Why twenty amino acid residue types suffice(d) to support all living systems.

It is well known that proteins are built up from an alphabet of 20 different amino acid types. These suffice to enable the protein to fold into its operative form relevant to its required functional roles. For carrying out these allotted functions, there may in some cases be a need for post-translational modifications and it has been established that an additional three types of amino acid have at some point been recruited into this process.

A tensegrity model for hydrogen bond networks in proteins.

Hydrogen-bonding networks in proteins considered as structural tensile elements are in balance separately from any other stabilising interactions that may be in operation. The hydrogen bond arrangement in the network is reminiscent of tensegrity structures in architecture and sculpture. Tensegrity has been discussed before in cells and tissues and in proteins.

The fate of proteins in outer space.

It is well established that any properly conducted biophysical studies of proteins must take appropriate account of solvent. For water-soluble proteins it has been an article of faith that water is largely responsible for stabilizing the fold, a notion that has recently come under increasing scrutiny. Further, there are some instances when proteins are studied experimentally in the absence of solvent, as in matrix-assisted laser desorption/ionization or electrospray mass spectrometry, for example, or in organic solvents for protein engineering purposes.

Melody discrimination and protein fold classification.

One of the greatest challenges in theoretical biophysics and bioinformatics is the identification of protein folds from sequence data. This can be regarded as a pattern recognition problem. In this paper we report the use of a melody generation software where the inputs are derived from calculations of evolutionary information, secondary structure, flexibility, hydropathy and solvent accessibility from multiple sequence alignment data.

Comparison of Algorithms for Prediction of Protein Structural Features from Evolutionary Data.

Proteins have many functions and predicting these is still one of the major challenges in theoretical biophysics and bioinformatics. Foremost amongst these functions is the need to fold correctly thereby allowing the other genetically dictated tasks that the protein has to carry out to proceed efficiently. In this work, some earlier algorithms for predicting protein domain folds are revisited and they are compared with more recently developed methods.