Profile of Martin Karplus, Michael Levitt, and Arieh Warshel, 2013 nobel laureates in chemistry

Molecules in Environments: Toward Systematic Quantum Embedding of Electrons and Drude Oscillators

We develop a quantum embedding method that enables accurate and efficient treatment of interactions between molecules and an environment, while explicitly including many-body correlations. The molecule is composed of classical nuclei and quantum electrons, whereas the environment is modeled via charged quantum harmonic oscillators. We construct a general Hamiltonian and introduce a variational Ansatz for the correlated ground state of the fully interacting molecule-environment system. This wave function is optimized via the variational Monte Carlo method and the ground state energy is subsequently estimated through the diffusion Monte Carlo method. The proposed scheme allows an explicit many-body treatment of electrostatic, polarization, and dispersion interactions between the molecule and the environment. We study solvation energies and excitation energies of benzene derivatives, obtaining excellent agreement with explicit ab initio calculations and experiments.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Molecular dynamics simulation of mechanical properties of carbon nanotube reinforced cellulose

Cellulose, hemicellulose, and lignin are the major chemical components in wood paper. Various types of wet and dry strength additives are used to enhance the optical and mechanical properties of recycled paper. One of the possible materials is the carbon nanotube. In order to explore the probability of the use of carbon nanotubes as reinforcing materials and to understand how carbon nanotubes affect the mechanical properties of paper, a single-walled carbon nanotube is inserted into a [Formula: see text] cellulose nanocrystal, and its mechanical properties are studied by using energy minimization and molecular dynamics (MD) simulations. During simulations, the crystals are stretched in the axial direction at a constant speed, and stress and strain are computed and recorded at the atomic level. Our results indicate that carbon nanotube can significantly enhance the mechanical properties of paper.

Modeling Solution Behavior of Poly(N-isopropylacrylamide): A Comparison between Water Models

Water is known to play a fundamental role in determining the structure and functionality of macromolecules. The same crucial contribution is also found in the in silico description of polymer aqueous solutions. In this work, we exploit the widely investigated synthetic polymer poly(N-isopropylacrylamide) (PNIPAM) to understand the effect of the adopted water model on its solution behavior and to refine the computational setup. By means of atomistic molecular dynamics simulations, we perform a comparative study of PNIPAM aqueous solution using two advanced water models: TIP4P/2005 and TIP4P/Ice. The conformation and hydration features of an atactic 30-mer at infinite dilution are probed at a range of temperature and pressure suitable to detect the coil-to-globule transition and to map the P–T phase diagram. Although both water models can reproduce the temperature-induced coil-to-globule transition at atmospheric pressure and the polymer hydration enhancement that occurs with increasing pressure, the PNIPAM–TIP4P/Ice solution shows better agreement with experimental findings. This result can be attributed to a stronger interaction of TIP4P/Ice water with both hydrophilic and hydrophobic groups of PNIPAM, as well as to a less favorable contribution of the solvent entropy to the coil-to-globule transition.

Competing Protonation and Halide Elimination as a Probe of the Character of Thiamin-Derived Reactive Intermediates

Decarboxylation reactions from comparable thiamin diphosphate- and thiamin-derived adducts of p-(halomethyl)benzoylformic acids in enzymic and non-enzymic reactions, respectively, reveal critical distinctions in otherwise similar Breslow intermediates. The ratio of protonation to chloride elimination from the Breslow intermediate is 10²-fold greater in the enzymic process. This is consistent with a lower intrinsic barrier to proton transfer on the enzyme, implicating formation of a localized tetrahedral (sp³) carbanion that is formed as CO₂ is produced. In contrast, slower protonation in solution of the decarboxylated intermediate is consistent with formation of a delocalized planar carbanionic enol/enamine. The proposed structural and reactive character of the enzymic Breslow intermediate is consistent with Warshel's general theory of enzymic catalysis, structural characterization of related intermediates, and the lower kinetic barrier in reactions that occur without changes in hybridization.

Computational structural enzymology methodologies for the study and engineering of fatty acid synthases, polyketide synthases and nonribosomal peptide synthetases

Various computational methodologies can be applied to enzymological studies on enzymes in the fatty acid, polyketide, and non-ribosomal peptide biosynthetic pathways. These multi-domain complexes are called fatty acid synthases, polyketide synthases, and non-ribosomal peptide synthetases. These mega-synthases biosynthesize chemically diverse and complex bioactive molecules, with the intermediates being chauffeured between catalytic partners via a carrier protein. Recent efforts have been made to engineer these systems to expand their product diversity. A major stumbling block is our poor understanding of the transient protein-protein and protein-substrate interactions between the carrier protein and its many catalytic partner domains and product intermediates. The innate reactivity of pathway intermediates in two major classes of polyketide synthases has frustrated our mechanistic understanding of these interactions during the biosynthesis of these natural products, ultimately impeding the engineering of these systems for the generation of engineered natural products. Computational techniques described in this chapter can aid data interpretation or used to generate testable models of these experimentally intractable transient interactions, thereby providing insight into key interactions that are difficult to capture otherwise, with the potential to expand the diversity in these systems.

Charge Dispersion and Its Effects on the Reactivity of Thiamin-Derived Breslow Intermediates

The enzymic decarboxylation of 2-ketoacids proceeds via their C2-thiazolium adducts of thiamin diphosphate (ThDP). Loss of CO₂ from these adducts leads to reactive species that are known as Breslow intermediates. The protein-bound adducts of the 2-ketoacids and ThDP are several orders of magnitude more reactive than the synthetic analogues in solution. Studies of enzymes are consistent with formulation of protein-bound Breslow intermediates with localized carbanionic character at the reactive C2α position, reflecting the charge-stabilized transition state that leads to this form. Our study reveals that nonenzymic decarboxylation of the related thiamin adducts proceeds to the alternative charge-dispersed enol form of the Breslow intermediate. These differences suggest that the greatly enhanced rate of decarboxylation of the precursors to Breslow intermediates in enzymes arises from maintenance of the carbanionic character at the position from which the carboxyl group departs, avoiding charge dispersion by stabilizing electrostatic interactions with the protein as formulated by Warshel. Applying Guthrie's "no-barrier" addition to Marcus theory also leads to the conclusion that maintaining the tetrahedral carbanion at C2α of the resulting adduct minimizes associated kinetic barriers by avoiding rehybridization as part of steps to and from the intermediate. Finally, maintenance of the reactive energetic carbanion agrees with the concepts of Albery and Knowles as the outcome of evolved enzymic processes.

Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions

Recent and rapidly evolving progress on high-throughput measurement techniques and computational performance has led to the emergence of new disciplines, such as systems medicine and translational systems biology. At the core of these disciplines lies the desire to produce multiscale models: mathematical models that integrate multiple scales of biological organization, ranging from molecular, cellular and tissue models to organ, whole-organism and population scale models. Using such models, hypotheses can systematically be tested. In this review, we present state-of-the-art multiscale modelling of bacterial and fungal infections, considering both the pathogen and host as well as their interaction. Multiscale modelling of the interactions of bacteria, especially Mycobacterium tuberculosis, with the human host is quite advanced. In contrast, models for fungal infections are still in their infancy, in particular regarding infections with the most important human pathogenic fungi, Candida albicans and Aspergillus fumigatus. We reflect on the current availability of computational approaches for multiscale modelling of host-pathogen interactions and point out current challenges. Finally, we provide an outlook for future requirements of multiscale modelling.