Multitarget, Selective Compound Design Yields Potent Inhibitors of a Kinetoplastid Pteridine Reductase 1.

The optimization of compounds with multiple targets is a difficult multidimensional problem in the drug discovery cycle. Here, we present a systematic, multidisciplinary approach to the development of selective antiparasitic compounds. Computational fragment-based design of novel pteridine derivatives along with iterations of crystallographic structure determination allowed for the derivation of a structure-activity relationship for multitarget inhibition.

Stereoinversion of tetrahedral p-block element hydrides.

The potential energy surfaces of 15 tetrahedral p-block element hydrides were screened on the multireference level. It was addressed whether stereoinversion competes against other reactions, such as reductive H-elimination or hydride loss, and if so, along which pathway the stereomutation occurs. Importantly, stereoinversion transition structures for the ammonium cation (C) and the tetrahydridoborate anion (C) were identified for the first time.

Opportunities and challenges in machine learning-based newborn screening-A systematic literature review.

The development and continuous optimization of newborn screening (NBS) programs remains an important and challenging task due to the low prevalence of screened diseases and high sensitivity requirements for screening methods. Recently, different machine learning (ML) methods have been applied to support NBS. However, most studies only focus on single diseases or specific ML techniques making it difficult to draw conclusions on which methods are best to implement.

Martini 3 coarse-grained force field for poly(-phenylene ethynylene)s.

Poly(-phenylene ethynylene)s, or short PPEs, are a class of conjugated and semi-flexible polymers with a strongly delocalized π electron system and increased chain stiffness. Due to this, PPEs have a wide range of technological applications. Although the material properties of single-chains or mixtures of few PPE chains have been studied in detail, the properties of large assemblies remain to be fully explored.

The Effect of an Additional Structured Methods Presentation on Decision-Makers' Reading Time and Opinions on the Helpfulness of the Methods in a Quantitative Report: Nonrandomized Trial.

Background: Although decision-makers in health care settings need to read and understand the validity of quantitative reports, they do not always carefully read information on research methods. Presenting the methods in a more structured way could improve the time spent reading the methods and increase the perceived relevance of this important report section.

Objective: To test the effect of a structured summary of the methods used in a quantitative data report on reading behavior with eye-tracking and measure the effect on the perceived importance of this section.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Development and Biological Characterization of a Novel Selective TrkA Agonist with Neuroprotective Properties against Amyloid Toxicity.

Neurotrophins are growth factors that exert important neuroprotective effects by preventing neuronal death and synaptic loss. Nerve Growth Factor (NGF) acts through the activation of its high-affinity, pro-survival TrkA and low-affinity, pro-apoptotic p75 receptors. NGF has been shown to slow or prevent neurodegenerative signals in Alzheimer's Disease (AD) progression.

Methane formation driven by reactive oxygen species across all living organisms.

Methane (CH), the most abundant hydrocarbon in the atmosphere, originates largely from biogenic sources linked to an increasing number of organisms occurring in oxic and anoxic environments. Traditionally, biogenic CH has been regarded as the final product of anoxic decomposition of organic matter by methanogenic archaea. However, plants, fungi, algae and cyanobacteria can produce CH in the presence of oxygen.

ATP allosterically stabilizes integrin-linked kinase for efficient force generation.

SignificanceThe pseudokinase integrin-linked kinase (ILK) is a central component of focal adhesions, cytoplasmic multiprotein complexes that integrate and transduce biochemical and mechanical signals from the extracellular environment into the cell and vice versa. However, the precise molecular functions, particularly the mechanosensory properties of ILK and the significance of retained adenosine triphosphate (ATP) binding, are still unclear. Combining molecular-dynamics simulations with cell biology, we establish a role for ATP binding to pseudokinases.

The Non-phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenase GapN Is a Potential New Drug Target in .

The strict human pathogen causes infections of varying severity, ranging from self-limiting suppurative infections to life-threatening diseases like necrotizing fasciitis or streptococcal toxic shock syndrome. Here, we show that the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase GapN is an essential enzyme for . GapN converts glyceraldehyde 3-phosphate into 3-phosphoglycerate coupled to the reduction of NADP to NADPH.

Computational Models for Clinical Applications in Personalized Medicine-Guidelines and Recommendations for Data Integration and Model Validation.

The future development of personalized medicine depends on a vast exchange of data from different sources, as well as harmonized integrative analysis of large-scale clinical health and sample data. Computational-modelling approaches play a key role in the analysis of the underlying molecular processes and pathways that characterize human biology, but they also lead to a more profound understanding of the mechanisms and factors that drive diseases; hence, they allow personalized treatment strategies that are guided by central clinical questions. However, despite the growing popularity of computational-modelling approaches in different stakeholder communities, there are still many hurdles to overcome for their clinical routine implementation in the future.

Strength and Nature of Host-Guest Interactions in Metal-Organic Frameworks from a Quantum-Chemical Perspective.

Metal-organic frameworks (MOFs) offer a convenient means for capturing, transporting, and releasing small molecules. Their rational design requires an in-depth understanding of the underlying non-covalent host-guest interactions, and the ability to easily and rapidly pre-screen candidate architectures in silico. In this work, we devised a recipe for computing the strength and analysing the nature of the host-guest interactions in MOFs.

Mechanical force can enhance c-Src kinase activity by impairing autoinhibition.

Cellular mechanosensing is pivotal for virtually all biological processes, and many molecular mechano-sensors and their way of function are being uncovered. In this work, we suggest that c-Src kinase acts as a direct mechano-sensor. c-Src is responsible for, among others, cell proliferation, and shows increased activity in stretched cells.

Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy.

The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model.

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology.

Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol-disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins.

The binding of heparin to spike glycoprotein inhibits SARS-CoV-2 infection by three mechanisms.

Heparin, a naturally occurring glycosaminoglycan, has been found to have antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus of COVID-19. To elucidate the mechanistic basis for the antiviral activity of heparin, we investigated the binding of heparin to the SARS-CoV-2 spike glycoprotein by means of sliding window docking, molecular dynamics simulations, and biochemical assays. Our simulations show that heparin binds at long, positively charged patches on the spike glycoprotein, thereby masking basic residues of both the receptor-binding domain (RBD) and the multifunctional S1/S2 site.

EnzymeML-a data exchange format for biocatalysis and enzymology.

EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases.

Phosphorylation tunes elongation propensity and cohesiveness of INCENP's intrinsically disordered region.

The inner centromere protein, INCENP, is crucial for correct chromosome segregation during mitosis. It connects the kinase Aurora B to the inner centromere allowing this kinase to dynamically access its kinetochore targets. However, the function of its central, 440-residue long intrinsically disordered region (IDR) and its multiple phosphorylation sites is unclear.

The HIV-1 Nucleocapsid Regulates Its Own Condensation by Phase-Separated Activity-Enhancing Sequestration of the Viral Protease during Maturation.

A growing number of studies indicate that mRNAs and long ncRNAs can affect protein populations by assembling dynamic ribonucleoprotein (RNP) granules. These phase-separated molecular 'sponges', stabilized by quinary (transient and weak) interactions, control proteins involved in numerous biological functions. Retroviruses such as HIV-1 form by self-assembly when their genomic RNA (gRNA) traps Gag and GagPol polyprotein precursors.

Improving the FAIRness of Health Studies in Germany: The German Central Health Study Hub COVID-19.

The German Central Health Study Hub COVID-19 is an online service that offers bundled access to COVID-19 related studies conducted in Germany. It combines metadata and other information of epidemiologic, public health and clinical studies into a single data repository for FAIR data access. In addition to study characteristics the system also allows easy access to study documents, as well as instruments for data collection.