IBM forms large protein folding team

Understanding of this process would also represent understanding of how the code in the one-dimensional DNA molecules becomes the three-dimensional form that we call life, would allow us to interpret the output of the human genome project and other genome projects, and improve our ability to design drugs by seeing the three- dimensional molecular details of the proteins in our bodies (with which almost all kinds of drug interact). At present, such bottlenecks as the inability to read the human genome, and understand it in terms of protein structure and function, are prohibiting the development of major health care applications and pharmaceutical markets.

Proteins are also interesting as useful molecules themselves, not just as targets for drugs. The biotechnology industry is primarily concerned in producing proteins, ideally including novel proteins, as therapeutics. However, since proteins can also be made synthetically, by purely chemical methods, and fold up spontaneously according to the message in the sequence of amino acid residues which comprises them, a deeper understanding of how such pre-programmed chains of atoms fold up might have profound effect for all industry. It would allow us not only to design novel proteins, but also novel polymers and smart new materials. Ultimately this could also include a more practical approach to designing and producing those tiny machines and molecular-scale computer chips and storage devices envisaged by nanotechnology.

The team is drawn from many research and related divisions of IBM including several groups at the T.J. Watson Research Center in New York, Almaden in California, Zurich, Haifa and Tokyo, amongst others. The team first pulled together by Andrea Califano and Barry Robson, runs itself on a panel basis and the panel meets regularly, at New York or by telephone conference. Each team emphasises different aspects of the problem: particle and molecular mechanics simulation, mathematical optimization, the structure and searching of phase space, force fields, quantum mechanics, heuristic use of experimental and genome data, pattern recognition and biological data mining, game theory and computational theory including parallel processing methods, development of automated protein modelling and drug design pipelines, and other pharmaceutical, medical and health care applications including the longer term vision of fast-response, personalised molecular medicine.

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