Simple stochastic model for the evolution of protein lengths.
We analyze a simple discrete-time stochastic process for the theoretical modeling of the evolution of protein lengths. At every step of the process, a new protein is produced as a modification of one of the proteins already existing, and its length is assumed to be a random variable that depends only on the length of the originating protein. Thus a random recursive tree is produced over the natural numbers. If (quasi) scale invariance is assumed, the length distribution in a single history tends to a log-normal form with a specific signature of the deviations from exact Gaussianity. Comparison with the very large Similarity Matrix of Proteins database shows good agreement.
Dipartimento di Fisica G. Occhialini, Università di Milano-Bicocca and INFN, Sezione di Milano, Piazza della Scienza 3, I-20126 Milano, Italy.
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D000595:Amino Acid Sequence; D001483:Base Sequence; D003198:Computer Simulation; D019143:Evolution, Molecular; D008956:Models, Chemical; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D017421:Sequence Analysis / Q000379:methods*; D013269:Stochastic Processes
D011506:Proteins