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Next Generation First-Principles Based Molecular Dynamics with Application to Biomimetic and Materials Design

English title Next Generation First-Principles Based Molecular Dynamics with Application to Biomimetic and Materials Design
Applicant Röthlisberger Ursula
Number 165863
Funding scheme Project funding (Div. I-III)
Research institution Laboratoire de chimie et biochimie computationnelles EPFL - SB - ISIC - LCBC
Institution of higher education EPF Lausanne - EPFL
Main discipline Physical Chemistry
Start/End 01.05.2016 - 30.04.2019
Approved amount 552'325.00
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Keywords (10)

molecular dynamics; Protein Engineering; artificial intelligence; multiscale modelling; Photovoltaics; machine learning; Biomimetic Design; Computational Chemistry; QM/MM ; Computational Biophysics

Lay Summary (German)

Lead
Die nächste Generation von first-principles Molecular Dynamik Simulationen mit Anwendungen in der Biomimetik und im Design von Materialien
Lay summary

Während unseres bisherigen SNF-Grants haben wir Multi-Rang-QML/QMH MD-Methoden entwickelt, die es erlauben, Simulationen unter Beibehalt der rechnerischen Kosten einer niederrangigen Methode mit der Genauigkeit einer hochrangigen Methode durchzuführen. Hierzu wurden komplett zeitreversible Multi-Zeitschritt (MTS) Integratoren verwendet. Durch die Verbindung des Programms CPMD mit anderen quantenchemischen Programmen (GAUSSIAN und TURBOMOLE) waren wir in der Lage, bspw. B3LYP oder MP2-Rechnungen mit einem um einen Faktor 5-10 tieferen Rechenaufwand durchzuführen.

Wir schlagen hier vor, die Flexibilität und Effizienz dieser MTS-QML/QMH Simulationen zu vergrössern (durch eine Erweiterung auf gemischte QM/MM- und QML&QMH/MM-Systeme; durch Implementierung stochastischer Thermostaten um Resonanzen zu minimieren; sowie die Entwicklung und Implementierung neuartiger Ansätze zur schnellen Berechnung von Austauschintegralen), und diese mit Ansätzen aus künstlicher Intelligenz (AI) zu kombinieren.

Die Kombination von Kraft-adaptierten klassischen Kraftfeldern mit spontanem Maschinellen Lernen (ML) für die Evaluierung quantenmechanischer Kräfte sollte es ermöglichen, Simulationen der nächsten Generation mit um Grössenordnungen längeren Zeitschritten durchzuführen.

Verschiedene Kombinationen dieser MTS-ML-MD-Ansätze (MTS-MM&QM(ML), MTS-QML(ML)-QMH, MTS-MM&QM(ML)/MM etc.) werden sich in einem breiten Anwendungsbereich in der Biologie und den Materialwissenschaften als äusserst nützlich erweisen. In diesem Antrag liegt der Schwerpunkt im Speziellen auf Anwendungen mit Bezug zu Peptid- und Proteindesign, sowie auf der Entwicklung biomimetischer Systeme für Katalyse und Lichtnutzung.

Direct link to Lay Summary Last update: 03.05.2016

Responsible applicant and co-applicants

Employees

Publications

Publication
From a week to less than a day: Speedup and scaling of coordinate-scaled exact exchange calculations in plane waves
Bircher Martin P., Rothlisberger Ursula (2020), From a week to less than a day: Speedup and scaling of coordinate-scaled exact exchange calculations in plane waves, in Computer Physics Communications, 247, 106943-106943.
Ruddlesden–Popper Phases of Methylammonium-Based Two-Dimensional Perovskites with 5-Ammonium Valeric Acid AVA 2 MA n –1 Pb n I 3 n +1 with n = 1, 2, and 3
Ashari-Astani Negar, Jahanbakhshi Farzaneh, Mladenović Marko, Alanazi Anwar Q. M., Ahmadabadi Iman, Ejtehadi Mohammad Reza, Dar M. Ibrahim, Grätzel Michael, Rothlisberger Ursula (2019), Ruddlesden–Popper Phases of Methylammonium-Based Two-Dimensional Perovskites with 5-Ammonium Valeric Acid AVA 2 MA n –1 Pb n I 3 n +1 with n = 1, 2, and 3, in The Journal of Physical Chemistry Letters, 10(13), 3543-3549.
Vertical Ionization Energies and Electron Affinities of Native and Damaged DNA Bases, Nucleotides, and Pairs from Density Functional Theory Calculations: Model Assessment and Implications for DNA Damage Recognition and Repair
Diamantis Polydefkis, Tavernelli Ivano, Rothlisberger Ursula (2019), Vertical Ionization Energies and Electron Affinities of Native and Damaged DNA Bases, Nucleotides, and Pairs from Density Functional Theory Calculations: Model Assessment and Implications for DNA Damage Recognition and Repair, in Journal of Chemical Theory and Computation, 15(3), 2042-2052.
Shedding Light on the Basis Set Dependence of the Minnesota Functionals: Differences Between Plane Waves, Slater Functions, and Gaussians
Bircher Martin P., López-Tarifa Pablo, Rothlisberger Ursula (2018), Shedding Light on the Basis Set Dependence of the Minnesota Functionals: Differences Between Plane Waves, Slater Functions, and Gaussians, in Journal of Chemical Theory and Computation, 15(1), 557-571.
Exploiting Coordinate Scaling Relations To Accelerate Exact Exchange Calculations
Bircher Martin P., Rothlisberger Ursula (2018), Exploiting Coordinate Scaling Relations To Accelerate Exact Exchange Calculations, in The Journal of Physical Chemistry Letters, 9(14), 3886-3890.
The Structure of the Protonated Serine Octamer
Scutelnic Valeriu, Perez Marta A. S., Marianski Mateusz, Warnke Stephan, Gregor Aurelien, Rothlisberger Ursula, Bowers Michael T., Baldauf Carsten, von Helden Gert, Rizzo Thomas R., Seo Jongcheol (2018), The Structure of the Protonated Serine Octamer, in Journal of the American Chemical Society, 140(24), 7554-7560.
A Versatile Multiple Time Step Scheme for Efficient ab Initio Molecular Dynamics Simulations
Liberatore Elisa, Meli Rocco, Rothlisberger Ursula (2018), A Versatile Multiple Time Step Scheme for Efficient ab Initio Molecular Dynamics Simulations, in Journal of Chemical Theory and Computation, 14(6), 2834-2842.
Plane-Wave Implementation and Performance of à-la-Carte Coulomb-Attenuated Exchange-Correlation Functionals for Predicting Optical Excitation Energies in Some Notorious Cases
Bircher Martin P., Rothlisberger Ursula (2018), Plane-Wave Implementation and Performance of à-la-Carte Coulomb-Attenuated Exchange-Correlation Functionals for Predicting Optical Excitation Energies in Some Notorious Cases, in Journal of Chemical Theory and Computation, 14(6), 3184-3195.
Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein
Bozkurt Esra, Perez Marta A. S., Hovius Ruud, Browning Nicholas J., Rothlisberger Ursula (2018), Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein, in Journal of the American Chemical Society, 140(13), 4517-4521.
Can Biomimetic Zinc Compounds Assist a (3 + 2) Cycloaddition Reaction? A Theoretical Perspective
Bozkurt Esra, Soares Thereza A., Rothlisberger Ursula (2017), Can Biomimetic Zinc Compounds Assist a (3 + 2) Cycloaddition Reaction? A Theoretical Perspective, in Journal of Chemical Theory and Computation, 13(12), 6382-6390.
Computational Characterization of the Dependence of Halide Perovskite Effective Masses on Chemical Composition and Structure
Ashari-Astani Negar, Meloni Simone, Salavati Amir Hesam, Palermo Giulia, Grätzel Michael, Rothlisberger Ursula (2017), Computational Characterization of the Dependence of Halide Perovskite Effective Masses on Chemical Composition and Structure, in The Journal of Physical Chemistry C, 121(43), 23886-23895.
How Rhodopsin Tunes the Equilibrium between Protonated and Deprotonated Forms of the Retinal Chromophore
van Keulen Siri C., Solano Alicia, Rothlisberger Ursula (2017), How Rhodopsin Tunes the Equilibrium between Protonated and Deprotonated Forms of the Retinal Chromophore, in Journal of Chemical Theory and Computation, 13(9), 4524-4534.
Stabilization of the Perovskite Phase of Formamidinium Lead Triiodide by Methylammonium, Cs, and/or Rb Doping
Syzgantseva Olga A., Saliba Michael, Grätzel Michael, Rothlisberger Ursula (2017), Stabilization of the Perovskite Phase of Formamidinium Lead Triiodide by Methylammonium, Cs, and/or Rb Doping, in The Journal of Physical Chemistry Letters, 8(6), 1191-1196.
Does Proton Conduction in the Voltage-Gated H + Channel hHv1 Involve Grotthuss-Like Hopping via Acidic Residues?
van Keulen Siri C., Gianti Eleonora, Carnevale Vincenzo, Klein Michael L., Rothlisberger Ursula, Delemotte Lucie (2017), Does Proton Conduction in the Voltage-Gated H + Channel hHv1 Involve Grotthuss-Like Hopping via Acidic Residues?, in The Journal of Physical Chemistry B, 121(15), 3340-3351.
Chapter 9. First Principles Methods in Biology: From Continuum Models to Hybrid Ab initio Quantum Mechanics/Molecular Mechanics
Dreyer Jens, Brancato Giuseppe, Ippoliti Emiliano, Genna Vito, De Vivo Marco, Carloni Paolo, Rothlisberger Ursula (2016), Chapter 9. First Principles Methods in Biology: From Continuum Models to Hybrid Ab initio Quantum Mechanics/Molecular Mechanics, in Tunon Inaki, Moliner Vicent (ed.), Royal Society of Chemistry, Cambridge, 294-339.

Collaboration

Group / person Country
Types of collaboration
Prof. Vassily Hatzimanikatis, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Michael Graetzel, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Paolo Carloni, GRS Jülich, RWTH Aachen Germany (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Thomas Rizzo, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Anatole von Lilienfeld, University of Basel Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Nigel Richards, Indiana University- Purdue University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Prof. Kai Johnsson, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
Prof. Thereza Soares, Universidade Federal de Pernambuco Brazil (South America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
CECAM School on Hybrid Quantum Mechanics / Molecular Mechanics (QM/MM) Approaches to Biochemistry and Beyond Talk given at a conference MIMIC: A New CPMD Interface for Multi-Scale Simulations 11.04.2019 Lausanne, Switzerland Röthlisberger Ursula;
Invited talk at the MPI for Solid State Physics Individual talk Next-generation first-principles based molecular dynamics: from biological systems to materials 06.03.2019 Stuttgart, Germany Röthlisberger Ursula;
CECAM workshop on Multiscale Modeling from Macromolecules to Cell: Opportunities and Challenges of Biomolecular Simulations Talk given at a conference Taking advantage of multiple scales 05.02.2019 Lausanne, Switzerland Röthlisberger Ursula;
Temple Rome Symposium - Computer Simulation in the Physical and Life Sciences Talk given at a conference Molecular Simulation Joining Forces with Artificial Intelligence 25.10.2018 Rome, Italy Röthlisberger Ursula;
NANOGE Fall Meeting Talk given at a conference Modelling Nucleation and Growth of Lead Halide Perovskites 22.10.2018 Torremolinos, Spain Röthlisberger Ursula;
4th Quantum Bioinorganic Chemistry Talk given at a conference Design of Biomimetic Metalloenzymes 04.09.2018 Bath, Great Britain and Northern Ireland Röthlisberger Ursula;
11th Congress on Electronic Structure Principles and Applications ESPA Talk given at a conference Next-Generation First-Principles Based Molecular Dynamics in Ground and Excited States 17.07.2018 Toledo, Spain Röthlisberger Ursula;
CECAM workshop on Physiological Role of Ions in the Brain: Towards a Comprehenisve View by Molecular Simulation Talk given at a conference Design of Biomimetic Metalloenzymes 21.05.2018 Pisa, Italy Röthlisberger Ursula;
International meeting on "Coupling Quantum Mechanics and Molecular Mechanics: Developments and Applications" Talk given at a conference Next Generation First-Principles Based QM/MM Simulations 05.09.2017 Manchester, Great Britain and Northern Ireland Röthlisberger Ursula;
SBDD Meeting Talk given at a conference De novo Design of Metalloenzymes and Biomimetic Systems 05.09.2017 Lausanne, Switzerland Röthlisberger Ursula;
Award Lecture at the 11EUCO-TCC - European Conference on Theoretical and Computational Chemistry Talk given at a conference When Computational Chemistry Meets Artificial Intelligence 04.09.2017 Barcelona, Spain Röthlisberger Ursula;
WATOC 2017 Talk given at a conference Next Generation First-Principles Based Multiscale Simulations: Computational Chemistry Meets Artificial Intelligence 01.09.2017 Münich, Germany Röthlisberger Ursula;
Plenary talk at the 17th International Conference on Density Functional Theory and ist Applications Talk given at a conference Nature Knows Best: Computational Strategies for the Design of Biomimetic Systems 21.08.2017 Tällberg, Sweden Röthlisberger Ursula;
PASC17 Talk given at a conference Computational Studies of Perovskite Solar Cell Materials 27.06.2017 Lugano, Switzerland Röthlisberger Ursula;
CECAM School on Hybrid Quantum Mechanics / Molecular Mechanics (QM/MM) Approaches to Biochemistry and Beyond Talk given at a conference Interaction between QM and MM Subsystem 15.05.2017 Lausanne, Switzerland Röthlisberger Ursula;
CECAM School on Hybrid Quantum Mechanics / Molecular Mechanics (QM/MM) Approaches to Biochemistry and Beyond Talk given at a conference MIMIC: A New Multiscale Interface for First-Principles Molecular Dynamics 15.05.2017 Lausanne, Switzerland Röthlisberger Ursula;
ACS Meeting Talk given at a conference MIMIC: A New Multiscale Interface for First-Principles Molecular Dynamics 21.08.2016 Philadelphia, United States of America Röthlisberger Ursula;
ACS Meeting Talk given at a conference First-Principles and Force Field Based Simulations of Organic/Inorganic Halide Perovskites 21.08.2016 Philadelphia, United States of America Röthlisberger Ursula;
8th Molecular Quantum Mechanics Conference Talk given at a conference Next Generation First-Prinicples Based Multiscale Simulations 26.06.2016 Uppsala, Sweden Röthlisberger Ursula;
CECAM workshop on "Exploring Chemical Space with Machine Learning and Quantum Mechanics" Talk given at a conference Evolutionary Algorithms for the Computational Design of Biomimetic Systems 30.05.2016 Zürich, Switzerland Röthlisberger Ursula;
CPMD2016 Conference Talk given at a conference New Multiscale Simulations in CPMD 18.05.2016 Chicago, United States of America Röthlisberger Ursula;


Self-organised

Title Date Place
CECAM Workshop - Frontiers and challenges of computing metals for biochemical, medical and technological applications 11.07.2018 paris, France
IAQMS 16-ICQC Satellite Conference on "Computational Chemistry meets Artificial Intelligence" 13.06.2018 Lausanne, Switzerland
QM/MM CECAM Tutorial 15.05.2017 Lausanne, Switzerland
CECAM Workshop - "1336 Enzyme Engineering : Bright Strategies from Theory and Experiments" 27.06.2016 Lausane, Switzerland

Awards

Title Year
Ron Hides Award 2017 of the American Society of Mass Spectrometry (for the paper: Infrared spectroscopy of mobility-selected H+ Gly-Pro-Gly-Gly (GPGG), JASMS DOI: 10.1007/s13361-015-1172-4 (2015) by A. Masson, M. Z. Kamrath, M. A. S. Perez, M. S. Glover, U. Rothlisberger, D. E. Clemmer, and T. R. Rizzo) 2017
Doron Prize 2016

Associated projects

Number Title Start Funding scheme
146645 Multiscale Simulations for Biological Signaling and Biomimetic Design 01.05.2013 Project funding (Div. I-III)
185092 Next-Generation Multiscale Molecular Dynamics: Promoting Computational Chemistry with Artificial Intelligence 01.05.2019 Project funding (Div. I-III)
130082 Multiscale Modelling of Electronically Triggered Biological Signalling 01.05.2010 Project funding (Div. I-III)

Abstract

Molecular dynamics (MD) simulations are arguably the most widely used molecular simulation method today and force-field based classical MD has been highly successful in the simulation of condensed phase systems for both biological and materials science applications. In addition, the advent of quantum mechanical based first-principles MD (FPMD) has enabled the treatment of electronic phenomena such as chemical reactions and photoexcitations. The introduction of multiscale mixed quantum mechanical/molecular mechanical (QM/MM) simulations in combination with a range of powerful enhanced sampling methods has allowed extending both spatial and temporal scales of FPMD. Together with the increase in computer power, it has become possible to perform FPMD with several 100 -1000 of atoms for 10-100 picoseconds. However, the combined challenge of system size, sampling time and high accuracy is still formidable. Ideally, one would like to perform MD simulations with the system size and sampling times typical of force-field based MD but with the accuracy of a high level ab initio method. During our previous SNF grant, we have developed multi-rung QML&QMH MD methods that allow to perform simulations with the accuracy of a high level method for essentially the cost of a lower level description. To this end, we have made extensive use of fully time-reversible multiple time step (MTS) integrators. By interfacing the FPMD program CPMD with other quantum chemical programs (GAUSSIAN and TURBOMOLE), we were able to perform e.g. B3LYP or MP2 based FPMD with a 5-10 times reduced computational cost. Here we propose, to further extend the versatility and efficiency of these MTS-QML&QMH simulations (via extension into a mixed QM/MM and QML&QMH/MM context; by implementation of stochastic thermostats to minimize resonances; and through the development and implementation of a novel approach for fast exact exchange) and to combine them with approaches from artificial intelligence. Combining force-matched classical force fields with on-the-fly machine learning (ML) for QM force evaluations, it should become feasible to run next-generation FPMD simulations with several orders of magnitude speedup.These MTS-ML MD approaches in various combinations (MTS-MM&QM(ML), MTS-QML(ML)-QMH, MTS-MM&QM(ML)/MM etc..) will be highly useful for a wide range of applications in biology and material science. In this proposal, we focus especially on applications related to peptide and protein engineering and the development of biomimetic systems for catalysis and light harvesting. The design of such biomimetic systems involves the steps of 1) FPMD or QM/MM simulations of the mechanism of action of the natural target; 2) analysis of the simulation data and identification of the relevant descriptor that influence the function of the natural system and 3) search of chemical and/or sequence space for optimal biomimetic counter parts. For all three steps, we will combine molecular simulations with approaches from artificial intelligence: For step 1), the use of an on-the-fly machine learning approach will enable highly efficient force evaluations that can be used as lower level forces within an MTS scheme. Feature selection and causality inference techniques will be crucial for an identification of the relevant descriptor in the highly dimensional simulation data generated in step 1) and last but not least, in step 3) efficient explorations of chemical and sequence space will be performed with the help of evolutionary optimization algorithms (genetic algorithms and particle swarm optimization) by using and further extending the program toolbox EVOLVE that we have been developing during our previous SNF grants.
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