1
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Zaman N, Azam SS. Quantum Dynamics and Bi Metal Force Field Parameterization Yielding Significant Antileishmanial Targets. J Chem Inf Model 2023; 63:1371-1385. [PMID: 36730993 DOI: 10.1021/acs.jcim.2c01100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Amid emerging drug resistance to metal inhibitors, high toxicity, and onerous drug delivery procedures, the computational design of alternate formulations encompassing functional metal-containing compounds greatly relies on large-scale atomistic simulations. Simulations particularly with Au(I), Ag, Bi(V), and Sb(V) pose a major challenge to elucidate their molecular mechanism due to the absence of force field parameters. This study thus quantum mechanically derives force field parameters of Bi(V) as an extension of the previous experimental study conducted on heteroleptic triorganobismuth(V) biscarboxylates of type [BiR3(O2CR')2]. We have modeled two organo-bismuth(V) carboxylates, which are optimized and parameterized along with the famous pentavalent antimonial drug: meglumine antimoniate using quantum mechanics original Seminarian methods with the SBKJC effective core potential (ECP) basis set. Furthermore, molecular dynamics (MD) simulations of bismuth- and antimony-containing compounds in complex with two enzymes, trypanothione synthetase-amidase (TSA) and trypanothione reductase, are performed to target the (T(SH)2) pathway at multiple points. MD simulations provide novel insights into the binding mechanism of TSA and highlight the role of a single residue Arg569 in modulating the ligand dynamics. Moreover, the presence of an ortho group in a ligand is emphasized to facilitate interactions between Arg569 and the active site residue Arg313 for higher inhibitory activity of TSA. This preliminary generation of parameters specific to bismuth validated by simulations in replica will become a preamble of future computational and experimental research work to open avenues for newer and suitable drug targets.
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Affiliation(s)
- Naila Zaman
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad45320, Pakistan
| | - Syed Sikander Azam
- Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University, Islamabad45320, Pakistan
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2
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Falbo E, Fusè M, Lazzari F, Mancini G, Barone V. Integration of Quantum Chemistry, Statistical Mechanics, and Artificial Intelligence for Computational Spectroscopy: The UV-Vis Spectrum of TEMPO Radical in Different Solvents. J Chem Theory Comput 2022; 18:6203-6216. [PMID: 36166322 PMCID: PMC9558374 DOI: 10.1021/acs.jctc.2c00654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Indexed: 11/30/2022]
Abstract
The ongoing integration of quantum chemistry, statistical mechanics, and artificial intelligence is paving the route toward more effective and accurate strategies for the investigation of the spectroscopic properties of medium-to-large size chromophores in condensed phases. In this context we are developing a novel workflow aimed at improving the generality, reliability, and ease of use of the available computational tools. In this paper we report our latest developments with specific reference to unsupervised atomistic simulations employing non periodic boundary conditions (NPBC) followed by clustering of the trajectories employing optimized feature spaces. Next accurate variational computations are performed for a representative point of each cluster, whereas intracluster fluctuations are taken into account by a cheap yet reliable perturbative approach. A number of methodological improvements have been introduced including, e.g., more realistic reaction field effects at the outer boundary of the simulation sphere, automatic definition of the feature space by continuous perception of solute-solvent interactions, full account of polarization and charge transfer in the first solvation shell, and inclusion of vibronic contributions. After its validation, this new approach has been applied to the challenging case of solvatochromic effects on the UV-vis spectra of a prototypical nitroxide radical (TEMPO) in different solvents. The reliability, effectiveness, and robustness of the new platform is demonstrated by the remarkable agreement with experiment of the results obtained through an unsupervised approach characterized by a strongly reduced computational cost as compared to that of conventional quantum mechanics and molecular mechanics models without any accuracy reduction.
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Affiliation(s)
- Emanuele Falbo
- Scuola
Normale Superiore di Pisa, piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Marco Fusè
- Scuola
Normale Superiore di Pisa, piazza dei Cavalieri 7, 56126 Pisa, Italy
- Dipartimento
di Medicina Molecolare e Traslazionale, Università di Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Federico Lazzari
- Scuola
Normale Superiore di Pisa, piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Giordano Mancini
- Scuola
Normale Superiore di Pisa, piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Vincenzo Barone
- Scuola
Normale Superiore di Pisa, piazza dei Cavalieri 7, 56126 Pisa, Italy
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3
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Lee S, Ermanis K, Goodman JM. MolE8: finding DFT potential energy surface minima values from force-field optimised organic molecules with new machine learning representations. Chem Sci 2022; 13:7204-7214. [PMID: 35799803 PMCID: PMC9214916 DOI: 10.1039/d1sc06324c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 05/23/2022] [Indexed: 11/21/2022] Open
Abstract
The use of machine learning techniques in computational chemistry has gained significant momentum since large molecular databases are now readily available. Predictions of molecular properties using machine learning have advantages over the traditional quantum mechanics calculations because they can be cheaper computationally without losing the accuracy. We present a new extrapolatable and explainable molecular representation based on bonds, angles and dihedrals that can be used to train machine learning models. The trained models can accurately predict the electronic energy and the free energy of small organic molecules with atom types C, H N and O, with a mean absolute error of 1.2 kcal mol-1. The models can be extrapolated to larger organic molecules with an average error of less than 3.7 kcal mol-1 for 10 or fewer heavy atoms, which represent a chemical space two orders of magnitude larger. The rapid energy predictions of multiple molecules, up to 7 times faster than previous ML models of similar accuracy, has been achieved by sampling geometries around the potential energy surface minima. Therefore, the input geometries do not have to be located precisely on the minima and we show that accurate density functional theory energy predictions can be made from force-field optimised geometries with a mean absolute error 2.5 kcal mol-1.
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Affiliation(s)
- Sanha Lee
- Yusuf Hamied Department of Chemistry, University of Cambridge Lensfield Road Cambridge CB2 1EW UK
| | | | - Jonathan M Goodman
- Yusuf Hamied Department of Chemistry, University of Cambridge Lensfield Road Cambridge CB2 1EW UK
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4
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Pant P, Pathak A, Jayaram B. Bicyclo-DNA mimics with enhanced protein binding affinities: insights from molecular dynamics simulations. J Biomol Struct Dyn 2022; 41:4040-4047. [PMID: 35403569 DOI: 10.1080/07391102.2022.2061594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
DNA-protein interactions occur at all levels of DNA expression and replication and are crucial determinants for the survival of a cell. Several modified nucleotides have been utilized to manipulate these interactions and have implications in drug discovery. In the present article, we evaluated the binding of bicyclo-nucleotides (generated by forming a methylene bridge between C1' and C5' in sugar, leading to a bicyclo system with C2' axis of symmetry at the nucleotide level) to proteins. We utilized four ssDNA-protein complexes with experimentally known binding free energies and investigated the binding of modified nucleotides to proteins via all-atom explicit solvent molecular dynamics (MD) simulations (200 ns), and compared the binding with control ssDNA-protein systems. The modified ssDNA displayed enhanced binding to proteins as compared to the control ssDNA, as seen by means of MD simulations followed by MM-PBSA calculations. Further, the Delphi-based electrostatic estimation revealed that the high binding of modified ssDNA to protein might be related to the enhanced electrostatic complementarity displayed by the modified ssDNA molecules in all the four systems considered for the study. The improved binding achieved with modified nucleotides can be utilized to design and develop anticancer/antisense molecules capable of targeting proteins or ssRNAs.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Pradeep Pant
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi, India
| | - Amita Pathak
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi, India
| | - B Jayaram
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi, India.,Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India
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5
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Tarzia A, Jelfs KE. Unlocking the computational design of metal-organic cages. Chem Commun (Camb) 2022; 58:3717-3730. [PMID: 35229861 PMCID: PMC8932387 DOI: 10.1039/d2cc00532h] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 02/22/2022] [Indexed: 12/11/2022]
Abstract
Metal-organic cages are macrocyclic structures that can possess an intrinsic void that can hold molecules for encapsulation, adsorption, sensing, and catalysis applications. As metal-organic cages may be comprised from nearly any combination of organic and metal-containing components, cages can form with diverse shapes and sizes, allowing for tuning toward targeted properties. Therefore, their near-infinite design space is almost impossible to explore through experimentation alone and computational design can play a crucial role in exploring new systems. Although high-throughput computational design and screening workflows have long been known as powerful tools in drug and materials discovery, their application in exploring metal-organic cages is more recent. We show examples of structure prediction and host-guest/catalytic property evaluation of metal-organic cages. These examples are facilitated by advances in methods that handle metal-containing systems with improved accuracy and are the beginning of the development of automated cage design workflows. We finally outline a scope for how high-throughput computational methods can assist and drive experimental decisions as the field pushes toward functional and complex metal-organic cages. In particular, we highlight the importance of considering realistic, flexible systems.
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Affiliation(s)
- Andrew Tarzia
- Department of Chemistry, Molecular Sciences Research Hub, Imperial College London, White City Campus, Wood Lane, London, W12 0BZ, UK.
| | - Kim E Jelfs
- Department of Chemistry, Molecular Sciences Research Hub, Imperial College London, White City Campus, Wood Lane, London, W12 0BZ, UK.
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6
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Mancini G, Fusè M, Lipparini F, Nottoli M, Scalmani G, Barone V. Molecular Dynamics Simulations Enforcing Nonperiodic Boundary Conditions: New Developments and Application to the Solvent Shifts of Nitroxide Magnetic Parameters. J Chem Theory Comput 2022; 18:2479-2493. [PMID: 35257572 PMCID: PMC9009096 DOI: 10.1021/acs.jctc.2c00046] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
![]()
Multiscale methods
combining quantum mechanics and molecular mechanics
(QM/MM) have become the most suitable and effective strategies for
the investigation of the spectroscopic properties of medium-to-large
size chromophores in condensed phases. In this context, we are developing
a novel workflow aimed at improving the generality, reliability, and
ease of use of the available computational tools. In this paper, we
report our latest developments with specific reference to a general
protocol based on atomistic simulations, carried out under nonperiodic
boundary conditions (NPBC). In particular, we add to our in house
MD engine a new efficient treatment of mean field electrostatic contributions
to energy and forces, together with the capability of performing the
simulations either in the canonical (NVT) or in the
isothermal–isobaric (NPT) ensemble. Next,
we provide convincing evidence that the NBPC approach enhanced by
specific tweaks for rigid body propagation, allows for the simulation
of solute–solvent systems with a minimum number of degrees
of freedom and large integration time step. After its validation,
this new approach is applied to the challenging case of solvatochromic
effects on the electron paramagnetic resonance (EPR) spectrum of a
prototypical nitroxide radical. To this end, we propose and validate
also an automated protocol to extract and weight simulation snapshots,
making use of a continuous description of the strength of solute–solvent
hydrogen bridges. While further developments are being worked on,
the effectiveness of our approach, even in its present form, is demonstrated
by the accuracy of the results obtained through an unsupervised approach
characterized by a strongly reduced computational cost as compared
to that of conventional QM/MM models, without any appreciable deterioration
of accuracy.
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Affiliation(s)
- Giordano Mancini
- Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
| | - Marco Fusè
- Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Universitaá di Pisa, Via G. Moruzzi 13, 56124 Pisa, Italy
| | - Michele Nottoli
- Dipartimento di Chimica e Chimica Industriale, Universitaá di Pisa, Via G. Moruzzi 13, 56124 Pisa, Italy
| | - Giovanni Scalmani
- Gaussian, Inc., 340 Quinnipiac Street, Building 40, Wallingford, Connecticut 06492, United States
| | - Vincenzo Barone
- Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
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7
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Gervasoni S, Spencer J, Hinchliffe P, Pedretti A, Vairoletti F, Mahler G, Mulholland AJ. A multiscale approach to predict the binding mode of metallo beta-lactamase inhibitors. Proteins 2022; 90:372-384. [PMID: 34455628 PMCID: PMC8944931 DOI: 10.1002/prot.26227] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/09/2021] [Accepted: 08/18/2021] [Indexed: 02/03/2023]
Abstract
Antibiotic resistance is a major threat to global public health. β-lactamases, which catalyze breakdown of β-lactam antibiotics, are a principal cause. Metallo β-lactamases (MBLs) represent a particular challenge because they hydrolyze almost all β-lactams and to date no MBL inhibitor has been approved for clinical use. Molecular simulations can aid drug discovery, for example, predicting inhibitor complexes, but empirical molecular mechanics (MM) methods often perform poorly for metalloproteins. Here we present a multiscale approach to model thiol inhibitor binding to IMP-1, a clinically important MBL containing two catalytic zinc ions, and predict the binding mode of a 2-mercaptomethyl thiazolidine (MMTZ) inhibitor. Inhibitors were first docked into the IMP-1 active site, testing different docking programs and scoring functions on multiple crystal structures. Complexes were then subjected to molecular dynamics (MD) simulations and subsequently refined through QM/MM optimization with a density functional theory (DFT) method, B3LYP/6-31G(d), increasing the accuracy of the method with successive steps. This workflow was tested on two IMP-1:MMTZ complexes, for which it reproduced crystallographically observed binding, and applied to predict the binding mode of a third MMTZ inhibitor for which a complex structure was crystallographically intractable. We also tested a 12-6-4 nonbonded interaction model in MD simulations and optimization with a SCC-DFTB QM/MM approach. The results show the limitations of empirical models for treating these systems and indicate the need for higher level calculations, for example, DFT/MM, for reliable structural predictions. This study demonstrates a reliable computational pipeline that can be applied to inhibitor design for MBLs and other zinc-metalloenzyme systems.
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Affiliation(s)
- Silvia Gervasoni
- Department of Pharmaceutical Sciences, University of Milan, Milan, Italy
| | - James Spencer
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Philip Hinchliffe
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | | | - Franco Vairoletti
- Laboratorio de Química Farmacéutica, Departamento de Química Orgánica, Facultad de Química, Universidad de la República (UdelaR), Avda. General Flores 2124, Montevideo, Uruguay
| | - Graciela Mahler
- Laboratorio de Química Farmacéutica, Departamento de Química Orgánica, Facultad de Química, Universidad de la República (UdelaR), Avda. General Flores 2124, Montevideo, Uruguay
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8
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Norjmaa G, Vidossich P, Maréchal JD, Ujaque G. Modeling Kinetics and Thermodynamics of Guest Encapsulation into the [M 4L 6] 12- Supramolecular Organometallic Cage. J Chem Inf Model 2021; 61:4370-4381. [PMID: 34505774 PMCID: PMC8479806 DOI: 10.1021/acs.jcim.1c00348] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
The encapsulation
of molecular guests into supramolecular hosts
is a complex molecular recognition process in which the guest displaces
the solvent from the host cavity, while the host deforms to let the
guest in. An atomistic description of the association would provide
valuable insights on the physicochemical properties that guide it.
This understanding may be used to design novel host assemblies with
improved properties (i.e., affinities) toward a given class of guests.
Molecular simulations may be conveniently used to model the association
processes. It is thus of interest to establish efficient protocols
to trace the encapsulation process and to predict the associated magnitudes
ΔGbind and ΔGbind⧧. Here, we report the calculation of the Gibbs energy barrier and
Gibbs binding energy by means of explicit solvent molecular simulations
for the [Ga4L6]12– metallocage
encapsulating a series of cationic molecules. The ΔGbind⧧ for encapsulation was estimated by means of umbrella sampling simulations.
The steps involved were identified, including ion-pair formation and
naphthalene rotation (from L ligands of the metallocage) during the
guest’s entrance. The ΔGbind values were computed using the attach–pull–release
method. The results reveal the sensitivity of the estimates on the
force field parameters, in particular on atomic charges, showing that
higher accuracy is obtained when charges are derived from implicit
solvent quantum chemical calculations. Correlation analysis identified
some indicators for the binding affinity trends. All computed magnitudes
are in very good agreement with experimental observations. This work
provides, on one side, a benchmarked way to computationally model
a highly charged metallocage encapsulation process. This includes
a nonstandard parameterization and charge derivation procedure. On
the other hand, it gives specific mechanistic information on the binding
processes of [Ga4L6]12– at
the molecular level where key motions are depicted. Taken together,
the study provides an interesting option for the future design of
metal–organic cages.
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Affiliation(s)
- Gantulga Norjmaa
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA), Universitat Autònoma de Barcelona, Cerdanyola del Valles, 08193 Cerdanyola del Vallès, Catalonia, Spain
| | - Pietro Vidossich
- Laboratory of Molecular Modeling and Drug Discovery, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Jean-Didier Maréchal
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA), Universitat Autònoma de Barcelona, Cerdanyola del Valles, 08193 Cerdanyola del Vallès, Catalonia, Spain
| | - Gregori Ujaque
- Departament de Química and Centro de Innovación en Química Avanzada (ORFEO-CINQA), Universitat Autònoma de Barcelona, Cerdanyola del Valles, 08193 Cerdanyola del Vallès, Catalonia, Spain
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9
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Nde J, Zhang P, Ezerski JC, Lu W, Knapp K, Wolynes PG, Cheung MS. Coarse-Grained Modeling and Molecular Dynamics Simulations of Ca 2+-Calmodulin. Front Mol Biosci 2021; 8:661322. [PMID: 34504868 PMCID: PMC8421859 DOI: 10.3389/fmolb.2021.661322] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 07/21/2021] [Indexed: 12/21/2022] Open
Abstract
Calmodulin (CaM) is a calcium-binding protein that transduces signals to downstream proteins through target binding upon calcium binding in a time-dependent manner. Understanding the target binding process that tunes CaM’s affinity for the calcium ions (Ca2+), or vice versa, may provide insight into how Ca2+-CaM selects its target binding proteins. However, modeling of Ca2+-CaM in molecular simulations is challenging because of the gross structural changes in its central linker regions while the two lobes are relatively rigid due to tight binding of the Ca2+ to the calcium-binding loops where the loop forms a pentagonal bipyramidal coordination geometry with Ca2+. This feature that underlies the reciprocal relation between Ca2+ binding and target binding of CaM, however, has yet to be considered in the structural modeling. Here, we presented a coarse-grained model based on the Associative memory, Water mediated, Structure, and Energy Model (AWSEM) protein force field, to investigate the salient features of CaM. Particularly, we optimized the force field of CaM and that of Ca2+ ions by using its coordination chemistry in the calcium-binding loops to match with experimental observations. We presented a “community model” of CaM that is capable of sampling various conformations of CaM, incorporating various calcium-binding states, and carrying the memory of binding with various targets, which sets the foundation of the reciprocal relation of target binding and Ca2+ binding in future studies.
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Affiliation(s)
- Jules Nde
- Department of Physics, University of Houston, Houston, TX, United States.,Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
| | - Pengzhi Zhang
- Department of Physics, University of Houston, Houston, TX, United States
| | - Jacob C Ezerski
- Department of Physics, University of Houston, Houston, TX, United States
| | - Wei Lu
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
| | - Kaitlin Knapp
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
| | - Peter G Wolynes
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
| | - Margaret S Cheung
- Department of Physics, University of Houston, Houston, TX, United States.,Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
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10
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Malek SMA, Kwan V, Saika-Voivod I, Consta S. Low Density Interior in Supercooled Aqueous Nanodroplets Expels Ions to the Subsurface. J Am Chem Soc 2021; 143:13113-13123. [PMID: 34375522 DOI: 10.1021/jacs.1c04142] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The interaction between water and ions within droplets plays a key role in the chemical reactivity of atmospheric and man-made aerosols. Here we report direct computational evidence that in supercooled aqueous nanodroplets a lower density core of tetrahedrally coordinated water expels the cosmotropic ions to the denser and more disordered subsurface. In contrast, at room temperature, depending on the nature of the ion, the radial distribution in the droplet core is nearly uniform or elevated toward the center. We analyze the spatial distribution of a single ion in terms of a reference electrostatic model. The energy of the system in the analytical model is expressed as the sum of the electrostatic and surface energy of a deformable droplet. The model predicts that the ion is subject to a harmonic potential centered at the droplet's center of mass. We name this effect "electrostatic confinement". The model's predictions are consistent with the simulation findings for a single ion at room temperature but not at supercooling. We anticipate this study to be the starting point for investigating the structure of supercooled (electro)sprayed droplets that are used to preserve the conformations of macromolecules originating from the bulk solution.
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Affiliation(s)
- Shahrazad M A Malek
- Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's A1B 3X7, Canada
| | - Victor Kwan
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Ivan Saika-Voivod
- Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's A1B 3X7, Canada.,Department of Applied Mathematics, Western University, London, Ontario N6A 3K7, Canada
| | - Styliani Consta
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
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11
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Barone V, Puzzarini C, Mancini G. Integration of theory, simulation, artificial intelligence and virtual reality: a four-pillar approach for reconciling accuracy and interpretability in computational spectroscopy. Phys Chem Chem Phys 2021; 23:17079-17096. [PMID: 34346437 DOI: 10.1039/d1cp02507d] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The established pillars of computational spectroscopy are theory and computer based simulations. Recently, artificial intelligence and virtual reality are becoming the third and fourth pillars of an integrated strategy for the investigation of complex phenomena. The main goal of the present contribution is the description of some new perspectives for computational spectroscopy, in the framework of a strategy in which computational methodologies at the state of the art, high-performance computing, artificial intelligence and virtual reality tools are integrated with the aim of improving research throughput and achieving goals otherwise not possible. Some of the key tools (e.g., continuous molecular perception model and virtual multifrequency spectrometer) and theoretical developments (e.g., non-periodic boundaries, joint variational-perturbative models) are shortly sketched and their application illustrated by means of representative case studies taken from recent work by the authors. Some of the results presented are already well beyond the state of the art in the field of computational spectroscopy, thereby also providing a proof of concept for other research fields.
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Affiliation(s)
- Vincenzo Barone
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.
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12
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Ryazantsev MN, Strashkov DM, Nikolaev DM, Shtyrov AA, Panov MS. Photopharmacological compounds based on azobenzenes and azoheteroarenes: principles of molecular design, molecular modelling, and synthesis. RUSSIAN CHEMICAL REVIEWS 2021. [DOI: 10.1070/rcr5001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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13
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Farkaš B, de Leeuw NH. A Perspective on Modelling Metallic Magnetic Nanoparticles in Biomedicine: From Monometals to Nanoalloys and Ligand-Protected Particles. MATERIALS (BASEL, SWITZERLAND) 2021; 14:3611. [PMID: 34203371 PMCID: PMC8269646 DOI: 10.3390/ma14133611] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 12/24/2022]
Abstract
The focus of this review is on the physical and magnetic properties that are related to the efficiency of monometallic magnetic nanoparticles used in biomedical applications, such as magnetic resonance imaging (MRI) or magnetic nanoparticle hyperthermia, and how to model these by theoretical methods, where the discussion is based on the example of cobalt nanoparticles. Different simulation systems (cluster, extended slab, and nanoparticle models) are critically appraised for their efficacy in the determination of reactivity, magnetic behaviour, and ligand-induced modifications of relevant properties. Simulations of the effects of nanoscale alloying with other metallic phases are also briefly reviewed.
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Affiliation(s)
- Barbara Farkaš
- School of Chemistry, Cardiff University, Cardiff CF10 3AT, UK;
| | - Nora H. de Leeuw
- School of Chemistry, Cardiff University, Cardiff CF10 3AT, UK;
- School of Chemistry, University of Leeds, Leeds LS2 9JT, UK
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14
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Michaels W, Zhao Y, Qin J. Atomistic Modeling of PEDOT:PSS Complexes II: Force Field Parameterization. Macromolecules 2021. [DOI: 10.1021/acs.macromol.1c00860] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Wesley Michaels
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Yan Zhao
- Department of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430070, China
| | - Jian Qin
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
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15
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Pant P, Pathak A, Jayaram B. Symmetric Nucleosides as Potent Purine Nucleoside Phosphorylase Inhibitors. J Phys Chem B 2021; 125:2856-2862. [PMID: 33715357 DOI: 10.1021/acs.jpcb.0c10553] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Nucleic acids are one of the most enigmatic biomolecules crucial to several biological processes. Nucleic acid-protein interactions are vital for the coordinated and controlled functioning of a cell, leading to the design of several nucleoside/nucleotide analogues capable of mimicking these interactions and hold paramount importance in the field of drug discovery. Purine nucleoside phosphorylase is a well-established drug target due to its association with numerous immunodeficiency diseases. Here, we study the binding of human purine nucleoside phosphorylase (PNP) to some bidirectional symmetric nucleosides, a class of nucleoside analogues that are more flexible due to the absence of sugar pucker restraints. We compared the binding energies of PNP-symmetric nucleosides to the binding energies of PNP-inosine/Imm-H (a transition-state analogue), by means of 200 ns long all-atom explicit-solvent Gaussian accelerated molecular dynamics simulations followed by energetics estimation using the MM-PBSA methodology. Quite interestingly, we observed that a few symmetric nucleosides, namely, ν3 and ν4, showed strong binding with PNP (-14.1 and -12.6 kcal/mol, respectively), higher than inosine (-6.3 kcal/mol) and Imm-H (-9.6 kcal/mol). This is rationalized by an enhanced hydrogen-bond network for symmetric nucleosides compared to inosine and Imm-H while maintaining similar van der Waals contacts. We note that the chemical structures of both ν3 and ν4, due to an additional unsaturation in them, resemble enzymatic transition states and fall in the category of transition-state analogues (TSAs), which are quite popular.
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Affiliation(s)
- Pradeep Pant
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi 110016, India
| | - Amita Pathak
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi 110016, India
| | - B Jayaram
- Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.,Supercomputing Facility for Bioinformatics & Computational Biology, Hauz Khas, New Delhi 110016, India.,Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
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16
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Pant P, Fisher M. Marshall's nucleic acid: From double-helical structure to a potent intercalator. Biophys Chem 2021; 269:106525. [PMID: 33352335 DOI: 10.1016/j.bpc.2020.106525] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 12/09/2020] [Accepted: 12/09/2020] [Indexed: 02/06/2023]
Abstract
Deoxyribonucleic acid (DNA) not only stores genetic information but also emerged as a popular drug target. Modified nucleotides/nucleosides have been extensively studied in recent years wherein the sugar/nucleobase/phosphate-backbone has been altered. Several such molecules are FDA approved, capable of targeting nucleic acids and proteins. In this article, we modified negatively charged phosphate backbone to marshall's acid-based neutral backbone and analyzed the resultant structures by utilizing Gaussian accelerated molecular dynamics simulations (1 μs) in aqueous media at 150 mM salt concentration. We noted that the double-helical marshall's nucleic acid structure was partially denatured during the course of simulations, however, after using conformationally locked sugar, the marshall's nucleic acid (hereby called MNA) maintained the double-helical structure throughout the simulations. Despite the fact that MNA has a more extended backbone than the regular DNA, surprisingly, both showed similar helical rise (~3.4 Å) along with a comparable Watson-Crick hydrogen bond profile. The backbone difference was majorly compensated in terms of helical twist (~56° (MNA) and ~ 35° (control DNA)). Further, we examined a few MNA based ss-dinucleotides as intercalating ligands for a regular B-DNA. Quite strikingly, the ligands unwinded the DNA and showed intercalating properties with high DNA binding affinities. Hence, the use of small fragments of MNA based molecules in DNA targeted drug discovery is foreseen.
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Affiliation(s)
- Pradeep Pant
- Department of Chemistry, Indian Institute of Technology Delhi, India.
| | - Maria Fisher
- Department of Biosciences, University of Helsinki, Finland
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17
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Mancini G, Del Galdo S, Chandramouli B, Pagliai M, Barone V. Computational Spectroscopy in Solution by Integration of Variational and Perturbative Approaches on Top of Clusterized Molecular Dynamics. J Chem Theory Comput 2020; 16:5747-5761. [PMID: 32697580 PMCID: PMC8009517 DOI: 10.1021/acs.jctc.0c00454] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
![]()
Multiscale QM/MM approaches have
become the most suitable and effective
methods for the investigation of spectroscopic properties of medium-
or large-size chromophores in condensed phases. On these grounds,
we are developing a novel workflow aimed at improving the generality,
reliability, and ease of use of the available tools. In the present
paper, we report the latest developments of such an approach with
specific reference to a general workplan starting with the addition
of acetonitrile to the panel of solvents already available in the
General Liquid Optimized Boundary (GLOB) model enforcing nonperiodic
boundary conditions (NPBC). Next, the solvatochromic shifts induced
by acetonitrile on both rigid (uracil and thymine) and flexible (thyrosine)
chromophores have been studied introducing in our software a number
of new features ranging from rigid-geometry NPBC molecular dynamics
based on the quaternion formalism to a full integration of variational
(ONIOM) and perturbative (perturbed matrix method (PMM)) approaches
for describing different solute–solvent topologies and local
fluctuations, respectively. Finally, thymine and uracil have been
studied also in methanol to point out the generality of the computational
strategy. While further developments are surely needed, the strengths
of our integrated approach even in its present version are demonstrated
by the accuracy of the results obtained by an unsupervised approach
and coupled to a computational cost strongly reduced with respect
to that of conventional QM/MM models without any appreciable accuracy
deterioration.
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Affiliation(s)
- Giordano Mancini
- Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
| | - Sara Del Galdo
- Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, I-56126 Pisa, Italy
| | | | - Marco Pagliai
- Dipartimento di Chimica "Ugo Schiff", Università degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Vincenzo Barone
- Scuola Normale Superiore di Pisa, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
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18
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Lukaczynska-Anderson M, Mamme MH, Ceglia A, Van den Bergh K, De Strycker J, De Proft F, Terryn H, Ustarroz J. The role of hydrogen bond donor and water content on the electrochemical reduction of Ni 2+ from solvents - an experimental and modelling study. Phys Chem Chem Phys 2020; 22:16125-16135. [PMID: 32638784 DOI: 10.1039/d0cp02408b] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Deep Eutectic Solvents (DESs) are hygroscopic liquids composed of a hydrogen bond donor (HBD) and acceptor (HBA). Their physical, chemical and electrochemical properties can be tailored to use them as solvents for different applications, i.e. electrodeposition, catalysis, extraction, etc. This can be done by changing the HBD, as well by adding water. However, the interrelated influence of H2O and HBD on the structure of the electrolyte, and on the behavior of the active species is not fully understood. In this work, we select nickel electrodeposition as a case study and we combine electrochemical techniques (cyclic voltammetry, chronoamperometry) with UV-vis spectroscopy and molecular dynamics to understand the influence of water and HBD on the electrochemical behaviour of DESs. The unique combination of these different experimental and modelling techniques provides new insights into the field. The addition of H2O changes, not only the interactions between the constituents of the liquid, but also the coordination of metal cations, which is reflected in the electrochemical performance of different DESs. More importantly, we show that, in the presence of very little (between 0.1 wt% and 2.8 wt%) and high (>4.5 wt%) water contents, DESs behave differently, and the changes in their electrochemical behavior are caused by both the complexation of metal cations and the electrolyte transport properties.
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Affiliation(s)
- Monika Lukaczynska-Anderson
- Vrije Universiteit Brussel, Research Group Electrochemical and Surface Engineering (SURF), Pleinlaan 2, 1050 Brussels, Belgium.
| | - Mesfin Haile Mamme
- Vrije Universiteit Brussel, Research Group Electrochemical and Surface Engineering (SURF), Pleinlaan 2, 1050 Brussels, Belgium. and Vrije Universiteit Brussel, Eenheid Algemene Chemie (ALGC), Pleinlaan 2, 1050 Brussels, Belgium
| | - Andrea Ceglia
- Vrije Universiteit Brussel, Brussels Photonic Team (B-PHOT), Pleinlaan 2, 1050 Brussels, Belgium
| | | | | | - Frank De Proft
- Vrije Universiteit Brussel, Eenheid Algemene Chemie (ALGC), Pleinlaan 2, 1050 Brussels, Belgium
| | - Herman Terryn
- Vrije Universiteit Brussel, Research Group Electrochemical and Surface Engineering (SURF), Pleinlaan 2, 1050 Brussels, Belgium.
| | - Jon Ustarroz
- Vrije Universiteit Brussel, Research Group Electrochemical and Surface Engineering (SURF), Pleinlaan 2, 1050 Brussels, Belgium. and Université Libre de Bruxelles, Chemistry of Surfaces, Interfaces and Nanomaterials (ChemSIN), Boulevard du Triomphe 2, 1050 Brussels, Belgium.
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19
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Macchiagodena M, Pagliai M, Andreini C, Rosato A, Procacci P. Upgraded AMBER Force Field for Zinc-Binding Residues and Ligands for Predicting Structural Properties and Binding Affinities in Zinc-Proteins. ACS OMEGA 2020; 5:15301-15310. [PMID: 32637803 PMCID: PMC7331063 DOI: 10.1021/acsomega.0c01337] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 05/13/2020] [Indexed: 05/08/2023]
Abstract
We developed a novel force field in the context of AMBER parameterization for glutamate and aspartate zinc(II)-binding residues. The interaction between the zinc ion and the coordinating atoms is represented by a spherical nonbonded parameterization. The polarization effect due to the zinc ion has been taken into account by redefining the atomic charges on the residues through accurate quantum mechanical calculations. The new zinc-binding ASP and GLU residues, along with the CYS and HIS zinc-binding residues, parameterized in a recent work [Macchiagodena M.;J. Chem. Inf. Model.2019, 59, 3803-3816], allow users to reliably simulate 96% of the Zn-proteins available in the Protein Data Bank. The upgraded force field for zinc(II)-bound residues has been tested performing molecular dynamics simulations with an explicit solvent and comparing the structural information with experimental data for five different proteins binding zinc(II) with GLU, ASP, HIS, and CYS. We further validated our approach by evaluating the binding free energy of (R)-2-benzyl-3-nitropropanoic acid to carboxypeptidase A using a recently developed nonequilibrium alchemical method. We demonstrated that in this setting it is crucial to take into account polarization effects also on the metal-bound inhibitor.
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Affiliation(s)
- Marina Macchiagodena
- Dipartimento
di Chimica “Ugo Schiff”, Università
degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Marco Pagliai
- Dipartimento
di Chimica “Ugo Schiff”, Università
degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
| | - Claudia Andreini
- Dipartimento
di Chimica “Ugo Schiff”, Università
degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
- Magnetic
Resonance Center (CERM), Università
degli Studi di Firenze, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Antonio Rosato
- Dipartimento
di Chimica “Ugo Schiff”, Università
degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
- Magnetic
Resonance Center (CERM), Università
degli Studi di Firenze, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Piero Procacci
- Dipartimento
di Chimica “Ugo Schiff”, Università
degli Studi di Firenze, Via della Lastruccia 3, 50019 Sesto Fiorentino, Italy
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20
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Bose S, Chakrabarty S, Ghosh D. Support Vector Regression-Based Monte Carlo Simulation of Flexible Water Clusters. ACS OMEGA 2020; 5:7065-7073. [PMID: 32280847 PMCID: PMC7143414 DOI: 10.1021/acsomega.9b02968] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
Molecular simulations based on classical force fields are computationally efficient but lack accuracy due to the empirical formulation of non-bonded interactions. Quantum mechanical (QM) methods, albeit accurate, have inhibitory computational costs for large molecules and clusters. Hence, to overcome the bottleneck, machine learning (ML)-based methods have been employed in the recent years. We had earlier reported a combined scheme of many-body expansion (MBE) and ML to predict the interaction energies of rigid water clusters. In this work, we proceed toward building a flexible water model using the ML-MBE scheme. This ML-MBE scheme has an error of <1% for interaction energy prediction in comparison to the parent QM method for flexible water decamers. Machine learning-based Monte Carlo simulations (MLMC) are performed with this water model, and the structural properties of these configurations are compared with those obtained from ab initio molecular dynamics (AIMD) and the TIP3P classical force field. The radial distribution functions, tetrahedral order parameters, and number of hydrogen bonds in AIMD and MLMC have a similar qualitative and quantitative trend, whereas the classical force fields show a significant deviation.
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Affiliation(s)
- Samik Bose
- School
of Chemical Sciences, Indian Association
for the Cultivation of Science, Kolkata 700032, West Bengal, India
| | - Suman Chakrabarty
- Department
of Chemical, Biological & Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Kolkata 700106, West Bengal, India
| | - Debashree Ghosh
- School
of Chemical Sciences, Indian Association
for the Cultivation of Science, Kolkata 700032, West Bengal, India
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21
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MacDermott-Opeskin H, McDevitt CA, O'Mara ML. Comparing Nonbonded Metal Ion Models in the Divalent Cation Binding Protein PsaA. J Chem Theory Comput 2020; 16:1913-1923. [PMID: 32059108 DOI: 10.1021/acs.jctc.9b01180] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Divalent metal cations are essential for many biological processes; however, accurately modeling divalent metal ions has proved a significant challenge for molecular dynamics force fields. Here we show that the choice of ion model influences the observed dynamics in PsaA, a metal binding protein from Streptococcus pneumoniae. We conduct extensive unbiased simulations and free energy calculations of PsaA bound to its cognate ligand Mn2+ and inhibitory ligand Zn2+ using three nonbonded ion models: a 12-6 model, a 12-6-4 model, and a multisite model. The observed coordination geometries and metal binding dynamics are sensitive to the choice of ion model, with the most dramatic differences observed in free energy calculations of ion release. We show that the conformational ensemble of Mn-bound PsaA is more similar to the crystallographic metal bound open state. This work extends the current model of PsaA metal binding and provides a framework for the rationalization of experimentally determined metal binding behavior. Our findings support the use of the 12-6-4 ion model for further simulations of divalent cation binding proteins.
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Affiliation(s)
- Hugo MacDermott-Opeskin
- Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory 2601, Australia
| | - Christopher A McDevitt
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria 3000, Australia
| | - Megan L O'Mara
- Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory 2601, Australia
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22
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Syrlybaeva RR, Talipov MR. CBSF: A New Empirical Scoring Function for Docking Parameterized by Weights of Neural Network. COMPUTATIONAL AND MATHEMATICAL BIOPHYSICS 2019. [DOI: 10.1515/cmb-2019-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
A new CBSF empirical scoring function for the estimation of binding energies between proteins and small molecules is proposed in this report. The final score is obtained as a sum of three energy terms calculated using descriptors based on a simple counting of the interacting protein-ligand atomic pairs. All the required weighting coefficients for this method were derived from a pretrained neural network. The proposed method demonstrates a high accuracy and reproduces binding energies of protein-ligand complexes from the CASF-2016 test set with a standard deviation of 2.063 kcal/mol (1.511 log units) and an average error of 1.682 kcal/mol (1.232 log units). Thus, CBSF has a significant potential for the development of rapid and accurate estimates of the protein-ligand interaction energies.
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Affiliation(s)
- Raulia R. Syrlybaeva
- Department of Chemistry and Biochemistry , New Mexico State University , Las Cruces, New Mexico 88003 , United States ; College of Pharmacy , University of Georgia , Athens , Georgia 30602 , United States
| | - Marat R. Talipov
- Department of Chemistry and Biochemistry , New Mexico State University , Las Cruces , New Mexico 88003 , United States
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23
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Ryazantsev MN, Nikolaev DM, Struts AV, Brown MF. Quantum Mechanical and Molecular Mechanics Modeling of Membrane-Embedded Rhodopsins. J Membr Biol 2019; 252:425-449. [PMID: 31570961 DOI: 10.1007/s00232-019-00095-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 09/10/2019] [Indexed: 12/20/2022]
Abstract
Computational chemistry provides versatile methods for studying the properties and functioning of biological systems at different levels of precision and at different time scales. The aim of this article is to review the computational methodologies that are applicable to rhodopsins as archetypes for photoactive membrane proteins that are of great importance both in nature and in modern technologies. For each class of computational techniques, from methods that use quantum mechanics for simulating rhodopsin photophysics to less-accurate coarse-grained methodologies used for long-scale protein dynamics, we consider possible applications and the main directions for improvement.
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Affiliation(s)
- Mikhail N Ryazantsev
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, Saint Petersburg, Russia, 198504
| | - Dmitrii M Nikolaev
- Saint-Petersburg Academic University - Nanotechnology Research and Education Centre RAS, Saint Petersburg, Russia, 194021
| | - Andrey V Struts
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, 85721, USA.,Laboratory of Biomolecular NMR, Saint Petersburg State University, Saint Petersburg, Russia, 199034
| | - Michael F Brown
- Department of Chemistry and Biochemistry, University of Arizona, Tucson, AZ, 85721, USA. .,Department of Physics, University of Arizona, Tucson, AZ, 85721, USA.
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24
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Macchiagodena M, Pagliai M, Andreini C, Rosato A, Procacci P. Upgrading and Validation of the AMBER Force Field for Histidine and Cysteine Zinc(II)-Binding Residues in Sites with Four Protein Ligands. J Chem Inf Model 2019; 59:3803-3816. [PMID: 31385702 DOI: 10.1021/acs.jcim.9b00407] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
We developed and validated a novel force field in the context of the AMBER parameterization for the simulation of zinc(II)-binding proteins. The proposed force field assumes nonbonded spherical interactions between the central zinc(II) and the coordinating residues. A crucial innovative aspect of our approach is to account for the polarization effects of the cation by redefining the atomic charges of the coordinating residues and an adjustment of Lennard-Jones parameters of Zn-interacting atoms to reproduce mean distance distributions. The optimal transferable parametrization was obtained by performing accurate quantum mechanical calculations on a training set of high-quality protein structures, encompassing the most common folds of zinc(II) sites. The addressed sites contain a zinc(II) ion tetra-coordinated by histidine and cysteine residues and represent about 70% of all physiologically relevant zinc(II) sites in the Protein Data Bank. Molecular dynamics simulations with explicit solvent, carried out on several zinc(II)-binding proteins not included in the training set, show that our model for zinc(II) sites preserves the tetra-coordination of the metal site with remarkable stability, yielding zinc(II)-X mean distances similar to experimental data. Finally, the model was tested by evaluating the zinc(II)-binding affinities, using the alchemical free energy perturbation approach. The calculated dissociation constants correlate satisfactorily with the experimental counterpart demonstrating the validity and transferability of the proposed parameterization for zinc(II)-binding proteins.
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Affiliation(s)
- Marina Macchiagodena
- Dipartimento di Chimica "Ugo Schiff" , Università degli Studi di Firenze , Via della Lastruccia 3 , 50019 Sesto Fiorentino , Italy
| | - Marco Pagliai
- Dipartimento di Chimica "Ugo Schiff" , Università degli Studi di Firenze , Via della Lastruccia 3 , 50019 Sesto Fiorentino , Italy
| | - Claudia Andreini
- Dipartimento di Chimica "Ugo Schiff" , Università degli Studi di Firenze , Via della Lastruccia 3 , 50019 Sesto Fiorentino , Italy.,Magnetic Resonance Center (CERM)-Università degli Studi di Firenze , Via L. Sacconi 6 , 50019 Sesto Fiorentino , Italy
| | - Antonio Rosato
- Dipartimento di Chimica "Ugo Schiff" , Università degli Studi di Firenze , Via della Lastruccia 3 , 50019 Sesto Fiorentino , Italy.,Magnetic Resonance Center (CERM)-Università degli Studi di Firenze , Via L. Sacconi 6 , 50019 Sesto Fiorentino , Italy
| | - Piero Procacci
- Dipartimento di Chimica "Ugo Schiff" , Università degli Studi di Firenze , Via della Lastruccia 3 , 50019 Sesto Fiorentino , Italy
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25
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Nikitin A, Del Frate G. Development of Nonbonded Models for Metal Cations Using the Electronic Continuum Correction. J Comput Chem 2019; 40:2464-2472. [PMID: 31301182 DOI: 10.1002/jcc.26021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 05/14/2019] [Accepted: 06/06/2019] [Indexed: 12/24/2022]
Abstract
The parametrization of classical nonbonded models of metal ions has been widely addressed in the recent years. Despite the continuous development of novel and more physically inspired functional forms, the 12-6 Lennard-Jones plus Coulomb potential is still the most adopted force field in molecular dynamics (MD) codes, owing to its simple form and easy implementation. However, due to the integer formal charge, unpolarizable force fields of ions may suffer from overestimated interatomic electrostatic interactions, leading to nonphysical clustering or repulsion between such full charges. The electronic continuum correction (ECC) can fix this problem through a simple inclusion of solvent polarization effects via ionic charge rescaling. In this work, the development of novel nonbonded models for mono, divalent, and highly charged metal ions is presented. For each metal species, the ionic charge has been scaled, according to the ECC. Lennard-Jones parameters have been optimized using experimental structural and thermodynamic properties as target quantities. Performances of the proposed models are discussed and compared with the literature data, while transferability attitudes among different and well-known water models are evaluated. © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Alexei Nikitin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russian Federation.,Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126, Pisa, Italy
| | - Gianluca Del Frate
- IMT School for Advanced Studies Lucca, Piazza S. Francesco 19, I-55100, Lucca, Italy
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26
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Xu M, Zhu T, Zhang JZH. Molecular Dynamics Simulation of Zinc Ion in Water with an ab Initio Based Neural Network Potential. J Phys Chem A 2019; 123:6587-6595. [DOI: 10.1021/acs.jpca.9b04087] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Mingyuan Xu
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - Tong Zhu
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
| | - John Z. H. Zhang
- State Key Lab of Precision Spectroscopy, Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
- Department of Chemistry, New York University, New York City, New York 10003, United States
- Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
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27
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Chandramouli B, Del Galdo S, Fusè M, Barone V, Mancini G. Two-level stochastic search of low-energy conformers for molecular spectroscopy: implementation and validation of MM and QM models. Phys Chem Chem Phys 2019; 21:19921-19934. [DOI: 10.1039/c9cp03557e] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The search for stationary points in the molecular potential energy surfaces (PES) is a problem of increasing relevance in molecular sciences especially for large, flexible systems featuring several large-amplitude internal motions.
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Affiliation(s)
| | | | | | - Vincenzo Barone
- Scuola Normale Superiore
- 56126 Pisa
- Italy
- Istituto Nazionale di Fisica Nucleare (INFN)
- Sezione di Pisa
| | - Giordano Mancini
- Scuola Normale Superiore
- 56126 Pisa
- Italy
- Istituto Nazionale di Fisica Nucleare (INFN)
- Sezione di Pisa
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28
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Chandramouli B, Del Galdo S, Mancini G, Barone V. Mechanistic insights into metal ions transit through threefold ferritin channel. Biochim Biophys Acta Gen Subj 2018; 1863:472-480. [PMID: 30496786 DOI: 10.1016/j.bbagen.2018.11.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 10/26/2018] [Accepted: 11/14/2018] [Indexed: 12/22/2022]
Abstract
BACKGROUND The mechanism of how the hydrophilic threefold channel (C3) of ferritin nanocages facilitates diffusion of diverse metal ions into the internal cavity remains poorly explored. METHODS Computational modeling and free energy estimations were carried out on R. catesbeiana H´ ferritin. Transit features and associated energetics for Fe2+, Mg2+, Zn2+ ions through the C3 channel have been examined. RESULTS We highlight that iron conduction requires the involvement of two Fe2+ ions in the channel. In such doubly occupied configuration, as observed in X-ray structures, Fe2+ is displaced from the internal site (stabilized by D127) at lower energetic cost. Moreover, comparison of Fe2+, Mg2+ and Zn2+ transit features shows that E130 geometric constriction provides not only an electrostatic anchor to the incoming ions but also differentially influence their diffusion kinetics. CONCLUSIONS Overall, the study provides insights into Fe2+ entry mechanism and characteristic features of metal-protein interactions that influence the metal ions passage. The dynamics data suggest that E130 may act as a metal selectivity gate. This implicates an ion-specific entry mechanism through the channel with the distinct diffusion kinetics being the discriminating factor. GENERAL SIGNIFICANCE Ferritin nanocages not only act as biological iron reservoirs but also have gained importance in material science as template scaffolds for synthesizing metal nanoparticles. This study provides mechanistic understanding on the conduction of different metal ions through the channel.
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Affiliation(s)
- Balasubramanian Chandramouli
- Compunet, Istituto Italiano di Tecnologia (IIT), Via Morego 30, I-16163 Genova, Italy; Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.
| | - Sara Del Galdo
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy; Consiglio Nazionale delle Ricerche, Istituto di Chimica dei Composti OrganoMetallici (ICCOMCNR), UOS di Pisa, Area della Ricerca CNR, Via G. Moruzzi 1, I-56124 Pisa, Italy
| | - Giordano Mancini
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy; Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, I-56127, Pisa, Italy
| | - Vincenzo Barone
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy; Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3, I-56127, Pisa, Italy
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Del Frate G, Nikitin A. Including Electronic Screening in Classical Force Field of Zinc Ion for Biomolecular Simulations. ChemistrySelect 2018. [DOI: 10.1002/slct.201802864] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Gianluca Del Frate
- Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa Italy
- Present address: IMT School for Advanced Studies Lucca Piazza S.Francesco 19 Lucca 55100 Italy
| | - Alexei Nikitin
- Engelhardt Institute of Molecular BiologyRussian Academy of Sciences Moscow 119991 Russia
- Scuola Normale Superiore Piazza dei Cavalieri 7 6126 Pisa Italy
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30
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Bose S, Dhawan D, Nandi S, Sarkar RR, Ghosh D. Machine learning prediction of interaction energies in rigid water clusters. Phys Chem Chem Phys 2018; 20:22987-22996. [PMID: 30156235 DOI: 10.1039/c8cp03138j] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Classical force fields form a computationally efficient avenue for calculating the energetics of large systems. However, due to the constraints of the underlying analytical form, it is sometimes not accurate enough. Quantum mechanical (QM) methods, although accurate, are computationally prohibitive for large systems. In order to circumvent the bottle-neck of interaction energy estimation of large systems, data driven approaches based on machine learning (ML) have been employed in recent years. In most of these studies, the method of choice is artificial neural networks (ANN). In this work, we have shown an alternative ML method, support vector regression (SVR), that provides comparable accuracy with better computational efficiency. We have further used many body expansion (MBE) along with SVR to predict interaction energies in water clusters (decamers). In the case of dimer and trimer interaction energies, the root mean square errors (RMSEs) of the SVR based scheme are 0.12 kcal mol-1 and 0.34 kcal mol-1, respectively. We show that the SVR and MBE based scheme has a RMSE of 2.78% in the estimation of decamer interaction energy against the parent QM method in a computationally efficient way.
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Affiliation(s)
- Samik Bose
- School of Mathematical and Computational Sciences, Indian Association for the Cultivation of Science, Kolkata-700032, West Bengal, India.
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31
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Chandramouli B, Del Galdo S, Mancini G, Tasinato N, Barone V. Tailor-made computational protocols for precise characterization of small biological building blocks using QM and MM approaches. Biopolymers 2018. [DOI: 10.1002/bip.23109] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Balasubramanian Chandramouli
- Scuola Normale Superiore, Piazza dei Cavalieri 7; Pisa 56126 Italy
- Compunet, Istituto Italiano di Tecnologia, via Morego 30; Genova Italy
| | - Sara Del Galdo
- Scuola Normale Superiore, Piazza dei Cavalieri 7; Pisa 56126 Italy
| | - Giordano Mancini
- Scuola Normale Superiore, Piazza dei Cavalieri 7; Pisa 56126 Italy
- Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3; Pisa 56127 Italy
| | - Nicola Tasinato
- Scuola Normale Superiore, Piazza dei Cavalieri 7; Pisa 56126 Italy
| | - Vincenzo Barone
- Scuola Normale Superiore, Piazza dei Cavalieri 7; Pisa 56126 Italy
- Istituto Nazionale di Fisica Nucleare (INFN) sezione di Pisa, Largo Bruno Pontecorvo 3; Pisa 56127 Italy
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32
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Yao K, Herr JE, Toth DW, Mckintyre R, Parkhill J. The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics. Chem Sci 2018; 9:2261-2269. [PMID: 29719699 PMCID: PMC5897848 DOI: 10.1039/c7sc04934j] [Citation(s) in RCA: 248] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 01/17/2018] [Indexed: 12/24/2022] Open
Abstract
We construct a robust chemistry consisting of a nearsighted neural network potential, TensorMol-0.1, with screened long-range electrostatic and van der Waals physics. It is offered in an open-source Python package and achieves millihartree accuracy and a scalability to tens-of-thousands of atoms on ordinary laptops.
Traditional force fields cannot model chemical reactivity, and suffer from low generality without re-fitting. Neural network potentials promise to address these problems, offering energies and forces with near ab initio accuracy at low cost. However a data-driven approach is naturally inefficient for long-range interatomic forces that have simple physical formulas. In this manuscript we construct a hybrid model chemistry consisting of a nearsighted neural network potential with screened long-range electrostatic and van der Waals physics. This trained potential, simply dubbed “TensorMol-0.1”, is offered in an open-source Python package capable of many of the simulation types commonly used to study chemistry: geometry optimizations, harmonic spectra, open or periodic molecular dynamics, Monte Carlo, and nudged elastic band calculations. We describe the robustness and speed of the package, demonstrating its millihartree accuracy and scalability to tens-of-thousands of atoms on ordinary laptops. We demonstrate the performance of the model by reproducing vibrational spectra, and simulating the molecular dynamics of a protein. Our comparisons with electronic structure theory and experimental data demonstrate that neural network molecular dynamics is poised to become an important tool for molecular simulation, lowering the resource barrier to simulating chemistry.
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Affiliation(s)
- Kun Yao
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - John E Herr
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - David W Toth
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - Ryker Mckintyre
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
| | - John Parkhill
- Dept. of Chemistry and Biochemistry , The University of Notre Dame du Lac , USA .
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Licari D, Fusè M, Salvadori A, Tasinato N, Mendolicchio M, Mancini G, Barone V. Towards the SMART workflow system for computational spectroscopy. Phys Chem Chem Phys 2018; 20:26034-26052. [DOI: 10.1039/c8cp03417f] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Is it possible to convert highly specialized research in the field of computational spectroscopy into robust and user-friendly aids to experiments and industrial applications?
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Affiliation(s)
- Daniele Licari
- Scuola Normale Superiore
- 56126 Pisa
- Italy
- Istituto Italiano di Tecnologia
- 16163 Genova
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