Mercedes Alonso

General Chemistry Department (ALGC), Vrije Universiteit Brussel (VUB), Pleinlaan 2, Brussels, Belgium

Creating functional nanoscale devices using single molecules as active electronic components is the ultimate goal of the field of molecular electronics. Besides their potential to meet the growing demand for miniaturization of electronics, molecular electronics opens up the possibility of devices with novel, unforeseen functionalities beyond silicon-based technologies, such as molecular switches. Through a bottom-up quantum chemistry approach, we have shown that expanded porphyrins are flexible enough to switch between different π-conjugation topologies encoding distinct electronic properties and aromaticity.^[1]Since these topology/aromaticity switches can be induced by different external stimuli,^[2]these macrocycles represent a unique platform to develop molecular switches for different nanoelectronic applications.

The first application involves the conductance switching in molecular junctions through aromaticity and topology changes. In this regard, the electron transport properties of the different states of the switches were carefully investigated with the non-equilibrium Green´s function formalism in combination with density functional theory for various configurations of the gold contacts.^[3]Our findings reveal that the negative relationship between conductance and molecular aromaticity or polarizability does not hold for most of the configurations of the molecular junctions, so we devise new selection rules to predict the occurrence of quantum interference around the Fermi level for Hückel and Möbius systems.^[4]A second application concerns the design of bithermoelectric switches, an entirely new class of switches that revert the direction of the heat and /or charge transport. Our in-house calculations reveal that the Hückel-Möbius topology switch in heptaphyrins causes the Seedbeck coefficient or thermopower to change considerably from +50 mV/K to -40 mV/K.^[5]Finally, the mechanical activation of this novel type of switches is explored for the first time, leading to a straightforward approach based on distance matrices for the selection of pulling scenarios that promote either the Hückel or the Möbius topology.^[6] Overall, our work demonstrates how the concept of aromaticity and molecular topology can be exploited to create a novel type of efficient switching devices.^[7]

Figure 1.A bottom-up quantum chemical approach to design efficient nanoscale devices.

Recording:

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References

[1] M. Alonso, P. Geerlings, F. De Proft, Chem. Eur. J. 2013, 19, 1617.

[2] M. Alonso, B. Pinter, P. Geerlings, F. De Proft, Chem. Eur. J2015, 21, 17631; T. Woller, J. Contreras-García, P. Geerlings, F. De Proft, M. Alonso, Phys. Chem. Chem. Phys. 2016, 18, 11885;

[3] T. Stuyver, F. De Proft, P. Geerlings, M. Perrin, M. Alonso, J. Am. Chem. Soc.2018, 140, 1313.

[4] T. Stuyver, S. Fias, P. Geerlings, F. De Proft, M. Alonso, J. Phys. Chem. C2018, 122, 19482.

[5] T. Stuyver, P. Geerlings, F. De Proft, M. Alonso, J. Phys. Chem. C2018, 122, 24436.

[6] T. Bettens, M. Hoffmann, M. Alonso, P. Geerlings, A. Dreuw, F. De Proft, Chem. Eur. J. 2021, ASAP.

[7] Woller, T.; Geerlings, P.; De Proft, F.; Champagne, B.; Alonso, M. J. Phys. Chem. C2019, 123, 7318.

Dr. Edina Rosta

Senior Lecturer
King's College London

Abstract

Important biological processes taking place on the millisecond to second time scales are too slow to model using unbiased atomistic simulations. To obtain free energy profiles on long time scales, enhanced sampling methods have been developed. We show that novel Markov modelling-based tools can be used to analyse biased and unbiased simulations. Using our dynamic weighted histogram analysis method (DHAM), systematic errors due to insufficient global convergence can be corrected [1]. In addition, DHAM also provides direct kinetic information on the conformational transitions intrinsic to the system. We also demonstrate that a variationally optimal kinetic coarse graining allows us to obtain Markov models, where not only metastable, but also transition states can be automatically identified [2]. Applications include analysis of molecular dynamics simulations of RAF kinases [3] and umbrella sampling quantum classical QM/MM simulations of catalytic reactions [4].

James W. Gauld, Professor

Department of Chemistry and Biochemistry,
University of Windsor,
Windsor,
Ontario, N9B 3P4
Canada

Abstract

Elucidating the properties and chemistry of enzymes has long been of significant importance. This is due in part to the fact that they are central to many physiological processes that occur in cells. In particular, they are critical for ensuring that metabolically important reactions that occur within cells and organisms occur with life-sustaining rates, efficiency, and accuracy. Furthermore, they often achieve this under relatively mild conditions. Thus, in addition to the fundamental knowledge to be gained, they also present tremendous potential health and industrial benefits.
Indeed, it has been estimated that in the US more than 90% of chemical and pharmaceutical manufacturing requires catalysts.¹ Meanwhile, due to their critical physiological roles, enzymes are often the desired target of therapeutic drugs. Recently, the World Health Organization declared "antibiotic resistance one of the biggest threats to global health, food security, and development".² Rational design is a powerful tool for developing new drugs to combat this present and growing threat. For those that target enzymes this requires detailed knowledge of the latter's active site structures, properties, and mechanisms. Unfortunately, this knowledge is often at best limited.
^3,4Computational enzymology, in its broadest sense, is the use of computers to study the properties and mechanisms of enzymes. However, one of its major goals is to elucidate the catalytic mechanism of an enzyme or enzymes, the role of their key active site residues, and/or surrounding protein and solvent environment. Nowadays there are a range of computational methods available to the researcher that can be brought to bear on such challenges including molecular dynamics, quantum mechanical (QM)-chemical cluster, quantum mechanical/molecular mechanic (QM/MM). Increasingly, it is common to complementarily apply several of these methods.
In this lecture we will discuss several key aspects of computational enzymology including chemical model construction, commonly applied computational methods and their complementary application and challenges. These will be illustrated using examples from the literature as well as our own research in the Gauld group.

James W. Gauld

Department of Chemistry and Biochemistry,
University of Windsor,
Windsor,
Ontario, N9B 3P4
Canada

Video Recording

Video is available only for registered users.

Abstract

Elucidating the properties and chemistry of enzymes has long been of significant importance. This is partly due to the fact that they are central to many physiological processes occurring in cells. Indeed, they are critical for ensuring that metabolically important reactions within cells and organisms occur at life-sustaining rates, efficiency, and accuracy. Impressively, they often achieve this under relatively mild conditions. Thus, in addition to the fundamental knowledge to be gained, they also present tremendous potential health and industrial benefits. Indeed, it has been estimated that in the US more than 90% of chemical and pharmaceutical manufacturing requires catalysts.¹ Meanwhile, due to their critical physiological roles, enzymes are often the target of therapeutic drugs. Recently, the World Health Organization declared "antibiotic resistance one of the biggest threats to global health, food security, and development".² Rational design is a powerful tool for developing new drugs to combat this present and growing threat.^3,4 For those that target enzymes this requires detailed knowledge of the latter's active site structure, properties, and mechanisms. Unfortunately, this knowledge is often limited.

Computational enzymology is the application of computational chemistry methods to the study enzymes. One of its major goals is to elucidate enzyme's catalytic mechanisms, the role of active site residues, as well as the surrounding protein/solvent environment. Nowadays, there are a range of computational methods available to the researcher including molecular dynamics, quantum mechanical (QM)-chemical cluster, quantum mechanical/molecular mechanic (QM/MM). Increasingly, it is common to complementarily apply several of these methods. Each method has its strengths and limitations, which themselves at times can teach us about some aspect of enzymology. As a result, the modern practitioner must increasingly be adept at multiple methodologies.

In this lecture we will discuss what is computational enzymology, as well as practicalities of such aspects as chemical model construction, commonly applied computational methods and their application as well as challenges. These will be illustrated using examples from the literature and research from the Gauld group.

Professor György M Keserű

Medicinal Chemistry, Research Center for Natural Sciences, Budapest, Hungary

Covalent drugs are electrophilic molecules that bound to the target protein by forming covalent bond with the targeted nucleophilic residue at the binding site. Formerly, covalent inhibitors were typically filtered out in drug discovery programs due to the risk of off-target activity attributed to their reactivity. Few compounds acting by covalent mechanism of action were discovered serendipitously. However, a paradigm change has occurred around the millennium owing to the recognition of distinct therapeutic advantages of covalent inhibition that include potentially full target occupancy and long-action, decoupling pharmacodynamics from pharmacokinetics. Therefore, the rational design of targeted covalent inhibitors (TCIs) has gained increased attention.

The binding of covalent inhibitors follows a two-step mechanism including the first non-covalent binding stage that is the molecular recognition of the non-covalent scaffold. Then the electrophilic functionality of the inhibitor, called warhead reacts with the targeted nucleophilic sidechain of the protein. Here I would focus both steps at two different levels. First I discuss virtual screening applications that allow the prioritization of compounds for experimental testing. After the evaluation of available covalent docking tools [1] we developed new methodologies that allow warhead independent docking of potential covalent inhibitors [2-4]. Next I turned to the accurate prediction of the binding free energy of covalent inhibitors by QM/MM calculations [5]. This approach allows the investigation of the molecular mechanism of action that together with the thermodynamic characterisation facilitate the design of potent covalent inhibitors [6,7].

Recording:

Video is available only for registered users.

References:

1. Andrea Scarpino, Gyorgy G Ferenczy and György M Keserű:Comparative Evaluation of Covalent Docking Tools Journal of Chemical Information and Modeling, 2018, 58 (7), 1441-1458.
2. Andrea Scarpino, László Petri, Damijan Knez, Tímea Imre, Péter Ábrányi-Balogh, György G. Ferenczy, Stanislav Gobec and György M. Keserű:WIDOCK: a reactive docking protocol for virtual screening of covalent inhibitors Journal of Computer-Aided Molecular Design, 2021, 35, 223–244.
3. Andrea Scarpino, György G. Ferenczy, György M. Keserű:Binding Mode Prediction and Virtual Screening Applications by Covalent Docking In: Protein-Ligand Interactions and Drug Design (ed. Flavio Ballante), Springer, 2021, pp. 73-88.
4. Moira Rachman, Andrea Scarpino, Dávid Bajusz, Gyula Pálfy, István Vida, András Perczel, Xavier Barril, György M Keserű:DUckCov: a Dynamic Undocking‐based Virtual Screening Protocol for Covalent Binders ChemMedChem, 2019, 14, 1011-1021. 
5. Levente M. Mihalovits, György G. Ferenczy, György M. Keserű:The role of quantum chemistry in covalent inhibitor design International Journal of Quantum Chemistry, 2021, 1-17
6. Levente M. Mihalovits, György G. Ferenczy, György M. Keserű:Affinity and Selectivity Assessment of Covalent Inhibitors by Free Energy Calculations Journal of Chemical Information and Modeling, 2020, 60 (12), 6579-6594.
7. Levente M. Mihalovits, György G. Ferenczy, György M. Keserű:Mechanistic and thermodynamic characterization of oxathiazolones as potent and selective covalent immunoproteasome inhibitors Computational and Structural Biotechnology Journal, 2021, 19, 4486-4496.

Joakim Halldin Stenlid

Department of Physics, Stockholm University, Stockholm, Sweden

Video Recording

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Abstract

When interacting with electron-donors, neutral compounds of copper, silver and gold form bonds that are similar to hydrogen and halogen bonds. This type of bonding is referred to as regium bonding and it have been used to rationalize e.g. noble metal catalysis. Compounds donating regium, halogen and hydrogen bonds have in common local regions deficient in electron density, known as σ-holes. The chemistry of such regions can be characterized by local maxima in the electrostatic potential evaluated on contour surfaces of constant electron density (V_S,max); the position of the VS,max identify sites susceptible to interactions with nucleophiles, e.g. H₂O, H₂S, NH₃ and CO, while the magnitude of a V_S,max scales with the strength of the corresponding interaction. By this approach, information on the reaction and interaction tendencies of a compound can be readily accessed by standard DFT calculations. Regium bonds contains contributions from electrostatics, but also from polarization and charge-transfer. The latter are not directly captured by VS,max, but can be well-described by a newly introduced property called the local surface electron attachment energy. Minima in this property (E_S,min) provide a measure of the local electron affinity. E_S,min is used complementary to V_S,max to identity and rank interaction sites.
The use of molecular properties, such as the electrostatic potential and the electron attachment energies, is generally referred to as the Molecular Surface Property Approach (MSPA). These properties can be computed by e.g. DFT and provides estimate of reaction and/or interaction propensities of multiple sites of a compound from a single calculation. Historically MSPA has primarily been employed within the molecular science. The current presentation will exemplify how the MSPA can also be used as a guide to understand and predict the chemistry of materials and nanoparticles, opening up for a new realm of applications..

Professor Ivan Rivalta

Dipartimento di Chimica Industriale “Toso Montanari”, Università di Bologna, Bologna, Italy

Laboratoire de Chimie UMR 5182, École Normale Supérieure de Lyon, CNRS, UCBL, Lyon, France

Two-dimensional electronic spectroscopy (2DES) is a developing multidimensional technique based on ultrashort laser pulses used to track electronic transitions in complex systems with femtosecond spectral and time resolution. 2DES in the ultraviolet (2DUV) can be used to investigate structure, conformation dynamics, energy transfer, and chemical/photochemical reactivity in a wide range of systems in physical chemistry, energy sciences and biophysics. The interpretation of 2D electronic spectra is challenging and computational modeling is required to disentangle the congested information contained in the nonlinear optical response of the sample. In this presentation, the 2DES technique and its theoretical basis are introduced along with an illustration of the computational tools and protocols that we developed to perform first-principles simulations of 2DES spectra.[1] The methodology has been so far applied to the study of structure and dynamics of various biological systems, including proteic systems [2], organic fluorescent probes [3] and DNA/RNA nucleobases.[4] Wavefunctions methods have been used to reliably calculate the electronic properties of multichromophoric systems, and compared with time-dependent density functional theory methodologies, using hybrid QM/MM schemes and in conjunction with molecular dynamics techniques to assess environmental and conformational effects that shape the 2D electronic spectra [5].

Recording:

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References

1. I. Rivalta, Nenov A., Cerullo G., Mukamel S. and Garavelli M. Int. J. Quantum Chem. 2014, 114, 85-93; Segarra-Marti J., Mukamel, S., Garavelli, M., Nenov, A. and Rivalta I. Top. Curr. Chem. 2018, 376, 24.

2. Nenov A., Mukamel S., Garavelli M. and Rivalta I. J. Chem. Theory Comput. 2015, 11, 3755-3771.

3. Nenov A., Giussani A., Fingerhut B. P., Rivalta I., Dumont E., Mukamel S. and Garavelli M. Phys. Chem. Chem. Phys. 2015, 46, 30925-30936.

4. Segarra-Marti J., Jaiswal V. K., Pepino A. J., Giussani A., Nenov A., Mukamel S., Garavelli M. and Rivalta I. Faraday Discuss. 2018, 207, 233-250.

5. Borrego Varillas R., Nenov A., Ganzer L., Oriana A., Manzoni C., Rivalta I., Mukamel S., Garavelli M., Cerullo G. Chem. Sci., 2019,10, 9907-9921; Segarra-Marti J., Segatta F., Mackenzie T.A., Nenov, A., Rivalta I., Bearpark M.J., Garavelli M. Faraday Discuss., 2020, 221, 219

Professor Samer Gozem

Department of Chemistry, Georgia State University, Atlanta, GA 30303, USA

UV-visible and photoelectron spectroscopy are powerful tools for probing the structure of
matter from the subatomic to the bulk scale. The experimental spectra are generally
plotted using two properties: energies and absorption strength (the latter typically reported
as molar attenuation coefficients or cross sections). Energies and transition strengths
could also be predicted from first principles with quantum chemical methods. In the gas
phase, experiments and computations can be reconciled when the appropriate quantum
chemical methods are used. In the condensed phase, however, experimental spectra are
shifted and broadened by intermolecular interactions that complicate the comparison
between theory and computations. At the same time, the condensed-phase spectra
encode potential important information about these intermolecular interactions and how
they modulate a solute’s electronic structure. The first part of the presentation will cover
the basics of computational spectroscopy, and discuss how computed energies and
intensities can be compared with experimental ones. The second part of the presentation
will bring the computations into the condensed phase with hybrid quantum chemical /
molecular mechanical (QM/MM) models, which can be used to understand the effect of a
solvent (or a protein host) on the spectroscopic properties of a solute (or cofactor).

Recording:

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References:

1. Gozem, S.; Krylov, A.I. The ezSpectra suite: An easy‐to‐use toolkit for
spectroscopy modeling. WIREs Comp. Mol. Sci. e1546. 2021.
2. Tarleton, A.; Garcia-Alvarez, J.; Wynn, A.; Awbrey, C.; Roberts, T.; Gozem, S.
OS100: A Benchmark Set of 100 Digitized UV-Visible Spectra and Derived
Experimental Oscillator Strengths. ChemRxiv 2021. This content is a preprint and
has not been peer-reviewed.
3. Dratch, B.D.; Orozco-Gonzalez, Y.; Gadda, G.; Gozem, S. The Ionic Atmosphere
Effect on the Absorption Spectrum of a Flavoprotein: A Reminder to Consider
Solution Ions. J. Phys. Chem. Lett. 12 (34), 8384–8396. 2021.
4. Orozco-Gonzalez, Y.; Kabir, M.P.; Gozem, S. Electrostatic Spectral Tuning Maps
for Biological Chromophores. J. Phys. Chem. B. 148, 4813—4824. 2019.