MutateX: an automated pipeline for in silico saturation mutagenesis of protein structures and structural ensembles.

Mutations, which result in amino acid substitutions, influence the stability of proteins and their binding to biomolecules. A molecular understanding of the effects of protein mutations is both of biotechnological and medical relevance. Empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. In silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of known mutations. Often software such as FoldX, while fast and reliable, lack the necessary automation features to apply them in a high-throughput manner. We introduce MutateX, a software to automate the prediction of ΔΔGs associated with the systematic mutation of each residue within a protein, or protein complex to all other possible residue types, using the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles, upon post-translational modifications and in multimeric assemblies. At the heart of MutateX lies an automated pipeline engine that handles input preparation, parallelization and outputs publication-ready figures. We illustrate the MutateX protocol applied to different case studies. The results of the high-throughput scan provided by our tools can help in different applications, such as the analysis of disease-associated mutations, to complement experimental deep mutational scans, or assist the design of variants for industrial applications. MutateX is a collection of Python tools that relies on open-source libraries. It is available free of charge under the GNU General Public License from https://github.com/ELELAB/mutatex.

AMBRA1 regulates cyclin D to guard S-phase entry and genomic integrity.

Mammalian development, adult tissue homeostasis and the avoidance of severe diseases including cancer require a properly orchestrated cell cycle, as well as error-free genome maintenance. The key cell-fate decision to replicate the genome is controlled by two major signalling pathways that act in parallel-the MYC pathway and the cyclin D-cyclin-dependent kinase (CDK)-retinoblastoma protein (RB) pathway1,2. Both MYC and the cyclin D-CDK-RB axis are commonly deregulated in cancer, and this is associated with increased genomic instability. The autophagic tumour-suppressor protein AMBRA1 has been linked to the control of cell proliferation, but the underlying molecular mechanisms remain poorly understood. Here we show that AMBRA1 is an upstream master regulator of the transition from G1 to S phase and thereby prevents replication stress. Using a combination of cell and molecular approaches and in vivo models, we reveal that AMBRA1 regulates the abundance of D-type cyclins by mediating their degradation. Furthermore, by controlling the transition from G1 to S phase, AMBRA1 helps to maintain genomic integrity during DNA replication, which counteracts developmental abnormalities and tumour growth. Finally, we identify the CHK1 kinase as a potential therapeutic target in AMBRA1-deficient tumours. These results advance our understanding of the control of replication-phase entry and genomic integrity, and identify the AMBRA1-cyclin D pathway as a crucial cell-cycle-regulatory mechanism that is deeply interconnected with genomic stability in embryonic development and tumorigenesis.

Toward mechanistic models for genotype-phenotype correlations in phenylketonuria using protein stability calculations.

Phenylketonuria (PKU) is a genetic disorder caused by variants in the gene encoding phenylalanine hydroxylase (PAH), resulting in accumulation of phenylalanine to neurotoxic levels. Here, we analyzed the cellular stability, localization, and interaction with wild-type PAH of 20 selected PKU-linked PAH protein missense variants. Several were present at reduced levels in human cells, and the levels increased in the presence of a proteasome inhibitor, indicating that proteins are proteasome targets. We found that all the tested PAH variants retained their ability to associate with wild-type PAH, and none formed aggregates, suggesting that they are only mildly destabilized in structure. In all cases, PAH variants were stabilized by the cofactor tetrahydrobiopterin (BH4 ), a molecule known to alleviate symptoms in certain PKU patients. Biophysical calculations on all possible single-site missense variants using the full-length structure of PAH revealed a strong correlation between the predicted protein stability and the observed stability in cells. This observation rationalizes previously observed correlations between predicted loss of protein destabilization and disease severity, a correlation that we also observed using new calculations. We thus propose that many disease-linked PAH variants are structurally destabilized, which in turn leads to proteasomal degradation and insufficient amounts of cellular PAH protein.

The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer.

SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.