Tyrp1 Mutant Variants Associated with OCA3: Computational Characterization of Protein Stability and Ligand Binding.

Oculocutaneous albinism type 3 (OCA3) is an autosomal recessive disorder caused by mutations in the TYRP1 gene. Tyrosinase-related protein 1 (Tyrp1) is involved in eumelanin synthesis, catalyzing the oxidation of 5,6-dihydroxyindole-2-carboxylic acid oxidase (DHICA) to 5,6-indolequinone-2-carboxylic acid (IQCA). Here, for the first time, four OCA3-causing mutations of Tyrp1, C30R, H215Y, D308N, and R326H, were investigated computationally to understand Tyrp1 protein stability and catalytic activity. Using the Tyrp1 crystal structure (PDB:5M8L), global mutagenesis was conducted to evaluate mutant protein stability. Consistent with the foldability parameter, C30R and H215Y should exhibit greater instability, and two other mutants, D308N and R326H, are expected to keep a native conformation. SDS-PAGE and Western blot analysis of the purified recombinant proteins confirmed that the foldability parameter correctly predicted the effect of mutations critical for protein stability. Further, the mutant variant structures were built and simulated for 100 ns to generate free energy landscapes and perform docking experiments. Free energy landscapes formed by Y362, N378, and T391 indicate that the binding clefts of C30R and H215Y mutants are larger than the wild-type Tyrp1. In docking simulations, the hydrogen bond and salt bridge interactions that stabilize DHICA in the active site remain similar among Tyrp1, D308N, and R326H. However, the strengths of these interactions and stability of the docked ligand may decrease proportionally to mutation severity due to the larger and less well-defined natures of the binding clefts in mutants. Mutational perturbations in mutants that are not unfolded may result in allosteric alterations to the active site, reducing the stability of protein-ligand interactions.

Characterization of Temperature-Dependent Kinetics of Oculocutaneous Albinism-Causing Mutants of Tyrosinase.

Human tyrosinase (Tyr) is a glycoenzyme that catalyzes the first and rate-limiting step in melanin production, and its gene (TYR) is mutated in many cases of oculocutaneous albinism type 1 (OCA1). The mechanisms by which individual mutations contribute to the diverse pigmentation phenotype in patients with OCA1 have only began to be examined and remain to be delineated. Here, we analyze the temperature-dependent kinetics of wild-type Tyr (WT) and two OCA1B mutant variants (R422Q and P406L) using Michaelis-Menten and Van't Hoff analyses. Recombinant truncated human Tyr proteins (residues 19-469) were produced in the whole insect Trichoplusia Ni larvae. Proteins were purified by a combination of affinity and size-exclusion chromatography. The temperature dependence of diphenol oxidase protein activities and kinetic parameters were measured by dopachrome absorption. Using the same experimental conditions, computational simulations were performed to assess the temperature-dependent association of L-DOPA and Tyr. Our results revealed, for the first time, that the association of L-DOPA with R422Q and P406L followed by dopachrome formation is a complex reaction supported by enthalpy and entropy forces. We show that the WT has a higher turnover number as compared with both R422Q and P406L. Elucidating the kinetics and thermodynamics of mutant variants of Tyr in OCA1B helps to understand the mechanisms by which they lower Tyr catalytic activity and to discover novel therapies for patients.

Finding Druggable Sites in Proteins Using TACTICS.

Structure-based drug discovery efforts require knowledge of where drug-binding sites are located on target proteins. To address the challenge of finding druggable sites, we developed a machine-learning algorithm called TACTICS (trajectory-based analysis of conformations to identify cryptic sites), which uses an ensemble of molecular structures (such as molecular dynamics simulation data) as input. First, TACTICS uses k-means clustering to select a small number of conformations that represent the overall conformational heterogeneity of the data. Then, TACTICS uses a random forest model to identify potentially bindable residues in each selected conformation, based on protein motion and geometry. Lastly, residues in possible binding pockets are scored using fragment docking. As proof-of-principle, TACTICS was applied to the analysis of simulations of the SARS-CoV-2 main protease and methyltransferase and the Yersinia pestis aryl carrier protein. Our approach recapitulates known small-molecule binding sites and predicts the locations of sites not previously observed in experimentally determined structures. The TACTICS code is available at https://github.com/Albert-Lau-Lab/tactics_protein_analysis.