Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer's disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting nonspecifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42 and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target biomolecules other than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.

• Publication type
• Journal Article MeSH

Interferon induced transmembrane proteins (IFITMs) play a dual role in the restriction of RNA viruses and in cancer progression, yet the mechanism of their action remains unknown. Currently, there is no data about the basic biochemical features or biophysical properties of the IFITM1 protein. In this work, we report on description and biochemical characterization of three conformational variants/oligomeric species of recombinant IFITM1 protein derived from an Escherichia coli expression system. The protein was extracted from the membrane fraction, affinity purified, and separated by size exclusion chromatography where two distinct oligomeric species were observed in addition to the expected monomer. These species remained stable upon re-chromatography and were designated as "dimer" and "oligomer" according to their estimated molecular weight. The dimer was found to be less stable compared to the oligomer using circular dichroism thermal denaturation and incubation with a reducing agent. A two-site ELISA and HDX mass spectrometry suggested the existence of structural motif within the N-terminal part of IFITM1 which might be significant in oligomer formation. Together, these data show the unusual propensity of recombinant IFITM1 to naturally assemble into very stable oligomeric species whose study might shed light on IFITM1 anti-viral and pro-oncogenic functions in cells.

• Keywords
• IFITM proteins, hydrogen deuterium exchange, oligomerization, protein conformation, protein structure,
• MeSH
• Antiviral Agents pharmacology   chemistry   metabolism   MeSH
• Antigens, Differentiation * metabolism   chemistry   MeSH
• Protein Conformation * MeSH
• Humans MeSH
• Recombinant Proteins chemistry   isolation & purification   metabolism   biosynthesis   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antiviral Agents MeSH
• Antigens, Differentiation * MeSH
• leu-13 antigen MeSH Browser
• Recombinant Proteins MeSH

Microflow liquid chromatography interfaced with mass spectrometry (μLC-MS/MS) is increasingly applied for high-throughput profiling of biological samples and has been proven to have an acceptable trade-off between sensitivity and reproducibility. However, lipidomics applications are scarce. We optimized a μLC-MS/MS system utilizing a 1 mm inner diameter × 100 mm column coupled to a triple quadrupole mass spectrometer to establish a sensitive, high-throughput, and robust single-shot lipidomics workflow. Compared to conventional lipidomics methods, we achieve a ∼4-fold increase in response, facilitating quantification of 351 lipid species from a single iPSC-derived cerebral organoid during a 15 min LC-MS analysis. Consecutively, we injected 303 samples over ∼75 h to prove the robustness and reproducibility of the microflow separation. As a proof of concept, μLC-MS/MS analysis of Alzheimer's disease patient-derived iPSC cerebral organoid reveals differential lipid metabolism depending on APOE phenotype (E3/3 vs E4/4). Microflow separation proves to be an environmentally friendly and cost-effective method as it reduces the consumption of harmful solvents. Also, the data demonstrate robust, in-depth, high-throughput performance to enable routine clinical or biomedical applications.

• MeSH
• Apolipoproteins E MeSH
• Chromatography, Liquid methods   MeSH
• Phenotype MeSH
• Liquid Chromatography-Mass Spectrometry * MeSH
• Humans MeSH
• Lipidomics MeSH
• Reproducibility of Results MeSH
• Tandem Mass Spectrometry * methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Apolipoproteins E MeSH