PACSAB: Coarse-Grained Force Field for the Study of Protein–Protein Interactions and Conformational Sampling in Multiprotein Systems

Emperador, Agustí; Sfriso, Pedro; Villarreal, Marcos Ariel; Gelpí, Josep Lluís; Orozco, Modesto

doi:10.1021/acs.jctc.5b00660

Cited by 15 publications

(32 citation statements)

References 47 publications

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“…In the context of discrete molecular dynamics, a new coarse-grained force field has been recently introduced to investigate PPI and conformational sampling of multiprotein systems. 491 Interestingly, it was also reported that coarsegrained models can accurately reproduce interaction strength for protein complexes of known structure. 492 An interesting example of a coarse-grained approach to protein docking is the ATTRACT model.…”

Section: Protein Interactionsmentioning

confidence: 99%

Coarse-Grained Protein Models and Their Applications

et al. 2016

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The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.

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Section: Protein Interactionsmentioning

confidence: 99%

Coarse-Grained Protein Models and Their Applications

et al. 2016

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“…To avoid being trapped in such minima, the HS--MMC switches between an all--atom Hamiltonian to an excluded volume Hamiltonian to push the IDR away from the ordered domain.Both, MD--based and MC--based approaches may suffer from inaccuracies of current energy models, which are better suited to globular proteins, and tend to provide structurally biased ensembles that do not properly reflect the conformational behaviour in solution of unstructured proteins(Best et al, 2014;Henriques et al, 2015). The development of more suitable force--fields and solvation models for IDPs are key issues for a correct performance of computational methods(Vitalis and Pappu, 2009b;Emperador et al, 2015).Knowledge--based statistical approaches are an alternative to physics--based energy functions. The most representative knowledge--based method for the generation of atomistic models of disordered proteins is Flexible--Meccano (FM)(Bernadó et al, 2005;Ozenne et al, 2012), although other similar methods have been described(Jha et al, 2005).…”

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confidence: 99%

Structural Characterization of Highly Flexible Proteins by Small-Angle Scattering

Cordeiro

Herranz-Trillo

Urbanek

et al. 2017

Advances in Experimental Medicine and Biology

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Intrinsically Disordered Proteins (IDPs) are fundamental actors of biological processes. Their inherent plasticity facilitates very specialized tasks in cell regulation and signalling, and their malfunction is linked to severe pathologies. Understanding the functional role of disorder requires the structural characterization of IDPs and the complexes they form. Small-angle Scattering of X-rays (SAXS) and Neutrons (SANS) have notably contributed to this structural understanding. In this review we summarize the most relevant developments in the field of SAS studies of disordered proteins. Emphasis is given to ensemble methods and how SAS data can be combined with computational approaches or other biophysical information such as NMR. The unique capabilities of SAS enable its application to extremely challenging disordered systems such as low-complexity regions, amyloidogenic proteins and transient biomolecular complexes. This reinforces the fundamental role of SAS in the structural and dynamic characterization of this elusive family of proteins.

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“…In this work, we apply our PACSAB model [ 9 ] to the study of protein aggregation and protein–protein molecular recognition. The PACSAB model is a coarse-grained protein model based on an implicit solvent approach, which uses a highly detailed coarse-grained representation of the amino acid side chains, while keeping an atomistic representation of the backbone in order to describe accurately secondary structure elements.…”

Section: Introductionmentioning

confidence: 99%

Accurate Description of Protein–Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model

Emperador

2021

Polymers

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We used the PACSAB protein model, based on the implicit solvation approach, to simulate protein–protein recognition and study the effect of helical structure on the association of aggregating peptides. After optimization, the PACSAB force field was able to reproduce correctly both the correct binding interface in ubiquitin dimerization and the conformational ensemble of the disordered protein activator for hormone and retinoid receptor (ACTR). The PACSAB model allowed us to predict the native binding of ACTR with its binding partner, reproducing the refolding upon binding mechanism of the disordered protein.

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PACSAB: Coarse-Grained Force Field for the Study of Protein–Protein Interactions and Conformational Sampling in Multiprotein Systems

Cited by 15 publications

References 47 publications

Coarse-Grained Protein Models and Their Applications

Coarse-Grained Protein Models and Their Applications

Structural Characterization of Highly Flexible Proteins by Small-Angle Scattering

Accurate Description of Protein–Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model

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