Understanding the molecular function of proteins is greatly enhanced by insights gained from their three-dimensional structures. Since experimental structures are only available for a small fraction of proteins, computational methods for protein structure modeling play an increasingly important role. Comparative protein structure modeling is currently the most accurate method, yielding models suitable for a wide spectrum of applications, such as structure-guided drug development or virtual screening. Stable and reliable automated prediction pipelines have been developed to apply large-scale comparative modeling to whole genomes or entire sequence databases. Model repositories give access to these annotated and evaluated models. In this review, we will discuss recent developments in automated comparative modeling and provide selected examples illustrating the use of homology models.
Kopp et al. (Fri,) studied this question.
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