The Determination of Free Energy of Hydration of Water Ions from First Principles

We model the autoionization of water by determining the free energy of hydration of the major intermediate species of water ions. We represent the smallest ions─the hydroxide ion OH-, the hydronium ion H3O+, and the Zundel ion H5O2+─by bonded models and the more extended ionic structures by strong nonbonded interactions (e.g., the Eigen H9O4+ = H3O+ + 3(H2O) and the Stoyanov H13O6+ = H5O2+ + 4(H2O)). Our models are faithful to the precise QM energies and their components to within 1% or less. Using the calculated free energies and atomization energies, we compute the pKa of pure water from first principles as a consistency check and arrive at a value within 1.3 log units of the experimental one. From these calculations, we conclude that the hydronium ion, and its hydrated state, the Eigen cation, are the dominant species in the water autoionization process.

Control of the antitumour activity and specificity of CAR T cells via organic adapters covalently tethering the CAR to tumour cells

On-target off-tumour toxicity limits the anticancer applicability of chimaeric antigen receptor (CAR) T cells. Here we show that the tumour-targeting specificity and activity of T cells with a CAR consisting of an antibody with a lysine residue that catalytically forms a reversible covalent bond with a 1,3-diketone hapten can be regulated by the concentration of a small-molecule adapter. This adapter selectively binds to the hapten and to a chosen tumour antigen via a small-molecule binder identified via a DNA-encoded library. The adapter therefore controls the formation of a covalent bond between the catalytic antibody and the hapten, as well as the tethering of the CAR T cells to the tumour cells, and hence the cytotoxicity and specificity of the cytotoxic T cells, as we show in vitro and in mice with prostate cancer xenografts. Such small-molecule switches of T-cell cytotoxicity and specificity via an antigen-independent 'universal' CAR may enhance the control and safety profile of CAR-based cellular immunotherapies.

Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties

We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.

Combining Force Fields and Neural Networks for an Accurate Representation of Bonded Interactions

We present a formalism of a neural network encoding bonded interactions in molecules. This intramolecular encoding is consistent with the models of intermolecular interactions previously designed by this group. Variants of the encoding fed into a corresponding neural network may be used to economically improve the representation of torsional degrees of freedom in any force field. We test the accuracy of the reproduction of the ab initio potential energy surface on a set of conformations of two dipeptides, methyl-capped ALA and ASP, in several scenarios. The encoding, either alone or in conjunction with an analytical potential, improves agreement with ab initio energies that are on par with those of other neural network-based potentials. Using the encoding and neural nets in tandem with an analytical model places the agreements firmly within "chemical accuracy" of ±0.5 kcal/mol.

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

Class I histone deacetylase complex: Structure and functional correlates

The Schizosaccharomyces pombe Clr6S complex, a class I histone deacetylase complex, functions as a zinc-dependent enzyme to remove acetyl groups from lysine residues in histone tails. We report here the cryo-EM structure of Clr6S alone and a cryo-EM map of Clr6S in complex with a nucleosome. The active center, revealed at near-atomic resolution, includes features important for catalysis-A water molecule coordinated by zinc, the likely nucleophile for attack on the acetyl-lysine bond, and a loop that may position the substrate for catalysis. The cryo-EM map in the presence of a nucleosome reveals multiple Clr6S-nucleosome contacts and a high degree of relative motion of Clr6S and the nucleosome. Such flexibility may be attributed to interaction at a site in the flexible histone tail and is likely important for the function of the deacetylase, which acts at multiple sites in other histone tails.

Role of the histone tails in histone octamer transfer

The exceptionally high positive charge of the histones, concentrated in the N- and C-terminal tails, is believed to contribute to the stability of the nucleosome by neutralizing the negative charge of the nucleosomal DNA. We find, on the contrary, that the high positive charge contributes to instability, performing an essential function in chromatin remodeling. We show that the tails are required for removal of the histone octamer by the RSC chromatin remodeling complex, and this function is not due to direct RSC-tail interaction. We also show that the tails are required for histone octamer transfer from nucleosomes to DNA, and this activity of the tails is a consequence of their positive charge. Thus, the histone tails, intrinsically disordered protein regions, perform a critical role in chromatin structure and transcription, unrelated to their well-known role in regulation through posttranscriptional modification.

Protein-Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field

Protein-ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)─a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein-ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ∼0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

Harnessing coronavirus spike proteins' binding affinity to ACE2 receptor through a novel baculovirus surface display system

Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly emerging infectious disease currently spreading across the world. The spike (S) protein plays a key role in the receptor recognition and cell membrane fusion, making it an important target for developing vaccines, therapeutic antibodies and diagnosis. In this study, we constructed a baculovirus surface display system that efficiently presents both SARS-CoV and SARS-CoV-2 S proteins (including ectodomain, S1 subunit and receptor-binding-domain, RBD) on the surface of recombinant baculoviruses, utilizing transmembrane anchors from gp64 (signal peptide) and vesicular stomatitis virus (VSV). These recombinant baculoviruses were capable of transducing engineered HEK 293T cells overexpressing ACE2 receptors with significantly higher transduction efficiencies, indicating that S proteins displayed on baculovirus surface have antigenicity and can recognize and bind ACE2 receptors. Additionally, the transduction of SARS-CoV-2 S proteins can be inhibited by an antibody against the SARS-CoV-2 RBD. These results demonstrate that this baculovirus surface display system is a promising tool for developing antibodies, vaccines and recombinant protein production.

Accurate determination of solvation free energies of neutral organic compounds from first principles

The main goal of molecular simulation is to accurately predict experimental observables of molecular systems. Another long-standing goal is to devise models for arbitrary neutral organic molecules with little or no reliance on experimental data. While separately these goals have been met to various degrees, for an arbitrary system of molecules they have not been achieved simultaneously. For biophysical ensembles that exist at room temperature and pressure, and where the entropic contributions are on par with interaction strengths, it is the free energies that are both most important and most difficult to predict. We compute the free energies of solvation for a diverse set of neutral organic compounds using a polarizable force field fitted entirely to ab initio calculations. The mean absolute errors (MAE) of hydration, cyclohexane solvation, and corresponding partition coefficients are 0.2 kcal/mol, 0.3 kcal/mol and 0.22 log units, i.e. within chemical accuracy. The model (ARROW FF) is multipolar, polarizable, and its accompanying simulation stack includes nuclear quantum effects (NQE). The simulation tools' computational efficiency is on a par with current state-of-the-art packages. The construction of a wide-coverage molecular modelling toolset from first principles, together with its excellent predictive ability in the liquid phase is a major advance in biomolecular simulation.

Structure of mitotic chromosomes

Chromatin fibers must fold or coil in the process of chromosome condensation. Patterns of coiling have been demonstrated for reconstituted chromatin, but the actual trajectories of fibers in condensed states of chromosomes could not be visualized because of the high density of the material. We have exploited partial decondensation of mitotic chromosomes to reveal their internal structure at sub-nucleosomal resolution by cryo-electron tomography, without the use of stains, fixatives, milling, or sectioning. DNA gyres around nucleosomes were visible, allowing the nucleosomes to be identified and their orientations to be determined. Linker DNA regions were traced, revealing the trajectories of the chromatin fibers. The trajectories were irregular, with almost no evidence of coiling and no short- or long-range order of the chromosomal material. The 146-bp core particle, long known as a product of nuclease digestion, is identified as the native state of the nucleosome, with no regular spacing along the chromatin fibers.

Gold nanoparticles and tilt pairs to assess protein flexibility by cryo-electron microscopy

A computational method was developed to recover the three-dimensional coordinates of gold nanoparticles specifically attached to a protein complex from tilt-pair images collected by electron microscopy. The program was tested on a simulated dataset and applied to a real dataset comprising tilt-pair images recorded by cryo electron microscopy of RNA polymerase II in a complex with four gold-labeled single-chain antibody fragments. The positions of the gold nanoparticles were determined, and comparison of the coordinates among the tetrameric particles revealed the range of motion within the protein complexes.

3D genomics across the tree of life reveals condensin II as a determinant of architecture type

We investigated genome folding across the eukaryotic tree of life. We find two types of three-dimensional (3D) genome architectures at the chromosome scale. Each type appears and disappears repeatedly during eukaryotic evolution. The type of genome architecture that an organism exhibits correlates with the absence of condensin II subunits. Moreover, condensin II depletion converts the architecture of the human genome to a state resembling that seen in organisms such as fungi or mosquitoes. In this state, centromeres cluster together at nucleoli, and heterochromatin domains merge. We propose a physical model in which lengthwise compaction of chromosomes by condensin II during mitosis determines chromosome-scale genome architecture, with effects that are retained during the subsequent interphase. This mechanism likely has been conserved since the last common ancestor of all eukaryotes.

Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator

Gene activator proteins comprise distinct DNA-binding and transcriptional activation domains (ADs). Because few ADs have been described, we tested domains tiling all yeast transcription factors for activation in vivo and identified 150 ADs. By mRNA display, we showed that 73% of ADs bound the Med15 subunit of Mediator, and that binding strength was correlated with activation. AD-Mediator interaction in vitro was unaffected by a large excess of free activator protein, pointing to a dynamic mechanism of interaction. Structural modeling showed that ADs interact with Med15 without shape complementarity (‘fuzzy’ binding). ADs shared no sequence motifs, but mutagenesis revealed biochemical and structural constraints. Finally, a neural network trained on AD sequences accurately predicted ADs in human proteins and in other yeast proteins, including chromosomal proteins and chromatin remodeling complexes. These findings solve the longstanding enigma of AD structure and function and provide a rationale for their role in biology.

Cells adapt and respond to changes by regulating the activity of their genes. To turn genes on or off, they use a family of proteins called transcription factors. Transcription factors influence specific but overlapping groups of genes, so that each gene is controlled by several transcription factors that act together like a dimmer switch to regulate gene activity.

The presence of transcription factors attracts proteins such as the Mediator complex, which activates genes by gathering the protein machines that read the genes. The more transcription factors are found near a specific gene, the more strongly they attract Mediator and the more active the gene is. A specific region on the transcription factor called the activation domain is necessary for this process. The biochemical sequences of these domains vary greatly between species, yet activation domains from, for example, yeast and human proteins are often interchangeable.

To understand why this is the case, Sanborn et al. analyzed the genome of baker’s yeast and identified 150 activation domains, each very different in sequence. Three-quarters of them bound to a subunit of the Mediator complex called Med15. Sanborn et al. then developed a machine learning algorithm to predict activation domains in both yeast and humans. This algorithm also showed that negatively charged and greasy regions on the activation domains were essential to be activated by the Mediator complex.

Further analyses revealed that activation domains used different poses to bind multiple sites on Med15, a behavior known as ‘fuzzy’ binding. This creates a high overall affinity even though the binding strength at each individual site is low, enabling the protein complexes to remain dynamic. These weak interactions together permit fine control over the activity of several genes, allowing cells to respond quickly and precisely to many changes.

The computer algorithm used here provides a new way to identify activation domains across species and could improve our understanding of how living things grow, adapt and evolve. It could also give new insights into mechanisms of disease, particularly cancer, where transcription factors are often faulty.

Mediator structure and conformation change

Mediator is a universal adaptor for transcription control. It serves as an interface between gene-specific activator or repressor proteins and the general RNA polymerase II (pol II) transcription machinery. Previous structural studies revealed a relatively small part of Mediator and none of the gene activator-binding regions. We have determined the cryo-EM structure of the Mediator at near-atomic resolution. The structure reveals almost all amino acid residues in ordered regions, including the major targets of activator proteins, the Tail module, and the Med1 subunit of the Middle module. Comparison of Mediator structures with and without pol II reveals conformational changes that propagate across the entire Mediator, from Head to Tail, coupling activator- and pol II-interacting regions.

A Novel AKR1C3 Specific Prodrug TH3424 With Potent Antitumor Activity in Liver Cancer

Overexpression of AKR1C3, an aldo-keto reductase, was recently discovered in liver cancers. In this study, an inverse correlation between AKR1C3 expression and survival of patients with liver cancer was observed. AKR1C3 inhibitors, however, failed to suppress liver cancer cell growth. The prodrug TH3424, which releases a DNA alkylating reagent upon reduction by AKR1C3, was developed to target tumors with overexpression of AKR1C3. TH3424 showed specific killing of liver cancer cells with AKR1C3 overexpression both in vitro and in vivo. In patient-derived mouse xenograft models, TH3424 at doses as low as 1.5 mg/kg eliminated liver tumors with no apparent toxicity. Therefore, TH3424 is a promising drug candidate for liver cancer and other types of cancers overexpressing AKR1C3.

Primary Role of the Nucleosome

Whereas the core nucleosome is thought to serve as a packaging device for the coiling and contraction in length of genomic DNA, we suggest that it serves primarily in the regulation of transcription. A nucleosome on a promoter prevents the initiation of transcription. The association of nucleosomes with most genomic DNA prevents initiation from cryptic promoters. The nucleosome thus serves not only as a general gene repressor, but also as a repressor of all transcription (genic, intragenic, and intergenic). The core nucleosome performs a fundamental regulatory role, apart from the histone "tails," which modulate gene activity.

FGF21 trafficking in intact human cells revealed by cryo-electron tomography with gold nanoparticles

The fibroblast growth factor FGF21 was labeled with molecularly defined gold nanoparticles (AuNPs), applied to human adipocytes, and imaged by cryo-electron tomography (cryo-ET). Most AuNPs were in pairs about 80 Å apart, on the outer cell surface. Pairs of AuNPs were also abundant inside the cells in clathrin-coated vesicles and endosomes. AuNPs were present but no longer paired in multivesicular bodies. FGF21 could thus be tracked along the endocytotic pathway. The methods developed here to visualize signaling coupled to endocytosis can be applied to a wide variety of cargo and may be extended to studies of other intracellular transactions.

Histone Acetylation Inhibits RSC and Stabilizes the +1 Nucleosome

The +1 nucleosome of yeast genes, within which reside transcription start sites, is characterized by histone acetylation, by the displacement of an H2A-H2B dimer, and by a persistent association with the RSC chromatin-remodeling complex. Here we demonstrate the interrelationship of these characteristics and the conversion of a nucleosome to the +1 state in vitro. Contrary to expectation, acetylation performs an inhibitory role, preventing the removal of a nucleosome by RSC. Inhibition is due to both enhanced RSC-histone interaction and diminished histone-chaperone interaction. Acetylation does not prevent all RSC activity, because stably bound RSC removes an H2A-H2B dimer on a timescale of seconds in an irreversible manner.

On the importance of accounting for nuclear quantum effects in ab initio calibrated force fields in biological simulations

In many important processes in chemistry, physics, and biology the nuclear degrees of freedom cannot be described using the laws of classical mechanics. At the same time, the vast majority of molecular simulations that employ wide-coverage force fields treat atomic motion classically. In light of the increasing desire for and accelerated development of quantum mechanics (QM)-parameterized interaction models, we reexamine whether the classical treatment is sufficient for a simple but crucial chemical species: alkanes. We show that when using an interaction model or force field in excellent agreement with the "gold standard" QM data, even very basic simulated properties of liquid alkanes, such as densities and heats of vaporization, deviate significantly from experimental values. Inclusion of nuclear quantum effects via techniques that treat nuclear degrees of freedom using the laws of classical mechanics brings the simulated properties much closer to reality.

Structure Determination of a Water-Soluble 144-Gold Atom Particle at Atomic Resolution by Aberration-Corrected Electron Microscopy

Structure determination by transmission electron microscopy has revealed the long sought 144-gold atom particle. The structure exhibits deviations from face-centered cubic packing of the gold atoms, similar to the solution structure of another gold nanoparticle, and in contrast to a previous X-ray crystal structure. Evidence from analytical methods points to a low number of 3-mercaptobenzoic acid ligands covering the surface of the particle.