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TransCent: computational enzyme design by transferring active sites and considering constraints relevant for catalysis.

Fischer A, Enkler N, Neudert G, Bocola M, Sterner R, Merkl R - BMC Bioinformatics (2009)

Bottom Line: The redesign of oxidoreductase cytochrome P450 was analyzed in detail.A recapitulation test on native enzymes showed that TransCent proposes active sites that resemble the native enzyme more than those generated by RosettaDesign alone.Additional tests demonstrated that each module contributes to the overall performance in a statistically significant manner.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut für Biophysik und Physikalische Biochemie, Universität Regensburg, Regensburg, Germany. andre.fischer@biologie.uni-regensburg.de

ABSTRACT

Background: Computational enzyme design is far from being applicable for the general case. Due to computational complexity and limited knowledge of the structure-function interplay, heuristic methods have to be used.

Results: We have developed TransCent, a computational enzyme design method supporting the transfer of active sites from one enzyme to an alternative scaffold. In an optimization process, it balances requirements originating from four constraints. These are 1) protein stability, 2) ligand binding, 3) pKa values of active site residues, and 4) structural features of the active site. Each constraint is handled by an individual software module. Modules processing the first three constraints are based on state-of-the-art concepts, i.e. RosettaDesign, DrugScore, and PROPKA. To account for the fourth constraint, knowledge-based potentials are utilized. The contribution of modules to the performance of TransCent was evaluated by means of a recapitulation test. The redesign of oxidoreductase cytochrome P450 was analyzed in detail. As a first application, we present and discuss models for the transfer of active sites in enzymes sharing the frequently encountered triosephosphate isomerase fold.

Conclusion: A recapitulation test on native enzymes showed that TransCent proposes active sites that resemble the native enzyme more than those generated by RosettaDesign alone. Additional tests demonstrated that each module contributes to the overall performance in a statistically significant manner.

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Dependence of distance to the ligand and residue conservation for recapitulated and not recapitulated residues on TransCent's configuration. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. All residues resi ϵACT_CENT were analyzed. The left panel depicts the mean distance of their Cβ-atoms (Cα in case of Gly) to the nearest atom of the ligand. The right panel depicts the mean conservation as deduced from the respective columns of the MSA and as expressed by the score cons(resi). For the models, residues were grouped: "identical AA" are those residues possessing the same amino acid as the templates, "different AA" are those ones, where TransCent proposed a different amino acid. Abbreviations for modules are: ST (stability), LB (ligand binding), KP (knowledge-based potential) and PK (pKa values).
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Figure 3: Dependence of distance to the ligand and residue conservation for recapitulated and not recapitulated residues on TransCent's configuration. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. All residues resi ϵACT_CENT were analyzed. The left panel depicts the mean distance of their Cβ-atoms (Cα in case of Gly) to the nearest atom of the ligand. The right panel depicts the mean conservation as deduced from the respective columns of the MSA and as expressed by the score cons(resi). For the models, residues were grouped: "identical AA" are those residues possessing the same amino acid as the templates, "different AA" are those ones, where TransCent proposed a different amino acid. Abbreviations for modules are: ST (stability), LB (ligand binding), KP (knowledge-based potential) and PK (pKa values).

Mentions: For the above recapitulation test, all residues of ACT_CENT are considered equally important. However, their distance to the ligand and their conservation levels (deduced from the MSA) differ. For a model of higher quality, it is plausible to expect a higher rate of recapitulated amino acids at those positions which are closer to the ligand or which are more conserved. Analyzing these two parameters, we further assessed the performance of TransCent. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. For each residue resi, the distance of the Cβ-atom (Cα in case of Gly) to the nearest atom of the ligand was determined. In addition, related MSAs were used to deduce the residue-specific conservation cons(resi); see Eq. (7). Modeled residues were grouped according to their concordance with the template. The group "identical AA" contains the recapitulated positions; "different AA" are those ones, where TransCent proposed an amino acid not seen in the template. For these two groups, mean distance values were determined and plotted. Figure 3 shows the results. By utilizing more modules, the distance of "identical AA", i.e. recapitulated residues, decreased steadily from 4.0 Å when using TransCent(ST), to 3.6 Å when enabling all modules. Synchronously, the distance of "different AA" increased from 3.9 Å to 4.3 Å. That is, the more modules are used, the higher is the probability that residues located close to the ligand are recapitulated. The right panel depicts the mean conservation as deduced from the respective MSAs and as expressed by the score cons(resi). By using more modules, the conservation level of "identical AA" (recapitulated residues) increased, whereas the conservation level of "different AA" decreased. For TransCent(ST), the conservation for "identical AA" is 0.79 and for "different AA" it is 0.75. For TransCent(*), the mean conservation for "identical AA" increased to 0.84, whereas the score for "different AA" fell to 0.64. That is, the more modules are used, the higher is the probability of conserved residues to be recapitulated. In summary, the results indicate that the active sites became more similar to the template by using additional modules. Note that the shell defining an active site for TransCent is larger than that used elsewhere [11]. Therefore, it is not implausible, that a certain fraction of these residues differs from the template. This notion is supported by the above results: The mean conservation for the set "different AA", i.e. those residues decorated by TransCent with an amino acid not seen in the template is 0.64. This value indicates a substantial degree of variation even in MSAs which sample closely related homologs.


TransCent: computational enzyme design by transferring active sites and considering constraints relevant for catalysis.

Fischer A, Enkler N, Neudert G, Bocola M, Sterner R, Merkl R - BMC Bioinformatics (2009)

Dependence of distance to the ligand and residue conservation for recapitulated and not recapitulated residues on TransCent's configuration. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. All residues resi ϵACT_CENT were analyzed. The left panel depicts the mean distance of their Cβ-atoms (Cα in case of Gly) to the nearest atom of the ligand. The right panel depicts the mean conservation as deduced from the respective columns of the MSA and as expressed by the score cons(resi). For the models, residues were grouped: "identical AA" are those residues possessing the same amino acid as the templates, "different AA" are those ones, where TransCent proposed a different amino acid. Abbreviations for modules are: ST (stability), LB (ligand binding), KP (knowledge-based potential) and PK (pKa values).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2667513&req=5

Figure 3: Dependence of distance to the ligand and residue conservation for recapitulated and not recapitulated residues on TransCent's configuration. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. All residues resi ϵACT_CENT were analyzed. The left panel depicts the mean distance of their Cβ-atoms (Cα in case of Gly) to the nearest atom of the ligand. The right panel depicts the mean conservation as deduced from the respective columns of the MSA and as expressed by the score cons(resi). For the models, residues were grouped: "identical AA" are those residues possessing the same amino acid as the templates, "different AA" are those ones, where TransCent proposed a different amino acid. Abbreviations for modules are: ST (stability), LB (ligand binding), KP (knowledge-based potential) and PK (pKa values).
Mentions: For the above recapitulation test, all residues of ACT_CENT are considered equally important. However, their distance to the ligand and their conservation levels (deduced from the MSA) differ. For a model of higher quality, it is plausible to expect a higher rate of recapitulated amino acids at those positions which are closer to the ligand or which are more conserved. Analyzing these two parameters, we further assessed the performance of TransCent. Different combinations of modules were used to generate 20 models each in a recapitulation experiment for all enzymes belonging to ENZ_TESThom. For each residue resi, the distance of the Cβ-atom (Cα in case of Gly) to the nearest atom of the ligand was determined. In addition, related MSAs were used to deduce the residue-specific conservation cons(resi); see Eq. (7). Modeled residues were grouped according to their concordance with the template. The group "identical AA" contains the recapitulated positions; "different AA" are those ones, where TransCent proposed an amino acid not seen in the template. For these two groups, mean distance values were determined and plotted. Figure 3 shows the results. By utilizing more modules, the distance of "identical AA", i.e. recapitulated residues, decreased steadily from 4.0 Å when using TransCent(ST), to 3.6 Å when enabling all modules. Synchronously, the distance of "different AA" increased from 3.9 Å to 4.3 Å. That is, the more modules are used, the higher is the probability that residues located close to the ligand are recapitulated. The right panel depicts the mean conservation as deduced from the respective MSAs and as expressed by the score cons(resi). By using more modules, the conservation level of "identical AA" (recapitulated residues) increased, whereas the conservation level of "different AA" decreased. For TransCent(ST), the conservation for "identical AA" is 0.79 and for "different AA" it is 0.75. For TransCent(*), the mean conservation for "identical AA" increased to 0.84, whereas the score for "different AA" fell to 0.64. That is, the more modules are used, the higher is the probability of conserved residues to be recapitulated. In summary, the results indicate that the active sites became more similar to the template by using additional modules. Note that the shell defining an active site for TransCent is larger than that used elsewhere [11]. Therefore, it is not implausible, that a certain fraction of these residues differs from the template. This notion is supported by the above results: The mean conservation for the set "different AA", i.e. those residues decorated by TransCent with an amino acid not seen in the template is 0.64. This value indicates a substantial degree of variation even in MSAs which sample closely related homologs.

Bottom Line: The redesign of oxidoreductase cytochrome P450 was analyzed in detail.A recapitulation test on native enzymes showed that TransCent proposes active sites that resemble the native enzyme more than those generated by RosettaDesign alone.Additional tests demonstrated that each module contributes to the overall performance in a statistically significant manner.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut für Biophysik und Physikalische Biochemie, Universität Regensburg, Regensburg, Germany. andre.fischer@biologie.uni-regensburg.de

ABSTRACT

Background: Computational enzyme design is far from being applicable for the general case. Due to computational complexity and limited knowledge of the structure-function interplay, heuristic methods have to be used.

Results: We have developed TransCent, a computational enzyme design method supporting the transfer of active sites from one enzyme to an alternative scaffold. In an optimization process, it balances requirements originating from four constraints. These are 1) protein stability, 2) ligand binding, 3) pKa values of active site residues, and 4) structural features of the active site. Each constraint is handled by an individual software module. Modules processing the first three constraints are based on state-of-the-art concepts, i.e. RosettaDesign, DrugScore, and PROPKA. To account for the fourth constraint, knowledge-based potentials are utilized. The contribution of modules to the performance of TransCent was evaluated by means of a recapitulation test. The redesign of oxidoreductase cytochrome P450 was analyzed in detail. As a first application, we present and discuss models for the transfer of active sites in enzymes sharing the frequently encountered triosephosphate isomerase fold.

Conclusion: A recapitulation test on native enzymes showed that TransCent proposes active sites that resemble the native enzyme more than those generated by RosettaDesign alone. Additional tests demonstrated that each module contributes to the overall performance in a statistically significant manner.

Show MeSH
Related in: MedlinePlus