Identifying conformational isomers of organic molecules in solution via unsupervised clustering

We present a systematic approach for the identification of statistically relevant conformational macrostates of organic molecules from molecular dynamics trajectories. The approach applies to molecules characterised by an arbitrary number of torsional degrees of freedom and enables the transferability of the macrostates definition across different environments. We formulate a dissimilarity measure between molecular configurations that incorporates information on the characteristic energetic cost associated with transitions along all relevant torsional degrees of freedom. Such metric is employed to perform unsupervised clustering of molecular configurations based on the fast search and find of density peaks algorithm. We apply this method to investigate the equilibrium conformational ensemble of Sildenafil, a conformationally complex pharmaceutical compound, in different environments including the crystal bulk, the gas phase and three different solvents (acetonitrile, 1-butanol, and toluene). We demonstrate that, while Sildenafil can adopt more than one hundred metastable conformational configurations, only 12 are significantly populated across all the environments investigated. Despite the complexity of the conformational space, we find that the most abundant conformers in solution are the closest to the conformers found in the most common Sildenafil crystal phase.

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Modeling the Thermodynamics of Conformational Isomerism in Solution via Unsupervised Clustering: The Case of Sildenafil

10.26434/chemrxiv.13247309 ◽

2020 ◽

Author(s):

Veselina Marinova ◽

Laurence Dodd ◽

Song-Jun Lee ◽

Geoffrey P. F. Wood ◽

Ivan Marziano ◽

...

Keyword(s):

Gas Phase ◽

Degrees Of Freedom ◽

Systematic Approach ◽

Organic Molecules ◽

Unsupervised Clustering ◽

Conformational Space ◽

Energetic Cost ◽

Conformational Ensemble ◽

Density Peaks ◽

Crystal Bulk

We present a systematic approach for the identification of statistically relevant conformational macrostates of organic molecules from molecular dynamics trajectories. The approach applies to molecules characterised by an arbitrary number of torsional degrees of freedom and enables the transferability of the macrostates definition across different environments. We formulate a dissimilarity measure between molecular configurations that incorporates information on the characteristic energetic cost associated with transitions along all relevant torsional degrees of freedom. Such metric is employed to perform unsupervised clustering of molecular configurations based on the fast search and find of density peaks algorithm. We apply this method to investigate the equilibrium conformational ensemble of Sildenafil, a conformationally complex pharmaceutical compound, in different environments including the crystal bulk, the gas phase and three different solvents (acetonitrile, 1-butanol, and toluene). We demonstrate that, while Sildenafil can adopt more than one hundred metastable conformational configurations, only 12 are significantly populated across all the environments investigated. Despite the complexity of the conformational space, we find that the most abundant conformers in solution are the closest to the conformers found in the most common Sildenafil crystal phase.

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Modeling the Thermodynamics of Conformational Isomerism in Solution via Unsupervised Clustering: The Case of Sildenafil

10.26434/chemrxiv.13247309.v1 ◽

2020 ◽

Author(s):

Veselina Marinova ◽

Laurence Dodd ◽

Song-Jun Lee ◽

Geoffrey P. F. Wood ◽

Ivan Marziano ◽

...

Keyword(s):

Gas Phase ◽

Degrees Of Freedom ◽

Systematic Approach ◽

Organic Molecules ◽

Unsupervised Clustering ◽

Conformational Space ◽

Energetic Cost ◽

Conformational Ensemble ◽

Density Peaks ◽

Crystal Bulk

We present a systematic approach for the identification of statistically relevant conformational macrostates of organic molecules from molecular dynamics trajectories. The approach applies to molecules characterised by an arbitrary number of torsional degrees of freedom and enables the transferability of the macrostates definition across different environments. We formulate a dissimilarity measure between molecular configurations that incorporates information on the characteristic energetic cost associated with transitions along all relevant torsional degrees of freedom. Such metric is employed to perform unsupervised clustering of molecular configurations based on the fast search and find of density peaks algorithm. We apply this method to investigate the equilibrium conformational ensemble of Sildenafil, a conformationally complex pharmaceutical compound, in different environments including the crystal bulk, the gas phase and three different solvents (acetonitrile, 1-butanol, and toluene). We demonstrate that, while Sildenafil can adopt more than one hundred metastable conformational configurations, only 12 are significantly populated across all the environments investigated. Despite the complexity of the conformational space, we find that the most abundant conformers in solution are the closest to the conformers found in the most common Sildenafil crystal phase.

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Identifying Conformational Isomers of Organic Molecules in Solution via Unsupervised Clustering

Journal of Chemical Information and Modeling ◽

10.1021/acs.jcim.0c01387 ◽

2021 ◽

Author(s):

Veselina Marinova ◽

Laurence Dodd ◽

Song-Jun Lee ◽

Geoffrey P. F. Wood ◽

Ivan Marziano ◽

...

Keyword(s):

Organic Molecules ◽

Unsupervised Clustering ◽

Conformational Isomers

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Dynamical Behavior and Conformational Selection Mechanism of the Intrinsically Disordered Sic1 Kinase-Inhibitor Domain

Life ◽

10.3390/life10070110 ◽

2020 ◽

Vol 10 (7) ◽

pp. 110 ◽

Cited By ~ 1

Author(s):

Davide Sala ◽

Ugo Cosentino ◽

Anna Ranaudo ◽

Claudio Greco ◽

Giorgio Moro

Keyword(s):

Kinase Inhibitor ◽

Dynamical Behavior ◽

Md Simulations ◽

Molecular Shape ◽

Conformational Space ◽

Coarse Grained ◽

Conformational Ensemble ◽

Selection Mechanism ◽

Conformational Selection ◽

Intrinsically Disordered

Intrinsically Disordered Peptides and Proteins (IDPs) in solution can span a broad range of conformations that often are hard to characterize by both experimental and computational methods. However, obtaining a significant representation of the conformational space is important to understand mechanisms underlying protein functions such as partner recognition. In this work, we investigated the behavior of the Sic1 Kinase-Inhibitor Domain (KID) in solution by Molecular Dynamics (MD) simulations. Our results point out that application of common descriptors of molecular shape such as Solvent Accessible Surface (SAS) area can lead to misleading outcomes. Instead, more appropriate molecular descriptors can be used to define 3D structures. In particular, we exploited Weighted Holistic Invariant Molecular (WHIM) descriptors to get a coarse-grained but accurate definition of the variegated Sic1 KID conformational ensemble. We found that Sic1 is able to form a variable amount of folded structures even in absence of partners. Among them, there were some conformations very close to the structure that Sic1 is supposed to assume in the binding with its physiological complexes. Therefore, our results support the hypothesis that this protein relies on the conformational selection mechanism to recognize the correct molecular partners.

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The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds

10.1101/2020.11.09.374991 ◽

2020 ◽

Author(s):

Jiaxing Chen ◽

Sofia Zaer ◽

Paz Drori ◽

Joanna Zamel ◽

Khalil Joron ◽

...

Keyword(s):

Single Molecule ◽

Resonance Energy Transfer ◽

Resonance Energy ◽

Intrinsically Disordered Protein ◽

Structural Heterogeneity ◽

Conformational Space ◽

Conformational Ensemble ◽

Time Resolved ◽

Intrinsically Disordered ◽

Transient Nature

AbstractThe intrinsically disordered protein, α-synuclein, implicated in synaptic vesicle homeostasis and neurotransmitter release, is also associated with several neurodegenerative diseases. The different roles of α-synuclein are characterized by distinct structural states (membrane-bound, dimer, tetramer, oligomer, and fibril), which are originated from its various monomeric conformations. The pathological states, determined by the ensemble of α-synuclein monomer conformations and dynamic pathways of interconversion between dominant states, remain elusive due to their transient nature. Here, we use inter-dye distance distributions from bulk time-resolved Förster resonance energy transfer as restraints in discrete molecular dynamics simulations to map the conformational space of the α-synuclein monomer. We further confirm the generated conformational ensemble in orthogonal experiments utilizing far-UV circular dichroism and cross-linking mass spectrometry. Single-molecule protein-induced fluorescence enhancement measurements show that within this conformational ensemble, some of the conformations of α-synuclein are surprisingly stable, exhibiting conformational transitions slower than milliseconds. Our comprehensive analysis of the conformational ensemble reveals essential structural properties and potential conformations that promote its various functions in membrane interaction or oligomer and fibril formation.

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Electronic structure at coarse-grained resolutions from supervised machine learning

Science Advances ◽

10.1126/sciadv.aav1190 ◽

2019 ◽

Vol 5 (3) ◽

pp. eaav1190 ◽

Cited By ~ 15

Author(s):

Nicholas E. Jackson ◽

Alec S. Bowen ◽

Lucas W. Antony ◽

Michael A. Webb ◽

Venkatram Vishwanath ◽

...

Keyword(s):

Machine Learning ◽

Electronic Structure ◽

Quantum Chemical Calculations ◽

Spatial Resolution ◽

Quantum Chemical ◽

Degrees Of Freedom ◽

Soft Materials ◽

Conformational Space ◽

Supervised Machine Learning ◽

Coarse Grained

Computational studies aimed at understanding conformationally dependent electronic structure in soft materials require a combination of classical and quantum-mechanical simulations, for which the sampling of conformational space can be particularly demanding. Coarse-grained (CG) models provide a means of accessing relevant time scales, but CG configurations must be back-mapped into atomistic representations to perform quantum-chemical calculations, which is computationally intensive and inconsistent with the spatial resolution of the CG models. A machine learning approach, denoted as artificial neural network electronic coarse graining (ANN-ECG), is presented here in which the conformationally dependent electronic structure of a molecule is mapped directly to CG pseudo-atom configurations. By averaging over decimated degrees of freedom, ANN-ECG accelerates simulations by eliminating backmapping and repeated quantum-chemical calculations. The approach is accurate, consistent with the CG spatial resolution, and can be used to identify computationally optimal CG resolutions.

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Complete Atlas Database of 2-DOF Kinematic Chains and Creative Design of Mechanisms

Journal of Mechanical Design ◽

10.1115/1.4005866 ◽

2012 ◽

Vol 134 (3) ◽

Cited By ~ 13

Author(s):

Huafeng Ding ◽

Wenao Cao ◽

Andrés Kecskeméthy ◽

Zhen Huang

Keyword(s):

Creative Process ◽

Degrees Of Freedom ◽

Systematic Approach ◽

Computer Models ◽

Creative Design ◽

Kinematic Structure ◽

Topological Graphs ◽

Kinematic Chains ◽

First Time ◽

Intuitive Manner

The creation of novel kinematic structures of mechanisms still represents a major challenge in the quest for developing new, innovative devices. In this setting, computer models that can automatically generate and visualize all possible independent structures in an intuitive manner prove to be valuable as a support in the creative process of the designer. This paper proposes an automatic approach for establishing the complete atlas database of 2-DOF kinematic chains and a systematic approach for the creative design of mechanisms based on such an atlas. First, the transformation of the kinematic structure into a graph-based representation is addressed. Then, an approach for the generation of all nonfractionated topological graphs of 2-DOF (degrees of freedom) kinematic chains using contracted graphs as well as a method for synthesizing all the fractionated topological graphs through the combination of corresponding 1-DOF kinematic chains are addressed. Based on these methods, the complete atlas database of 2-DOF kinematic chains up to 15 links is established in this paper for the first time. Using this complete database, a systematic approach for the creative design of mechanisms can be derived, as illustrated for the example of an 11-link 2-DOF rode tractor.

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Extent of N-terminus exposure by altered long-range interactions of monomeric alpha-synuclein determines its aggregation propensity

10.1101/740241 ◽

2019 ◽

Author(s):

Amberley D. Stephens ◽

Maria Zacharopoulou ◽

Rani Moons ◽

Giuliana Fusco ◽

Neeleema Seetaloo ◽

...

Keyword(s):

Long Range ◽

Intrinsically Disordered Protein ◽

Local Environment ◽

Alpha Synuclein ◽

Conformational Space ◽

Conformational Ensemble ◽

Aggregation Propensity ◽

Intrinsically Disordered ◽

Long Range Interactions ◽

N Terminus

AbstractAs an intrinsically disordered protein, monomeric alpha synuclein (aSyn) constantly reconfigures and probes the conformational space. Long-range interactions across the protein maintain its solubility and mediate this dynamic flexibility, but also provide residual structure. Certain conformations lead to aggregation prone and non-aggregation prone intermediates, but identifying these within the dynamic ensemble of monomeric conformations is difficult. Herein, we used the biologically relevant calcium ion to investigate the conformation of monomeric aSyn in relation to its aggregation propensity. By using calcium to perturb the conformational ensemble, we observe differences in structure and intra-molecular dynamics between two aSyn C-terminal variants, D121A and pS129, and the aSyn familial disease mutants, A30P, E46K, H50Q, G51D, A53T and A53E, compared to wild-type (WT) aSyn. We observe that the more exposed the N-terminus and the beginning of the NAC region are, the more aggregation prone monomeric aSyn conformations become. N-terminus exposure occurs upon release of C-terminus interactions when calcium binds, but the level of exposure is specific to the aSyn mutation present. There was no correlation between single charge alterations, calcium affinity, or the number of ions bound on aSyn’s aggregation propensity, indicating that sequence or post-translation modification (PTM)-specific conformational differences between the N- and C-termini and the specific local environment mediate aggregation propensity instead. Understanding aggregation prone conformations of monomeric aSyn and the environmental conditions they form under will allow us to design new therapeutics targeted to the monomeric protein, to stabilise aSyn in non-aggregation prone conformations, by either preserving long-range interactions between the N- and C-termini or by protecting the N-terminus from exposure.

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pH swing cycle for CO2 capture electrochemically driven through proton-coupled electron transfer

Energy & Environmental Science ◽

10.1039/d0ee01834a ◽

2020 ◽

Vol 13 (10) ◽

pp. 3706-3722

Author(s):

Shijian Jin ◽

Min Wu ◽

Roy G. Gordon ◽

Michael J. Aziz ◽

David G. Kwabi

Keyword(s):

Electron Transfer ◽

Co2 Capture ◽

Redox Reactions ◽

Organic Molecules ◽

Aqueous Electrolyte ◽

Energetic Cost ◽

Proton Coupled Electron Transfer ◽

Electrochemical Redox ◽

Ph Swing

This study analyzes the energetic cost of CO2 separation using a pH swing created by electrochemical redox reactions of organic molecules involving PCET in aqueous electrolyte, and compares the experimental energetic cost to other methods.

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