Abstract
The proteins of the Bcl-2 family play crucial roles in regulating apoptosis. It is
divided into pro-survival and pro-apoptotic proteins that determine cellular fate. In
particular, Bax is a crucial executor of apoptosis as its activation initiates the apop-
totic phenotype. Hence, targeting this protein represents an attractive therapeutic
approach, which can aid in regulating apoptotic signalling and potentially contribute
to the development of novel therapies against cancer and neurodegenerative diseases.
Here, we introduce a digital paradigm, which relies on rational design and computer
simulations to develop and validate peptide-based agents that bind to Bax, thereby
inhibiting its apoptotic properties. The peptides are rationally designed and optimized
to bind to Bax starting from the crystal structures of affimers in complex with Bcl-2
proteins. Next, molecular dynamics simulations (MD) are employed to probe the sta-
bility of the Bax-peptide complexes and to estimate the binding free energies. The
1
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Results
show that the designed peptides bind with high affinity to Bax. Two of the
designed peptides bind in the canonical hydrophobic groove (BH1 domain) of Bax and
one peptide binds to the outside of the BH3 domain ( α2-helix). Notably, the peptides
restrict the flexibility of the α1-α2 loop, modulating the bottom trigger site associated
with toxicity. All in all, the results highlight the potential of these peptides as valuable
tools for further exploration in modulating apoptotic pathways and set the structural
foundation for a machine learning powered engine for peptide design.
2
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Introduction
Programmed cell death or apoptosis is a tightly regulated process in multicellular organisms.1
Dysregulation of this mechanism can lead to several diseases, including cancer and possi-
bly neurodegenerative disorders such as Parkinson’s disease. 2,3 In the healthy cell, the B-cell
lymphoma 2 (Bcl-2) protein family maintains the homeostasis of the mitochondrial apoptotic
pathway through complex interactions,4,5 while also regulating mitochondrial dynamics, the
endoplasmatic reticulum, calcium storage and autophagy. 6 The Bcl-2 family consists out of
26 currently known members that are classified into pro-survival (or anti-apoptotic) Bcl-2
proteins, signalling pro-apoptotic members (or BH3-only proteins) and executor proteins. 7
The pro-survival proteins inhibit cell death by binding to the pro-apoptotic Bcl-2 proteins
and vice-versa. In response to cellular stress BH3-only proteins are activated which in turn
activate the executor proteins. The executor proteins transfer from the cytosol to the mito-
chondrial outer membrane where they accumulate, oligomerize, and facilitate mitochondrial
outer membrane permeabilization releasing cytochrome c and other factors. 8,9 In dopamine
neurons Mcl-1 is a critical Bcl-2 pro-survival factor as its chemical inhibition has been shown
to activate the pro-apoptotic protein Bax, caspases and result in neuronal cell death. 3 As
the loss of dopamine neurons is a hallmark of Parkinson’s disease Mcl-1 function may be
related to disease onset and possibly provide a therapeutic target. 3,10
The Bcl-2-associated X protein (Bax) is a proapoptotic Bcl-2 family protein, which
shares structural and sequence similarities with other Bcl-2 family proteins, such as the
anti-apoptotic Mcl-1. 11 Bax consists of nine α-helices, which are structured around a hy-
drophobic core composed of helices α2-α5 and has a globular structure (Fig. 1 - left panel).
In its inactive form, the trans membrane α9-helix is folded into the hydrophobic groove. In
the active state, the helix is inserted into the mitochondrial membrane. It has been proposed
that the α-helices of the BH3 domains of Bim (BH3-only protein) can transiently bind to
an activator site near the N-terminus (α 1/α6) of Bax, thereby causing its activation. 12 This
interaction displaces the α9-helix from the hydrophobic groove and initiates mitochondrial
3
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 1: Peptide development strategy. Bax protein in its inactive state (PDB ID:
1F16 11). Here, the BH1 domain is coloured in purple, BH2 domain in orange, BH3 domain
in cyan and the α9-helix in red (left panel). The peptides are rationally designed from
available 3D structures of protein complexes. Briefly, the residues that interact with the
protein are grafted from an affimer. The terminal residues are then cyclized via head-to-
tail cyclization and the complexes are subjected to molecular dynamics simulations. The
peptides that do not stably attached to Bax are optimized via single point mutations. If the
complex is stable, the binding affinities of the peptides to Bax are determined and the best
candidates are advanced into experimental testing.
outer membrane integration. The opening of the hydrophobic groove provides the possibil-
ity of interaction by the activator BH3 domains, further inducing conformational changes
to Bax where unfolding of the α2 helix occurs followed by the dissociation of both α1 and
the α6-α8 latch, and forming homodimers with neighbouring molecules by inserting the ev-
erted BH3 domain into their hydrophobic groove. 13,14 Another activation binding site was
reported at the proximal α1-α2 loop in mitochondrial Bax triggered by generated monoclonal
antibodies, opening up new possibilities for activation of Bax besides the use of BH3-only
proteins. 15 The vMIA protein (viral mitochondria localized inhibitor of apoptosis) binds Bax
at the α3-α4 and α5-α6 hairpins and was shown to have inhibitory effects. 16 Adjacent to this
binding site is the Bcl-2 (pro-survival protein) BH4 domain binding domain, consisting of
residues located on α1, the α1-α2 loop, the α3-α4 and α5-α6 hairpins, 17 which contribute
to the inhibition of Bax mediated apoptosis by restricting conformational changes. Small
molecule binding at the same site allosterically activates Bax. 18
Cyclic peptides are rapidly evolving as therapeutics and are emerging as powerful in-
4
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
hibitors in the drug development field. 19,20 Cyclic peptides are developed to combine con-
formational rigidity and solubility to enable binding to undruggable interfaces with high
affinity.21 Cyclic peptides have proven to be excellent candidates for cancer therapy, 22 organ
transplantation23 and inhibition of amyloid aggregation. 24,25 Their size and functional prop-
erties ensure that the contact area is large enough to provide high selectivity, their ability to
form salt-bridges and hydrogen bonds can lead to strong binding affinities, 26 and cyclization
increases their proteolytic stability.27 Engineering new peptides with tailored properties and
high affinities towards a desired targets is a non-trivial, resource-demanding and challenging
task. Experimentally, phage display or mRNA display allow the generation of large libraries
of peptides with target specificity.28 These libraries can produce a vast array of peptides, but
the chemical synthesis and the numerous experimental trials require significant resources.
Digital design and simulations are complementary tools that help to overcome some of
these difficulties. For instance, recent advances with digital tools like RosettaFold 29 and
AlphaFold230,31 can help with the determination of three-dimensional (3D) high resolution
structures of protein-peptide complexes. These conformations can then be used as starting
structures for molecular dynamics simulations to probe stability and dynamics, which can
then be leveraged to design better binders potentially using machine learning techniques
prior to experimental testing. 19 The advantages are three-fold. First, the simulations have
atomistic resolution and can provide information on the dynamics of the complex and the
isolated peptides, which exceed experimental resolution. 32 Second, the simulations allow the
exploration of a vast parameter space, which can help in the optimization of the designed
peptides. Third, this step reduces the number of experimental trials to be carried out and
increases the number of potent binders that can be generated and designed.
Recently, we proposed a recipe for generating a digital twin that would rely on information
from computational and experimental findings to simulate the effect of a cyclic peptide-
based drug on amyloidogenic targets.19 This digital twin would therefore require the efficient
incorporation of data from different sources, including binding constants, conformations,
5
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
specificity etc., to enhance the design and optimization of future peptide-based drugs. Here,
we take the first step towards building this digital twin and we use Bax as a model system.
Hence, we introduce a novel strategy to design cyclic peptide-based binders that can compete
with Mcl-1 for binding to Bax, thereby freeing up Mcl-1 and enhancing cellular resilience. 6,11
For this, we introduce a novel digital strategy that relies on rational design and molecular
dynamics simulations to develop and validate the new binders in silico prior to experimental
validation (Fig. 1). First, we rationally design cyclic peptides starting from known three
dimensional structures of BCL-2 family members in complex with non-antibody scaffold
proteins. Second, we optimize the peptide sequences via single point mutations to enhance
binding to the target. Third, we probe their structural stability and estimate their binding
free energies to Bax by using (enhanced sampling) molecular dynamics simulations. The
Results
reveal the mechanisms of interaction between three optimized cyclic peptides and
Bax and characterize their binding to the target. Furthermore, the calculated binding free
energies show that the peptides favorably bind to Bax. This aids in understanding the
mechanisms behind cyclic peptide-Bax stability and provides the starting information for
building a digital twin tailored for cyclic peptide design.
Theory and Methods
System preparation
The aim of the present study is to develop novel peptide-based ligands that compete against
MCL-1 against Bax binding. For this, the 15-166 segment of the pro-apoptotic protein Bax
was extracted from solution NMR (PDB: 1F16 11), Fig. 1 - left panel. To reduce compu-
tational cost, the disordered N-terminal residues 1-14 were removed. Additionally, residues
167-192, forming the α9-helix that mediates the formation and bioactivity of heterodimers,
were removed to simulate Bax in its active state. For the rational design of the cyclic pep-
tides, the X-ray diffration structures of MCL-1 and BCL-xL in complex with affimers were
6
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
used as scaffold (PDB IDs: 6STJ and 6HJL, 33 respectively).
Rational design of cyclic peptides
Each system was prepared by aligning the complexes of MCL-1 or BCL-xL and affimers
with the homologous Bax structure. The peptides were defined starting from the interfacial
residues for the affimers, independently. In particular, the residues located at the epitopes
and the amino acids in the loops of the affimer sequences that point towards the proteins and
contribute to the binding affinities were isolated.33 Subsequently, each peptide was optimized
via single point mutatations, head-to-tail cyclized, and the covalent bond only was minimized
using Maestro 2023-3. 34
Following this protocol, three peptides were designed. Peptide 37QGGVNPEEM45 (P1)
was grafted from the chain E affimer residues sourced from the MCL-1-affimer complex (PDB:
6STJ 33). To avoid steric clashes, residue M38 was mutated to G38. The negative control
(NC) 37QKKGGGEER45 is derived from P1 by introducing the G38K, G39K, V40G, N41G,
P42G and R45M mutations to disfavor binding. Peptide 68VWVKRDLVFGGPENFK83
(P2) was designed from the first loop of the affimer chain D sourced from the BCL-xL-
affimer structure (PDB: 6ST2 33). Peptide 70VKPALLWSPHGNF82 (P3) was engineered
from the first loop of the affimer chain C, extracted from the BCL-xL-affimer structure
(PDB: 6HJL 33). The topology of the new Bax-cyclic peptide system was then subjected to
long molecular dynamics simulations to investigate the stability of the complex.
Simulation protocol
Four sets of simulations were carried out using the same simulation parameters. First,
unrestrained 1 µs MD simulations were conducted in duplicate in the NVT ensemble. For
the systems that proved stable, i.e., no peptide detachment or sliding/reattachment of the
peptide at secondary locations, a stable complex conformation was selected as the starting
configuration for the next set of simulations. For the systems that were not stable, i.e.,
7
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
the peptide detached from the surface of Bax, single point mutations in the peptides were
introduces to avoid steric clashes (e.g. P1) and the protocol was repeated. Second, ten
500-ns simulations of the selected complexes were run to probe the statistical stability of
the complex and characterize the peptide-Bax interactions. Third, ten 500-ns simulations of
Bax and the peptide alone were performed to compare the structural stability and properties
of the protein and the peptides in the bound and unbound states. The bound starting
configuration was selected from the simulations of the complex. Fourth, umbrella sampling
simulations were performed to determine the binding free energies of the peptides to Bax.
Simulation details
The simulations were carried out using the GROMACS 2020.4 simulation package. All
simulations were performed using the all-atom CHARMM36m force field 35,36 and the TIP3P
water model. 37 The systems were solvated in cubic boxes with edge lengths of 7 nm and
4.3 nm for the Bax and peptide only systems (3.7 nm for P3 only), respectively. The Bax-
peptide complexes were solvated in cubic boxes with edge lengths of 7.3 nm (8.2 nm for
the Bax-P2 complex). Each system was neutralized and a background concentration of
150 mM of NaCl was added. Steepest decent energy minimisation was followed by a two-
step isothermal-isobaric ensemble (NPT) equilibration. The temperature and pressure were
kept constant at of 300 K and 1 bar using the velocity rescaling 38 (modified Berendsen)
thermostat and Berendsen barostat, 39 respectively. The temperature and pressure coupling
times were fixed to 0.1 and 2 ps, respectively. The NPT equilibration was performed in two
steps with position restraints of 1000 kJ ·mol-1·nm-2 on the heavy atoms for 5 ns, followed by
an equilibration with restraints of 100 kJ ·mol-1·nm-2 for 5 ns to gently equilibrate the newly
generated protein-peptide complex. The production simulations were performed in the NVT
ensemble in absence of restraints. The short range interaction was cutoff beyond a distance
of 1.2 nm and the potential smoothly decays to zero using the Verlet cutoff scheme. For the
energy and pressure, a long-range dispersion correction was applied. To compute long-range
8
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
electrostatic interactions, the Particle Mesh Ewald technique 40,41 was employed with a cubic
interpolation order, a real space cutoff of 1.2 nm, and a 0.16 nm grid spacing. A fourth order
LINCS algorithm with two iterations was employed to constrain all bond lengths. 42
Umbrella sampling
To determine the intermolecular binding energies between the peptide and Bax, umbrella
sampling was used. 43,44 In essence, an additional energy term, a bias, is applied to the sys-
tem to ensure efficient sampling along a chosen reaction coordinate to connect energetically
separated states. Here, the distance between the centers of mass of the peptide and the
protein, d, was used as the reaction coordinate. The reaction coordinate of range d is then
divided into several ”windows” centered at values di where the harmonic bias potential ωi(d)
only restricts the reaction coordinate in the i th window to fluctuate around di by:45
ωi(d) = 1
2 K(d − di)2. (1)
with K the force constant. This changes the total energy of the system to Eb(i) = Eu(i) +
ωi(d) with E being the total energy and the superscripts ’b’ and ’u’ denoting the biased and
unbiased quantities, respectively. The unbiased free energy for window i, Ai(d), is based on
the probability distributions P b
i and the bias potential and can be obtained by
Ai(d) = −β ln P b
i (d) − ωi(d) + fi (2)
where β = 1/kBT , kB being the Boltzmann constant, T the temperature and, fi a window-
dependent offset: fi = −(1/β) ln⟨exp[−βωi(d)]⟩. The windows are then combined using the
weighted histogram analysis method (WHAM) 46–48 to determine fi.
To generate the series of configurations along the reaction coordinate, chosen as the
center of mass distance between the peptide and the protein, the peptide was pulled away
from the protein along the z-axis. As starting configuration, a stable conformation of the
9
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
ten 500 ns simulations was used. The peptides were pulled with a pull-rate of 0.01 nm/ps
over the course of 400 ps of MD using a harmonic potential with a force constant of 1000
kJ·mol-1·nm-2, saving snapshots every 1 ps. In addition, the backbone of the protein was
restrained with a force constant of 1000 kJ ·mol-1·nm-2. The windows were sampled along
the z-axis with a spacing of 0.2 nm and a force constant of 1000 kJ ·mol-1·nm-2 for Bax-P1
complex. For both P2- and P3-Bax complexes a spacing of 0.1 nm, a force constant of 5000
kJ·mol-1·nm-2 were used. For the umbrella sampling simulations, the box was elongated
along the direction of the pull by 5 nm and the same parameters were used for the MD
simulations of the windows. Each umbrella window was simulated in the NPT ensemble for
305 ns (except for P1, which reached convergence after 105 ns) from which the first 5 ns
were considered to be part of the equilibration.
Results
and discussion
Peptide binding reduces Bax flexibility
For each Bax-peptide complex, two initial simulations of 1 µs were performed to investigate
the structural stability. The results from these sets of simulations revealed that the negative
control detaches from the surface of Bax, and does not reattach at secondary locations.
Peptides P1, P2 and P3 slide on the surface of Bax within the first few ns of the simulations
and converge to new interaction hotspots, which they preserve throughout the simulations.
Specifically, P1 rearranges and binds at the α2-helix in the BH3 domain. Both P2 and P3
attached to the BH1 domain, comprised of mainly the α4-α5 loop and part of the α5-helix
(Fig. 2(a)). These conformations were the selected as initial configurations for ten 500-ns
simulations to investigate complex stability and peptide binding effects on the structure and
dynamics of Bax.
The analysis focused on the structural stability of the complex, reveals that P2 and
P3 remain attached to Bax in all the 5- µs simulations, with average deviations of from
10
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 2: Structural overlap of Bax in complex with the peptides. Highlighted are P1, P2
and P3 in orange, green and blue (a). Root mean square fluctuations (RMSF) profiles of Bax
(b). Compared are the free Bax (black), Bax in complex with P1 (orange), Bax in complex
with P2 (green) and Bax in complex with P3 (blue). The RMSF profiles are calculated as the
average over 50 independent 100-ns profiles. The shaded areas represent the standard error
calculated as the standard deviation of the RMSFs of the 50 independent 100-ns profiles.
For the P1 simulations only 30 independent 100-ns profiles are used from the systems with
a stable interface. Highlighted are the secondary structure elements of Bax (top, and the
binding sites of the peptides (horizontal lines).
the reattached structures of the three bound peptides 0.2 ± 0.1 nm and 0.17 ±0.02 nm,
respectively (Fig. S1). P1 is the least stable as it detaches in four of the ten simulations and
occasionally reattaches at a secondary interaction site. Hence, only the runs, in which P1
remains stably attached (average deviations of 0.27±0.02 nm, Fig. S1) to Bax are considered
for the analysis. In absence of peptides, Bax is structurally stable with average deviations
from the crystal structure of 0.22 ± 0.03 nm. In complex with the peptides the average
deviations from the crystal structure are reduced (0.19 ±0.01 nm, 0.16 ±0.02 nm and 0.17
±0.01 nm in the Bax-P1, Bax-P2 and Bax-P3 complexes, respectively, Fig. S2), suggesting
that the peptides modulate the stability of Bax.
The analysis focused on the protein flexibility shows that peptide attachment has marginal
impact on the plasticity of the secondary structure elements of Bax and affects to a higher
degree the fluctuations of the loops (Fig. 1(b)). Specifically, low fluctuations of the secondary
11
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
structure elements are observed independently of the free or the complexed Bax state, except
for α2, which is decreased upon peptide binding. In contrast, peptide attachment reduces the
mobility of the α1-α2 and α4-α5 loops. The flexibility of loop α3-α4 is differently modulated
by the three peptides i.e., P3 has no impact, while P1 and P2 reduce its plasticity, with the
latter having a more pronounced effect. This modulating effect in the loops can be linked
to the binding sites of the peptides. P1 binds at the C-terminus of the BH3 domain, which
contributes to the reduced flexibility of the α2-helix and the allosteric stiffening at the loops.
P2 and P3 contact the α4-α5 loop, which leads to the stabilization of the BH1 domain, com-
prised of mainly of this loop and part of the α5-helix Furthermore, during the simulations
P2 was was observed to enter the canonical hydrophobic groove (α2-α5 49) and form multiple
contacts at both sites of the groove (to be discussed in the following paragraphs). By en-
tering the pocket, the groove opens, thereby reducing the flexibility of the connecting α3-α4
loop. P3, which also binds more superficially in the hydrophobic groove at the BH1 domain
as compared to P2. As a result, the plasticity of the α3-α4 loop is reduced. Furthermore, the
flexibility of the α3-α4 remains comparable to the one of Bax in the free state but restricts
the motion of α3 as compared to the other systems. The subtle differences in the effects of
P2 and P3 may be ascribed to the longer sequence in case of P2 (sixteen residues compared
to thirteen residues P3), which enables a larger contact area with the protein.
Peptide binding modulates the opening of the hydrophobic groove
and closes the trigger bottom pocket
To further investigate the modulating effects of the peptides on the hydrophobic groove, the
structural and dynamic details of the α3-α4 domain were analyzed (Fig. 3(a)). The impact
on the flexibility of the loop reflects in the solvent accessible surface area (SASA) of the
α3-α4 sequence (spanning residues M74-M99) (Fig. 3(b)). Specifically, the binding of P1 and
P2 leads to an increase in SASA, with the latter having a more pronounced effect. This
correlates with the reduced flexibility of the loop (Fig. 2(b)), despite the peptides binding at
12
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 3: (a) Snapshot of the hydrophobic groove. Highlighted are helices α3 and α4 and
the the residues used to characterize the top and bottom sites. (b) Average solvent accessible
areas of the hydrophobic groove defined as the M74-M99 sequence encompassing the α3-α4
helices. (c) Average distance between the C α atoms of residues M74 and M99 defining the
top of the groove. (d) Average distance between the Cα atoms of residues A81 - R89 defining
the bottom of the groove.
different sites on the surface of Bax. In contrast, P3, which does not affect the flexibility of
the loop, reduces the solvent accessibility of the canonical hydrophobic groove. The peptide
binding effect is also reflected in specific distances between the helices, i.e., M74-M99 and
A81-R89 highlighting the top and the bottom of the groove, respectively (Fig. 3(c-d)). Hence,
the reduced flexibility upon P1 attachment translates into a rearrangement of the helices
characterized by the opening of the groove at the top and closing at the bottom (scissor
motion). The closing of the loop is also associated with the unfolding of the C-terminus
of the α3-helix, which populates more coil structures (Fig. S4). P2 attachment leads to an
increase of about 0.2 nm in both the top and the bottom distances of the groove, which is a
consequence of the insertion of the peptide in the canonical hydrophobic groove. Thus, the
peptide P2 induces the opening of the groove, whereas P1 allosterically opens the top and
closes the bottom of the groove.
13
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 4: Hydrogen bond between Bax and the individual peptides. A hydrogen
bond is considered if the donor-H acceptor distance 120° The error bars represent the standard error of the mean calculated as the
standard deviation of the average values over the independent runs (black points).
Intermolecular hydrogen bonds ensure complex stability
The stability of the protein-peptide interface is driven by a series of hydrogen bonds. These
vary with protein sequence ranging from 2.1 ± 0.3 upon P1 binding to 3.8 ± 0.3 and 5.1 ±
0.4 for P2 and P3, respectively. P1 binds on the surface of the canonical groove at the BH3
domain contacting the α2-helix and the C-terminus of α8. The peptide is ”encapsulated”
around the side chain of residue K58 with two major stabilizing contacts being hydrogen bond
pairs K58-E44 and K58-G38. A quantitative analysis revealed that the backbone of the cyclic
peptide interacts with the K58 side chain over 90%, of the simulation time (Fig. 4(a)). A
series of other H-bonds and salt bridges were identified to contribute to a lesser degree to
the stability of the complex. The P1 binding site is shared by vMIA, a previously identified
Bax suppressor. 16 The mechanism of action of the suppressor is to position itself in such a
way to simultaneously stabilise the α3-α4 and α5-α6 hairpins, preventing the conformational
changes that Bax needs to undergo for its mitochondrial outer membrane insertion and
oligomerization, events that invariably lead to the death of the cell.
14
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Peptides P2 and P3 insert into the canonical hydrophobic cleft of Bax, which is the
binding target of many BH3 only activator proteins such as Bid, Bim, and Bad. 50–52 The
peptides mimic key hydrophobic and polar contacts of the BH3 ligands. Three major contacts
contribute the most to the stability of the P2-Bax complex, i.e., the backbone F76-nitrogen
D98 H-bond, and the two E69-K83 and E75-K71 salt bridges. The corroborated effect of
the less populated D102-G77 and R109-F76 interactions, which encompass residues on the
α4 helix and the α4-α5 loop, and the F76-D98 hydrogen bond is the reduced flexibility of the
α4 helix and the subsequent loop. The less frequent interaction between between Bax Y164
and peptide E80 may contribute to the stabilization of the C-terminus of Bax. Despite its
shorter and distinct sequence as compared to P2 (13 residues as opposed to the 16 residues),
P3 forms more contacts with Bax and the two peptides both interact with residues D98,
E75, D102 and R109 in Bax. The P3-Bax interface is largely stabilized by five interactions
(N104-S77, N104-P78, R109-L75, D98-K71 and D102-K71), which are situated at the α4 and
α5 helices (Fig. 4(c)). The long-lived R109-L75 salt bridge and N104-S77 hydrogen bond
located at the α4-α5 loop may contribute to the reduced flexibility observed in the RMSF
(Fig. 2(b)).
Bax stabilizes specific peptide conformations
To investigate the effects of Bax on the conformations of the peptides, each peptide was
individually subjected to ten 500-ns simulations in absence of the protein. The starting con-
formations of the free peptides were extracted from the simulations of the complexes, i.e.,
the initial conformation corresponds to a stably bound peptide conformation (see Methods).
The peptides in the free state sample conformations that deviate from the bound configura-
tions, with C α RMSD values relative to their bound states of 0.16 ± 0.01 nm for P1, 0.24 ±
0.07 nm for P2 and 0.24 ± 0.02 nm (Fig. S3). The analysis focused on the P1 intramolecular
contacts revealed that the free peptide maintains the internal E44-N41 H-bond (Fig. 5(a)),
yet to lesser extent as compared to the complexed state. A series of distinct contacts are
15
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 5: Peptide intramolecular hydrogen bond occupancy. Compared are the
contacts in the bound state (dark color) and the unbound state (light color, left panels).
Shown are representative snapshots of the peptides in the bound state with the residues
involved in the most populated contacts highlighted (right snapshots). A hydrogen bond is
considered if the donor-H acceptor distance 120°. The error bars represent the standard error of the mean calculated as the standard
deviation of the average values over the independent runs (black points).
transiently formed in the free state, which indicates that the peptide is more dynamic than
in the bound conformation. Additionally, in both the bound and unbound state, the peptide
is devoid of any secondary structure and is rich in coils and turns (Fig. S5(a)).
In contrast, the differences between the bound and unbound state of P2 and P3 are
more pronounced. In complex, P2 attains a twisted boat conformation, rationalized via
”reduction” to cycloalkane conformations, where the side chain of R72 is inserted between
the peptide backbones, hence contributing to the stability of the peptide. The conformation
is lost in the unbound simulations as the peptide moves from a boat conformation to a chair
conformation where the side chain of R72 is no longer engaged in stabilizing interactions
with the peptide backbone. Instead, the hydrophobic phenyl group of F82 occasionally
moves to maintain the bound state hydrogen bonds K83-N81 and F82-R72. Nevertheless,
the dynamics of these contacts reflects in the larger error bars as compared to the bound
16
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
state (Fig. 5(b)). Thus, the protein favors the twisted boat conformation, which is sampled
to a lesser extent in the free simulations (Fig. S7). As for P1, P2 is devoid of secondary
structure elements and is rich in coils and turns (Fig. S5(b)).
Similar to P2, the predominant intramolecular interactions in the bound P3 are signif-
icantly reduced in the free state. The peptide in complex with Bax, is stabilized by five
hydrogen bonds. Furthermore, in the bound state, the A73-L75 segment predominantly
adopts a 3 10 helical conformation, a structure marginally sampled in the unbound simula-
tions (Fig. S6). The free peptide is dynamic as highlighted by the large error bars in the
contact occupancies (Fig. 5(c)) and devoid of secondary structure elements (Fig. S5(c)).
Favorable peptide binding
Having characterized the structural details of the protein, the complexes and the peptides
independently, the next natural step is to quantify the binding of the peptides to Bax. For
this, four sets of umbrella sampling simulations were performed, one for each peptide and one
for the negative control (see Methods). Because the peptides bind at different locations and
have different binding modes, the profiles in Fig. 6 were shifted along the reaction coordinate
for ease of comparison. This does not affect the calculation of the binding free energies. The
negative control peptide was constructed from the sequence P1 to disrupt hydrogen bond
formation and/or induce steric clashes (see Methods).
The free energy curves of all peptides show a minimum at the optimal attachment sites
of the peptides, which corresponds to the center of mass distance between the protein and
the peptide (Fig. 6). The negative control has a relatively shallow minimum as compared
to the designed peptides. This stands as evidence for the lack of stabilizing contacts in the
complex and is in line with the conventional molecular dynamics simulations, which show no
long-lived attachment of NC to Bax. Peptides P1, P2 and P3 all remained in stable contact
during the MD simulations. In the P1-Bax complex, the two hydrogen bonds (K58-E44 and
K58-G38) are preserved at the minimum of the free energy profile. Upon pulling the peptide
17
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Figure 6: Free energy curves as a function of the center of mass distances between
Bax and the peptides. The black curve corresponds to the profile of the negative control
(NC).
away from the protein, the hydrogen bonds start alternating between the two residues until
no contact is established at longer distances. The gradual breaking of the hydrogen bonds
reflects in a broad free energy curve (Fig. 6). The profile of the P2-Bax complex presents
a lower minimum, which is ascribed to four stabilizing hydrogen bonds (D98-F76, E69-K83,
E75-K71 and D102-G77). Similar as in the case of P1, the detachment is gradual and occurs
with the step wise breaking of the H-bonds, i.e., D98-F76 is the first bond to break, followed
by E69-K83 and N73-K71, and subsequently D102-KG77. The P3-Bax profile shows the
lowest minimum across the tested peptides, which corresponds to five dominant hydrogen
bonds (R109-L75, N104-S77, D98-K71, N104-P78, D102-K71). Upon pulling the peptide
away from the protein, four bonds break simultaneously (N104-S77, N104-P78, R109-L75,
and D102-N81), which results in a steeper profile as compared to P1 and P2. The last
contact to break is the D102-K71 salt bridge.
To estimate the binding free energies, the detachment free energies of each peptide are
first calculated by 53,54
∆G = −RT ln
"
4πd2
0
Q(d0) c0
Z d‡
0
Q( ¯d)d ¯d
#
. (3)
Here, the partition function as a function of distance, Q(d), is derived from simulations for
18
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
short distances using Q(d) = exp[−A(d)/(RT )]. For distances beyond the interaction range,
an entropy-dominated extrapolation is used: Q( ¯d) = Q(d0) ¯d2/d2
0. Here, d0 is an arbitrary
distance beyond the interaction range that merges the two partial solutions, d‡ represents
the location of the transition state of the binding reaction and was chosen to be 1.5 nm, R
is the gas constant, and c0 is a reference concentration, typically 1 M. The numerical results
of the binding free energies are shown in Table 1. These have been evaluated also relative
to the negative control. The results show that the number of hydrogen bonds stabilizing
the protein-peptide complex contribute the most to the binding free energies. Hence, the
binding of a peptide becomes more favorable with increasing number of stabilizing H-bonds
as in the specific case of P3.
Table 1: Free energy change upon binding to Bax (∆ G) and relative to the negative control
(∆∆G).
Peptide ∆G (kJ/mol) ∆∆ G (kJ/mol)
NC -7.5 -
P1 -42 -34.5
P2 -70 -62.5
P3 -89 -81.5
Discussion
and Conclusion
Neurodegeneration is the leading cause of brain disorders worldwide, and Parkinson’s disease
is the fastest growing among them. 55 Parkinson’s disease involves the loss of dopamine-
producing neurons in the brain, leading to motor symptoms. Here, we introduce a novel
computational strategy to develop and validate cyclic peptides with the ultimate intent to
prevent the initiation of intrinsic apoptosis and possibly prevent or delay the degeneration
of neurons as observed in Parkinson’s disease. Our strategy relies on three steps prior
to experimental testing. We first rationally design a series of peptides starting from high
resolution structures of protein complexes. Subsequently, we computationally validate and
optimize the binding of the three peptides to Bax by introducing single point mutations and
19
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
relying on results from (enhanced sampling) molecular dynamics simulations. Finally, we
determine their binding free energies and advance the peptides to experimental testing. Our
Results
reveal that the Bax-peptide complexes are structurally stable on timescales of 5 µs
and are stabilized by a series of inter- and intra-molecular hydrogen bonds. Furthermore,
the peptides reduced the intrinsic flexibility of the protein by binding at the hydrophobic
groove (the dimerization site of Bax 13) and at allosteric sites. Interestingly, the peptides
modulate the dynamics of the canonical hydrophobic groove in a different way. Peptide 3
(70VKPALLWSPHGNF82) has a marginal impact, while peptide 1 ( 37QGGVNPEEM45) and
peptide 2 (68VWVKRDLVFGGPENFK83) both open the hydrophobic groove. The latter has
a more pronounced impact, which can potentially impede the ability of Bax to oligomerize,
a hypothesis we will test experimentally. Finally, we determined the binding free energies of
the peptides to Bax, highlighting the role of the hydrogen bonds and peptide conformational
stability in the integrity of the complex.
It has been proposed that Bax activation may require cooperation among various binding
sites. 56 This suggests that finding binders that engage sites beyond the typical hydrophobic
groove might lead to allosteric inhibitors. Here, we developed P1, which binds the D53-R65
segment outside the hydrophobic groove but still modulates its dynamics. Hence, further
exploration of the impact of one or multiple P1 peptides on Bax, can provide new avenues
towards the allosteric modulation of Bax. To access the allosteric pocket one might consider
enriching the solvent with small molecules that can gently open the pocket without disrupting
its secondary structure. 57
Our results show that P2 and P3 bind with high affinity and at similar interaction sites to
Bax. They insert themselves in the so-called S184 cryptic pocket, referring to a pocket near
residue S184 on the α9-helix that is prone to phosphorylation. 58 Phosphorylation of the S184
residue causes full length Bax to lose its pro-apoptotic function. 58–60 The pocket consists of
residues at the α4-α5 loop and the α9-helix. P3 binds with stronger affinity than P2, which
is ascribed to more intermolecular contacts with Bax on the α4-α5 helices and the connecting
20
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
loop. Hence this peptide would arguably fit better in the cryptic S184 pocket than peptide
P2. Binding at that site mimics pro-survival proteins and may thus result in inhibition
of Bax. However, Bax activators such as the α-helical BidBH3 peptide, also occupy the
canonical hydrophobic surface groove. 61 Notably, upon binding of these activators, cavities
appear on Bax at the interface between the core and latch domains ( α2, α5 and α8). 13,62
Such cavities are destabilizing and suggest that the binders thereby induce conformational
changes which lead to release of the core and its α2 segment.63 These cavities do not form
in complexes with pro-survival proteins 13 and are not accessible on the timescales of our
simulations.
As mentioned in the introduction, our long-term goal is to create a machine learning
powered platform for peptide design. 19 This platform would work as a digital twin and rely
on input from computational and experimental results to generate novel and better binders
towards a target. Evidently, building such a platform is not effortless. As such, the present
study sets the stage for generating the computational component of the platform. Future
studies will address further computational optimization and experimental validation of the
developed peptides. Importantly, the concepts and strategies introduced here extend beyond
drug design and will aid in the development of novel bio-inspired materials.
In conclusion, this study lays the foundation for the iterative development of peptides
that bind to Bax. We introduced and validated a new protocol for digital peptide develop-
ment, in which we rationally designed and computationally dissected three cyclic peptides,
which can modulate the dynamics of the canonical hydrophobic groove (Bax dimerization
site 13). Furthermore, the stability of a Bax-peptide complex is maintained by a series of
inter- and intra-molecular hydrogen bonds, which reflects in the calculated binding free en-
ergies. Importantly, this novel protocol can be easily tailored and extended to other protein
targets, for which peptides represent attractive binders and for which suitable high resolution
structures and/or dynamics studies are available. 64,65
21
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Acknowledgement
I.M.I. acknowledges support from the Sectorplan B` eta & Techniek of the Dutch Government
and the Dementia Research - Synapsis Foundation Switzerland. I.M.I. and L.H. acknowledge
support from the Molecular Material Design Technology Impulse grant.
References
(1) Taylor, R. C.; Cullen, S. P.; Martin, S. J. Apoptosis: controlled demolition at the
cellular level. Nat. Rev. Mol. Cell Biol. 2008, 9, 231–241.
(2) Thompson, C. B. Apoptosis in the Pathogenesis and Treatment of Disease. Science
1995, 267, 1456–1462.
(3) Robinson, E. J.; Aguiar, S. P.; Kouwenhoven, W. M.; Starmans, D. S.; von Oerthel, L.;
Smidt, M. P.; van der Heide, L. P. Survival of midbrain dopamine neurons depends on
the Bcl2 factor Mcl1. Cell Death Discovery 2018, 4, 107.
(4) Green, D. R.; Evan, G. I. A matter of life and death. 2002, 1, 19–30.
(5) Pemberton, J. M.; Pogmore, J. P.; Andrews, D. W. Neuronal cell life, death, and axonal
degeneration as regulated by the BCL-2 family proteins. Cell Death & Differentiation
2020, 28, 108–122.
(6) Chipuk, J. E.; Moldoveanu, T.; Llambi, F.; Parsons, M. J.; Green, D. R. The BCL-2
Family Reunion. 2010, 37, 299–310.
(7) Hardwick, J. M.; Soane, L. Multiple Functions of BCL-2 Family Proteins. Cold Spring
Harbor Perspectives in Biology 2013, 5, a008722–a008722.
(8) Chipuk, J. E.; Moldoveanu, T.; Llambi, F.; Parsons, M. J.; Green, D. R. The BCL-2
Family Reunion. Molecular Cell 2010, 37, 299–310.
22
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
(9) Lovell, J. F.; Billen, L. P.; Bindner, S.; Shamas-Din, A.; Fradin, C.; Leber, B.; An-
drews, D. W. Membrane Binding by tBid Initiates an Ordered Series of Events Culmi-
nating in Membrane Permeabilization by Bax. Cell 2008, 135, 1074–1084.
(10) Robinson, E. J.; Aguiar, S.; Smidt, M. P.; van der Heide, L. P. MCL1 as a Therapeutic
Target in Parkinson’s Disease? Trends in Molecular Medicine 2019, 25, 1056–1065.
(11) Suzuki, M.; Youle, R. J.; Tjandra, N. Structure of Bax. Cell 2000, 103, 645–654.
(12) Gavathiotis, E.; Reyna, D. E.; Davis, M. L.; Bird, G. H.; Walensky, L. D. BH3-Triggered
Structural Reorganization Drives the Activation of Proapoptotic BAX. Molecular Cell
2010, 40, 481–492.
(13) Czabotar, P. E.; Westphal, D.; Dewson, G.; Ma, S.; Hockings, C.; Fairlie, W. D.;
Lee, E. F.; Yao, S.; Robin, A. Y.; Smith, B. J.; Huang, D. C.; Kluck, R. M.;
Adams, J. M.; Colman, P. M. Bax Crystal Structures Reveal How BH3 Domains Ac-
tivate Bax and Nucleate Its Oligomerization to Induce Apoptosis. Cell 2013, 152,
519–531.
(14) Subburaj, Y.; Cosentino, K.; Axmann, M.; Pedrueza-Villalmanzo, E.; Hermann, E.;
Bleicken, S.; Spatz, J.; Garc´ ıa-S´ aez, A. J. Bax monomers form dimer units in the
membrane that further self-assemble into multiple oligomeric species. Nature Commu-
nications 2015, 6, 8042.
(15) Iyer, S.; Anwari, K.; Alsop, A. E.; Yuen, W. S.; Huang, D. C. S.; Carroll, J.;
Smith, N. A.; Smith, B. J.; Dewson, G.; Kluck, R. M. Identification of an activation
site in Bak and mitochondrial Bax triggered by antibodies. Nature Communications
2016, 7, 11734.
(16) Ma, J.; Edlich, F.; Bermejo, G. A.; Norris, K. L.; Youle, R. J.; Tjandra, N. Structural
mechanism of Bax inhibition by cytomegalovirus protein vMIA. Proceedings of the
National Academy of Sciences 2012, 109, 20901–20906.
23
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
(17) Barclay, L. A.; Wales, T. E.; Garner, T. P.; Wachter, F.; Lee, S.; Guerra, R. M.;
Stewart, M. L.; Braun, C. R.; Bird, G. H.; Gavathiotis, E.; Engen, J. R.; Walensky, L. D.
Inhibition of Pro-Apoptotic BAX by a Noncanonical Interaction Mechanism. Molecular
Cell 2015, 57, 873–886.
(18) Brahmbhatt, H.; Uehling, D.; Al-awar, R.; Leber, B.; Andrews, D. Small molecules
reveal an alternative mechanism of Bax activation. Biochemical Journal 2016, 473,
1073–1083.
(19) de Raffele, D.; Ilie, I. M. Unlocking novel therapies: cyclic peptide design for amy-
loidogenic targets through synergies of experiments, simulations, and machine learning.
Chem. Comm. 2024, 60, 632–645.
(20) Zorzi, A.; Deyle, K.; Heinis, C. Cyclic peptide therapeutics: past, present and future.
Curr. Op. Chem. Biol. 2017, 38, 24–29.
(21) Dougherty, P. G.; Sahni, A.; Pei, D. Understanding Cell Penetration of Cyclic Peptides.
Chem. Rev. 2019, 119, 10241–10287.
(22) Kurrikoff, K.; Aphkhazava, D.; Langel, U. The future of peptides in cancer treatment.
Curr. Op. Pharmacology 2019, 47, 27–32.
(23) Flores, C.; Fouquet, G.; Moura, I. C.; Maciel, T. T.; Hermine, O. Lessons to Learn
From Low-Dose Cyclosporin-A: A New Approach for Unexpected Clinical Applications.
Frontiers in Immunology 2019, 10 .
(24) Armiento, V.; Hille, K.; Naltsas, D.; Lin, J.; Barron, A.; Kapurniotu, A. The human
cathelicidin LL-37 is a nanomolar inhibitor of amyloid self-assembly of islet amyloid
polypeptide (IAPP). Angew. Chem., Int. Ed. 2020, 59, 3372–3384.
(25) Ikenoue, T.; Aprile, F.; Sormanni, P.; Vendruscolo, M. Rationally designed bicyclic pep-
24
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
tides prevent the conversion of Aβ42 assemblies into fibrillar structures.Front. Neurosci.
2021, 15, 1–9.
(26) Patel, K. et al. Cyclic peptides can engage a single binding pocket through highly
divergent modes. Proc. Nat. Acad. Sci. 2020, 117, 26728–26738.
(27) Etayash, H.; Pletzer, D.; Kumar, P.; Straus, S. K.; Hancock, R. E. W. Cyclic Derivative
of Host-Defense Peptide IDR-1018 Improves Proteolytic Stability, Suppresses Inflam-
mation, and Enhances In Vivo Activity. J. Med. Chem. 2020, 63, 9228–9236.
(28) Sohrabi, C.; Foster, A.; Tavassoli, A. Methods for generating and screening libraries of
genetically encoded cyclic peptides in drug discovery.Nat. Rev. Chem. 2020, 4, 90–101.
(29) Baek, M.; DiMaio, F.; Anishchenko, I.; Dauparas, J.; Ovchinnikov, S.; Lee, G. R.;
Wang, J.; Cong, Q.; Kinch, L. N.; Schaeffer, R. D.; others Accurate prediction of
protein structures and interactions using a three-track neural network. Science 2021,
373, 871–876.
(30) Jumper, J.; Evans, R.; Pritzel, A.; Green, T.; Figurnov, M.; Ronneberger, O.; Tunya-
suvunakool, K.; Bates, R.; ˇZ´ ıdek, A.; Potapenko, A.; others Highly accurate protein
structure prediction with AlphaFold. Nature 2021, 596, 583–589.
(31) Casadevall, G.; Duran, C.; Osuna, S. AlphaFold2 and Deep Learning for Elucidating
Enzyme Conformational Flexibility and Its Application for Design. JACS Au 2023, 3,
1554–1562.
(32) Damjanovic, J.; Miao, J.; Huang, H.; Lin, Y.-S. Elucidating Solution Structures of
Cyclic Peptides Using Molecular Dynamics Simulations. Chem. Rev. 2021, 121, 2292–
2324.
(33) Miles, J. A.; Hobor, F.; Trinh, C. H.; Taylor, J.; Tiede, C.; Rowell, P. R.; Jackson, B. R.;
Nadat, F. A.; Ramsahye, P.; Kyle, H. F.; Wicky, B. I. M.; Clarke, J.; Tomlinson, D. C.;
25
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Wilson, A. J.; Edwards, T. A. Selective Affimers Recognise the BCL-2 Family Proteins
BCL-xL and MCL-1 through Noncanonical Structural Motifs**. ChemBioChem 2021,
22, 232–240.
(34) Schr¨ odinger release 2023-3: Maestro, Schr¨ odinger. 2023.
(35) Huang, J.; MacKerell, A. D. CHARMM36 all-atom additive protein force field: Vali-
dation based on comparison to NMR data. J. Comp. Chem. 2013, 34, 2135–2145.
(36) Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B. L.;
Grubm¨ uller, H.; MacKerell, A. D. CHARMM36m: an improved force field for folded
and intrinsically disordered proteins. Nat. Met. 2017, 14, 71–73.
(37) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L.
Comparison of simple potential functions for simulating liquid water. J. Chem. Phys.
1983, 79, 926–935.
(38) Bussi, G.; Donadio, D.; Parrinello, M. Canonical sampling through velocity rescaling.
J. Chem. Phys. 2007, 126 .
(39) Berendsen, H.; van der Spoel, D.; van Drunen, R. GROMACS: A message-passing
parallel molecular dynamics implementation. Comput. Phys. Commun. 1995, 91, 43–
56.
(40) Darden, T.; York, D.; Pedersen, L. Particle mesh Ewald: An ¡i¿N¡/i¿ log( ¡i¿N¡/i¿ )
Method
for Ewald sums in large systems. J. Chem. Phys. 1993, 98, 10089–10092.
(41) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A
smooth particle mesh Ewald method. J. Chem. Phys. 1995, 103, 8577–8593.
(42) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. LINCS: A linear con-
straint solver for molecular simulations. J. Comp. Chem. 1997, 18, 1463–1472.
26
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
(43) Torrie, G. M.; Valleau, J. P. Monte Carlo free energy estimates using non-Boltzmann
sampling: Application to the sub-critical Lennard-Jones fluid. Chem. Phys. Lett 1974,
28, 578–581.
(44) Torrie, G.; Valleau, J. Nonphysical sampling distributions in Monte Carlo free-energy
estimation: Umbrella sampling. J. Chem. Phys. 1977, 23, 187–199.
(45) K¨ astner, J. Umbrella sampling. WIREs Computational Molecular Science 2011, 1,
932–942.
(46) Kumar, S.; Rosenberg, J. M.; Bouzida, D.; Swendsen, R. H.; Kollman, P. A. THE
weighted histogram analysis method for free-energy calculations on biomolecules. I.
The method. J. Comp. Chem. 1992, 13, 1011–1021.
(47) Roux, B. The calculation of the potential of mean force using computer simulations.
Comput. Phys. Commun. 1995, 91, 275–282.
(48) Souaille, M.; Roux, B. Extension to the weighted histogram analysis method: combining
umbrella sampling with free energy calculations. Comput. Phys. Commun. 2001, 135,
40–57.
(49) Li, M. X.; Tan, I. K. L.; Ma, S. B.; Hockings, C.; Kratina, T.; Dengler, M. A.; Al-
sop, A. E.; Kluck, R. M.; Dewson, G. BAK α6 permits activation by BH3-only proteins
and homooligomerization via the canonical hydrophobic groove. Proceedings of the Na-
tional Academy of Sciences 2017, 114, 7629–7634.
(50) Yang, E.; Zha, J.; Jockel, J.; Boise, L. H.; Thompson, C. B.; Korsmeyer, S. J. Bad,
a heterodimeric partner for Bcl-xL and Bcl-2, displaces bax and promotes cell death.
Cell 1995, 80, 285–291.
(51) Wang, K.; Yin, X. M.; Chao, D. T.; Milliman, C. L.; Korsmeyer, S. J. BID: a novel
BH3 domain-only death agonist. Genes & Development 1996, 10, 2859–2869.
27
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
(52) O’Connor, L. Bim: a novel member of the Bcl-2 family that promotes apoptosis. The
EMBO Journal 1998, 17, 384–395.
(53) Ilie, I. M.; den Otter, W. K.; Briels, W. J. The attachment of α-synuclein to a fiber: A
coarse-grain approach. The Journal of Chemical Physics 2017, 146 .
(54) Ilie, I. M.; Nayar, D.; den Otter, W. K.; van der Vegt, N. F. A.; Briels, W. J. Intrin-
sic Conformational Preferences and Interactions in α-Synuclein Fibrils: Insights from
Molecular Dynamics Simulations. Journal of Chemical Theory and Computation 2018,
14, 3298–3310.
(55) Dorsey, E. R. et al. Global, regional, and national burden of Parkinson’s disease,
1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The
Lancet Neurology 2018, 17, 939–953.
(56) Rouchidane Eyitayo, A.; Daury, L.; Priault, M.; Manon, S. The membrane insertion
of the pro-apoptotic protein Bax is a Tom22-dependent multi-step process: a study in
nanodiscs. 2024, 10 .
(57) Ilie, I. M.; Ehrhardt, C.; Caflisch, A.; Weitz-Schmidt, G. Decrypting Integrins by Mixed-
Solvent Molecular Dynamics Simulations. J. Chem. Inf. Model. 2023, 63, 3878–3891.
(58) Kale, J.; Kutuk, O.; Brito, G. C.; Andrews, T. S.; Leber, B.; Letai, A.; Andrews, D. W.
Phosphorylation switches Bax from promoting to inhibiting apoptosis thereby increas-
ing drug resistance. EMBO reports 2018, 19 .
(59) Xin, M.; Deng, X. Protein Phosphatase 2A Enhances the Proapoptotic Function of Bax
through Dephosphorylation. Journal of Biological Chemistry 2006, 281, 18859–18867.
(60) Xin, M.; Deng, X. Nicotine Inactivation of the Proapoptotic Function of Bax through
Phosphorylation. Journal of Biological Chemistry 2005, 280, 10781–10789.
28
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
(61) Gavathiotis, E.; Suzuki, M.; Davis, M. L.; Pitter, K.; Bird, G. H.; Katz, S. G.; Tu, H.-
C.; Kim, H.; Cheng, E. H.-Y.; Tjandra, N.; Walensky, L. D. BAX activation is initiated
at a novel interaction site. Nature 2008, 455, 1076–1081.
(62) Czabotar, P. E.; Lessene, G.; Strasser, A.; Adams, J. M. Control of apoptosis by the
BCL-2 protein family: implications for physiology and therapy. Nature Reviews Molec-
ular Cell Biology 2014, 15, 49–63.
(63) Baase, W. A.; Liu, L.; Tronrud, D. E.; Matthews, B. W. Lessons from the lysozyme of
phage T4. Protein Science 2010, 19, 631–641.
(64) Ilie, I. M.; Caflisch, A. Antibody binding increases the flexibility of the prion protein.
Biochim. et Biophys. Acta - Proteins Proteom. 2022, 1870, 11–12.
(65) Ilie, I. M.; Bacci, M.; Vitalis, A.; Caflisch, A. Antibody binding modulates the dynamics
of the membrane-bound prion protein. Biophys. J. 2022, 121, 2813–2825.
29
.CC-BY-NC-ND 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 31, 2024. ; https://doi.org/10.1101/2024.10.28.617283doi: bioRxiv preprint
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.