After 30 years of intensive study on AMPs, still an accepted, universal model
of activity is missing. This is not due to the poorness of scientific research,
rather to the simple fact that a universal model do not exists. Instead of a
single one AMPs exploit a huge variety of mechanisms (i.e. altering the membrane
equilibrium, creating pores, disrupting the membrane, docking a proteic receptor
and so on).
YADAMP is a web database dedicated to antimicrobial peptides with detailed information about activities, structural features and biological origin. Moreover, YADAMP permits to BLAST AMPs as well as free sequences. These AMPs come from all biological sources, ranging from bacteria and plants to animals, including humans. Also YADAMP gives links to the paper where the antimicrobial activities were originally reported.
Sequences of active AMP were extracted and extended from other public databases and from scientific literature.
In this way, we collected important information on 2525 AMPs. In YADAMP one can retrieve data about peptide name, aminoacid sequence, length, presence of disulfide bridges, date of discovery. In addition the most relevant chemical physical properties are calculated, like charge, hydrophobic moment, helicity, flexibility, isoelectric point, Boman and instability index, penetration capabilities, and DG.
All indexes are calculated according standard procedures and published algorithms.
STRUCTURAL AND BIOPHYSICAL PARAMETERS
Some AMPs are famous and baptized with a name. You can search them if you know their name
If you want to learn about a particular sequence, you have two possibilities: either to search the sequence inside YADAMP, or to blast it to check for similar peptides
This query is self-explanatory
In most cases the 3D structure of a peptide is not known. Even when the sequence is known (by NMR, for example) peptide exhibit very high flexibility and they can change their secondary structure. Discrimination of protein Secondary structure Class predicts protein secondary structure from the primary sequence. The prediction can be based on a single sequence or a sequence alignment. The overall per residue three-state accuracy of the prediction is approximately 70%. The secondary structure prediction is based upon the DSC algorithm from King and Sternberg [King, R.D. and Sternberg, M.J.E. (1996) Identification and application of the concepts important for accurate and reliable protein secondary structure prediction. Protein Science, 5, 2298-2310.].
Some AMPs interact directly with lipid membranes. The interaction can be on the surface only, or the peptide can insert into the membrane, or even to self-assembly in a barrel structure. Moving from the water bulk into the membrane, the structure of peptides vary significantly. A parameter that control the possibility of a peptide to adapt its morphology to the environment is the flexibility.
The flexibility of a-AMPs is computed according to a conformational flexibility scale for amino acids in peptides [Fang, H. and Werner, M.N. (2003) A Conformational Flexibility Scale for Amino Acids in Peptides. Angew. Chem. Int. Ed., 42, 2269–2272], which provides an absolute measure for the time scale of conformational changes in short structureless peptides as a function of the amino acid type.
The presence of Cysteins suggest the presence of disulfide bridges. The presence of such bonds destroy the helical conformation and change the topology of the peptide. With this field you can choose the desired peptide topology
It is well knows that the major drawback of AMPs is their instability in vivo, due to their degradation operated by a multitude of proteases. The Instability index provide a rough guess of the in vivo stability and it is calculated as described in [ref]
MEAN HYD. MOM.
A measure of the amphipaticity of a peptide is given by the hydrophobicity moment, that is calculated assuming a perfect helical conformation calculating the vectorial sum of hydrophobic moment of each aminoacid. This index is the ratio between the total hydrophobic moment and the peptide number of aminoacids. The amphipaticity is calculated along 3 different hydrophobic scales: CCS [Tossi, A., Sandri, L. and Giangaspero, A. (2002) In Ziino (ed.), Peptides 2002, Napoli, Italy, pp. 416-417], Kyte-Doolittle [J., K. and R., D. (1982) A simple method for displaying the hydropathic character of a protein. J. Mol. Biol., 157, 105-132.], and Eisenberg [Eisenberg, D., Weiss, R.M., Terwilliger, C.T. and Wilcox, W. (1982) Hydrophobic moments and protein structure. Faraday Symp. Chem. Soc. , 17, 109-120.].
In the late ’90, a popular model for AMPs activity assumed that mainly cationic peptide could be antimicrobial, since a positive charge is need to interact with negatively charged bacterial surface. Time passed and the charge is no longer considered sufficient to predict a bactericidal activity. Nevertheless, the charge is a fundamental property to control. Assuming the residues to be independent of each other, we calculated the charge of each peptide by the formula:
where Ni are the number, and pKai the pKa values, of the N-terminus and the side chains of Arginine, Lysine, and Histidine. The j-index pertain to the C-terminus and the Aspartic Acid, Glutamic Acid, Cysteine, Tyrosine amino acids. The charge is calculated at three different pH, 5,7, and 9. A quick inspection to the database, reveals that, mainly because the great variation in lysine, the charge of certain peptides can largely vary at different pH.
The isoelectric point (pI) is the pH at which a protein has no net electrical charge. Below the isoelectric point proteins carry a net positive charge, above it a net negative charge. In YADAMP the isoelectric point is calculated according to [Bjellqvist, B., Basse, B., Olsen, E. and Celis, J.E. (1994) Reference points for comparisons of two-dimensional maps of proteins from different human cell types defined in a pH ]scale where isoelectric points correlate with polypeptide compositions. Electrophoresis 15, 529-539.]
Molecular Lipophilicity Potential (MLP) is an empirical approach for evaluation and detailed visualization of the hydrophobic/hydrophilic properties of organic molecules or macromolecules. MLP is calculated as described in [P. Gaillard, P.A. Carrupt, B. Testa, A. Boudon, "Molecular Lipophilicity Potential, a tool in 3D QSAR: Method and applications", Journal of Computer-Aided Molecular Design, 1994, 8(2), 83-96]
This parameter is the acronym of Cell Penetrating Peptides. The parameter can take values between 0 and 1. 1 corresponds with the highest probability of a peptide to penetrate a membrane, and 0 indicates the impossibility to enter a membrane. The values are calculated with the server http://bioware.ucd.ie/~testing/biowareweb/Server_pages/cpppred.php according to [Holton, Thérèse A., et al. "CPPpred: prediction of cell penetrating peptides."Bioinformatics (2013): btt518 ]
As Boman first pointed out [Boman,
H.G. (2003) Antibacterial peptides: basic facts and emerging concepts. Journal
of Internal Medicine 254,
197-215], in the past most authors have agreed on a
positive net charge (to facilitate binding to bacterial phospholipids) and on an
element of amphipathicity that will help the molecule to ‘flip’ into a bacterial
membrane. These criteria are rather general and they fit groups of other
polypeptides like histones and angiotenins, which also often have antibacterial
The Boman index (for protein-binding potential) shown a certain degree of discrimination between membrane interacting and protein interacting peptides, and it is the sum of the free energies of the respective side chains for transfer from cyclohexane to water taken from Radzeka and Wolfenden [Radzeka, A. and Wolfenden, R. (1988) Comparing the polarities of amino acids: side-chain distribution coefficients between vapor phase, cyclohexane, 1-octanol and neutral aqueous solution. Biochemistry 27, 1664-1670] and divided by the total number of residues.
DG – FREE ENERGY OF BINDING
The free energy of binding is calculated for peptides between 15 and 30 aminoacids. The theory behind the calculation is well described in [Hessa, T., Meindl-Beinker, N., Bernsel, A., Kim, J., Sato, Y., Lerch, M., Lundin, C., Nilsson, I., White, SH. and von Heijne, G. (2007) Molecular code for transmembrane-helix recognition by the Sec61 translocon. Nature. 450, 1026-1030. [PubMed]]
Experimental MIC values (expressed in µM) were manually extracted from careful reading. The MIC values expressed in µg/mL were converted in µM using the formula:
MIC E. coli
MIC P. aeruginosa
MIC S. aureus
MIC B. subtilis
MIC C. albicans
The origin of the AMPs can be searched in terms of phylum, class, order, family and genus. Moreover, it is possible to perform BLAST search on any AMP or any arbitrary sequence.