ConSurf

ConSurf estimates evolutionary conservation of amino acid and nucleotide positions in proteins, DNA, and RNA by analyzing phylogenetic relationships among homologous sequences.

Key Features:

• Site-Specific Conservation Analysis: Assesses conservation of amino acid and nucleotide positions by estimating site-specific evolutionary rates, where functionally or structurally important sites show lower rates.
• Probabilistic Methods: Employs maximum-likelihood and Bayesian paradigms to infer site-specific evolutionary rates while considering parameters such as number of sequences, branch lengths, rate-distribution shapes, and sequence length.
• Bayesian Superiority: Comparative simulation studies indicate the Bayesian approach yields more accurate site-rate inference than maximum-likelihood under a wide range of conditions by incorporating prior information.
• Branch Length Estimation: Emphasizes sequential estimation of branch lengths prior to site-rate inference, which produces superior results compared to simultaneous estimation.

Scientific Applications:

• Functional and Structural Analysis: Identifies conserved sites to infer regions critical for protein function or stability.
• Evolutionary Studies: Highlights positions under evolutionary constraint to study selective pressures on biomolecules.
• Protein Engineering: Guides design decisions by distinguishing conserved and variable sites to avoid disrupting essential functions.

Methodology:

Performs phylogenetic analysis using trees constructed from homologous sequences; conducts simulation studies to compare maximum-likelihood and Bayesian paradigms and to optimize parameters; and employs sequential estimation by estimating branch lengths prior to inferring site-specific evolutionary rates.