Purushottam Dixit

We look forward to submitting our revision. As always, our experience with the new reviewing model of @elife.bsky.social has been wonderful! 6/n n =6

The implications?
It’s not just who binds tighter, but who survives the network's non-equilibrium processing.

Ligand-specificity is an emergent property of the entire network architecture not just binding thermodynamics 5/n

This behavior emerges only when the system is driven out of equilibrium. Energy dissipation (via dissociation and degradation) enables sharp ligand discrimination—not possible in equilibrium systems. 4/n

This means:
➡️Increasing ligand affinity can decrease signaling.
➡️The system has an optimal “sweet spot” for specificity and kinase activity
➡️Ligands with similar affinities can produce very different outputs depending on cellular parameters 3/n

We built a minimal model of receptor signaling that includes common signaling receptor features: Multi-site phosphorylation, rapid dissociation, and Ligand-dependent receptor degradation. Together, they create non-monotonic responses to ligand affinity and kinase activity. 2/n

It’s often assumed that stronger ligand binding = stronger signaling with non-equilibrium effects further enhancing this preference (a.k.a. kinetic proofreading). But often, thermodynamics preference is reversed! We asked: could non-equilibrium mechanisms help explain why? 1/n

Just out: new preprint (with @ralitsamadsen.bsky.social) is now #Reviewed at @eLife! "Non-equilibrium strategies for ligand specificity in signaling networks". We show how cells use non-equilibrium strategies to discriminate between ligands in surprising ways 🔗 elifesciences.org/reviewed-pre...

We have a funding for postdoctoral fellowship that needs to be filled very soon. We are exploring new directions (1) at the interface of non-equilibrium computations and physical learning and (2) in building ecologically motivated machine learning models for microbiomes. Please spread the word!

Accessible surface area - Wikipedia

What about accessible surface area? You get to choose the size of the "probe" which may be useful: en.wikipedia.org/wiki/Accessi...

Just learnt that our collaborative grant proposal on identifying master regulators of T cell metabolism in Lupus will not be reviewed as the study section was indefinitely postponed, along with many other grants that are vital to biomedical research.

Ugh that sucks! Let's hope for the best..

Thank you! We submitted one last December, so it technically is before the expiration date in Jan 2025.

Has anybody looked at approximate Bayesian computation (ABC) using stat mech? The formulation used in rejection ABC: rho(S(D),S(D')) < eps (rho is discrepancy function, S is a summary stat, D is data, D' is simulated data) looks an awful lot like the microcanonical ensemble with an energy = S(D).

Designing host-associated microbiomes using the consumer/resource model | mSystems Generative models are extremely popular in modern biology. They have been used to model the variation of protein sequences, entire genomes, and RNA sequencing profiles. Importantly, generative models ...

Our work on computational design of microbiomes with desired host properties using mechanistic models is now out in mSystems: journals.asm.org/doi/10.1128/...

Analysis of available signaling network parameters suggests that LAGS is widely applicable. Moreover, preferential degradation is just one mechanism for integral feedback control. Therefore, other habituation mechanisms e.g. activity induced inactivation, should also work the same way!

Additionally, when combined with receptor oligomerization, an increase in preferential degradation allows cells to sense relative ligand gradients over a larger range of background ligand concentrations. This is sometimes known as the Weber-Fechner law.

In LAGS, receptor activity is localized through receptor degradation or ligand unbinding. In contrast, uniform ligand sensitivity is maintained through receptor diffusion. Thus, increasing active receptor degradation and increasing diffusion of all receptors both sharpen receptor polarization.

This phenomenon can be summarized as a general principle: Localized Activity Global Sensitization (LAGS).

Many receptor families undergo activity-induced degradation. Additionally, receptors undergo lateral diffusion. Both these processes will blunt receptor polarization. Using a simple model, we show that two wrongs can make a right! The two processes in fact collaborate to enhance polarization.

Unlike small prokaryotes, large eukaryotic cells can sense chemical gradients on their cell surface via receptor polarization; asymmetric partitioning of ligand-bound activated receptors in alignment with extracellular gradients.

Receptor polarization through localized activity and global sensitization Eukaryotic cells chemosense concentration gradients of extracellular ligands using membrane-bound receptors that polarize their activity. Receptors from several chemosensing families are preferentiall...

Happy to present our second paper on understanding ligand sensing using non-equilibrium reaction networks. Here, we look at some counterintuitive results on how eukaryotic cells sense extracellular spatial gradients in ligands (e.g. growth factors): www.biorxiv.org/content/10.1...

Could you please add me?

Given the ubiquity of receptor degradation and desensitization in signaling networks, we think that this mechanism is likely to be quite universal, e.g. in GPCRs and ligand gated ion channels.

We stumbled on a mechanism, kinetic sorting, that is likely to be generally applicable. The signaling network sorts the flux of receptors towards degradation/desensitization depending on the bound ligand. This allows it to change its discrimination in favor of the weaker ligand.

We set out to explain this observation which goes against traditional proofreading, a non-equilibrium mechanism that typically enhances discrimination in favor of the high-affinity ligand beyond thermodynamic preference.

This started with a figure by Freed et al. from the
@lemmonferguson.bsky.social lab where the authors showed that a high-affinity ligand EGF leads to a lower steady state response compared to low-affinity ligands. This is opposite of what one expects from thermodynamics.

This is the fastest manuscript I’ve ever written. We started thinking about it seriously when I met Ralitsa at the FASEB conference on signaling in August. Though, the topic was bothering both of us independently for a year.

As my first post here, I am really excited to share a new manuscript with @ralitsamadsen.bsky.social on this platform. We looked how non-equilibrium thermodynamics helps ligand discrimination in signaling networks: t.co/ZA6NteUmaS