3D structure generation, virtual screening and docking of humanRas-associated binding (Rab3A) protein involvedin tumourigenesis
Sharad S. Lodhi • Rohit Farmer • Atul Kumar Singh •
Yogesh K. Jaiswal • Gulshan Wadhwa
Received: 7 May 2013 / Accepted: 11 February 2014
� Springer Science+Business Media Dordrecht 2014
Abstract Rab3A is expressed predominantly in brain and
synaptic vesicles. Rab3A is involved specifically in teth-
ering and docking of synaptic vesicles prior to fusion
which is a critical step in regulated release of neurotrans-
mitters. The precise function of Rab3A is still not known.
However, up-regulation of Rab3A has been reported in
malignant neuroendocrine and breast cancer cells. In the
present study, the structure of Rab3A protein was gener-
ated using MODELLER 9v8 software. The modeled pro-
tein structure was validated and subjected to molecular
docking analyses. Docking with GTP was carried out on
the binding site of Rab3A using GOLD software. The
Rab3A-GTP complex has best GOLD fitness value of
77.73. Ligplot shows hydrogen bondings (S16, S17, V18,
G19, K20, T21, S22, S31, T33, A35, S38, T39 and G65)
and hydrophobic interacting residues (F25, F32, P34, F36,
V37, D62 and A64) with the GTP ligands in the binding
site of Rab3A protein. Here, the ligand molecules of NCI
diversity set II from the ZINC database against the active
site of the Rab3A protein were screened. For this purpose,
the incremental construction algorithm of GLIDE and the
genetic algorithm of GOLD were used. Docking results
were analyzed for top ranking compounds using a con-
sensus scoring function of X-Score to calculate the binding
affinity and Ligplot was used to measure protein–ligand
interactions. Five compounds which possess good inhibi-
tory activity and may act as potential high affinity inhibi-
tors against Rab3A active site were identified. The
top ranking molecule (ZINC13152284) has a Glide score of
-6.65 kcal/mol, X-Score of -3.02 kcal/mol and GOLD
score of 64.54 with 03 hydrogen bonds and 09 hydrophobic
contacts. This compound is thus a good starting point for
further development of strong inhibitors.
Keywords Rab3A � GTP � GOLD Docking �Tumourigenesis
Introduction
The Rab (Ras-associated binding) GTPases comprise the
largest subfamily of the Ras superfamily and function as
regulators of various steps in vesicle trafficking pathways. In
human genome, more than 60 Rab genes are known, out of
which Rab3 is found to be involved in regulation of exocy-
tosis of neurotransmitters and hormones [1–4]. The Rab3
subfamily includes four isoforms: Rab3A, B, C and D, which
are differentially expressed in neuronal and endocrine tissues
[5, 6]. The most abundant expression of Rab3A can be
observed in brain where it is present in almost all synapses,
while Rab3B and Rab3C are only present in a subset of
Electronic supplementary material The online version of thisarticle (doi:10.1007/s11033-014-3263-x) contains supplementarymaterial, which is available to authorized users.
S. S. Lodhi � Y. K. Jaiswal
School of Studies in Biochemistry, Jiwaji University,
Gwalior 474011, India
S. S. Lodhi � G. Wadhwa (&)
Apex Bioinformatics Centre (BTISNET), Department of
Biotechnology, Ministry of Science and Technology, 7th Floor,
Block-2, CGO Complex, New Delhi 110003, India
e-mail: [email protected]
R. Farmer
Department of Computational Biology and Bioinformatics, Sam
Higginbottom Institute of Agriculture, Technology and Sciences,
Allahabad 211007, UP, India
A. K. Singh
Centre for Research in Nanotechnology & Science, Indian
Institute of Technology-Bombay, Mumbai 400076, India
123
Mol Biol Rep
DOI 10.1007/s11033-014-3263-x
synapses [7]. Like other Rab-GTPases, Rab3 interacts with
membranes via C-terminal geranylgeranyl moieties and
cycles between a synaptic vesicle-associated GTP-bound
form and a cytosolic GDP-bound form [8, 9]. This cycling is
regulated by three types of regulators: Rab GDP dissociation
inhibitor (GDI), Rab3 GDP/GTP exchange protein, and
Rab3 GAP [10]. Mutations in the genes encoding regulatory
and catalytic subunits of the Rab3 GAP lead to Warburg
Micro and Martsolf syndromes characterized by develop-
mental abnormalities of the eye, nervous system and geni-
talia [11, 12]. Because the cyclical activation is coupled with
membrane association and allows both spatial and temporal
control of Rab3A activity, these regulators are thought to be
important for the proper functioning of Rab3A in synaptic
vesicle transport. The diverse actions of Rab proteins are
mediated via their multiple effectors, which usually interact
with the GTP bound form of Rabs [9]. The known potential
effectors of Rab3A are Rabin3, Rabphilin, RIM1a, RIM2a,
Granuphilin, Noc2, PRA1, Munc18-1, INPP5B, SNAP-29,
Synapsin and Calmodulin [8, 13–16]. However, further
research is needed to determine physiological importance of
these effectors and their mode of coordination to mediate the
diverse actions of Rab3A.
Despite a lot of research being carried out, the involve-
ment of Rab3a in various pathways has been identified but its
precise function has not yet been known. Many studies show
the variation of Rab3A function from species to species.
Rab3A appears to be involved in regulation of targeting and
docking of synaptic vesicle at the active zone. Loss-of
function mutations of Rab3A gene in C. elegans lead to a
significant depletion of synaptic vesicles at presynaptic ter-
minals and a concomitant elevation of vesicles along the
axons [17]. Whereas Rab3A deletion in mice does not appear
to affect synaptic vesicle distribution at the resting state, it
abolishes the activity-dependent recruitment of synaptic
vesicles to the active zone and impairs the replenishment of
docked vesicles after exhaustive stimulation [18]. Rab3A
also seems to regulate the post-docking step in synaptic
vesicle fusion. Electrophysiological studies on Rab3A null
mutant mice show that while the size of the readily releasable
pool of vesicles is unaltered, Ca2?-triggered synaptic vesicle
exocytosis and paired pulse facilitation is increased [19] and
mossy fiber long-term potentiation is abolished [20]. Support
for a role of Rab3A at a late step during Ca2?-triggered
exocytosis is also provided by studies on aplysia neurons
injected with a GTPase-deficient form of Rab3A [21].
Rab3A might coordinate the regulation of coupling between
synaptic vesicle exocytosis and endocytosis through its
putative effector Rabphilin [13]. A recent study also
explored the function of Rab3A at ribbon synapses in the
retina of the tiger salamander (Ambystoma tigrinum), where
the Rab3A mutant blocks synaptic release in an activity-
dependent manner, with more frequent stimulation leading
to more rapid block. The frequency dependence of block by
exogenous Rab3A suggests that it acts competitively with
synaptic vesicles to interfere with their resupply to release
sites. This finding suggests a crucial role of Rab3A in
delivering vesicles to Ca2?-dependent release sites at ribbon
synapses as well [22]. In humans, over expression of Rab3A
has been reported in malignant neuroendocrine cells [23] and
breast cancer cells, which suggests its potential role in the
process of tumourigenesis.
In the present study we aim to explore the Rab3A pro-
tein through molecular modeling and virtual screening of
potential inhibitors. The modeled structure of Rab3A pro-
duced in this study identified new interactions important in
the regulation of GTPase activity.
Materials and methods
3D structure generation
The amino acid sequence of human Rab3A (target Rab3A)
was retrieved from the NCBI sequence database (http://
www.ncbi.nlm.nih.gov) (accession no. AAF67748.1, 220
aa). To identify the templates for homology modeling of
Rab3A, a BLASTP search (http://blast.ncbi.nlm.nih.gov/
Blast.cgi?PAGE0Proteins) was performed against the
Brookhaven Protein Data Bank with the default parameters.
The sequence alignment between target and template were
carried out using the CLUSTAL Wv2 (http://www.ebi.ac.
uk/clustalw) program [24]. The template used was PDB ID
1ZBD which is the crystal structure of the small G protein
Rab3A complexed with the effector domain of rabphilin-3A
from Rattus norvegicu. There was 95 % sequence identity
between template and target with 90 % query coverage. The
academic version of MODELLER9v8 (http://salilab.org/
modeller/), was used for 3D structure generation based on the
information obtained from sequence alignment [25]. Out of
20 models generated by MODELLER, one model central to
cluster was selected and subjected to stereo chemical check
to find the deviations from normal bond length, dihedrals and
non-bonded atom–atom distances. Each model with the
highest G-score of PROCHECK [26], and VERIFY3D [27]
profile was subjected to energy minimization. The energy
minimization was started with side chains and then applied to
main chain of Ca backbone. All calculations were performed
by using ACCELRYS DS modeling 2.5 (Accelrys Inc. San
Diego, CA 92121, USA) software suites. STRIDE [28] was
used for the prediction of secondary structure of the modeled
Rab3A protein. PROSA was used for calculating Z-scores.
The weighted root mean square deviation (RMSD) of the
modeled protein structure was calculated using the combi-
natorial extension algorithm [29]. The modeled structure
was then superimposed on the crystal template without
Mol Biol Rep
123
altering the coordinate systems of atomic position in the
template. The residue profiles of the three-dimensional
models were further checked using VERIFY3D. PRO-
CHECK analysis was performed to assess the stereo-chem-
ical properties of the three-dimensional models and
Ramachandran plots.
Molecular dynamics (MD) simulations
The MD simulations of modeled Rab3A protein were
performed with the GROMACS 4.5.4 software package
[30] using GROMOS 96 force field [31] and the flexible
SPC water model. The initial structure was immersed in a
periodic water box of truncated octahedron shape (0.5 nm
thick). Electrostatic energy was calculated using the par-
ticle mesh Ewald method [32]. Cutoff distance for the
calculation of the Coulomb and Vander Waals interaction
was 1.0. After energy minimization using a steepest des-
cent for 1,000 steps, the system was subjected to equili-
bration at 300 k and normal pressure for 100 ps under the
conditions of position restraints for heavy atoms. LINCS
[33] constraints were performed for all bonds, keeping the
whole protein molecule fixed and allowing only the water
molecule to move to equilibrate with respect to the protein
structure. The system was coupled to the external bath by
the Berendsen pressure and temperature coupling [34]. The
system contained 7 negative charges which were stabilized
by counter 7 NA? ions. The final MD calculations were
performed for 1 ns under the same conditions except that
the position restraints were removed. The results were
analyzed using the standard software provided by the
GROMACS package. An average structure was refined
further using a steepest descent energy minimization.
The modeled structure through various structure vali-
dation and molecular dynamics simulation was subjected
for the prediction of possible active sites using putative
active sites with spheres (PASS) and CastP programs
simultaneously. PASS is a simple computational tool that
uses geometry to characterize regions of buried volume in
proteins and to identify positions likely to represent bind-
ing sites based upon the size, shape, and burial extent of
these volumes [35]. CastP server uses the weighted Dela-
unay triangulation and the alpha complex for shape mea-
surements. It provides identification and measurements of
surface accessible pockets as well as interior inaccessible
cavities, for proteins and other molecules [36].
Virtual screening of NCI diversity set II against Rab3A
protein
The ligand molecules of NCI diversity set II were obtained
for virtual screening in mol2 format from ZINC database,
provided by the Shoichet Laboratory in the Department of
Pharmaceutical Chemistry at the University of California,
San Francisco (UCSF). ZINC database is a central repos-
itory of commercially available compounds for virtual
screening synthesized by several organizations, which
include government organizations such as National Cancer
Institute (NCI) and several private players. It is usually
easier to retrieve data from ZINC in many different formats
and because it gives a unique id to each and every molecule
it is also easier to refer to them later in the analysis.
The NCI diversity set is a small library, ideal for
beginning a screening campaign. NCI diversity set II
consists of a collection of 1,364 synthetic small molecules
selected from the full NCI screening collection. It is a
complete dataset of manageable size with the currently
available computational resources. Moreover, NCI diver-
sity sets are specifically designed for cancer research. This
reduces the efforts for screening large compound libraries,
which may or may not be useful for the purpose.
Therefore, the NCI diversity set II compounds produced
by National Cancer Institute (NCI) and the molecular
database maintained by the ZINC were used in our
analysis.
Protein ligand docking
The ligand library was extracted from the ZINC database
(http://zinc.docking.org/). The shortlisted ligands were
subjected to further predocking preparations where
hydrogens were added followed by minimization and
optimization in OPLS_2005 force field. Finally, 10 con-
formations for each ligand were generated, and ready for
docking. The docking of ligand molecules to Rab3A
structure using GLIDE was performed and cross validation
was done using GOLD. GLIDE uses systematic and sim-
ulation method for searching the poses and ligand flexi-
bility. In a systematic method, it uses incremental
construction for searching, and its output GScore is an
empirical scoring function which is a combination of var-
ious parameters [37] The GScore is calculated in Kcal/mol
as:
G � Score ¼ H bond þ Lipo þ Metalþ Site
þ 0:130 Coulþ 0 : 065 vdW�BuryP�RotB
where H bond = Hydrogen bonds, Lipo = hydrophobic
interactions, Metal = metal-binding term, Site = polar
interactions in the binding site, vdW = Vander-Waals
forces, Coul = columbic forces, Bury P = penalty for
buried polar group, RotB = freezing rotable bonds.
Library of ligands were subjected to glide docking.
Since each ligand has 10 stereoisomers or conformations,
each conformation was first screened through the high
throughput virtual screening module of GLIDE. Finally,
Mol Biol Rep
123
the top five ranked ligands were selected according to
GLIDE and were docked again using GOLD docking
software to obtain consistent and improved results. GOLD
v4.0 [38] is an automated ligand-docking program that uses
a genetic algorithm to explore the full range of ligand
conformational flexibility, namely full acyclic ligand flex-
ibility and partial cyclic ligand flexibility, with partial
flexibility of the protein in the neighbourhood of the pro-
tein active site, and satisfies the fundamental requirement
that the binding of ligand must displace loosely bound
water. In GOLD docking, fifty independent docking runs
were performed for each molecule with default parameters.
Docking result analysis
A molecule was ranked relatively high if it scores well with
these two different methods (or scoring functions). These
methods have different search algorithms and scoring
functions. Hence, it was not possible to compare the fitness
scores of GOLD and GLIDE directly. For comparison and
validation of docking results we used X-Score v1.2.1, [39] a
consensus scoring function. X-Score calculates the negative
logarithm of the dissociation constant of the ligand to the
protein, 2log Kd, as the average of three scoring functions
(HPScore, HMScore and HSScore), and predicts the binding
energy (Kcal/mol) of the ligand. X-Score was reported to
have an accuracy of 62.2 kcal/mol relative to the actual
binding energies. For analysing the interactions of docked
protein–ligand complexes, the Ligplot programme [40] was
used to check the hydrogen bond and hydrophobic interac-
tions between receptor and ligand atoms within a range of
5 A�. Also PyMOL (V-1.3) [41] and Chimera (V-1.4.1) [42]
were used to visualize the interactions and to prepare figures
for top ranked molecules.
Results and discussion
Model building and protein structure validation
The structure of human Rab3A protein was determined by
using homology modeling protocol. BLASTP search was
performed against PDB with default parameters to find suit-
able templates for homology modeling. Based on the maxi-
mum identity with high score and lower e-value 1ZBD chain
A was used as the template for homology modeling. Sequence
alignment between the Rab3A and the template was generated
using CLUSTALW programme. The models generated were
subjected to structure validation and molecular dynamics and
best model was identified for further analysis. The predicted
structure of human Rab3A (Supplementary Fig. 1) shows
typical GTPase fold, comprising six beta strands surrounded
by five alpha helices (Fig. 1).
Following the structure prediction the models generated
were examined for their correctness in terms of stereo
chemical properties and three dimensional residue profile
using PROCHECK and Verfiy 3D respectively. For the
most accurate model it was found that the phi/psi angles of
94.1 % residues fell in the most favored regions (Supple-
mentary Fig. 2). The overall PROCHECK G-factor for the
homology modeled structure was -0.07. These statistics
confirmed good quality of the predicted model. High
quality of model is also confirmed from VERIFY 3D server
as 88.20 % of residues of modeled protein showed a score
higher than 0.2. The structural superimposition of Ca trace
of the target model after MD simulation over template
structure 1ZBD chain A (Fig. 2) resulted in a root mean
square deviation (RMSD) of 0.2 A (Z-score 177) using
DaliLite server. It indicates a valid structure of the model.
Based on these results, it was ascertained that the obtained
structure has reasonably good quality.
Fig. 1 The secondary structure elements in the corresponding region
of the protein sequence indicated
Fig. 2 Superimposition of Ca trace of human Rab3A protein and
1ZBD chain A (template)
Mol Biol Rep
123
Upon verification for physico-chemical properties using
various tools and molecular dynamics simulation the pre-
dicted model showed good enough structural properties for
further analysis. The structure was modeled with a very
high sequence identity with the template that ensures the
correct arrangement of the secondary structures and the
placement of the side chains.
Molecular dynamics simulations
The MD simulation of the modeled Rab3A protein struc-
ture was performed and the resulted trajectory was ana-
lyzed to study the motional properties of the protein. The
time evolution of root mean square deviation (RMSD) was
computed for the modeled structure of the protein by taking
the whole protein as initial structure. It is evident from the
Fig. 3 that RMSD increased slowly up to 300 ps and then
decreases up to 500 ps then again slightly increases up to
600 ps and attained the equilibrium. As the modeled
structure did not undergo any drastic motion beyond
600 psm, the MD simulation was performed only for 1 ns.
Based on intrinsic dynamics, structural stability and
improved relaxation of the modeled structure, the energy
(Fig. 4) of the energy minimized structure was also cal-
culated. The energy and RMSD calculations demonstrated
that the protein is highly conserved in nature i.e. the protein
is not much flexible. Root mean square fluctuation (RMSF)
indicates the flexibility of the protein. Figure 5 under-
standably indicates relatively high fluctuation in few resi-
dues at the N and C-terminal of the protein, these residue
can be noticed in the loop regions as shown in Fig. 1, rest
of the residues are found to be quite stable which are part
of the much conserved secondary structure elements. The
compactness of the model was also confirmed by calcu-
lating radius of gyration (Rg). Rg for the protein backbone
is under continuous decrease over the time indicating rel-
ative compactness of the structure (Supplementary Fig. 3).
Rg value lies between 1.55 and 1.50 nm across the time
scale in ps.
The possible binding sites of modeled Rab3A were pre-
dicted using PASS software and were compared with the
predictions from the CastP webserver and the template
structure. The consensus residues in the comparison were
considered as the active site lining residues. The volume
center of the cavity predicted by PASS was used as the grid
center for the docking analysis where as cavity lining resi-
dues were obtained through CastP results. The cavity lining
residues as found through CastP were SER16, SER17,
GLY19, LYS20, THR21, SER22, PHY25, SER31, PHY32,
THR33, PRO34, ALA35, PHY36, VAL37, SER38, THR39,
THR63, ALA64, GLY65, GLN66, LYS121 and LYS152 for
the most conserved active site of Rab3A protein.
Docking result analysis
We used GLIDE and GOLD docking programs to screen
1,364 molecules from the ZINC database against Rab3A to
identify potential inhibitor molecule as mentioned in the
Methods section. The top five ranking molecules based on
GLIDE scores are listed in Table 1. The GLIDE scores
Fig. 3 Trajectories of the overall Ca (RMSD) of the human Rab3A
protein structure with respect to the starting structure over 1,000 ps
MD simulation. The x axis represents the simulation time in
picoseconds. The y axis represents RMSD in nm unit
Fig. 4 Calculated energy versus time plot using GROMACS soft-
ware. The x axis represents the simulation time in picoseconds. The
y axis represents energy in nm unit. The average energy recorded was
-209,791 kJ/mol
Fig. 5 Residue-wise RMSF profiles of the human Rab3A protein
structure computed after stabilization of the RMSD trajectories. The x
axis represents the residue number. The y axis represents RMSF in nm
Mol Biol Rep
123
and X-Scores of these compounds have ranges of -6.65 to
-2.52 kcal/mol and -4.22 to -2.61 kcal/mol respectively.
The top ranking molecule (ZINC13152284) has a Glide
score of -6.65 kcal/mol and X-Score of -3.02 kcal/mol
with 03 hydrogen bonds and 09 hydrophilic contacts. For
each compound docked using the GLIDE and GOLD
programs, the X-Score (consensus scoring function) pro-
gram was used to calculate binding energies and listed in
Table 1 along with IUPAC name of the compounds and
their respective ZINC ID’s. Interactions (hydrogen and
hydrophobic) for the top five best ranking ligands based on
LIGPLOT showing hydrogen bonding and hydrophobic
contacts between the docked poses of protein and ligands
(Fig. 6).
GTP docking
Docking with GTP was carried out on the binding site of
Rab3A using GOLD software applying the parameters of
standard default setting with 50 genetic algorithm runs,
filtering poses based on GOLD fitness function. The
Rab3A-GTP complex has best GOLD fitness value of
77.73. To substantiate the estimations done by the GOLD
program, we used consensus scoring program X-Score. The
scoring schema used in the software X-Score computes a
binding score for a given protein–ligand complex structure.
The predicted binding energy for the docked complex was
found as 5.51 kcal/mol and predicted average Log Kd as
3.77, using X-Score program. Ligplot shows hydrogen
bonding (S16, S17, V18, G19, K20, T21, S22, S31, T33,
A35, S38, T39 and G65) and hydrophobic interacting
residue (F25, F32, P34, F36, V37, D62 and A64) with the
GTP ligand in the binding site of Rab3A protein (Fig. 7).
Variations in structure have been observed for different
GTPases [43]. There are more than 10 conserved features
in the Rab3 subfamily of proteins. Conserved domain
database was used in identifying critical variations, if any,
in human Rab3A protein [44]. The chemical binding site,
binds GTP and stabilizes the conformation of active Rab.
All the conserved residues in this motif, critical for func-
tion are intact in this motif. In Rabs the residues included in
this site are 32–38, 49, 50, 53, 55–56, 82, 136, 137, 139,
140 and 166–168. The effector interaction site in human
Rab3A is mapped onto the site that includes amino acid
residues 22, 56, 58–60, 75, 77, 84, 85, 88, 92, 94–97,
126–128, 184, 187.
The promotion of GDP bound Rab to GTP bound form
is catalyzed by Guanine nucleotide exchange factors. There
is little sequence similarity in the amino acid sequences of
Rab effectors, GEFs, and GAPs and regulators or effectors
for other GTPases. The putative GEF interaction site in
human Rab is conserved within the family and is formed by
53, 57–64, 71, 73. Guanine nucleotide dissociation inhib-
itors facilitate Rab recycling by masking C-terminal lipid
binding and helping in cytosolic localization. The GDI site,
prediction was based on interaction between S. cervisiae
YPT1 and its guanine nucleotide dissociation inhibitor.
This site includes 56, 57, 59, 77, 78, 85, 87, 89–91.
The Rab subfamily includes surface loops that undergo
conformational changes upon GTP binding, called switch I
and switch II. In Rab3A, the active conformation is further
stabilized by an extensive hydrophobic interface involving
conserved residues in both of switch regions. The switch I
in human Rab3A is represented by 48, 53–61, whereas
switch II is represented by residues 81, 83–93. The G-box
motifs involved in nucleotide binding are conserved in
human Rab3A. The walker A motif includes residues
30–37, whereas walker B motif includes 78–81.
Rab GTPases involved in the regulation of exocytic
vesicle trafficking pathways show a conserved set of amino
acid residues for active conformation of switch regions
[45]. Conserved serine residues along with others are
important for stabilizing the active conformation in Rab’s.
Serine 22 as described earlier is involved in the effector
Table 1 Top ranking ligands (molecules from Zinc database) after virtual screening against Rab3A using GLIDE and GOLD docking programs
S. no. ZINC ID IUPAC name of ligand Glide score
(Kcal/mol)
Glide X-score
(Kcal/mol)
Gold
score
Gold X-score
(Kcal/mol)
1 ZINC13152284 5-phenyl-2-[(2S)-5-phenyl-2,3-dihydro-1,3-benzoxazol-2-yl]
-2, 3-dihydro-1,3-benzoxazole
-6.659 -3.02 64.54 -3.12
2 ZINC13143009 (S)-[(2R)-piperidin-1-ium-2-yl]-[2-(trifluoromethyl)
-6-[4-(trifluoromethyl)phenyl]pyridin-4-yl]methanol
-2.647 -2.62 59.60 -2.48
3 ZINC00247785 3-hydroxy-N-(3-nitrophenyl) naphthalene-2-carboxamide -5.539 -4.22 55.29 -3.92
4 ZINC13143008 (S)-[(2S)-piperidin-1-ium-2-yl]-[2-(trifluoromethyl)
-6-[4-(trifluoromethyl)phenyl]pyridin-4-yl]methanol
-3.509 -2.61 55.70 -3.01
5 ZINC01705919 2-isoquinolin-1-yl-4-(4-methylphenyl)-5-phenyl-1,3-oxazole -2.521 -4.08 64.85 -3.97
cFig. 6 Molecular interaction plots showing interacting cavity lining
residues between human Rab3A receptor and NCI diversity set II
molecules (a) (b) (c) (d) (e)
Mol Biol Rep
123
KeyLigand bond
Non-ligand bond
3.0 Hydrogen bond and its length
His 53 Non-ligand residues involved in hydrophobiccontact(s)
Corresponding atoms involved in hydrophobic contact(s)
KeyLigand bond
Non-ligand bond
3.0 Hydrogen bond and its length
His 53 Non-ligand residues involved in hydrophobiccontact(s)
Corresponding atoms involved in hydrophobic contact(s)
KeyLigand bond
Non-ligand bond
3.0 Hydrogen bond and its length
His 53 Non-ligand residues involved in hydrophobiccontact(s)
Corresponding atoms involved in hydrophobic contact(s)
KeyLigand bond
Non-ligand bond
3.0 Hydrogen bond and its length
His 53 Non-ligand residues involved in hydrophobiccontact(s)
Corresponding atoms involved in hydrophobic contact(s)
KeyLigand bond
Non-ligand bond
3.0 Hydrogen bond and its length
His 53 Non-ligand residues involved in hydrophobiccontact(s)
Corresponding atoms involved in hydrophobic contact(s)
3.05
C8
C9 N1
C5
O1
C20
C10
C11 N2
C12
C19
C18 C17
C16
C13
C15
C14
C25
C21
C24
C23
C22
C4
C6
C3
C2
C1
C7
N
CA
CB
C
OG
O
Phe 25
Phe 36
Thr 33
Gly 19
Thr 21
Val 37
Ser 17
Phe 32Ser 31
A B
C
E
D
Lig 178
Ser 22
2.973.17
2.98
3.03
3.07
3.25
3.24
2.89
3.07
C11
O1 N1
C7
C12
C6
C8
C5
O4
C4
C3
C9
C2
C10
C1
C17 C13
C16
C15 N2
C14
O2
O3
N
CA
CB
C
CG
CD
CE NZ
O
N
CA
CB
C
OG1 CG2
O
N
CA
CB
C
OG
O
N
CA
C
O
N
CA
CB
C
CG1
CG2
O
N
CA
CB
C
OG
O
Phe 25
Phe 36
Thr 33
Lig 178
Lys 20
Thr 21
Ser 17
Gly 19
Val 37
Ser 22
3.11
3.04
2.80
3.30
C7 C8
C12
C4
C9
C10
C11
O1
N1
C13
C14
O2
N2
C20
C15 C19
C16
C18
C17
C21
C26
C22
C25
C24
C23
C3
C5
C2
C1 C6
N
CA
CB C
CG1
CG2
O
N
CA CB
C OG
O
N CA
CB
C
O
Phe 36
Phe 25
Thr 21
Lys 121
Gly 19
Lig 178
Val 37
Ser 22
Ala 35
3.05
3.22 C7
C8
N1
C6
C9 C10
C13
C11 C12
C14
O1 C15
N2
C16
C17
C18
C1
C5 C2
C3 C4
C19
F4
F5
F6
F1
F2
F3
N
CA
CB
C OG
O
N
CA
CB
C
CG
CD
CE
NZ
O
Phe 36
Phe 25
Gly 19
Thr 21
Thr 33
Lig 178
Ser 17
Lys 121
3.07
C7
C8
N1
C6
C9 C10
C13
C11 C12
C14
O1 C15
N2
C16
C17
C18
C1
C5
C2 C3
C4
C19
F4
F5
F6
F1
F2
F3
N
CA CB
C
CG
CD
CE
NZ
O
Phe 36
Phe 25
Ser 17
Gly 19
Thr 21Thr 33
Lig 178
Lys 121
Mol Biol Rep
123
binding site according to sequence homology studies.
Interestingly the molecular interaction plots of 3 NCI
diversity set molecules show involvement of the S22 res-
idue in hydrogen bonding with human Rab3A. The other
hits found in this study indicate potential binding sites in
the G1 box of human Rab3A that spans residues 30–37.
Conclusion
Although much of the physical entity in the protein struc-
ture is conserved in human Rab3A, many non random
substitutions in sequence within functionally important
regions are known. These variations could imply differ-
ences in functional properties that contribute to the speci-
ficity of interactions. With undisputed role in molecular
trafficking and regulation of cell cycle, the structure of
Rab3A provided in this study identifies new interactions
that are predicted to be important in the regulation of
GTPase activity. Apart from structural description of
Rab3A, elaboration of binding sites for inhibitors and
phosphorylation site in Rab3A provides us with an
opportunity to utilize binding pockets in targeted inacti-
vation of this protein. The top ranking molecule
(ZINC13152284) is a good starting point for further
development of strong inhibitors. Rab3A has also been
reported in malignant neuroendocrine cells and breast
cancer cells, which suggests its potential role in tumouri-
genesis. Rab3A could be an important target for cancer
therapeutics and our study can serve as a valuable reference
for structural and functional analysis.
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