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Although incorporation of amino acid analogs provides a powerful means of producing new protein structures with interesting functions, many amino acid analogs cannot be incorporated easily by using the wild-type aminoacyl-tRNA synthetase (aaRS). To be able to incorporate specific amino acid analogs site-specifically, it is useful to build a mutant aaRS that preferentially activates the analog compared with the natural amino acids. Experimental combinatorial studies to find such mutant aaRSs have been successful but can easily become costly and time-consuming. In this article, we describe the clash opportunity progressive (COP) computational method for designing a mutant aaRS to preferentially take up the analog compared with the natural amino acids. To illustrate this COP procedure, we apply it to the design of mutant Methanococcus jannaschii tyrosyltRNA synthetase (M.jann-TyrRS). Because the three-dimensional structure for M.jann-TyrRS was not available, we used the STRUCTFAST homology modeling procedure plus molecular dynamics with continuum solvent forces to predict the structure of wild-type M.jann-TyrRS. P roteins are synthesized with precise control over sequence, leading to the vast range of specific structures and functional properties observed in nature. Even so, the monomer pool for proteins is limited to the 20 natural amino acids. Increasing the monomer pool by incorporating new amino acid analogs would allow development of fascinating new bioderived polymers exhibiting novel but well controlled architectures (1, 2) and could lead to many interesting applications ranging from incorporating a fluorescence probe to elucidating specifics of protein structure and function (3), to incorporating selenium-substituted serine to facilitate crystallization processes in proteins (4).The in vivo incorporation of amino acid analogs into proteins is controlled in large measure by aminoacyl-tRNA synthetases (aaRS), the class of enzymes that safeguards the fidelity of amino acid incorporation into proteins. It has been demonstrated that the wild-type translational apparatus can be used to incorporate some amino acid analogs into protein (5-11). However, few amino acid analogs have been incorporated in proteins in vivo and the functionalities of these analogs have been limited. To expand the range of amino acid analogs that can be incorporated in vivo, it is desirable to manipulate the activity of the aaRS (12, 13). There has been steady progress in developing the 21st aaRS-suppressor tRNA pairs in vivo (14,15). A big success is the design of a novel orthogonal tRNA and tyrosyl-tRNA synthetase (TyrRS) from Methanococcus jannaschii TyrRS (hereafter denoted as M.jann-TyrRS) that incorporates O-methyl-L-tyrosine (OMe-Tyr) site-specifically in protein in response to an amber nonsense codon (16). Such procedures have tremendous potential to expand the genetic codes in living cells, but the current combinatorial experiments, which considered 5 20 mutation trials on 5 residues expected to be at the binding site of the tyros...

Structural genomics projects are producing protein structure data at an unprecedented rate. In this paper, we present the Target Informatics Platform (TIP), a novel structural informatics approach for amplifying the rapidly expanding body of experimental protein structure information to enhance the discovery and optimization of small molecule protein modulators on a genomic scale. In TIP, existing experimental structure information is augmented using a homology modeling approach, and binding sites across multiple target families are compared using a clique detection algorithm. We report here a detailed analysis of the structural coverage for the set of druggable human targets, highlighting drug target families where the level of structural knowledge is currently quite high, as well as those areas where structural knowledge is sparse. Furthermore, we demonstrate the utility of TIP's intra- and inter-family binding site similarity analysis using a series of retrospective case studies. Our analysis underscores the utility of a structural informatics infrastructure for extracting drug discovery-relevant information from structural data, aiding researchers in the identification of lead discovery and optimization opportunities as well as potential "off-target" liabilities.

STRUCTFAST is a novel profile-profile alignment algorithm capable of detecting weak similarities between protein sequences. The increased sensitivity and accuracy of the STRUCTFAST method are achieved through several unique features. First, the algorithm utilizes a novel dynamic programming engine capable of incorporating important information from a structural family directly into the alignment process. Second, the algorithm employs a rigorous analytical formula for profile-profile scoring to overcome the limitations of ad hoc scoring functions that require adjustable parameter training. Third, the algorithm employs Convergent Island Statistics (CIS) to compute the statistical significance of alignment scores independently for each pair of sequences. STRUCTFAST routinely produces alignments that meet or exceed the quality obtained by an expert human homology modeler, as evidenced by its performance in the latest CAFASP4 and CASP6 blind prediction benchmark experiments.

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