NDP52 acts as a redox sensor in PINK1/Parkin-mediated mitophagy.

Mitophagy, the elimination of mitochondria via the autophagy-lysosome pathway, is essential for the maintenance of cellular homeostasis. The best characterised mitophagy pathway is mediated by stabilisation of the protein kinase PINK1 and recruitment of the ubiquitin ligase Parkin to damaged mitochondria. Ubiquitinated mitochondrial surface proteins are recognised by autophagy receptors including NDP52 which initiate the formation of an autophagic vesicle around the mitochondria. Damaged mitochondria also generate reactive oxygen species (ROS) which have been proposed to act as a signal for mitophagy, however the mechanism of ROS sensing is unknown. Here we found that oxidation of NDP52 is essential for the efficient PINK1/Parkin-dependent mitophagy. We identified redox-sensitive cysteine residues involved in disulphide bond formation and oligomerisation of NDP52 on damaged mitochondria. Oligomerisation of NDP52 facilitates the recruitment of autophagy machinery for rapid mitochondrial degradation. We propose that redox sensing by NDP52 allows mitophagy to function as a mechanism of oxidative stress response.

A de novo designed coiled coil-based switch regulates the microtubule motor kinesin-1.

Many enzymes are allosterically regulated via conformational change; however, our ability to manipulate these structural changes and control function is limited. Here we install a conformational switch for allosteric activation into the kinesin-1 microtubule motor in vitro and in cells. Kinesin-1 is a heterotetramer that accesses open active and closed autoinhibited states. The equilibrium between these states centers on a flexible elbow within a complex coiled-coil architecture. We target the elbow to engineer a closed state that can be opened with a de novo designed peptide. The alternative states are modeled computationally and confirmed by biophysical measurements and electron microscopy. In cells, peptide-driven activation increases kinesin transport, demonstrating a primary role for conformational switching in regulating motor activity. The designs are enabled by our understanding of ubiquitous coiled-coil structures, opening possibilities for controlling other protein activities.

Rationally seeded computational protein design of ɑ-helical barrels.

Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.

De novo designed peptides for cellular delivery and subcellular localisation.

Increasingly, it is possible to design peptide and protein assemblies de novo from first principles or computationally. This approach provides new routes to functional synthetic polypeptides, including designs to target and bind proteins of interest. Much of this work has been developed in vitro. Therefore, a challenge is to deliver de novo polypeptides efficiently to sites of action within cells. Here we describe the design, characterisation, intracellular delivery, and subcellular localisation of a de novo synthetic peptide system. This system comprises a dual-function basic peptide, programmed both for cell penetration and target binding, and a complementary acidic peptide that can be fused to proteins of interest and introduced into cells using synthetic DNA. The designs are characterised in vitro using biophysical methods and X-ray crystallography. The utility of the system for delivery into mammalian cells and subcellular targeting is demonstrated by marking organelles and actively engaging functional protein complexes.

Sorting drug conformers in enzyme active sites: the XTB way.

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Positivity preserving density matrix minimization at finite temperatures via square root.

We present a Wave Operator Minimization (WOM) method for calculating the Fermi-Dirac density matrix for electronic structure problems at finite temperature while preserving physicality by construction using the wave operator, i.e., the square root of the density matrix. WOM models cooling a state initially at infinite temperature down to the desired finite temperature. We consider both the grand canonical (constant chemical potential) and canonical (constant number of electrons) ensembles. Additionally, we show that the number of steps required for convergence is independent of the number of atoms in the system. We hope that the discussion and results presented in this article reinvigorate interest in density matrix minimization methods.

Protein-ligand interactions from a quantum fragmentation perspective: The case of the SARS-CoV-2 main protease interacting with α-ketoamide inhibitors.

We present a hybrid, multi-method, computational scheme for protein/ligand systems well suited to be used on modern and forthcoming massively parallel computing systems. The scheme relies on a multi-scale polarizable molecular modeling, approach to perform molecular dynamics simulations, and on an efficient Density Functional Theory (DFT) linear scaling method to post-process simulation snapshots. We use this scheme to investigate recent α-ketoamide inhibitors targeting the main protease of the SARS-CoV-2 virus. We assessed the reliability and the coherence of the hybrid scheme, in particular, by checking the ability of MM and DFT to reproduce results from high-end ab initio computations regarding such inhibitors. The DFT approach enables an a posteriori fragmentation of the system and an investigation into the strength of interaction among identified fragment pairs. We show the necessity of accounting for a large set of plausible protease/inhibitor conformations to generate reliable interaction data. Finally, we point out ways to further improve α-ketoamide inhibitors to more strongly interact with particular protease domains neighboring the active site.

Complexity reduction in density functional theory: Locality in space and energy.

We present recent developments of the NTChem program for performing large scale hybrid density functional theory calculations on the supercomputer Fugaku. We combine these developments with our recently proposed complexity reduction framework to assess the impact of basis set and functional choice on its measures of fragment quality and interaction. We further exploit the all electron representation to study system fragmentation in various energy envelopes. Building off this analysis, we propose two algorithms for computing the orbital energies of the Kohn-Sham Hamiltonian. We demonstrate that these algorithms can efficiently be applied to systems composed of thousands of atoms and as an analysis tool that reveals the origin of spectral properties.

Probing disorder in 2CzPN using core and valence states.

Molecules which exhibit thermally activated delayed fluorescence (TADF) show great promise for use in efficient, environmentally-friendly OLEDs, and thus the design of new TADF emitters is an active area of research. However, when used in devices, they are typically in the form of disordered thin films, where both the external molecular environment and thermally-induced internal variations in parameters such as the torsion angle can strongly influence their electronic structure. In this work, we use density functional theory and X-ray photoelectron spectroscopy to investigate the impact of disorder on both core and valence states in the TADF emitter 2CzPN (1,2-bis(carbazol-9-yl)-4,5-dicyanobenzene). By simulating gas phase molecules displaying varying levels of disorder, we assess the relative sensitivity of the different states to factors such as varying torsion angle. The theoretical results for both core and valence states show good agreement with experiment, thereby also highlighting the advantages of our approach for interpreting experimental spectra of large aromatic molecules, which are too complex to interpret based solely on experimental data.

Modeling the Conformational Preference of the Lignocellulose Interface and Its Interaction with Weak Acids.

We have examined the conformational space of model systems for the hydrogen-bonded and covalent linkages between the sugar and lignin components of lignocellulose. Specifically, glucose and paracoumaryl alcohol moieties are used in our models. Multistage screening protocols are used to identify and validate a set of lowest-energy isomers. We found a cost-effective screening process involving an initial screening with DFTB3/3ob using a 20 kJ mol-1 threshold, a refinement with the SCANh/6-31+G(2d,p) method with a 10 kJ mol-1 cutoff, a third step at the DSD-PBEP86/ma-def2-TZVP//MS1-D3/6-31+G(2d,p) level with the same 10 kJ mol-1 threshold, and a last step at the CCSD(T)/CBS//B3LYP/cc-pVTZ level with a tighter 5 kJ mol-1 threshold. The use of machine learning (with the London and Axilrod-Teller-Muto potential) can further accelerate the screening process. In general, all low-energy conformers are characterized by hydrogen bonding between the sugar and lignin moieties. We examined the interactions of covalently bonded sugar-lignin models with weak acids (HSO3-, H2PO3-, HSeO3-, H2citrate-, etc.) and found that they interacted strongly with the oxygen of the sugar-O-lignin linkage. Our results suggest that acids such as dihydrogen citrate may be attractive alternatives to the commonly used HSO3- for lignocellulose processing.

Searching for a Reliable Density Functional for Molecule-Environment Interactions, Found B97M-V/def2-mTZVP.

In the present study, we have examined density functional theory methods for the calculation of the interaction energy between a small molecule and its environment. For simple systems such as a neutral solute in a neutral solvent, good accuracy can be attained using low-cost "3c" methods, in particular r2SCAN-3c. When part(s) of the system is charged, the accurate computation of the interactions is more challenging. In these cases, we find the B97M-V/def2-mTZVP method to agree well with reference values; it also shows good accuracy for the more straightforward neutral systems. Thus, B97M-V/def2-mTZVP provides a means for accurate and low-cost computation of interaction energies, notably the binding between a substrate or a drug molecule and an enzyme, which may facilitate rational drug design.

How Coiled-Coil Assemblies Accommodate Multiple Aromatic Residues.

Rational protein design requires understanding the contribution of each amino acid to a targeted protein fold. For a subset of protein structures, namely, α-helical coiled coils (CCs), knowledge is sufficiently advanced to allow the rational de novo design of many structures, including entirely new protein folds. Current CC design rules center on using aliphatic hydrophobic residues predominantly to drive the folding and assembly of amphipathic α helices. The consequences of using aromatic residues-which would be useful for introducing structural probes, and binding and catalytic functionalities-into these interfaces are not understood. There are specific examples of designed CCs containing such aromatic residues, e.g., phenylalanine-rich sequences, and the use of polar aromatic residues to make buried hydrogen-bond networks. However, it is not known generally if sequences rich in tyrosine can form CCs, or what CC assemblies these would lead to. Here, we explore tyrosine-rich sequences in a general CC-forming background and resolve new CC structures. In one of these, an antiparallel tetramer, the tyrosine residues are solvent accessible and pack at the interface between the core and the surface. In another more complex structure, the residues are buried and form an extended hydrogen-bond network.

Taking Advantage of a Systematic Energy Non-linearity Error in Density Functional Theory for the Calculation of Electronic Energy Levels.

We present an approximate approach for the calculation of ionization potential (IP) and electron affinity (EA) by exploiting the complementary energy non-linearity errors for a species M and its one-electron-ionized counterpart (M+). Reasonable IPs and EAs are thus obtained by averaging the orbital energies of M and M+, even with a low-level method such as BLYP/6-31G(d). By combining the corrected IPs and EAs, we can further obtain reasonable excitation energies. The errors in uncorrected valence IPs and uncorrected virtual-orbital energies show systematic trends. These characteristics provide a convenient and computationally efficient avenue for qualitative estimation of these properties with single corrections for multiple IPs and excitation energies.

Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations.

The BigDFT project was started in 2005 with the aim of testing the advantages of using a Daubechies wavelet basis set for Kohn-Sham (KS) density functional theory (DFT) with pseudopotentials. This project led to the creation of the BigDFT code, which employs a computational approach with optimal features of flexibility, performance, and precision of the results. In particular, the employed formalism has enabled the implementation of an algorithm able to tackle DFT calculations of large systems, up to many thousands of atoms, with a computational effort that scales linearly with the number of atoms. In this work, we recall some of the features that have been made possible by the peculiar properties of Daubechies wavelets. In particular, we focus our attention on the usage of DFT for large-scale systems. We show how the localized description of the KS problem, emerging from the features of the basis set, is helpful in providing a simplified description of large-scale electronic structure calculations. We provide some examples on how such a simplified description can be employed, and we consider, among the case-studies, the SARS-CoV-2 main protease.

Equilibration and analysis of first-principles molecular dynamics simulations of water.

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. We assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. A comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

Asymptomatic spread of huanglongbing and implications for disease control.

Huanglongbing (HLB) is a bacterial infection of citrus trees transmitted by the Asian citrus psyllid Diaphorina citri. Mitigation of HLB has focused on spraying of insecticides to reduce the psyllid population and removal of trees when they first show symptoms of the disease. These interventions have been only marginally effective, because symptoms of HLB do not appear on leaves for months to years after initial infection. Limited knowledge about disease spread during the asymptomatic phase is exemplified by the heretofore unknown length of time from initial infection of newly developing cluster of young leaves, called flush, by adult psyllids until the flush become infectious. We present experimental evidence showing that young flush become infectious within 15 d after receiving an inoculum of Candidatus Liberibacter asiaticus (bacteria). Using this critical fact, we specify a microsimulation model of asymptomatic disease spread and intensity in a grove of citrus trees. We apply a range of psyllid introduction scenarios to show that entire groves can become infected with up to 12,000 psyllids per tree in less than 1 y, before most of the trees show any symptoms. We also show that intervention strategies that reduce the psyllid population by 75% during the flushing periods can delay infection of a full grove, and thereby reduce the amount of insecticide used throughout a year. This result implies that psyllid surveillance and control, using a variety of recently available technologies, should be used from the initial detection of invasion and throughout the asymptomatic period.

Chemoenzymatic Assembly of Isotopically Labeled Folates.

Pterin-containing natural products have diverse functions in life, but an efficient and easy scheme for their in vitro synthesis is not available. Here we report a chemoenzymatic 14-step, one-pot synthesis that can be used to generate 13C- and 15N-labeled dihydrofolates (H2F) from glucose, guanine, and p-aminobenzoyl-l-glutamic acid. This synthesis stands out from previous approaches to produce H2F in that the average yield of each step is >91% and it requires only a single purification step. The use of a one-pot reaction allowed us to overcome potential problems with individual steps during the synthesis. The availability of labeled dihydrofolates allowed the measurement of heavy-atom isotope effects for the reaction catalyzed by the drug target dihydrofolate reductase and established that protonation at N5 of H2F and hydride transfer to C6 occur in a stepwise mechanism. This chemoenzymatic pterin synthesis can be applied to the efficient production of other folates and a range of other natural compounds with applications in nutritional, medical, and cell-biological research.

Unraveling the role of protein dynamics in dihydrofolate reductase catalysis.

Protein dynamics have controversially been proposed to be at the heart of enzyme catalysis, but identification and analysis of dynamical effects in enzyme-catalyzed reactions have proved very challenging. Here, we tackle this question by comparing an enzyme with its heavy ((15)N, (13)C, (2)H substituted) counterpart, providing a subtle probe of dynamics. The crucial hydride transfer step of the reaction (the chemical step) occurs more slowly in the heavy enzyme. A combination of experimental results, quantum mechanics/molecular mechanics simulations, and theoretical analyses identify the origins of the observed differences in reactivity. The generally slightly slower reaction in the heavy enzyme reflects differences in environmental coupling to the hydride transfer step. Importantly, the barrier and contribution of quantum tunneling are not affected, indicating no significant role for "promoting motions" in driving tunneling or modulating the barrier. The chemical step is slower in the heavy enzyme because protein motions coupled to the reaction coordinate are slower. The fact that the heavy enzyme is only slightly less active than its light counterpart shows that protein dynamics have a small, but measurable, effect on the chemical reaction rate.

A personal history of virus-based vector construction.

The ability to express foreign genes or to silence endogenous genes in plants has revolutionized both basic and applied plant biology. Virus-based expression systems, in which the foreign mRNA is greatly amplified by virus replication, can produce very high levels of proteins or peptides in leaves and other tissues. Vectors have been available for about 25 years. They are commonplace as laboratory tools, but their initial commercial expectations have not been met for numerous reasons. Yet, applications of viral vectors are still evolving. This chapter focuses on our laboratory's involvement in developing virus-based vectors in plants. We created the first 'add-a-gene' vectors that were capable of replication and movement throughout plants. These vectors were based on tobacco mosaic virus. Through the evolution of several prototypes, stable vectors were developed that produced relatively large amounts of product in plants. Recently, we created similar vectors for citrus trees based on citrus tristeza virus. Even though the citrus vectors were created as laboratory tools for improving the crop, circumstances have changed the applications to protection and therapy of trees in the field.

Protein isotope effects in dihydrofolate reductase from Geobacillus stearothermophilus show entropic-enthalpic compensatory effects on the rate constant.

Catalysis by dihydrofolate reductase from the moderately thermophilic bacterium Geobacillus stearothermophilus (BsDHFR) was investigated by isotope substitution of the enzyme. The enzyme kinetic isotope effect for hydride transfer was close to unity at physiological temperatures but increased with decreasing temperatures to a value of 1.65 at 5 °C. This behavior is opposite to that observed for DHFR from Escherichia coli (EcDHFR), where the enzyme kinetic isotope effect increased slightly with increasing temperature. These experimental results were reproduced in the framework of variational transition-state theory that includes a dynamical recrossing coefficient that varies with the mass of the protein. Our simulations indicate that BsDHFR has greater flexibility than EcDHFR on the ps-ns time scale, which affects the coupling of the environmental motions of the protein to the chemical coordinate and consequently to the recrossing trajectories on the reaction barrier. The intensity of the dynamic coupling in DHFRs is influenced by compensatory temperature-dependent factors, namely the enthalpic barrier needed to achieve an ideal transition-state configuration with minimal nonproductive trajectories and the protein disorder that disrupts the electrostatic preorganization required to stabilize the transition state. Together with our previous studies of other DHFRs, the results presented here provide a general explanation why protein dynamic effects vary between enzymes. Our theoretical treatment demonstrates that these effects can be satisfactorily reproduced by including a transmission coefficient in the rate constant calculation, whose dependence on temperature is affected by the protein flexibility.