Peter Schwander's research while affiliated with University of Wisconsin - Milwaukee and other places
What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.
If you're a ResearchGate member, you can follow this page to keep up with this author's work.
If you are this author, and you don't want us to display this page anymore, please let us know.
Publications (25)
Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To valida...
Phytochromes are essential photoreceptor proteins in plants with homologs in bacteria and fungi that regulate a variety of important environmental responses. They display a reversible photocycle between two distinct states, the red-light absorbing Pr and the far-red light absorbing Pfr, each with its own structure. The reversible Pr to Pfr photocon...
Here, a machine learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron density (DED) maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (Kinetics Inspired NN for Time-Resolved X-ray Crystallography). To...
For decades, researchers have elucidated essential enzymatic functions on the atomic length scale by tracing atomic positions in real-time. Our work builds on possibilities unleashed by mix-and-inject serial crystallography (MISC) at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by mixing substrate or lig...
ManifoldEM is an established method of geometric machine learning developed to extract information on conformational motions of molecules from their projections obtained by cryogenic electron microscopy (cryo-EM). In a previous work, in-depth analysis of the properties of manifolds obtained for simulated ground-truth data from molecules exhibiting...
Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processe...
For decades, researchers have been determined to elucidate essential enzymatic functions on the atomic lengths scale by tracing atomic positions in real time. Our work builds on new possibilities unleashed by mix-and-inject serial crystallography (MISC) at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered by...
For decades, researchers have been determined to elucidate essential enzymatic functions on the atomic lengths scale by tracing atomic positions in real time. Our work builds on new possibilities unleashed by mix-and-inject serial crystallography (MISC) 1–5 at X-ray free electron laser facilities. In this approach, enzymatic reactions are triggered...
Biomolecules undergo complex conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, f...
This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method-now termed ManifoldEM-capable of reconstructing 3D movies and accompanying free-energy landscapes from single-particle cryo-EM images of macromolecules exercising multiple conformationa...
An error in Fig. 3( c ) of the article by Assalauova et al. [ IUCrJ (2020), 7 , 1102–1113] is corrected.
Serial femtosecond crystallography (SFX) is a powerful technique that exploits X-ray free-electron lasers to determine the structure of macromolecules at room temperature. Despite the impressive exposition of structural details with this novel crystallographic approach, the methods currently available to introduce crystals into the path of the X-ra...
Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combin...
![FIG. 5: Subplots [A] and [B] showcase elements of the...](publication/352552730/figure/fig2/AS:1036784909680641@1624200193256/Subplots-A-and-B-showcase-elements-of-the-previously-described-construction_Q320.jpg)
This work is based on the manifold-embedding approach to the study of biological molecules exhibiting conformational changes in a continuum. Previous studies established a workflow capable of reconstructing atomic-level structures in the conformational continuum from cryo-EM images so as to reveal the latent space of macromolecules undergoing multi...
A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of...
Single Particle Imaging (SPI) with intense coherent X-ray pulses from X-ray free-electron lasers (XFELs) has the potential to produce molecular structures without the need for crystallization or freezing. Here we present a dataset of 285,944 diffraction patterns from aerosolized Coliphage PR772 virus particles injected into the femtosecond X-ray pu...
An improved analysis for single-particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the Atomic, Molecular and Optical Science instrument at the Linac Coherent Light Source as part of the SPI initiative. Existing methods were modified to cope with the shortco...
A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformationa...
From Static Structures to Continuous Conformational Changes on the Energy Landscapes - Ghoncheh Mashayekhi, Ali Dashti, Peter Schwander, Abbas Ourmazd
An improved analysis for single particle imaging (SPI) experiments, using the limited data, is presented here. Results are based on a study of bacteriophage PR772 performed at the AMO instrument at the Linac Coherent Light Source (LCLS) as part of the SPI initiative. Existing methods were modified to cope with the shortcomings of the experimental d...
Ever since the first atomic structure of an enzyme was solved, the discovery of the mechanism and dynamics of reactions catalyzed by biomolecules has been the key goal for the understanding of the molecular processes that drive life on earth. Despite a large number of successful methods for trapping reaction intermediates, the direct observation of...
Citations
... In particular, investigations of protein dynamics and time-resolved studies on short timescales require the sample to be at room temperature in solution phase, rather than frozen, thus tremendously profiting from measurements at room temperature. [4][5][6][7][8] Dynamic, time-resolved room-temperature crystallography [8][9][10][11][12] can provide additional information such as mechanistic studies of protein inhibition processes related to the protein-ligand complex formation and, thus, aids drug discovery. 13,14 These technical limitations can be addressed using serial femtosecond crystallography. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/11431281099187414-1669232786628_Q64/Tek-Narsingh-Malla-2.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1080265027924002-1634566661255_Q64/Marius-Schmidt-3.jpg)
... Recently, much work has been devoted to extracting free-energy landscapes of proteins from the analysis of particle distributions in cryo-EM imaging experiments [44][45][46][47][48][49] . Our findings challenge the straightforward assumption that the particle distribution is a faithful reporter of the conformational landscape of the protein. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/831774154313731-1575321820917_Q64/Raison-Dsouza.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/11431281116801470-1675318168552_Q64/Roshanak-Etemadpour.jpg)
... Enhancing the analyze-landscape pipeline [17] or extending the Manifold-EM [19] to a higher dimension are promising strategies. Such development could lead to advancements in our ultimate 310 goal of identifying kinetically probable paths for biomolecules in single-particle cryo-EM. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1185359589314567-1659623157485_Q64/Suvrajit-Maji.jpg)
... Previously, characterization of the 3D-printed GDVNs with a 100 µm orifice demonstrated that jet velocities of ~25 m/s arise with the aqueous flow rates employed in this work (18-22 µL/min) corresponding to gas mass flow rates of ~20 mg/min. 31,49 Therefore, we calculated the distance traveled by a given sample volume in 358 µs to amount to 5 mm. A typical GDVN jet produced by a 3D printed nozzle is 3-10 µm in diameter. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/880707672997893-1586988480503_Q64/Jorvani-Cruz-Villarreal.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/345683157635073-1459428695388_Q64/Alexandra-Ros.jpg)
... For example, more hidden layers can be added to the conversion NN shown in Fig. 3. Furthermore, the linear coupled differential equation solver (shown by the red dashed box in Fig. 3) can be replaced by a non-linear type. In this way, processes that include higher-order reactions or processes involving diffusion of substrates or ligands (Malla et al., 2023;Olmos et al., 2018;Pandey et al., 2021) could be analyzed as well. Now, KINNTREX needs to be applied to experimental data. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/941533234753537-1601490424262_Q64/Suraj-Pandey.jpg)
... 103 A heuristic analysis of manifolds obtained with a simulated heterogeneous cryo-EM data set was used to build a framework from which reconstituting the quasi-continuum of conformational states. 154 CryoDrgn 230 proposed a method using a variational autoencoder architecture trained to encode the particle images in a latent space, the manifold. e2gmm 23 is another deep learning based algorithm. ...
... The presented paper lays the groundwork for the identification of specific terms in the matter correlation functions related to the relevant features in the diffraction signals. The analysis, possibly, sets the ground for more accurate interpretations of the snapshot diffraction measurements, reconstruction algorithms beyond density-based heuristics [19,[62][63][64][65][66][67], and provides a theoretical framework for further developments pertinent to the single-particle imaging using FEL radiation sources [26,68]. One of the promising applications of such an elaborate description lies in time-domain structural biology. ...
... The structures and density maps are available at the GitHub repository: https://github.com/LiuLab-CSRC/Clr-Dynamics (56). ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/11431281158129397-1684047817564_Q64/Tokushi-Sato-2.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/925178175438849-1597591074696_Q64/Ishwor-Poudyal.jpg)
... 1 Since then, the progress has been steady, and the community has been able to reach higher and higher resolution and imaging smaller and smaller objects. [2][3][4][5][6] Imaging macromolecules in the gas phase requires them to be taken out of solution and into vacuum, gently enough for their structures to remain native-like as they interact with the beam. A growing mass of evidence indicates that under the right conditions, protein structures remain native-like with (nano)electrospray ionization. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/969137538994177-1608071803101_Q64/Haoyuan-Li-11.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/359291597934593-1462673200064_Q64/Reza-Nazari.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/385353165885441-1468886762729_Q64/B-Abbey.jpg)
... The integration of XFEL technology with advanced computational methods is set to help make the most out of the current data processing routines. Current achievements of ML in XFEL imaging include: efficient data classification for online analysis [96,97], preprocessing to improve signal quality [98,87], offline analysis and structural fitting in 2D and 3D for geometrical metallic nanoparticles [99,100,98,101,81] and for nanodroplets [102], and the optimization of beamline parameters [103,90,104]. The field of AI is vast and evergrowing, and the research landscape is developing too quickly to keep track of all technological applications. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1129796385947652-1646375857010_Q64/Young-Yong-Kim.jpg)
