Toward Computing Accurate Free Energies in Heterogeneous Catalysis: a Case Study for Adsorbed Isobutene in H-ZSM-5

Herein, we propose a novel computational protocol that enables calculating free energies with improved accuracy by combining the best available techniques for enthalpy and entropy calculation. While the entropy is described by enhanced sampling molecular dynamics techniques, the energy is calculated using ab initio methods. We apply the method to assess the stability of isobutene adsorption intermediates in the zeolite H-SSZ-13, a prototypical problem that is computationally extremely challenging in terms of calculating enthalpy and entropy. We find that at typical operating conditions for zeolite catalysis (400 °C), the physisorbed π-complex, and not the tertiary carbenium ion as often reported, is the most stable intermediate. This method paves the way for sampling-based techniques to calculate the accurate free energies in a broad range of chemistry-related disciplines, thus presenting a big step forward toward predictive modeling

Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations

Quantum mechanics/molecular mechanics (QM/MM) hybrid technique is emerging as a reliable computational method to investigate and characterize chemical reactions occurring in enzymes. From a drug discovery perspective, a thorough understanding of enzyme catalysis appears pivotal to assist the design of inhibitors able to covalently bind one of the residues belonging to the enzyme catalytic machinery. Thanks to the current advances in computer power, and the availability of more efficient algorithms for QM-based simulations, the use of QM/MM methodology is becoming a viable option in the field of covalent inhibitor design. In the present review, we summarized our experience in the field of QM/MM simulations applied to drug design problems which involved the optimization of agents working on two well-known drug targets, namely fatty acid amide hydrolase (FAAH) and epidermal growth factor receptor (EGFR). In this context, QM/MM simulations gave valuable information in terms of geometry (i.e., of transition states and metastable intermediates) and reaction energetics that allowed to correctly predict inhibitor binding orientation and substituent effect on enzyme inhibition. What is more, enzyme reaction modelling with QM/MM provided insights that were translated into the synthesis of new covalent inhibitor featured by a unique combination of intrinsic reactivity, on-target activity, and selectivity

Coarse-grained modeling for molecular discovery:Applications to cardiolipin-selectivity

The development of novel materials is pivotal for addressing global challenges such as achieving sustainability, technological progress, and advancements in medical technology. Traditionally, developing or designing new molecules was a resource-intensive endeavor, often reliant on serendipity. Given the vast space of chemically feasible drug-like molecules, estimated between 106 - 10100 compounds, traditional in vitro techniques fall short.Consequently, in silico tools such as virtual screening and molecular modeling have gained increasing recognition. However, the computational cost and the limited precision of the utilized molecular models still limit computational molecular design.This thesis aimed to enhance the molecular design process by integrating multiscale modeling and free energy calculations. Employing a coarse-grained model allowed us to efficiently traverse a significant portion of chemical space and reduce the sampling time required by molecular dynamics simulations. The physics-informed nature of the applied Martini force field and its level of retained structural detail make the model a suitable starting point for the focused learning of molecular properties.We applied our proposed approach to a cardiolipin bilayer, posing a relevant and challenging problem and facilitating reasonable comparison to experimental measurements.We identified promising molecules with defined properties within the resolution limit of a coarse-grained representation. Furthermore, we were able to bridge the gap from in silico predictions to in vitro and in vivo experiments, supporting the validity of the theoretical concept. The findings underscore the potential of multiscale modeling and free-energy calculations in enhancing molecular discovery and design and offer a promising direction for future research

Coarse-grained modeling for molecular discovery:Applications to cardiolipin-selectivity

The development of novel materials is pivotal for addressing global challenges such as achieving sustainability, technological progress, and advancements in medical technology. Traditionally, developing or designing new molecules was a resource-intensive endeavor, often reliant on serendipity. Given the vast space of chemically feasible drug-like molecules, estimated between 106 - 10100 compounds, traditional in vitro techniques fall short.Consequently, in silico tools such as virtual screening and molecular modeling have gained increasing recognition. However, the computational cost and the limited precision of the utilized molecular models still limit computational molecular design.This thesis aimed to enhance the molecular design process by integrating multiscale modeling and free energy calculations. Employing a coarse-grained model allowed us to efficiently traverse a significant portion of chemical space and reduce the sampling time required by molecular dynamics simulations. The physics-informed nature of the applied Martini force field and its level of retained structural detail make the model a suitable starting point for the focused learning of molecular properties.We applied our proposed approach to a cardiolipin bilayer, posing a relevant and challenging problem and facilitating reasonable comparison to experimental measurements.We identified promising molecules with defined properties within the resolution limit of a coarse-grained representation. Furthermore, we were able to bridge the gap from in silico predictions to in vitro and in vivo experiments, supporting the validity of the theoretical concept. The findings underscore the potential of multiscale modeling and free-energy calculations in enhancing molecular discovery and design and offer a promising direction for future research

Polarisable force fields:what do they add in biomolecular simulations?

The quality of biomolecular simulations critically depends on the accuracy of the force field used to calculate the potential energy of the molecular configurations. Currently, most simulations employ non-polarisable force fields, which describe electrostatic interactions as the sum of Coulombic interactions between fixed atomic charges. Polarization of these charge distributions is incorporated only in a mean-field manner. In the past decade, extensive efforts have been devoted to developing simple, efficient, and yet generally applicable polarisable force fields for biomolecular simulations. In this review, we summarise the latest developments in accounting for key biomolecular interactions with polarisable force fields and applications to address challenging biological questions. In the end, we provide an outlook for future development in polarisable force fields.Comment: 25 pages, 3 figure

Polarisable force fields: what do they add in biomolecular simulations?

The quality of biomolecular simulations critically depends on the accuracy of the force field used to calculate the potential energy of the molecular configurations. Currently, most simulations employ non-polarisable force fields, which describe electrostatic interactions as the sum of Coulombic interactions between fixed atomic charges. Polarisation of these charge distributions is incorporated only in a mean-field manner. In the past decade, extensive efforts have been devoted to developing simple, efficient, and yet generally applicable polarisable force fields for biomolecular simulations. In this review, we summarise the latest developments in accounting for key biomolecular interactions with polarisable force fields and applications to address challenging biological questions. In the end, we provide an outlook for future development in polarisable force fields

Glycan receptor specificity as a useful tool for characterization and surveillance of influenza A virus

Influenza A viruses are rapidly evolving pathogens with the potential for novel strains to emerge and result in pandemic outbreaks in humans. Some avian-adapted subtypes have acquired the ability to bind to human glycan receptors and cause severe infections in humans but have yet to adapt to and transmit between humans. The emergence of new avian strains and their ability to infect humans has confounded their distinction from circulating human virus strains through linking receptor specificity to human adaptation. Herein we review the various structural and biochemical analyses of influenza hemagglutinin–glycan receptor interactions. We provide our perspectives on how receptor specificity can be used to monitor evolution of the virus to adapt to human hosts so as to facilitate improved surveillance and pandemic preparedness.National Institutes of Health (U.S.) (Merit Award R37 GM057073-13)Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology)Skolkovo Institute of Science and Technolog