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CONTRIBUTORS:
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CONFERENCE NAME:
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CONF. LOCATION:
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Cluj-Napoca, Romania, October 23-26
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CONFERENCE YEAR:
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2007
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PUB TYPE:
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Conference Presentation
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SUBJECT(S):
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chemistry - biochemistry; informatics - applied; mathematics - statistics; medicine - informatics
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DISCIPLINE:
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Chemistry
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HTTP:
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http://lori.academicdirect.org/works/?id=162
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LANGUAGE:
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English
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PUB ID:
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103-438-312
(Last edited on
2011/01/14 03:45:55 US/Mountain)
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SPONSOR(S):
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ABSTRACT:
The aim of the present research was to perform a structural modeling analysis of amino acids hydrophobicity in order to identify and characterize if there exists a relationship between the structure and hydrophobicity and how strong the relationships is.
The Molecular Descriptors Family on Structure-Property Relationships approached [1,2] has been used as method of investigation.
The molecular descriptors have been generated on a sample of twenty amino acids and the best performing models in terms of goodness-to-fit were collected and analyzed. The amino acids used in models construction were: Alanine (Ala), Arginine (Arg), Asparagine (Asn), Aspartate (Asp), Cysteine (Cys), Glutamine (Gln), Glutamate (Glu), Glycine (Gly), Histidine (His), Isoleucine (Ile), Leucine (Leu), Lysine (Lys), Methionine (Met), Phenylalanine (Phe), Proline (Pro), Serine (Ser), threonine (Thr), Tryptophan (Trp), Tyrosine (Tyr), and Valine (Val). The hydrophobic or hydrophilic character was the property of interest. Twenty seven different hydrophobicity scales have been analyzed [3-29]. The prediction abilities of the obtained models have been investigated on a sample of eleven amino acids: Seleno-L-Cysteine (Sec), Pyrrolysine (Pyl), Lanthionine (Lth), 2-Aminoisobutyric Acid (Aib), Dehydroalanine (Dhd), Gamma-Aminobutyric Acid (Gab), Ornithine (Oth), Citrulline (Ciu), Homocysteine (Hcy), Hydroxyproline (Hyp), and Dopamine (Dop).
All structure-property relationships models were significantly statistics, obtaining a probability associated to Fisher parameter less than 0.0001. The correlation coefficient between measured property and the molecular descriptor varied from 0.6649 (for hydrophobicity reported by Welling et al. 1985) to 0.9504 (for hydrophobicity reported by Monera et all., 1995). With one exception (the hydrophobicity reported by Guy, 1985), the dominant property of the amino acids directly related with hydrophobicity was the atomic charge. The assessment of the obtained models was performed by using internal validation methods as leave-one-out analysis. The prediction ability of each model has been analyzed by using an external set of eleven amino acids. The overall results are presented and a discussion on structural modeling of amino acids hydrophobicity by using the proposed monovariate approach is conducted.
As a conclusion it can be say that the amino acids hydrophobicity is a property linear related with compounds structure, being on strong relationship with atomic charge through geometry iteration.
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STATISTICS
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