Exploring human porphobilinogen synthase metalloprotein by quantum biochemistry and evolutionary methods

Author:

Barbosa E D1ORCID,Neto J X Lima1ORCID,Teixeira D G2ORCID,Bezerra K S1ORCID,do Amaral V S3ORCID,Oliveira J I N1ORCID,Lima J P M Santos3ORCID,Machado L D4ORCID,Fulco U L1ORCID

Affiliation:

1. Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, 59072-970 Natal-RN, Brazil

2. Institute of Tropical Medicine, Universidade Federal do Rio Grande do Norte, 59072-970 Natal-RN, Brazil

3. Departamento de Bioquímica, Universidade Federal do Rio Grande do Norte, 59072-970 Natal-RN, Brazil

4. Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, 59072-970 Natal-RN, Brazil

Abstract

Abstract Previous studies have shown the porphobilinogen synthase (PBGS) zinc-binding mechanism and its conservation among the living cells. However, the precise molecular interaction of zinc with the active center of the enzyme is unknown. In particular, quantum chemistry techniques within the density functional theory (DFT) framework have been the key methodology to describe metalloproteins, when one is looking for a compromise between accuracy and computational feasibility. Considering this, we used DFT-based models within the molecular fractionation with conjugate caps scheme to evaluate the binding energy features of zinc interacting with the human PBGS. Besides, phylogenetic and clustering analyses were successfully employed in extracting useful information from protein sequences to identify groups of conserved residues that build the ions-binding site. Our results also report a conservative assessment of the relevant amino acids, as well as the benchmark analysis of the calculation models used. The most relevant intermolecular interactions in Zn2+–PBGS are due to the amino acids CYS0122, CYS0124, CYS0132, ASP0169, SER0168, ARG0221, HIS0131, ASP0120, GLY0133, VAL0121, ARG0209, and ARG0174. Among these residues, we highlighted ASP0120, GLY0133, HIS0131, SER0168, and ARG0209 by co-occurring in all clusters generated by unsupervised clustering analysis. On the other hand, the triple cysteines at 2.5 Å from zinc (CYS0122, CYS0124, and CYS0132) have the highest energy attraction and are absent in the taxa Viridiplantae, Sar, Rhodophyta, and some Bacteria. Additionally, the performance of the DFT-based models shows that the processing time-dependence is more associated with the choice of the basis set than the exchange–correlation functional.

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Oxford University Press (OUP)

Subject

Metals and Alloys,Biochemistry,Biomaterials,Biophysics,Chemistry (miscellaneous)

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