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Posts by Christian Seitz

Finally, I am still looking for new roles in computational chemistry/biophysics. I have 12 years of research experience in computational protein dynamics and drug discovery. If you know of any openings don't hesitate to reach out, DMs are open 🙏🏻 3/3

2 days ago 0 0 0 0
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Christian Seitz ’16 tackles global vaccine research A professor’s encouragement helped Christian Seitz ’16 discover a passion for chemistry that ultimately led him to global vaccine research. Now working through the University of Chicago, Seitz studies...

Big achievement as one of the school's top alumni distinctions - could not have done it without the support of my mentors at Elon: Karl Sienerth, Joel Karty, Olivia Jones Choplin, Sophie Adamson, Sarah Glasco. Team effort! 2/3
www.elon.edu/u/news/2026/...

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It's about time I make this official, I'm super honored to be awarded Elon University's Top 10 under 10 awards for the most exciting alumni from the past 10 years. 1/3

2 days ago 0 0 1 0

Hello everyone, I am looking for my next role in the computational chemistry/biophysics space 🛫

I have 12 years of research experience in protein simulations/SBDD, looking for national lab/industry scientist positions anywhere in the world. Any connections/leads welcomed - thanks in advance! 🙏🏻

1 month ago 0 0 0 0

Paper was rejected today! Scanning through the reviews, there were some factual/scientific errors that need to be corrected before it can be published 😱 Happy that peer review caught this, would much rather publish a better paper later than rush one out with errors

4 months ago 2 0 0 0

Congrats Isabelle, that's great!

4 months ago 0 0 0 0
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Visual context affects the perceived timing of tactile sensations elicited through intracortical microstimulation: a case study of two participants | Journal of Neurophysiology | American Physiologica... Intracortical microstimulation (ICMS) is a technique to provide tactile sensations for a somatosensory brain-machine interface (BMI). A viable BMI must function within the rich, multisensory environme...

Reviving this account to say that the last paper from my PhD is out in final form!

Here, we look at how the timing of artificial tactile sensations (delivered via intracortical microstimulation/ICMS) is perceived relative to visual cues in two participants with spinal cord injuries. 🧠✋👀

4 months ago 3 2 2 0
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The war on science in the US is already having an effect on private sector research like AlphaFold. Bears repeating but the private sector builds on top of things created by academic research for the public good. This hurts everyone.

10 months ago 238 105 2 12

Are you a grad student or postdoc at the bench in the UC system? If so, please DM.

(for the record, this is a question about laboratory procedure, not any individual PI)

#chemsky ⚗️

10 months ago 8 4 0 0

congrats Kai + co! 🥳

11 months ago 0 0 0 0

Here at the BV-BRC workshop - refreshing to be at a workshop without a set problem to solve. Learning just for the sake of learning 😉

11 months ago 1 0 0 0
Examples of alternate conformations with environmental explanations.
(A) a protein in two states (open and closed) mediated by allosteric effects; (B) a population of two discrete rotamer states of a sidechain; (C) bound and unbound states due to ligand interaction; (D) different oxidation states of a cysteine pair. Furthermore, some regions in many protein structures exhibit such a degree of flexibility, that no accurate modelling is possible (dashed lines, E). The backbone conformation cannot be determined with crystallographic methods in such cases.

Examples of alternate conformations with environmental explanations. (A) a protein in two states (open and closed) mediated by allosteric effects; (B) a population of two discrete rotamer states of a sidechain; (C) bound and unbound states due to ligand interaction; (D) different oxidation states of a cysteine pair. Furthermore, some regions in many protein structures exhibit such a degree of flexibility, that no accurate modelling is possible (dashed lines, E). The backbone conformation cannot be determined with crystallographic methods in such cases.

Failure of ensemble prediction algorithms in altloc segments.
Although structure and ensemble prediction techniques based on amino acid sequences are capable of accurately reconstructing the overall backbone structure (left column), they consistently fail to produce viable samples corresponding to one of the two altloc conformations (as shown in the magnified regions in the second through fourth columns).

Failure of ensemble prediction algorithms in altloc segments. Although structure and ensemble prediction techniques based on amino acid sequences are capable of accurately reconstructing the overall backbone structure (left column), they consistently fail to produce viable samples corresponding to one of the two altloc conformations (as shown in the magnified regions in the second through fourth columns).

Some crystal structures show evidence of multiple stable conformations, such as loops or side chains with two distinct regions of density. These can be correctly modeled by MD, but not modern protein ensemble prediction tools like AlphaFlow or DiG (BioEmu not tested)

www.biorxiv.org/content/10.1...

11 months ago 45 12 0 0
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For Teachers - Letters to a Pre-Scientist Overview Are you a 5-8th grade STEM teacher in the US who wants to bring Letters to a Pre-Scientist into your classroom? We would love to hear from you! Teacher ...

This is a cool program I've worked with for a few years matching STEM professionals and students as pen pals; if you're a 5th-8th grade teacher interested in pen pals for the fall, check out prescientist.org/for-teachers/

1 year ago 1 0 0 0

every time I'm off blue sky for more than a day or two and return, my feed (I only follow scientists) morphs into a tsunami of political clickbait, worse than twitter. Blocking left and right but it never gets any better. Spending less and less time here because of all the political junk smh

1 year ago 0 0 0 0

not attending but met up with @leftymiller.bsky.social at #ACSSpring2025! I feel people are always excited about the science at conferences but I'm always excited about the connections and the people behind the science

1 year ago 3 0 0 0
Job Board All OMSF positions are currently remote, and we generally accept applications worldwide. Some positions may be restricted to the United States. All positions require a valid work permit - OMSF has lim...

happy to say it - our projects are hiring again!

1 year ago 1 1 0 0

Water-mediated interactions between glycans are weakly repulsive and unexpectedly long-ranged www.biorxiv.org/content/10.1101/2025.02....

1 year ago 2 1 0 0
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Figure 1 from arXiv preprint https://doi.org/10.1101/2025.01.06.631610

Fig. 1 Espaloma is an end-to-end differentiable molecular mechanics parameter assignment scheme for arbitrary organic molecules. Espaloma (extensible surrogate potential optimized by message-passing) is a modular approach for directly computing molecular mechanics force field parameters FFF from a chemical graph G such as a small molecule or biopolymer via a process that is fully differentiable in the model parameters FNN. In Stage 1, a graph neural network is used to generate continuous latent atom embeddings describing local chemical environments from the chemical graph. In Stage 2, these atom embeddings are transformed into feature vectors that preserve appropriate symmetries for atom, bond, angle, and proper/improper torsion inference via Janossy pooling.54 In Stage 3, molecular mechanics parameters are directly predicted from these feature vectors using feed-forward neural networks. This parameter assignment process is performed once per molecular species, allowing the potential energy to be rapidly computed using standard molecular mechanics or molecular dynamics frameworks thereafter. The collection of parameters FNN describing the espaloma model can be considered as the equivalent complete specification of a traditional molecular mechanics force field such as GAFF38,39/AM1-BCC55,56 in that it encodes the equivalent of traditional typing rules, parameter assignment tables, and even partial charge models. Reproduced from ref. 49 with permission from the Royal Society of Chemistry.

Figure 1 from arXiv preprint https://doi.org/10.1101/2025.01.06.631610 Fig. 1 Espaloma is an end-to-end differentiable molecular mechanics parameter assignment scheme for arbitrary organic molecules. Espaloma (extensible surrogate potential optimized by message-passing) is a modular approach for directly computing molecular mechanics force field parameters FFF from a chemical graph G such as a small molecule or biopolymer via a process that is fully differentiable in the model parameters FNN. In Stage 1, a graph neural network is used to generate continuous latent atom embeddings describing local chemical environments from the chemical graph. In Stage 2, these atom embeddings are transformed into feature vectors that preserve appropriate symmetries for atom, bond, angle, and proper/improper torsion inference via Janossy pooling.54 In Stage 3, molecular mechanics parameters are directly predicted from these feature vectors using feed-forward neural networks. This parameter assignment process is performed once per molecular species, allowing the potential energy to be rapidly computed using standard molecular mechanics or molecular dynamics frameworks thereafter. The collection of parameters FNN describing the espaloma model can be considered as the equivalent complete specification of a traditional molecular mechanics force field such as GAFF38,39/AM1-BCC55,56 in that it encodes the equivalent of traditional typing rules, parameter assignment tables, and even partial charge models. Reproduced from ref. 49 with permission from the Royal Society of Chemistry.

Everything is chaos, but I wanted to share some awesome recent science from the lab that hints at where the future of biomolecular simulation is headed:

Foundation simulation models that can be fine-tuned to experimental free energy data to produce systematically more accurate predictions.

1 year ago 106 30 3 1

exciting times! Will definitely be trying this out

1 year ago 0 0 0 0
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Markov State Models with Weighted Ensemble Simulation: How to Eliminate the Trajectory Merging Bias The weighted ensemble (WE) algorithm is gaining popularity as a rare event method for studying long timescale processes with molecular dynamics. WE is particularly useful for determining kinetic prope...

#compchem Good read: Markov State Models with Weighted Ensemble Simulation: How to Eliminate the Trajectory Merging Bias #compchemsky #biosky
pubs.acs.org/doi/10.1021/...

1 year ago 10 7 1 0
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🚨Preprint Alert!🚨

#ProteinDesign is advancing rapidly—wouldn't it be great to seamlessly combine design tools to achieve more than what each can do alone?🤔

Here, we introduce AI.zymes: A modular platform for evolutionary #EnzymeDesign.♻️🖥️

biorxiv.org/content/10.1...
1/🧵

1 year ago 30 7 1 1
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We’re thrilled to announce the launch of Bind Research, the UK’s first not-for-profit Focused Research Organisation, with long-term support from the Department for Science, Innovation and Technology’s Research Ventures Catalyst Programme, industry, and charities.

1 year ago 25 13 1 2

We developed a computationally efficient method to predict hot spots driving conformational changes in small molecule sensing proteins. It can easily be generalized to explore allosteric couplings in a wide range of proteins. Code available in the preprint, check it out ! #compchem #compbio

1 year ago 2 1 0 0
Nanobodies with extended CDR3 conformations are correctly predicted the majority of the time, whereas kinked CDR3 conformations are rarely correctly predicted

Nanobodies with extended CDR3 conformations are correctly predicted the majority of the time, whereas kinked CDR3 conformations are rarely correctly predicted

CDR3 loop conformation, specifically whether the C-terminus is kinked or not, is a major determinants of whether a nanobody-antigen complex is correctly predicted using SOTA protein structure prediction software doi.org/10.1021/acs....

1 year ago 13 4 0 1

congrats Steffen + co!

1 year ago 1 0 1 0
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Nonequilibrium friction and free energy estimates for kinetic coarse-graining -- Driven particles in responsive media Predicting the molecular friction and energy landscapes under nonequilibrium conditions is key to coarse-graining the dynamics of selective solute transport through complex, fluctuating and responsive...

First new work from @moldynfr.bsky.social and me in collaboration with Sebastian Milster and Joe Dzubiella herein Freiburg: coarse-graining the transport dynamics of particles through responsive media via Langevin equation models. #Chemsky #compchem #softmatter arxiv.org/abs/2501.18484

1 year ago 6 2 1 0
Molecular Biophysics Database

Our colleagues in Prague have released a database for molecular biophysics data - mbdb-data.org! 🌍📊 A great step forwards FAIR data in biophysics. 🙌✨ @mosbri.bsky.social

1 year ago 15 6 1 1
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Memorial Sloan Kettering Cancer Center hiring AI Drug Discovery Lead in New York, NY | LinkedIn Posted 4:46:37 PM. $118,800.00-$196,200.00Company Overview The people of Memorial Sloan Kettering Cancer Center (MSK)…See this and similar jobs on LinkedIn.

MSKCC is looking for an AI Drug Discovery Lead to drive collaborations between researchers and pharma/biotech within the Office of Technology Development to accelerate the discovery and development of new therapeutics:
www.linkedin.com/jobs/view/41...

1 year ago 9 1 0 0
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There's just one week until the application period ends for the Frontera Fellowship! Collaborate with experts at the Texas Advanced Computing Center and use the powerful Frontera supercomputer to aid your research. Applications close February 7.

Learn more: bit.ly/425QQc7

1 year ago 1 2 0 0

It was helpful for me when I was writing my thesis, great job

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