Molecular dynamic modelling of the interaction of a synthetic zinc-finger miniprotein with DNA

Abstract

We report the modelling of the DNA complex of an artificial miniprotein composed of two zinc finger modules and an AT-hook linking peptide. The computational study provides for the first time a structural view of these types of complexes, dissecting interactions that are key to modulate their stability. The relevance of these interactions was validated experimentally. These results confirm the potential of this type of computational approach for studying peptide-DNA complexes and suggest that they could be very useful for the rational design of non-natural, DNA binding miniproteins.

Full text

rsc.li/rsc-chembio
rsc.li/rsc-chembio
ISSN 2633-0679
PAPER
Nosang V. Myung, Yong-Ho Choa et al.
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Volume 1
Number 1
January 2020
RSC
Chemical Biology
RSC
Chemical Biology
Accepted Manuscript
This is an Accepted Manuscript, which has been through the
Royal Society of Chemistry peer review process and has been accepted
for publication.
Accepted Manuscripts are published online shortly after acceptance,
before technical editing, formatting and proof reading. Using this free
service, authors can make their results available to the community, in
citable form, before we publish the edited article. We will replace this
Accepted Manuscript with the edited and formatted Advance Article as
soon as it is available.
You can find more information about Accepted Manuscripts in the
Information for Authors.
Please note that technical editing may introduce minor changes to the
text and/or graphics, which may alter content. The journal’s standard
Terms & Conditions and the Ethical guidelines still apply. In no event
shall the Royal Society of Chemistry be held responsible for any errors
or omissions in this Accepted Manuscript or any consequences arising
from the use of any information it contains.
View Article Online
View Journal
This article can be cited before page numbers have been issued, to do this please use: J. Rodriguez, F.
Battistini, S. Learte Aymamí, M. Orozco and J. L. Mascareñas, RSC Chem. Biol., 2023, DOI:
10.1039/D3CB00053B.

ARTICLE
Please do not adjust margins
Please do not adjust margins
Received 00th January 20xx,
Accepted 00th January 20xx
DOI: 10.1039/x0xx00000x
Molecular dynamic modelling of the interaction of a synthetic
zinc-finger miniprotein with DNA
Jessica Rodriguez,*a,b Federica Battistini,b,c Soraya Learte-Aymamí,a Modesto Orozco*b,c and José L.
Mascareñas*a
We report the modelling of the DNA complex of an artificial miniprotein composed of two zinc finger modules and an
AT-hook linking peptide. The computational study provides for the first time a structural view of this type of complexes,
dissecting interactions that are key to modulate their stability. The relevance of these interactions was validated
experimentally. These results confirm the potential of this type of computational approaches for studying peptide-DNA
complexes and suggest that they could be very useful for the rational design of non-natural, DNA binding miniproteins.
Introduction
The regulation of eukaryote protein expression is mainly
achieved at the level of transcription, and it is ultimately
dependent on the interaction of specialized proteins called
transcription factors (TFs) with specific DNA sequences.1 TFs are
classified into families in function of the structure of their DNA
binding domain. Zinc fingers (ZFs) constitute the largest family
of eukaryotic TFs, and play a key role in regulating the
expression of numerous genes that are essential for different
cellular processes.2 These proteins are composed of several
repeats of zinc-containing modules, usually made of two
β-sheets and one α-helix, that cooperate to bind specific DNA
sequences.3 In the more classical Cys2-His2 ZF proteins, the zinc
atom is coordinated by two cysteines in one chain and two
histidines in the other, coordination that is key to stabilize the
3D folding.
The binding to the DNA is mainly carried out by insertion
of the
α-helix into the major groove, where specific amino acids
establish well-defined contacts with the edge of the bases.
Noteworthy, the DNA affinity of individual zinc-finger modules
is low, and therefore the binding requires cooperative tandem
repeats. The modular nature of these proteins has inspired the
genetic engineering of a broad variety of non-natural polydactyl
zinc-finger derivatives that bind designed DNA sequences by
programmed interactions through the major groove thread
.
4
,
5
The zinc finger motive has also inspired the design of
synthetic miniproteins capable of interacting with specific DNA
sequences.6 In particular, our group has demonstrated that an
appropriate conjugation of the zinc finger of the Drosophila
transcription factor GAGA
7
with
minor groove binding units allows
for high affinity DNA binding.8 Note that this zinc finger by itself (as
isolated module) fails to interact with its target site
(GAGAG),
something that Nature has solved in the GAGA factor by
including two highly basic protein regions at the N-terminus,
BR1 and BR2.
Our designed conjugates interact with high affinity
and selectivity to a DNA sequence bearing the peptide and the minor
groove recognition regions in adjacent sites.8
Particularly appealing in our designs is the use of an AT-hook type
of peptide as minor groove anchor, because its peptidic nature
facilitates the synthetic access to the conjugates.9,10,11 Specifically,
we have reported the synthesis of three different non-natural
DNA-binding miniproteins, i.e., Hk-gaga, gaga-Hk and gaga-Hk-gaga
(Figure 1),10 made by one AT-hook motif tethered to the ZF domain
of the GAGA TF (Ser28 to Phe58 in the reference pdb structure).12
These newly designed miniproteins, with a fully peptide backbone,
bind, with high affinity (two digit nanomolar) and excellent
selectivity, composite DNA sequences of up to 14 base pairs.10
Whereas these results confirm the viability of making synthetic
DNA binding agents, there is a lack of structural information on the
DNA complexes, and all attempts to obtain crystallographic data
have so far been unsuccessful. In this context, molecular modelling,
and especially molecular dynamic (MD) simulations, may not only
provide an overview of the interaction, but also unveil relevant
information on the factors controlling the recognition.13
Molecular dynamic studies on protein-nucleic acid complexes,14
and particularly those entailing zinc finger modules,15 are scarce, and
restricted to a few natural systems. For example, the group of Case
used MDs in combination with NMR to study the hydration of the
DNA complex of transcription factor IIIA,16 while Gago performed a
MD simulation on the DNA binding of TF Sp1. These studies helped
to decode the bases of DNA-binding selectivity and gave results that
were in consonance with previously reported experimental data.17
MDs of ZF-nucleic acid complexes have also been investigated for the
TATA18, CreA19, WRKY20, ZAP21, NCp722 and GR23 proteins, among
a.Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares
(CIQUS), and Departamento de Química Orgánica, Universidade de Santiago de
Compostela Rúa Jenaro de la Fuente s/n, 15782, Santiago de Compostela, Spain.
b.Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of
Science and Technology (BIST), Baldiri Reixac 10-12, 08028 Barcelona, Spain.
c. Department of Biochemistry and Molecular Biology. University of Barcelona, 08028
Barcelona, Spain.
† Electronic Supplementary Information (ESI) available. See
DOI: 10.1039/x0xx00000x
Page 1 of 8 RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

ARTICLE Journal Name
2 | J. Name., 2012, 00 , 1-3 This journal is © The Royal Society of Chemistry 20xx
Please do not adjust margins
Please do not adjust margins
others. To our knowledge, MD simulations on DNA complexes
involving non-natural protein binders have not been described.
Figure 1. Top: Schematic representation of the major-minor-major groove interaction of
the miniprotein gaga-Hk-gaga. The sequence of the peptidic linkers tethering the ZF
domains of the GAGA TF and the AT-hook connector are highlighted in red. Bottom:
Schematic illustration of the sequences of the designed miniproteins. Note that in the
C-terminal GAGA fragment (in orange), the N-terminal Ser residue was removed.9
Herein, we report a MD study of a complex between the
synthetic miniprotein gaga-Hk-gaga and its target DNA site:
CTCTC-AATT-GAGAG. The calculations revealed interactions
in
the DNA major groove
that are key for the formation of a stable
complex.24 The relevance of these interactions was
experimentally confirmed using DNA-binding assays. Our
results not only demonstrate the potential of the modelling to
obtain a structural picture of the complex and dissect relevant
contacts, but also pave the way for a future rational design of
new miniproteins targeting selective DNA sequences.
Results and discussion
Structural model for the binding of gaga-Hk-gaga to its
consensus DNA sequence
Using as starting point the structural data available for the DNA
interaction of the GAGA ZF,12 and one AT-hook of
HMG-I(Y)25 we assembled a hypothetical model for the DNA
complex of gaga-Hk-gaga, with two ZF GAGA fragments bound
to adjacent major grooves, and linked through an AT-hook
anchor, inserted into the central minor groove. The Gly/Lys
linkers were built and connected to the peptidic fragments
using PyMOL. Once assembled, we carried out a MD simulation
extending up to 500 ns using atomistic representation and
explicit solvent (see the experimental section). The resulting
MD ensemble of structures shows that there is little structural
variability over the simulation time (Figure 2a). The final frame
of the MD simulation, after ensuring that the structure has
converged according to the RMSD values (Figure S5), was
chosen as a representative snapshot of the trajectory.
Inspection of this frame reveals that the ZF modules of gaga-Hk-
gaga bind, as expected, the major grooves of the target DNA
and recognize the first three GAG bases in a similar way to that
observed in the solution structure of the native GAGA TF/DNA
complex (Figure 2b).12 Whereas in the native GAGA protein the
formation of a stable DNA complex requires the two basic
regions in addition to the zinc finger module, in the designed
conjugate gaga-Hk-gaga the additional contacts required for
the binding are provided by the AT-hook, which inserts into the
central minor groove facilitating the docking of both ZFs. We
have previously shown that only sequences with a central A/T
region are appropriately recognized by the miniproteins.10
Of note, the polyglycine units linking the ZFs and the
AT-hook do not exhibit interactions with the DNA,26 but provide
the right connection to span the required distances between
the binding modules. The design of the spacers is key to obtain
efficient DNA-binding conjugates: the spacer must not only
span the required distance between the DNA-binding domains,
but also be flexible enough to allow the adaptation of the
modules to their respective DNA binding sites.6g-n
109 1112
Arg64
G13
Asn61
A14
Arg60
R60 N61 R64
G15
b)
c) d)
a)
5’ – G T A C T C T C A A T T G A G A GT A C – 3’
13 14 15 16 17
Page 2 of 8RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

Journal Name ARTICLE
This journal is © The Royal Society of Chemistry 20xx J. Name., 2013, 00, 1-3 | 3
Please do not adjust margins
Please do not adjust margins
Figure 2. a) Top and lateral views of the superimposition of snapshots from the MD
simulation of miniprotein gaga-Hk-gaga bound to the target DNA sequence, going from
0 to 500 ns every 100 ns of simulation (colour scale from red to blue, being white in the
middle of the simulation). b) Snapshot from the final frame of the 500 ns MD simulation
of miniprotein gaga-Hk-gaga bound to the target DNA sequence: CTCTC-AATT-GAGAG.
c) and d) Key hydrogen bonding interactions in the major groove.
The modelled structural information shows that the native
interactions of the side chains of the ZF of GAGA with the DNA
bases G13, A14 and G15, are conserved in both ZFs of the
synthetic conjugate. In the simulation of the DNA complex of
gaga-Hk-gaga, Arg64, Asn61 and Arg60 interact with the
nucleobases G13, A14 and G15, respectively (Figure 2c, d and
Table S1). The guanidium group of Arg64 recognizes the N7 and
O6 atoms of G13 (hydrogen bonds observed in >38% of the
simulation time), the carboxyamide of Asn61 interacts with the
N7 and NH2 atoms of A14 (hydrogen bonds observed in >39% of
the simulation time) and the guanidinium group of Arg60 with
the O6 and N7 atoms of G15 (hydrogen bonds observed in 94%
and 30% of the simulation time, respectively). Moreover, most
of the supplementary electrostatic interactions of the ZF with
the sugar phosphate backbone present in the DNA complex of
the original GAGA TF are maintained.12 Importantly, we found
35 water molecules at the protein-DNA interface, which
establish bridged hydrogen bonds with both the nucleobases
and the amino acids (see the ESI, Figure S4), playing an
important role in the stabilization of the protein-DNA complex.
The AT-hook module is essential for the formation of the
complex, as it interacts with the DNA through its central
Arg-Gly-Arg core deeply inserted into the minor groove and
adopting an extended conformation, resembling that in the
native AT-hook/DNA complex (Figure 3).25 It establishes key
interactions (Figure 3b and Table S1): the guanidium group of
Arg78 interacts with the O2 atom of T12 (hydrogen bonds
observed in 52% of the simulation time), the backbone amine
group of Gly79 recognizes the O2 atom of T11 (hydrogen bonds
observed in 27% of the simulation time) and the guanidium
group of Arg80 forms a hydrogen bond with the N3 atom of A9
(hydrogen bonds observed in 17% of the simulation time).
Overall, the DNA recognition entails well balanced
supramolecular contacts of the zinc finger modules with the
GAG sequences, and of the AT-hook peptide with the edge of
the bases in the minor groove. All these structural information
obtained by modelling the ternary complex is also valid for the
bivalent DNA binders gaga-Hk and Hk-gaga (confirmed from
MD simulation of the binary complex Hk-gaga, see Figure S3 in
the ESI).
R
R
G
a) b)
Arg78
T12
Gly79
T11
Arg80
A9
Figure 3. a) Superposition of a snapshot for the minor groove interaction extracted
from the final frame of the 1000 ns MD simulation of gaga-Hk-gaga (tan) with the
structure of an AT-hook complex (PDB ID 2EZF, light blue). b) Interactions of the
AT-hook moiety of the miniprotein gaga-Hk-gaga with its target DNA. Key
hydrogen bonds are shown as yellow dashed lines.
Mutational studies
With the model at hand, we wondered whether it could be used
to assess the relevance of individual interactions occurring in
the major groove of the miniprotein/DNA complex. Thus, we
carried out MD simulations with oligonucleotides mutated
either at positions 13, 14 and 15 (see Figure 2 for the
numbering).
G13C mutation
Having in mind the distribution of hydrogen bond donors and
acceptors in the major groove of the DNA (Figure 4a), we
hypothesized that mutation of G13 by a cytosine, should
prevent the formation of hydrogen bonds with the guanidium
group of Arg64, and thus might have a considerable effect in the
formation of the complex. Indeed, MD simulations showed that
this mutation results in loss of the interaction with Arg64
(hydrogen bonds observed in <1% of the simulation time), and
a subsequent displacement of the ZF helix out from the groove
(Figure 4b,c).27 This displacement also conveys the loss of the
Asn61/A14 contact (hydrogen bonds observed in <1% of the
simulation time, see also Figure 4d,e). The only conserved
contacts are with Arg60 (hydrogen bonds observed in >50% of
the simulation time, see Table S2).
Overall, the model suggests a cancellation in the DNA
binding of this zinc finger module. We therefore envisioned that
this mutation should have a drastic effect in the DNA interaction
of the bivalent peptide gaga-Hk (the trivalent gaga-Hk-gaga
might still keep a substantial affinity due to interaction of the
second ZF fragment).10 We therefore assessed the DNA binding
of gaga-Hk to the mutated sequence using non-denaturing
electrophoresis mobility shift assays (EMSA) in polyacrylamide
gels.28 As can be deduced from Figure 4f (lanes 1-4), we didn't
observe retarded bands when using the double stranded (ds)
oligonucleotide CAGAG containing a G to C mutation, which
contrasts with the clear shifted band formed when using the
dsDNA bearing the consensus target site (GAGAG, lane 6). It is
interesting to note that the native transcription factor GAGA is
quite tolerant to this (and other) mutations, likely because the
presence of the complementary basic regions (BR1 and BR2),
which make a significant contribution to the affinity.12 However,
in our synthetic constructs, the presence of a low affinity minor
groove binder cannot compensate the loss of binding upon
mutation of the GAG region.
Therefore, our synthetic bivalent miniproteins are fine-tuned to
bind their consensus DNA sites, and exhibit a great sensitivity to
single mutations, which is clearly beneficial in terms of
selectivity.
Page 3 of 8 RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

ARTICLE Journal Name
4 | J. Name., 2012, 00 , 1-3 This journal is © The Royal Society of Chemistry 20xx
Please do not adjust margins
Please do not adjust margins
R60 N61
R64
b)
d)
4321
f)
5 6
Arg64
C13
Asn61
A14
Arg60
G15
e)
a)
c)
Figure 4. a) A/T and G/C base pairing in DNA depicting the distribution of hydrogen
bond donors and acceptors. b) Lateral view of the superimposition of snapshots
from the MD simulation of gaga-Hk-gaga with a DNA containing the mutated DNA
CAGAG, going from 0 to 500 ns every 100 ns of simulation (colour scale from red
to blue, being white in the middle of the simulation). c) Superposition of snapshots
from the final frames of the MD simulations of gaga-Hk-gaga with the consensus
DNA (tan) and with a DNA containing the mutated DNA CAGAG (magenta). For
simplification, only the ZF bound to the mutated DNA region is shown in this and
the rest of the pictures. d) and e) Zoom of a snapshot from the final frame of the
MD simulation showing the interactions of the ZF domain with the mutated DNA
CAGAG. Key hydrogen bonds are shown as dashed lines. f) EMSA DNA binding
studies results for binary conjugate gaga-Hk. Lanes 1-4: [gaga-Hk] = 0, 300, 700,
1000 nM, and 75 nM of dsDNA CAGAG. Lanes 5-6: [gaga-Hk] = 0, 1000 nM, and 75
nM GAGAG. Oligonucleotide sequences (only one strand shown): CAGAG:
5´–CGCGTCATAATTCAGAGCGC–3´; GAGAG: 5´–CGCGTCATAATTGAGAGCGC– 3´.
A14C, A14G and G15A mutations
We next explored the impact of mutations at positions 14 and
15 of the target DNA. The mutation of A14 by any other
nucleobase (C, T, G) may remove one of the hydrogen bonds
between the carboxyamide of Asn61 and the DNA. Similarly,
mutation of G15 by adenine (A) should abolish one of the
hydrogen bonds with the guanidium group of Arg60.
MD simulations of A14C or A14G mutations indeed
display the loss of the bidentate DNA interaction with Asn61,
but there is not displacement of the ZF helix from the major
groove during the simulation time (Figure 5a,c,d and Figure
S6a,b). In Tables S3 and S4, it is shown that the frequency of
hydrogen bonds with Asn61 is reduced to 17-19% of the
simulation time, while it was present in >39% with the target
DNA sequence. Moreover, it can be observed that the
frequency of hydrogen bonds with Arg64 and Arg60 is also
significantly reduced.
On the other hand, MD simulation of the complex with a
G15A mutation showed loss of the interaction with Arg60,
together with a huge displacement of the ZF helix out from the
major groove (Figure 5b,e,f), which triggered the loss of the
Asn61/A14 and Arg64/G13 interactions (Figure 5f). Indeed, no
significant interaction was found in the hydrogen bond analysis
of this simulation (Table S5).
Page 4 of 8RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

Journal Name ARTICLE
This journal is © The Royal Society of Chemistry 20xx J. Name., 2013, 00, 1-3 | 5
Please do not adjust margins
Please do not adjust margins
a)
R60
N61
R64
c)
R60
N61
R64
e)
R60
N61
R64
b)
d)
Arg64
G13
Asn61
C14
Arg60
G15
Arg64
G13
Asn61
G14
Arg60
G15
Arg64
A13
Asn61
A14
Arg60
G15
f)
Figure 5. a) Superposition of snapshots from the final frames of the MD
simulations of gaga-Hk-gaga with the consensus DNA (tan), and with DNAs with
mutated sequences GCGAG (green) and GGGAG (red). For simplification, only the
ZF bound to the mutated DNA region is shown in this and the rest of the pictures.
b) Superposition of snapshots from the final frames of the MD simulations with
the consensus DNA (tan) and with the mutated DNA GAAAG (yellow). c) Zoom of
a snapshot from the final frame of the MD simulation showing the interactions of
the ZF domain with the mutated sequence GCGAG. d) Zoom of a snapshot from
the final frame of the MD simulation showing the interactions of the ZF domain
with the mutated DNA GGGAG. e) Lateral view of the superimposition of
snapshots from the MD simulation of gaga-Hk-gaga with a DNA containing the
mutated DNA GAAAG, going from 0 to 500 ns every 100 ns of simulation (colour
scale from red to blue, being white in the middle of the simulation). f) Zoom of a
snapshot from the final frame of the MD simulation showing the loss of interaction
of the ZF domain with the mutated sequence GAAAG. Key hydrogen bonds are
shown as dashed lines.
In agreement with MD simulations, EMSA analysis revealed
that gaga-Hk does not elicit retarded bands when incubated
with ds-oligonucleotides containing the mutated sequences
GCGAG, GGGAG or GAAAG (Figure 6). These results confirm
that perturbing the interaction with either Asn61 or Arg60
results in a drastic effect on the DNA binding. Again, in the case
of the native TF GAGA motif, this effect is less pronounced, and
it exhibits a considerable interaction with DNAs featuring the
mutations GCGAG / GGGAG in the major groove.12 This further
highlights the advantage of our synthetic constructs in terms of
selectivity.
Figure 6. EMSA DNA binding studies results for binary conjugate gaga-Hk. Lanes
1-4: [gaga-Hk] = 0, 300, 700, 1000 nM, and 75 nM of dsDNA GCGAG. Lanes 5-8:
[gaga-Hk] = 0, 300, 700, 1000 nM, and 75 nM of dsDNA GGGAG. Lanes 9-12:
[gaga-Hk] = 0, 300, 700, 1000 nM, and 75 nM of dsDNA GAAAG. Oligonucleotide
sequences (only one strand shown): GCGAG: 5´–CGCGTCATAATTGCGAGCGC–3´;
GGGAG: 5´–CGCGTCATAATTGGGAGCGC–3´; GAAAG: 5´–CGCGTCATAATTGAAAG
CGC–3´.
Taken together, these results demonstrate that single base DNA
mutations can largely affect the DNA binding of our bivalent
conjugates and inform about the relevance of specific hydrogen
bonding interactions established by the zinc-finger unit.
Mutations in the synthetic miniprotein
After these studies, based on single base DNA mutations, we
also made an initial assessment of mutations in the peptide. We
questioned whether changing Asn61 (with a side chain
exhibiting one hydrogen-bond donor and one hydrogen-bond
acceptor) by Arg (with a side chain featuring a bidentate
hydrogen-bond donor), the resulting peptides could bind a site
with a guanine instead of adenine (sequence: 5’-GGGAG-3’), as
arginine might establish a bidentate interaction between its
guanidium group and the N7 and O6 atoms of G. MD simulations
with a mutated miniprotein gaga-Hk-gaga(N61R) bound to a
ds-oligonucleotide containing the designed target sequence
showed that, while Arg61 is able to bind G14 (Figure 7d and
Table S6, hydrogen bonds observed in >22% of the simulation
time) the higher length of Arg compared to Asn promotes a
displacement of the helix, which abolish the Arg64/G13
interaction (no significant interaction was found in the
hydrogen bond analysis), and very likely the overall DNA binding
(Figure 7a,c,d). This effect was confirmed experimentally, with
Page 5 of 8 RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

ARTICLE Journal Name
6 | J. Name., 2012, 00 , 1-3 This journal is © The Royal Society of Chemistry 20xx
Please do not adjust margins
Please do not adjust margins
the mutated synthetic peptide gaga-Hk(N61R), which was not
able to form stable complexes with the designed target
ds-oligonucleotide, even at concentrations of 1 μM (Figure 7b).
a) b)
R60
R61
R64
c)
4321 5
Arg64
G13
Arg61
G14
Arg60
G15
d)
Figure 7. a) Superposition of snapshots from the final frames of the MD
simulations of gaga-Hk-gaga with the consensus DNA (tan) and
gaga-Hk-gaga(N61R) with a DNA containing the GGGAG sequence (pink). For
simplification, only the ZF bound to the mutated DNA region is shown in this and
the rest of the pictures. b) EMSA DNA binding studies results for binary conjugate
gaga-Hk(N61R). Lanes 1-5: [gaga-Hk(N61R)] = 0, 300, 500, 700, 1000 nM, and 75
nM of dsDNA GGGAG. Oligonucleotide sequence (only one strand shown):
GGGAG: 5´–CGCGTCATAATTGGGAGCGC–3´. c) Lateral view of the
superimposition of snapshots from the MD simulation of gaga-Hk-gaga(N61R)
with a DNA containing the GGGAG sequence, going from 0 to 500 ns every 100 ns
of simulation (colour scale from red to blue, being white in the middle of the
simulation). d) Zoom of a snapshot from the final frame of the MD simulation of
gaga-Hk-gaga(N61R) with a DNA containing the GGGAG sequence showing the
interactions of the ZF domain of the gaga-Hk-gaga(N61R) miniprotein with the
GGGAG DNA sequence. Key hydrogen bonds are shown as dashed lines.
Conclusions
MD simulations allowed to obtain a detailed and realistic
structural model for the DNA interaction of the
miniprotein gaga-Hk-gaga, a synthetic, non-natural DNA binder
made of
two ZF
domains
linked to an AT-hook peptide
. The high
affinity and selective DNA binding of gaga-Hk-gaga, as well as of
the corresponding binary analogues (gaga-Hk and Hk-gaga)
derives from a cooperative major-minor groove recognition
provided by the ZF and the AT-Hook moieties. The ZF has a
strong preference for the sequence GAG, whereas the AT-hook
inserts in the minor groove of the adjacent AATT sequence. The
modelling allowed us to trace key recognition interactions,
which were validated experimentally. Overall, MD simulations
have been proven very useful to dissect the relevance of single
base-amino acid interactions in protein-DNA complexes. Future
work will seek to make use of MD simulations for the design of
new miniproteins capable of interacting to different type of
sequences.
Experimental
Peptide synthesis and purification
Peptides were synthesized using a Liberty Blue Lite automatic
microwave assisted peptide synthesizer from CEM Corporation,
following the manufacturer’s recommended procedures. Peptide
synthesis was performed using standard Fmoc solid-phase method
on a PAL–PEG–PS resin (0.19 mmol/g). Amino acids were coupled in
5-fold excess using DIC (N,N'-Diisopropylcarbodiimide) as activator,
Oxime as base, and DMF as solvent. Couplings were conducted for 4
min at 90 °C. Deprotection of the temporal Fmoc protecting group
was performed by treating the resin with 20% piperidine in DMF for
1 min at 75 °C. The cleavage/deprotection step was performed by
treatment of the resin-bound peptide for 1.5–2h with the following
cleavage cocktail: 940 μL TFA, 25 μL EDT, 25 μL H2O and 10 μL TIS (1
mL of cocktail / 40 mg resin). The crude products were purified by
RP−HPLC, 4 mL/min, gradient 10 to 50% B over 40 min. (A: H2O 0.1%
TFA, B: CH3CN 0.1% TFA) and identified as the desired peptides.
High-Performance Liquid Chromatography (HPLC) was performed
using an Agilent 1100 series Liquid Chromatograph Mass
Spectrometer system. Analytical HPLC was carried out using a Eclipse
XDB-C18 analytical column (4.6 x 150 mm, 5 μm), 1 mL/min, gradient
5 to 75% B over 30 min. Purification of the peptides was performed
on a semipreparative Phenomenex Luna–C18 (250 × 10 mm) reverse-
phase column.
EMSA experiments
EMSAs were performed with a BioRad Mini Protean gel system,
powered by an electrophoresis power supplies Power Pac Basic
model, maximum power 150 V, frequency 50-60 Hz at 140 V
(constant V). Binding reactions were performed over 30 min in 18
mM Tris-HCl buffer (pH 7.5), 90 mM KCl, 1.8 mM MgCl2, 0.2 mM
TCEP, 9% glycerol, 0.11 mg/mL BSA, 2.2% NP-40 and 0.02 mM of
ZnCl2. In the experiments we used 75 nM of the ds−DNAs and a total
incubation volume of 20 μL. After incubation for 30 min products
were resolved by PAGE using a 10% non-denaturing polyacrylamide
gel and 0.5× TBE buffer for 40 min at 20 ºC and analyzed by staining
with SyBrGold (Molecular Probes: 5 μL in 50 mL of 1× TBE) for 10 min
and visualized by fluorescence. 5× TBE buffer: 0.445M Tris, 0.445 M
Boric acid.
Molecular dynamics simulations
Starting structures were taken from the PDB database (1YUI, 2EZF),
and the initial systems to be studied (gaga-Hk-gaga and Hk-gaga
bound to their respective target DNAs) were assembled using
PyMOL. All systems were hydrated by truncated octahedral box of
TIP3P water molecules,29 with a minimum thickness of 10 Å around
Page 6 of 8RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

Journal Name ARTICLE
This journal is © The Royal Society of Chemistry 20xx J. Name., 2013, 00, 1-3 | 7
Please do not adjust margins
Please do not adjust margins
the solute. The system was neutralized with K+ cations and K+ and Cl-
were added till a physiological concentration of 150 mM. Systems
were optimized, thermalized and equilibrated using standard
procedures30 which involves energy minimizations of the solvent,
slow thermalization and a final re-equilibration for 10 ns, prior to the
500 ns production runs. Trajectories were collected in the
isothermal-isobaric ensemble (T = 298 K, P = 1 atm) using the
parmbsc1 force field for DNA,31 Amber99SBildn force field for
protein, Dang parameters for potassium and chlorine ions32 and ZAFF
parameters for Zn.33 Simulations were performed using AMBER 1834.
All trajectories were processed with the cpptraj module of the
AmberTools 18 package using default values (for hydrogen bonds a
distance cutoff of 3.0 Å and an angle cutoff of 135º). Root mean
square deviations (RMSDs) for each simulation were calculated using
heavy atoms for both the protein and the DNA. DNA base pair
parameters were derived using Curves+.35
Author Contributions
J.R. and F.B. performed the calculations and analyzed the data. S.L.
performed the EMSA assays. J.R., M.O. and J.L.M. guided the
research and wrote the manuscript.
Conflicts of interest
There are no conflicts to declare.
Acknowledgements
This work has received financial support from Spanish grants
(IJC2019-040358-I funded by MCIN/AEI/10.13039/501100011033 to
J.R., PID2019-108624RB-I00 funded by MCIN/AEI/10.13039/
501100011033 to J.L.M. and RTI2018-096704-B-100 and PID2020-
116620GB-I00 to M.O.), the Consellería de Cultura, Educación e
Ordenación Universitaria (Grants 2015-CP082, ED431C-2017/19 and
ED431G 2019/03: Centro Singular de Investigación de Galicia
accreditation 2019-2022 to J.L.M.) and the European Union
(European Regional Development Fund-ERDF corresponding to the
multiannual financial framework 2014-2020 to J.L.M.). This work was
also supported by the BioExcel-2. Centre of Excellence for
Computational Biomolecular Research” (823830, M.O.) and
the Instituto de Salud Carlos III–Instituto Nacional de Bioinformática
(ISCIII PT 17/0009/0007 co-funded by the Fondo Europeo de
Desarrollo Regional, M.O.). Funding was also provided by the
MINECO Severo Ochoa Award of Excellence from the Government of
Spain (awarded to IRB Barcelona). The authors acknowledge
RES-HPC (BCV-2022-3-0002 and BCV-2023-1-0004) for providing
generous computational resources.
Notes and references
1 C. W. Garvie and C. Wolberger, Mol. Cell, 2001, 8, 937.
2 a) C. O. Pabo, E. Peisach and R. A. Grant, Annu. Rev. Biochem.,
2001, 70, 313; b) S. Iuchi, N. Kudell, Zinc finger proteins: from
atomic contact to cellular function, ISBN: 0-306-48231-2, Landes
Biosciences: Georgetown, TX, 2004.
3 a) A. Klug, Annu. Rev. Biochem., 2010, 79, 213; b) J. Miller, A. D.
McLachlan, A. Klug, EMBO Journal, 1985, 4, 1609.
4 a) F. D. Urnov, E. J. Rebar, M. C. Holmes, H. S. Zhang and P. D.
Gregory, Nat Rev Genet., 2010, 11, 636; b) S. A. Wolfe, L.
Nekludova and C. O. Pabo, Annu. Rev. Biophys. Biomol. Struct.
2000, 29, 183.
5 G. A. Gersbach, T. Gaj, C. F. Barbas, Acc. Chem. Res., 2014, 47,
2309.
6 a) D. J. Segal, C. F. Barbas III, Curr. Opin. in Biotech., 2001, 12, 632;
b) D. Jantz, B. T. Amann, G. J. Gatto Jr., J. M. Berg, Chem. Rev.,
2004, 104, 789. For other DNA-binding peptides, see: c) Y. Ruiz
García, Y. V. Pabon-Martinez, C. I. E. Smith and A. Madder, Chem.
Commun., 2017, 53, 6653; d) Y. Ruiz García, A. Iyer, D. Van
Lysebetten, Y. Vladimir Pabon, B. Louage, M. Honcharenko, B. G.
De Geest, C. I. Smith, R. Strömberg and A. Madder, Chem.
Commun., 2015, 51, 17552; e) Y. Ruiz García, J. Zelenka, Y. V.
Pabon, A. Iyer, M. Buděšínský, T. Kraus, C. I. Smith and A. Madder,
Org. Biomol. Chem., 2015, 13, 5273; f) G. A. Woolley, A. S. I.
Jaikaran, M. Berezovski, J. P. Calarco, S. N. Krylov, O. S. Smart and
J. R. Kumita, Biochemistry, 2006, 45, 6075; g) J. Mosquera, J.
Rodríguez, M. E. Vázquez, J. L. Mascareñas, ChemBioChem, 2014,
15, 1092; h) J. Rodríguez, C. Perez-Gonzalez, M. Martínez-Calvo,
J. Mosquera, J. L. Mascareñas, RSC Advances, 2022, 12, 3500; i)
E. Oheix and A. F. A. Peacock, Chem. Eur. J., 2014, 20, 2829; j) G.
A. Bullen, J. H. Tucker and A. F. Peacock, Chem. Commun., 2015,
51, 8130; k) J. Mosquera, A. Jiménez-Balsa, V. I. Dodero, M. E.
Vázquez, J. L. Mascarenas, Nat. Commun. 2013, 4, 1874; l) J. B.
Blanco, M. E. Vázquez, J. Martinez-Costas, L. Castedo, J. L.
Mascareñas, Chem. Biol. 2003, 10, 713; m) A. Jiménez-Balsa, E.
Pazos, B. Martínez-Albardonedo, J. L. Mascareñas, M. E. Vázquez,
Angew. Chem. Int. Ed, 2012, 51, 8825; n) O. Vázquez, M. I.
Sánchez, J. Martinez-Costas, M. E. Vázquez, J. L. Mascarenas, Org.
Lett. 2010, 12, 216.
7 P. V. Pedone, R. Ghirlando, G. M. Clore, A. M. Gronenborn, G.
Felsenfeld and J. G. Omichinski, Proc. Natl. Acad. Sci. USA, 1996,
93, 2822.
8 a) O. Vázquez, M. E. Vázquez, J. B. Blanco, L. Castedo and J. L.
Mascareñas, Angew. Chem. Int. Ed, 2007, 46, 6886; b) J.
Rodríguez, J. Mosquera, O. Vázquez, M. E. Vázquez and J. L.
Mascareñas Chem. Commun. 2014, 50, 2258.
9 a) J. Rodríguez, J. Mosquera, J. R. Couceiro, M. E. Vázquez and J.
L. Mascareñas Chem. Sci., 2015, 6, 4767; b) J. Rodríguez, J.
Mosquera, R. García-Fandiño, M. E. Vázquez and J. L. Mascareñas
Chem. Sci., 2016, 7, 3298.
10 J. Rodríguez, S. Learte-Aymamí, J. Mosquera, G. Celaya, D.
Rodríguez, M. E. Vázquez and J. L. Mascareñas, Chem. Sci., 2018,
9, 4118
11 a) J. Rodríguez, J. Mosquera, M. E. Vázquez and J. L. Mascareñas
Chem. Eur. J., 2016, 22, 13474; b) S. Learte-Aymamí, J. Rodríguez,
M. E. Vázquez and J. L. Mascareñas, Chem. Eur. J., 2020, 26, 8875;
c) J. Rodríguez, J. Mosquera, S. Learte-Aymamí, M. E. Vázquez
and J. L. Mascareñas, Acc. Chem. Res., 2020, 53, 2286.
12 J. G. Omichinski, P. V. Pedone, G. Felsenfeld, A. M. Gronenborn
and G. M. Clore, Nat. Struct. Biol. 1997, 4, 122 (PDB ID: 1YUI).
13 For docking studies of Ru(II)-based DNA binding agents, see: a) D.
Bouzada, I. Salvado, G. Barka, G. Rama, J. Martinez-Costas, R.
Lorca, A. Somoza, M. Melle-Franco, M. E. Vazquez and M.
Vazquez Lopez, Chem. Commun., 2018, 54, 658; b) M. I. Sanchez,
G. Rama, R. Calo-Lapido, K. Ucar, P. Lincoln, M. Vazquez-Lopez,
M. Melle-Franco, J. L. Mascareñas and M. E. Vazquez, Chem. Sci.,
2019, 10, 8668. For MD simulations of metallopeptides, see: c) S.
Learte, P. Martin-Malpartida, L. Roldán-Martín, G. Sciortino, J. R.
Couceiro, J.-D- Maréchal, M. J. Macias, J. L. Mascareñas and M.
E. Vázquez, Commun. Chem., 2022, 5, 75.
14 a) D. L. Beveridge, S. B. Dixit, B. L. Kormos, A. M. Baranger, B.
Jayaram, Molecular Dynamics Simulations and Free Energy
Calculations on Protein-Nucleic Acid Complexes, in: J. Šponer, F.
Lankaš (eds), Computational Studies of RNA and DNA., 2006, vol
2. Springer, Dordrecht; b) S. Khalid, P. M. Rodger, Progress in
Page 7 of 8 RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B

ARTICLE Journal Name
8 | J. Name., 2012, 00 , 1-3 This journal is © The Royal Society of Chemistry 20xx
Please do not adjust margins
Please do not adjust margins
Reaction Kinetics and Mechanism, 2004, 29, 167; c) Z.
Pirkhezranian, M. Tahmoorespur, X. Daura, H. Monhemi, M. H.
Sekhavati, BMC Genomics, 2020, 21, 60; d) M. Garton, C.
Laughton, J. Mol. Biol., 2013, 425, 2910; e) L. Etheve, J. Martin
and R. Lavery, Nucleic Acids Res., 2016, 44, 1440.
15 a) G. Roxstrom, I. Velazquez, M. Paulino, O. Tapia, J. Phys. Chem.
B, 1998, 102, 1828; b) B. R. Morgan and F. Massi, Prot. Sci. 2010,
19, 1222; c) M. Y. Hamed, J. Comput. Aided Mol. Des. 2018, 32,
657.
16 a) V. Tsui, I. Radhakrishnan, P. E. Wright, D. A. Case, J. Mol. Biol.,
2000, 302, 1101. See also: b) A. Dreab, C. A. Bayse, J. Chem. Inf.
Model., 2022, 62, 903.
17 E. Marco, R. Garcia-Nieto and F. Gago, J. Mol. Biol., 2003, 328, 9.
18 B. Yang, Y. Zhu, Y. Wang, G. Chen, J. Comput. Chem., 2011, 32,
416.
19 M. Paulino, P. Esperón, M. Vega, C. Scazzocchio, O. Tapia, Journal
of Molecular Structure: THEOCHEM, 2002, 580, 225.
20 B. Pandey, A. Grover, P. Sharma, BMC Genomics, 2018, 19, 132.
21 S. Pal, A. Kumar, H. Vashisth, J. Chem. Inf. Model., 2023, 63, 1002.
22 W. Ren, D. Ji, X. Xu, PLoS ONE, 2018, 13, e0196662.
23 Y. Wang, N. Ma, Y. Wang, G. Chen, PLoS ONE, 2012, 7, e35159.
24 “Key interactions” are defined as the hydrogen bond interactions
which allow selective DNA binding of the miniprotein.
25 a) J. R. Huth, C. A. Bewley, M. S. Nissen, J. N. Evans, R. Reeves, A.
M. Gronenborn, G. M. Clore, Nat. Struct. Biol. 1997, 4, 657 (PDB
ID: 2EZF); b) E. Fonfría-Subirós, F. Acosta-Reyes, N. Saperas, J.
Pous, J. A. Subirana and J. L. Campos, PLoS One, 2012, 7, e37120
(PDB ID: 3UXW).
26 The lysine residue introduced in the linker connecting the
C-terminal side of the AT-hook peptide and the N-terminus of the
GAGA ZF doesn't establish electrostatic contacts with the
phosphate backbone, as initially hypothesized (see ref. 10).
27
Comparison of the roll parameter for the different MD
simulations carried out in this study suggests that mutations
barely affect the DNA morphology (see
Figure S7 in
the ESI).
28 a) L. M. Hellman, M. G. Fried, Nature Protocols 2007, 2, 1849; b)
D. Lane, P. Prentki, M. Chandler, Microbiol. Rev. 1992, 56, 509.
29 W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey and
M. L. Klein, J. Chem. Phys., 1983, 79, 926–935.
30 a) A. Pérez, F. J. Luque and M. Orozco, J. Am. Chem. Soc., 2007,
129, 14739–14745; b) P. D. Dans, L. Danilāne, I. Ivani, T. Dršata,
F. Lankaš, A. Hospital, J. Walther, R. I. Pujagut, F. Battistini, J. L.
Gelpí, R. Lavery, M. Orozco, Nucleic Acids Res., 2016, 44, 4052–
4066; c) P. D. Dans, J. Walther, H. Gómez, Curr. Opin. Struct. Biol.,
2016, 37, 29–45.
31 I. Ivani, P. D. Dans, A. Noy, A. Pérez, I. Faustino, A. Hospital, J.
Walther, P. Andrio, R. Goñi, A. Balaceanu, G. Portella, F.
Battistini, J. L. Gelpí, C. González, M. Vendruscolo, C. A.
Laughton, S. A. Harris, D. A. Case, M. Orozco, Nat. Methods,
2015, 13, 55–58.
32 a) L. X. Dang, J. Am. Chem. Soc., 1995, 117, 6954–6960; b) L. X.
Dang and P. A. Kollman, J. Am. Chem. Soc., 1990, 112, 5716–5720.
33 M. B. Peters, Y. Yang, B. Wang, L. Füsti-Molnár, M. N. Weaver and
K. M. Merz, Jr., J. Chem. Theory Comput., 2010, 6, 2935–2947.
34 D. A. Case, I. Y. Ben-Shalom, S. R. Brozell, D. S. Cerutti, T. E.
Cheatham III, V. W. D. Cruzeiro, T. A. Darden, R. E. Duke, D.
Ghoreishi, M. K. Gilson, H. Gohlke, A. W. Goetz, D. Greene, R.
Harris, N. Homeyer, Y. Huang, S. Izadi, A. Kovalenko, T. Kurtzman,
T. S. Lee, S. LeGrand, P. Li, C. Lin, J. Liu, T. Luchko, R. Luo, D. J.
Mermelstein, K. M. Merz, Y. Miao, G. Monard, C. Nguyen, H.
Nguyen, I. Omelyan, A. Onufriev, F. Pan, R. Qi, D. R. Roe, A.
Roitberg, C. Sagui, S. Schott-Verdugo, J. Shen, C. L. Simmerling, J.
Smith, R. Salomon-Ferrer, J. Swails, R. C. Walker, J. Wang, H. Wei,
R. M. Wolf, X. Wu, L. Xiao, D. M.York and P. A. Kollman AMBER
2018. Univ. California, San Fr. 2018.
35 R. Lavery, M. Moakher, J. H. Maddocks, D. Petkeviciute, K.
Zakrzewska, Nucleic Acids Res., 2009, 37, 5917–5929.
Page 8 of 8
RSC Chemical Biology
RSC Chemical Biology Accepted Manuscript
Open Access Article. Published on 19 May 2023. Downloaded on 5/20/2023 1:39:55 PM.
This article is licensed under a
Creative Commons Attribution-NonCommercial 3.0 Unported Licence.
View Article Online
DOI: 10.1039/D3CB00053B