Molecular dynamics simulations of human α-thrombin in different structural contexts: evidence for an aptamer-guided cooperation between the two exosites

Troisi, Romualdo; Balasco, Nicole; Vitagliano, Luigi; Sica, F.

doi:10.1080/07391102.2020.1746693

Cited by 11 publications

(9 citation statements)

References 67 publications

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“…Metal ions control the folding of G4 and are critical to the inhibitory activities of aptamers [ 70 ]. Interestingly, Troisi et al showed that the binding of a G4 aptamer at one exosite to thrombin increases the binding affinity of another aptamer to thrombin at a different exosite [ 71 ].…”

Section: Aptamer Affinity Prediction Through Structural Informatiomentioning

confidence: 99%

Artificial Intelligence in Aptamer–Target Binding Prediction

Chen

Zhang

et al. 2021

IJMS

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Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer–target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer–target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization.

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Section: Aptamer Affinity Prediction Through Structural Informatiomentioning

confidence: 99%

Artificial Intelligence in Aptamer–Target Binding Prediction

Chen

Zhang

et al. 2021

IJMS

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“…Recently, several studies on the simultaneous binding of two aptamers at both thrombin exosites were performed, pointing out an aptamer-guided inter-exosite cooperativity. 15 , 16 , 17 , 18 …”

Section: Introductionmentioning

confidence: 99%

A terminal functionalization strategy reveals unusual binding abilities of anti-thrombin anticoagulant aptamers

Troisi¹,

Riccardi²,

Carvasal³

et al. 2022

Molecular Therapy - Nucleic Acids

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“…On this basis, the authors suggested that conformational selection, i.e., generalized allostery, is the dominant mechanism of thrombin-aptamer binding. These findings have been corroborated and expanded on through extensive MD simulations of thrombin in different association states: ligand-free and binary/ternary complexes with the aptamers TBA (exosite I) and HD22_27mer (exosite II) [ 111 ]. These analyses clearly indicate that the HD22_27mer binding at the exosite II favors conformations of exosite I that are prone to TBA association ( Figure 10 ).…”

Section: Beyond a Static View Of Thrombin: Functional And Structural Evidence Of Exosite Communicationmentioning

confidence: 77%

“… Simultaneous binding of TBA or NU172 (exosite I) and HD22_27mer (exosite II) to thrombin. MD studies [ 111 , 112 ] have shown that the HD22_27mer binding at the exosite II favors conformations of exosite I that are prone to the TBA/NU172 association (on the top) and vice versa (on the bottom). The conformational variations of the exosite I region between free (black) and HD22_27mer-bound (dark green) thrombin is highlighted in the inset on the top.…”

Section: Figurementioning

confidence: 99%

“…This is somewhat surprising considering the remarkable results recently achieved in the definition of the long-distance and dynamic allosteric regulation of this protein [ 106 , 107 ], a topic in which the experimental and computational characterizations of thrombin complexes with aptamers, either single-stranded DNA or RNA molecules, which selectively bind to a specific target, have played a major role [ 108 , 109 , 110 , 111 , 112 ]. To fill this gap and to attain an up-to-date view of thrombin structural biology, we couple a survey of literature papers with an extensive analysis of PDB content.…”

Section: Introduction—overview Of Thrombin: a Multi-partner Serine Protease Involved In Blood Coagulationmentioning

confidence: 99%

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Exosite Binding in Thrombin: A Global Structural/Dynamic Overview of Complexes with Aptamers and Other Ligands

Troisi

Balasco

Autiero

et al. 2021

IJMS

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Thrombin is the key enzyme of the entire hemostatic process since it is able to exert both procoagulant and anticoagulant functions; therefore, it represents an attractive target for the developments of biomolecules with therapeutic potential. Thrombin can perform its many functional activities because of its ability to recognize a wide variety of substrates, inhibitors, and cofactors. These molecules frequently are bound to positively charged regions on the surface of protein called exosites. In this review, we carried out extensive analyses of the structural determinants of thrombin partnerships by surveying literature data as well as the structural content of the Protein Data Bank (PDB). In particular, we used the information collected on functional, natural, and synthetic molecular ligands to define the anatomy of the exosites and to quantify the interface area between thrombin and exosite ligands. In this framework, we reviewed in detail the specificity of thrombin binding to aptamers, a class of compounds with intriguing pharmaceutical properties. Although these compounds anchor to protein using conservative patterns on its surface, the present analysis highlights some interesting peculiarities. Moreover, the impact of thrombin binding aptamers in the elucidation of the cross-talk between the two distant exosites is illustrated. Collectively, the data and the work here reviewed may provide insights into the design of novel thrombin inhibitors.

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Molecular dynamics simulations of human α-thrombin in different structural contexts: evidence for an aptamer-guided cooperation between the two exosites

Cited by 11 publications

References 67 publications

Artificial Intelligence in Aptamer–Target Binding Prediction

Artificial Intelligence in Aptamer–Target Binding Prediction

A terminal functionalization strategy reveals unusual binding abilities of anti-thrombin anticoagulant aptamers

Exosite Binding in Thrombin: A Global Structural/Dynamic Overview of Complexes with Aptamers and Other Ligands

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