1
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Lou H, Wu Y, Kuczera K, Schöneich C. Coarse-Grained Molecular Dynamics Simulation of Heterogeneous Polysorbate 80 Surfactants and their Interactions with Small Molecules and Proteins. Mol Pharm 2024; 21:5041-5052. [PMID: 39208298 DOI: 10.1021/acs.molpharmaceut.4c00461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Polysorbate 80 (PS80) is widely used in pharmaceutical formulations, and its commercial grades exhibit certain levels of structural heterogeneity. The objective of this study was to apply coarse-grained molecular dynamics simulations to better understand the effect of PS80 heterogeneity on micelle self-assembly, the loading of hydrophobic small molecules into the micelle core, and the interactions between PS80 and a protein, bovine serum albumin (BSA). Four representative PS80 variants with different head and tail structures were studied. Our simulations found that PS80 structural heterogeneity could affect blank micelle properties such as solvent-accessible surface area, aggregation number, and micelle aspect ratio. It was also found that hydrophobic small molecules such as ethinyl estradiol preferentially partitioned into the PS80 micelle core and PS80 dioleates formed a more hydrophobic core compared to PS80 monooleates. Furthermore, multiple PS80 molecules could bind to BSA, and PS80 heterogeneity profoundly changed the binding ratio as well as the surfactant-protein contact area.
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Affiliation(s)
- Hao Lou
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
| | - Yaqi Wu
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
| | - Krzysztof Kuczera
- Department of Chemistry, University of Kansas, Lawrence, Kansas 66045, United States
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas 66045, United States
| | - Christian Schöneich
- Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, Kansas 66047, United States
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2
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Mohimont F, Rieger J, Stoffelbach F. Synthesis of New Glycine-Based Polymers and their Thermoresponsive Behavior in Water. Macromol Rapid Commun 2024; 45:e2400286. [PMID: 38851296 DOI: 10.1002/marc.202400286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/04/2024] [Indexed: 06/10/2024]
Abstract
In this work, new glycine-derived polymers are developed that exhibit thermoresponsive properties in water. Therefore, a series of monomers containing one, two, or three amide functional groups and one terminal cyanomethyl group is synthesized. The resulting homopolymers, obtained by free radical polymerization (FRP) and reversible addition fragmentation chain transfer (RAFT) polymerization, display a sharp and reversible upper critical solution temperature (UCST)-type phase transition in water. Additionally, it is shown that the cloud point (TCP) can be adjusted over more than 60 °C by the number of glycyl groups present in the monomer structure and by the polymer's molar mass. These novel thermoresponsive polymers based on cyanomethylglycinamide enrich the range of nonionic UCST polymers and are promising to find applications in various fields.
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Affiliation(s)
- Florent Mohimont
- Sorbonne Université, CNRS, UMR 8232, Institut Parisien de Chimie Moléculaire (IPCM), Polymer Chemistry Team, 4 Place Jussieu, Cedex 05, Paris, 75252, France
| | - Jutta Rieger
- Sorbonne Université, CNRS, UMR 8232, Institut Parisien de Chimie Moléculaire (IPCM), Polymer Chemistry Team, 4 Place Jussieu, Cedex 05, Paris, 75252, France
| | - François Stoffelbach
- Sorbonne Université, CNRS, UMR 8232, Institut Parisien de Chimie Moléculaire (IPCM), Polymer Chemistry Team, 4 Place Jussieu, Cedex 05, Paris, 75252, France
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3
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Díaz-Salazar AJ, Espinosa-Roa A, Saldívar-Guerra E, Pérez-Isidoro R. The disordering effect of SARMs on a biomembrane model. Phys Chem Chem Phys 2024. [PMID: 39040033 DOI: 10.1039/d4cp01002g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
From medicine to sport, selective androgen receptor modulators (SARMs) have represented promising applications. The ability of SARMs to selectively interact with the androgen receptor (AR) indicates that this kind of molecule can interfere with numerous physiological and pathological processes controlled by the AR regulatory mechanism. However, critical concerns in relation to safety and potential side effects of SARMs remain under discussion and investigation. SARMs, being hydrophobic/organic compounds, can be subjected to hydrophobic interactions. In this perspective, we hypothesize that SARMs interact with lipid membranes, producing significant physical and chemical changes that could be associated with several effects that SARMs represent in biological systems. In this context, the effect of SARMs on lipid membranes mediated by non-specific interactions is little explored. Here, we report significant information related to the changes that ostarine, ligandrol, andarine, and cardarine produce in the thermodynamic properties of a lipid biomembrane model. Physical changes and chemical interactions of the systems were investigated by differential scanning calorimetry (DSC), dynamic light scattering (DLS), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and theoretical calculations implementing density functional theory (DFT). We demonstrate that ostarine, ligandrol, andarine, and cardarine can strongly interact with a lipid biomembrane model composed of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and accordingly, these molecules can be incorporated into the polar/hydrophobic regions of the lipid bilayer. By employing theoretical calculations, we gained insights into the possible electrostatic interactions between SARMs and phospholipid molecules, enhancing our understanding of the driving forces behind the interactions of SARMs with lipid membranes. Overall, this investigation provides relevant knowledge related to the biophysical-chemical effects that SARMs produce in biomembrane models and could be of practical reference for promising applications of SARMs in medicine and sport.
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Affiliation(s)
- Alma Jessica Díaz-Salazar
- Laboratorio de Bio-fisicoquímica. Departamento de Fisicoquímica, Facultad de Química, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
| | - Arián Espinosa-Roa
- CONAHCyT-Centro de Investigación en Química Aplicada (CIQA), Unidad Monterrey. Alianza Sur no. 204, Parque de Investigación en Innovación Tecnológica (PIIT), km 10 autopista internacional Mariano Escobedo, C.P. 66628, Apodaca, Nuevo León, Mexico.
| | - Enrique Saldívar-Guerra
- Centro de Investigación en Química Aplicada (CIQA), Enrique Reyna, 140, 25294 Saltillo Coahuila, Mexico.
| | - Rosendo Pérez-Isidoro
- Centro de Investigación en Química Aplicada (CIQA), Enrique Reyna, 140, 25294 Saltillo Coahuila, Mexico.
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4
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Bursik B, Eller J, Gross J. Predicting Solvation Free Energies from the Minnesota Solvation Database Using Classical Density Functional Theory Based on the PC-SAFT Equation of State. J Phys Chem B 2024; 128:3677-3688. [PMID: 38579126 DOI: 10.1021/acs.jpcb.3c07447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2024]
Abstract
We critically assess the capabilities of classical density functional theory (DFT) based on the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state to predict the solvation free energies of small molecules in various hydrocarbon solvents. We compare DFT results with experimental data from the Minnesota solvation database and utilize statistical methods to analyze the accuracy of our approach, as well as its weaknesses. The mean absolute error of the solvation free energies is 3.7 kJ mol-1 for n-alkane solvents, ranging from pentane to hexadecane, with 473 solute-solvent systems. For solvents consisting of cyclic hydrocarbons (cyclohexane, benzene, toluene, and ethylbenzene) with 245 solute-solvent systems, we report a slightly larger mean absolute error of 4.2 kJ mol-1. We identify three possible sources of errors: (i) the neglect of solute-solvent and solvent-solvent Coulomb interactions, which limits the applicability of PC-SAFT DFT to nonpolar and weakly polar molecules; (ii) the solute's Lennard-Jones parameters supplied by the general AMBER force field, which are not parametrized toward solvation free energies; and (iii) the application of the Lorentz-Berthelot combining rules to the dispersive interactions between a segment of the PC-SAFT solvent and a Lennard-Jones interaction site of the solute. The approach is more accurate than standard implementations of phenomenological models in common chemistry software packages, which exhibit mean absolute errors larger than 9.12 kJ mol-1, even though newer phenomenological models achieve a mean absolute error of about 2 kJ mol-1. PC-SAFT DFT is more computationally efficient than state of the art explicit molecular simulations in combination with free energy perturbation methods. It is predictive with respect to solvation free energies, i.e., the input for the model is the (element-specific) molecular force field, the solute configuration from molecular dynamics simulations, and the (substance-specific) PC-SAFT parameters. The PC-SAFT parametrization uses pure-component data and does not require experimental solvation free energies. The PC-SAFT equation of state, without applying a DFT formalism, can also be used to calculate solvation free energies, provided that the PC-SAFT parameters for the solute are available. A large number of substances was recently parametrized by members of our group (Esper, T.; Bauer, G.; Rehner, P.; Gross, J. Ind. Eng. Chem. Res. 2023, 62), which enables a comparison to the DFT approach for 103 substances. Accurate results are obtained from the PC-SAFT equation of state with an MAE below 2.51 kJ mol-1. The DFT approach does not require PC-SAFT parameters for the solute and can be applied to all solutes that can be represented by the molecular force field.
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Affiliation(s)
- Benjamin Bursik
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Stuttgart 70569, Germany
| | - Johannes Eller
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Stuttgart 70569, Germany
| | - Joachim Gross
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Stuttgart 70569, Germany
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5
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Magadla A, Mpeta LS, Britton J, Nyokong T. Photodynamic antimicrobial chemotherapy activities of phthalocyanine-antibiotic conjugates against bacterial biofilms and interactions with extracellular polymeric substances. Photodiagnosis Photodyn Ther 2023; 44:103878. [PMID: 37918559 DOI: 10.1016/j.pdpdt.2023.103878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/18/2023] [Accepted: 10/31/2023] [Indexed: 11/04/2023]
Abstract
This study sheds light on how to rationally design efficient photodynamic antimicrobial chemotherapy (PACT) agents by covalently linking phthalocyanines (Pcs) as photosensitizers with an antibiotic: Ciprofloxacin (CIP). Pcs used are zinc (II) 3-(4-((3,17,23-tris(4-(Benzo(d)thiazol-2-yl] thiol) phthalocyanine-9-yl) oxy) phenyl) propanoic acid (1) and zinc (II) 3-(4-(3,17,23-tris(3-(4-(triphenylphosphine) butyl) benzo[d]thiazol-3-ium bromide phthalocyanine-9-yl) oxy) phenyl) propanoic acid (2). High singlet oxygen quantum yields are observed in the presence of CIP. Square wave voltammetry was used to analyse the Pc-CIP uptake by bacteria biofilms of Streptococcus pneumoniae (S. pneumonia) and Escherichia coli (E. coli). Electrochemical impedance spectroscopy and scanning electron spectroscopy were used to study the stability of the biofilms in the presence Pc-CIP complexes and when exposed to light. Raman and time of flight-secondary ion mass spectrometry (TOF-SIMS) are used to identify the breakdown of cellular components of the biofilm and penetration of the Pc-CIP into the biofilms, respectively.
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Affiliation(s)
- Aviwe Magadla
- Institute for Nanotechnology Innovation, Rhodes University, Makhanda 6140, South Africa
| | - Lekhetho S Mpeta
- Institute for Nanotechnology Innovation, Rhodes University, Makhanda 6140, South Africa
| | - Jonathan Britton
- Institute for Nanotechnology Innovation, Rhodes University, Makhanda 6140, South Africa
| | - Tebello Nyokong
- Institute for Nanotechnology Innovation, Rhodes University, Makhanda 6140, South Africa.
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6
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Gheta SKO, Bonin A, Gerlach T, Göller AH. Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state. J Comput Aided Mol Des 2023; 37:765-789. [PMID: 37878216 DOI: 10.1007/s10822-023-00538-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/02/2023] [Indexed: 10/26/2023]
Abstract
In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to predict the absolute solubility of drug-like compounds. The QM-derived descriptors account for the molecular properties of the solute, i.e., the solute-solute interactions in an artificial-liquid-state (super-cooled liquid), and the solute-solvent interactions in solution. We employ two main approaches to predict solubility: (i) a hypothetical pathway that involves melting the solute at room temperature T = T¯ ([Formula: see text]) and mixing the artificially liquid solute into the solvent ([Formula: see text]). In this approach [Formula: see text] is predicted using machine learning models, and the [Formula: see text] is obtained from COSMO-RS calculations; (ii) direct solubility prediction using machine learning algorithms. The models were trained on a large number of Bayer in-house compounds for which water solubility data is available at physiological pH of 6.5 and ambient temperature. We also evaluated our models using external datasets from a solubility challenge. Our models present great improvements compared to the absolute solubility prediction with the QSAR model for the artificial liquid state as implemented in the COSMOtherm software, for both in-house and external datasets. We are furthermore able to demonstrate the superiority of QM-derived descriptors compared to cheminformatics descriptors. We finally present low-cost alternative models using fragment-based COSMOquick calculations with only marginal reduction in the quality of predicted solubility.
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Affiliation(s)
- Sadra Kashef Ol Gheta
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany
| | - Anne Bonin
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany
| | - Thomas Gerlach
- Bayer AG, Crop Science, R&D, Digital Transformation, 40789, Monheim, Germany
- Bayer AG, Engineering & Technology, Thermal Separation Technologies, 51368, Leverkusen, Germany
| | - Andreas H Göller
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany.
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7
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Xia S, Chen E, Zhang Y. Integrated Molecular Modeling and Machine Learning for Drug Design. J Chem Theory Comput 2023; 19:7478-7495. [PMID: 37883810 PMCID: PMC10653122 DOI: 10.1021/acs.jctc.3c00814] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023]
Abstract
Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on molecular mechanics optimized geometries. Meanwhile, we discuss remaining challenges and promising directions for further development and use a retrospective example of FDA approved kinase inhibitor Erlotinib to demonstrate the use of these newly developed computational tools.
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Affiliation(s)
- Song Xia
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Eric Chen
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Yingkai Zhang
- Department
of Chemistry, New York University, New York, New York 10003, United States
- Simons
Center for Computational Physical Chemistry at New York University, New York, New York 10003, United States
- NYU-ECNU
Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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8
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Ali HS, Henchman RH. Energy-entropy multiscale cell correlation method to predict toluene-water log P in the SAMPL9 challenge. Phys Chem Chem Phys 2023; 25:27524-27531. [PMID: 37800345 PMCID: PMC11411597 DOI: 10.1039/d3cp03076h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
The energy-entropy multiscale cell correlation (EE-MCC) method is used to calculate toluene-water log P values of 16 drug molecules in the SAMPL9 physical properties challenge. EE-MCC calculates the free energy, energy and entropy from molecular dynamics (MD) simulations of the water and toluene solutions. Specifically, MCC evaluates entropy by partitioning the system into cells of correlated atoms at multiple length scales and further partitioning the local coordinates into energy wells, yielding vibrational and topographical terms from the energy-well sizes and probabilities. The log P values calculated by EE-MCC using three 200 ns MD simulations have a mean average error of 0.82 and standard error of the mean of 0.97 versus experiment, which is comparable with the best methods entered in SAMPL9. The main contribution to log P is from energy. Less polar drugs have more favourable energies of transfer. The entropy of transfer consists of increased solute vibrational and conformational terms in toluene due to weaker interactions, fewer solute positions in the larger-molecule solvent, reduced water vibrational entropy, negligible change in toluene vibrational entropy, and gains in solvent orientational entropy. The solvent entropy contributions here may be slightly underestimated because software limitations and statistical fluctuations meant that only the first shell could be included while averaged over the whole solution. Nonetheless, such issues will be addressed in future software to offer a general method to calculate entropy directly from MD simulation and to provide molecular understanding or guide system design.
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Affiliation(s)
- Hafiz Saqib Ali
- Chemistry Research Laboratory, Department of Chemistry and the INEOS Oxford Institute for Antimicrobial Research, University of Oxford, 12 Mansfield Road, Oxford OX1 3TA, UK.
| | - Richard H Henchman
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
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9
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Anjos LRBD, Costa VAF, Neves BJ, Junqueira-Kipnis AP, Kipnis A. Repurposing miconazole and tamoxifen for the treatment of Mycobacterium abscessus complex infections through in silico chemogenomics approach. World J Microbiol Biotechnol 2023; 39:273. [PMID: 37553519 DOI: 10.1007/s11274-023-03718-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 07/28/2023] [Indexed: 08/10/2023]
Abstract
Drug repositioning is an alternative to overcome the complexity of the drug discovery and approval procedures for the treatment of Mycobacterium abscessus Complex (MABSC) infections that are increasing globally due to the emergency of antimicrobial resistance mechanisms. Here, an in silico chemogenomics approach was performed to compare the sequences from 4942 M. abscessus subsp. abscessus (M. abscessus) proteins with 5258 or 3473 therapeutic targets registered in the DrugBank or Therapeutic Target Database, respectively. This comparison identified 446 drugs or drug candidates whose targets were homologous to M. abscessus proteins. These identified drugs were considered potential inhibitors of MABSC (anti-MABSC activity). Further screening and inspection resulted in the selection of ezetimibe, furosemide, itraconazole, miconazole (MCZ), tamoxifen (TAM), and thiabendazole (THI) for experimental validation. Among them, MCZ and TAM showed minimum inhibitory concentrations (MIC) of 32 and 24 µg mL-1 against M. abscessus, respectively. For M. bolletii and M. massiliense strains, MCZ and TAM showed MICs of 16 and 24 µg mL-1, in this order. Subsequently, the antibacterial activity of MCZ was confirmed in vivo, indicating its potential to reduce the bacterial load in the lungs of infected mice. These results show that MCZ and TAM can serve as molecular scaffolds for the prospective hit-2-lead optimization of new analogs with greater potency, selectivity, and permeability.
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Affiliation(s)
| | | | - Bruno Junior Neves
- Faculty of Pharmacy, Laboratory of Cheminformatics (LabChem), Federal University of Goiás, Goiânia, Goiás, Brazil
| | | | - André Kipnis
- Department of Biosciences and Technology, Federal University of Goiás, Goiânia, Goiás, Brazil.
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10
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Zamora WJ, Viayna A, Pinheiro S, Curutchet C, Bisbal L, Ruiz R, Ràfols C, Luque FJ. Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models. Phys Chem Chem Phys 2023. [PMID: 37376995 DOI: 10.1039/d3cp01428b] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds. Thus, the difference between n-octanol/water and toluene/water partition coefficients has proven to be a valuable descriptor to study the propensity of molecules to form intramolecular hydrogen bonds and exhibit chameleon-like properties that modulate solubility and permeability. In this context, this study reports the experimental toluene/water partition coefficients (log Ptol/w) for a series of 16 drugs that were selected as an external test set in the framework of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind challenge. This external set has been used by the computational community to calibrate their methods in the current edition (SAMPL9) of this contest. Furthermore, the study also investigates the performance of two computational strategies for the prediction of log Ptol/w. The first relies on the development of two machine learning (ML) models, which are built up by combining the selection of 11 molecular descriptors in conjunction with either the multiple linear regression (MLR) or the random forest regression (RFR) model to target a dataset of 252 experimental log Ptol/w values. The second consists of the parametrization of the IEF-PCM/MST continuum solvation model from B3LYP/6-31G(d) calculations to predict the solvation free energies of 163 compounds in toluene and benzene. The performance of the ML and IEF-PCM/MST models has been calibrated against external test sets, including the compounds that define the SAMPL9 log Ptol/w challenge. The results are used to discuss the merits and weaknesses of the two computational approaches.
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Affiliation(s)
- William J Zamora
- CBio3 Laboratory, School of Chemistry, University of Costa Rica, San Pedro, San José, Costa Rica.
- Laboratory of Computational Toxicology and Artificial Intelligence (LaToxCIA), Biological Testing Laboratory (LEBi), University of Costa Rica, San Pedro, San José, Costa Rica
- Advanced Computing Lab (CNCA), National High Technology Center (CeNAT), Pavas, San José, Costa Rica
| | - Antonio Viayna
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), Av. Prat de la Riba 171, 08921 Santa Coloma de Gramenet, Spain.
- Institut de Biomedicina (IBUB), Universitat de Barcelona (UB), Barcelona, Spain
- Institut de Química Teòrica i Computacional (IQTC-UB), Universitat de Barcelona (UB), Barcelona, Spain
| | - Silvana Pinheiro
- CBio3 Laboratory, School of Chemistry, University of Costa Rica, San Pedro, San José, Costa Rica.
- Laboratory of Computational Toxicology and Artificial Intelligence (LaToxCIA), Biological Testing Laboratory (LEBi), University of Costa Rica, San Pedro, San José, Costa Rica
| | - Carles Curutchet
- Institut de Química Teòrica i Computacional (IQTC-UB), Universitat de Barcelona (UB), Barcelona, Spain
- Departament de Farmàcia i Tecnologia Farmacèutica, i Fisicoquímica, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), Av. Joan XXIII 27-31, 08028, Barcelona, Spain
| | - Laia Bisbal
- Institut de Biomedicina (IBUB), Universitat de Barcelona (UB), Barcelona, Spain
- Departament d'Enginyeria Química i Química Analítica, Universitat de Barcelona (UB), Martí i Franquès 1-11, 08028 Barcelona, Spain.
| | - Rebeca Ruiz
- Pion Inc., Forest Row Business Park, Forest Row RH18 5DW, UK
| | - Clara Ràfols
- Institut de Biomedicina (IBUB), Universitat de Barcelona (UB), Barcelona, Spain
- Departament d'Enginyeria Química i Química Analítica, Universitat de Barcelona (UB), Martí i Franquès 1-11, 08028 Barcelona, Spain.
| | - F Javier Luque
- Departament de Nutrició, Ciències de l'Alimentació i Gastronomia, Facultat de Farmàcia i Ciències de l'Alimentació, Universitat de Barcelona (UB), Av. Prat de la Riba 171, 08921 Santa Coloma de Gramenet, Spain.
- Institut de Biomedicina (IBUB), Universitat de Barcelona (UB), Barcelona, Spain
- Institut de Química Teòrica i Computacional (IQTC-UB), Universitat de Barcelona (UB), Barcelona, Spain
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11
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Wang N, DeFever RS, Maginn EJ. Alchemical Free Energy and Hamiltonian Replica Exchange Molecular Dynamics to Compute Hydrofluorocarbon Isotherms in Imidazolium-Based Ionic Liquids. J Chem Theory Comput 2023. [PMID: 37195874 DOI: 10.1021/acs.jctc.3c00206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Ionic liquids (ILs) have shown promise for applications that leverage differential gas solubility in an IL solvent, e.g., gas separations. Although most available literature provides Henry's law constants, the ability to efficiently estimate full isotherms is important for engineering design calculations. Molecular simulation can be used as a tool to predict full isotherms of gas in ILs. However, particle insertions or deletions in a charge-dense IL medium and the sluggish conformational dynamics of ILs present two sampling challenges for these systems. We therefore devised a method that uses Hamiltonian replica exchange (HREX) molecular dynamics (MD) combined with alchemical free energy calculations to compute full solubility isotherms of two different hydrofluorocarbons (HFCs) in imidazolium-based IL binary mixtures. This workflow is significantly faster than the Gibbs ensemble Monte Carlo (GEMC) simulations which fail to deal with the slow conformational relaxation caused by the sluggish dynamics of ILs. Multiple free energy estimators, including thermodynamic integration, free energy perturbation, and multistate Bennett acceptance ratio method, provided consistent results. Overall, the simulated Henry's law constant, isotherm curvature, and solubility trends match experimental results reasonably well. We close by calculating the full solubility isotherms of two HFCs in IL mixtures that have not been reported in the literature, demonstrating the potential of this method to be used for solubility prediction and setting the stage for future computational screening studies that search for the "best" IL to separate azeotropic HFC mixtures.
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Affiliation(s)
- Ning Wang
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Ryan S DeFever
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - Edward J Maginn
- Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, Indiana 46556, United States
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12
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Gul G, Faller R, Ileri-Ercan N. Coarse-grained modeling of polystyrene-modified CNTs and their interactions with lipid bilayers. Biophys J 2023; 122:1748-1761. [PMID: 37056052 PMCID: PMC10209035 DOI: 10.1016/j.bpj.2023.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/31/2023] [Accepted: 04/05/2023] [Indexed: 04/15/2023] Open
Abstract
In the present work, we describe Martini3 coarse-grained models of polystyrene and carboxyl-terminated polystyrene functionalized carbon nanotubes (CNTs) and investigate their interactions with lipid bilayers with and without cholesterol (CHOL) using molecular dynamics simulations. By changing the polystyrene chain length and grafting density at the end ring of the CNTs at two different nanotube concentrations, we observe the translocation of nanoparticles as well as changes in the lipid bilayer properties. Our results show that all developed models passively diffuse into the membranes without causing any damage to the membrane integrity, although high concentrations of CNTs induce structural and elastic changes in lipid bilayers. In the presence of CHOL, increasing CNT concentration results in decreased rates of CHOL transmembrane motions. On the other hand, CNTs are prone to lipid and polystyrene blockage, which affects their equilibrated configurations, and tilting behavior within the membranes. Hence, we demonstrate that polystyrene-functionalized CNTs are promising drug-carrier agents. However, polystyrene chain length and grafting density are important factors to consider to enhance the efficiency of drug delivery.
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Affiliation(s)
- Gulsah Gul
- Department of Chemical Engineering, Bogazici University, Istanbul, Turkey; Department of Chemical Engineering, University of California, Davis, Davis, California
| | - Roland Faller
- Department of Chemical Engineering, University of California, Davis, Davis, California
| | - Nazar Ileri-Ercan
- Department of Chemical Engineering, Bogazici University, Istanbul, Turkey.
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13
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Sun Y, Hou T, He X, Man VH, Wang J. Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method. J Comput Chem 2023; 44:1300-1311. [PMID: 36820817 PMCID: PMC10101867 DOI: 10.1002/jcc.27086] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/16/2022] [Accepted: 01/29/2023] [Indexed: 02/24/2023]
Abstract
The logarithm of n-octanol-water partition coefficient (logP) is frequently used as an indicator of lipophilicity in drug discovery, which has substantial impacts on the absorption, distribution, metabolism, excretion, and toxicity of a drug candidate. Considering that the experimental measurement of the property is costly and time-consuming, it is of great importance to develop reliable prediction models for logP. In this study, we developed a transfer free energy-based logP prediction model-FElogP. FElogP is based on the simple principle that logP is determined by the free energy change of transferring a molecule from water to n-octanol. The underlying physical method to calculate transfer free energy is the molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), thus this method is named as free energy-based logP (FElogP). The superiority of FElogP model was validated by a large set of 707 structurally diverse molecules in the ZINC database for which the measurement was of high quality. Encouragingly, FElogP outperformed several commonly-used QSPR or machine learning-based logP models, as well as some continuum solvation model-based methods. The root-mean-square error (RMSE) and Pearson correlation coefficient (R) between the predicted and measured values are 0.91 log units and 0.71, respectively, while the runner-up, the logP model implemented in OpenBabel had an RMSE of 1.13 log units and R of 0.67. Given the fact that FElogP was not parameterized against experimental logP directly, its excellent performance is likely to be expanded to arbitrary organic molecules covered by the general AMBER force fields.
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Affiliation(s)
- Yuchen Sun
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Xibing He
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Viet Hoang Man
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
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14
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Losada-Barreiro S, Paiva-Martins F, Bravo-Díaz C. Partitioning of Antioxidants in Edible Oil-Water Binary Systems and in Oil-in-Water Emulsions. Antioxidants (Basel) 2023; 12:828. [PMID: 37107202 PMCID: PMC10135117 DOI: 10.3390/antiox12040828] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/16/2023] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
In recent years, partitioning of antioxidants in oil-water two-phase systems has received great interest because of their potential in the downstream processing of biomolecules, their benefits in health, and because partition constant values between water and model organic solvents are closely related to important biological and pharmaceutical properties such as bioavailability, passive transport, membrane permeability, and metabolism. Partitioning is also of general interest in the oil industry. Edible oils such as olive oil contain a variety of bioactive components that, depending on their partition constants, end up in an aqueous phase when extracted from olive fruits. Frequently, waste waters are subsequently discarded, but their recovery would allow for obtaining extracts with antioxidant and/or biological activities, adding commercial value to the wastes and, at the same time, would allow for minimizing environmental risks. Thus, given the importance of partitioning antioxidants, in this manuscript, we review the background theory necessary to derive the relevant equations necessary to describe, quantitatively, the partitioning of antioxidants (and, in general, other drugs) and the common methods for determining their partition constants in both binary (PWOIL) and multiphasic systems composed with edible oils. We also include some discussion on the usefulness (or not) of extrapolating the widely employed octanol-water partition constant (PWOCT) values to predict PWOIL values as well as on the effects of acidity and temperature on their distributions. Finally, there is a brief section discussing the importance of partitioning in lipidic oil-in-water emulsions, where two partition constants, that between the oil-interfacial, POI, and that between aqueous-interfacial, PwI, regions, which are needed to describe the partitioning of antioxidants, and whose values cannot be predicted from the PWOIL or the PWOCT ones.
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Affiliation(s)
- Sonia Losada-Barreiro
- Departamento Química-Física, Facultad de Química, Universidade de Vigo, 36310 Vigo, Spain
- REQUIMTE-LAQV, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal
| | - Fátima Paiva-Martins
- REQUIMTE-LAQV, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal
| | - Carlos Bravo-Díaz
- Departamento Química-Física, Facultad de Química, Universidade de Vigo, 36310 Vigo, Spain
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15
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Morita R, Shigeta Y, Harada R. Efficient screening of protein-ligand complexes in lipid bilayers using LoCoMock score. J Comput Aided Mol Des 2023; 37:217-225. [PMID: 36943644 DOI: 10.1007/s10822-023-00502-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/05/2023] [Indexed: 03/23/2023]
Abstract
Membrane proteins are attractive targets for drug discovery due to their crucial roles in various biological processes. Studying the binding poses of amphipathic molecules to membrane proteins is essential for understanding the functions of membrane proteins and docking simulations can facilitate the screening of protein-ligand complexes at low computational costs. However, identifying docking poses for a ligand in non-aqueous environments such as lipid bilayers can be challenging. To address this issue, we propose a new docking score called logP-corrected membrane docking (LoCoMock) score. To screen putative protein-ligand complexes embedded in a membrane, the LoCoMock score considers the affinity between a target ligand and the membrane. It combines the docking score of the protein-ligand complex with the logP of the target ligand. In demonstrations using several model ligands, the LoCoMock score screened more putative complexes than the conventional docking score. As extended docking, the LoCoMock score makes it possible to screen membrane proteins more effectively as drug targets than the conventional docking.
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Affiliation(s)
- Rikuri Morita
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, 305-8577, Tsukuba, Ibaraki, Japan.
| | - Yasuteru Shigeta
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, 305-8577, Tsukuba, Ibaraki, Japan
| | - Ryuhei Harada
- Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, 305-8577, Tsukuba, Ibaraki, Japan.
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16
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Kotla NG, Pandey A, Vijaya Kumar Y, Ramazani F, Fisch A. Polyester-based long acting injectables: Advancements in molecular dynamics simulation and technological insights. Drug Discov Today 2023; 28:103463. [PMID: 36481584 DOI: 10.1016/j.drudis.2022.103463] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/21/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Long-acting injectable (LAI) delivery technologies have enabled the development of several pharmaceutical products that improve patient health by delivering therapeutics from weeks to months. Over the last decade, due to its good biocompatibility, formulation tunability, wide range of degradation rates, and extensive clinical studies, polyester-based LAI technologies including poly(lactic-co-glycolic acid) (PLGA) have made substantial progress. Herein, we discuss PLGA properties with seminal approaches in the development of LAIs, the role of molecular dynamic simulations of polymer-drug interactions, and their effects on quality attributes. We also outline the landscape of various advanced PLGA-based and a few non-PLGA LAI technologies; their design, delivery, and challenges from laboratory scale to preclinical and clinical use; and commercial products incorporating the importance of end-user preferences.
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Affiliation(s)
- Niranjan G Kotla
- Novartis Institutes for Biomedical Research (NIBR), Novartis Pharma AG, Basel 4002, Switzerland.
| | - Abhijeet Pandey
- Technical Research and Development, Novartis Pharma AG, Hyderabad 500081, India.
| | - Y Vijaya Kumar
- Technical Research and Development, Novartis Pharma AG, Hyderabad 500081, India
| | - Farshad Ramazani
- Technical Research and Development (TRD), Novartis Pharma AG, Basel 4002, Switzerland
| | - Andreas Fisch
- Technical Research and Development (TRD), Novartis Pharma AG, Basel 4002, Switzerland
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17
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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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18
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Isert C, Kromann JC, Stiefl N, Schneider G, Lewis RA. Machine Learning for Fast, Quantum Mechanics-Based Approximation of Drug Lipophilicity. ACS OMEGA 2023; 8:2046-2056. [PMID: 36687099 PMCID: PMC9850743 DOI: 10.1021/acsomega.2c05607] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/21/2022] [Indexed: 06/17/2023]
Abstract
Lipophilicity, as measured by the partition coefficient between octanol and water (log P), is a key parameter in early drug discovery research. However, measuring log P experimentally is difficult for specific compounds and log P ranges. The resulting lack of reliable experimental data impedes development of accurate in silico models for such compounds. In certain discovery projects at Novartis focused on such compounds, a quantum mechanics (QM)-based tool for log P estimation has emerged as a valuable supplement to experimental measurements and as a preferred alternative to existing empirical models. However, this QM-based approach incurs a substantial computational cost, limiting its applicability to small series and prohibiting quick, interactive ideation. This work explores a set of machine learning models (Random Forest, Lasso, XGBoost, Chemprop, and Chemprop3D) to learn calculated log P values on both a public data set and an in-house data set to obtain a computationally affordable, QM-based estimation of drug lipophilicity. The message-passing neural network model Chemprop emerged as the best performing model with mean absolute errors of 0.44 and 0.34 log units for scaffold split test sets of the public and in-house data sets, respectively. Analysis of learning curves suggests that a further decrease in the test set error can be achieved by increasing the training set size. While models directly trained on experimental data perform better at approximating experimentally determined log P values than models trained on calculated values, we discuss the potential advantages of using calculated log P values going beyond the limits of experimental quantitation. We analyze the impact of the data set splitting strategy and gain insights into model failure modes. Potential use cases for the presented models include pre-screening of large compound collections and prioritization of compounds for full QM calculations.
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Affiliation(s)
- Clemens Isert
- Department
of Chemistry and Applied Biosciences, ETH
Zurich, Vladimir-Prelog-Weg 4, 8093Zurich, Switzerland
- Novartis
Institutes for BioMedical Research, 4056Basel, Switzerland
| | - Jimmy C. Kromann
- Novartis
Institutes for BioMedical Research, 4056Basel, Switzerland
| | - Nikolaus Stiefl
- Novartis
Institutes for BioMedical Research, 4056Basel, Switzerland
| | - Gisbert Schneider
- Department
of Chemistry and Applied Biosciences, ETH
Zurich, Vladimir-Prelog-Weg 4, 8093Zurich, Switzerland
- ETH
Singapore SEC Ltd., 1
CREATE Way, #06-01 CREATE Tower138602, Singapore, Singapore
| | - Richard A. Lewis
- Novartis
Institutes for BioMedical Research, 4056Basel, Switzerland
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19
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Xia S, Zhang D, Zhang Y. Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties. J Chem Theory Comput 2023; 19:10.1021/acs.jctc.2c01024. [PMID: 36607141 PMCID: PMC10323048 DOI: 10.1021/acs.jctc.2c01024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The past few years have witnessed significant advances in developing machine learning methods for molecular energetics predictions, including calculated electronic energies with high-level quantum mechanical methods and experimental properties, such as solvation free energy and logP. Typically, task-specific machine learning models are developed for distinct prediction tasks. In this work, we present a multitask deep ensemble model, sPhysNet-MT-ens5, which can simultaneously and accurately predict electronic energies of molecules in gas, water, and octanol phases, as well as transfer free energies at both calculated and experimental levels. On the calculated data set Frag20-solv-678k, which is developed in this work and contains 678,916 molecular conformations, up to 20 heavy atoms, and their properties calculated at B3LYP/6-31G* level of theory with continuum solvent models, sPhysNet-MT-ens5 predicts density functional theory (DFT)-level electronic energies directly from force field-optimized geometry within chemical accuracy. On the experimental data sets, sPhysNet-MT-ens5 achieves state-of-the-art performances, which predict both experimental hydration free energy with a RMSE of 0.620 kcal/mol on the FreeSolv data set and experimental logP with a RMSE of 0.393 on the PHYSPROP data set. Furthermore, sPhysNet-MT-ens5 also provides a reasonable estimation of model uncertainty which shows correlations with prediction error. Finally, by analyzing the atomic contributions of its predictions, we find that the developed deep learning model is aware of the chemical environment of each atom by assigning reasonable atomic contributions consistent with our chemical knowledge.
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Affiliation(s)
- Song Xia
- Department of Chemistry, New York University, New York, New York 10003, United States
| | - Dongdong Zhang
- Department of Chemistry, New York University, New York, New York 10003, United States
| | - Yingkai Zhang
- Department of Chemistry, New York University, New York, New York 10003, United States
- Simons Center for Computational Physical Chemistry at New York University, New York, New York 10003, United States
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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20
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Jia Q, Ni Y, Liu Z, Gu X, Cui Z, Fan M, Zhu Q, Wang Y, Ma J. Fast Prediction of Lipophilicity of Organofluorine Molecules: Deep Learning-Derived Polarity Characters and Experimental Tests. J Chem Inf Model 2022; 62:4928-4936. [PMID: 36223527 DOI: 10.1021/acs.jcim.2c01201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Fast and accurate estimation of lipophilicity for organofluorine molecules is in great demand for accelerating drug and materials discovery. A lipophilicity data set of organofluorine molecules (OFL data set), containing 1907 samples, is constructed through density functional theory (DFT) calculations and experimental measurements. An efficient and interpretable model, called PoLogP, is developed to predict the n-octanol/water partition coefficient, log Po/w, of organofluorine molecules on the basis of the descriptors of polarization, which is a combination of polarity descriptors, including the molecular polarity index and molecular polarizability (α), and hydrogen bond (HBs) index, consisting of the number of donors (NHBD) and acceptors (NHBA and NHB-FA). The present PoLogP with a combination of polarity descriptors is demonstrated to perform better than the dipole moment (μ) alone for the F-contained molecules. With the aid of a multilevel attention graph convolutional neural network model, the fast generation of polarity descriptors of organofluorine molecules could be achieved with the DFT accuracy based only on a topological molecular graph structure. The performance of PoLogP is further validated on synthesized organofluorine molecules and 2626 non-fluorinated molecules with satisfactory accuracy, highlighting the potential usage of PoLogP in high-throughput screening of the functional molecules with the desired solubility in various solvent media.
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Affiliation(s)
- Qingqing Jia
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Yifan Ni
- Jiangsu Key Laboratory of Advanced Organic Materials, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Ziteng Liu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Xu Gu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Ziyi Cui
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Mengting Fan
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Qiang Zhu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Yi Wang
- Jiangsu Key Laboratory of Advanced Organic Materials, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
| | - Jing Ma
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China.,Jiangsu Key Laboratory of Advanced Organic Materials, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
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21
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Correa GB, Maciel JCSL, Tavares FW, Abreu CRA. A New Formulation for the Concerted Alchemical Calculation of van der Waals and Coulomb Components of Solvation Free Energies. J Chem Theory Comput 2022; 18:5876-5889. [PMID: 36189930 DOI: 10.1021/acs.jctc.2c00563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Alchemical free energy calculations via molecular dynamics have been widely used to obtain thermodynamic properties related to protein-ligand binding and solute-solvent interactions. Although soft-core modeling is the most common approach, the linear basis function (LBF) methodology [Naden, L. N.; et al. J. Chem. Theory Comput.2014, 10 (3), 1128; 2015, 11 (6), 2536] has emerged as a suitable alternative. It overcomes the end-point singularity of the scaling method while maintaining essential advantages such as ease of implementation and high flexibility for postprocessing analysis. In the present work, we propose a simple LBF variant and formulate an efficient protocol for evaluating van der Waals and Coulomb components of an alchemical transformation in tandem, in contrast to the prevalent sequential evaluation mode. To validate our proposal, which results from a careful optimization study, we performed solvation free energy calculations and obtained octanol-water partition coefficients of small organic molecules. Comparisons with results obtained via the sequential mode using either another LBF approach or the soft-core model attest to the effectiveness and correctness of our method. In addition, we show that a reaction field model with an infinite dielectric constant can provide very accurate hydration free energies when used instead of a lattice-sum method to model solute-solvent electrostatics.
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Affiliation(s)
- Gabriela B Correa
- Chemical Engineering Program, Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa em Engenharia, Universidade Federal do Rio de Janeiro, 21941-909Rio de Janeiro, RJ, Brazil
| | - Jéssica C S L Maciel
- Chemical Engineering Department, Escola de Química, Universidade Federal do Rio de Janeiro, 21941-909Rio de Janeiro, RJ, Brazil
| | - Frederico W Tavares
- Chemical Engineering Program, Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa em Engenharia, Universidade Federal do Rio de Janeiro, 21941-909Rio de Janeiro, RJ, Brazil.,Chemical Engineering Department, Escola de Química, Universidade Federal do Rio de Janeiro, 21941-909Rio de Janeiro, RJ, Brazil
| | - Charlles R A Abreu
- Chemical Engineering Department, Escola de Química, Universidade Federal do Rio de Janeiro, 21941-909Rio de Janeiro, RJ, Brazil
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22
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Zhu Q, Jia Q, Liu Z, Ge Y, Gu X, Cui Z, Fan M, Ma J. Molecular partition coefficient from machine learning with polarization and entropy embedded atom-centered symmetry functions. Phys Chem Chem Phys 2022; 24:23082-23088. [PMID: 36134471 DOI: 10.1039/d2cp02648a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Efficient prediction of the partition coefficient (log P) between polar and non-polar phases could shorten the cycle of drug and materials design. In this work, a descriptor, named 〈q - ACSFs〉conf, is proposed to take the explicit polarization effects in the polar phase and the conformation ensemble of energetic and entropic significance in the non-polar phase into consideration. The polarization effects are involved by embedding the partial charge directly derived from force fields or quantum chemistry calculations into the atom-centered symmetry functions (ACSFs), together with the entropy effects, which are averaged according to the Boltzmann distribution of different conformations taken from the similarity matrix. The model was trained with high-dimensional neural networks (HDNNs) on a public dataset PhysProp (with 41 039 samples). Satisfactory log P prediction performance was achieved on three other datasets, namely, Martel (707 molecules), Star & Non-Star (266) and Huuskonen (1870). The present 〈q - ACSFs〉conf model was also applicable to n-carboxylic acids with the number of carbons ranging from 2 to 14 and 54 kinds of organic solvent. It is easy to apply the present method to arbitrary sized systems and give a transferable atom-based partition coefficient.
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Affiliation(s)
- Qiang Zhu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Qingqing Jia
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Ziteng Liu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Yang Ge
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Xu Gu
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Ziyi Cui
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Mengting Fan
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
| | - Jing Ma
- Key Laboratory of Mesoscopic Chemistry of Ministry of Education Institute of Theoretical and Computational Chemistry School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, P. R. China.
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23
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Molecular dynamics and network analysis reveal the contrasting roles of polar solutes within organic phase amphiphile aggregation. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.119226] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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24
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Kanamaru Y, Matsui T. Factor analysis of error in oxidation potential calculation: A machine learning study. J Comput Chem 2022; 43:1504-1512. [PMID: 35762851 DOI: 10.1002/jcc.26953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/23/2022] [Accepted: 06/06/2022] [Indexed: 11/11/2022]
Abstract
The conductor-like polarizable continuum model (C-PCM), which is a low-cost solvation model, cannot treat characteristic interactions between the solvent and substructure(s) of the solute. Moreover, the error in a charged system is significant. Using machine learning, we clarified that the systematic error of the oxidation potential calculated by the G3B3/C-PCM was correlated with the molecular size of a solute. The G3B3/C-PCM overestimated the Gibbs oxidation energy by averaging 6.94 kcal/mol. According to the performance of related methods reported in previous studies, this error is mainly due to the solvation energy of the charged solute. Additionally, we succeeded in reducing the error to 2.27 kcal/mol (32%)-3.2 kcal/mol (40%) by correction based on the substructure information of the solute. To modify the C-PCM, effects that correlate with the molecular size of the solute in the charged system should be incorporated.
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Affiliation(s)
- Yuki Kanamaru
- Department of Chemistry, Graduate School of Pure and Applied Science, University of Tsukuba, Tsukuba, Japan
| | - Toru Matsui
- Department of Chemistry, Graduate School of Pure and Applied Science, University of Tsukuba, Tsukuba, Japan
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25
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Mech-Warda P, Giełdoń A, Kawiak A, Maciejewska N, Olszewski M, Makowski M, Chylewska A. Low-Molecular Pyrazine-Based DNA Binders: Physicochemical and Antimicrobial Properties. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27123704. [PMID: 35744829 PMCID: PMC9228100 DOI: 10.3390/molecules27123704] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/07/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022]
Abstract
Pyrazine and its derivatives are a large group of compounds that exhibit broad biological activity, the changes of which can be easily detected by a substituent effect or a change in the functional group. The present studies combined theoretical research with the density functional theory (DFT) approach (B3LYP/6-311+G**) and experimental (potentiometric and spectrophotometric) analysis for a thorough understanding of the structure of chlorohydrazinopyrazine, its physicochemical and cytotoxic properties, and the site and nature of interaction with DNA. The obtained results indicated that 2-chloro-3-hydrazinopyrazine (2Cl3HP) displayed the highest affinity to DNA. Cytotoxicity studies revealed that the compound did not exhibit toxicity toward human dermal keratinocytes, which supported the potential application of 2Cl3HP in clinical use. The study also attempted to establish the possible equilibria occurring in the aqueous solution and, using both theoretical and experimental methods, clearly showed the hydrophilic nature of the compound. The experimental and theoretical results of the study confirmed the quality of the compound, as well as the appropriateness of the selected set of methods for similar research.
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Affiliation(s)
- Paulina Mech-Warda
- Department of Bioinorganic Chemistry, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (P.M.-W.); (M.M.)
| | - Artur Giełdoń
- Department of Theoretical Chemistry, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland;
| | - Anna Kawiak
- Institute of Biotechnology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Abrahama 58, 80-307 Gdańsk, Poland;
| | - Natalia Maciejewska
- Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland; (N.M.); (M.O.)
| | - Mateusz Olszewski
- Faculty of Chemistry, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland; (N.M.); (M.O.)
| | - Mariusz Makowski
- Department of Bioinorganic Chemistry, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (P.M.-W.); (M.M.)
| | - Agnieszka Chylewska
- Department of Bioinorganic Chemistry, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (P.M.-W.); (M.M.)
- Correspondence:
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26
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Membrane Cholesterol Content and Lipid Organization Influence Melittin and Pneumolysin Pore-Forming Activity. Toxins (Basel) 2022; 14:toxins14050346. [PMID: 35622592 PMCID: PMC9147762 DOI: 10.3390/toxins14050346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/03/2022] [Accepted: 05/06/2022] [Indexed: 12/12/2022] Open
Abstract
Melittin, the main toxic component in the venom of the European honeybee, interacts with natural and artificial membranes due to its amphiphilic properties. Rather than interacting with a specific receptor, melittin interacts with the lipid components, disrupting the lipid bilayer and inducing ion leakage and osmotic shock. This mechanism of action is shared with pneumolysin and other members of the cholesterol-dependent cytolysin family. In this manuscript, we investigated the inverse correlation for cholesterol dependency of these two toxins. While pneumolysin-induced damage is reduced by pretreatment with the cholesterol-depleting agent methyl-β-cyclodextrin, the toxicity of melittin, after cholesterol depletion, increased. A similar response was also observed after a short incubation with lipophilic simvastatin, which alters membrane lipid organization and structure, clustering lipid rafts. Therefore, changes in toxin sensitivity can be achieved in cells by depleting cholesterol or changing the lipid bilayer organization.
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27
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Brosz M, Michelarakis N, Bunz UHF, Aponte-Santamaría C, Gräter F. Martini 3 coarse-grained force field for poly( para-phenylene ethynylene)s. Phys Chem Chem Phys 2022; 24:9998-10010. [PMID: 35412534 DOI: 10.1039/d1cp04237h] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Poly(para-phenylene ethynylene)s, or short PPEs, are a class of conjugated and semi-flexible polymers with a strongly delocalized π electron system and increased chain stiffness. Due to this, PPEs have a wide range of technological applications. Although the material properties of single-chains or mixtures of few PPE chains have been studied in detail, the properties of large assemblies remain to be fully explored. Here, we developed a coarse-grained model for PPEs with the Martini 3 force field to enable computational studies of PPEs in large-scale assembly. We used an optimization geometrical approach to take the shape of the π conjugated backbone into account and also applied an additional angular potential to tune the mechanical bending stiffness of the polymer. Our Martini 3 model reproduces key structural and thermodynamic observables of single PPE chains and mixtures, such as persistence length, density, packing and stacking. We show that chain entanglement increases with the expense of nematic ordering with growing PPE chain length. With the Martini 3 PPE model at hand, we are now able to cover large spatio-temporal scales and thereby to uncover key aspects for the structural organization of PPE bulk systems. The model is also predicted to be of high applicability to investigate out-of-equilibrium behavior of PPEs under mechanical force.
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Affiliation(s)
- Matthias Brosz
- Heidelberg Institute for Theoretical Studies, Am Schlosswolfsbrunnenweg 35, 69118 Heidelberg, Germany. .,Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Nicholas Michelarakis
- Heidelberg Institute for Theoretical Studies, Am Schlosswolfsbrunnenweg 35, 69118 Heidelberg, Germany.
| | - Uwe H F Bunz
- Institute of Organic Chemistry, Heidelberg University, Im Neuenheimer Feld 270, 69120 Heidelberg, Germany
| | - Camilo Aponte-Santamaría
- Heidelberg Institute for Theoretical Studies, Am Schlosswolfsbrunnenweg 35, 69118 Heidelberg, Germany.
| | - Frauke Gräter
- Heidelberg Institute for Theoretical Studies, Am Schlosswolfsbrunnenweg 35, 69118 Heidelberg, Germany. .,Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
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28
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Akar I, Foster JC, Leng X, Pearce AK, Mathers RT, O’Reilly RK. Log Poct/SA Predicts the Thermoresponsive Behavior of P(DMA- co-RA) Statistical Copolymers. ACS Macro Lett 2022; 11:498-503. [PMID: 35575334 PMCID: PMC9022432 DOI: 10.1021/acsmacrolett.1c00776] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
![]()
Polymers that exhibit
a lower critical solution temperature (LCST)
have been of great interest for various biological applications such
as drug or gene delivery, controlled release systems, and biosensing.
Tuning the LCST behavior through control over polymer composition
(e.g., upon copolymerization of monomers with different hydrophobicity)
is a widely used method, as the phase transition is greatly affected
by the hydrophilic/hydrophobic balance of the copolymers. However,
the lack of a general method that relates copolymer hydrophobicity
to their temperature response leads to exhaustive experiments when
seeking to obtain polymers with desired properties. This is particularly
challenging when the target copolymers are comprised of monomers that
individually form nonresponsive homopolymers, that is, only when copolymerized
do they display thermoresponsive behavior. In this study, we sought
to develop a predictive relationship between polymer hydrophobicity
and cloud point temperature (TCP). A series
of statistical copolymers were synthesized based on hydrophilic N,N-dimethyl acrylamide (DMA) and hydrophobic
alkyl acrylate monomers, and their hydrophobicity was compared using
surface area-normalized octanol/water partition coefficients (Log Poct/SA). Interestingly, a correlation between
the Log Poct/SA of the copolymers and
their TCPs was observed for the P(DMA-co-RA) copolymers, which allowed TCP prediction of a demonstrative copolymer P(DMA-co-MMA). These results highlight the strong potential of this computational
tool to improve the rational design of copolymers with desired temperature
responses prior to synthesis.
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Affiliation(s)
- Irem Akar
- School of Chemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Jeffrey C. Foster
- School of Chemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Xiyue Leng
- School of Chemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Amanda K. Pearce
- School of Chemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Robert T. Mathers
- Department of Chemistry, Pennsylvania State University, New Kensington, Pennsylvania 15068, United States
| | - Rachel K. O’Reilly
- School of Chemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
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29
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Subbotina J, Lobaskin V. Multiscale Modeling of Bio-Nano Interactions of Zero-Valent Silver Nanoparticles. J Phys Chem B 2022; 126:1301-1314. [PMID: 35132861 PMCID: PMC8859825 DOI: 10.1021/acs.jpcb.1c09525] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
![]()
Understanding the
specifics of interaction between the protein
and nanomaterial is crucial for designing efficient, safe, and selective
nanoplatforms, such as biosensor or nanocarrier systems. Routing experimental
screening for the most suitable complementary pair of biomolecule
and nanomaterial used in such nanoplatforms might be a resource-intensive
task. While a range of computational tools are available for prescreening
libraries of proteins for their interactions with small molecular
ligands, choices for high-throughput screening of protein libraries
for binding affinities to new and existing nanomaterials are very
limited. In the current work, we present the results of the systematic
computational study of interaction of various biomolecules with pristine
zero-valent noble metal nanoparticles, namely, AgNPs, by using the UnitedAtom multiscale approach. A set of blood plasma and
dietary proteins for which the interaction with AgNPs was described
experimentally were examined computationally to evaluate the performance
of the UnitedAtom method. A set of interfacial descriptors
(log PNM, adsorption affinities, and adsorption
affinity ranking), which can characterize the relative hydrophobicity/hydrophilicity/lipophilicity
of the nanosized silver and its ability to form bio(eco)corona, was
evaluated for future use in nano-QSAR/QSPR studies.
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Affiliation(s)
- Julia Subbotina
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
| | - Vladimir Lobaskin
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland
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30
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Waibl F, Kraml J, Fernández-Quintero ML, Loeffler JR, Liedl KR. Explicit solvation thermodynamics in ionic solution: extending grid inhomogeneous solvation theory to solvation free energy of salt-water mixtures. J Comput Aided Mol Des 2022; 36:101-116. [PMID: 35031880 PMCID: PMC8907097 DOI: 10.1007/s10822-021-00429-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/28/2021] [Indexed: 12/03/2022]
Abstract
Hydration thermodynamics play a fundamental role in fields ranging from the pharmaceutical industry to environmental research. Numerous methods exist to predict solvation thermodynamics of compounds ranging from small molecules to large biomolecules. Arguably the most precise methods are those based on molecular dynamics (MD) simulations in explicit solvent. One theory that has seen increased use is inhomogeneous solvation theory (IST). However, while many applications require accurate description of salt-water mixtures, no implementation of IST is currently able to estimate solvation properties involving more than one solvent species. Here, we present an extension to grid inhomogeneous solvation theory (GIST) that can take salt contributions into account. At the example of carbazole in 1 M NaCl solution, we compute the solvation energy as well as first and second order entropies. While the effect of the first order ion entropy is small, both the water-water and water-ion entropies contribute strongly. We show that the water-ion entropies are efficiently approximated using the Kirkwood superposition approximation. However, this approach cannot be applied to the water-water entropy. Furthermore, we test the quantitative validity of our method by computing salting-out coefficients and comparing them to experimental data. We find a good correlation to experimental salting-out constants, while the absolute values are overpredicted due to the approximate second order entropy. Since ions are frequently used in MD, either to neutralize the system or as a part of the investigated process, our method greatly extends the applicability of GIST. The use-cases range from biopharmaceuticals, where many assays require high salt concentrations, to environmental research, where solubility in sea water is important to model the fate of organic substances.
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Affiliation(s)
- Franz Waibl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes Kraml
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Monica L Fernández-Quintero
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Johannes R Loeffler
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria
| | - Klaus R Liedl
- Department of General, Inorganic, and Theoretical Chemistry, University of Innsbruck, Innrain 80/82, 6020, Innsbruck, Austria.
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31
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Salthammer T, Grimme S, Stahn M, Hohm U, Palm WU. Quantum Chemical Calculation and Evaluation of Partition Coefficients for Classical and Emerging Environmentally Relevant Organic Compounds. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:379-391. [PMID: 34931808 DOI: 10.1021/acs.est.1c06935] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Octanol/water (KOW), octanol/air (KOA), and hexadecane/air (KHdA) partition coefficients are calculated for 67 organic compounds of environmental concern using computational chemistry. The extended CRENSO workflow applied here includes the calculation of extensive conformer ensembles with semiempirical methods and refinement through density functional theory, taking into account solvation models, especially COSMO-RS, and thermostatistical contributions. This approach is particularly advantageous for describing large and nonrigid molecules. With regard to KOW and KHdA, one can refer to many experimental data from direct and indirect measurement methods, and very good matches with results from our quantum chemical workflow are evident. In the case of the KOA values, however, good matches are only obtained for the experimentally determined values. Larger systematic deviations between data computed here and available, nonexperimental quantitative structure-activity relationship literature data occur in particular for phthalic acid esters and organophosphate esters. From a critical analysis of the coefficients calculated in this work and comparison with available literature data, we conclude that the presented quantum chemical composite approach is the most powerful so far for calculating reliable partition coefficients because all physical contributions to the conformational free energy are considered and the structure ensembles for the two phases are generated independently and consistently.
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Affiliation(s)
- Tunga Salthammer
- Department of Material Analysis and Indoor Chemistry, Fraunhofer WKI, 38108 Braunschweig, Germany
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Institute for Physical and Theoretical Chemistry, University of Bonn, 53115 Bonn, Germany
| | - Marcel Stahn
- Mulliken Center for Theoretical Chemistry, Institute for Physical and Theoretical Chemistry, University of Bonn, 53115 Bonn, Germany
| | - Uwe Hohm
- Institute of Physical and Theoretical Chemistry, University of Braunschweig─Institute of Technology, 38106 Braunschweig, Germany
| | - Wolf-Ulrich Palm
- Institute of Sustainable and Environmental Chemistry, Leuphana University Lüneburg, 21335 Lüneburg, Germany
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32
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Machine learning & deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry. Future Med Chem 2021; 14:245-270. [PMID: 34939433 DOI: 10.4155/fmc-2021-0243] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) have substantial implications in virtual screening, peptide synthesis, drug ADMET screening and biomarker discovery. These strategies can increase the positive outcomes in the drug discovery process without false-positive rates and can be achieved in a cost-effective way with a minimum duration of time by high-quality data acquisition. This review substantially discusses the recent updates in AI tools as cheminformatics application in medicinal chemistry for the data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry while improving small-molecule bioactivities and properties.
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33
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Bahr MN, Nandkeolyar A, Kenna JK, Nevins N, Da Vià L, Işık M, Chodera JD, Mobley DL. Automated high throughput pK a and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge. J Comput Aided Mol Des 2021; 35:1141-1155. [PMID: 34714468 DOI: 10.1007/s10822-021-00427-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 10/13/2021] [Indexed: 11/28/2022]
Abstract
The goal of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge is to improve the accuracy of current computational models to estimate free energy of binding, deprotonation, distribution and other associated physical properties that are useful for the design of new pharmaceutical products. New experimental datasets of physicochemical properties provide opportunities for prospective evaluation of computational prediction methods. Here, aqueous pKa and a range of bi-phasic logD values for a variety of pharmaceutical compounds were determined through a streamlined automated process to be utilized in the SAMPL8 physical property challenge. The goal of this paper is to provide an in-depth review of the experimental methods utilized to create a comprehensive data set for the blind prediction challenge. The significance of this work involves the use of high throughput experimentation equipment and instrumentation to produce acid dissociation constants for twenty-three drug molecules, as well as distribution coefficients for eleven of those molecules.
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Affiliation(s)
- Matthew N Bahr
- Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA.
| | - Aakankschit Nandkeolyar
- Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA.,Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA.,Department of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, Irvine, CA, 92697, USA
| | - John K Kenna
- Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA
| | - Neysa Nevins
- Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA
| | - Luigi Da Vià
- Pharmaceutical Research and Development, GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, UK
| | - Mehtap Işık
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - John D Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - David L Mobley
- Department of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, Irvine, CA, 92697, USA
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34
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Salassi S, Caselli L, Cardellini J, Lavagna E, Montis C, Berti D, Rossi G. A Martini Coarse Grained Model of Citrate-Capped Gold Nanoparticles Interacting with Lipid Bilayers. J Chem Theory Comput 2021; 17:6597-6609. [PMID: 34491056 PMCID: PMC8515808 DOI: 10.1021/acs.jctc.1c00627] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Indexed: 12/29/2022]
Abstract
Citrate capping is one of the most common strategies to achieve the colloidal stability of Au nanoparticles (NPs) with diameters ranging from a few to hundreds of nanometers. Citrate-capped Au nanoparticles (CNPs) represent a step of the synthesis of Au NPs with specific functionalities, as CNPs can be further functionalized via ligand-exchange reactions, leading to the replacement of citrate with other organic ligands. In vitro, CNPs are also used to address the fundamental aspects of NP-membrane interactions, as they can directly interact with cells or model cell membranes. Their affinity for the bilayer is again mediated by the exchange of citrate with lipid molecules. Here, we propose a new computational model of CNPs compatible with the coarse grained Martini force field. The model, which we develop and validate through an extensive comparison with new all-atom molecular dynamics (MD) simulations and UV-vis and Fourier transform infrared spectroscopy data, is aimed at the MD simulation of the interaction between citrate-capped NPs and model phosphatidylcholine lipid membranes. As a test application we show that, during the interaction between a single CNP and a flat planar 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayer, the citrate coating is spontaneously replaced by lipids on the surface of Au NPs, while the NP size and shape determine the final structural configuration of the NP-bilayer complex.
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Affiliation(s)
- Sebastian Salassi
- Department
of Physics, University of Genoa, Via Dodecaneso 33, Genoa 16146, Italy
| | - Lucrezia Caselli
- Department
of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
- CSGI,
Consorzio Sistemi a Grande Interfase and Department of Chemistry “Ugo
Schiff” University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
| | - Jacopo Cardellini
- Department
of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
- CSGI,
Consorzio Sistemi a Grande Interfase and Department of Chemistry “Ugo
Schiff” University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
| | - Enrico Lavagna
- Department
of Physics, University of Genoa, Via Dodecaneso 33, Genoa 16146, Italy
| | - Costanza Montis
- Department
of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
- CSGI,
Consorzio Sistemi a Grande Interfase and Department of Chemistry “Ugo
Schiff” University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
| | - Debora Berti
- Department
of Chemistry “Ugo Schiff”, University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
- CSGI,
Consorzio Sistemi a Grande Interfase and Department of Chemistry “Ugo
Schiff” University of Florence, Via della Lastruccia 3, Sesto Fiorentino, Florence 50019, Italy
| | - Giulia Rossi
- Department
of Physics, University of Genoa, Via Dodecaneso 33, Genoa 16146, Italy
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35
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Ghanadzadeh Gilani A, Jahanbin sardroodi J, Verpoort F, Rahmdel S. Experimental study and thermodynamic modeling of phase equilibria of systems containing cyclohexane, alcohols (C4 and C5), and deep eutectic solvents. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.117196] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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36
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Prediction of Partition Coefficients in SDS Micelles by DFT Calculations. Symmetry (Basel) 2021. [DOI: 10.3390/sym13091750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
A computational methodology using Density-Functional Theory (DFT) calculations was developed to determine the partition coefficient of a compound in a solution of Sodium Dodecyl Sulfate (SDS) micelles. Different sets of DFT calculations were used to predict the free energy of a set of 63 molecules in 15 different solvents with the purpose of identifying the solvents with similar physicochemical characteristics to the studied micelles. Experimental partition coefficients were obtained from Micellar Electrokinetic Chromatography (MEKC) measurements. The experimental partition coefficient of these molecules was compared with the predicted partition coefficient in heptane/water, cyclohexane/water, N-dodecane/water, pyridine/water, acetic acid/water, decan-1-ol/water, octanol/water, propan-2-ol/water, acetone/water, propan-1-ol/water, methanol/water, 1,2-ethane diol/water, dimethyl sulfoxide/water, formic acid/water, and diethyl sulphide/water systems. It is observed that the combination of pronan-1-ol/water solvent was the most appropriated to estimate the partition coefficient for SDS micelles. This approach allowed us to estimate the partition coefficient orders of magnitude faster than the classical molecular dynamics simulations. The DFT calculations were carried out with the well-known exchange correlation functional B3LYP and with the global hybrid functional M06-2X from the Minnesota functionals with 6-31++G ** basis set. The effect of solvation was considered by the continuum model based on density (SMD). The proposed workflow for the prediction rate of the participation coefficient unveiled the symmetric balance between the experimental data and the computational methods.
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37
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Sabatino SJ, Paluch AS. Predicting octanol/water partition coefficients using molecular simulation for the SAMPL7 challenge: comparing the use of neat and water saturated 1-octanol. J Comput Aided Mol Des 2021; 35:1009-1024. [PMID: 34495430 DOI: 10.1007/s10822-021-00415-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 08/09/2021] [Indexed: 11/29/2022]
Abstract
Blind predictions of octanol/water partition coefficients at 298.15 K for 22 drug-like compounds were made for the SAMPL7 challenge. The octanol/water partition coefficients were predicted using solvation free energies computed using molecular dynamics simulations, wherein we considered the use of both pure and water-saturated 1-octanol to model the octanol-rich phase. Water and 1-octanol were modeled using TIP4P and TrAPPE-UA, respectively, which have been shown to well reproduce the experimental mutual solubility, and the solutes were modeled using GAFF. After the close of the SAMPL7 challenge, we additionally made predictions using TIP4P/2005 water. We found that the predictions were sensitive to the choice of water force field. However, the effect of water in the octanol-rich phase was found to be even more significant and non-negligible. The effect of inclusion of water was additionally sensitive to the chemical structure of the solute.
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Affiliation(s)
- Spencer J Sabatino
- Department of Chemical, Paper, and Biomedical Engineering, Miami University, Oxford, OH, 45056, USA
| | - Andrew S Paluch
- Department of Chemical, Paper, and Biomedical Engineering, Miami University, Oxford, OH, 45056, USA.
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38
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Falcioni F, Kalayan J, Henchman RH. Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters. J Comput Aided Mol Des 2021; 35:831-840. [PMID: 34244906 PMCID: PMC8295089 DOI: 10.1007/s10822-021-00401-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 06/17/2021] [Indexed: 12/23/2022]
Abstract
Partition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.
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Affiliation(s)
- Fabio Falcioni
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
| | - Jas Kalayan
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
| | - Richard H Henchman
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
- School of Chemistry, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
- Sydney Medical School, The University of Sydney, Sydney, NSW, 2006, Australia.
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Petris PC, Becherer P, Fraaije JGEM. Alkane/Water Partition Coefficient Calculation Based on the Modified AM1 Method and Internal Hydrogen Bonding Sampling Using COSMO-RS. J Chem Inf Model 2021; 61:3453-3462. [PMID: 34165298 PMCID: PMC8317156 DOI: 10.1021/acs.jcim.0c01478] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
We introduce a physics-based
model for calculating partition coefficients
of solutes between water and alkanes, using a combination of a semi-empirical
method for COSMO charge density calculation and statistical sampling
of internal hydrogen bonds (IHBs). We validate the model on the experimental
partition data (∼3500 molecules) of small organics, drug-like
molecules, and statistical assessment of modeling of proteins and
ligand drugs. The model combines two novel algorithms: a bond-correction
method for improving the calculation of COSMO charge density from
AM1 calculations and a sampling method to deal with IHBs. From a comparison
of simulated and experimental partition coefficients, we find a root-mean-square
deviation of roughly one log 10 unit. From IHB analysis, we know that
IHBs can be present in two states: open (in water) and closed (in
apolar solvent). The difference can lead to a shift of as much as
two log 10 units per IHB; not taking this effect into account can
lead to substantial errors. The method takes a few minutes of calculation
time on a single core, per molecule. Although this is still much slower
than quantitative structure–activity relationship, it is much
faster than molecular simulations and can be readily incorporated
into any screening method.
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Affiliation(s)
- Panagiotis C Petris
- Leiden Institute of Chemistry, Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands.,Siemens Industry Software Netherlands B.V., Galileiweg 8, 2333 BD Leiden, The Netherlands
| | - Paul Becherer
- Siemens Industry Software Netherlands B.V., Galileiweg 8, 2333 BD Leiden, The Netherlands
| | - Johannes G E M Fraaije
- Leiden Institute of Chemistry, Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands.,Siemens Industry Software Netherlands B.V., Galileiweg 8, 2333 BD Leiden, The Netherlands
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40
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Spoel D, Zhang J, Zhang H. Quantitative predictions from molecular simulations using explicit or implicit interactions. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1560] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- David Spoel
- Uppsala Center for Computational Chemistry, Science for Life Laboratory, Department of Cell and Molecular Biology Uppsala University Uppsala Sweden
| | - Jin Zhang
- Department of Chemistry Southern University of Science and Technology Shenzhen China
| | - Haiyang Zhang
- Department of Biological Science and Engineering, School of Chemistry and Biological Engineering University of Science and Technology Beijing Beijing China
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41
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Kashefolgheta S, Wang S, Acree WE, Hünenberger PH. Evaluation of nine condensed-phase force fields of the GROMOS, CHARMM, OPLS, AMBER, and OpenFF families against experimental cross-solvation free energies. Phys Chem Chem Phys 2021; 23:13055-13074. [PMID: 34105547 PMCID: PMC8207520 DOI: 10.1039/d1cp00215e] [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: 01/15/2021] [Accepted: 04/28/2021] [Indexed: 12/02/2022]
Abstract
Experimental solvation free energies are nowadays commonly included as target properties in the validation of condensed-phase force fields, sometimes even in their calibration. In a previous article [Kashefolgheta et al., J. Chem. Theory. Comput., 2020, 16, 7556-7580], we showed how the involved comparison between experimental and simulation results could be made more systematic by considering a full matrix of cross-solvation free energies . For a set of N molecules that are all in the liquid state under ambient conditions, such a matrix encompasses N×N entries for considering each of the N molecules either as solute (A) or as solvent (B). In the quoted study, a cross-solvation matrix of 25 × 25 experimental value was introduced, considering 25 small molecules representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This experimental data was used to compare the relative accuracies of four popular condensed-phase force fields, namely GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In the present work, the comparison is extended to five additional force fields, namely GROMOS-54A7, GROMOS-ATB, OPLS-LBCC, AMBER-GAFF2, and OpenFF. Considering these nine force fields, the correlation coefficients between experimental values and simulation results range from 0.76 to 0.88, the root-mean-square errors (RMSEs) from 2.9 to 4.8 kJ mol-1, and average errors (AVEEs) from -1.5 to +1.0 kJ mol-1. In terms of RMSEs, GROMOS-2016H66 and OPLS-AA present the best accuracy (2.9 kJ mol-1), followed by OPLS-LBCC, AMBER-GAFF2, AMBER-GAFF, and OpenFF (3.3 to 3.6 kJ mol-1), and then by GROMOS-54A7, CHARM-CGenFF, and GROMOS-ATB (4.0 to 4.8 kJ mol-1). These differences are statistically significant but not very pronounced, and are distributed rather heterogeneously over the set of compounds within the different force fields.
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Affiliation(s)
- Sadra Kashefolgheta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
| | - Shuzhe Wang
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
| | - William E. Acree
- Department of Chemistry, University of North Texas1155 Union Circle Drive #305070DentonTexas 76203USA
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
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Warnau J, Wichmann K, Reinisch J. COSMO-RS predictions of logP in the SAMPL7 blind challenge. J Comput Aided Mol Des 2021; 35:813-818. [PMID: 34125358 DOI: 10.1007/s10822-021-00395-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 06/04/2021] [Indexed: 11/25/2022]
Abstract
We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.
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Affiliation(s)
- Judith Warnau
- Dassault Systemes Deutschland GmbH, Imbacher Weg 46, 51379, Leverkusen, Germany.
| | - Karin Wichmann
- Dassault Systemes Deutschland GmbH, Imbacher Weg 46, 51379, Leverkusen, Germany
| | - Jens Reinisch
- Dassault Systemes Deutschland GmbH, Imbacher Weg 46, 51379, Leverkusen, Germany
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43
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Heckel J, Batti F, Mathers RT, Walther A. Spinodal decomposition of chemically fueled polymer solutions. SOFT MATTER 2021; 17:5401-5409. [PMID: 33969370 DOI: 10.1039/d1sm00515d] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Out-of-equilibrium phase transitions driven by dissipation of chemical energy are a common mechanism for morphological organization and temporal programming in biology. Inspired by this, dissipative self-assembly utilizes chemical reaction networks (CRNs) that consume high-energy molecules (chemical fuels) to generate transient structures and functionality. While a wide range of chemical fuels and building blocks are now available for chemically fueled systems, so far little attention has been paid to the phase-separation process itself. Herein, we investigate the chemically fueled spinodal decomposition of poly(norbornene dicarboxylic acid) (PNDAc) solution, which is driven by a cyclic chemical reaction network. Our analysis encompasses both the molecular level in terms of the CRN, but also the phase separation process. We investigate the morphology of formed domains, as well as the kinetics and mechanism of domain growth, and develop a kinetic/thermodynamic hybrid model to not only rationalize the dependence of the system on fuel concentration and pH, but also open pathways towards predictive design of future fueled polymer systems.
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Affiliation(s)
- Jonas Heckel
- Institute for Macromolecular Chemistry, University of Freiburg, Stefan-Meier-Str. 31, 79104 Freiburg, Germany and Freiburg Materials Research Center (FMF), University of Freiburg, Stefan-Meier-Str. 21, 79104 Freiburg, Germany and Freiburg Center for Interactive Materials and Bioinspired Technologies (FIT), University of Freiburg, Georges-Köhler-Allee 105, 79110 Freiburg, Germany
| | - Fabio Batti
- Institute for Macromolecular Chemistry, University of Freiburg, Stefan-Meier-Str. 31, 79104 Freiburg, Germany
| | - Robert T Mathers
- Department of Chemistry, Pennsylvania State University, New Kensington, PA 15068, USA.
| | - Andreas Walther
- A3BMS Lab, Department of Chemistry, University of Mainz, Duesbergweg 10-14, 55128 Mainz, Germany. and Cluster of Excellence livMatS @ FIT - Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, Georges-Köhler-Allee 105, 79110 Freiburg, Germany
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44
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Borges R, Colby SM, Das S, Edison AS, Fiehn O, Kind T, Lee J, Merrill AT, Merz KM, Metz TO, Nunez JR, Tantillo DJ, Wang LP, Wang S, Renslow RS. Quantum Chemistry Calculations for Metabolomics. Chem Rev 2021; 121:5633-5670. [PMID: 33979149 PMCID: PMC8161423 DOI: 10.1021/acs.chemrev.0c00901] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Indexed: 02/07/2023]
Abstract
A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.
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Affiliation(s)
- Ricardo
M. Borges
- Walter
Mors Institute of Research on Natural Products, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil
| | - Sean M. Colby
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Susanta Das
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Arthur S. Edison
- Departments
of Genetics and Biochemistry and Molecular Biology, Complex Carbohydrate
Research Center and Institute of Bioinformatics, University of Georgia, Athens, Georgia 30602, United States
| | - Oliver Fiehn
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Tobias Kind
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Jesi Lee
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Amy T. Merrill
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Kenneth M. Merz
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Thomas O. Metz
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Jamie R. Nunez
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Dean J. Tantillo
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Lee-Ping Wang
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Shunyang Wang
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Ryan S. Renslow
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
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45
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Lind C, Pandey P, Pastor RW, MacKerell AD. Functional Group Distributions, Partition Coefficients, and Resistance Factors in Lipid Bilayers Using Site Identification by Ligand Competitive Saturation. J Chem Theory Comput 2021; 17:3188-3202. [PMID: 33929848 DOI: 10.1021/acs.jctc.1c00089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Small molecules such as metabolites and drugs must pass through the membrane of the cell, a barrier primarily comprising phospholipid bilayers and embedded proteins. To better understand the process of passive diffusion, knowledge of the ability of various functional groups to partition across bilayers and the associated energetics would be of utility. In the present study, the site identification by ligand competitive saturation (SILCS) methodology has been applied to sample the distributions of a diverse set of chemical solutes representing the functional groups of small molecules across phospholipid bilayers composed of 0.9:0.1 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine/cholesterol and a mixture of 0.52:0.18:0.3 1,2-dioleoyl-sn-glycero-3-phospho-l-serine/1,2-dioleoyl-sn-glycero-3-phosphocholine/cholesterol used in parallel artificial membrane permeability assay experiments. A combination of oscillating chemical potential grand canonical Monte Carlo and molecular dynamics in the SILCS simulations was applied to achieve solute sampling through the bilayers and surrounding aqueous environment from which the distribution of solutes and the functional groups they represent were obtained. Results show differential distribution of aliphatic versus aromatic groups with the former having increased sampling in the center of the bilayers versus in the region of the glycerol linker for the latter. Variations in the distribution of different polar groups are evident, with large differences between negative acetate and positive methylammonium with accumulation of the polar-neutral and acetate solutes above the bilayer head groups. Conversion of the distributions to absolute free energies allows for a detailed understanding of energetics of functional groups in different regions of the bilayers and for calculation of absolute free-energy profiles of multifunctional drug-like molecules across the bilayers from which partition coefficients and resistance factors suitable for insertion into the homogenous solubility-diffusion equation for calculation of permeability were obtained. Comparisons of the calculated bilayer/solution partition coefficients with 1-octanol/water experimental data for both drug-like molecules and the solutes show overall good agreement, validating the calculated distributions and associated absolute free-energy profiles.
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Affiliation(s)
- Christoffer Lind
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, Maryland 21201, United States
| | - Poonam Pandey
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, Maryland 21201, United States
| | - Richard W Pastor
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Alexander D MacKerell
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Baltimore, Maryland 21201, United States
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Nardi P, Laanbroek HJ, Nicol GW, Renella G, Cardinale M, Pietramellara G, Weckwerth W, Trinchera A, Ghatak A, Nannipieri P. Biological nitrification inhibition in the rhizosphere: determining interactions and impact on microbially mediated processes and potential applications. FEMS Microbiol Rev 2021; 44:874-908. [PMID: 32785584 DOI: 10.1093/femsre/fuaa037] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 08/10/2020] [Indexed: 12/11/2022] Open
Abstract
Nitrification is the microbial conversion of reduced forms of nitrogen (N) to nitrate (NO3-), and in fertilized soils it can lead to substantial N losses via NO3- leaching or nitrous oxide (N2O) production. To limit such problems, synthetic nitrification inhibitors have been applied but their performance differs between soils. In recent years, there has been an increasing interest in the occurrence of biological nitrification inhibition (BNI), a natural phenomenon according to which certain plants can inhibit nitrification through the release of active compounds in root exudates. Here, we synthesize the current state of research but also unravel knowledge gaps in the field. The nitrification process is discussed considering recent discoveries in genomics, biochemistry and ecology of nitrifiers. Secondly, we focus on the 'where' and 'how' of BNI. The N transformations and their interconnections as they occur in, and are affected by, the rhizosphere, are also discussed. The NH4+ and NO3- retention pathways alternative to BNI are reviewed as well. We also provide hypotheses on how plant compounds with putative BNI ability can reach their targets inside the cell and inhibit ammonia oxidation. Finally, we discuss a set of techniques that can be successfully applied to solve unresearched questions in BNI studies.
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Affiliation(s)
- Pierfrancesco Nardi
- Consiglio per la ricerca e l'analisi dell'economia agraria - Research Centre for Agriculture and Environment (CREA-AA), Via della Navicella 2-4, Rome 00184, Italy
| | - Hendrikus J Laanbroek
- Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands; Ecology and Biodiversity Group, Department of Biology, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Graeme W Nicol
- Laboratoire Ampère, École Centrale de Lyon, Université de Lyon, Ecully, 69134, France
| | - Giancarlo Renella
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padua, Viale dell'Università 16, 35020 Legnaro, Italy
| | - Massimiliano Cardinale
- Department of Biological and Environmental Sciences and Technologies - DiSTeBA, University of Salento, Centro Ecotekne - via Provinciale Lecce-Monteroni, I-73100, Lecce, Italy
| | - Giacomo Pietramellara
- Department of Agriculture, Food, Environment and Forestry, University of Firenze, P.le delle Cascine 28, Firenze 50144, Italy
| | - Wolfram Weckwerth
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, Vienna, 1090, Austria; Vienna Metabolomics Center (VIME), University of Vienna, Althanstrasse 14, Vienna, 1090, Austria
| | - Alessandra Trinchera
- Consiglio per la ricerca e l'analisi dell'economia agraria - Research Centre for Agriculture and Environment (CREA-AA), Via della Navicella 2-4, Rome 00184, Italy
| | - Arindam Ghatak
- Molecular Systems Biology (MOSYS), Department of Functional and Evolutionary Ecology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, Vienna, 1090, Austria
| | - Paolo Nannipieri
- Department of Agriculture, Food, Environment and Forestry, University of Firenze, P.le delle Cascine 28, Firenze 50144, Italy
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Kalayan J, Henchman RH. Convergence behaviour of solvation shells in simulated liquids. Phys Chem Chem Phys 2021; 23:4892-4900. [PMID: 33616583 DOI: 10.1039/d0cp05903j] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
A convenient way to analyse solvent structure around a solute is to use solvation shells, whereby solvent position around the solute is discretised by the size of a solvent molecule, leading to multiple shells around the solute. The two main ways to define multiple shells around a solute are either directly with respect to the solute, called solute-centric, or locally for both solute and solvent molecules alike. It might be assumed that both methods lead to solvation shells with similar properties. However, our analysis suggests otherwise. Solvation shells are analysed in a series of simulations of five pure liquids of differing polarity. Shells are defined locally working outwards from each molecule treated as a reference molecule using two methods: the cutoff at the first minimum in the radial distribution function and the parameter-free Relative Angular Distance method (RAD). The molecular properties studied are potential energy, coordination number and coordination radius. Rather than converging to bulk values, as might be expected for pure solvents, properties are found to deviate as a function of shell index. This behaviour occurs because molecules with larger coordination numbers and radius have more neighbours, which make them more likely to be connected to the reference molecule via fewer shells. The effect is amplified for RAD because of its more variable coordination radii and for water with its more open structure and stronger interactions. These findings indicate that locally defined shells should not be thought of as directly comparable to solute-centric shells or to distance. As well as showing how box size and cutoff affect the non-convergence, to restore convergence we propose a hybrid method by defining a new set of shells with boundaries at the uppermost distance of each locally derived shell.
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Affiliation(s)
- Jas Kalayan
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. and Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Richard H Henchman
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. and Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
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Abstract
Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.
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Bunker A, Róg T. Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery. Front Mol Biosci 2020; 7:604770. [PMID: 33330633 PMCID: PMC7732618 DOI: 10.3389/fmolb.2020.604770] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 11/02/2020] [Indexed: 12/12/2022] Open
Abstract
In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.
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Affiliation(s)
- Alex Bunker
- Division of Pharmaceutical Biosciences, Drug Research Program, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Tomasz Róg
- Department of Physics, University of Helsinki, Helsinki, Finland
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The Role of Structure and Biophysical Properties in the Pleiotropic Effects of Statins. Int J Mol Sci 2020; 21:ijms21228745. [PMID: 33228116 PMCID: PMC7699354 DOI: 10.3390/ijms21228745] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/12/2020] [Accepted: 11/16/2020] [Indexed: 12/13/2022] Open
Abstract
Statins are a class of drugs used to lower low-density lipoprotein cholesterol and are amongst the most prescribed medications worldwide. Most statins work as a competitive inhibitor of 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGR), but statin intolerance from pleiotropic effects have been proposed to arise from non-specific binding due to poor enzyme-ligand sensitivity. Yet, research into the physicochemical properties of statins, and their interactions with off-target sites, has not progressed much over the past few decades. Here, we present a concise perspective on the role of statins in lowering serum cholesterol levels, and how their reported interactions with phospholipid membranes offer a crucial insight into the mechanism of some of the more commonly observed pleiotropic effects of statin administration. Lipophilicity, which governs hepatoselectivity, is directly related to the molecular structure of statins, which dictates interaction with and transport through membranes. The structure of statins is therefore a clinically important consideration in the treatment of hypercholesterolaemia. This review integrates the recent biophysical studies of statins with the literature on the physiological effects and provides new insights into the mechanistic cause of statin pleiotropy, and prospective means of understanding the cholesterol-independent effects of statins.
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