Chemical Fate of Particulate Sulfur from Nighttime Oxidation of Thiophene.

Sulfur-containing volatile organic compounds emitted during wildfire events, such as dimethyl sulfide, are known to form secondary aerosols containing inorganic sulfate (SO ) and surfactant-like organic compounds; however, little is known about the fate of sulfur in other emitted reduced organosulfur species. This study aimed to determine the sulfurous product distribution resulting from the nighttime oxidation of thiophene as a model system. Ion chromatography (IC) and aerosol mass spectrometry (a mini aerosol mass spectrometer, mAMS) were used to constrain the proportions of sulfurous compounds produced under wildfire-relevant conditions ([NO]/[O] = 0.

Konnektor: A Framework for Using Graph Theory to Plan Networks for Free Energy Calculations.

Alchemical free energy campaigns can be planned using graph theory by building networks that contain nodes representing molecules that are connected by possible transformations as edges. We introduce Konnektor, an open-source Python package, for systematically planning, modifying, and analyzing free energy calculation networks. Konnektor is designed to aid in the drug discovery process by enabling users to easily setup free energy campaigns using complex graph manipulation methods.

Automated Absolute Binding Free Energy Calculation Workflow for Drug Discovery.

Absolute binding free energies play a crucial role in drug development, particularly as part of the lead discovery process. In recent work, we showed how predictions directly could support drug development by ranking and recommending favorable ideas over unfavorable ones. Here, we demonstrate a Python workflow that enables the calculation of ABFEs with minimal manual input effort, such as the receptor PDB and ligand SDF files, and outputs a .

Relative Humidity Modulates the Physicochemical Processing of Secondary Brown Carbon Formation from Nighttime Oxidation of Furan and Pyrrole.

Light-absorbing secondary organic aerosols (SOAs), also known as secondary brown carbon (BrC), are major components of wildfire smoke that can have a significant impact on the climate system; however, how environmental factors such as relative humidity (RH) influence their formation is not fully understood, especially for heterocyclic precursors. We conducted chamber experiments to investigate secondary BrC formation from the nighttime oxidation of furan and pyrrole, two primary heterocyclic precursors in wildfires, in the presence of pre-existing particles at RH < 20% and ∼ 50%. Our findings revealed that increasing RH significantly affected the size distribution dynamics of both SOAs, with pyrrole SOA showing a stronger potential to generate ultrafine particles via intensive nucleation processes.

Kartograf: A Geometrically Accurate Atom Mapper for Hybrid-Topology Relative Free Energy Calculations.

Relative binding free energy (RBFE) calculations have emerged as a powerful tool that supports ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular, the setup of such calculations. Atom mapping algorithms are an essential component in setting up automatic large-scale hybrid-topology RBFE calculation campaigns.

Accelerating Alchemical Free Energy Prediction Using a Multistate Method: Application to Multiple Kinases.

Alchemical free-energy methods based on molecular dynamics (MD) simulations have become important tools to identify modifications of small organic molecules that improve their protein binding affinity during lead optimization. The routine application of pairwise free-energy methods to rank potential binders from best to worst is impacted by the combinatorial increase in calculations to perform when the number of molecules to assess grows. To address this fundamental limitation, our group has developed replica-exchange enveloping distribution sampling (RE-EDS), a pathway-independent multistate method, enabling the calculation of alchemical free-energy differences between multiple ligands ( > 2) from a single MD simulation.

Accounting for Solvation Correlation Effects on the Thermodynamics of Water Networks in Protein Cavities.

Macromolecular recognition and ligand binding are at the core of biological function and drug discovery efforts. Water molecules play a significant role in mediating the protein-ligand interaction, acting as more than just the surrounding medium by affecting the thermodynamics and thus the outcome of the binding process. As individual water contributions are impossible to measure experimentally, a range of computational methods have emerged to identify hydration sites in protein pockets and characterize their energetic contributions for drug discovery applications.

Leveraging the sampling efficiency of RE-EDS in OpenMM using a shifted reaction-field with an atom-based cutoff.

Replica-exchange enveloping distribution sampling (RE-EDS) is a pathway-independent multistate free-energy method currently implemented in the GROMOS software package for molecular dynamics (MD) simulations. It has a high intrinsic sampling efficiency as the interactions between the unperturbed particles have to be calculated only once for multiple end-states. As a result, RE-EDS is an attractive method for the calculation of relative solvation and binding free energies.

Replica-Exchange Enveloping Distribution Sampling Using Generalized AMBER Force-Field Topologies: Application to Relative Hydration Free-Energy Calculations for Large Sets of Molecules.

Free-energy differences between pairs of end-states can be estimated based on molecular dynamics (MD) simulations using standard pathway-dependent methods such as thermodynamic integration (TI), free-energy perturbation, or Bennett's acceptance ratio. Replica-exchange enveloping distribution sampling (RE-EDS), on the other hand, allows for the sampling of multiple end-states in a single simulation without the specification of any pathways. In this work, we use the RE-EDS method as implemented in GROMOS together with generalized AMBER force-field (GAFF) topologies, converted to a GROMOS-compatible format with a newly developed GROMOS++ program , to compute relative hydration free energies for a series of benzene derivatives.

Replica-Exchange Enveloping Distribution Sampling: Calculation of Relative Free Energies in GROMOS.

Molecular dynamics (MD) simulations have become an important tool to investigate biological systems. Free-energy calculations based on MD are playing an increasingly important role for computer-aided drug design and material discovery in recent years. Free-energy differences between pairs of end-states can be estimated using well-established methods such as thermodynamic integration (TI) or Bennett's acceptance ratio (BAR).

Polar/apolar interfaces modulate the conformational behavior of cyclic peptides with impact on their passive membrane permeability.

Cyclic peptides have the potential to vastly extend the scope of druggable proteins and lead to new therapeutics for currently untreatable diseases. However, cyclic peptides often suffer from poor bioavailability. To uncover design principles for permeable cyclic peptides, a promising strategy is to analyze the conformational dynamics of the peptides using molecular dynamics (MD) and Markov state models (MSMs).

RestraintMaker: a graph-based approach to select distance restraints in free-energy calculations with dual topology.

The calculation of relative binding free energies (RBFE) involves the choice of the end-state/system representation, of a sampling approach, and of a free-energy estimator. System representations are usually termed "single topology" or "dual topology". As the terminology is often used ambiguously in the literature, a systematic categorization of the system representations is proposed here.

Relative free-energy calculations for scaffold hopping-type transformations with an automated RE-EDS sampling procedure.

The calculation of relative free-energy differences between different compounds plays an important role in drug design to identify potent binders for a given protein target. Most rigorous methods based on molecular dynamics simulations estimate the free-energy difference between pairs of ligands. Thus, the comparison of multiple ligands requires the construction of a "state graph", in which the compounds are connected by alchemical transformations.

Recent developments in multiscale free energy simulations.

Physics-based free energy simulations enable the rigorous calculation of properties, such as conformational equilibria, solvation or binding free energies. While historically most applications have occurred at the atomistic level of resolution, a range of advances in the past years make it possible now to reliably cross the temporal, spatial and theory scales for the modeling of complex systems or the efficient prediction of results at the accuracy level of expensive quantum-mechanical calculations. In this mini-review, we discuss recent methodological advances as well as opportunities opened up by the introduction of machine learning approaches, which tackle the diverse challenges across the different scales, improve the accuracy and feasibility, and push the boundaries of multiscale free energy simulations.

Efficient Alchemical Intermediate States in Free Energy Calculations Using λ-Enveloping Distribution Sampling.

Alchemical free energy calculations generally require intermediate states along a coupling parameter λ to establish sufficient phase space overlap for obtaining converged results. Such intermediate states can also be engineered to lower the energy barriers and, consequently, reduce the required sampling time. The recently introduced λ-enveloping distribution sampling (λ-EDS) scheme combines the properties of the minimum variance pathway and the EDS methods to improve sampling and allow for larger steps along the alchemical pathway compared to conventional approaches.

Passing the Barrier - How Computer Simulations Can Help to Understand and Improve the Passive Membrane Permeability of Cyclic Peptides.

Proteins with large and flat binding sites as well as protein-protein interactions are considered ' undruggable ' with conventional small-molecule drugs. Cyclic peptides have been found to be capable of binding to such targets with high affinity, making this class of compounds an interesting source for possible therapeutics. However, the oftentimes poor passive membrane permeability of cyclic peptides still imposes restrictions on the applicability of cyclic peptide drugs.

Modulation of the Passive Permeability of Semipeptidic Macrocycles: N- and C-Methylations Fine-Tune Conformation and Properties.

Incorporating small modifications to peptidic macrocycles can have a major influence on their properties. For instance, N-methylation has been shown to impact permeability. A better understanding of the relationship between permeability and structure is of key importance as peptidic drugs are often associated with unfavorable pharmacokinetic profiles.

Volume-scaled common nearest neighbor clustering algorithm with free-energy hierarchy.

The combination of Markov state modeling (MSM) and molecular dynamics (MD) simulations has been shown in recent years to be a valuable approach to unravel the slow processes of molecular systems with increasing complexity. While the algorithms for intermediate steps in the MSM workflow such as featurization and dimensionality reduction have been specifically adapted to MD datasets, conventional clustering methods are generally applied to the discretization step. This work adds to recent efforts to develop specialized density-based clustering algorithms for the Boltzmann-weighted data from MD simulations.

Ensembler: A Simple Package for Fast Prototyping and Teaching Molecular Simulations.

Ensembler is a Python package that enables method prototyping using 1D and 2D model systems and allows deepening of the understanding of different molecular dynamics (MD) methods, starting from basic techniques to enhanced sampling and free-energy approaches. The ease of installing and using the package increases shareability, comparability, and reproducibility of scientific code developments. Here, we describe the implementation and usage of the package and provide an application example for free-energy calculation.

[Validation of the Hungarian version of the Professional Quality of Life Scale].

Introduction: The Professional Quality of Life Scale, measuring the quality of professional life, has been developed to examine the positive and negative changes in the work of those who have undergone extremely stressful experiences. The quality of life of the personnel of palliative-hospice teams may be influenced physically as well as emotionally by their every-day experiences of suffering, death, dying and the patients' traumas.

Aim: The aim of the study was the examination of the psychometric features and factor structure of the Hungarian version of the Professional Quality of Life Scale questionnaire, which can measure compassion fatigue and satisfaction, secondary traumatisation and burnout.

Interfaces between Model Co-W-C Alloys with Various Carbon Contents and Tungsten Carbide.

Interfaces between alloys simulating binders in WC-Co cemented carbides and tungsten carbide were examined on the micro-, nano-, and atomic-scale. The precipitation of fine WC grains and η-phase occurs at the interface of the alloy with the low carbon content. The precipitation of such grains almost does not occur in the alloy with the medium-low carbon content and does not take place in the alloy with the high carbon content.

Examining Emergency Department Treatment Processes in Severe Pediatric Traumatic Brain Injury.

Background: In the treatment of pediatric traumatic brain injury (TBI), timely treatment of patients can affect the outcome. Our objectives were to examine the treatment process of acute pediatric TBI and the impact of non-value-added time (NVAT) on patient outcomes.

Methods: Data for 136 pediatric trauma patients (age < 18 years) with severe TBI from 2 trauma centers in the United States were collected.

Complexity and Algorithms for Finding a Perfect Phylogeny from Mixed Tumor Samples.

Hajirasouliha and Raphael (WABI 2014) proposed a model for deconvoluting mixed tumor samples measured from a collection of high-throughput sequencing reads. This is related to understanding tumor evolution and critical cancer mutations. In short, their formulation asks to split each row of a binary matrix so that the resulting matrix corresponds to a perfect phylogeny and has the minimum number of rows among all matrices with this property.

The GTPase activity of murine guanylate-binding protein 2 (mGBP2) controls the intracellular localization and recruitment to the parasitophorous vacuole of Toxoplasma gondii.

One of the most abundantly IFN-γ-induced protein families in different cell types is the 65-kDa guanylate-binding protein family that is recruited to the parasitophorous vacuole of the intracellular parasite Toxoplasma gondii. Here, we elucidate the relationship between biochemistry and cellular host defense functions of mGBP2 in response to Toxoplasma gondii. The wild type protein exhibits low affinities to guanine nucleotides, self-assembles upon GTP binding, forming tetramers in the activated state, and stimulates the GTPase activity in a cooperative manner.