Insight into membraneless organelles and their associated proteins: Drivers, Clients and Regulators.

In recent years, attention has been devoted to proteins forming immiscible liquid phases within the liquid intracellular medium, commonly referred to as membraneless organelles (MLO). These organelles enable the spatiotemporal associations of cellular components that exchange dynamically with the cellular milieu. The dysregulation of these liquid-liquid phase separation processes (LLPS) may cause various diseases including neurodegenerative pathologies and cancer, among others. Until very recently, databases containing information on proteins forming MLOs, as well as tools and resources facilitating their analysis, were missing. This has recently changed with the publication of 4 databases that focus on different types of experiments, sets of proteins, inclusion criteria, and levels of annotation or curation. In this study we integrate and analyze the information across these databases, complement their records, and produce a consolidated set of proteins that enables the investigation of the LLPS phenomenon. To gain insight into the features that characterize different types of MLOs and the roles of their associated proteins, they were grouped into categories: High Confidence MLO associated (including Drivers and reviewed proteins), Potential Clients and Regulators, according to their annotated functions. We show that none of the databases taken alone covers the data sufficiently to enable meaningful analysis, validating our integration effort as essential for gaining better understanding of phase separation and laying the foundations for the discovery of new proteins potentially involved in this important cellular process. Lastly, we developed a server, enabling customized selections of different sets of proteins based on MLO location, database, disorder content, among other attributes (https://forti.shinyapps.io/mlos/).

Distance-Based Metrics for Comparing Conformational Ensembles of Intrinsically Disordered Proteins.

Intrinsically disordered proteins are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons because their conformational diversity precludes optimal superimposition of the atomic coordinates necessary for deriving common similarity measures such as the root mean-square deviation of these coordinates. Here, we introduce superimposition-free metrics that are based on computing matrices of the Cα-Cα distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the root mean-square difference between the medians of the Cα-Cα distance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of intrinsically disordered proteins derived using experimental restraints or by molecular simulations and for proteins containing both structured and disordered regions.

Modeling protein-protein, protein-peptide, and protein-oligosaccharide complexes: CAPRI 7th edition.

We present the seventh report on the performance of methods for predicting the atomic resolution structures of protein complexes offered as targets to the community-wide initiative on the Critical Assessment of Predicted Interactions. Performance was evaluated on the basis of 36 114 models of protein complexes submitted by 57 groups-including 13 automatic servers-in prediction rounds held during the years 2016 to 2019 for eight protein-protein, three protein-peptide, and five protein-oligosaccharide targets with different length ligands. Six of the protein-protein targets represented challenging hetero-complexes, due to factors such as availability of distantly related templates for the individual subunits, or for the full complex, inter-domain flexibility, conformational adjustments at the binding region, or the multi-component nature of the complex. The main challenge for the protein-peptide and protein-oligosaccharide complexes was to accurately model the ligand conformation and its interactions at the interface. Encouragingly, models of acceptable quality, or better, were obtained for a total of six protein-protein complexes, which included four of the challenging hetero-complexes and a homo-decamer. But fewer of these targets were predicted with medium or higher accuracy. High accuracy models were obtained for two of the three protein-peptide targets, and for one of the protein-oligosaccharide targets. The remaining protein-sugar targets were predicted with medium accuracy. Our analysis indicates that progress in predicting increasingly challenging and diverse types of targets is due to closer integration of template-based modeling techniques with docking, scoring, and model refinement procedures, and to significant incremental improvements in the underlying methodologies.

De novo missense variants in RAC3 cause a novel neurodevelopmental syndrome.

PURPOSE: RAC3 is an underexamined member of the Rho GTPase gene family that is expressed in the developing brain and linked to key cellular functions. De novo missense variants in the homolog RAC1 were recently associated with developmental disorders. In the RAC subfamily, transforming missense changes at certain shared residues have been observed in human cancers and previously characterized in experimental studies. The purpose of this study was to determine whether constitutional dysregulation of RAC3 is associated with human disease. METHODS: We discovered a RAC3 variant in the index case using genome sequencing, and searched for additional variants using international data-sharing initiatives. Functional effects of the variants were assessed using a multifaceted approach generalizable to most clinical laboratory settings. RESULTS: We rapidly identified five individuals with de novo monoallelic missense variants in RAC3, including one recurrent change. Every participant had severe intellectual disability and brain malformations. In silico protein modeling, and prior in vivo and in situ experiments, supported a transforming effect for each of the three different RAC3 variants. All variants were observed in databases of somatic variation in cancer. CONCLUSIONS: Missense variants in RAC3 cause a novel brain disorder, likely through a mechanism of constitutive protein activation.

Modeling protein-protein and protein-peptide complexes: CAPRI 6th edition.

We present the sixth report evaluating the performance of methods for predicting the atomic resolution structures of protein complexes offered as targets to the community-wide initiative on the Critical Assessment of Predicted Interactions (CAPRI). The evaluation is based on a total of 20,670 predicted models for 8 protein-peptide complexes, a novel category of targets in CAPRI, and 12 protein-protein targets in CAPRI prediction Rounds held during the years 2013-2016. For two of the protein-protein targets, the focus was on the prediction of side-chain conformation and positions of interfacial water molecules. Seven of the protein-protein targets were particularly challenging owing to their multicomponent nature, to conformational changes at the binding site, or to a combination of both. Encouragingly, the very large multiprotein complex with the nucleosome was correctly predicted, and correct models were submitted for the protein-peptide targets, but not for some of the challenging protein-protein targets. Models of acceptable quality or better were obtained for 14 of the 20 targets, including medium quality models for 13 targets and high quality models for 8 targets, indicating tangible progress of present-day computational methods in modeling protein complexes with increased accuracy. Our evaluation suggests that the progress stems from better integration of different modeling tools with docking procedures, as well as the use of more sophisticated evolutionary information to score models. Nonetheless, adequate modeling of conformational flexibility in interacting proteins remains an important area with a crucial need for improvement. Proteins 2017; 85:359-377. © 2016 Wiley Periodicals, Inc.

Computational proteome-wide screening predicts neurotoxic drug-protein interactome for the investigational analgesic BIA 10-2474.

The investigational compound BIA 10-2474, designed as a long-acting and reversible inhibitor of fatty acid amide hydrolase for the treatment of neuropathic pain, led to the death of one participant and hospitalization of five others due to intracranial hemorrhage in a Phase I clinical trial. Putative off-target activities of BIA 10-2474 have been suggested to be major contributing factors to the observed neurotoxicity in humans, motivating our study's proteome-wide screening approach to investigate its polypharmacology. Accordingly, we performed an in silico screen against 80,923 protein structures reported in the Protein Data Bank. The resulting list of 284 unique human interactors was further refined using target-disease association analyses to a subset of proteins previously linked to neurological, intracranial, inflammatory, hemorrhagic or clotting processes and/or diseases. Eleven proteins were identified as potential targets of BIA 10-2474, and the two highest-scoring proteins, Factor VII and thrombin, both essential blood-clotting factors, were predicted to be inhibited by BIA 10-2474 and suggest a plausible mechanism of toxicity. Once this small molecule becomes commercially available, future studies will be conducted to evaluate the predicted inhibitory effect of BIA 10-2474 on blood clot formation specifically in the brain.

Intercellular network structure and regulatory motifs in the human hematopoietic system.

The hematopoietic system is a distributed tissue that consists of functionally distinct cell types continuously produced through hematopoietic stem cell (HSC) differentiation. Combining genomic and phenotypic data with high-content experiments, we have built a directional cell-cell communication network between 12 cell types isolated from human umbilical cord blood. Network structure analysis revealed that ligand production is cell type dependent, whereas ligand binding is promiscuous. Consequently, additional control strategies such as cell frequency modulation and compartmentalization were needed to achieve specificity in HSC fate regulation. Incorporating the in vitro effects (quiescence, self-renewal, proliferation, or differentiation) of 27 HSC binding ligands into the topology of the cell-cell communication network allowed coding of cell type-dependent feedback regulation of HSC fate. Pathway enrichment analysis identified intracellular regulatory motifs enriched in these cell type- and ligand-coupled responses. This study uncovers cellular mechanisms of hematopoietic cell feedback in HSC fate regulation, provides insight into the design principles of the human hematopoietic system, and serves as a foundation for the analysis of intercellular regulation in multicellular systems.

Expanding the landscape of chromatin modification (CM)-related functional domains and genes in human.

Chromatin modification (CM) plays a key role in regulating transcription, DNA replication, repair and recombination. However, our knowledge of these processes in humans remains very limited. Here we use computational approaches to study proteins and functional domains involved in CM in humans. We analyze the abundance and the pair-wise domain-domain co-occurrences of 25 well-documented CM domains in 5 model organisms: yeast, worm, fly, mouse and human. Results show that domains involved in histone methylation, DNA methylation, and histone variants are remarkably expanded in metazoan, reflecting the increased demand for cell type-specific gene regulation. We find that CM domains tend to co-occur with a limited number of partner domains and are hence not promiscuous. This property is exploited to identify 47 potentially novel CM domains, including 24 DNA-binding domains, whose role in CM has received little attention so far. Lastly, we use a consensus Machine Learning approach to predict 379 novel CM genes (coding for 329 proteins) in humans based on domain compositions. Several of these predictions are supported by very recent experimental studies and others are slated for experimental verification. Identification of novel CM genes and domains in humans will aid our understanding of fundamental epigenetic processes that are important for stem cell differentiation and cancer biology. Information on all the candidate CM domains and genes reported here is publicly available.

Mechanism and energy landscape of domain swapping in the B1 domain of protein G.

Three-dimensional domain swapping has emerged as a ubiquitous process for homo-oligomer formation in many unrelated proteins, but the molecular mechanism of this process is still poorly understood. Here we present a mechanism for the swapping reaction in the B1 domain of the immunoglobulin G binding protein from group G of Streptococcus (GB1). This is a particularly attractive system for investigating the swapping process, as the swapped dimer formed by the quadruple mutant (L5V/F30V/Y33F/A34F) of GB1 was recently shown to exist in equilibrium with a monomer-like conformation over time scales of minutes. According to our mechanism, swapping in GB1 starts from the C-terminus of the polypeptide chain and progresses by exchanging an increasing portion of the chains until a stable conformational state is reached. This exchange process does not involve unfolding. Rather, the conformational changes of individual monomers and their association are tightly coupled to minimize solvent exposure and maximize the total number of native contacts at all times, thereby closely approximating the minimum energy path of the reaction. Using detailed atomic descriptions, we compute the complete free-energy profiles of the exchange reaction for the GB1 quadruple mutant that forms swapped dimers and for the wild-type protein, which is monomeric. In both GB1 forms, intermediates sample a surprisingly wide range of nearly isoenergetic association modes and hinge conformations, indicating that the exchange reaction is a non-specific process akin to encounter complex formation where the amino acid sequence plays a marginal role. The main role of the mutations in the swapping process is to destabilize the GB1 monomer state, while stabilizing the swapped dimer conformation, with non-native intersubunit interactions, fostered by mutant side chains, contributing significantly to this stabilization. Our findings are rationalized in terms of a generic swapping mechanism that involves the association of activated molecular species, and it is argued that a similar mechanism may apply to swapping in other protein systems.

Shift in nucleotide conformational equilibrium contributes to increased rate of catalysis of GpAp versus GpA in barnase.

The microbial ribonuclease barnase exhibits low catalytic activity toward GpN dinucleotides, where G is guanosine, p is phosphate and N represents any nucleoside. When a phosphate is added to the 3'-end, as in GpNp, substrate affinity is enhanced by one order of magnitude, and the catalytic rate by two. In order to gain insight into this phenomenon, we analyzed the nucleotide conformations and protein-nucleotide interactions of 4 ns molecular dynamics (MD) trajectories of complexes of barnase with guanylyl(3'-5') adenosine (GpA) and guanylyl(3'-5') adenosine 3'-monophosphate (GpAp), respectively, in the presence of solvent and counter ions. We found that, in a majority of the bound GpA conformations, the guanine base was firmly bound to the recognition site. The phosphate and adenosine moieties pointed into the solvent, and interactions with key catalytic residues were absent. In contrast, the bound GpAp adopted conformations in which all of the nucleotide portions remained tightly bound to the enzyme and interactions with key catalytic residues were maintained. These observations indicate that, for GpA, a significant proportion of the bound nucleotide adopts non-productive conformations and that adding the terminal phosphate as in GpAp shifts the equilibrium of the bound conformations towards structures capable of undergoing catalysis. Incorporating this property into the kinetic equations yields an increase in both the apparent rate constant (kcat) and the apparent dissociation constant (K(M)) for GpAp versus GpA. The increase in K(M), caused by the presence of additional non-productive binding modes for GpA, should however be counterbalanced by the propensity of free GpA to adopt folded conformations in solution, which are unable to bind the enzyme and by the tighter binding of GpAp (Giraldo J, Wodak SJ, Van Belle D. Conformational analysis of GpA and GpAp in aqueous solution by molecular dynamics and statistical methods. J Mol Biol 1998; 283:863-882). Addition of the terminal phosphate is shown to significantly influence the collective motion of the enzyme in a manner that fosters interactions with key catalytic residues, representing a further likely contribution to the catalytic rate enhancement.

Automatic sequence design of major histocompatibility complex class I binding peptides impairing CD8+ T cell recognition.

An automatic protein design procedure was used to compute amino acid sequences of peptides likely to bind the HLA-A2 major histocompatibility complex (MHC) class I allele. The only information used by the procedure are a structural template, a rotamer library, and a well established classical empirical force field. The calculations are performed on six different templates from x-ray structures of HLA-A0201-peptide complexes. Each template consists of the bound peptide backbone and the full atomic coordinates of the MHC protein. Sequences within 2 kcal/mol of the minimum energy sequence are computed for each template, and the sequences from all the templates are combined and ranked by their energies. The five lowest energy peptide sequences and five other low energy sequences re-ranked on the basis of their similarity to peptides known to bind the same MHC allele are chemically synthesized and tested for their ability to bind and form stable complexes with the HLA-A2 molecule. The most efficient binders are also tested for inhibition of the T cell receptor recognition of two known CD8(+) T effectors. Results show that all 10 peptides bind the expected MHC protein. The six strongest binders also form stable HLA-A2-peptide complexes, albeit to varying degrees, and three peptides display significant inhibition of CD8(+) T cell recognition. These results are rationalized in light of our knowledge of the three-dimensional structures of the HLA-A2-peptide and HLA-A2-peptide-T cell receptor complexes.

Pescador: the PEptides in Solution ConformAtion Database: Online Resource.

In recent years a large body of data has been obtained from Nuclear Magnetic Resonance and Circular Dichroism experiments on the influence of the amino acid sequence and various other parameters on the conformational state of peptides in solution. Interpreting the experimental data in terms of the conformational populations of the peptides remains a key problem, for which current solutions leave appreciable room for improvement. Considering that making this body of data available for surveys and analysis should be instrumental in tackling the problem, we undertook the development of Pescador: The 'PEptides in Solution ConformAtion Database: Online Resource'. Pescador contains data from NMR and CD spectroscopy on peptides in solution as well as information on the structural parameters derived from these data. It also features specialized Web-based tools for data deposition, and means for readily accessing the stored information for analysis purposes. To illustrate the use of the database in deriving information for the conformational analysis of peptides, we show how the alpha proton delta-values stored in Pescador and measured by NMR for different peptides in different laboratories can be used to derive a new set of 'random coil' chemical shift values. Firstly, we show these values to be very similar to those obtained experimentally for model peptides in water, and their variation with increasing Tri-Fluoro-Ethanol (TFE) concentration is similar to that reported for model peptides. We show, furthermore, that the chemical shift data in Pescador can be used to derive correction factors that take into account effects of neighboring residues. These correction factors compare favorably with those recently derived from a series of model GGXGG peptides (Schwarzinger et al., 2001). These encouraging results suggest that, as the quantity of NMR data on peptide deposited in Pescador increases, surveys of these data should be a valuable means of deriving key parameters for the analysis of peptide conformation.