A model-informed method to retrieve intrinsic from apparent cooperativity and project cellular target occupancy for ternary complex-forming compounds.

There is an increasing interest to develop therapeutics that modulate challenging or undruggable target proteins a mechanism that involves ternary complexes. In general, such compounds can be characterized by their direct affinities to a chaperone and a target protein and by their degree of cooperativity in the formation of the ternary complex. As a trend, smaller compounds have a greater dependency on intrinsic cooperativity to their thermodynamic stability relative to direct target (or chaperone) binding.

Efficacy and safety of MAS825 (anti-IL-1β/IL-18) in COVID-19 patients with pneumonia and impaired respiratory function.

MAS825, a bispecific IL-1β/IL-18 monoclonal antibody, could improve clinical outcomes in COVID-19 pneumonia by reducing inflammasome-mediated inflammation. Hospitalized non-ventilated patients with COVID-19 pneumonia (n = 138) were randomized (1:1) to receive MAS825 (10 mg/kg single i.v.

Time matters - cellular disposition kinetics help rationalizing cellular potency disconnects.

Loss in potency is commonly observed in early drug discovery when moving from biochemical to more complex cellular systems. Among other factors, low permeability is often considered to cause such potency disconnects.We developed a novel cellular disposition assay in MDCK cells to determine passive uptake clearance (PS), cell-to-medium ratios at steady-state () and the time to reach 90% steady-state (TTSS) from a single experiment in a high-throughput format.

High-Dimensional Analysis of Immune Cell Composition Predicts Periprosthetic Joint Infections and Dissects Its Pathophysiology.

Accurate diagnosis of periprosthetic joint infections (PJI) is one of the most widely researched areas in modern orthopedic endoprosthesis. However, our understanding of the immunological basis of this severe complication is still limited. In this study, we developed a flow cytometric approach to precisely characterize the immune cell composition in periprosthetic joints.

Perturbation biology links temporal protein changes to drug responses in a melanoma cell line.

Cancer cells have genetic alterations that often directly affect intracellular protein signaling processes allowing them to bypass control mechanisms for cell death, growth and division. Cancer drugs targeting these alterations often work initially, but resistance is common. Combinations of targeted drugs may overcome or prevent resistance, but their selection requires context-specific knowledge of signaling pathways including complex interactions such as feedback loops and crosstalk.

Protein Structure from Experimental Evolution.

Natural evolution encodes rich information about the structure and function of biomolecules in the genetic record. Previously, statistical analysis of co-variation patterns in natural protein families has enabled the accurate computation of 3D structures. Here, we explored generating similar information by experimental evolution, starting from a single gene and performing multiple cycles of in vitro mutagenesis and functional selection in Escherichia coli.

Computer-guided design of optimal microbial consortia for immune system modulation.

Manipulation of the gut microbiota holds great promise for the treatment of diseases. However, a major challenge is the identification of therapeutically potent microbial consortia that colonize the host effectively while maximizing immunologic outcome. Here, we propose a novel workflow to select optimal immune-inducing consortia from microbiome compositicon and immune effectors measurements.

MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses.

Predicting dynamics of host-microbial ecosystems is crucial for the rational design of bacteriotherapies. We present MDSINE, a suite of algorithms for inferring dynamical systems models from microbiome time-series data and predicting temporal behaviors. Using simulated data, we demonstrate that MDSINE significantly outperforms the existing inference method.

Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types.

Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile.

The gastrointestinal tracts of mammals are colonized by hundreds of microbial species that contribute to health, including colonization resistance against intestinal pathogens. Many antibiotics destroy intestinal microbial communities and increase susceptibility to intestinal pathogens. Among these, Clostridium difficile, a major cause of antibiotic-induced diarrhoea, greatly increases morbidity and mortality in hospitalized patients.

Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota.

The intestinal microbiota is a microbial ecosystem of crucial importance to human health. Understanding how the microbiota confers resistance against enteric pathogens and how antibiotics disrupt that resistance is key to the prevention and cure of intestinal infections. We present a novel method to infer microbial community ecology directly from time-resolved metagenomics.

On the need for widespread horizontal gene transfers under genome size constraint.

Background: While eukaryotes primarily evolve by duplication-divergence expansion (and reduction) of their own gene repertoire with only rare horizontal gene transfers, prokaryotes appear to evolve under both gene duplications and widespread horizontal gene transfers over long evolutionary time scales. But, the evolutionary origin of this striking difference in the importance of horizontal gene transfers remains by and large a mystery.

Hypothesis: We propose that the abundance of horizontal gene transfers in free-living prokaryotes is a simple but necessary consequence of two opposite effects: i) their apparent genome size constraint compared to typical eukaryote genomes and ii) their underlying genome expansion dynamics through gene duplication-divergence evolution, as demonstrated by the presence of many tandem and block repeated genes.