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PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

Islam SM, Sajed T, Kearney CM, Baker EJ - BMC Bioinformatics (2015)

Bottom Line: Their effective interstitial and macro-environmental use requires energetic and structural stability.As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology.The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Studies, Baylor University, Waco, TX, USA. S_Islam@Baylor.edu.

ABSTRACT

Background: Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology.

Results: We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB.

Conclusion: PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

No MeSH data available.


Related in: MedlinePlus

Comparison of the compactness of disulfide bonds in different types of tri-disulfide array containing peptides. Illustration of distances among the non-pairing sulfur molecules participating in the tri-disulfide array. Distances between different sulfur molecule pairs (yellow balls) were measured using jmol software. The mean of these distances indicates the average distance among the disulfide bonds demonstrating the compactness of the tri-disulfide fold in the peptide. a, b, c and d show distances of a sample representative of knotted STPs, nonknotted STPs, compact NTPs and non-compact NTPs, respectively, together with their PDB ids. The average of distance in STP toxins (a and b) is typically less than 0.85 nm, while it is more than 1.2 nm in other tri-disulfide peptides (Non-compact NTPs, data not shown) (d). Some NTPs demonstrate a similar compactness (average distance) to STPs and can be designated as compact NTPs (c)
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Fig2: Comparison of the compactness of disulfide bonds in different types of tri-disulfide array containing peptides. Illustration of distances among the non-pairing sulfur molecules participating in the tri-disulfide array. Distances between different sulfur molecule pairs (yellow balls) were measured using jmol software. The mean of these distances indicates the average distance among the disulfide bonds demonstrating the compactness of the tri-disulfide fold in the peptide. a, b, c and d show distances of a sample representative of knotted STPs, nonknotted STPs, compact NTPs and non-compact NTPs, respectively, together with their PDB ids. The average of distance in STP toxins (a and b) is typically less than 0.85 nm, while it is more than 1.2 nm in other tri-disulfide peptides (Non-compact NTPs, data not shown) (d). Some NTPs demonstrate a similar compactness (average distance) to STPs and can be designated as compact NTPs (c)

Mentions: Despite a wide range of diversity based on their sources and modes of actions, all cystine stabilized toxins contain a fold with multiple disulfide connectivity [19]. A sequential array of tri-disulfide connectivity is regarded as the most stable [20]. It has a compact cystine trio, where the first cysteine participating in the fold makes a disulfide bond with the fourth cysteine, the second one with the fifth cysteine and the third one with the sixth cysteine (C1–C4, C2–C5, C3–C6). There may be other cysteines in the primary sequence of these peptides, but they do not participate in that sequential tri-disulfide connectivity. This class of proteins includes several large protein families such as knottins [21], scorpion toxin-like superfamily [22], cyclotides [23], and a substantial proportion of diverse peptides comprising antimicrobial peptides and defensins [24]. For clarity, toxic peptides containing this particular stable disulfide connectivity can be referred to as sequential tri-disulfide peptide toxins (STP toxins). Cystine stabilized toxins which do not contain the exact STP bonding array may also offer stability and toxicity [25–28] and can be denoted as nonsequential tri-disulfide peptides (NTPs) (Fig. 1). While STP toxins imply a compact tri-disulfide tertiary confirmation, NTPs toxins may contain both compact or non-compact tri-disulfide folds (Fig. 2).Fig. 1


PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

Islam SM, Sajed T, Kearney CM, Baker EJ - BMC Bioinformatics (2015)

Comparison of the compactness of disulfide bonds in different types of tri-disulfide array containing peptides. Illustration of distances among the non-pairing sulfur molecules participating in the tri-disulfide array. Distances between different sulfur molecule pairs (yellow balls) were measured using jmol software. The mean of these distances indicates the average distance among the disulfide bonds demonstrating the compactness of the tri-disulfide fold in the peptide. a, b, c and d show distances of a sample representative of knotted STPs, nonknotted STPs, compact NTPs and non-compact NTPs, respectively, together with their PDB ids. The average of distance in STP toxins (a and b) is typically less than 0.85 nm, while it is more than 1.2 nm in other tri-disulfide peptides (Non-compact NTPs, data not shown) (d). Some NTPs demonstrate a similar compactness (average distance) to STPs and can be designated as compact NTPs (c)
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4491269&req=5

Fig2: Comparison of the compactness of disulfide bonds in different types of tri-disulfide array containing peptides. Illustration of distances among the non-pairing sulfur molecules participating in the tri-disulfide array. Distances between different sulfur molecule pairs (yellow balls) were measured using jmol software. The mean of these distances indicates the average distance among the disulfide bonds demonstrating the compactness of the tri-disulfide fold in the peptide. a, b, c and d show distances of a sample representative of knotted STPs, nonknotted STPs, compact NTPs and non-compact NTPs, respectively, together with their PDB ids. The average of distance in STP toxins (a and b) is typically less than 0.85 nm, while it is more than 1.2 nm in other tri-disulfide peptides (Non-compact NTPs, data not shown) (d). Some NTPs demonstrate a similar compactness (average distance) to STPs and can be designated as compact NTPs (c)
Mentions: Despite a wide range of diversity based on their sources and modes of actions, all cystine stabilized toxins contain a fold with multiple disulfide connectivity [19]. A sequential array of tri-disulfide connectivity is regarded as the most stable [20]. It has a compact cystine trio, where the first cysteine participating in the fold makes a disulfide bond with the fourth cysteine, the second one with the fifth cysteine and the third one with the sixth cysteine (C1–C4, C2–C5, C3–C6). There may be other cysteines in the primary sequence of these peptides, but they do not participate in that sequential tri-disulfide connectivity. This class of proteins includes several large protein families such as knottins [21], scorpion toxin-like superfamily [22], cyclotides [23], and a substantial proportion of diverse peptides comprising antimicrobial peptides and defensins [24]. For clarity, toxic peptides containing this particular stable disulfide connectivity can be referred to as sequential tri-disulfide peptide toxins (STP toxins). Cystine stabilized toxins which do not contain the exact STP bonding array may also offer stability and toxicity [25–28] and can be denoted as nonsequential tri-disulfide peptides (NTPs) (Fig. 1). While STP toxins imply a compact tri-disulfide tertiary confirmation, NTPs toxins may contain both compact or non-compact tri-disulfide folds (Fig. 2).Fig. 1

Bottom Line: Their effective interstitial and macro-environmental use requires energetic and structural stability.As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology.The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Studies, Baylor University, Waco, TX, USA. S_Islam@Baylor.edu.

ABSTRACT

Background: Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology.

Results: We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB.

Conclusion: PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

No MeSH data available.


Related in: MedlinePlus