the tested force fields can yield roughly similar features for equilibrium conformational ensembles and detailed folding free-energy profiles for short α-helical TC10b in an implicit solvent, the measured counterparts are significantly discrepant in the cases of larger or β-structured peptides (HP35, 1E0Q, and GTT). Additionally, the calculated folding/unfolding thermodynamic quantities can only partially match the experimental data. Although a combination of the force fields and GB-Neck2 implicit model able to describe all aspects of the folding transitions towards the native structures of all the considered peptides was not identified, we found that FF14SBonlysc coupled with the GB-Neck2 model seems to be a reasonably balanced combination to predict peptide folding preferences.
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Affiliation(s)
- Qiang Shao
- Drug Discovery and Design Center, CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China.
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42
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Anderson J, Lake PT, McCullagh M. Initial Aggregation and Ordering Mechanism of Diphenylalanine from Microsecond All-Atom Molecular Dynamics Simulations. J Phys Chem B 2018; 122:12331-12341. [PMID: 30511861 DOI: 10.1021/acs.jpcb.8b10335] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Self-assembled diphenylalanine (FF) nanostructures have recently been demonstrated to be interesting materials for antibacterial and anticancer applications. These applications, among others, seek to take advantage of the high-order and resulting appealing physical properties of FF nanostructures by modifying the peptide in some way to achieve specific functionality. To rationally design modifications to the dipeptide that allow for this behavior, the driving forces of FF self-assembly must be understood. Molecular simulations have been utilized to assess these properties but have yielded conflicting conclusions due to inconsistencies in models chosen as well as the lack of quantitative analyses on the specific driving forces. Here, we present an all-atom explicit solvent molecular dynamics-based study on different length scales of FF aggregation. We utilize a free energy decomposition analysis as well as a dimer cluster analysis to identify the initial aggregation driving force to be FF intermolecular electrostatics, whereas solvent-mediated forces drive crystal growth. These data are consistent with the hypothesis that all hydrophobic dipeptides will have a similar initial aggregation mechanism until a critical aggregate size is reached, at which point crystallization occurs and subsequent crystal growth is dominated by solvent-mediated forces. We demonstrate that this proposed mechanism is testable by infrared spectroscopy focusing on the blueshift of the amide I peak as well as the ordering of the carboxylate peak.
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Affiliation(s)
- Jakob Anderson
- Department of Chemistry , Colorado State University , Fort Collins , Colorado 80523 , United States
| | - Peter T Lake
- Department of Chemistry , Colorado State University , Fort Collins , Colorado 80523 , United States
| | - Martin McCullagh
- Department of Chemistry , Colorado State University , Fort Collins , Colorado 80523 , United States
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43
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Hagler AT. Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics. J Comput Aided Mol Des 2018; 33:205-264. [DOI: 10.1007/s10822-018-0134-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 07/18/2018] [Indexed: 01/04/2023]
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44
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Valenzuela-Riffo F, Gaete-Eastman C, Stappung Y, Lizana R, Herrera R, Moya-León MA, Morales-Quintana L. Comparative in silico study of the differences in the structure and ligand interaction properties of three alpha-expansin proteins from Fragaria chiloensis fruit. J Biomol Struct Dyn 2018; 37:3245-3258. [PMID: 30175949 DOI: 10.1080/07391102.2018.1517610] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Expansins are cell wall proteins associated with several processes, including changes in the cell wall during ripening of fruit, which matches softening of the fruit. We have previously reported an increase in expression of specific expansins transcripts during softening of Fragaria chiloensis fruit. Here, we characterized three α-expansins. Their full-length sequences were obtained, and through qRT-PCR (real-time PCR) analyses, their transcript accumulation during softening of F. chiloensis fruit was confirmed. Interestingly, differential but overlapping expression patterns were observed. With the aim of elucidating their roles, 3D protein models were built using comparative modeling methodology. The models obtained were similar and displayed cellulose binding module(CBM ) with a β-sandwich structure, and a catalytic domain comparable to the catalytic core of protein of the family 45 glycosyl hydrolase. An open groove located at the central part of each expansin was described; however, the shape and size are different. Their protein-ligand interactions were evaluated, showing favorable binding affinity energies with xyloglucan, homogalacturonan, and cellulose, cellulose being the best ligand. However, small differences were observed between the protein-ligand conformations. Molecular mechanics-generalized Born-surface area (MM-GBSA) analyses indicate the major contribution of van der Waals forces and non-polar interactions. The data provide a dynamic view of interaction between expansins and cellulose as putative cell wall ligands at the molecular scale. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Felipe Valenzuela-Riffo
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile.,b Phytohormone Research Laboratory , Instituto de Ciencias Biológicas, Universidad de Talca , Talca , Chile
| | - Carlos Gaete-Eastman
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile
| | - Yazmina Stappung
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile
| | - Rodrigo Lizana
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile
| | - Raúl Herrera
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile
| | - María Alejandra Moya-León
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile
| | - Luis Morales-Quintana
- a Functional genomics, biochemistry and plant physiology group , Instituto de Ciencias Biológicas , Universidad de Talca , Talca , Chile.,c Multidisciplinary Agroindustry Research Laboratory , Carrera de Ingeniería en Informática, Universidad Autónoma de Chile , Talca , Chile.,d Instituto de Ciencias Biomédicas , Universidad Autónoma de Chile Sede Talca , Talca , del Maule , Chile
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45
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Joseph JA, Wales DJ. Intrinsically Disordered Landscapes for Human CD4 Receptor Peptide. J Phys Chem B 2018; 122:11906-11921. [DOI: 10.1021/acs.jpcb.8b08371] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Affiliation(s)
- Jerelle A. Joseph
- Department of Chemistry, University of Cambridge, Lenfield Road, Cambridge CB2 1EW, United Kingdom
| | - David J. Wales
- Department of Chemistry, University of Cambridge, Lenfield Road, Cambridge CB2 1EW, United Kingdom
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46
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Ghahremanpour MM, van Maaren PJ, Caleman C, Hutchison GR, van der Spoel D. Polarizable Drude Model with s-Type Gaussian or Slater Charge Density for General Molecular Mechanics Force Fields. J Chem Theory Comput 2018; 14:5553-5566. [PMID: 30281307 DOI: 10.1021/acs.jctc.8b00430] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Gas-phase electric properties of molecules can be computed routinely using wave function methods or density functional theory (DFT). However, these methods remain computationally expensive for high-throughput screening of the vast chemical space of virtual compounds. Therefore, empirical force fields are a more practical choice in many cases, particularly since force field methods allow one to routinely predict the physicochemical properties in the condensed phases. This work presents Drude polarizable models, to increase the physical realism in empirical force fields, where the core particle is treated as a point charge and the Drude particle is treated either as a 1 s-Gaussian or a ns-Slater ( n = 1, 2, 3) charge density. Systematic parametrization to large high-quality quantum chemistry data obtained from the open access Alexandria Library ( https://doi.org/10.5281/zenodo.1004711 ) ensures the transferability of these parameters. The dipole moments and isotropic polarizabilities of the isolated molecules predicted by the proposed Drude models are in agreement with experiment with accuracy similar to DFT calculations at the B3LYP/aug-cc-pVTZ level of theory. The results show that the inclusion of explicit polarization into the models reduces the root-mean-square deviation with respect to DFT calculations of the predicted dipole moments of 152 dimers and clusters by more than 50%. Finally, we show that the accuracy of the electrostatic interaction energy of the water dimers can be improved systematically by the introduction of polarizable smeared charges as a model for charge penetration.
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Affiliation(s)
- Mohammad Mehdi Ghahremanpour
- Uppsala Center for Computational Chemistry, Department of Cell and Molecular Biology , Uppsala University , Husargatan 3 , Box 596, SE-75124 Uppsala , Sweden
| | - Paul J van Maaren
- Uppsala Center for Computational Chemistry, Department of Cell and Molecular Biology , Uppsala University , Husargatan 3 , Box 596, SE-75124 Uppsala , Sweden
| | - Carl Caleman
- Department of Physics and Astronomy , Uppsala University , Box 516, SE-75120 Uppsala , Sweden.,Center for Free-Electron Laser Science , Deutsches Elektronen-Synchrotron , DE-22607 Hamburg , Germany
| | - Geoffrey R Hutchison
- Department of Chemistry , University of Pittsburgh , Pittsburgh , Pennsylvania 15260 , United States
| | - David van der Spoel
- Uppsala Center for Computational Chemistry, Department of Cell and Molecular Biology , Uppsala University , Husargatan 3 , Box 596, SE-75124 Uppsala , Sweden
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47
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Thapa B, Beckett D, Erickson J, Raghavachari K. Theoretical Study of Protein–Ligand Interactions Using the Molecules-in-Molecules Fragmentation-Based Method. J Chem Theory Comput 2018; 14:5143-5155. [DOI: 10.1021/acs.jctc.8b00531] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Bishnu Thapa
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Daniel Beckett
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
| | - Jon Erickson
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, Indiana 47285, United States
| | - Krishnan Raghavachari
- Department of Chemistry, Indiana University, Bloomington, Indiana 47405, United States
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48
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Riquelme M, Lara A, Mobley DL, Verstraelen T, Matamala AR, Vöhringer-Martinez E. Hydration Free Energies in the FreeSolv Database Calculated with Polarized Iterative Hirshfeld Charges. J Chem Inf Model 2018; 58:1779-1797. [PMID: 30125107 PMCID: PMC6195221 DOI: 10.1021/acs.jcim.8b00180] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Computer simulations of biomolecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in biomolecular systems and are therein described by atomic point charges. In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model, and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the AM1-BCC and the MBIS atomic charge methods. The latter includes the solvent polarization and presents a root-mean-square error of 2.0 kcal mol-1 for the 613 organic molecules studied. The largest deviation was observed for phosphorus-containing molecules and the molecules with amide, ester and amine functional groups.
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Affiliation(s)
- Maximiliano Riquelme
- Departamento de Físico-Química, Facultad de Ciencias Químicas , Universidad de Concepción , 4070386 Concepción , Chile
| | - Alejandro Lara
- Departamento de Físico-Química, Facultad de Ciencias Químicas , Universidad de Concepción , 4070386 Concepción , Chile
| | - David L Mobley
- Departments of Pharmaceutical Sciences and Chemistry, 147 Bison Modular , University of California, Irvine , Irvine , California 92617 , United States
| | - Toon Verstraelen
- Center for Molecular Modeling (CMM) , Ghent University , Technologiepark 903 , B-9052 Ghent , Belgium
| | - Adelio R Matamala
- Departamento de Físico-Química, Facultad de Ciencias Químicas , Universidad de Concepción , 4070386 Concepción , Chile
| | - Esteban Vöhringer-Martinez
- Departamento de Físico-Química, Facultad de Ciencias Químicas , Universidad de Concepción , 4070386 Concepción , Chile
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49
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Zhang H, Jiang Y, Cui Z, Yin C. Force Field Benchmark of Amino Acids. 2. Partition Coefficients between Water and Organic Solvents. J Chem Inf Model 2018; 58:1669-1681. [DOI: 10.1021/acs.jcim.8b00493] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
| | - Yang Jiang
- Beijing Key Lab of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Box 53, 100029 Beijing, China
| | - Ziheng Cui
- Beijing Key Lab of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Box 53, 100029 Beijing, China
| | - Chunhua Yin
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, 100083 Beijing, China
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50
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Cerutti DS, Debiec KT, Case DA, Chong LT. Links between the charge model and bonded parameter force constants in biomolecular force fields. J Chem Phys 2018; 147:161730. [PMID: 29096508 DOI: 10.1063/1.4985866] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The ff15ipq protein force field is a fixed charge model built by automated tools based on the two charge sets of the implicitly polarized charge method: one set (appropriate for vacuum) for deriving bonded parameters and the other (appropriate for aqueous solution) for running simulations. The duality is intended to treat water-induced electronic polarization with an understanding that fitting data for bonded parameters will come from quantum mechanical calculations in the gas phase. In this study, we compare ff15ipq to two alternatives produced with the same fitting software and a further expanded data set but following more conventional methods for tailoring bonded parameters (harmonic angle terms and torsion potentials) to the charge model. First, ff15ipq-Qsolv derives bonded parameters in the context of the ff15ipq solution phase charge set. Second, ff15ipq-Vac takes ff15ipq's bonded parameters and runs simulations with the vacuum phase charge set used to derive those parameters. The IPolQ charge model and associated protocol for deriving bonded parameters are shown to be an incremental improvement over protocols that do not account for the material phases of each source of their fitting data. Both force fields incorporating the polarized charge set depict stable globular proteins and have varying degrees of success modeling the metastability of short (5-19 residues) peptides. In this particular case, ff15ipq-Qsolv increases stability in a number of α-helices, correctly obtaining 70% helical character in the K19 system at 275 K and showing appropriately diminishing content up to 325 K, but overestimating the helical fraction of AAQAA3 by 50% or more, forming long-lived α-helices in simulations of a β-hairpin, and increasing the likelihood that the disordered p53 N-terminal peptide will also form a helix. This may indicate a systematic bias imparted by the ff15ipq-Qsolv parameter development strategy, which has the hallmarks of strategies used to develop other popular force fields, and may explain some of the need for manual corrections in this force fields' evolution. In contrast, ff15ipq-Vac incorrectly depicts globular protein unfolding in numerous systems tested, including Trp cage, villin, lysozyme, and GB3, and does not perform any better than ff15ipq or ff15ipq-Qsolv in tests on short peptides. We analyze the free energy surfaces of individual amino acid dipeptides and the electrostatic potential energy surfaces of each charge model to explain the differences.
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Affiliation(s)
- David S Cerutti
- Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghueysen Road, Piscataway, New Jersey 08854-8066, USA
| | - Karl T Debiec
- Epic Systems, 1979 Milky Way, Verona, Wisconsin 53593, USA
| | - David A Case
- Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghueysen Road, Piscataway, New Jersey 08854-8066, USA
| | - Lillian T Chong
- Department of Chemistry, University of Pittsburgh, 219 Parkman Avenue, Pittsburgh, Pennsylvania 15260, USA
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