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Recipe: ST - Charge Compatibility Index (CCI) - kimo
Created by Seagat2011 45 1438
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Name: ST - Charge Compatibility Index (CCI) - kimo
ID: 28845
Created on: Tue, 05/24/2011 - 16:24
Updated on: Wed, 05/25/2011 - 05:49

run this on Amino Acid (AA) sequences you want evaluated for charge compatibility.

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Joined: 08/24/2010

ST - Charge Compatibility Index (CCI) - v1.0.0.0 -

This recipe uses an amino acid Charge Compatibility Matrix and Index, where _pI denotes the Isoelectric point (pI). Similar to the HCI recipe, this does a similar comparison of 2 Amino Acids based on electric charge.

A simple characterization of a molecule's charge properties is the isoelectric point (pI), which is the pH at which the overall charge of the molecule is neutral. These values are determined for the entire free amino acid. However, amino acids differ from each other only in side chains. Therefore the pI usually reflects differences in the pKs of the side chains.

The intracellular pH is 6.8 while the extracellular pH is 7.4. Those amino acids having lower pI than this are negatively charged, those with higher pI are positively charged.

Most amino acids (15 out of 20) have an isoelectric point (pI) very close to 6 so they are regarded as having neutral overall charge; Asp and Glu are negatively charged, acidic (pI 2.7 and 3.2) and His, Lys, Arg are positively charged, basic (pI 7.5, 9.7, and 10.7). Only 16/64 codons encode charged amino acids, so the calculated overall frequency of charged amino acids is about 26% and the calculated frequency of charge-determined amino acid-amino acid interactions is 5 × 5/2 of 20 × 20/2, i.e. only 6.25%. The influence of charge on amino acid co-location is therefore much less than the influence of the hydrophobe force.

For mathematical expression of the size and direction of charge-determined forces, between A nd B, we have constructed the charge compatibility index (CCI) and collected these indexes into a charge compatibility index and matrix (CCI). The formula used to calculate CCI at pH = 7 is

CCI(AB) = 11 - [pI(A)-7] [pI(B)-7] × 19/33.8

This formula gives an index between 1 and 20. The lowest index indicates the lowest possible attraction between amino acids (Asp-Asp) while the highest index indicates the highest possible attraction between amino acids (Arg-Asp). (In some cases it was convenient to move the range of CCI by -10.4 to give the neutral amino acid interaction a zero value. [1]

Example -

if we use Arginine, Arg(pI=10.76), and Aspartic acid, Asp(pI=2.85), we should get a charge compatibility index and matrix (CCI) of 19.9, according to table [1]

CCI(AB) = 11 - [pI(A)-7] [pI(B)-7] × 19/33.8

CCI(Arg|Asp) = 11 - [pI(Arg)-7] [pI(Asp)-7] × 19/33.8

CCI(Arg|Asp) = 11 - [(10.76)-7] [(2.85)-7] × 19/33.8

CCI(Arg|Asp) = 11 - [3.76] [-4.15] × 19/33.8

CCI(Arg|Asp) = 11 - [-15.60] × 19/33.8

CCI(Arg|Asp) = 11 + 15.60 × 19/33.8

CCI(Arg|Asp) = 11 + 296.40/33.8

CCI(Arg|Asp) = 11 + 8.77

CCI(Arg|Asp) = 19.77

19.77 is approx. equal to the 19.9 value, given in the table.[1]

Recommended for ligand puzzles, and any puzzle involving catalytic areas.

run this on Amino Acid (AA) sequences which should be evaluated for charge compatibility.

1. "Amino acid size, charge, hydropathy indices and matrices for protein structure analysis" -

Joined: 08/24/2010

-- OPTIONS 1: Enter Amino Acids (AAs) into an array, targeted, for comparison
amino_segs_brief = {'a', .. }

-- OPTIONAL 2: Remove abbreviated (1-letter) names of AAs you do not wish to have examined.
amino_segs_brief2 = {'a', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'k', 'l', 'm', 'n', 'p', 'q', 'r', 's', 't', 'v', 'w', 'y'}

-- OPTIONAL 3: Enter index ranges ( set: use_strands = true )
use_strands = true -- enabled (by default) if you wish to compare beta sheet strands

start_strand1 = 1 -- start index of First beta strand or residue [smallest value]
end_strand1 = 12 -- end of First beta strand or residue

start_strand2 = 14 -- start index of Second beta strand or residue
end_strand2 = 25 -- end of Second beta strand or residue [largest value]

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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, Boehringer Ingelheim, RosettaCommons