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.

Direct Correlation of Cell Toxicity to Conformational Ensembles of Genetic Aβ Variants

We report a systematic analysis of conformational ensembles generated from multiseed molecular dynamics simulations of all 15 known genetic variants of Aβ42. We show that experimentally determined variant toxicities are largely explained by random coil content of the amyloid ensembles (correlation with smaller EC50 values; R(2) = 0.54, p = 0.01), and to some extent the helix character (more helix-character is less toxic, R(2) = 0.32, p = 0.07) and hydrophobic surface (R(2) = 0.37, p = 0.04). Our findings suggest that qualitative structural features of the amyloids, rather than the quantitative levels, are fundamentally related to neurodegeneration. The data provide molecular explanations for the high toxicity of E22 variants and for the protective features of the recently characterized A2T variant. The identified conformational features, for example, the local helix-coil-strand transitions of the C-terminals of the peptides, are of likely interest in the direct targeting of amyloids by rational drug design.

Ligand-dependent intra- and interdomain motions in the PDZ12 tandem regulate binding interfaces in postsynaptic density protein-95

The postsynaptic density protein-95 (PSD-95) regulates synaptic plasticity through interactions mediated by its peptide-binding PDZ domains. The two N-terminal PDZ domains of PSD-95 form an autonomous structural unit, and their interdomain orientation and dynamics depend on ligand binding. To understand the mechanistic details of the effect of ligand binding, we generated conformational ensembles using available experimentally determined nuclear Overhauser effect interatomic distances and S² order parameters. In our approach, the fast dynamics of the two domains is treated independently. We find that intradomain structural changes induced by ligand binding modulate the probability of the occurrence of specific domain-domain orientations. Our results suggest that the β2-β3 loop in the PDZ domains is a key regulatory region, which influences both intradomain motions and supramodular rearrangement.

The Effect of Pulling and Twisting Forces on Chameleon Sequence Peptides

Chameleon sequences are amino acid sequences found in several distinct configurations in experiment. They challenge our understanding of the link between sequence and structure, and provide insight into structural competition in proteins. Here, we study the energy landscapes for three such sequences, and interrogate how pulling and twisting forces impact the available structural ensembles. Chameleon sequences do not necessarily exhibit multiple structural ensembles on a multifunnel energy landscape when we consider them in isolation. The application of even small forces leads to drastic changes in the energy landscapes. For pulling forces, we observe transitions from helical to extended structures in a very small span of forces. For twisting forces, the picture is much more complex, and highly dependent on the magnitude and handedness of the applied force as well as the reference angle for the twist. Depending on these parameters, more complex and more simplistic energy landscapes are observed alongside more and less diverse structural ensembles. The impact of even small forces is significant, confirming their likely role in folding events. In addition, small forces exerted by the remaining scaffold of a protein may be sufficient to lead to the adoption of a specific structural ensemble by a chameleon sequence.