Predicting the Effect of Mutations on Protein Folding and Protein-Protein Interactions

The structural basis of conserved residue variant effect on enzyme activity of UGT2B15

UDP-glucuronosyltransferase 2B15 (UGT2B15) is a crucial phase II drug-metabolizing enzyme, which glucuronidates various compounds, including clinical drugs and hormones. Mutants might affect glucuronidation, leading to a disruption of drug metabolism in vivo and decrease of therapeutic effect. Here, we mainly analyzed two representative mutants, H401P and L446S, on UGT2B15 activity using glucuronidation assays, molecular dynamic (MD) simulation and X-ray diffraction methods. The enzyme activity of L446S obviously increased six-fold than the wild type, although the enzyme activities of P191L, T374A, and H401P were lost apparently. Furthermore, we used MD simulations to calculate the energy change in the catalytic process of H401P and L446S, and the results indicated the free binding energies of H401P mutant to oxazepam and UDPGA were -30.98 ± 1.00 kcal/mol and -36.42 ± 1.04 kcal/mol, respectively, increased obviously compared to wild type, suggesting the mutation on position 401 had a crucial effect on the catalysis. Moreover, the three-dimensional structure of UGT2B15 C-terminal domain L446S was determined through protein crystallography and X-ray diffraction technology and the results suggested that one more hydrogen bonding between S446 and K410 was formed in the S446 crystal structure, compared to the wild type. Isothermal titration calorimetry assay further revealed the K_d values of C-terminal domain of UGT2B15 harbored L446S towards the cofactor UDPGA was similar to the value of wild type. Above all, our results pointed out that H401P and L446S affected the enzyme activity by different mechanism. Our work provided a helpful mechanism for variance explained in the UGTs catalyzation process.

Multitasking Na+/Taurocholate Cotransporting Polypeptide (NTCP) as a Drug Target for HBV Infection: From Protein Engineering to Drug Discovery

Hepatitis B virus (HBV) infections are among the major public health concerns worldwide with more than 250 million of chronically ill individuals. Many of them are additionally infected with the Hepatitis D virus, a satellite virus to HBV. Chronic infection frequently leads to serious liver diseases including cirrhosis and hepatocellular carcinoma, the most common type of liver cancer. Although current antiviral therapies can control HBV replication and slow down disease progress, there is an unmet medical need to identify therapies to cure this chronic infectious disease. Lately, a noteworthy progress in fighting against HBV has been made by identification of the high-affinity hepatic host receptor for HBV and HDV, namely Na⁺/taurocholate cotransporting polypeptide (NTCP, gene symbol SLC10A1). Next to its primary function as hepatic uptake transporter for bile acids, NTCP is essential for the cellular entry of HBV and HDV into hepatocytes. Due to this high-ranking discovery, NTCP has become a valuable target for drug development strategies for HBV/HDV-infected patients. In this review, we will focus on a newly predicted three-dimensional NTCP model that was generated using computational approaches and discuss its value in understanding the NTCP’s membrane topology, substrate and virus binding taking place in plasma membranes. We will review existing data on structural, functional, and biological consequences of amino acid residue changes and mutations that lead to loss of NTCP’s transport and virus receptor functions. Finally, we will discuss new directions for future investigations aiming at development of new NTCP-based HBV entry blockers that inhibit HBV tropism in human hepatocytes.

Performance of Web tools for predicting changes in protein stability caused by mutations

BACKGROUND

Despite decades on developing dedicated Web tools, it is still difficult to predict correctly the changes of the thermodynamic stability of proteins caused by mutations. Here, we assessed the reliability of five recently developed Web tools, in order to evaluate the progresses in the field.

RESULTS

The results show that, although there are improvements in the field, the assessed predictors are still far from ideal. Prevailing problems include the bias towards destabilizing mutations, and, in general, the results are unreliable when the mutation causes a ΔΔG within the interval ± 0.5 kcal/mol. We found that using several predictors and combining their results into a consensus is a rough, but effective way to increase reliability of the predictions.

CONCLUSIONS

We suggest all developers to consider in their future tools the usage of balanced data sets for training of predictors, and all users to combine the results of multiple tools to increase the chances of having correct predictions about the effect of mutations on the thermodynamic stability of a protein.

Molecular mechanics and dynamic simulations of well-known Kabuki syndrome-associated KDM6A variants reveal putative mechanisms of dysfunction

BACKGROUND

Kabuki syndrome is a genetic disorder that affects several body systems and presents with variations in symptoms and severity. The syndrome is named for a common phenotype of faces resembling stage makeup used in a Japanese traditional theatrical art named kabuki. The most frequent cause of this syndrome is mutations in the H3K4 family of histone methyltransferases while a smaller percentage results from genetic alterations affecting the histone demethylase, KDM6A. Because of the rare presentation of the latter form of the disease, little is known about how missense changes in the KDM6A protein sequence impact protein function.

RESULTS

In this study, we use molecular mechanic and molecular dynamic simulations to enhance the annotation and mechanistic interpretation of the potential impact of eleven KDM6A missense variants found in Kabuki syndrome patients. These variants (N910S, D980V, S1025G, C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W, and R1351Q) are predicted to be pathogenic, likely pathogenic or of uncertain significance by sequence-based analysis. Here, we demonstrate, for the first time, that although Kabuki syndrome missense variants are found outside the functionally critical regions, they could affect overall function by significantly disrupting global and local conformation (C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W and R1351Q), chemical environment (C1153R, C1153Y, P1195L, L1200F, Q1212R, Q1248R, R1255W and R1351Q), and/or molecular dynamics of the catalytic domain (all variants). In addition, our approaches predict that many mutations, in particular C1153R, could allosterically disrupt the key enzymatic interactions of KDM6A.

CONCLUSIONS

Our study demonstrates that the KDM6A Kabuki syndrome variants may impair histone demethylase function through various mechanisms that include altered protein integrity, local environment, molecular interactions and protein dynamics. Molecular dynamics simulations of the wild type and the variants are critical to gain a better understanding of molecular dysfunction. This type of comprehensive structure- and MD-based analyses should help develop improved impact scoring systems to interpret the damaging effects of variants in this protein and other related proteins as well as provide detailed mechanistic insight that is not currently predictable from sequence alone.

Insight into molecular characteristics of SARS-CoV-2 spike protein following D614G point mutation, a molecular dynamics study

Undoubtedly, the SARS-CoV-2 has become a major concern for all societies due to its catastrophic effects on public health. In addition, mutations and changes in the structure of the virus make it difficult to design effective treatment. Moreover, the amino acid sequence of a protein is a major factor in the formation of the second and tertiary structure in a protein. Amino acid replacement can have noticeable effects on the folding of a protein, especially if an asymmetric change (substitution of polar residue with non-polar, charged with an uncharged, positive charge with a negative charge, or large residue with small residue) occurs. D614G as a spike mutant of SARS-CoV-2 previously identified as an associated risk factor with a high mortality rate of this virus. Using structural bioinformatics, our group determined that D614G mutation could cause extensive changes in SARS-CoV-2 behavior including the secondary structure, receptor binding pattern, 3D conformation, and stability of it.

Communicated by Ramaswamy H. Sarma

Approaches to Investigating the Protein Interactome of PTEN

The tumor suppressor phosphatase and tensin homologue (PTEN) is a redox-sensitive dual specificity phosphatase with an essential role in the negative regulation of the PI3K-AKT signaling pathway, affecting metabolic and cell survival processes. PTEN is commonly mutated in cancer, and dysregulation in the metabolism of PIP₃ is implicated in other diseases such as diabetes. PTEN interactors are responsible for some functional roles of PTEN beyond the negative regulation of the PI3K pathway and are thus of great importance in cell biology. Both high-data content proteomics-based approaches and low-data content PPI approaches have been used to investigate the interactome of PTEN and elucidate further functions of PTEN. While low-data content approaches rely on co-immunoprecipitation and Western blotting, and as such require previously generated hypotheses, high-data content approaches such as affinity pull-down proteomic assays or the yeast 2-hybrid system are hypothesis generating. This review provides an overview of the PTEN interactome, including redox effects, and critically appraises the methods and results of high-data content investigations into the global interactome of PTEN. The biological significance of findings from recent studies is discussed and illustrates the breadth of cellular functions of PTEN that can be discovered by these approaches.

Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge

Predicting the impact of mutations on proteins remains an important problem. As part of the CAGI5 frataxin challenge, we evaluate the accuracy with which Provean, FoldX, and ELASPIC can predict changes in the Gibbs free energy of a protein using a limited data set of eight mutations. We find that different methods have distinct strengths and limitations, with no method being strictly superior to other methods on all metrics. ELASPIC achieves the highest accuracy while also providing a web interface which simplifies the evaluation and analysis of mutations. FoldX is slightly less accurate than ELASPIC but is easier to run locally, as it does not depend on external tools or datasets. Provean achieves reasonable results while being computational less expensive than the other methods and not requiring a structure of the protein. In addition to methods submitted to the CAGI5 community experiment, and with the aim to inform about other methods with high accuracy, we also evaluate predictions made by Rosetta's ddg_monomer protocol, Rosetta's cartesian_ddg protocol, and thermodynamic integration calculations using Amber package. ELASPIC still achieves the highest accuracy, while Rosetta's catesian_ddg protocol appears to perform best in capturing the overall trend in the data.