Biology subjects

Perlinska, A. P.

Publications and source records attributed to Perlinska, A. P..

4 recordsLinked to original sources

bioRxiv2023

Knot or Not? Sequence-Based Identification of Knotted Proteins With Machine Learning

Knotted proteins, although scarce, are crucial structural components of certain protein families, and their roles remain a topic of intense research. Capitalizing on the vast collection of protein structure predictions offered by AlphaFold, this study computationally examines the entire UniProt database to create a robust dataset of knotted and unknotted proteins. Utilizing this dataset, we develop a machine learning model capable of accurately predicting the presence of knots in protein structures solely from their amino acid sequences, with our best-performing model demonstrating a 98.5% overall accuracy. Unveiling the sequence factors that contribute to knot formation, we discover that proteins predicted to be unknotted from known knotted families are typically non-functional fragments missing a significant portion of the knot core. The study further explores the significance of the substrate binding site in knot formation, particularly within the SPOUT protein family. Our findings spotlight the potential of machine learning in enhancing our understanding of protein topology and propose further investigation into the role of knotted structures across other protein families. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/556468v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1466077org.highwire.dtl.DTLVardef@1674829org.highwire.dtl.DTLVardef@1b283a5org.highwire.dtl.DTLVardef@e0e962_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Nucleolar Essential Protein 1 (Nep1): Elucidation of Enzymatic Catalysis Mechanism by Combined Molecular Dynamics Simulation and Quantum Chemical Calculations

Nep1 is a protein essential for the formation of the eukaryotic and archaeal small ribosomal subunit. It is an enzyme responsible for the site-specific SAM-dependent methylation of pseudouridine ({Psi}) during the pre-rRNA processing. It possesses a non-trivial topology, namely, a 31 knot in the active site. Herein, we investigate the structure and mechanism of catalysis of Nep1 using a combination of bioinformatics, computational, and experimental methods. In particular, we address the issue of seemingly unfeasible deprotonation of {Psi} nucleobase in the active site of Nep1 by a distant aspartate residue (e.g., D101 in Nep1 of S. cerevisiae). Sequence alignment analysis across different organisms identifies a conserved serine/threonine residue that may play a role of a proton-transfer mediator (e.g., S233 in Nep1 from S. cerevisiae), facilitating the reaction. Two enzyme-substrate complexes, one based on an available crystal structure and the other generated by molecular docking, of representative eukaryotic (from S. cerevisiae) and archaeal (from A. fulgidus) Nep1 homologs are subjected to molecular dynamics (MD) simulations. The resulting trajectories confirm that the hydroxyl-containing amino acid can indeed adopt a position suitable for proton-shuttling, with the OH group located in between the proton donor and acceptor. However, during the MD simulations, a water molecule emerges from arrangements of the active site, which can assume the role of the proton-transfer mediator instead. To discern between these two alternative pathways, we evaluate the possible methylation mechanisms by quantum-chemical calculations based on density functional theory, using the cluster approach. The obtained energy profiles indicate that the most facile course of the reaction for both the yeast and archaeal enzymes is to engage the water molecule. These results are corroborated by agreement of the computed energy barriers with experimentally measured enzyme kinetics. Moreover, mutational studies show that, while aspartate D101 is crucial for the catalytic activity, serine S233 is irrelevant in this context, indirectly supporting the water-mediated proton transfer. Our findings comprehensively elucidate the mode of action of Nep1 and provide implication for understanding the catalytic mechanisms of other enzymes that involve a proton transfer in the active site over extended distances.

biophysics↗

bioRxiv2022

New 63 knot and other knots in human proteome from AlphaFold predictions

AlphaFold is a new, highly accurate machine learning protein structure prediction method that outperforms other methods. Recently this method was used to predict the structure of 98.5% of human proteins. We analyze here the structure of these AlphaFold-predicted human proteins for the presence of knots. We found that the human proteome contains 65 robustly knotted proteins, including the most complex type of a knot yet reported in proteins. That knot type, denoted 63 in mathematical notation, would necessitate a more complex folding path than any knotted proteins characterized to date. In some cases AlphaFold structure predictions are not highly accurate, which either makes their topology hard to verify or results in topological artifacts. Other structures that we found, which are knotted, potentially knotted, and structures with artifacts (knots) we deposited in a database available at: https://knotprot.cent.uw.edu.pl/alphafold.

molecular biology↗

bioRxiv2019

Restriction of S-adenosylmethionine conformational freedom by knotted protein binding sites

S-adenosylmethionine (SAM) is one of the most important enzyme substrates. It is vital for the function of various proteins, including large group of methyltransferases (MTs). Intriguingly, some bacterial and eukaryotic MTs, while catalysing the same reaction, possess significantly different topologies, with the former being a knotted one. Here, we conducted a comprehensive analysis of SAM conformational space and factors that affect its vastness. We investigated SAM in two forms: free in water (via NMR studies and explicit solvent simulations) and bound to proteins (based on all data available in the PDB). We identified structural descriptors - angles which show the major differences in SAM conformation between unknotted and knotted methyltransferases. Moreover, we report that this is caused mainly by a characteristic for knotted MTs tight binding site formed by the knot and the presence of adenine-binding loop. Additionally, we elucidate conformational restrictions imposed on SAM molecules by other protein groups in comparison to conformational space in water. Author summaryThe topology of a folded polypeptide chain has great impact on the resulting protein function and its interaction with ligands. Interestingly, topological constraints appear to affect binding of one of the most ubiquitous substrates in the cell, S-adenosylmethionine (SAM), to its target proteins. Here, we demonstrate how binding sites of specific proteins restrict SAM conformational freedom in comparison to its unbound state, with a special interest in proteins with non-trivial topology, including an exciting group of knotted methyltransferases. Using a vast array of computational methods combined with NMR experiments, we identify key structural features of knotted methyltransferases that impose unorthodox SAM conformations. We compare them with the characteristics of standard, unknotted SAM binding proteins. These results are significant for understanding differences between analogous, yet topologically different enzymes, as well as for future rational drug design.

biophysics↗