SBILib: a handle for protein modeling and engineering.

SUMMARY: The SBILib Python library provides an integrated platform for the analysis of macromolecular structures and interactions. It combines simple 3D file parsing and workup methods with more advanced analytical tools. SBILib includes modules for macromolecular interactions, loops, super-secondary structures, and biological sequences, as well as wrappers for external tools with which to integrate their results and facilitate the comparative analysis of protein structures and their complexes. The library can handle macromolecular complexes formed by proteins and/or nucleic acid molecules (i.e. DNA and RNA). It is uniquely capable of parsing and calculating protein super-secondary structure and loop geometry. We have compiled a list of example scenarios which SBILib may be applied to and provided access to these within the library. AVAILABILITY AND IMPLEMENTATION: SBILib is made available on Github at https://github.com/structuralbioinformatics/SBILib.

The N-Terminal Phosphorylation of RB by p38 Bypasses Its Inactivation by CDKs and Prevents Proliferation in Cancer Cells.

Control of the G1/S phase transition by the Retinoblastoma (RB) tumor suppressor is critical for the proliferation of normal cells in tissues, and its inactivation is one of the most fundamental events leading to cancer. Cyclin-dependent kinase (CDK) phosphorylation inactivates RB to promote cell cycle-regulated gene expression. Here we show that, upon stress, the p38 stress-activated protein kinase (SAPK) maximizes cell survival by downregulating E2F gene expression through the targeting of RB. RB undergoes selective phosphorylation by p38 in its N terminus; these phosphorylations render RB insensitive to the inactivation by CDKs. p38 phosphorylation of RB increases its affinity toward the E2F transcription factor, represses gene expression, and delays cell-cycle progression. Remarkably, introduction of a RB phosphomimetic mutant in cancer cells reduces colony formation and decreases their proliferative and tumorigenic potential in mice.

SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions.

BACKGROUND: Statistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we decomposed the statistical potentials in different terms, named Split-Statistical Potentials, accounting for the type of amino acid pairs, their hydrophobicity, solvent accessibility and type of secondary structure. These potentials have been successfully used to identify near-native structures in protein structure prediction, rank protein docking poses, and predict PPI binding affinities. RESULTS: Here, we present the SPServer, a web server that applies the Split-Statistical Potentials to analyze protein folds and protein interfaces. SPServer provides global scores as well as residue/residue-pair profiles presented as score plots and maps. This level of detail allows users to: (1) identify potentially problematic regions on protein structures; (2) identify disrupting amino acid pairs in protein interfaces; and (3) compare and analyze the quality of tertiary and quaternary structural models. CONCLUSIONS: While there are many web servers that provide scoring functions to assess the quality of either protein folds or PPI structures, SPServer integrates both aspects in a unique easy-to-use web server. Moreover, the server permits to locally assess the quality of the structures and interfaces at a residue level and provides tools to compare the local assessment between structures. SERVER ADDRESS: https://sbi.upf.edu/spserver/ .

Transcription Factor NRF2 as a Therapeutic Target for Chronic Diseases: A Systems Medicine Approach.

Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases.

A Collection of Designed Peptides to Target SARS-CoV-2 Spike RBD-ACE2 Interaction.

The angiotensin-converting enzyme 2 (ACE2) is the receptor used by SARS-CoV and SARS-CoV-2 coronaviruses to attach to cells via the receptor-binding domain (RBD) of their viral spike protein. Since the start of the COVID-19 pandemic, several structures of protein complexes involving ACE2 and RBD as well as monoclonal antibodies and nanobodies have become available. We have leveraged the structural data to design peptides to target the interaction between the RBD of SARS-CoV-2 and ACE2 and SARS-CoV and ACE2, as contrasting exemplar, as well as the dimerization surface of ACE2 monomers. The peptides were modelled using our original method: PiPreD that uses native elements of the interaction between the targeted protein and cognate partner(s) that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations surrogating key interactions at the interface. To facilitate the access to this information we have created a freely available and dedicated web-based repository, PepI-Covid19 database, providing convenient access to this wealth of information to the scientific community with the view of maximizing its potential impact in the development of novel therapeutic and diagnostic agents.

Evaluation of Computationally Designed Peptides against TWEAK, a Cytokine of the Tumour Necrosis Factor Ligand Family.

The tumour necrosis factor-like weak inducer of apoptosis (TWEAK) is a member of the tumour necrosis factor ligand family and has been shown to be overexpressed in tumoral cells together with the fibroblast growth factor-inducible 14 (Fn14) receptor. TWEAK-Fn14 interaction triggers a set of intracellular pathways responsible for tumour cell invasion and migration, as well as proliferation and angiogenesis. Hence, modulation of the TWEAK-Fn14 interaction is an important therapeutic goal. The targeting of protein-protein interactions by external agents, e.g., drugs, remains a substantial challenge. Given their intrinsic features, as well as recent advances that improve their pharmacological profiles, peptides have arisen as promising agents in this regard. Here, we report, by in silico structural design validated by cell-based and in vitro assays, the discovery of four peptides able to target TWEAK. Our results show that, when added to TWEAK-dependent cellular cultures, peptides cause a down-regulation of genes that are part of TWEAK-Fn14 signalling pathway. The direct, physical interaction between the peptides and TWEAK was further elucidated in an in vitro assay which confirmed that the bioactivity shown in cell-based assays was due to the targeting of TWEAK. The results presented here are framed within early pre-clinical drug development and therefore these peptide hits represent a starting point for the development of novel therapeutic agents. Our approach exemplifies the powerful combination of in silico and experimental efforts to quickly identify peptides with desirable traits.

CACNA1A Mutations Causing Early Onset Ataxia: Profiling Clinical, Dysmorphic and Structural-Functional Findings.

The CACNA1A gene encodes the pore-forming α1A subunit of the voltage-gated CaV2.1 Ca2+ channel, essential in neurotransmission, especially in Purkinje cells. Mutations in CACNA1A result in great clinical heterogeneity with progressive symptoms, paroxysmal events or both. During infancy, clinical and neuroimaging findings may be unspecific, and no dysmorphic features have been reported. We present the clinical, radiological and evolutionary features of three patients with congenital ataxia, one of them carrying a new variant. We report the structural localization of variants and their expected functional consequences. There was an improvement in cerebellar syndrome over time despite a cerebellar atrophy progression, inconsistent response to acetazolamide and positive response to methylphenidate. The patients shared distinctive facial gestalt: oval face, prominent forehead, hypertelorism, downslanting palpebral fissures and narrow nasal bridge. The two α1A affected residues are fully conserved throughout evolution and among the whole human CaV channel family. They contribute to the channel pore and the voltage sensor segment. According to structural data analysis and available functional characterization, they are expected to exert gain- (F1394L) and loss-of-function (R1664Q/R1669Q) effect, respectively. Among the CACNA1A-related phenotypes, our results suggest that non-progressive congenital ataxia is associated with developmental delay and dysmorphic features, constituting a recognizable syndromic neurodevelopmental disorder.

CDK2-dependent activation of PARP-1 is required for hormonal gene regulation in breast cancer cells.

Eukaryotic gene regulation implies that transcription factors gain access to genomic information via poorly understood processes involving activation and targeting of kinases, histone-modifying enzymes, and chromatin remodelers to chromatin. Here we report that progestin gene regulation in breast cancer cells requires a rapid and transient increase in poly-(ADP)-ribose (PAR), accompanied by a dramatic decrease of cellular NAD that could have broad implications in cell physiology. This rapid increase in nuclear PARylation is mediated by activation of PAR polymerase PARP-1 as a result of phosphorylation by cyclin-dependent kinase CDK2. Hormone-dependent phosphorylation of PARP-1 by CDK2, within the catalytic domain, enhances its enzymatic capabilities. Activated PARP-1 contributes to the displacement of histone H1 and is essential for regulation of the majority of hormone-responsive genes and for the effect of progestins on cell cycle progression. Both global chromatin immunoprecipitation (ChIP) coupled with deep sequencing (ChIP-seq) and gene expression analysis show a strong overlap between PARP-1 and CDK2. Thus, progestin gene regulation involves a novel signaling pathway that connects CDK2-dependent activation of PARP-1 with histone H1 displacement. Given the multiplicity of PARP targets, this new pathway could be used for the pharmacological management of breast cancer.

On the mechanisms of protein interactions: predicting their affinity from unbound tertiary structures.

Motivation: The characterization of the protein-protein association mechanisms is crucial to understanding how biological processes occur. It has been previously shown that the early formation of non-specific encounters enhances the realization of the stereospecific (i.e. native) complex by reducing the dimensionality of the search process. The association rate for the formation of such complex plays a crucial role in the cell biology and depends on how the partners diffuse to be close to each other. Predicting the binding free energy of proteins provides new opportunities to modulate and control protein-protein interactions. However, existing methods require the 3D structure of the complex to predict its affinity, severely limiting their application to interactions with known structures. Results: We present a new approach that relies on the unbound protein structures and protein docking to predict protein-protein binding affinities. Through the study of the docking space (i.e. decoys), the method predicts the binding affinity of the query proteins when the actual structure of the complex itself is unknown. We tested our approach on a set of globular and soluble proteins of the newest affinity benchmark, obtaining accuracy values comparable to other state-of-art methods: a 0.4 correlation coefficient between the experimental and predicted values of ΔG and an error < 3 Kcal/mol. Availability and implementation: The binding affinity predictor is implemented and available at http://sbi.upf.edu/BADock and https://github.com/badocksbi/BADock. Contact: j.planas-iglesias@warwick.ac.uk or baldo.oliva@upf.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Deciphering the role of the signal- and Sty1 kinase-dependent phosphorylation of the stress-responsive transcription factor Atf1 on gene activation.

Adaptation to stress triggers the most dramatic shift in gene expression in fission yeast (Schizosaccharomyces pombe), and this response is driven by signaling via the MAPK Sty1. Upon activation, Sty1 accumulates in the nucleus and stimulates expression of hundreds of genes via the nuclear transcription factor Atf1, including expression of atf1 itself. However, the role of stress-induced, Sty1-mediated Atf1 phosphorylation in transcriptional activation is unclear. To this end, we expressed Atf1 phosphorylation mutants from a constitutive promoter to uncouple Atf1 activity from endogenous, stress-activated Atf1 expression. We found that cells expressing a nonphosphorylatable Atf1 variant are sensitive to oxidative stress because of impaired transcription of a subset of stress genes whose expression is also controlled by another transcription factor, Pap1. Furthermore, cells expressing a phospho-mimicking Atf1 mutant display enhanced stress resistance, and although expression of the Pap1-dependent genes still relied on stress induction, another subset of stress-responsive genes was constitutively expressed in these cells. We also observed that, in cells expressing the phospho-mimicking Atf1 mutant, the presence of Sty1 was completely dispensable, with all stress defects of Sty1-deficient cells being suppressed by expression of the Atf1 mutant. We further demonstrated that Sty1-mediated Atf1 phosphorylation does not stimulate binding of Atf1 to DNA but, rather, establishes a platform of interactions with the basal transcriptional machinery to facilitate transcription initiation. In summary, our results provide evidence that Atf1 phosphorylation by the MAPK Sty1 is required for oxidative stress responses in fission yeast cells by promoting transcription initiation.