How the protonation state of a phosphorylated amino acid governs molecular recognition: insights from classical molecular dynamics simulations

Kawade, Raiji; Kuroda, Daisuke; Tsumoto, Kouhei

doi:10.1002/1873-3468.13674

Cited by 12 publications

(6 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the pKa of the phosphorylated residues is around six [ 37 ], in reality it can fluctuate between

and

. Recent studies have suggested the importance of the protonation state of phosphorylated residues for molecular interactions [ 38 ], hence influencing salt bridge formation and the conformational ensemble. Therefore, this is suggested to be included in future investigations.…”

Section: Discussionmentioning

confidence: 99%

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

Rieloff

Skepö

2021

IJMS

View full text Add to dashboard Cite

Phosphorylation is a common post-translational modification among intrinsically disordered proteins and regions, which helps regulate function by changing the protein conformations, dynamics, and interactions with binding partners. To fully comprehend the effects of phosphorylation, computer simulations are a helpful tool, although they are dependent on the accuracy of the force field used. Here, we compared the conformational ensembles produced by Amber ff99SB-ILDN+TIP4P-D and CHARMM36m, for four phosphorylated disordered peptides ranging in length from 14–43 residues. CHARMM36m consistently produced more compact conformations with a higher content of bends, mainly due to more stable salt bridges. Based on comparisons with experimental size estimates for the shortest and longest peptide, CHARMM36m appeared to overestimate the compactness. The difference between the force fields was largest for the peptide showing the greatest separation between positively charged and phosphorylated residues, in line with the importance of charge distribution. For this peptide, the conformational ensemble did not change significantly upon increasing the ionic strength from 0 mM to 150 mM, despite a reduction of the salt-bridging probability in the CHARMM36m simulations, implying that salt concentration has negligible effects in this study.

show abstract

“…Since the pKa of the phosphorylated residues is around six [ 37 ], in reality it can fluctuate between

and

Section: Discussionmentioning

confidence: 99%

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

Rieloff

Skepö

2021

IJMS

View full text Add to dashboard Cite

show abstract

“…K d , crucial in drug discovery, quantifies the strength of interaction between a ligand and its target. Techniques like SPR and ITC may struggle to measure binding affinities for weak or transient complexes, limiting the assessment of potential drug candidates' efficacy and specificity [12,13]. In summary, traditional methods of acquiring structural and K d data face significant challenges, including financial constraints, time intensiveness, scalability limitations, and difficulties in capturing dynamic interactions.…”

Section: Of 11mentioning

confidence: 99%

In Silico Generation of Structural and Intermolecular Binding Affinity Data with Reasonable Accuracy: Expanding Horizons in Drug Discovery and Design

2024

Preprint

View full text Add to dashboard Cite

In the domain of drug discovery and design, the acquisition of precise structural and intermolecular Kd data for biological molecules is paramount. However, conventional methods for obtaining such data are often beset by challenges including high costs, time intensiveness, and inherent limitations in scalability and diversity. This article puts forward a high-throughput approach for in silico generation of structural and intermolecular binding affinity (Kd) data, which keeps exploring the uncharted territories of drug discovery & design by harnessing computational methodologies to synthetically generate diverse datasets. Through a meticulously designed workflow encompassing molecular structural modeling, structural biophysics-based calculations of intermolecular binding affinity (Kd), this innovative methodology transcends the constraints of traditional experimentation, offering a cost-effective, scalable, and efficient alternative. By simulating molecular interactions and binding interfaces and predicting binding affinities with reasonable accuracy, this approach not only expedites the drug development process but also enables the exploration of vast molecular space, thereby facilitating the discovery of novel therapeutics beyond conventional drug modality as a form factor. Moreover, the versatility of synthetic data extends beyond virtual screening and lead optimization, encompassing applications such as dataset augmentation, model validation, and benchmarking against experimental data. This article elucidates the conceptual underpinnings, methodological intricacies, validation strategies, and potential ramifications of in silico generated data, heralding a paradigm shift in drug discovery paradigms. By fostering synergy between computational and experimental research domains, this innovative approach promises to accelerate the pace of drug discovery, enhance the robustness of predictive models, and pave the way for transformative advancements in the entire pharmaceutical industry.

show abstract

“…[265][266][267] The same argument applies to the efficient use of polarizable force fields when dealing with PTM protonation state. 268,269 Aside from parameterization improvements, advances in structure prediction methodology raise the possibility of predicting covalently modified proteoform conformations. Software like DeepMind's AlphaFold, along with the Baker lab's RoseTTaFold, have now revolutionized protein structure prediction with their machine learning-based template-free methods that, in most cases, can rival experimental structure quality.…”

Section: Outlooks On Ptm Modeling and Simulationsmentioning

confidence: 99%

“…265–267 The same argument applies to the efficient use of polarizable force fields when dealing with PTM protonation state. 268,269…”

Section: Outlooks On Ptm Modeling and Simulationsmentioning

confidence: 99%

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Weigle

Feng

Shukla

2022

Phys. Chem. Chem. Phys.

View full text Add to dashboard Cite

show abstract

How the protonation state of a phosphorylated amino acid governs molecular recognition: insights from classical molecular dynamics simulations

Cited by 12 publications

References 41 publications

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins: A Force Field Comparison

In Silico Generation of Structural and Intermolecular Binding Affinity Data with Reasonable Accuracy: Expanding Horizons in Drug Discovery and Design

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Contact Info

Product

Resources

About