Biology subjects

Souza, P. C. T.

Publications and source records attributed to Souza, P. C. T..

9 recordsLinked to original sources

bioRxiv2026

Signal peptidase complexes set species-specific rules for signal peptide cleavage

Protein secretion is essential for cell function and begins when signal peptides direct nascent proteins into the secretory pathway, where they are cleaved by the signal peptidase complex (SPC). Although this pathway is highly conserved, signal peptides do not always function efficiently across species, and the molecular basis for this incompatibility remains unclear. Here, we show that human signal peptides with longer hydrophobic cores efficiently target and translocate nascent proteins in both yeast and human but are frequently left uncleaved in yeast, identifying signal peptide cleavage as a major barrier to cross-species compatibility. Molecular dynamics (MD) simulations reveal that, despite their highly conserved architectures, yeast and human SPCs generate distinct membrane-thinning profiles near the signal peptide-binding region. Our results support a model in which SPC-lipid interactions tune the local membrane environment to accommodate signal peptides of distinct hydrophobic core length, providing a biophysical mechanism for species-specific signal peptide recognition. These findings offer a mechanistic framework for understanding and potentially engineering protein secretion across diverse expression hosts.

cell biology↗

bioRxiv2026

Towards transferable explicit-solvent coarse-grained models for biomolecular condensates

Biomolecular condensates formed by intrinsically disordered proteins require molecular models that accurately describe proteins in both dilute solution and condensed phases. Explicit-solvent coarse-grained models offer an attractive balance between chemical resolution and computational efficiency. Yet, it remains unclear whether improving dilute-state properties is sufficient to obtain an accurate description of condensates. Here, we address this question by introducing minimal modifications to the Martini 3 force field that combine recent advances in bonded interactions with refined protein-water interactions and strengthened glycine self-interactions, while preserving the underlying chemical transferability of the model. The resulting model substantially improves the description of single-chain conformations across a diverse benchmark of disordered proteins. We then investigate phase separation of the well-characterized low-complexity domain of heterogeneous nuclear ribonucleoprotein A1 and its sequence variants. The model reproduces several key physicochemical properties of biomolecular condensates, including chain expansion in the dense phase, sequence-dependent intermolecular contacts, protein diffusion and its relation to single-chain dimensions, and hydration, while revealing quantitative limitations in condensate density, phase equilibria, and ion partitioning. Our results show that improving dilute-state behaviour translates into a better description of condensed-phase properties, including condensate density, but is not sufficient to quantitatively reproduce the equilibrium between the dilute and dense phases.

biophysics↗

bioRxiv2026

When lipids embrace RNA: pH-driven dynamics and mechanisms of LNP-mediated siRNA delivery

We present a comprehensive analysis of an efficient lipid nanoparticle (LNP) formulation that exhibits strong nucleic-acid delivery and potent inhibition of targeted RNAs. Using a combination of coarse-grained and atomistic molecular dynamics simulations, we characterized the pH-dependent structure of both unloaded and RNA-loaded LNPs, elucidated the mechanism of RNA encapsulation, and used these models to propose a plausible mechanism of endosomal escape. Consistent with prior experimental and computational studies, our simulations reproduce an inverted-hexagonal-type morphology in RNA-loaded LNPs, in which a hydrated core provides a polar environment suitable for accommodating RNA, whose charge is neutralized mainly by ionizable lipids that remain protonated near the RNA even at high pH, thereby bridging the RNA with the surrounding lipid environment. This structural picture is consistently observed across our multiscale simulations, with smaller self-assembled LNP mimetics reproducing the same local organization at both coarse-grained and atomistic resolution. A potential mechanism of endosomal escape emerges spontaneously from the simulations, involving stalk formation between the LNP and the endosomal membrane, followed by the opening of a water-filled pore that permits slow RNA diffusion, in line with the low efficiency and slow kinetics reported for endosomal escape. The rate-limiting step of endosomal escape arises from persistent electrostatic coupling between RNA and protonated ionizable lipids maintained by the immediate RNA-lipid environment, hindering cargo disengagement even after pore formation. This delayed release is consistent with the experimentally observed time-dependent inhibitory activity of the loaded LNP. Together, these results highlight the importance of local pK and protonation effects near the RNA, which are not captured by global apparent pK measurements.

biophysics↗

bioRxiv2025

Martini 3 protein models - a practical introduction to different structure bias models and their comparison

Biophysical characterization of protein structure and dynamics is essential in many scientific fields, including molecular biology, drug discovery, and enzyme design. Molecular dynamics (MD) simulations have become an increasingly important tool for studying these properties. This chapter provides a hands-on introduction to protein modeling with the Martini 3 coarse-grained (CG) force field. We outline its two-layer framework, where the first layer defines molecular topology and interactions, while the second layer applies structural bias to maintain secondary, tertiary, and quaternary structures. Three structure bias approaches - Elastic Network (EN), G[o]Martini, and OLIVES - are discussed, highlighting their advantages and trade-offs. Using a protein kinase as a case study, we demonstrate the step-by-step setup of Martini 3 protein models for simulations with the program package GROMACS, including system preparation, fine-tuning, and validation against atomistic reference simulations. Additionally, we explore the combination of an intrinsically disordered region (IDR) with a structured protein domain. By the end of this chapter, readers will have the necessary expertise to apply Martini 3-based protein modeling to a wide range of research applications.

biophysics↗

bioRxiv2024

Creating Coarse-Grained Systems with COBY: Towards Higher Accuracy in Membrane Complexity

Current trends in molecular modelling are geared towards increasingly realistic representations of the modelled systems. This is reflected in larger, more complex systems, which are difficult to build and would ideally rely on a software that converts userprovided descriptors into system coordinates. This is not a trivial task, as the building algorithms use simplifications that can introduce inaccuracies in the system properties that do not correspond to the requested values. We created COBY, a coarse-grained system builder that can create a large variety of systems in a single command call using Martini molecule models. We improved the accuracy of the complex membrane and solvent building procedures, introduced a variety of arguments that can be used to build diverse systems, and implemented features intended for force field development. COBY can be used to build flat membranes of any degree of complexity, handle protein and solvent insertion, solute flooding, stacked membranes, membrane patches and pores, and includes advanced functionalities such as molecule import, lipid building from fragments, handling of multiple parameter libraries, and several choices of algorithms for interpreting user-provided system descriptors. COBY is an open-source software written in Python 3, and the code, documentation, and tutorials are hosted at github.com/MikkelDA/COBY. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/604601v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@15e46a4org.highwire.dtl.DTLVardef@6fd668org.highwire.dtl.DTLVardef@657541org.highwire.dtl.DTLVardef@f51840_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

GoMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The G[o]Martini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced G[o]Martini model, which combines a virtual-site implementation of G[o] models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with G[o] models.

biophysics↗

bioRxiv2022

Coarse-graining made easy with the MArtini Database Server

The MArtini Database (MAD - www.mad.ibcp.fr) is a web server designed for the sharing structures and topologies of molecules parameterized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems and deliver all files necessary to start simulations in the GROMACS MD engine.

biophysics↗

bioRxiv2021

Predicting Transmembrane (TM) Domain Dimer Structures using Martini 3

Determination of the structure and dynamics of transmembrane (TM) regions of single-transmembrane receptors is key to understanding their mechanism of signal transduction across the plasma membrane. Although many studies have been performed on isolated soluble extra- and intracellular receptor domains in aqueous solutions, limited knowledge exists on the lipid embedded TM domain. In this study, we examine the assembly of configurations of receptor TM region dimers using the Martini 3 force field for coarse-grain (CG) molecular dynamics simulations. This recently published version of Martini has new bead types and sizes, which allows more accurate predictions of molecular interactions compared to the previous versions. At first glance our results with Martini 3 simulations show only a reasonable agreement with ab initio predictions using PREDDIMER (for TM domains only), AlphaFold2 Multimer and with available NMR derived structures for TM helix dimers. Specifically, 6 of 11 CG TM structures are similar to the NMR structures (within < 3.5 [A] mainchain RMSD) compared to 10 of 11 and 9 of 11 using PREDDIMER and Alphafold, respectively (7 structures of the latter are within 1.5 [A]) Surprisingly, AlphaFold2 predictions are more comparable with NMR structures when the database of 2001 (mainly composed of soluble proteins) instead of 2020 PDB structures are used. While there are some differences in the conditions used, the CG simulations primarily reveal that alternate configurations of the TM dimers that are sampled, which readily interconvert with a predominant population. The implications of these findings for our understanding of the signalling mechanism of TM receptors are discussed, including opportunities for the development of new pharmaceuticals, some of which are peptide based.

biophysics↗

bioRxiv2021

Conformational clamping by a membrane ligand activates the EphA2 receptor

The EphA2 receptor is a promising drug target for cancer treatment, since EphA2 activation can inhibit metastasis and tumor progression. It has been recently described that the TYPE7 peptide activates EphA2 using a novel mechanism that involves binding to the single transmembrane domain of the receptor. TYPE7 is a conditional transmembrane (TM) ligand, which only inserts into membranes at neutral pH in the presence of the TM region of EphA2. However, how membrane interactions can activate EphA2 is not known. We systematically altered the sequence of TYPE7 to identify the binding motif used to activate EphA2. With the resulting six peptides, we performed biophysical and cell migration assays that identified a new potent peptide variant. We also performed a mutational screen that determined the helical interface that mediates dimerization of the TM domain of EphA2 in cells. These results, together with molecular dynamic simulations, allowed to elucidate the molecular mechanism that TYPE7 uses to activate EphA2, where the membrane peptide acts as a molecular clamp that wraps around the TM dimer of the receptor. We propose that this binding mode stabilizes the active conformation of EphA2. Our data, additionally, provide clues into the properties that TM ligands need to have in order to achieve activation of membrane receptors.

biophysics↗