Aug 2006, Vol. 6, No. 4: 606-624
Full Paper
Although most proteins of most living organisms are constructed from the same set of 20 amino acids, all indications are that this standard alphabet represents a mere subset of what was available to life during early evolution. However, we currently lack an appropriate quantitative framework with which to test the qualitative hypotheses that have been offered to date as explanations for nature's "choices." Specifically, although many indices have been developed to describe the 20 standard amino acids, few or no comparable data extend to prebiotically plausible alternatives because of the costly and time-consuming bench experiments that would be required. Computational chemistry (specifically quantitative structure property relationship methods) offers a potentially fast, cost-effective remedy for this knowledge gap by predicting such molecular properties in silico. Thus, we investigated the use of various freely accessible programs to predict three key amino acid properties (hydrophobicity, charge, and size). We assessed the accuracy of these predictions by comparisons with experimentally determined counterparts for appropriate test data sets. In light of these results, and factors of software accessibility and transparency, we suggest a method for further computational assessments of prebiotically plausible amino acids. The results serve as a starting point for future quantitative analysis of amino acid alphabet evolution.
About Astrobiology and The Astrobiology Web
Astrobiology is the leading peer-reviewed journal in its field. To promote this developing field, the Journal has teamed up with The Astrobiology Web to highlight one outstanding paper per issue of Astrobiology. This paper is available free online at www.liebertpub.com/ast and to visitors of The Astrobiology Web at www.astrobiology.com.
Astrobiology is published quarterly in print and online. The journal provides a forum for scientists seeking to advance our understanding of life’s origins, evolution, distribution and destiny in the universe. A complete table of contents and a full text for this issue may be viewed online at www.liebertpub.com/ast.
Mary Ann Liebert, Inc., is a privately held, fully integrated media company known for establishing authoritative peer-reviewed journals in many promising areas of science and biomedical research. Its biotechnology trade magazine, Genetic Engineering News (GEN), was the first in its field and is today the industry’s most widely read publication worldwide. A complete list of the firm’s 60 journals, books, and newsmagazines is available at www.liebertpub.com
Mary Ann Liebert, Inc. - 140 Huguenot St., New Rochelle, NY 10801-5215 - www.liebertpub.com - Phone: (914) 740-2100 - (800) M-LIEBERT - Fax: (914) 740-2101
