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Here, the authors show that decreasing the strength of protein-protein interactions leads to improved agreement of Martini 3 generated molecular dynamics simulations with experimental data on a wide set of systems.

Computational methods are becoming an increasingly important part of biological research. Using the Rosetta framework as an example, the authors demonstrate how community-driven development of computational methods can be done in a reproducible and reliable fashion.

SSEmb is a multi-modal machine learning model that predicts how changes in a protein’s amino acid sequence affect its function by combining information from a multiple sequence alignment and the three-dimensional structure.

Amyloid fibrils grow through the recruitment of soluble monomer to the fibril end that propagates the fibril structure. Here the transition state, the rate-limiting conformation, of such a reaction has been characterized by Φ-value analysis. An energy landscape model has been developed and fibril growth rates predicted from first principles.

The molecular mechanisms of how small changes in the degree of inclusion of a neuron-specific microexon in CPEB4 lead to dominant-negative effects in the expression of genes associated with autism spectrum disorder are identified.

Asymmetric phospholipid distribution in cell membranes is vital for cellular function. Here, authors reveal how ATP8B1, a P4-ATPase, can transport different lipids, including phosphatidylinositol.

An important step in understanding and using proteins is to identify the residues that are important for function. The authors present a machine-learning based method to predict functional sites that leverages and combines the information available in protein sequences and structures.

The details of how the protein folding and degradation systems collaborate to combat potentially toxic non-native proteins are unknown. Here the authors perform systematic studies of missense and nonsense variants of the cytosolic aspartoacylase, ASPA, where loss-of-function variants are linked to Canavan disease.

How misfolded proteins are selected by the ubiquitin-conjugating system for elimination is largely unknown. Here, the authors identify conserved features of proteome-derived degradation signals, including amino acid and structural preferences, that trigger quality-control-associated proteolysis.

Gene variants can affect folding and stability of the encoded protein. Here, the authors apply deep mutational scanning to provide genotype-phenotype information for 99% of the possible PRKN variants and reveal mechanistic details on how some variants cause loss-of-function and Parkinsons disease.

A computational model generates conformational ensembles of 28,058 intrinsically disordered proteins and regions (IDRs) in the human proteome and sheds light on the relationship between sequence, conformational properties and functions of IDRs.

Polyglutamine (polyQ) tracts are low-complexity regions and their expansion is linked to certain neurodegenerative diseases. Here the authors combine experimental and computational approaches to find that the length of the androgen receptor polyQ tract correlates with its helicity and show that the polyQ helical structure is stabilized by hydrogen bonds between the Gln side chains and main chain carbonyl groups.

The prolactin receptor consists of a folded extracellular domain, a transmembrane domain and an intracellular intrinsically disordered domain. Here the authors use a combined experimental and computational approach to obtain a structure of a class I cytokine receptor, the human prolactin receptor.

Here, the authors evaluate the performance of AlphaFold2 and its predicted structures on common structural biological applications, including missense variants, function and ligand binding site prediction, modeling of interactions and modeling of experimental structural data.

In placental malaria, interactions between parasite protein VAR2CSA and human glycosaminoglycan chondroitin sulfate A (CS) sequesters infected red blood cells in the placenta. Here, the authors provide cryo-EM structures of VAR2CSA and placental CS, identifying molecular interactions that could guide design of placental malaria vaccines.

Heterologous expression of recombinant proteins often results in misfolding, aggregation and degradation. Here, we show an in vivo dual-biosensor system that simultaneously assesses protein translation and protein folding, thereby enabling rapid screening of expression strains as well as mutant libraries.

The dopamine transporter is responsible for termination of neurotransmission through Na⁺-driven reuptake of neurotransmitter from the extracellular space. Here authors use hydrogen-deuterium exchange mass spectrometry to monitor Na⁺- and dopamine-induced conformational dynamics of the dopamine transporter.

The realization that the cell is abundantly compartmentalized into biomolecular condensates has opened new opportunities for understanding the physics and chemistry underlying many cellular processes¹, fundamentally changing the study of biology². The term biomolecular condensate refers to non-stoichiometric assemblies that are composed of multiple types of macromolecules in cells, occur through phase transitions, and can be investigated by using concepts from soft matter physics³. As such, they are intimately related to aqueous two-phase systems⁴ and water-in-water emulsions⁵. Condensates possess tunable emergent properties such as interfaces, interfacial tension, viscoelasticity, network structure, dielectric permittivity, and sometimes interphase pH gradients and electric potentials^6–14. They can form spontaneously in response to specific cellular conditions or to active processes, and cells appear to have mechanisms to control their size and location^15–17. Importantly, in contrast to membrane-enclosed organelles such as mitochondria or peroxisomes, condensates do not require the presence of a surrounding membrane.

In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm.

The authors present and showcase applications for an easy-to-use Python package to predict FRET efficiencies from ensembles of protein conformations via a rotamer library approach.

Louise Hamborg et al. use a cell-based screen in E. coli to look for mutants of chymotrypsin inhibitor 2 which are either destabilized or stabilized, in an effort to identify a larger library of mutants which might improve stability prediction. Their work demonstrates how subtle conformational effects in proteins may modulate protein stability.

The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.