Dynamics of hydrogen bonds in the secondary structures of allosteric protein Avena Sativa phototropin 1

Ibrahim, Mayar Tarek; Trozzi, Francesco; Tao, Peng

doi:10.1016/j.csbj.2021.11.038

Cited by 13 publications

(15 citation statements)

References 47 publications

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“…Autoinhibition is a common inactivating switch mechanism in nature [80] , [81] , [82] , [83] , [84] , [85] . The principle is straightforward and since the inactivating segment is covalently linked, it is highly efficient.…”

Section: Resultsmentioning

confidence: 99%

Allosteric regulation of autoinhibition and activation of c-Abl

Liu

Zhang²,

Tsai³

et al. 2022

Computational and Structural Biotechnology Journal

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Section: Resultsmentioning

confidence: 99%

Allosteric regulation of autoinhibition and activation of c-Abl

Liu

Zhang²,

Tsai³

et al. 2022

Computational and Structural Biotechnology Journal

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“…To demonstrate the efficacy of the model, two examples that were not part of the training and validation sets are presented in Figure 3. These examples show the predicted allosteric sites of the light‐oxygen‐voltage domains of Phaeodactylum tricornutum Aureochrome 1a 39 and Avena Sativa phototropin 1 40 obtained using the LambdaMART model. The top 3 pockets are highlighted in red, orange, and yellow, respectivley, and with the corresponding predicted relevance scores.…”

Section: Resultsmentioning

confidence: 98%

PASSerRank: Prediction of allosteric sites with learning to rank

et al. 2023

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Allostery plays a crucial role in regulating protein activity, making it a highly sought‐after target in drug development. One of the major challenges in allosteric drug research is the identification of allosteric sites. In recent years, many computational models have been developed for accurate allosteric site prediction. Most of these models focus on designing a general rule that can be applied to pockets of proteins from various families. In this study, we present a new approach using the concept of Learning to Rank (LTR). The LTR model ranks pockets based on their relevance to allosteric sites, that is, how well a pocket meets the characteristics of known allosteric sites. After the training and validation on two datasets, the Allosteric Database (ASD) and CASBench, the LTR model was able to rank an allosteric pocket in the top three positions for 83.6% and 80.5% of test proteins, respectively. The model outperforms other common machine learning models with higher F1 scores (0.662 in ASD and 0.608 in CASBench) and Matthews correlation coefficients (0.645 in ASD and 0.589 in CASBench). The trained model is available on the PASSer platform (https://passer.smu.edu) to aid in drug discovery research.

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“…All four mutants were found to lack the hydrogen bond between Thr407 and Ala452 found in the WT. Thr407 wa identified to be essential in the unfolding mechanism of A’α helix 15 . This missing hydrogen bond i suggested to be the main reason of the high fluctuations observed in the N-terminal.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, extensive MD simulations were conducted on the selected mutations of As LOV2 to investigate its allosteric mechanisms with the focus on the role of Hβ sheet and Iβ sheet. Combining simulation analysis and Markov state model 15,16 , we identified some intriguing mutant behaviors potentially due the change of the hydrogen bond pattern in mutants.…”

Section: Introductionmentioning

confidence: 99%

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

Xiao,

Ibrahim,

Verkhivker

et al. 2023

Preprint

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Avena Sativa phototropin 1 Light-oxygen-voltage 2 domain (AsLOV2) is the model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change is initiated by the unfolding of the N-terminal helix in the dark state followed by the unfolding of the C-terminal helix. The light state is defined by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, β-sheets have been identified as crucial components for mediating allosteric signal transmission between the two termini. In this study, we combined microsecond all-atm molecular dynamics simulations and Markov state modeling of conformational states to quantify molecular basis of mutation-induced allostery in the AsLOV2 protein. Through a combination of computational investigations, we determine that the Hβ and Iβ strands are the most critical structural elements involved in the allosteric mechanism. To elucidate the role of these β-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive simulation analysis. The results highlighted the role of two hydrogen bond Asn482-Leu453 and Gln479-Val520 in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. The comprehensive atomistic-level analysis of the conformational landscapes revealed the critical functional role of β-sheet segments in the transmission of the allosteric signal upon the photoactivation of the light state.

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Dynamics of hydrogen bonds in the secondary structures of allosteric protein Avena Sativa phototropin 1

Abstract: Graphical abstract

Cited by 13 publications

References 47 publications

Allosteric regulation of autoinhibition and activation of c-Abl

Allosteric regulation of autoinhibition and activation of c-Abl

PASSerRank: Prediction of allosteric sites with learning to rank

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

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