COCOMO2: A coarse-grained model for interacting folded and disordered proteins

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 1, 2024

ABSTRACT Biomolecular interactions are essential in many biological processes, including complex formation and phase separation processes. Coarse-grained computational models especially valuable for studying such processes via simulation. Here, we present COCOMO2, an updated residue-based coarse-grained model that extends its applicability from intrinsically disordered peptides to folded proteins. This is accomplished with the introduction of a surface exposure scaling factor, which adjusts interaction strengths based on solvent accessibility, enable more realistic modeling involving domains without additional costs. COCOMO2 was parameterized directly solubility data improve performance predicting concentration-dependent broader range biomolecular systems compared original version. enables new applications study condensates involve IDPs together assembly also provides expanded foundation development multi-scale approaches span residue-level atomistic resolution. Table Contents Figure

Язык: Английский

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BaNDyT: Bayesian Network modeling of molecular Dynamics Trajectories

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 8, 2024

Bayesian network modeling (BN modeling, or BNM) is an interpretable machine learning method for constructing probabilistic graphical models from the data. In recent years, it has been extensively applied to diverse types of biomedical datasets. Concurrently, our ability perform long-timescale molecular dynamics (MD) simulations on proteins and other materials increased exponentially. However, analysis MD simulation trajectories not data-driven but rather dependent user's prior knowledge systems, thus limiting scope utility simulations. Recently, we pioneered using BNM analyzing protein complexes. The resulting BN yield novel fully insights into functional importance amino acid residues that modulate proteins' function. this report, describe BaNDyT software package implements specifically attuned We believe first include specialized advanced features a model. here software's uses, methods associated with it, comprehensive Python interface underlying generalist code. This provides powerful versatile mechanism users control workflow. As application example, have utilized methodology study how membrane proteins, G protein-coupled receptors, selectively couple proteins. can be used any as well polymeric materials.

Язык: Английский

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Charged peptides enriched in aromatic residues decelerate condensate ageing driven by cross-β-sheet formation

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 20, 2024

Biomolecular condensates, formed through liquid-liquid phase separation, play wide-ranging roles in cellular compartmentalization and biological processes. However, their transition from a functional liquid-like into solid-like state - usually termed as condensate ageing represents hallmark associated with the onset of multiple neurodegenerative diseases. In this study, we design computational pipeline to explore potential candidates, form small peptides, regulate kinetics biomolecular condensates. By combining equilibrium non-equilibrium simulations sequence-dependent residue-resolution force field, investigate impact peptide insertion different composition, patterning, net charge diagram archetypal proteins driving ageing: TDP-43 FUS. We reveal that peptides composed by specific balance aromatic charged residues can substantially decelerate up two orders magnitude. The mechanism is controlled density reduction induced self-repulsive electrostatic interactions specifically target protein regions prone cross-beta-sheet fibrils. Our work proposes an efficient framework rapidly scan molecule develop novel pathways for controlling transitions relevant disease prevention.

Язык: Английский

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