bims-lances 2024-02-04 papers

Issue of 2024‒02‒04
five papers selected by
James M. Krieger, National Centre for Biotechnology

Int J Biol Macromol. 2024 Jan 30. pii: S0141-8130(24)00646-9. [Epub ahead of print]261(Pt 2): 129843

Comparative analysis of structural dynamics and allosteric mechanisms of RecA/Rad51 family proteins: Integrated atomistic MD simulation and network-based analysis.

Yue Pan, Chong Zhao, Wenyu Fu, Shuo Yang, Shaowu Lv.

Homologous recombination plays a key role in double-strand break repair, stalled replication fork repair, and meiosis. The RecA/Rad51 family recombinases catalyze the DNA strand invasion reaction that occurs during homologous recombination. However, the high sequence differences between homologous groups have hindered the thoroughly studies of this ancient protein family. The dynamic mechanisms of the family, particularly at the residual level, remain poorly understood. In this work, five representative RecA/Rad51 recombinase family members from all major kingdoms of living organisms: prokaryotes, eukaryotes, archaea, and viruses, were selected to explore the molecular mechanisms behind their conserved biological significance. A variety of techniques, including all-atom molecular dynamics simulation, perturbation response scanning, and protein structure network analysis, were used to examine the flexibility and correlation of protein domains, distribution of sensors and effectors and conserved hub residues. Furthermore, the potential communication routes between the ATP-binding region and the DNA-binding region of each recombinase were identified. Our results demonstrate the conserved molecular dynamics of these recombinases in the early stage of homologous recombination, including cooperative motions between regions, conserved sensing and effecting functional residue distribution, and conserved hub residues. Meanwhile, the unique ATP-DNA communication routes of each recombinase was also revealed. These results provide new insights into the mechanism of RecA/Rad51 family proteins, and provide new theoretical guidance for the development of allosteric inhibitors and the application of RecA/Rad51 family proteins.

Keywords: Homologous recombination; Molecular dynamic simulation; RecA/Rad51 family

DOI: https://doi.org/10.1016/j.ijbiomac.2024.129843

Nature. 2024 Jan 31.

Conformational ensembles of the human intrinsically disordered proteome.

Giulio Tesei, Anna Ida Trolle, Nicolas Jonsson, Johannes Betz, Frederik E Knudsen, Francesco Pesce, Kristoffer E Johansson, Kresten Lindorff-Larsen.

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.

DOI: https://doi.org/10.1038/s41586-023-07004-5

Proc Natl Acad Sci U S A. 2024 Feb 06. 121(6): e2313360121

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model.

Thomas R Sisk, Paul Robustelli.

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.

Keywords: Markov state models; deep learning; intrinsically disordered proteins; molecular dynamics; protein folding

DOI: https://doi.org/10.1073/pnas.2313360121

Biophys Chem. 2024 Jan 22. pii: S0301-4622(24)00019-X. [Epub ahead of print]307 107190

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics.

Shingo Ito, Yuji Sugita.

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

Keywords: Collective variables; Enhanced sampling methods; Free-energy landscapes; Implicit membrane model; Molecular dynamics simulations; Transmembrane protein structures

DOI: https://doi.org/10.1016/j.bpc.2024.107190

bioRxiv. 2024 Jan 17. pii: 2024.01.16.575914. [Epub ahead of print]

Structural basis of respiratory complexes adaptation to cold temperatures.

Young-Cheul Shin, Pedro Latorre-Muro, Amina Djurabekova, Oleksii Zdorevskyi, Christopher F Bennett, Nils Burger, Kangkang Song, Chen Xu, Vivek Sharma, Maofu Liao, Pere Puigserver.

In response to cold, mammals activate brown fat for respiratory-dependent thermogenesis reliant on the electron transport chain (1, 2). Yet, the structural basis of respiratory complex adaptation to cold remains elusive. Herein we combined thermoregulatory physiology and cryo-EM to study endogenous respiratory supercomplexes exposed to different temperatures. A cold-induced conformation of CI:III 2 (termed type 2) was identified with a ∼25° rotation of CIII 2 around its inter-dimer axis, shortening inter-complex Q exchange space, and exhibiting different catalytic states which favor electron transfer. Large-scale supercomplex simulations in lipid membrane reveal how unique lipid-protein arrangements stabilize type 2 complexes to enhance catalytic activity. Together, our cryo-EM studies, multiscale simulations and biochemical analyses unveil the mechanisms and dynamics of respiratory adaptation at the structural and energetic level.

DOI: https://doi.org/10.1101/2024.01.16.575914