An<i>in silico</i>investigation of the binding modes and pathway of APTO-253 on c-KIT G-quadruplex DNA

Pal, Saikat; Paul, Sandip

doi:10.1039/d0cp05210h

Cited by 7 publications

(10 citation statements)

References 141 publications

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“…The potential of mean forces (PMFs) between two PHF6 peptides were calculated via an umbrella sampling (US) method. − The distance between the center of mass of backbone atoms of the two peptides is considered as the reaction coordinate for the PMF calculations. For this, first two PHF6 peptides were equilibrated for 500 ns in the absence and presence of ATP with TIP3P water following the above simulation protocols.…”

Section: Simulation Methodsmentioning

confidence: 99%

Deciphering the Role of ATP on PHF6 Aggregation

2022

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The aggregation of Tau protein, which are involved in Alzheimer’s disease, are associated with the self-assembly of the hexapeptide sequence, paired helical filament 6 (PHF6) from repeat 3 of Tau. In order to treat Alzheimer’s disease and other such tauopathies, one of the therapeutic strategies is to inhibit aggregation of Tau and its nucleating segments. Therefore, we have studied the effect of adenosine triphosphate (ATP) on the aggregation of PHF6. ATP has, interestingly, demonstrated its ability to inhibit and dissolve protein aggregates. Using classical molecular dynamics simulations, we observed that the hydrophobic core of PHF6 segment displays extended β-sheet conformation, which stabilizes PHF6 aggregates. However, the distribution of ATP around the vicinity of the peptides enables PHF6 to remain discrete and attain random coil conformers. The interpeptide interactions are substituted by PHF6–ATP interactions through hydrogen bonding and hydrophobic interactions (including π–π stacking). Furthermore, the adenosine moiety of ATP contributes more than the triphosphate chain toward PHF6–ATP interaction. Ultimately, this work establishes the inhibitory activity of ATP against Tau aggregation; hence, the therapeutic effect of ATP should be explored further in regard to the effective treatment of Alzheimer’s disease.

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Section: Simulation Methodsmentioning

confidence: 99%

Deciphering the Role of ATP on PHF6 Aggregation

2022

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“…The binding free energy of D-nl peptides with hIAPP is calculated using Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), , using the Python script, MMPBSA.py . The binding energy (Δ G bind ) between a receptor and a ligand is calculated as Δ E vac is the energy in vacuum (gas phase).…”

Section: Simulation Methodsmentioning

confidence: 99%

“…104 The cutoff distance between two aromatic rings considered to form π−π stacking is 6 Å along with an angle (formed by the normals of two aromatic rings of two interacting species) of 0°−30°or 150°−180°for parallel stacking, 30°−60°or 120°−150°for herringbone orientation, and 60°−120°for perpendicular or T-shaped stacking. 28 The binding free energy of D-nl peptides with hIAPP is calculated using Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), 105,106 using the Python script, MMPBSA.py. 107 The binding energy (ΔG bind ) between a receptor and a ligand is calculated as…”

Section: Simulation Methodsmentioning

confidence: 99%

hIAPP-Amyloid-Core Derived d-Peptide Prevents hIAPP Aggregation and Destabilizes Its Protofibrils

Roy

Paul

2022

J. Phys. Chem. B

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The aberrant misfolding of human islet amyloid polypeptide into cytotoxic amyloid aggregates is the hallmark of type II diabetes. In order to avert the formation of amyloid aggregation, a variety of peptides has been used as inhibitors. Recently, a peptide derived from the amyloidogenic core of hIAPP (hIAPP22–27) and consisting of all d-amino acid residues (D-nl), was found to efficiently prevent hIAPP fibril formation. To investigate the mechanism via which D-nl inhibits hIAPP aggregation, we have carried out all-atom molecular dynamics simulations, where we observe that the ordered β-sheet structure of hIAPP22–27 is completely destabilized when D-nl is incorporated in it. The formation of β-sheet structures by full-length hIAPP is also not favored in the presence of D-nl peptides, due to which hIAPP tends to attain a random loosely packed conformation. As a control, we also study the influence of hIAPP22–27 (L-nl) on the aggregation propensity of full length hIAPP. While L-nl supports the aggregation of hIAPP by stabilizing the β-sheet rich aggregates, D-nl interrupts hIAPP–hIAPP interactions via hydrogen bonding and hydrophobic interactions, thus obstructing the self-aggregation of hIAPP. Further, D-nl also partially dissolves the preformed hIAPP protofibrils. This work provides new insight into the activity of peptide inhibitors against amyloid aggregation at a molecular level and can be exploited to advance the field of diabetes treatment.

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“…They are more recently dominant Amber force fields to implement MD simulation for DNA, also for GQ. [35][36][37] Moreover, CHARMM force fields are likewise employed extensively, yet of which CHARMM27 has been validated to be far from satisfactory in MD simulation of GQ. 27 In 2014, Savelyev and MacKerell released a CHARMM polarizable force field termed Drude2013 for DNA based on the classical Drude oscillator model.…”

Section: Introductionmentioning

confidence: 99%

Extensive Evaluation of Force Fields for G-Quadruplexes

Li¹,

Zhu

2021

Preprint

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<p><a></a><a></a><a>G-Quadruplexes</a> (GQs), folded by guanine-rich <a></a><a></a><a>nucleic acid</a> <a></a><a></a><a></a><a>sequences</a>, involve in gene expression processes and closely associated with the formation of tumors. So far, GQ has drawn widespread attention for its notable application of serving as potential anti-cancer target. Recently, theoretical studies for GQs have achieved significant progress, most of which are inseparable from molecular dynamics (MD) simulation. As a necessary tool to explore <a></a><a></a><a>dynamics behavior</a> of molecules, MD simulations strictly depend on force field parameters, which is a sticking point to obtain accurate results. Currently, many force fields for nucleic acids have been developed, but none of them have been accepted widely for GQs. In this paper, we selected five popular force fields, which are parmbsc0, parmbsc1, OL15, Drude2017 and AMOEBANUC17, and conducted explicit-solvent MD simulations on two DNA GQs respectively. We evaluated these force fields from many aspects in detail. Meanwhile, we compared conformational energy using quantum chemistry calculations. With the comprehensive evaluation, Drude2017 achieved better description for GQs, which we suggest that using Drude2017 force field should <a></a><a></a><a>be taken into account</a> first when investigating GQs by MD simulation<a></a><a></a><a></a><a></a><a>.</a></p>

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Anin silicoinvestigation of the binding modes and pathway of APTO-253 on c-KIT G-quadruplex DNA

Abstract: Identification of the top, bottom and side loop binding modes of the APTO-253 ligand on c-KIT G-quadruplex DNA.

Cited by 7 publications

References 141 publications

Deciphering the Role of ATP on PHF6 Aggregation

Deciphering the Role of ATP on PHF6 Aggregation

hIAPP-Amyloid-Core Derived d-Peptide Prevents hIAPP Aggregation and Destabilizes Its Protofibrils

Extensive Evaluation of Force Fields for G-Quadruplexes

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