Biology subjects

Appadurai, R.

Publications and source records attributed to Appadurai, R..

6 recordsLinked to original sources

bioRxiv2025

Morpheus: A fragment-based algorithm to predict metamorphic behaviour in proteins across proteomes

Functionally important "fold-switching" proteins, which do not obey the classical folding dogma, are now thought to be widespread. Algorithms that can accurately annotate fold-switching proteins from sequence information can help uncover the true extent of the "metamorphome". Here, we present Morpheus, a fragment-based classification approach, that works by analysing the diversity of structures within a query protein sequence. Morpheus exhaustively curates and uses fragment structural data from the protein data bank as well as the AlphaFold Protein Structure Database. We employed our algorithm on 57 different proteomes consisting of a total of 601,218 proteins and identified about 10% of these proteins with the ability to fold switch. Additionally, we provide a web server for Morpheus to test for metamorphic propensities for user-defined sequences (http://mbu.iisc.ac.in/[~]anand/morpheus). Besides screening for metamorphic behaviour in proteomes, our work will be useful in de novo design and engineering of such proteins through further experimentation.

bioinformatics↗

bioRxiv2024

Unambiguous assignment of kinked beta sheets leads to insights into molecular grammar of reversibility in biomolecular condensates

Kinked-{beta} sheets are short peptide motifs that appear as distortions in {beta}-strands and often mediate formation of reversible amyloid fibrils in prion-like proteins. Standard methods for assigning secondary structures cannot distinguish these esoteric motifs. Here, we provide a supervised machine learning based structural quantification map to unambiguously characterize Kinked-{beta} sheets from coordinate data. We find that these motifs, although deviating from standard {beta}-strand region of the Ramachandran plot, scatter around the allowed regions. We also demonstrate the applicability of our technique in wresting out LARKS, which are kinked {beta}-strands with designated sequence. Additionally, from our exhaustive simulation generated conformations, we create a repository of potential kinked peptide-segments that can be used as a screening-library for assigning beta-kinks in unresolved coordinate dataset. Overall, our map for Kinked-{beta} provides a robust framework for detailed structural and kinetics investigation of these important motifs in prion-like proteins that lead to formation of amyloid fibrils.

biophysics↗

bioRxiv2023

Atomic-scale structural insights into the functional roles of the full low complexity domain of the hnRNPA1 protein

hnRNPA1, a protein from the heterogeneous-nuclear ribonucleoprotein fam-ily, mediates cellular processes such as RNA metabolism and DNA telomere maintenance. Besides the folded RNA recognition motifs, hnRNPA1 has a [~] 135 amino-acids long low-complexity domain (LCD) consisting of an RGG-rich region and a prion-like domain (PrLD). Biochemical data suggest that RGG-rich region modulates recognition of G-quadruplexes (GQs) in the telomeric repeats. Here, we utilize an in-house developed replica exchange technique (REHT) to generate the heterogeneous conformation ensemble of hnRNPA1-RGG and explore its functional significance in telomere maintenance. Single chain statistics and abundance of structural motifs, as well as consistency with experimentally reported struc-tural data, suggest faithful recapitulation of local interactions. We also introduce a protocol to generate functionally significant IDP-nucleic acid complex structures that corroborate well with the experimental knowledge of their binding. We find that RGG-box preferentially binds to the grooves and loops of GQs providing specificity towards certain GQ structures with its Phe, Tyr, and Asn residues forming essential hydrogen bonds and electrostatic interactions. Several of these residues were also identified as important by the reported HSQC chemical shift data. Our binding and simulations studies also revealed that a minor population of the RGG-box can destabilize telomeric GQs, thereby expediting the unfolding activities of hnRNPA1-UP1 at the telomeric end.

biophysics↗

bioRxiv2023

Glycans modulate lipid binding in Lili-Mip lipocalin protein

The unique viviparous Pacific Beetle cockroaches provide nutrition to their embryo by secreting milk proteins Lili-Mip, which is a lipid-binding glycoprotein that crystallizes in vivo. The resolved in vivo crystal structure of variably glycosylated Lili-Mip shows a classical Lipocalin fold with an eight-stranded antiparallel beta-barrel enclosing a fatty acid. The availability of physiologically unaltered glycoprotein structure makes Lili-Mip a very attractive model system to investigate the role of glycans on protein structure, dynamics, and function. Towards that end, we have employed all-atom molecular dynamics simulations on various glycosylated stages of a bound and free Lili-Mip protein and characterized the impact of glycans and the bound lipid on the dynamics of this glycoconjugate. Our work provides important molecular-level mechanistic insights into the role of glycans in the nutrient storage function of the Lili-Mip protein. Our analyses show that the glycans locally stabilize spatially proximal residues and regulate the low amplitude opening motions of the residues at the entrance of the binding pocket. Glycans, which are located at the portal end of the barrel, also restrict the distal barrel depth and allosterically modulate the lipid dynamics in the barrel. A simple but effective distance-based network analysis of the protein also reveals the role of glycans in the subtle rewiring of residues crucial for determining the barrel depth and lipid orientation.

biophysics↗

bioRxiv2022

Clustering conformational ensembles of intrinsically disordered proteins with t-distributed stochastic neighbor embedding

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the t-distributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, A{beta}42, and a C-terminal fragment of -synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered sub-states within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information and provide interpretable visualizations of the conformational heterogeneity within each ensemble and enable the quantification of cluster populations and their relative shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs. SignificanceGrouping heterogeneous conformations of IDPs into "structurally similar" clusters facilitates a clearer understanding of the properties of IDP conformational ensembles and provides insights into "structural ensemble: function" relationships. In this work, we provide a unique approach for clustering IDP ensembles efficiently using a non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), to create clusters with structurally similar IDP conformations. We show how this can be used for meaningful biophysical analyses such as understanding the binding mechanisms of IDPs such as -synuclein and Amyloid {beta}42 with small drug molecules. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/516231v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@8ef906org.highwire.dtl.DTLVardef@7f14e5org.highwire.dtl.DTLVardef@134f9eeorg.highwire.dtl.DTLVardef@104a2ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2020

High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid parallel tempering scheme

Determining the conformational ensemble for proteins with multi-funneled complex free-energy landscapes is often not possible with classical structure-biology methods that produce time and ensemble averaged data. With vastly improved force fields and advances in rare-event sampling methods, molecular dynamics (MD) simulations offer a complementary approach towards determining the collection of 3-dimensional structures that proteins can adopt. However, in general, MD simulations need to either impose restraints or reweigh the generated data to match experiments. The limitations extend beyond systems with high free-energy barriers as is the case with metamorphic proteins such as RFA-H. The predicted structures in even weakly-funneled intrinsically disordered proteins (IDPs) such as Histatin-5 (His-5) are too compact relative to experiments. Here, we employ a new computationally-efficient parallel-tempering based advanced-sampling method applicable across proteins with extremely diverse free-energy landscapes. And we show that the calculated ensemble averages match reasonably well with the NMR, SAXS and other biophysical experiments without the need to reweigh. We benchmark our method against standard model systems such as alanine di-peptide, TRP-cage and {beta}-hairpin and demonstrate significant enhancement in the sampling efficiency. The method successfully scales to large metamorphic proteins such as RFA-H and to highly disordered IDPs such as His-5 and produces experimentally-consistent ensemble. By allowing accurate sampling across diverse landscapes, the method enables for ensemble conformational sampling of deep multi-funneled metamorphic proteins as well as highly flexible IDPs with shallow multi-funneled free-energy landscape. Significance/Authors SummaryGenerating high-resolution ensemble of intrinsically disordered proteins, particularly the highly flexible ones with high-charge and low-hydrophobicity and with shallow multi-funneled free-energy landscape, is a daunting task and often not possible since information from biophysical experiments provide time and ensemble average data at low resolutions. At the other end of the spectrum are the metamorphic proteins with multiple deep funnels and elucidating the structures of the transition intermediates between the fold topologies is a non-trivial exercise. In this work, we propose a new parallel-tempering based advanced-sampling method where the Hamiltonian is designed to allow faster decay of water orientation dynamics, which in turn facilitates accurate and efficient sampling across a wide variety of free-energy landscapes.

biophysics↗