CLINICAL & BASIC RESEARCH

SQU Med J, February 2011, Vol. 11, Iss. 1, pp. 83-94, Epub. 12th Feb 11
Submitted 19th Jun 10
Revision ReQ. 27th Sept 10, Revisions Recd. 1st Nov 10
Accepted 7th Nov 10

1Department of Biochemistry, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman; 2Department of 
Biochemistry, Sultan Qaboos University Hospital, Muscat, Oman.
*Corresponding Author email: yaj@squ.edu.om

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منال العامري٬ خالد الرصادي٬ رياض بيومي٬ ياجنافالكا بانيرجي




VIIaIn SilicoIn Silico
Proline bracket
 –Tco�ee
VIIaVIIa
VIIa
VIIa





In SilicoVIIa:مفتاح الكلمات

aBStract: Objectives: The coagulation cascade initiated during vascular injury prevents bleeding. Unwanted 
clot formation is however detrimental and requires the use of anticoagulants for prophylaxis and treatment. 
Anticoagulants targeting a specific step or an enzyme in the clotting process are most preferred as they minimise 
disadvantageous side-effects. A principal step in the discovery of novel anticoagulants encompasses the in silico 
design of potential leads. This study depicts the in silico design of peptide anticoagulants targeting coagulation 
factor VIIa. Methods: Applying the proline bracket rule and using various bioinformatics tools: the basic alignment 
search tool (BLAST) of National Center for Biotechnology Information; the T-coffee module provided by European 
Molecular Biology Laboratory-European Bioinformatics Institute, and several modules available on the ExPASy 
server, we designed five bivalent chimeric anticoagulants targeting factor VIIa, using factor VIIa inhibitors – 
hemextin A from Hemachatus haemachatus (African Ringhals cobra) venom and factor VIIa exosite-inhibitor 
peptide as templates. Six peptides were derived from hemextin A, which were concomitantly fused with factor 
VIIa exosite-inhibitor peptide intermediated by a polyalanine spacer, and analysed for structural stability using 
the SWISS-MODEL software developed at the Swiss Institute of Bioinformatics and WebLab ViewerPro (Version 
4.2). Results: Twelve chimeric peptides were obtained; only five exhibited stable structures in silico. Conclusion: 
The five peptides obtained are probable anticoagulant leads that should be further evaluated using suitable in vitro 
and in vivo assays. Further, this study shows how simple web-based modules can be used for the rational design of 
probable leads targeting specific physiological molecular targets.

Keywords: Anticoagulant; Factor VIIa; In silico drug design

In Silico Design of Novel Anticoagulant 
Peptides targeting Blood Coagulation 

Factor VIIa
Manal S Q Al-Amri,1 Khalid Alrasadi,2 Riad Bayoumi,1 *Yajnavalka Banerjee1

CLINICAL & BASIC RESEARCH

ADVanceS in KnoWleDGe
1. Five potential bivalent chimeric peptide inhibitors of coagulation factor VIIa have been designed, which should be assessed using in vitro 

and in vivo assays.



In Silico Design of Novel Anticoagulant Peptides targeting Blood Coagulation Factor VIIa

84 | SQU Medical Journal, February 2011, Volume 11, Issue 1

Blood coagulation is a physiological response to vascular injury in which zymogens of serine proteases present 
in the plasma milieu are sequentially activated 
culminating in the formation of the fibrin clot.1-3 
Coagulation factor VIIa (FVIIa), along with cofactor 
tissue-factor (TF), act as the prima ballerinas to 
initiate the coagulation cascade.4-6 The extrinsic 
pathway is responsible for initiating the clotting 
process whereas the intrinsic pathway propagates 
the process of coagulation. A comprehensive 
description of both these pathways is summarised 
in Figure 1.

Although coagulation reactions are pivotal for 
appropriate homeostasis, unwanted clot formation 
can mediate debilitating affects leading to  
thrombosis and associated disorders. Anti-
coagulants are pivotal for the prevention and 
treatment of thromboembolic disorders, and 
~0.7% of the Western population receives 
oral anticoagulant treatment.7 Coumarins and 
heparin are the most well known clinically used 
anticoagulants. Coumarins inhibit the activity 
of all vitamin K-dependent proteins, including 
procoagulants (thrombin, FXa, FIXa, and FVIIa) 
and anticoagulants (activated protein C and 
protein S). Heparin mediates its anticoagulant 
activity by enhancing the inhibition of thrombin 
and FXa by antithrombin III.8,9 The non-specific 
mode of action of these anticoagulants accounts 
for their therapeutic limitations in maintaining 
a balance between thrombosis and haemostasis. 
These limitations have provided the impetus for 
the development of new anticoagulants that target 
specific coagulation enzymes or a particular step 
in the clotting process.10,11 Because of its relatively 
low concentrations in blood (10 nM) and its pivotal 
role in the initiation of the coagulation reactions,12 
FVII/FVIIa is an attractive drug target for the 
development of novel and specific anticoagulant 
agents. 

So far, only two proteins that specifically inhibit 

the TF-FVIIa complex have been evaluated in 
clinical trials, viz. tissue factor pathway inhibitor 
(TFPI) and nematode anticoagulant peptide c2 
(NAPc2). TFPI is an endogenous inhibitor of this 
complex, whereas NAPc2 is an exogenous inhibitor 
isolated from canine hookworm (Ancylostoma 
caninum).13-15 Of these, only NAPc2 has future 
viability as a probable anticoagulant lead. In a phase 
II study, NAPc2 showed promise in preventing 
venous thromboembolism after elective knee 
replacement surgery.16,17 Because of the lack of 
natural inhibitors that specifically interfere with 
FVIIa activity, a number of artificial inhibitors 
have been designed and developed. They include 
proteins that block the association of TF and FVIIa, 
such as antibodies against TF and FVIIa, TFAA (a 
TF mutant with reduced cofactor function for FX), 
FFR-VIIa (inactivated form of FVIIa with 5-fold 
higher affinity for TF compared with native FVIIa), 
and peptides derived from TF and FVIIa.18-22 In 
addition, two series of peptide exosite inhibitors 
were selected from phage display libraries for their 
ability to bind to the TF-FVIIa complex.18,19 They 
bind to two distinct exosites on the serine protease 
domain of FVIIa and exhibit steric and allosteric 
inhibition.21Although both peptide classes are 
potent and selective inhibitors of the TF-FVIIa 
complex, they fail to inhibit 100% activity even at 
saturating concentrations. This is overcome either 
by the fusion of the two peptides,22 or by using a 
protease switch with substrate phage.20 A number 
of synthetic compounds have also been designed 
as active-site inhibitors of FVIIa as well as the TF-
FVIIa complex.23,24 A number of naphthylamidines 
have recently been reported to have FVIIa inhibitory 
activity. They were synthesised by the coupling of 
amidinobenzaldehyde analogs to a polystyrene 
resin. However, apart from inhibiting FVIIa activity, 
these synthetic compounds nonspecifically inhibit 
the activity of other blood coagulation serine 
proteases.25

In the past, we reported the identification and 

2. Depiction of a scheme to design rationally peptide based drugs using simple web-based software tools

Application to Patient Care
1. The designed peptides, if viable in clinical trials, will provide the clinical community with an arsenal of anticoagulants targeting clot 

initiation thereby helping in the treatment and prophylaxis of thromboembolic and associated disorders.
2. The study has translational significance since it provides a simple and viable strategy to design peptide based drugs targeting different 

diseases/disorders.



Manal S Q Al-Amri, Khalid Alrasadi, Riad Bayoumi and Yajnavalka Banerjee

Clinical and Basic Research | 85

in-depth characterisation of a novel FVIIa inhibitor, 
christened hemextin AB complex, from the venom 
of the African Ringhals cobra.26-29 This synergistic 
anticoagulant complex consists of two proteins, 
hemextin A (HA) and hemextin B (HB), both of 
which belong to the three-finger family of snake 
venom proteins [Figure 2]. Of the two subunits, 
HA individually possesses anticoagulant activity 
whereas HB is inactive. Unlike NAPc2, HA of 
hemextin AB complex does not use coagulation 
factor Xa as a scaffold for FVIIa inhibitory 
activity positing a very unusual mechanism of 
anticoagulation.29 Thus HA provides us with a 

novel and intriguing anticoagulant lead that can be 
further developed into an anticoagulant.

In this study, we report the design of a short 
chimeric anticoagulant mimetic (with probable 
FVIIa inhibitory function) using peptides derived 
from HA (by applying the proline bracket rule) 
and fusing them with an already characterised 
peptide FVIIa-exosite inhibitor,20 using simple web-
based bioinformatics. Only five of the 12 designed 
peptides exhibited structural stability and warrant 
assessment with regards to anticoagulant activity. 
This study therefore not only provided a foundation 
in the quest for the rational design of anticoagulants 

Figure 1: The current model of the blood coagulation cascade. There are two blood coagulation pathways, the contact 
activation or “intrinsic” pathway and the primary or “extrinsic” pathway. These multicomponent processes are illustrated 
as enzymes, inhibitors, zymogens, or complexes. The contact activation pathway has no known bleeding cause associated 
with it; thus, this pathway is considered accessory to haemostasis. On injury to the vessel wall, tissue factor, the cofactor 
for the extrinsic tenase complex, is exposed to circulating FVIIa and forms the extrinsic tenase. FIX and FX are converted 
to their serine proteases FIXa and FXa, which then form the intrinsic tenase and the prothrombinase complexes with their 
cofactors, respectively. The combined actions of the intrinsic and extrinsic tenase and the prothrombinase complexes 
lead to an explosive burst of the key enzyme thrombin (IIa). In addition to its multiple procoagulant roles, thrombin also 
can act in an anticoagulant capacity when combined with the cofactor thrombomodulin in the protein Case complex. 
The product of the protein Case reaction, activated protein C (APC), inactivates the cofactors FVa (cofactor for FXa) and 
FVIIIa (cofactor for FIXa). The cleaved species, FVai and FVIIIai, no longer support the respective procoagulant activities. 
Once thrombin is generated through procoagulant mechanisms, thrombin cleaves fibrinogen (releasing fibrinopeptides 
A and B [FPA and FPB]) and activates FXIII to form a cross-linked fibrin clot. Thrombin–thrombomodulin also activates 
a thrombin activate-able fibrinolysis inhibitor that slows fibrin degradation by plasmin. The procoagulant response is 
downregulated at various stages by the stoichiometric inhibitors, tissue factor pathway inhibitor (TFPI) and antithrombin 
III (AT-III). TFPI serves to attenuate the activity of the extrinsic tenase trigger of coagulation. AT-III directly inhibits 
thrombin, FIXa, and FXa. The accessory pathway provides an alternate route for the generation of FIXa. Thrombin 
has also been shown to activate FXI. The fibrin clot is eventually degraded by plasmin yielding soluble fibrin peptides.



In Silico Design of Novel Anticoagulant Peptides targeting Blood Coagulation Factor VIIa

86 | SQU Medical Journal, February 2011, Volume 11, Issue 1

specifically targeting FVIIa, but also depicted a 
scheme that can be utilised in the rational design of 
drug leads using web-based bioinformatics.

Methods
The complete sequence of HA protein had been 
determined earlier using Edman degradation pro-
tein chemistry, and is depicted below (using the 
single letter amino acid code):  L KC H N K LV P-
F L S K T C P E G K N L C Y K M T M L K M P K I P I -
K R G C T D A C P K S S L LV K V V C C N K D K C N .
The sequence of the 26-mer FVIIa-exosite inhibi-
tor peptide was obtained from the literature,22 and 
is as follows: EEWEVLCWTWETCERGEGVEEL-
WEWR.

The various software employed in this study are 

freely available on the Internet and do not require 
special access to any paid database or server. Most 
of these modules are Windows based, however 
some operate at an optimum on a LINUX platform.

Sequence alignment involving HA involved a 
detailed search of homologous sequences from the 
National Center for Biotechnology Information 
protein database,30,31following which the basic 
alignment search tool (BLAST)32-34 was employed. 
The sequence alignment of HA was carried out 
by looking at the position of the cys residues 
using the online T-coffee module provided by 
the European Molecular Biology Laboratory-
European Bioinformatics Institute.35 In order to 
look at the various specifics of the amino acid 
sequence, appropriate modules available on the 
ExPASy server were used.36 In order to model 

Figure 2: Analysis of primary structure of HA. 1) Comparison of amino acid sequence of hemextin A with other 
sequences of the three-finger toxin family. The conserved cysteine residues are indicated in black. The four conserved 
disulfide linkages and the segments contributing to the three loops are outlined. Comparison were made with the 
following sequences: cytotoxin 1, cytotoxin 2, toxin 9B, weak toxin CM-1B, weak toxin CM-1C, toxin II, toxin IV are 
from Hemachatus haemachatus (African Ringhals Cobra); carditoxin γ from Naja nigricollis (Black spitting cobra); 
carditoxin A3 from Naja atra (Taiwan cobra); fasciculin from Dendroaspis angusticeps; mambin from Dendroaspis 
jamesoni; calciseptin from Dendrosaspis polylepsis; muscarinic toxin 2 from D. angusticeps; erabutoxin b from Laticauda 
semifasciata. 2) Three-dimensional structural similarity among three-finger toxins from snake venoms A) Erabutoxin 
a (1QKD); B) α-bungarotoxin (2ABX); C) cardiotoxin V4 (1CDT); D) κ-bungarotoxin (1KBA); E) candoxin (1JGK); F) 
fasciculin 2 (1FAS); G) muscarinic toxin MT-2 (1FF4; R Menez et al., pers. comm., 2002); (H) FS2 toxin (1TFS). Note all 
these ‘sibling’ toxins share a similar structural fold; three β-sheeted ‘fingers’ start from the core. These β-sheeted loops are 
numbered right to left as loop I, II and III, respectively. However, these toxins differ from each other in their biological 
activities.



Manal S Q Al-Amri, Khalid Alrasadi, Riad Bayoumi and Yajnavalka Banerjee

Clinical and Basic Research | 87

the three-dimensional structures of the HA and 
chimeric peptides, the sequences of the proteins 
were submitted to the SWISS-MODEL developed 
by the Protein Structure Bioinformatics group at 
the Swiss Institute of Bioinformatics (SIB) and the 
Biozentrum at the University of Basel.37 

The raw data obtained were then analysed 
using the WebLab ViewerPro (Version 4.2) 
(Accelrys, Inc. San Diego, CA, USA). The surface 
charge distribution of the modeled as well solved 
structures obtained from the protein data bank 
were analysed using the Molecular Graphics 
Laboratory Tools (MGLT) package obtained from 
The Scripps Research Institute (TSRI) molecular 
modeling server (TSRI, La Jolla, CA, USA) The 
Python Molecular Viewer (PMV) of the MGLT 
package was used predominantly in this study.38,39

Results
Our finding on the alignment of HA, was that 
HA belongs to the three-finger family of snake 
venom proteins [Figure 2A] and not to the family 
of snake venom serine protease inhibitors which 
are Kunitz type inhibitors with a very different cys 
bonding pattern. Proteins belonging to this group 
exhibit a characteristic β-sheet structure [Figure 
2B]. In order to design short peptides rationally 
from HA, we used the proline bracket rule.40,41 In 
this rule, unique physicochemical properties of 
proline, the most commonly found imino acid 
in proteins, are used for the prediction of active 

sites. The distinct properties of proline residues 
are due to the bulky pyrrolidine ring and the lack 
of protons important for hydrogen bond formation 
in the α-helix and β sheet. Proline residues are the 
common structural elements found in the flanking 
segments of protein-protein interaction sites and 
they enhance the protein-protein interactions. The 
proline residues most likely reduce the number 
of possible conformations due to their ability to 
constrain the conformation of the neighbouring 
residues. The short segments of 3-7 residues 
flanked by proline residues have been identified 
as the potential protein-protein interaction sites 
directly from the amino acid sequence of the 
protein.  A case in point is that incorporation of 
proline residues on either or both sides of the 
interaction site of an antiplatelet peptide (peptide 
that prevents platelet aggregation), IARGDMNA, 
enhances the antiplatelet activity to approximately 
the same extent (1.5- to 2.5-fold). The incorporation 
of proline residues on both sides enhances the 
activity by 7- to 13-fold. This enhancement of the 
biological activity of the peptide is probably due to a 
reduction in the number of possible conformations 
of the peptide, without introducing the rigidity 
that would accompany cyclization.40 Therefore we 
hypothesised that proline residues will be present 
on the flanking regions of the probable interaction/
active sites. Based on this premise, we designed the 
six short peptides from HA [Figure 3]. We also kept 
two amino residues beside each proline residue 
on each side to provide structural stability to the 

Figure 3: Peptides derived from HA. Six short peptides were derived from HA using the proline bracket rule. We kept 
two amino acids on the flanking region of each proline residue in order to provide structural stability to the peptide.



In Silico Design of Novel Anticoagulant Peptides targeting Blood Coagulation Factor VIIa

88 | SQU Medical Journal, February 2011, Volume 11, Issue 1

designed peptide.

For the modelling of the HA 3D-structure, the 
sequence alignment showed that HA has conserved 
cys residues with other members of the three-
finger toxin (3-FTX) family, which indicated that 
HA is a 3-FTX. Earlier studies involving circular 
dichroism spectroscopy also have supported this 
finding.26 In order to confirm further that HA has 
a similar architecture to three-finger proteins, 
we modelled the HA. As observed in Figure 4 A, 
it has a characteristic fold of a three-finger toxin, 
with anti-parallel β-sheets. Further, we mapped the 
surface charge distribution of HA using PyMOL 
molecular viewer (PMV) [Figure 4B].  HA shows a 
predominance of blue or positively charged patches, 
from which it can be concluded that HA is a basic 
protein and therefore will have a higher propensity 
of binding to negatively charged regions on its 
corresponding target molecule. This observation 
was further confirmed by the calculating the 
theoretical PI for HA, which was found to be 9.34, 
confirming that the protein is of basic nature.   

In order to predict the binding sites of HA on 
FVIIa, the structure of FVIIa was modelled using 
the X-ray crystallographic structure of TF-FVIIa as 
a template (PDB ID 1DAN).42 As shown in Figure 
5,  FVIIa consists of two chains, the heavy and 
the light chains. The heavy chain consists of the 
protease domain of the enzyme, whereas the light 

chain consists of two epidermal growth-factor-like 
domains and a γ-carboxyglutamic acid domain. HA 
does not bind to the light chain of FVIIa (data not 
shown) and therefore its binding site is located on 
the heavy chain. The heavy chain of FVIIa consists of 
a patch of negatively charged residues (highlighted 
in yellow in Figure 5) and HA, being predominantly 
basic in nature, will have its binding/interaction site 
localised to this acidic patch. Therefore, peptides 
derived from HA are supposedly going to bind to 
this acidic or negatively charged patch on FVIIa.

As to the design of chimeric peptides, since 
peptides derived from HA will bind to the acidic 
patch on the FVIIa molecule, we fused these HA 
derived peptides with another peptide that binds 
to the basic patch on the heavy chain. This peptide 
has already been characterised with regards to the 
structure-function details of the peptide.20,21 The 
binding site of the peptide on the FVIIa heavy 
chain is shown in Figure 6 A and was determined 
using X-ray crystallography (PDB ID 1JBU). The 
peptide is inherently highly acidic in nature and 
binds to a predominantly positively charged region 
on the FVIIa heavy chain, as shown in the surface 
potential plot in Figure 6 B. HA derived peptides 
were fused with this FVIIa exosite-inhibitory 
peptide. A spacer consisting of polyalanine residues 
was introduced between the HA derived and FVIIa 
exosite-inhibitory peptides in order to maintain 

Figure 4: Modeled three dimensional structure of HA. A) The ribbon representation of the three-dimensional structure of 
HA (Red). The amino acid residues are represented in line model with their corresponding one letter code. Note: HA exhibits 
a characteristic three-finger structure and is predominantly β-sheeted like other members of the three-finger family(Figure 
2B). B) Surface potential calculation of HA using PyMOL molecular viewer. HA is predominantly basic as revealed by the 
scale on top of the figure (blue represents positively charged patches where as red represents negatively charged patches).



Manal S Q Al-Amri, Khalid Alrasadi, Riad Bayoumi and Yajnavalka Banerjee

Clinical and Basic Research | 89

the distance between the acidic and the basic 
patches. The designed chimeric peptides are shown  
in Table 1.

The structural stability of the chimeras was 
assessed by modelling their structure in a way similar 
to that used for HA. Only five of the 12 chimeric 
proteins were found to be structurally stable [Figure 
7A-E], whereas the 3D-structure modelling of the 
other peptides failed, thus indicating their structural 
instability.  

Discussion
In the present study, we designed bivalent 
anticoagulant peptides targeting coagulation FVIIa, 
the clotting factor responsible for the initiation of 
the clotting reactions, employing simple web-based 
bioinformatics. For our study, we used two different 
proteins as templates: HA, a FVIIa inhibitor isolated 
and characterised from the venom of Hemachatus 
haemachatus (African Ringhals cobra), and factor 
VIIa exosite-inhibitor peptide which is a synthetic 
peptide identified in phage-display libraries.

The complete sequence alignment of HA 
revealed that it belongs to the three-finger family 
of snake venom proteins. This family of proteins is 
found only in the venoms of elapids (cobras, kraits 

and mambas) and hydrophids (sea snakes) and not 
those of vipers and crotalids (rattlesnakes). They 
contain four or five disulphide bridges, of which 
four are conserved in all members. Accordingly, 
all proteins of this family show a similar pattern of 
protein folding: three β-stranded loops extending 
from a central core containing the four conserved 
disulphide bridges [Figure 2]. Despite the overall 
similarity in structure, these polypeptides differ 
from each other in their biological activities. 
However, because of their well folded and compact 
structure, proteins belonging to this family are 
attractive as drug leads (if the parent protein is 
pharmacologically active) or are used as molecular 
scaffolds in the peptide based drug design.43 For our 
study one of the principal reasons for choosing HA 
was its well-folded and compact structure.

The idea of designing a bivalent inhibitor 
for a coagulation serine protease was first 
successfully implemented in case of thrombin,  
where two peptides acetyl-(d)F-P-R-P-Q-S-H-
N-D-G-D-F-E-E-I-P-E-E-Y-L-Q (binding to the 
catalytic active site) and (d)F-P-R-P-G-G-G-G-N-
G-D-F-E-E-I-P-E-E-Y-L (binding to the exosite of 
thrombin) were covalently linked, and the resultant 
peptide mimicked the activity of hirudin and had 
higher inhibitory potency than the individual 

Figure 5: Modeled three dimensional structure of FVIIa. FVIIa consists of heavy and light chains. 
The model was obtained from the solved structure of the TF-FVIIa complex (PDB ID 1DAN). The 
negatively charged cluster on the FVIIa molecule localized on the heavy chain is highlighted in yellow.



In Silico Design of Novel Anticoagulant Peptides targeting Blood Coagulation Factor VIIa

90 | SQU Medical Journal, February 2011, Volume 11, Issue 1

peptides.44 Some bivalent peptides, although having 
weak binding properties, have been derived from 
the activation sequences of thrombin-activated 
receptors, also referred to as protease-activated 

receptors (PARs). These peptides carry the 
LDPR sequence and binding motifs targeting the 
fibrinogen-recognition exosite of thrombin.45,46 
The essence of designing such inhibitors is to use 
peptides which are structurally stable and do not 
have overlapping binding sites.

In our study, we targeted coagulation FVIIa, 
since this serine protease is responsible for the 
initiation of the clotting cascade. Therefore, 
inhibiting the activity of this protein will inhibit the 
cascade in its initial stages. Also the levels of this 
protein in blood is low in comparison to some of the 
other coagulation serine proteases, necessitating 
the use of low levels of the designed anticoagulant, 
a key factor involved in the success of any drug.

Based on the surface charge calculations [Figure 
4 B], it is pertinent that HA is a basic protein and 
therefore peptides derived from it will bind to 
predominantly negatively charged regions on its 
target molecule. Also, previous studies have shown 
that HA is a specific inhibitor of FVIIa.29 Based 
on this premise we identified the regions of FVIIa 
which have a high density of negatively charged 
clusters. Such clusters exist in both the heavy and 
light chains of the FVIIa molecule. However, these 
clusters in the light chain are not accessible to HA 

since they are involved in co-factor (TF binding) 
as revealed in the crystallographic structure solved 
by Banner et al.42 and later confirmed by us (data 
not shown). Therefore, we localised the negatively 
charged cluster on the heavy chain of the protein 
using the solved structure of TF--FVIIa (PDB 
ID 1DAN) as the model [Figure 5, highlighted in 
yellow].

In order to derive peptides from HA we used 
the proline bracket rule [Figure 3] (see above with 
regards to the details). In our next step, we needed 
to select an FVIIa-inhibitory peptide whose binding 
site will not overlap with HA derived peptides. 
After a literature search we found a peptide 
( E E W E V L C W T W E TC E R G E G V E E LW E W R ) 
which is predominantly negatively charged (PI = 
3.98) as the ideal candidate to be used for the design 
of the chimera. Firstly, because of its inherent 
acidic nature, it will be involved in binding to a 
patch of residues which are positively charged 
and secondly [Figure 6 A and B], the presence of a 
disulfide bond in the peptide guarantees its having 
a well defined fold. Since HA derived peptides are 
positively charged and might interact with the 
FVIIa-inhibitory peptide, we introduced a spacer 
of nine alanine residues in between them. The 
designed chimeras were then assessed for structural 
stability using the appropriate tools mentioned in 
the Methods section. Only five of the designed 
12 chimeras were found to be structurally viable 

Figure 6: Binding site of the FVIIa-inhibitory peptide on FVIIa molecule. A) The ribbon representation of the 
FVIIa heavy chain molecule (blue) in complex with the FVIIa-inhibitory peptide (green) B) Surface charge 
distribution of the heavy chain and the inhibitory peptide. Note that the inhibitory peptide is negatively charged 
binding to a positively charged region on the FVIIa molecule keeping the HA binding site on FVIIa molecule free.



Manal S Q Al-Amri, Khalid Alrasadi, Riad Bayoumi and Yajnavalka Banerjee

Clinical and Basic Research | 91

[Figure 7 A-E]. One of the intriguing highlights of 
the study was that the designed structurally viable 
peptides had the positively and negatively charged 
residues separated as in observed in Figure 7. 

Also, we designed various combination of 
chimeras where the HA derived peptides were 
placed at the amino-terminal as well as the carboxy-
terminal ends. Switching of ends was found to affect 
the stability of the designed chimera. As shown 
in Table 1, for combination 3, the presence of the 
FVIIa-inhibitory peptide on the carboxy-terminal 
end leads to structural instability of the designed 
chimera, whereas its presence on the amino-
terminal does not affect its structural viability.

These putative bivalent anticoagulants still need 
to be evaluated in various in vitro and in vivo assays 
before they can be assessed in clinical trials. One 
of the advantages of the current strategy is that it 
can be successfully applied without the involvement 
of large financial commitment by researchers with 
limited knowledge of bioinformatics. However, 
the designed chimeric anticoagulant, although 
structurally viable, might lose its activity since the 
fold it attains might not favour its binding to its 
specific interaction sites.   

Conclusion

Table: 1. Designed Chimeric Peptides and Result of Structural modeling

Hemextin A (peptide) Terminal 
link

Chimera (HA p + Lazarus p) Structure 
Analysis

1.
A- LVPFLSKTAPEG
 

B- LVPFLSKTAPEG

COOH- 
terminal

NH2- 
terminal

LVPFLSKTAPEG + 
EEWEVLCWTWETCERGEGVEEELWEWR

EEWEVLCWTWETCERGEGVEEELWEWR 
+ LVPFLSKTAPEG

No recognisable 
fold was obtained

No recognisable 
fold was obtained

2.
A- TCPEGKNLCYKMTMLKMPKI
 

B- TCPEGKNLCYKMTMLKMPKI

COOH- 
terminal

NH2- 
terminal

TCPEGKNLCYKMTMLKMPKI + 
EEWEVLCWTWETCERGEGVEEELWEWR

EEWEVLCWTWETCERGEGVEEELWEWR 
+ TCPEGKNLCYKMTMLKMPKI

No recognisable 
fold was obtained

No recognisable 
fold was obtained

3.
A- KIPIKRGCTDACPKS
 
 
B- KIPIKRGCTDACPKS

COOH- 
terminal
 
NH2- 
terminal

KIPIKRGCTDACPKS + 
EEWEVLCWTWETCERGEGVEEELWEWR
 
EEWEVLCWTWETCERGEGVEEELWEWR 
+ KIPIKRGCTDACPKS

No recognisable 
fold was obtained
 
Distinct fold was 
observe wafter 
modeling

4.
A- TCPEGKNLCYKMTMLKMCKIPIK
 

B- TCPEGKNLCYKMTMLKMCKIPIK

COOH- 
terminal

NH2-
terminal

TCPEGKNLCYKMTMLKMCKIPIK + 
EEWEVLCWTWETCERGEGVEEELWEWR

EEWEVLCWTWETCERGEGVEEELWEWR 
+ TCPEGKNLCYKMTMLKMCKIPIK

Distinct fold was 
observe wafter 
modeling
Distinct fold was 
observe wafter 
modeling

5.
A- LVPFLSKTCCEGKNLCYKMTMLKMPKI
 

B- LVPFLSKTCCEGKNLCYKMTMLKMPKI

COOH- 
terminal

NH2- 
terminal

LVPFLSKTCCEGKNLCYKMTMLKMPKI 
+ EEWEVLCWTWE 
TCERGEGVEEELWEWR
EEWEVLCWTWETCERGEGVEEELWEWR 
+ LVPFLSKTCCEGKNLCYKMTMLKMPKI

Distinct fold was 
observe wafter 
modeling
Distinct fold was 
observe wafter 
modeling

6. 
A- KMPKICIKRGCTDACPKS
 

B- KMPKICIKRGCTDACPKS

COOH- 
terminal
 
NH2- 
terminal

KMPKICIKRGCTDACPKS + 
EEWEVLCWTWETCERGEGVEEELWEWR
 
EEWEVLCWTWETCERGEGVEEELWEWR 
+ KMPKICIKRGCTDACPKS

No recognisable 
fold was obtained
 
No recognisable 
fold was obtained

Notes: + denotes the nine alanine spacer; HA p denotes the peptide fragment derived from hemextin A; Lazarus p denotes the peptide designed at 
Genentech CA, USA by Dr Bob Lazarus and his colleagues.



In Silico Design of Novel Anticoagulant Peptides targeting Blood Coagulation Factor VIIa

92 | SQU Medical Journal, February 2011, Volume 11, Issue 1

In summary, we designed bivalent inhibitors 
for FVIIa using simple bioinformatics. The five 
structurally viable inhibitors will be assessed for 
functional potency using appropriate in vitro and in 
vivo assays/experiments in the near future. Although 
a great deal of effort was involved in the analysis of 
data and literature search during the study, it was 
relatively inexpensive since all the tools used were 
freely available on the Internet. Further, a similar 
strategy can be used for designing peptide based 
drugs for other physiological target molecules. Thus 
this study introduces a novel paradigm in strategy 
design for drug-leads.

c o n f l i c t o f i n t e r e s t
The authors reported no conflict of interest.

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