Biology subjects

Shrinivas, K.

Publications and source records attributed to Shrinivas, K..

8 recordsLinked to original sources

bioRxiv2026

Physics-guided design of intrinsically disordered proteins

Intrinsically disordered protein regions (IDPs) are found across the tree of life and characterized by the lack of a stable 3D fold, encoding function through a vast ensemble of conformations. This plasticity makes rational design of IDPs challenging. Physics-based approaches capturing distinct aspects of sequence composition, charge patterning, and molecular interactions have emerged as powerful predictors of ensemble-derived properties. Here, we present a machine learning framework for proteome-scale de novo IDP design by rationally inverting physics-based models. We first program IDPs to tunably sense and respond to diverse biophysical cues and show that IDP ensembles can directly encode complex signal processing, including threshold detection, bandpass filtering, and Boolean-type multi-input logic. We next engineer multicomponent IDP mixtures with tailored emergent condensate properties, including layering and number of phases, compositional specificity, and RNA-dependent remodeling of structure and composition. Finally, we demonstrate designed IDPs that selectively partition into or deplete from biological condensates in living cells. Together, our framework establishes a flexible and scalable strategy for design of ensemble-derived and collective properties in dynamic biomolecules.

biophysics↗

bioRxiv2025

Immiscible proteins compete for RNA binding to order condensate layers

Biomolecular condensates mediate diverse and essential cellular functions by compartmentalizing biochemical pathways. Many condensates have internal subdomains with distinct compositional identities. A major challenge lies in dissecting the multicomponent logic that relates biomolecular features to emergent condensate organization. Nuclear paraspeckles are paradigmatic examples of multi-domain condensates, comprising core and shell layers with distinct compositions that are scaffolded by the lncRNA NEAT1, which spans both layers. A prevailing model of paraspeckle assembly proposes that core proteins bind directly and specifically to core-associated NEAT1 domains. Combining informatics and biochemistry, we unexpectedly find that the essential core proteins FUS and NONO bind and condense preferentially with shell-associated NEAT1 domains. The shell protein TDP-43 exhibits similar NEAT1 domain preferences on its own but forms surfactant-like shell layers around core protein-driven condensates when both are present. Together, experiments and physics-based simulations suggest that competitive RNA binding and immiscibility between core and shell proteins orders paraspeckle layers. More generally, we propose that sub-condensate organization can spontaneously arise from a balance of collaborative and competitive protein binding to the same domains of a lncRNA. SignificanceThe cellular milieu is spatially organized into compartments called biomolecular condensates that exhibit rich internal organization which shapes their functions. Often comprising multiple proteins and RNAs, a major question concerns how molecular-scale features relate to emergent condensate forms. Here we study nuclear paraspeckles, archetypal multi-domain condensates comprising distinct core and shell layers assembled around a layer-spanning RNA scaffold. We find that different proteins associated with each layer all bind preferentially to the same shell-associated domains of the RNA scaffold. Core and shell proteins are inherently immiscible, establishing a competition that redirects core proteins to a suboptimal, core-associated domain of the scaffold. Our work reveals how a combination of competitive RNA binding and protein immiscibility can spatially organize multicomponent condensate subdomains.

biophysics↗

bioRxiv2024

Generalized design of sequence-ensemble-function relationships for intrinsically disordered proteins

The design of folded proteins has advanced significantly in recent years. However, many proteins and protein regions are intrinsically disordered (IDPs) and lack a stable fold i.e., the sequence of an IDP encodes a vast ensemble of spatial conformations that specify its biological function. This conformational plasticity and heterogeneity makes IDP design challenging. Here, we introduce a computational framework for de novo design of IDPs through rational and efficient inversion of molecular simulations that approximate the underlying sequence to ensemble relationship. We highlight the versatility of this approach by designing IDPs with diverse properties and arbitrary sequence constraints. These include IDPs with target ensemble dimensions, loops and linkers, highly sensitive sensors of physicochemical stimuli, and binders to target disordered substrates with distinct conformational biases. Overall, our method provides a general framework for designing sequence-ensemble-function relationships of biological macromolecules.

biophysics↗

bioRxiv2023

A model for cis-regulation of transcriptional condensates and gene expression by proximal lncRNAs

Long non-coding RNAs (lncRNAs) perform several important functions in cells including cis-regulation of transcription. Barring a few specific cases, the mechanisms underlying transcriptional regulation by lncRNAs remain poorly understood. Transcriptional proteins can form condensates via phase separation at protein-binding loci (BL) on the genome (e.g., enhancers and promoters). lncRNA-coding genes are present at loci in close genomic proximity of these BL and these RNAs can interact with transcriptional proteins via attractive heterotypic interactions mediated by their net charge. Motivated by these observations, we propose that lncRNAs can dynamically regulate transcription in cis via charge-based heterotypic interactions with transcriptional proteins in condensates. To study the consequences of this mechanism, we developed and studied a dynamical phase-field model. We find that proximal lncRNAs can promote condensate formation at the BL. Vicinally localized lncRNA can migrate to the BL to attract more protein because of favorable interaction free energies. However, increasing the distance beyond a threshold leads to a sharp decrease in protein recruitment to the BL. This finding could potentially explain why genomic distances between lncRNA-coding genes and protein-coding genes are conserved across metazoans. Finally, our model predicts that lncRNA transcription can fine-tune transcription from neighboring condensate-controlled genes, repressing transcription from highly expressed genes and enhancing transcription of genes expressed at a low level. This non-equilibrium effect can reconcile conflicting reports that lncRNAs can enhance or repress transcription from proximal genes. SIGNIFICANCELong non-coding RNAs (lncRNAs) form a significant part of the human genome but do not code for any proteins. They have many hypothesized functions in the cell, including the regulation of transcription. Transcriptional condensates are assemblies of transcriptional proteins that concentrate at specific genomic sites through phase separation and can regulate transcription. In this study, we propose that lncRNAs can regulate transcription by interacting with proteins in transcriptional condensates to modulate condensate formation. We find that this model can explain some puzzling observations such as conflicting reports of gene activation and repression by lncRNAs, and conservation of genomic distances between lncRNA-coding genes relative to protein-coding genes in metazoans. Experimentally testable predictions that can further explore our model are discussed.

biophysics↗

bioRxiv2022

Multiphase coexistence capacity in complex fluids

Complex fluids like the cytoplasm comprise hundreds of species organized into many coexisting phases. How molecular interactions, reflecting sequence, design, or functional constraints, dictate multiphase coexistence is a major open question. To answer this, we consider models of multicomponent fluids with both designed and random interactions. When crosstalk is introduced, we show that coexisting phases lose specificity beyond a common threshold. In a sequence model, we demonstrate that phase capacity is limited by sequence length and grows logarithmically/linearly with sequence length/number. These results provide a general route to program multiphase coexistence from molecular features.

biophysics↗

bioRxiv2022

Organization and regulation of nuclear condensates by gene activity

Condensation by phase separation has recently emerged as a mechanism underlying many nuclear compartments essential for cellular functions. Nuclear condensates enrich nucleic acids and proteins, localize to specific genomic regions, and often promote gene expression. How diverse properties characteristic of nuclear condensates are shaped by genome organization and activity is poorly understood. Here, we develop a physics-based model to interrogate this interplay between condensation, active transcription, and genome organization. We show that spatial clustering of active genes enables precise localization and de novo nucleation of condensates. We find that strong clustering and activity drives aspherical condensate morphologies. Condensates flow towards distant gene clusters and competition between multiple clusters lead to stretched morphologies and activity-dependent repositioning. Overall, our model predicts and recapitulates morphological and dynamical features of diverse nuclear condensates and offers a unified mechanistic framework to study the interplay between non-equilibrium processes, genome structure, and multicomponent condensates in cell biology.

biophysics↗

bioRxiv2021

Phase separation in fluids with many interacting components

Fluids in natural systems, like the cytoplasm of a cell, often contain thousands of molecular species that are organized into multiple coexisting phases that enable diverse and specific functions. How interactions between numerous molecular species encode for various emergent phases is not well understood. Here we leverage approaches from random matrix theory and statistical physics to describe the emergent phase behavior of fluid mixtures with many species whose interactions are drawn randomly from an underlying distribution. Through numerical simulation and stability analyses, we show that these mixtures exhibit staged phase separation kinetics and are characterized by multiple coexisting phases at equilibrium with distinct compositions. Random-matrix theory predicts the number of existing phases at equilibrium, validated by simulations with diverse component numbers and interaction parameters. Surprisingly, this model predicts an upper bound on the number of phases, derived from dynamical considerations, that is much lower than the limit from the Gibbs phase rule, which is obtained from equilibrium thermodynamic constraints. Using a biophysically motivated model of pairwise interactions between components, we design ensembles that encode either linear or non-monotonic scaling relationships between number of components and co-existing phases, which we validate through simulation and theory. Finally, inspired by parallels in biological systems, we show that including nonequilibrium turnover of components through chemical reactions can tunably modulate the number of coexisting phases at steady-state without changing overall fluid composition. Together, our study provides a model framework that describes the emergent dynamical and steady-state phase behavior of liquid-like mixtures with many interacting constituents.

biophysics↗

bioRxiv2018

Enhancer features that drive formation of transcriptional condensates

Enhancers, DNA elements that regulate gene expression, contain transcription factor (TF) binding sites. TFs bind short sequence motifs that are present throughout the genome at much higher frequency than active enhancers, and so the features that define active enhancers are not well understood. We show that DNA elements with TF binding site valency, density, and binding affinity above sharply defined thresholds can recruit TFs and coactivators in condensates by the cooperative process of phase separation. We demonstrate that weak cooperative interactions between IDRs of TFs and coactivators in combination with specific TF-DNA interactions are required for forming such transcriptional condensates. IDR-IDR interactions are relatively non-specific with the same molecular interactions shared by many TFs and coactivators, and phase separation is a universal cooperative mechanism. Therefore, whether a genomic locus is an enhancer that can assemble a transcriptional condensate is determined predominantly by its cognate TFs binding site valency and density.

molecular biology↗