Pivotal role of a conserved histidine in Escherichia coli ribonuclease HI as proposed by X-ray crystallography

Systematic enhancement of protein crystallization efficiency by bulk lysine-to-arginine (KR) substitution

Structural genomics consortia established that protein crystallization is the primary obstacle to structure determination using x-ray crystallography. We previously demonstrated that crystallization propensity is systematically related to primary sequence, and we subsequently performed computational analyses showing that arginine is the most overrepresented amino acid in crystal-packing interfaces in the Protein Data Bank. Given the similar physicochemical characteristics of arginine and lysine, we hypothesized that multiple lysine-to-arginine (KR) substitutions should improve crystallization. To test this hypothesis, we developed software that ranks lysine sites in a target protein based on the redundancy-corrected KR substitution frequency in homologs. This software can be run interactively on the worldwide web at https://www.pxengineering.org/. We demonstrate that three unrelated single-domain proteins can tolerate 5-11 KR substitutions with at most minor destabilization, and, for two of these three proteins, the construct with the largest number of KR substitutions exhibits significantly enhanced crystallization propensity. This approach rapidly produced a 1.9 Å crystal structure of a human protein domain refractory to crystallization with its native sequence. Structures from Bulk KR-substituted domains show the engineered arginine residues frequently make hydrogen-bonds across crystal-packing interfaces. We thus demonstrate that Bulk KR substitution represents a rational and efficient method for probabilistic engineering of protein surface properties to improve crystallization.

Metal-binding and folding thermodynamics of Escherichia coli ribonuclease HI related to its catalytic function

Escherichia coli ribonuclease HI (RNH) hydrolyzes the RNA strands of RNA/DNA hybrids in the presence of Mg²⁺ at the highest level, relative to other metal ions. The Mg²⁺ binding affinity was 8.39 × 10³ M^-1, which was lower than those of other metal ions. The low-affinity binder can express the maximum catalytic activity of RNH. The stability of RNH increased with increasing metal ion concentration, except for Zn²⁺. The thermodynamic origin for enhancing the stability of RNH with Mg²⁺ was more favorable entropy compared to those with other metal ions, indicating that Mg²⁺ binding changes the RNH structure while maintaining flexibility. Upon H124A mutation, the metal ion binding affinities decreased for Mn²⁺ and Zn²⁺ to a relatively large extent. The present thermodynamic analyses provide information on the structural dynamics of RNH with metal ion exchangeable binding, which can reasonably explain the metal-ion-dependent catalytic activity.

Verification: model-free phasing with enhanced predicted models in ARCIMBOLDO_SHREDDER

Structure predictions have matched the accuracy of experimental structures from close homologues, providing suitable models for molecular replacement phasing. Even in predictions that present large differences due to the relative movement of domains or poorly predicted areas, very accurate regions tend to be present. These are suitable for successful fragment-based phasing as implemented in ARCIMBOLDO. The particularities of predicted models are inherently addressed in the new predicted_model mode, rendering preliminary treatment superfluous but also harmless. B-value conversion from predicted LDDT or error estimates, the removal of unstructured polypeptide, hierarchical decomposition of structural units from domains to local folds and systematically probing the model against the experimental data will ensure the optimal use of the model in phasing. Concomitantly, the exhaustive use of models and stereochemistry in phasing, refinement and validation raises the concern of crystallographic model bias and the need to critically establish the information contributed by the experiment. Therefore, in its predicted_model mode ARCIMBOLDO_SHREDDER will first determine whether the input model already constitutes a solution or provides a straightforward solution with Phaser. If not, extracted fragments will be located. If the landscape of solutions reveals numerous, clearly discriminated and consistent probes or if the input model already constitutes a solution, model-free verification will be activated. Expansions with SHELXE will omit the partial solution seeding phases and all traces outside their respective masks will be combined in ALIXE, as far as consistent. This procedure completely eliminates the molecular replacement search model in favour of the inferences derived from this model. In the case of fragments, an incorrect starting hypothesis impedes expansion. The predicted_model mode has been tested in different scenarios.