SILVR: Guided Diffusion for Molecule Generation

Computationally generating novel synthetically accessible compounds with high affinity and low toxicity is a great challenge in drug design. Machine-learning models beyond conventional pharmacophoric methods have shown promise in generating novel small molecule compounds, but require significant tuning for a specific protein target. Here, we introduce a method called selective iterative latent variable refinement (SILVR) for conditioning an existing diffusion-based equivariant generative model without retraining. The model allows the generation of new molecules that fit into a binding site of a protein based on fragment hits. We use the SARS-CoV-2 Main protease fragments from Diamond X-Chem that form part of the COVID Moonshot project as a reference dataset for conditioning the molecule generation. The SILVR rate controls the extent of conditioning and we show that moderate SILVR rates make it possible to generate new molecules of similar shape to the original fragments, meaning that the new molecules fit the binding site without knowledge of the protein. We can also merge up to 3 fragments into a new molecule without affecting the quality of molecules generated by the underlying generative model. Our method is generalizable to any protein target with known fragments and any diffusion-based model for molecule generation.Comment: paper, 20 paper, 11 figure

Estimating Equilibrium Expectations from Time-Correlated Simulation Data at Multiple Thermodynamic States

Computing the equilibrium properties of complex systems, such as free energy differences, is often hampered by rare events in the dynamics. Enhanced sampling methods may be used in order to speed up sampling by, for example, using high temperatures, as in parallel tempering, or simulating with a biasing potential such as in the case of umbrella sampling. The equilibrium properties of the thermodynamic state of interest (e.g., lowest temperature or unbiased potential) can be computed using reweighting estimators such as the weighted histogram analysis method or the multistate Bennett acceptance ratio (MBAR). weighted histogram analysis method and MBAR produce unbiased estimates, the simulation samples from the global equilibria at their respective thermodynamic states—a requirement that can be prohibitively expensive for some simulations such as a large parallel tempering ensemble of an explicitly solvated biomolecule. Here, we introduce the transition-based reweighting analysis method (TRAM)—a class of estimators that exploit ideas from Markov modeling and only require the simulation data to be in local equilibrium within subsets of the configuration space. We formulate the expanded TRAM (xTRAM) estimator that is shown to be asymptotically unbiased and a generalization of MBAR. Using four exemplary systems of varying complexity, we demonstrate the improved convergence (ranging from a twofold improvement to several orders of magnitude) of xTRAM in comparison to a direct counting estimator and MBAR, with respect to the invested simulation effort. Lastly, we introduce a random-swapping simulation protocol that can be used with xTRAM, gaining orders-of-magnitude advantages over simulation protocols that require the constraint of sampling from a global equilibrium

Thermodynamics of trajectories of the one-dimensional Ising model

We present a numerical study of the dynamics of the one-dimensional Ising model by applying the large-deviation method to describe ensembles of dynamical trajectories. In this approach trajectories are classified according to a dynamical order parameter and the structure of ensembles of trajectories can be understood from the properties of large-deviation functions, which play the role of dynamical free-energies. We consider both Glauber and Kawasaki dynamics, and also the presence of a magnetic field. For Glauber dynamics in the absence of a field we confirm the analytic predictions of Jack and Sollich about the existence of critical dynamical, or space-time, phase transitions at critical values of the "counting" field $s$. In the presence of a magnetic field the dynamical phase diagram also displays first order transition surfaces. We discuss how these non-equilibrium transitions in the 1$d$ Ising model relate to the equilibrium ones of the 2$d$ Ising model. For Kawasaki dynamics we find a much simple dynamical phase structure, with transitions reminiscent of those seen in kinetically constrained models.Comment: 23 pages, 10 figure

HOUSEHOLDS' EXPERIENCES WITH THE RED IMPORTED FIRE ANT IN SOUTH CAROLINA

The red imported fire ant (Solenopsis invicta), abbreviated as RIFA, is believed to have been brought by accident to Mobile, Alabama in the 1930s via ship ballast from South America. The RIFA was first reported in Charleston and Orangeburg counties in South Carolina in 1952 and has since spread to all 46 counties in the state. The RIFA has had adverse impacts on the environments it has infested. In natural environments, the young of ground-nesting insects, reptiles, birds and mammals are subject to RIFA predation. In agriculture, the RIFA damages crops and livestock. The RIFA poses a health threat to humans, as it is aggressive and has a venomous sting. To learn more about the current impacts of the RIFA, a random sample of South Carolina households was conducted between November 1998 and January 1999. This report summarizes the survey results.Environmental Economics and Policy,

Just transition: Employment projections for the 2.0 °c and 1.5 °c scenarios

© The Author(s) 2019. This section provides the input data for two different employment development calculation methods: The quantitative analysis, which looks into the overall number of jobs in renewable and fossil fuel industries and the occupational analysis which looks into specific job categories required for the solar and wind sector as well as the oil, gas, and coal industry. Results are given with various figures and tables

Syntheses and Properties of Two-Dimensional, Dicationic Nonlinear Optical Chromophores Based on Pyrazinyl Cores

Six new dicationic 2D nonlinear optical (NLO) chromophores with pyrazinyl-pyridinium electron acceptors have been synthesized by nucleophilic substitutions of 2,6-dichloropyrazine with pyridyl derivatives. These compounds have been characterized as their PF_6^− salts by using various techniques including electronic absorption spectroscopy and cyclic voltammetry. Large red shifts in the intense, π → π* intramolecular charge-transfer (ICT) transitions on replacing −OMe with –Nme_2 substituents arise from the stronger π-electron donor ability of the latter. Each compound shows a number of redox processes which are largely irreversible. Single crystal X-ray structures have been determined for five salts, including two nitrates, all of which adopt centrosymmetric packing arrangements. Molecular first hyperpolarizabilities β have been determined by using femtosecond hyper-Rayleigh scattering at 880 and 800 nm, and depolarization studies show that the NLO responses of the symmetric species are strongly 2D, with dominant “off-diagonal” β_(zyy) components. Stark (electroabsorption) spectroscopic measurements on the ICT bands afford estimated static first hyperpolarizabilities β_0. The directly and indirectly derived β values are large, and the Stark-derived β_0 response for one of the new salts is several times greater than that determined for (E)-4′-(dimethylamino)-N-methyl-4-stilbazolium hexafluorophosphate. These Stark spectroscopic studies also permit quantitative comparisons with related 2D, binuclear RuII ammine complex salts

Self-organized emergence of folded protein-like network structures from geometric constraints

The intricate three-dimensional geometries of protein tertiary structures underlie protein function and emerge through a folding process from one-dimensional chains of amino acids. The exact spatial sequence and configuration of amino acids, the biochemical environment and the temporal sequence of distinct interactions yield a complex folding process that cannot yet be easily tracked for all proteins. To gain qualitative insights into the fundamental mechanisms behind the folding dynamics and generic features of the folded structure, we propose a simple model of structure formation that takes into account only fundamental geometric constraints and otherwise assumes randomly paired connections. We find that despite its simplicity, the model results in a network ensemble consistent with key overall features of the ensemble of Protein Residue Networks we obtained from more than 1000 biological protein geometries as available through the Protein Data Base. Specifically, the distribution of the number of interaction neighbors a unit (amino acid) has, the scaling of the structure's spatial extent with chain length, the eigenvalue spectrum and the scaling of the smallest relaxation time with chain length are all consistent between model and real proteins. These results indicate that geometric constraints alone may already account for a number of generic features of protein tertiary structures