Identification of Neuroactive Peptide from Venomous Species
using Structural Analysis: A Possible Neuronal Therapeutic Candidate
Chandrappa Chinna Poojari1, Sanjana1,
Levin Anbu Gomez2, Saba Shirin3,4, Ankit Kumar5,
Gangadahosahalli Krishnegowda Puneetha6, Praveen Kumar Guttula7,
Rajkumar Sekar8, Prathap Somu9*, Akhilesh Kumar Yadav10,11*
1Department
of Microbiology, Shridevi Institute of Allied Health Sciences, Tumakuru,
572106, India.
2Division
of Biotechnology, School of Agricultural Sciences, Karunya Institute of
Technology and Sciences, Karunya Nagar, Coimbatore, 641114, India.
3Department
of Environmental Science, School of Vocational Studies and Applied Sciences,
Gautam Buddha University, Greater
Noida, 201312, India.
4Department
of Mining Engineering,
Indian Institute of Technology
(Banaras Hindu University), Varanasi, 221005, India.
5Lohum
Cleantech Pvt. Ltd., Kasna Industrial Area, D-184, Site V, Greater Noida,
201306, India.
6Department
of Botany, Yuvaraja’s College, University of Mysore, Mysuru, 570005, India.
7Sprott
Centre for Stem Cell Research, Ottawa Hospital Research Institute, Ottawa, ON
K1Y 4E9, Canada.
8Department
of Chemistry, Karpaga Vinayaga College of Engineering and Technology,
Chengalpattu, 603308, India.
9Department
of Biotechnology and Chemical Engineering,
School of Civil and Chemical
Engineering, Manipal University Jaipur, Jaipur, 303007, India.
10Department
of Environmental Engineering and Management,
Chaoyang University of Technology,
Taichung, 413310, Taiwan.
11Department
of Bioengineering, Saveetha School of Engineering,
Saveetha Institute of Medical and
Technical Sciences, Chennai 602105, India.
*Corresponding Author E-mail:
yadavbasti@gmail.com, prathaps1987@gmail.com
ABSTRACT:
Neuroactive peptides derived
from venomous species have proven to be used as a lead compound for treating neurological
diseases. In the present study, the primary structure of the peptide toxins of snakes,
scorpions, spiders, cone snails, honey bees, and sea anemones was recovered from
different toxin databases. The 3-D structures of the peptide toxins were analyzed
with respect to secondary structural elements such as cysteine patterns and disulfide
connectivity’s using PYMOL. Their interaction with ion channels/receptors was studied
because of its pharmacological importance. The toxins retrieved were found to have
– C–Xn–C–Xn–CC–Xn–C–Xn–C-- cysteine pattern for n≥1 that was the same --C---C---CC---C---C—
cysteine pattern of ω-conotoxin and hanatoxin, but with a varying intervening
non-cysteine residue between cysteines. Hence, these provide insight for structure-based
drug design using these peptide toxin scaffolds. Given the optimal molecular weight
and specificity of peptides compared to conventional small molecule drugs, peptides
are considered future next-generation drug candidates.
KEYWORDS: Venomous species, Peptide toxin, Neurological disorders,
Intramolecular disulfide folds, Ion channels/receptors.
INTRODUCTION:
Diverse modes have evolved to achieve fundamental aspects
of adaptation in life, feeding, and defense. One of the critical modes of adaptation
is through chemical communication. Like plants use alkaloids and microorganisms
use secondary metabolites, certain venomous animals such as spiders, scorpions,
snakes, sea anemones, and cone snail uses peptide toxins to interact with the surrounding
environment. The reason why these species to have peptide toxins in the venom is
for prey immobilization or defend them by targeting the neuronal circuits of the
fatalities 1-5. Dissection of venom of cone snail alone has given valuable
lead compounds for therapeutics. As a variety of defense strategies, the venom of
venomous species contains a rich collection of potential pharmacological molecules
to treat neurological disorders. Decades of research on the structural and functional
characterization of venom peptides have provided a lot of information on the use
of peptide toxins in the treatment of various neurological disorders. ω-conotoxin
MVIIA derived from Conus magus is being used for the treatment of intractable pain
under generic name Prialt. Peptide toxins not only directly serve as drugs for the
treatment of disorders, but also serve as templates for the design of drug candidates.
The drug ‘captopril’ was designed using snake toxin 6 Precise analysis of the structural features of peptide
toxins provides information to use peptide toxins as templates for the design of
drug candidates. This introductory section gives a brief overview of sequences,
structures, and functions of peptide toxins derived.
The biologically active components of venom are peptide
toxins, composed of acyclic and disulphide bonded peptides 7-9. The length of the peptide varies from 8 to 80 residues
and contains multiple disulfide bonds, which vary from 1-5 intramolecular disulfide
bonds. The characteristic feature of peptide toxins in the presence of multiple
numbers of intramolecular disulfides along with a high degree of post-translational
modifications 10. Peptide toxins can be broadly classified based on the
number of intramolecular disulfides present in the given sequence, as one disulfide,
two disulfides, three disulfides, four disulfides and more disulfides containing
peptide toxins. Interestingly, the structural diversity of peptide toxins is due
to intramolecular disulfide bonds. As the number of disulfides increases, the peptide
toxins cysteine frameworks and disulfide isomers also increases tremendously, importing
different structures from the peptide toxins. ‘cysteine pattern’ or ‘cysteine framework’
indicates cysteine residues arrangement where cysteine residues are present in even
number in the given sequence. Specific disulfide connectivity between participating
cysteine residues in the sequence results in unique disulfide isomers 11. For example, peptide toxins may have the cysteine pattern
–C1--Xn—C2--Xn—C3C4--Xn—C5--Xn—C6—and have selective disulfide connectivity between
C3-C6, C2-C5, and C1-C4.
Change in disulfide connectivity imparts altered 3D-structure
to the identical polypeptide. Interestingly, similar cysteine patterns and disulphide
connectivities are observed across different venomous species. For example, —C1
— Xn —C2 — Xn — C3 — Xn — C4 — cysteine pattern has been observed in cone snail’s
ω- conotoxin, scorpion’s ω-hemotoxin and sarafotoxin derived from snakes
with the disulfide connectivity at C1 - C3 and C2 - C4.
Publically accessible and readily reachable toxin databases
for toxin of various venomous animals annotation ConoServer 12, Uniprot 13, ArachnoServer 14, and Animal toxin database 15 have categorized and catalogued peptide toxins into different
superfamilies based on signal sequence and cysteine pattern of peptide toxins. These
databases readily provide information about the sequence, structure, and function
of peptide toxins and thus serve as a platform for computational analysis of peptide
toxins. In general, depending on the research project, the source of 3D structures
used for finding cysteine patterns can vary. High-resolution 3D structures of proteins
and peptides can be obtained using experimental techniques such as X-ray crystallography
and NMR spectroscopy, and these structures are frequently stored in the PDB database.
Protein and peptide structures can also be predicted using
computational approaches such as AlphaFold. Although predicted structures may not
be as accurate as experimentally established structures, they can provide useful
insights into the structural characteristics of proteins and peptides.
X-ray crystallography, NMR spectroscopy, and cryogenic
electron microscopy (Cryo-EM) are a few structural analysis methods that can be
utilised to understand the three-dimensional (3D) structures of neuroactive peptides
from venomous species. Once a neuroactive peptide's structure is understood, it
can be used as a model to create new treatment candidates with increased activity
and selectivity. The computer-aided software techniques in simplifying and deriving
fruitful information has already proven and established independent discipline of
‘Bioinformatics’ in the field of biological sciences. The current work utilized
powerful bioinformatics tools in deriving useful information from naturally designed
neuroactive peptide toxins, which may serve as guiding principles for ‘de novo’
designing of novel molecules for the treatment of neurological diseases.
MATERIALS AND METHODS:
Analysis of peptide toxins:
Analysis of peptide toxins deposited in Animal
toxin annotation project of Uni Prot :
UniProt (http://www.uniprot.org/program/Toxins) has an
extensive data of the manually annotated venomous species peptide toxins. UniProt
database comprises records of more than 5703 manually curated peptide toxins. Each
of the toxin entry contains information about amino acid sequence, gene sequence,
3D structure, and biological target. Entries in the database have been scrutinized
manually based on the information concerning disulfide connectivity, cysteine patterns,
number of disulfide bonds, structural fold, and target. Cysteine patterns have been
determined through the analysis of the amino acid sequence of the toxin. The number
of intervening amino acids has been studied to deduce the pattern eventually. For
example, the amino acid sequence of ‘Maurocalcin’ is GDCLPHLKLCKENKDCCSKKCKRRGTNIEKRCR.
The cysteine pattern of ‘Maurocalcin’ is ----X2-----C-----X6-------C----X5----CC----X3-----C-----X10-----C---X1
3D-fold of the peptide toxin has determined by identifying the secondary structural
features such as alpha-helix and beta-sheet. Finally, the identification of biological
targets for each peptide toxins has been performed.
Analysis of peptide toxins deposited in Cono Server:
ConoServer (www.conoserver.org/) has an extensive collection
of peptide toxins derived from Cone snails. It is a dedicated database for conotoxins.
Nearly all the conotoxins that were characterized thus far are available in ConoServer.
The database contains the amino acid sequence, gene sequence, 3D-structure, and
biological target of conotoxins. The sequences of conotoxins have been manually
verified, and information was collected concerning disulfide connectivity, cysteine
patterns, number of disulfide bonds, structural fold, and target. Interestingly,
the database categorized conotoxins based on cysteine pattern, gene superfamilies,
and pharmacological target. Cysteine patterns were determined through the analysis
of the amino acid sequence of conotoxin, and also, the number of intervening amino
acids was found, and eventually, the pattern was deduced. For example, the amino
acid sequence of ‘α-conotoxin’ is DECCPDPPCKASNPDLCDWRS. The cysteine pattern
of ‘α-conotoxin’ is ----X2-----CC-----X4-------C----X7---- C---X4 3D-fold of
the peptide toxin was studied by identifying the secondary structural features such
as alpha-helix and beta-sheet. Biological targets were analyzed for each of the
peptide toxins.
Analysis of peptide toxins deposited in Aracno
Server:
AracnoServer (http://www.arachnoserver.org/)has an extensive
information about the peptide toxins derived from spiders and a dedicated database
for spider toxins. Nearly all the spider toxins that are characterized thus far
are available in AracnoServer. The database contains the amino acid sequence, gene
sequence, 3D-structure, and biological target of spider toxins. Sequences of spider
toxins were manually verified, and information was collected corresponding to the
number of disulfide bonds, cysteine patterns, disulfide connectivity, structural
fold, and target. Interestingly, the database categorized spider toxins based on
the cysteine pattern and pharmacological target. Cysteine patterns were determined
through the analysis of the amino acid sequence of conotoxin. The number of intervening
amino acids was determined, and eventually, the pattern was deduced. For example,
the amino acid sequence of ‘Hanatoxin’ is CLPPGKPCYGATQKIPCCGVC-SHNNCT. The cysteine
pattern of ‘Hanatoxin’ is ----C-----X6-------C----X8----CC----X2-----C-----X4-----C---X1..
3D-fold of the peptide toxin was determined by identifying the secondary structural
features such as alpha-helix and beta-sheet. Finally, the identification of biological
targets for each peptide toxins has been performed.
Analysis of peptide toxins deposited in Animal
toxin database:
Animal toxin database (http://protchem.hunnu.edu.cn/toxin/)has
an extensive information about the manually annotated peptide toxins obtained from
numerous venomous animals. The database contains a limited number of entries of
peptide toxins. Each of the toxin entry contains information about amino acid sequence,
gene sequence, 3D-structure, and biological target. Entries in the database were
manually inspected, and information was drawn for disulfide connectivity, cysteine
patterns, the number of disulfide bonds, structural fold, and target. Cysteine patterns
were determined through the analysis of the amino acid sequence of the toxin. The
number of intervening amino acids was calculated, and eventually, the pattern was
deduced. For example, the amino acid sequence of snake toxin Crotamine’ is QCHKKGGHCFPKEKICIPPSSDFGKMDCRWRWKCCKKGSGK.
The cysteine pattern of Crotamine’ is ----X1-----C-----X6-------C----X6----C----X11-----C-----X5-----CC---X6.
3D-fold of the peptide toxin was determined by identifying the secondary structural
features such as alpha-helix and beta-sheet. A biological target was noted for each
of the peptide toxins.
3D-Structure processing using PyMOL:
The structures of peptide toxins were downloaded from Protein
Databank (PDB). 3D structures of toxins were analyzed using PyMOL viewer. The procedure
for viewing 3D structure of peptide toxins is as follows- Upon opening PDB structure
in PyMOL, using the cartoon display option and ball & stick representation of
disulfides, the structures were processed. Upon displaying line representation of
the side chain of toxin and using Ray option, the structures were saved in image
format.
RASA Calculation for cysteines in peptide toxins:
ASA-View tool (http://www.abren.net/asaview/) was utilized
to compute the Relative Accessible Surface Area (RASA) of peptide toxins before
and after binding to the ion channels/receptor. The representative PDB files of
peptide toxins and receptor-bound toxins were downloaded from PDB. The coordinates
file of each of the toxins is uploaded separately to the ASA-View server. The output
obtained from RASA analysis encompasses a text file with the bar chart, and spiral
plot along with the information on RASA values (%) of individual amino acid residues
utilized for further analysis. The difference in the RASA value of each of the amino
acids was determined to identify the interacting surface of the toxin with the ion
channel/receptor. Similarly, in an approach of identifying the interacting surface
of the toxin with ion channel/receptor using PyMOL, surrounding residues of 4A°
to toxin were analyzed and marked.
RESULT AND DISCUSSION:
Peptide toxins have unique features of harbouring multiple
numbers of intramolecular disulfides. The importance of disulfide bonds on the functions
and structures of toxic peptides is well established. Given the critical role of
disulfides in peptide toxins, cysteine patterns were analyzed and disulphide connectivities
of peptide toxins were collected in peptide toxins databases. Due to uncertainties
and complications in complying with the data related to the disulfide mapping in
higher-order disulfide toxins, the analysis of toxins was restricted to four disulfides
16, 17. Intensive research in the area of venomics has discovered
a huge quantity of information about the peptide toxins sequence, peptide toxins
structure, and their functions that were deposited in multiple public databases
such as ArachnoServer, ConoServer, Animal toxin annotation project of Uniprot, and
Animal toxin database. Analyses of cysteine pattern and disulphide connectivity
were performed as reported in the methodology section.
Briefly, manual scrutiny of toxins present in the databases
was studied to determine cysteine pattern and disulphide connectivity and subsequently
classified concerning the number of intramolecular disulfides in the sequence. Venomous
species of snake, scorpion, spider, cone snail, and sea anemone peptide toxins were
well-studied for cysteine patterns and disulphide connectivities. There are reports
that toxic peptides (where n≥1) with cysteine pattern – C – Xn –C – Xn – CC
–Xn – C – Xn – C -- were deliberated to have the identical cysteine pattern – C
--- C --- CC --- C --- C —. For instance, ω-conotoxin and hanatoxin have a
dissimilar number of intervening non-cysteine residues between cysteines, but the
same cysteine pattern --C---C---CC---C---C—was observed. There are more entries
of similar toxins in the database, and all of them were having the same cysteine
pattern. ~150 entries of ω-conotoxins obtained from different cone snail species
had cysteine pattern --CC----C----C--, whereas nearly ~156 entries of short neurotoxins
were also found to have a pattern --C—C—C—C—C—CC— C were—. However, each entry of
toxin has been further scrutinized to know its molecular target, 3D structure, and
disulfide connectivity. The following section provides a summary of the analysis
concerning the venomous species snake, scorpion, spider, cone snail, and sea anemone.
Snake Venom
Peptide Toxins:
Table S1 provides the classification of snake venom peptides
based on cysteine patterns and disulfide connectivity’s. Single disulfide containing
snake venom peptide toxin is a natriuretic peptide, which is a critical lead compound
for cardiovascular diseases. A total of eight cysteine patterns was observed in
snake peptide toxins: --C---C---C---C--; --CC---C---C--; --C--C--C--C--C--C--; --C--C--C--C--CC--;
--C-C-C-C-C-CC-C--; --C-C-C-C-CC-C-C--; --C-CC-C-C-C-C-C--; and --C-C-C-C—C-CC-C--.
These patterns contribute to a total of nine (9) disulfide folds. Pattern --C---C---C---C—with
connectivity 1-2/3-4 and 1-4/2-3; pattern--C--C--C--C--C--C—with connectivity 1-6/2-4/3-5
and 1-2/3-6/4-5; pattern --C--C--C--C--CC— with connectivity 1-5/2-4/3-6; pattern
--C-C-C-C-C-CC-C—with connectivity 1-3/2-4/5-6/7-8; pattern --C-C-C-C-CC-C-C—with
connectivity 1-5/2-7/3-5/4-8; pattern --C-CC-C-C-C-CC— with connectivity 1-4/2-6/3-7/5-8
and pattern --C-C-C-C—C-CC-C—with connectivity 1-3/2-4/5-6/7-8. Disulfide connectivity
of cardiotoxin-like basic polypeptide ah needs to be established (Table S1). Fig.
1 shows representative 3D structures of snake venom peptide toxins.
Safarotoxin is an agonist of EDNRA/EDNRB receptor (Endotheline
receptor), which is a particular class of G-protein coupled receptors. This peptide
toxin has a cysteine stabilized alpha-helical motif. Dendrotoxin-1 blocks Kv channels
at picomolar to nanomolar concentration range and has 310ββα disulfide
fold. C-type lectin 6 modulates platelet aggregation. Myotoxin-A is a cell-penetrating
peptide with disulfide fold αβββ. This toxin is also Nav channel
modulators. Three-finger hemachatoxin has cardiotoxic and hypotensive activities.
Another three-finger toxin (Toxin-FS2) have reported to act as a specific blocker
of L-type Cav channel. These snake toxins have ββββββ
disulfide fold (TableS2). Nawaprin with disulfide fold βαβββ
shows antimicrobial activity. Disintegrinjerdostatin with βββ fold
shows inhibition of adhesion of alpha-1/beta-1-K562.
Scorpion
Venom Peptide Toxins:
Table S2 provides the classification of snake venom peptides
based on cysteine patterns and disulfide connectivities. A total of seven cysteine
patterns has been observed in scorpion peptide toxins: --C--C--CC--C--C--; --C--C--C--C--C--C--;
--C-C-C-C-C-CC-C--; --C-C-C-C-C-CC-C--; --C-C-CC-C-C-C-C--; --C-C-C-CC-C-C-C--;
and --CC-C—C-C-C-C-C--. These patterns contribute to a total of twelve (12) disulfide
folds - Cysteine pattern --C--C--CC--C--C— with connectivity 1-4/2-5/3-6; pattern
--C--C--C--C--C--C—with connectivity 1-4/2-5/3-6; pattern --C-C-C-C-C-CC-C—with
connectivity 1-3/2-6/4-7/5-8; pattern --C-C-C-C-C-C-CC— with connectivity 1-8/2-5/3-6/4-7;
1-2/3-6/4-7/5-8; 1-5/2-6/3-7/5-8; 1-5/2-6/3-4/7-8 and 1-4/2-5/3-6/7-8; pattern --C-C-CC-C-C-C-C—with
connectivity 1-4/2-8/3-6/5-7; and pattern --C-C-C-CC-C-C-C—with connectivity 1-4/2-6/3-7/5-8.
Disulfide connectivity of putative potassium channel blocker toxins is yet to be
established. Fig. 2 shows representative 3D structures of scorpion venom peptide
toxins. Maurocalcin with disulfide fold βαβββ (Inhibitory
cystine knot motif) potently and reversibly modifies RYR1 receptors. Charybdotoxin
and Toxin ImKTx104 with disulfide fold αββ target Kv channel. Kappabuthitoxin-
Tt2b with disulfide fold αα blocks sheker and hKv1.2 channel. Potassium
channel toxin alpha-KTx 10.2 targets sheker-B Kv channels.
Neurotoxin 2 with disulfide fold βαββ
binds site-3 of Nav channels. Butantoxin with disulfide fold βαββ
inhibits calcium-activated Kv channels. Toxin Vm24 with disulfide fold ββαβ
blocks hKv1.3/KCNA3 potassium channels. Maurotoxin with disulfide fold αββ
blocks Kv channel. Phaiodotoxin is Nav channel-specific neurotoxin. Potassium channel
toxin epsilon-KTx 1.1 with ββββ fold blocks Kv channels. Beta-insect
excitatory toxin Bj-xtrIT with βααββα bind Nav channels.
Fig. 1. Representative 3D-structures of peptide toxins derived from
snake venom with its PDB ID. Cysteine disulfides are indicated by the ball and stick
model. Structures were processed using PyMOL software.
Fig. 2. Representative 3D structures of peptide toxins derived
from scorpion venom with its PDB ID. Cysteine disulfides are indicated by the ball
and stick model. Structures were processed using PyMOL software.
Spider Venom Peptide Toxins:
Table
S3 provides the classification of spider venom peptides based on cysteine pattern
and disulfide connectivities. Totally Seven different cysteine pattern was detected
in spider peptide toxins: --C--C--CC--C--C—; --C--C--C--C--C--C--; --C-C-C-C-C-C-C-C--;
--C-C-CC-CCC- C--; --C-C-CC-C-C-C-C—; --C-C-C-CC-C-C-C—; and --C-C-CCC-C-C-C--.
These patterns contribute to a total of twelve (13) disulfide folds - cysteine pattern
--C--C--CC--C--C— with disulfide connectivity 1-4/2-5/3-6 and 1-4/2-6/3-5; cysteine
pattern --C--C--C--C--C--C—with connectivity 1-5/2-4/3-6; 1-4/2-6/3-5; 1-3/2-5/3-6;
and 1-3/2-6/4-5; cysteine pattern --C-C-C-C-C-C-C-C— with connectivity 1-3/2-7/4-5/6-8;
cysteine pattern --C-C-CC-CC-CC—with connectivity 1-6/2-7/3-4/5-8; cysteine pattern
--C-C-CC-C-C-C-C— with connectivity 1-4/2-5/3-8/6-7; 1-4/2-6/3-8/ 5-7; and 1-4/2-5/3-7/6-8;
cysteine pattern --C-C-CCC-C-C-C—with connectivity 1-5/2-6/3-8/4-7; and cysteine
pattern with connectivity 1-4/2-6/3-7/5-8. Kappa-hexatoxin-Hv1c with the pattern
--C-C-CC-CC-C-C—and connectivity 1-6/2-7/3-4/5-8 contains a vicinal disulfide bond.
Fig. 3 shows representative 3D-structures of spider venom peptide toxins.
Kappa-theraphotoxin-Gr1a (Hanatoxin-1) with disulfide fold
310 ββ (ICK motif) inhibits Kv channels. U1-agatoxin-Ta1a (Insecticidal
toxin 1) with disulfide fold αααα shows insecticidal activity.
U1-theraphotoxin-Hs1a (Huwentoxin-2) with disulfide fold ββββ
blocks neuromuscular transmission. Kappa-hexatoxin-Hv1c with vicinal disulfides
inhibits KCa channels. U2-hexatoxin-Hi1a (Agatoxin) with disulfide fold βββ
Inhibits Nav channels. U2-segestritoxin-Sf1a with ββ fold is an insecticidal
toxin. Deltahexatoxin- Hv1a (Delta-batrachotoxin) with βββ310 fold
inhibits tetrodotoxin sensitive Nav channel.
Cone Snail
Venom Peptide Toxins:
Table S4 provides the classification of cone snail venom
peptides based on cysteine pattern and disulfide connectivities. In cone snail peptide
toxins, a total of seventeen cysteine patterns has been observed as follows --C---C---C---C--;
--CC---C---C--; --C---C---CC--; --CC-----CC--; --C--C--CC--C--C--; --CCC--C--C--C--;
--C--C--CC--CC--; --CC--C--C--C--C--; --CC--C--C--CC--; --C--C--C--CC--C--; --C--CC--C--C--C--;
--C-C-CC-CC-C-C--; --C-C-C-CCC-C-C--; --C-C-CC-C-C-C-C--; --C-C-C-C-CC-CC--; --C-C-C—C-C-CCC--;
and --C—C-CC—C-CC-C--. These patterns contribute to a total of twelve (18) disulfide
folds. Cysteine pattern --C--C--C--C—with disulfide connectivity 1-3/2-4 and 1-4/2-3;
cysteine pattern --CC---C---C—with disulfide connectivity 1-3/2-4 and 1-4/2-3; cysteine
pattern --C---C---CC—with disulfide connectivity 1-4/2-3; cysteine pattern --CC-----CC--
with disulfide connectivity 1-3/2-4; cysteine pattern --C--C--CC--C--C—with disulfide
connectivity 1-4/2-5/3-6; cysteine pattern --CCC--C--C--C-- with disulfide connectivity
1-6/2-4/3-5; cysteine pattern --CC--C--C--C--C—with disulfide connectivity 1-3/2-5/4-6
and 1-5/2-3/4-6; cysteine pattern --CC--C--C--CC-- with disulfide connectivity 1-4/2-5/3-6;
cysteine pattern --C--C--C--CC--C—with disulfide connectivity 1-2/3-4/5-6; cysteine
pattern --C--C--C--CC--C— with disulfide connectivity 1-3/2-5/4-6; cysteine pattern
--C--CC--C--C--C—with disulfide connectivity 1-3/2-5/4-6; cysteine pattern --C-C-CC-CC-C-C—
with disulfide connectivity 1-4/2-6/3-7/5-8; and cysteine pattern --C-C-C-C-CC-C-C—with
disulfide connectivity 1-3/2-6/4-7/5-8. The disulfide connectivity for the patterns
--C-C-CC-C-C-C-C--; --C-C-C-C-CCCC--; --C-C-C—C-C-CCC--; and --C—C-CC—C-CC-C— yet
to be established. Fig. 4 shows representative 3D structures of venom peptide toxins
derived from cone snails. Alpha/kappa-conotoxin pl14a with disulfide α310310
fold inhibits Kv1.6 channels.
Kappa-conotoxin with αα fold blocks Kv channels.
Alpha-conotoxin GI with alpha-helix inhibits nAChR. ChiconotoxinMrIA with ββ
disulfide fold inhibits NET transporter. Conotoxin pc16a with β/α scaffold
is a potent neurotoxin. Omega-conotoxin GVIA with βββ (ICK) fold
inhibits the N-type Cav channel. Alpha-conotoxin S2 with αβ fold binds
to nAChR. αA-conotoxin PIVA with βα fold inhibits nAChR. Mu-conotoxin
GIIIA with βα fold blocks Nav channels. Iotaconotoxin RXIA ( r11a) with
ββββ fold is agonists of Nav channels. Several conotoxins have
reported to cause convulsions in mice by inducing excitatory symptoms and reversible
depression symptoms.
Sea anemone
and other peptide venom toxins:
Table S5 provides the classification of sea anemone venom
peptides based on cysteine pattern and disulfide connectivities. A total of four
cysteine patterns have been observed in sea anemone peptide toxins: --C--C--C--C--C--C--;
--CC--C--C--C--C--; --C--C--C--C--CC--; and --CC-C-C-C-C-C-C--. Cysteine pattern
--C--C--C--C--C--C—with connectivity 1-6/2-4/3-5; pattern --CC--C--C--C--C—with
connectivity 1-5/2-4/3-6; and pattern --C--C--C--C--CC— with connectivity 1-5/2-4/3-6.
Disulfide connectivity of the pattern --C-C-C-C-C-C-C-C— is yet to be established.
Fig. 5 shows representative 3D structures of sea aneomone venom peptide toxins.
Kappa-stichotoxin-She3a (Kappa-SHTX-She3a) with disulfide βααα
fold inhibits Kv channels. Delta-actitoxin-Avd2a (ATX III) with disulfide βββ
fold inhibits the inactivation of Nav channels. Delta-actitoxin-Avd1a with disulfide
ββββ fold binds Nav channels. Notable other toxins of interest
are cysteine stabilized alpha-helical peptide apamin, Horseshoe crab tachystatin-A1,
centipede peptide ω-scoloptoxin, wasp toxin, and bug toxin(Ptu1). Peptide toxins
of other neglected taxonomic lineages are of current interest. Comparing spiral
disulfide conformers to the other three fundamental disulfide conformers of peptide
toxins reveals a bias for greater DCa-Ca (>5) and lower DCb-Cb (4 ) values.
Fig. 3. Representative 3D-structures of peptide
toxins derived from spider venom with its PDB ID. Cysteine disulfides are indicated
by the ball and stick model. Structures were processed using PyMOL software.
Fig. 4. Representative 3D-structures of peptide toxins derived from cone snail venom with its PDB ID. Cysteine disulfides are indicated by ball & stick model. Structures were processed using PyMOL software.
Unity-diversity
relationship of peptide toxins and channels/receptors:
Cone snails have utilized a single disulfide scaffold in
designing three different functional toxins; κ-conotoxin, which targets the
sodium channel, the κ- conotoxin which targets the potassium channel, and ω-conotoxin
which targets the calcium channel as illustrated in Fig. 6.
Stable peptide
scaffolds such as ICK motif have been utilized in designing new functional entities
through surface modification other than the disulfide core resulting in identical
disulfide folds in functionally diverse toxins. ICK motif has cysteine pattern ---C----C----CC----C----C---
and disulfide connectivity 1-4/2-5/3-6. Toxic peptides reported to contain ICK motifs
are known to target RYR1 receptors, ASIC1a Channels, TRPV1 channels, voltage-gated
Ca channels, voltage-gated K channels, voltage-gated Na channels, and microbes.
As shown in Fig. 7, peptide toxin that targets the K+ channel is present in multiple
venomous species such as snakes, scorpions, spiders, and cone snails. The utilization
of identical folds having the same function in numerous venomous species and the
evolution of several disulfide folds acting at the same target highlights the unity-diversity
relationship in deadly peptide toxins. Similarly, sarafotoxin, κ-hefutoxin,
are κ-Conotoxin were the few examples of toxic peptide with cysteine pattern
---C---C---C---C--- and disulfide connectivity 1-3/2-4 which obtained from snake
scorpion, and cone snail, respectively.
There are reports
of the presence of molecular targets in κ-Conotoxin for the endothelin receptor
(EDNRA/EDNRB) as well as for the K+ channel. Numerous toxic peptides derived from
different venomous species with similar mechanisms of inhibition of proteases were
reported to have Kunitz disulfide folds with pattern ---C---C---C---C---C---C---
disulfide connectivity 1-6/2-4/3-5. Thus, these properties of toxic peptides derived
from different venomous species having similar disulfide folds and similar functions
offer valuable insights into the engineering of novel peptide toxins to target the
given channel/receptors or even to modulate relevant biological functions. The inhibitory
cystine knot (ICK) motif is extensively found commonly in multiple toxic peptides
18, 19. κ-conotoxin found in
the marine cone snails have reported to contain ICK-motif helps in delaying the
inactivation of the Na channel, thereby blocking the K channel 5. The application of the identical disulfide fold
in functionally deviating toxins suggests that toxin scaffolds can provide an entity
as lead compounds to treat neurological disorders. The results obtained from disulfide
folds’ analysis of various peptide toxins help in providing the required knowledge
in the planning of toxin disulfide folds by structure-based drug design.
Fig. 5. Representative 3D structures of peptide
toxins derived from sea anemone venom with its PDB ID. Cysteine disulfides are indicated
by the ball and stick model. Structures were processed using PyMOL software.
Fig. 6. Concept of unity-diversity and vice versa relationship of toxis peptides obtained from various venomous species and ion channel/receptors of excitable cells. (a) Cone snail explored ICK fold of peptide toxin with cysteine pattern ---C---C---CC---C---C—and connectivity 1-4/2-5/3-6 in different engineering channels targeting peptide toxins. (b) Snake, scorpion, and sea anemone have evolved distinctly different disulfide folds that target the same Kv ion channel.
Ion channels/
receptors:
Well-characterized
peptide toxins that target K(+) channel include κ-conotoxin, κ-hefutoxin,
BgK toxin, ShK toxin, hanatoxin-1, maurotoxin, charybdotoxin, and dendrotoxin-I.
These peptide toxins may have different binding sites and are capable of targeting
different isoforms of the K(+) channels (Hille 2001). The peptide toxins that target
Na(+) channel mainly are as follows huwentoxin-IV, ACTX toxin, ATX1a toxin, B-IV
toxin, ω-conotoxin, κ-atracotoxin-HvI, AahII toxin, crotamine, ω-conotoxin
KIIIA, BJ-XtrIT toxin, μO-conotoxin MrVIA. These peptide toxins may also have
different binding sites and target different isoforms of the Na(+) channels.
Well-characterized
peptide toxins that target Ca(2+) channel includes Ptu 1 toxin, ω-conotoxin
GVIA, three-finger toxin FS2, KP4 toxin, and ω-agatoxin. These peptide toxins
may also have different binding sites and different target isoforms of the Ca(2+)
channels. Well-characterized peptide toxins that target Cl(-) channel is chlorotoxin
derived from a scorpion. Well-characterized peptide toxins that nAChRs include α-conotoxin
from cone snails and α-bungarotoxin from snake venom. αA-conotoxin targets
nAChRs. α-conotoxin MrVIA targets the norepinephrine transporter. Maurocalcine
targets the ryanodine receptor. Other function of peptide toxins includes antimicrobial
activity, and hemolytic activity, and induces various behavioural symptoms in mice.
Complex
structures of peptide toxins with ion channels/receptors:
Characterization
of binding of peptide toxins with ion channels/receptors provides valuable insights
on the mode of interaction with macromolecular proteins. Co-crystal structures of
peptide toxins with channel/receptor have been studied using X-ray crystallographic
method. The co-crystal structures of toxins with channel/receptor were α-conotoxin
with acetyl choline-binding protein, α-cobratoxin with acetyl choline-binding
protein, fascicullin with acetylcholinesterase, charybdotoxin with K (+) channel,
psalmotoxin with acid-sensing ion channels (ASICs) and con-ikot-ikot with AMPA receptor.
Fig. 8 shows the 3D-structures of co-crystal structures of toxins with channel/receptor.
The PDB ID of
toxin and channel/receptor complex is as follows: α-cobratoxin-AChBP (1YI5),
α- conotoxin-AchBP (2BR8), Con-ikot-ikot- AMPA (4U5D), carybdotoxin-Kv channel
(4JTA), faciculin-acetylcholine esterase (1F8U), and double knotted toxin-TRP channel
(5IRX). It is apparent from Fig. 8, toxins interact with specific locations of targeting
macromolecular proteins. As predictable, it was observed that pentameric acetyl
choline-binding protein binds to four binding sites for peptide toxin as it contains
five binding sites for toxin and tetrameric channels. Interestingly, the α-conotoxin
and α-cobratoxin bind to the same acetyl choline-binding protein (AChBP). Both
toxins have the same binding pocket and bind at five positions of the pentameric
channel. α-Conotoxin has cysteine pattern ---CC---C---C--- with disulfide connectivity
1- 3/2-4. α-Cobratoxin has cysteine pattern ---C---C--- C---C---C---C--- C---C---
C---C--- with disulfide connectivity 1-3/2-6/4-5/7-8/9-10. These two toxins have
unrelated structures and are derived from different venomous species. α-Conotoxin
was obtained from cone snails, and α-cobratoxin was isolated from snake venom.
Yet, these toxins target nAChRs with picomolar concentration and demonstrate a high
degree of specificity for nAChRs.
Fig. 8 shows the
binding pocket of α-cobratoxin and α-conotoxin with AChBP. It is apparent
from Fig. 8, α-cobratoxin and ω-conotoxin has the same binding pocket
which suggests that the structures of toxins can be minimized without compromising
their activity, showing their potential as templates for drug design using peptide
toxins. The relatively accessible surface area of peptide toxins can be calculated
using the ASA view tool, thereby determining the interacting surface of the peptide
toxins with ion channels and receptors 20. RASA of toxin in unbound
and bound form with the receptor can be deduced using coordinates of the 3D-structure
of the toxin by uploading to the ASA View tool 20. The difference in RASA of
toxin between unbound and bound forms provides direct evidence for an interacting
surface of the toxin with the receptor. For example, fasciculin-II has been utilized
for further studies as it acts on acetylcholine esterase. For the identification
of the interacting residues of fasciculin-II with acetylcholine esterase, we have
subjected the unbound form of fasciculin-II (PDB ID: 1FSC) and the bound form of
fasciculin-II (PDB ID: 1F8U) for ASA view software. Fig. 9 shows the difference
in RASA of amino acid residues of fasciculin between the unbound and bound forms
of the toxin with acetylcholine esterase. It is found that T-8, T-9, R-11, A-12,
R-27, P-30, P-31, K-32, M-33, V-34, N-47, E-49, and Y-61 residues of fasciculin-II
interact with acetylcholine esterase.
Fig. 7. Co-crystal structures of peptide toxins
with ion channels/receptors. (a) α-Cobratoxin with Acetyl Choline Binding Protein
(AChBP). (b) α-Conotoxin with Acetyl Choline Binding Protein (AChBP). (c) charybdotoxin
with K (+) channel. (d) Fascicullin with Acetylcholinesterase. (e) Double-knotted
toxin with TRP channel. (f) Con-ikot-ikot peptide toxin with AMPA receptor
Fig. 8. Binding of peptide toxin to acetyl choline-binding
protein (AChBP). (a) α-Cobratoxin derived from the snake and its interacting
surface of AChBP. (b) α-Conotoxin derived from the snail and its interacting
surface of AChBP. The interacting surface was identified using PyMOL software. Note.
Unrelated toxins have similar binding pockets with AChBP. (c) α-Conotoxin-AChBP
complex,α-Conotoxin-AChBP complex and superpositionof α-Conotoxin-AChBP
complex α-Conotoxin-AChBP complex with binding site.
Fig. 9. The difference is a RASA of amino acid residues
of fasciculin-II between unbound isolated-form bound form with acetylcholine esterase.
The dashed line at 20% can be used to identify more profoundly interacting amino
acid residues of fasciculin-II with acetylcholine esterase. ASA view was used to
calculate the RASA of amino acids of fasciculin-II
CONCLUSION:
Structural analysis
of natural peptide toxins, which designed neuronal circuits modulating provided
insights for structure-based drug design where peptide toxins can be used as scaffolds.
Venom has hundred different toxins found to cause lethality, paralysis, severe pain,
and unbearable irritations upon direct injection into victims. However, the separation
of the venom into individual peptide toxin components has proven their applications
in neuroscience and as lead compounds in therapeutics. Some of the toxins are on
the market, such as Prialt (ω-conotoxin), for the treatment of neurological
disorders. Millions of years of effort on the evolution in the design of peptide
toxins to achieve exquisite specificity and selectivity for neuronal circuits offers
valuable insights and inputs for structure-based drug design using peptide scaffolds.
The distance of disulfide bond length of cysteine residues is 2.01 ± 0.01A. Given
the optimal molecular weight and specificity of peptides compared to conventional
small molecule drugs, peptides are considered future next-generation drug candidates.
Alpha Fold predictions are quite accurate in many circumstances, although it is
crucial to remember that the accuracy varies depending on the protein or peptide
being predicted. Furthermore, AlphaFold has not been specially optimised for predicting
the structures of neuroactive peptides, which may be difficult due to their tiny
size and flexibility. As a result, any predicted structures must be validated using
experimental techniques such as X-ray crystallography or NMR spectroscopy. It is
challenging in the absence of experimental validation.
ACKNOWLEDGEMENT:
The authors thank
our prestigious institute and other people who are involved in this study for their
direct and indirect contributions.
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Available online from December 27, 2024
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Table S2: Classification
of venom peptide toxins derived from scorpion concerning with cysteine pattern and
disulfide connectivity
