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Crystal structures and calorimetry reveal catalytically relevant binding mode of coproporphyrin and coproheme in coproporphyrin ferrochelatase.

ABSTRACT: Coproporphyrin ferrochelatases (CpfCs, EC 4.99.1.9) insert ferrous iron into coproporphyrin III yielding coproheme. CpfCs are utilized by prokaryotic, mainly monoderm (Gram-positive) bacteria within the recently detected coproporphyrin-dependent (CPD) heme biosynthesis pathway. Here, we present a comprehensive study on CpfC from Listeria monocytogenes (LmCpfC) including the first crystal structure of a coproheme-bound CpfC. Comparison of crystal structures of apo-LmCpfC and coproheme-LmCpfC allowed identification of structural rearrangements and of amino acids involved in tetrapyrrole macrocycle and Fe2+ binding. Differential scanning calorimetry of apo-, coproporphyrin III-, and coproheme-LmCpfC underline the pronounced noncovalent interaction of both coproporphyrin and coproheme with the protein (?Tm = 11 °C compared to apo-LmCpfC), which includes the propionates (p2, p4, p6, p7) and the amino acids Arg29, Arg45, Tyr46, Ser53, and Tyr124. Furthermore, the thermodynamics and kinetics of coproporphyrin III and coproheme binding to apo-LmCpfC is presented as well as the kinetics of insertion of ferrous iron into coproporphyrin III-LmCpfC that immediately leads to formation of ferric coproheme-LmCpfC (kcat /KM = 4.7 × 105 m-1 ·s-1 ). We compare the crystal structure of coproheme-LmCpfC with available structures of CpfCs with artificial tetrapyrrole macrocycles and discuss our data on substrate binding, iron insertion and substrate release in the context of the CPD heme biosynthesis pathway. ENZYME: EC 4.99.1.9 DATABASE: pdb-codes of structural data in this work: 6RWV, 6SV3.

SUBMITTER: Hofbauer S

PROVIDER: S-EPMC7340540 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Project description:Binding affinity prediction is one of the most critical components to computer-aided structure-based drug design. Despite advances in first-principle methods for predicting binding affinity, empirical scoring functions that are fast and only relatively accurate are still widely used in structure-based drug design. With the increasing availability of X-ray crystallographic structures in the Protein Data Bank and continuing application of biophysical methods such as isothermal titration calorimetry to measure thermodynamic parameters contributing to binding free energy, sufficient experimental data exists that scoring functions can now be derived by separating enthalpic (?H) and entropic (T?S) contributions to binding free energy (?G). PHOENIX, a scoring function to predict binding affinities of protein-ligand complexes, utilizes the increasing availability of experimental data to improve binding affinity predictions by the following: model training and testing using high-resolution crystallographic data to minimize structural noise, independent models of enthalpic and entropic contributions fitted to thermodynamic parameters assumed to be thermodynamically biased to calculate binding free energy, use of shape and volume descriptors to better capture entropic contributions. A set of 42 descriptors and 112 protein-ligand complexes were used to derive functions using partial least-squares for change of enthalpy (?H) and change of entropy (T?S) to calculate change of binding free energy (?G), resulting in a predictive r2 (r(pred)2) of 0.55 and a standard error (SE) of 1.34 kcal/mol. External validation using the 2009 version of the PDBbind "refined set" (n = 1612) resulted in a Pearson correlation coefficient (R(p)) of 0.575 and a mean error (ME) of 1.41 pK(d). Enthalpy and entropy predictions were of limited accuracy individually. However, their difference resulted in a relatively accurate binding free energy. While the development of an accurate and applicable scoring function was an objective of this study, the main focus was evaluation of the use of high-resolution X-ray crystal structures with high-quality thermodynamic parameters from isothermal titration calorimetry for scoring function development. With the increasing application of structure-based methods in molecular design, this study suggests that using high-resolution crystal structures, separating enthalpy and entropy contributions to binding free energy, and including descriptors to better capture entropic contributions may prove to be effective strategies toward rapid and accurate calculation of binding affinity.

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Crystal structures and calorimetry reveal catalytically relevant binding mode of coproporphyrin and coproheme in coproporphyrin ferrochelatase.

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