Correction to "Assessing Physicochemical Properties of Drug Molecules via Microsolvation Measurements with Differential Mobility Spectrometry".
Ontology highlight
ABSTRACT:
SUBMITTER: Liu C
PROVIDER: S-EPMC5408334 | biostudies-literature | 2017 Apr
REPOSITORIES: biostudies-literature
Publications
Correction to "Assessing Physicochemical Properties of Drug Molecules via Microsolvation Measurements with Differential Mobility Spectrometry".
Liu Chang C Le Blanc J C Yves JCY Schneider Bradley B BB Shields Jefry J Federico James J JJ Zhang Hui H Stroh Justin G JG Kauffman Gregory W GW Kung Daniel W DW Shapiro Michael M Ieritano Christian C Shepherdson Evan E Verbuyst Mitch M Melo Luke L Hasan Moaraj M Naser Dalia D Janiszewski John S JS Hopkins W Scott WS Campbell J Larry JL
ACS central science 20170315 4
[This corrects the article DOI: 10.1021/acscentsci.6b00297.]. ...[more]
Similar Datasets
Project description:The microsolvated state of a molecule, represented by its interactions with only a small number of solvent molecules, can play a key role in determining the observable bulk properties of the molecule. This is especially true in cases where strong local hydrogen bonding exists between the molecule and the solvent. One method that can probe the microsolvated states of charged molecules is differential mobility spectrometry (DMS), which rapidly interrogates an ion's transitions between a solvated and desolvated state in the gas phase (i.e., few solvent molecules present). However, can the results of DMS analyses of a class of molecules reveal information about the bulk physicochemical properties of those species? Our findings presented here show that DMS behaviors correlate strongly with the measured solution phase pKa and pKb values, and cell permeabilities of a set of structurally related drug molecules, even yielding high-resolution discrimination between isomeric forms of these drugs. This is due to DMS's ability to separate species based upon only subtle (yet predictable) changes in structure: the same subtle changes that can influence isomers' different bulk properties. Using 2-methylquinolin-8-ol as the core structure, we demonstrate how DMS shows promise for rapidly and sensitively probing the physicochemical properties of molecules, with particular attention paid to drug candidates at the early stage of drug development. This study serves as a foundation upon which future drug molecules of different structural classes could be examined.
| S-EPMC5324087 | biostudies-literature
Project description:The fast and accurate determination of molecular properties is highly desirable for many facets of chemical research, particularly in drug discovery where pre-clinical assays play an important role in paring down large sets of drug candidates. Here, we present the use of supervised machine learning to treat differential mobility spectrometry - mass spectrometry data for ten topological classes of drug candidates. We demonstrate that the gas-phase clustering behavior probed in our experiments can be used to predict the candidates' condensed phase molecular properties, such as cell permeability, solubility, polar surface area, and water/octanol distribution coefficient. All of these measurements are performed in minutes and require mere nanograms of each drug examined. Moreover, by tuning gas temperature within the differential mobility spectrometer, one can fine tune the extent of ion-solvent clustering to separate subtly different molecular geometries and to discriminate molecules of very similar physicochemical properties.
| S-EPMC6269546 | biostudies-literature
Project description:The structures and physicochemical properties of chemicals are important for determining their potential toxicological effects, toxicokinetics, and route(s) of exposure. These data are needed to prioritize the risk for thousands of environmental chemicals, but experimental values are often lacking. In an attempt to efficiently fill data gaps in physicochemical property information, we generated new data for 200 structurally diverse compounds, which were rigorously selected from the USEPA ToxCast chemical library, and whose structures are available within the Distributed Structure-Searchable Toxicity Database (DSSTox). This pilot study evaluated rapid experimental methods to determine five physicochemical properties, including the log of the octanol:water partition coefficient (known as log(Kow) or logP), vapor pressure, water solubility, Henry's law constant, and the acid dissociation constant (pKa). For most compounds, experiments were successful for at least one property; log(Kow) yielded the largest return (176 values). It was determined that 77 ToxPrint structural features were enriched in chemicals with at least one measurement failure, indicating which features may have played a role in rapid method failures. To gauge consistency with traditional measurement methods, the new measurements were compared with previous measurements (where available). Since quantitative structure-activity/property relationship (QSAR/QSPR) models are used to fill gaps in physicochemical property information, 5 suites of QSPRs were evaluated for their predictive ability and chemical coverage or applicability domain of new experimental measurements. The ability to have accurate measurements of these properties will facilitate better exposure predictions in two ways: 1) direct input of these experimental measurements into exposure models; and 2) construction of QSPRs with a wider applicability domain, as their predicted physicochemical values can be used to parameterize exposure models in the absence of experimental data.
| S-EPMC6214190 | biostudies-literature
Project description:Protein-protein interactions (PPIs) are associated with various diseases; hence, they are important targets in drug discovery. However, the physicochemical empirical properties of PPI-targeted drugs are distinct from those of conventional small molecule oral pharmaceuticals, which adhere to the "rule of five (RO5)". Therefore, developing PPI-targeted drugs using conventional methods, such as molecular generation models, is challenging. In this study, we propose a molecular generation model based on deep reinforcement learning that is specialized for the production of PPI inhibitors. By introducing a scoring function that can represent the properties of PPI inhibitors, we successfully generated potential PPI inhibitor compounds. These newly constructed virtual compounds possess the desired properties for PPI inhibitors, and they show similarity to commercially available PPI libraries. The virtual compounds are freely available as a virtual library.
| S-EPMC10420264 | biostudies-literature
Project description:Ion mobility spectrometry (IMS), and particularly differential IMS or field asymmetric waveform IMS (FAIMS), is emerging as a versatile tool for separation and identification of gas-phase ions, especially in conjunction with mass spectrometry. For over two decades since its inception, the utility of FAIMS was constrained by resolving power (R) of less than ∼20. Stronger electric fields and optimized gas mixtures have recently raised achievable R to ∼200, but further progress with such approaches is impeded by electrical breakdown. However, the resolving power of planar FAIMS devices using any gas and field intensity scales as the square root of separation time (t). Here, we extended t from the previous maximum of 0.2 s up to 4-fold by reducing the carrier gas flow and increased the resolving power by up to 2-fold as predicted, to >300 for multiply charged peptides. The resulting resolution gain has enabled separation of previously "co-eluting" peptide isomers, including folding conformers and localization variants of modified peptides. More broadly, a peak capacity of ∼200 has been reached in tryptic digest separations.
| S-EPMC3012152 | biostudies-literature
Project description:Differential ion mobility spectrometry (DIMS) can be used as a filter to remove undesired background ions from reaching the mass spectrometer. The ability to use DIMS as a filter for known analytes makes DIMS coupled to tandem mass spectrometry (DIMS-MS/MS) a promising technique for the detection of cancer antigens that can be predicted by computational algorithms. In experiments using DIMS-MS/MS that were performed without the use of high-performance liquid chromatography (HPLC), a predicted model antigen, GLR (FLSSANEHL), was detected at a concentration of 10 pM (20 amol) in a mixture containing 94 competing model peptide antigens, each at a concentration of 1 ?M. Without DIMS filtering, the GLR peptide was undetectable in the mixture even at 100 nM. Again, without using HPLC, DIMS-MS/MS was used to detect 2 of 3 previously characterized antigens produced by the leukemia cell line U937.A2. Because of its sensitivity, a targeted DIMS-MS/MS methodology can likely be used to probe for predicted cancer antigens from cancer cell lines as well as human tumor samples.
| S-EPMC4184456 | biostudies-literature
Project description:Applying Hadamard transform multiplexing to ion mobility separations (IMS) can significantly improve the signal-to-noise ratio and throughput for IMS coupled mass spectrometry (MS) measurements by increasing the ion utilization efficiency. However, it has been determined that fluctuations in ion intensity as well as spatial shifts in the multiplexed data lower the signal-to-noise ratios and appear as noise in downstream processing of the data. To address this problem, we have developed a novel algorithm that discovers and eliminates data artifacts. The algorithm employs an analytical approach to identify and remove artifacts from the data, decreasing the likelihood of false identifications in subsequent data processing. Following application of the algorithm, IMS-MS measurement sensitivity is greatly increased and artifacts that previously limited the utility of applying the Hadamard transform to IMS are avoided. Figure ?
| S-EPMC4223016 | biostudies-literature
Project description:Histone proteins are subject to dynamic post-translational modifications (PTMs) that cooperatively modulate the chromatin structure and function. Nearly all functional PTMs are found on the N-terminal histone domains (tails) of ?50 residues protruding from the nucleosome core. Using high-definition differential ion mobility spectrometry (FAIMS) with electron transfer dissociation, we demonstrate rapid baseline gas-phase separation and identification of tails involving monomethylation, trimethylation, acetylation, or phosphorylation in biologically relevant positions. These are by far the largest variant peptides resolved by any method, some with PTM contributing just 0.25% to the mass. This opens the door to similar separations for intact proteins and in top-down proteomics.
| S-EPMC5436587 | biostudies-literature
Project description:There is growing interest in the characterization of protein complexes and their interactions with ligands using native ion mobility mass spectrometry. A particular challenge, especially for membrane proteins, is preserving noncovalent interactions and maintaining native-like structures. Different approaches have been developed to minimize activation of protein complexes by manipulating charge on protein complexes in solution and the gas-phase. Here, we report the utility of polyamines that have exceptionally high charge-reducing potencies with some molecules requiring 5-fold less than trimethylamine oxide to elicit the same effect. The charge-reducing molecules do not adduct to membrane protein complexes and are also compatible with ion-mobility mass spectrometry, paving the way for improved methods of charge reduction.
| S-EPMC8056390 | biostudies-literature
Project description:Collision cross section (CCS) measurements resulting from ion mobility-mass spectrometry (IM-MS) experiments provide a promising orthogonal dimension of structural information in MS-based analytical separations. As with any molecular identifier, interlaboratory standardization must precede broad range integration into analytical workflows. In this study, we present a reference drift tube ion mobility mass spectrometer (DTIM-MS) where improvements on the measurement accuracy of experimental parameters influencing IM separations provide standardized drift tube, nitrogen CCS values (DTCCSN2) for over 120 unique ion species with the lowest measurement uncertainty to date. The reproducibility of these DTCCSN2 values are evaluated across three additional laboratories on a commercially available DTIM-MS instrument. The traditional stepped field CCS method performs with a relative standard deviation (RSD) of 0.29% for all ion species across the three additional laboratories. The calibrated single field CCS method, which is compatible with a wide range of chromatographic inlet systems, performs with an average, absolute bias of 0.54% to the standardized stepped field DTCCSN2 values on the reference system. The low RSD and biases observed in this interlaboratory study illustrate the potential of DTIM-MS for providing a molecular identifier for a broad range of discovery based analyses.
| S-EPMC5744684 | biostudies-literature