Biology subjects

Sacquin-Mora, S.

Publications and source records attributed to Sacquin-Mora, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Deep-learning predictions of biomolecular structures : persistent limitations and new horizons extended by explicit ion addition

The advent of deep learning-driven tools such as AlphaFold has revolutionized the prediction of biomolecular structures, offering unprecedented accuracy and accessibility for proteins, RNA, and their complexes. While these tools have demonstrated remarkable success in benchmarking competitions and enabled experimentalists to generate models with ease, their widespread use has also highlighted persistent challenges. These include difficulties in assessing model confidence, limitations in predicting transmembrane domains, nucleic acids, conformational diversity, and interactions with ions or ligands, as well as the tendency to misfold intrinsically disordered regions (IDRs). In this perspective, we critically evaluate the strengths and limitations of current AI-based structure prediction tools through illustrative examples with a particular emphasis on the impact of explicit ion modelling. We notably report how the explicit addition of a few potassium cations to the prediction of IDRs or G-quadruplexes can trigger massive conformational switches compared to "dry" predictions. On this basis, we suggest modelling sequences both "dry" and in the presence of explicit potassium cations as a simple, practical way to sample alternative conformations and to expose disordered regions that current predictors tend to over-fold. We discuss the importance of reporting confidence metrics in publications to avoid overinterpretation. Furthermore, we address the unique challenges of RNA structure prediction, where data scarcity and structural complexity limit the performance of both classical and deep learning methods. Our analysis underscores the need for continued methodological advancements, integration of complementary computational tools, and expansion of high-quality experimental datasets. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/740587v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@e950e9org.highwire.dtl.DTLVardef@1bf22b3org.highwire.dtl.DTLVardef@17f5229org.highwire.dtl.DTLVardef@1eb2e9f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Simulations of an extended Tau/tubulins interface reveal a complex disorder-disorder interplay mediated by the C-terminal tails

Building on a complex between a tubulin protofilament (PF) and a fragment of the Tau protein containing residues 169 to 367, we investigate the dynamics of the disordered elements of the system, namely the tubulin C-terminal tails (CTTs) and the Tau protein, using classical all-atom molecular dynamics simulations. Our results show that CTTs adopt a hook-like dynamic pattern on the bare PF while remaining highly mobile. The binding of Tau on the PF surface alters the dynamics of the I-CTTs in a sequence-dependent manner. While the repeat domains of Tau are mostly maintained on the PF by weak and strong binding patches with the tubulin cores, the Proline-Rich Region (PRR) relies on the wrapping phenomenon of I-CTTs to fuzzily stabilize its interaction with the PF. Our study thus provides a deep dive into the dynamic interplay between the Tau protein and the CTTs of microtubules, the latter being characterized extensively using a variety of disorder-adapted metrics. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/721901v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@b3f985org.highwire.dtl.DTLVardef@1c2bf70org.highwire.dtl.DTLVardef@a66b95org.highwire.dtl.DTLVardef@1e138e0_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

DynaPIN: A Tool for Characterizing Dynamic Protein Interfaces

Static structural models often fail to capture the dynamic mechanisms of protein interactions. To address this, we introduce DynaPIN, an open-source pipeline for extracting dynamic interface fingerprints from molecular simulations. DynaPIN unifies quality control metrics, interface prediction accuracy assessment, and atomistic interaction analysis into a single automated workflow, accessible at https://github.com/CSB-KaracaLab/DynaPIN. A key feature is our interface-specific analysis centered on a Dynamic Interface definition, which classifies residues based on the persistence of their interaction status over the simulation. We applied DynaPIN to representative rigid, medium, and difficult targets from the DynaBench dataset, an MD simulation resource for Docking Benchmark 5.5. Our results show that interface flexibility diverges from static accuracy classifications established in Docking Benchmark 5.5, as explored before. All in all, by providing standardized, frame-resolved outputs, DynaPINs aim is to facilitate mechanistic studies and generate standardized unbiased data for future dynamics-aware artificial intelligence models.

bioinformatics↗

bioRxiv2026

A comparative investigation of the mannose binding interface in DC-SIGN and MRC1 carbohydrate recognition domains with all-atom molecular dynamics simulations

Protein-carbohydrate interactions play a key role in numerous biological processes, including immune response, and glycan-based ligands that can target specific protein receptors on a cell surface represent promising candidates for therapeutics applications. For example, in retinoblastoma, the DC-SIGN mannose receptor is overexpressed on the surface of pathogenic cells and represents an interesting target for mannose-based ligands. At the same time, these ligands should not bind to the MRC1 receptor, which is expressed by adjacent, healthy, retinal pigment epithelial cells and presents a carbohydrate recognition domain (CRD) similar to the one of DC-SIGN. Therefore, the challenge remains to obtain a detailed picture of the recognition process between carbohydrates and proteins, in order to design effective and selective therapeutic compounds. In this work we used classical, all-atom molecular dynamics (MD) simulations to investigate the interaction between several mannose based ligands and the CRDs from DC-SIGN and MRC1. The analysis of the protein-carbohydrate contacts from the resulting trajectories highlights the variability of the mannose binding modes on both CRDs, and shows how the increased affinity of mannose for the MRC1 CRD can be related to a specific mannose binding state that is not accessible in the DC-SIGN CRD. TOC image: For Table of Contents use only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/699853v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1ea6c2forg.highwire.dtl.DTLVardef@164a064org.highwire.dtl.DTLVardef@15e1348org.highwire.dtl.DTLVardef@1441309_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Sticky salts: overbinding of monovalent cations to phosphorylations in all-atom forcefields

Phosphorylation is a major post-translational modification, which is involved in the regulation of the dynamics and function of Intrinsically Disordered Proteins (IDPs). We recently characterized a phenomenon, which we termed n-Phosphate collaborations (nP-collabs), where bulk cations form stable bridges between several phosphoresidues in all-atom molecular dynamic simulations. nP-collabs were found to be sensitive to the combination of forcefields and cation types. Here, we attempt to assess the physical relevance of these nP-collabs by evaluating the strength of the cation/phosphate interaction through osmotic coefficient ({phi}) calculations on the model [Formula] and [Formula] salts, using different classical forcefields for phosphorylations. All force-fields were found to overestimate the strength of the interaction to various degrees. We thus designed new parameters for CHARMM36m and AmberFF99SB-ILDN using the Electronic Continuum Correction (ECC) approach, which provide remarkable agreement for{phi} values for both cation types and over a range of concentrations. We provide a preliminary test of these ECC parameters for phosphorylations by simulating the sevenfold-phosphorylated rhodopsin peptide 7PP and comparing secondary chemical shifts to experimental data. Conformational ensembles resulting from the ECC-derived phosphorylated forcefields display both qualitative and quantitative improvements with regard to full-charge forcefields. We thus conclude that long-lasting nP-collabs are artifacts for classical forcefields born from the lack of explicit polarization, and propose a possible computational strategy for the extensive parameterization of phosphorylations. The presence of long-lived nP-collabs in simulations produced using classical forcefields is therefore a serious concern for the accurate modelling of multiphosphorylated peptides and IDPs, which are at the center of research questions regarding neurodegenerative diseases such as Alzheimers or Parkinsons.

biochemistry↗

bioRxiv2025

Across (conformational) space and (relaxation) time: using coarse-grainsimulations to probe the intra- and interdomain dynamics of the Tau protein

The biological importance of intrinsically disordered proteins (IDP) has been established for over two decades, yet these systems remain difficult to characterize, as they are better described by conformational ensembles instead of a single reference structure for their folded counterparts. Tau is a prominent member of the IDP family which sees its cellular function regulated by multiple phosphorylations sites, and whose hyperphosphorylation is involved in neurodegenerative diseases such as Alzheimers. We use coarse-grain MD simulations with the CALVADOS model to investigate the conformational landscape of tau without and with phosphorylations. Characterizing the local compactness of IDPs allows us to highlight how disorder comes in various flavors, as we can define different domains along the tau sequence. We define the IDPs Statistical Tertiary Organization (STO) as the average spatial arrangements of domains, which constitutes an extension of the tertiary structure of folded proteins. We also use IDP specific metrics to characterize the local curvature and flexibility of tau. Comparing the local flexibilities with T2 relaxation times from NMR experiments, we show how this metric is related to the protein dynamics. A curvature and flexibility pattern in the repeat domains can also be connected to tau binding properties, without having to explicitly model the proteins interaction partner. Finally, we rediscuss the original paperclip model that describes the spatial organization of tau, and how phosphorylations impact it. The resulting changes in the protein intra- and interdomain interaction pattern allow us to propose experimental setups to test our hypothesis. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/665865v3_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@7b7fc5org.highwire.dtl.DTLVardef@182a9org.highwire.dtl.DTLVardef@129515borg.highwire.dtl.DTLVardef@19c6d8f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Menger_Curvature : a MDAKit implementation to decipher the dynamics, curvatures and flexibilities of polymeric backbones at the residue level

Characterizing the dynamics of the backbone of flexible polymers such as Intrinsically Disordered Regions and Proteins (IDRs and IDPs) has proven to be a significant challenge in molecular dynamics (MD) simulations due to their high conformational variability. The widely-used mobility metric Root-Mean-Squared Fluctuations (RMSF) is powerless to provide information for highly flexible systems, as defining a relevant reference structure is often not possible. We previously introduced a new flexibility metric to remedy this gap : the Local Flexibilities (LFs), derived (alongside the Local Curvatures (LCs)) from the Proteic Menger Curvatures (PMCs). Here we present a numba accelerated implementation for any polymer of the calculation of Menger Curvatures as a MDAKit from the widely-used MDAnalysis package. We perform a benchmark with the RMSF and another flexibility metric derived from Proteic Blocks (PBs), the Equivalent Number of PBs (Neq), and show that the PMCs are an order of magnitude faster to compute on a modern CPU chip. We applied all 3 flexibility metrics to a {beta}III-tubulin monomer as an example, as tubulins are known to possess the entire range of proteic elements, from -helix and {beta}-sheets to a flexible loop and a disordered C-terminal tail (CTT). RMSF, LFs and Neq all succeed in identifying the flexible loops and the CTT, although the RMSF requires a system-specific alignment to do so. Finally, we expose different applications of PMCs, LCs and LFs ranging from mechanism characterization to NMR T2 predictions. We believe that Menger curvatures will prove to be a valuable metric to study protein dynamics and polymers in general. The MDAKit package Menger_Curvature is readily available at https://github.com/EtienneReboul/menger_curvature

bioinformatics↗

bioRxiv2025

Hydrodynamic Radius Determination of Tau and AT8 Phosphorylated Tau Mutants: A Combined Simulation and Experimental Study

Hyperphosphorylated Tau is a hallmark of Alzheimers disease leading to functional loss and fibrillar inclusions. We aim to understand how AT8 phosphorylation affects the Taus conformation and dynamics during early pathological transformation. We engineered an alanine Tau mutant to target specific phosphorylation sites restricted to the AT8 epitope, generating two distinct phosphorylation states. Using a combination of biophysical methods, and pCALVADOS forcefield, we found that AT8 phosphorylation do not alter the hydrodynamic radius or overall dynamics of Tau. Simulations revealed that local stiffening and extension at the AT8 epitope scale with phosphorylation extent. Interestingly, phosphorylation induces distant contact losses toward the N-terminus. This study advances our understanding of the structure-function-dynamics relationship of Tau in neurodegeneration.

biophysics↗

bioRxiv2025

Impact of multiple phosphorylations on the tau-R2/tubulin interface

The phosphorylation of the microtubule-associated tau protein plays a key role in the regulation of its physiological function. In particular, tau hyperphosphorylation affects its binding on the tubulin surface, destabilizing the tau-microtubule interface and leading to the accumulation of fibrillar aggregates in the brain. In this work, we performed classical Molecular Dynamics simulations for the tau-R2/tubulin assembly with various phosphorylations states of serines 285, 289 and 293. We analyze the resulting trajectories to obtain a detailed view of the protein interface in the complex, and the impact of tau phosphorylations on the stability of this assembly, and on the tubulin disordered C-Terminal tails (CTTs) mobility. We show how the tubulin CTTs help maintaining the tau-R2 fragment on the tubulin surface despite the destabilizing effect induced by phosphorylations. Conversely, tau phosphorylation affects the CTTs flexibility and their potential activity as MAP recruiting hooks. Furthermore, counterion mediated bridges between the phosphate groups and tubulin glutamates also contribute to the binding of tau-R2 on the MT. Overall, the complex dynamics of this fuzzy phosphorylated assembly sheds a new light on the importance of the cytoplasmic environment in neurons in the context of Alzheimers disease.

biochemistry↗

bioRxiv2024

nP-collabs: Investigating counterion mediated bridges in the multiply phosphorylated tau-R2 repeat

Tau is an instrinsically disordered (IDP), microtubule-associated protein (MAP) that plays a key part in microtubule assembly and organization. The function of tau can be regulated via multiple phosphorylation sites. These post-translational modifications are known to decrease the binding affinity of tau for microtubules, and abnormal tau phosphorylation patterns are involved in Alzheimers disease. Using all-atom molecular dynamics (MD) simulations, we compared the conformational landscapes explored by the tau R2 repeat domain (which comprises a strong tubulin binding site) in its native state and with multiple phosphorylations on the S285, S289 and S293 residues, with four different standard force field (FF)/water model combinations. We find that the different parameters used for the phosphate groups (which can be more or less flexible) in these FFs, and the specific interactions between bulk cations and water lead to the formation of a specific type of counterion bridge, termed nP-collab (for nPhosphate collaboration, with n being an integer), where counterions form stable structures binding with two or three phosphate groups simultaneously. The resulting effect of nP-collabs on the tau-R2 conformational space differs when using sodium or potassium cations, and is likely to impact the peptide overall dynamics, and how this MAP interacts with tubulins. We also investigated the effect of phosphoresidues spacing and ionic concentration by modeling polyalanine peptides containing two phosphoserines located one to six residues apart. Three new metrics specifically tailored for IDPs (Proteic Menger Curvature, Local Curvature and Local Flexibility) were introduced, which allow us to fully characterize the impact of nP-collabs on the dynamics of disordered peptides at the residue level. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/590060v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1b1b599org.highwire.dtl.DTLVardef@99047org.highwire.dtl.DTLVardef@1df34b9org.highwire.dtl.DTLVardef@fe60b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Combining computational biology and experimental knowledge to draw a structural profile of the active membrane-assembled NADPH oxidase complex

The phagocyte NADPH oxidase complex (NOX2) is activated by various intracellular stimuli, resulting in the generation of reactive oxygen species, which are responsible for many physiological processes, including innate immune defense. Structures of the cytochrome b558, membrane catalytic core of the complex, in their resting state have been solved experimentally. Unfortunately, very little is known about the structure of the active complex, as it involves the assembly of modular proteins and disordered regions, that have been shown to be essential to the function of the enzyme. Here, we modelled the supra-structure of the active complex using Alphafold2 and taking into account experimental data as well as conformational analyses by SRCD. AF2 ability to generate complexes enabled us to visualize ways in which subunits could assemble together, and revealed the implications of intrinsically disordered regions in protein-protein and membrane-protein interactions. Additional Molecular Dynamics simulations of the membrane embedded complex bring further insight regarding the system dynamics. Altogether, our work provides evidence for a model of the structure of the active complex where disordered regions can enable multi-subunit assembly.

biochemistry↗

bioRxiv2023

It takes two to tango: Investigating the fuzzy interaction between tau and tubulin C-terminal tails

The microtubule-associated protein (MAP) tau plays a key role in the regulation of microtubule assembly and spatial organisation. Tau hyperphosphorylation affects its binding on the tubulin surface and has been shown to be involved in several pathologies such as Alzheimer disease. As the tau binding site on the microtubule lays close to the disordered and highly flexible tubulin C-terminal tails (CTTs), these are likely to impact the tau-tubulin interaction. Since the disordered tubulin CTTs are missing from the available experimental structures, we used homology modeling to build two complete models of tubulin heterotrimers with different isotypes for the {beta}-tubulin subunit ({beta}I/I/ {beta}I and {beta}III/I/{beta}III). We then performed long timescale classical Molecular Dynamics simulations for the tau-R2/tubulin assembly (in systems with and without CTTs) and analyzed the resulting trajectories to obtain a detailed view of the protein interface in the complex and the impact of the CTTs on the stability of this assembly. Additional analyses of the CTTs mobility in the presence, or in the absence, of tau also highlight how tau might modulate the CTTs activity as hooks that are involved in the recruitment of several MAPs. In particular, we observe a wrapping mechanism, where the {beta}-tubulin CTTs form a loop over tau-R2, thus stabilizing its interaction with the tubulin surface and simultaneously reducing the CTTs availability for interactions with other MAPs.

biochemistry↗

bioRxiv2021

Between two walls: Modeling the adsorption behavior of β-glucosidase A on bare and SAM-functionalised gold surfaces

The efficient immobilization of enzymes on surfaces remains a complex but central issue in the biomaterials field, which requires us to understand this process at the atomic level. Using a multi-scale approach combining all-atom molecular dynamics and coarse-grain Brownian dynamics simulations, we investigated the adsorption behavior of {beta}-glucosidase A ({beta}GA) on bare and SAM-functionalized gold surfaces. We monitored the enzyme position and orientation during the MD trajectories, and measured the contacts it forms with both surfaces. While the adsorption process has little impact on the protein conformation, it can nonetheless perturb its mechanical properties and catalytic activity. Our results show that compared to the SAM-functionalized surface, the adsorption of {beta}GA on bare gold is more stable, but also less specific, and more likely to disrupt the enzymes function. This observation emphasizes the fact that the structural organization of proteins at the solid interface is a keypoint when designing devices based on enzyme immobilization, as one must find an acceptable stability-activity trade-off. TOC image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/450859v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@d3d0d7org.highwire.dtl.DTLVardef@3403e4org.highwire.dtl.DTLVardef@eb804dorg.highwire.dtl.DTLVardef@13469c2_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2020

Moving pictures: Reassessing docking experiments with a dynamic view of protein interfaces

The modeling of protein assemblies at the atomic level remains a central issue in structural biology, as protein interactions play a key role in numerous cellular processes. This problem is traditionally addressed using docking tools, where the quality of the models is based on their similarity to a single reference experimental structure. However, using a static reference does not take into account the dynamic quality of the protein interface. Here, we used all-atom classical Molecular Dynamics simulations to investigate the stability of the reference interface for three complexes that previously served as targets in the CAPRI competition. For each one of these targets, we also ran MD simulations for ten models that are distributed over the High, Medium and Acceptable accuracy categories. To assess the quality of these models from a dynamic perspective, we set up new criteria which take into account the stability of the reference experimental protein interface. We show that, when the protein interfaces are allowed to evolve along time, the original ranking based on the static CAPRI criteria no longer holds as over 50% of the docking models undergo a category change (which can be either toward a better or a lower accuracy group) when reassessing their quality using dynamic information. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/415885v2_ufig1.gif" ALT="Figure 1"> View larger version (9K): org.highwire.dtl.DTLVardef@1e4f4a8org.highwire.dtl.DTLVardef@7a4bccorg.highwire.dtl.DTLVardef@1064caforg.highwire.dtl.DTLVardef@948619_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2020

Implicit modeling of the impact of adsorption on solid surfaces for protein mechanics and activity with a coarse-grain representation

Surface immobilized enzymes play a key role in numerous biotechnological applications such as biosensors, biofuel cells or biocatalytic synthesis. As a consequence, the impact of adsorption on the enzyme structure, dynamics and function needs to be understood on the molecular level as it is critical for the improvement of these technologies. With this perspective in mind, we used a theoretical approach for investigating protein local flexibility on the residue scale that couples a simplified protein representation with an elastic network and Brownian Dynamics simulations. The protein adsorption on a solid surface is implicitly modeled via additional external constraints between the residues in contact with the surface. We first performed calculations on a redox enzyme, bilirubin oxidase (BOD) from M. verrucaria, to study the impact of adsorption on its mechanical properties. The resulting rigidity profiles show that, in agreement with the available experimental data, the mechanical variations observed in the adsorbed BOD will depend on its orientation and its anchor residues (i.e. residues that are in contact with the functionalized surface). Additional calculations on ribonuclease A and nitroreductase shed light on how seemingly stable adsorbed enzymes can nonetheless display an important decrease in their catalytic activity resulting from a perturbation of their mechanics and internal dynamics.

biophysics↗

bioRxiv2019

Coarse-grain simulations on NMR conformational ensembles highlight non catalytic functional residues in proteins

Dynamics are a key feature of protein function, and this is especially true of gating residues, which occupy cavity or tunnel lining positions in the protein structure, and will reversibly switch between open and closed conformations in order to control the diffusion of small molecules within a proteins internal matrix. Earlier work on globins and hydrogenases have shown that these gating residues can be detected using a multiscale scheme combining all atom classic molecular dynamics simulations and coarse grain calculations of the resulting conformational ensemble mechanical properties. Here we show that the structural variations observed in the conformational ensembles produced by NMR spectroscopy are sufficient to induce noticeable mechanical changes in a protein, which in turn can be used to identify residues important for function and forming a mechanical nucleus in the protein core. This new approach, which combines experimental data and rapid coarse-grain calculations and no longer needs to resort to time-consuming all-atom simulations, was successfully applied to five different protein families. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/532507v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@104c511org.highwire.dtl.DTLVardef@25ebecorg.highwire.dtl.DTLVardef@1a3d721org.highwire.dtl.DTLVardef@180f1d0_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2018

Protein interaction energy landscapes are shaped by functional and also non-functional partners

In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. We developed an original theoretical framework in order to interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters. Our theoretical framework relies on a two-dimensional (2D) representation of interaction energy landscapes with 2D energy maps that reflect in a synthetic way the propensity of a protein to interact with another protein. We investigated the propensity of protein surfaces to interact with functional and arbitrary partners and asked whether their interaction propensity is conserved during the evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the whole energy landscapes of 74 proteins interacting with different sets of homologs, corresponding to their functional partners family or arbitrary protein families. Then, we systematically compared the energy maps resulting from the docking of a given protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding site but also of the rest of the protein surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also to arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of selected partners and opens the way for further developments to study the behavior of proteins in a specific environment.

bioinformatics↗

bioRxiv2018

Hidden partners: Using cross-docking calculations to predict binding sites for proteins with multiple interactions

Protein-protein interactions control a large range of biological processes and their identification is essential to understand the underlying biological mechanisms. To complement experimental approaches, in silico methods are available to investigate protein-protein interactions. Cross-docking methods, in particular, can be used to predict protein binding sites. However, proteins can interact with numerous partners and can present multiple binding sites on their surface, which may alter the binding site prediction quality. We evaluate the binding site predictions obtained using complete cross-docking simulations of 358 proteins with two different scoring schemes accounting for multiple binding sites. Despite overall good binding site prediction performances, 68 cases were still associated with very low prediction quality, presenting individual area under the specificity-sensitivity ROC curve (AUC) values below the random AUC threshold of 0.5, since cross-docking calculations can lead to the identification of alternate protein binding sites (that are different from the reference experimental sites). For the large majority of these proteins, we show that the predicted alternate binding sites correspond to interaction sites with hidden partners, i.e. partners not included in the original cross-docking dataset. Among those new partners, we find proteins, but also nucleic acid molecules. Finally, for proteins with multiple binding sites on their surface, we investigated the structural determinants associated with the binding sites the most targeted by the docking partners.\n\nAbbreviationsANOVA: ANalysis Of Variance; AUC: Area Under the Curve; Best Interface: BI; CAPRI: Critical Assessment of Prediction of Interactions; CC-D: Complete Cross-Docking; DNA: DesoxyriboNucleic Acid; FDR: False Discovery Rate; FRIres(type): Fraction of each Residue type in the Interface; FP: False Positives; GI: Global Interface; HCMD: Help Cure Muscular Dystrophy; JET: Joint Evolutionary Tree; MAXDo: Molecular Association via Cross Docking; NAI: Nucleic Acid Interface; NPV: Negative Predicted Value; PDB: Protein Data Bank; PIP: Protein Interface Propensity; PiQSi: Protein Quaternary Structure investigation; PPIs: Protein-Protein Interactions; PPV: Positive Predicted Value; Prec.: Precision; PrimI: Primary Interface; RNA: RiboNucleic Acid; ROC: Receiver Operating Characteristic; SecI: Secondary Interface; Sen.: Sensitivity; Spe.: Specificity; TN: True Negatives; TP: True Positives; WCG: World Community Grid.

bioinformatics↗