role of molecular mechanism in biochemistry
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A major goal in cell biology is to bridge the gap in our understanding of how molecular mechanisms contribute to cell and organismal physiology. Approaches well established in the physical sciences could be instrumental in achieving this goal. A better integration of the physical sciences with cell biology will therefore be an important step in our quest to decipher how cells work together to construct a living organism.
Over the past 60 years, the field of cell biology has been firmly rooted in understanding the molecular basis of complex cellular processes including genome replication, migration, metabolism, and adhesion. This progress has been enabled by advances in molecular biology, biochemistry, physical chemistry, single-molecule physics, and microscopy. Bringing together these disciplines has been successful in identifying the molecular composition of macromolecular machines, characterizing the structure and physical properties of single proteins within cells, reconstituting complex macromolecular machinery in vitro, and imaging the dynamics and function of these machines in vivo.
Despite this amazing progress, a major challenge facing cell biology is understanding how the chemical and physical properties of molecular machinery come together to guide cell processes. How do varied physical and chemical signals in the environment determine whether a cell survives, proliferates, or migrates? What circuitry allows for a complex body plan to be constructed out of a single-celled embryo? The signals in the environment are noisy, with fluctuations in both time and space. Moreover, as anyone who has tried to characterize cells is aware, cell phenotypes are variable both across individual cells and within a single cell over time. In the presence of all this noise, cells execute some processes exceedingly reliably (e.g., DNA segregation in cell division). Others, such as the determination of protrusive activity in a migrating cell, appear to be more variable. How does this complex network of stochastic chemical and mechanical machinery enable robust and complex decision making at the cell scale?
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