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Velasquez, J.

Publications and source records attributed to Velasquez, J..

3 recordsLinked to original sources

BENDER: A Cross-taxon IDP Simulation Database Reveals Conserved Sequence-Ensemble Laws Across the Tree of Life

Intrinsically disordered proteins and regions are found across all kingdoms of life, yet the computational characterisation of their conformational ensembles has remained almost entirely confined to the human proteome. Whether the force fields used to generate them remain accurate for taxonomically distant organisms, and whether the sequence ensemble relationships they reveal transfer across taxa well enough to improve prediction on phylogenetically held-out organisms, are open questions. Here we introduce BENDER, a dataset of 11,533 IDP sequences spanning 13 taxonomic groups, each simulated under CALVADOS 2 molecular dynamics and annotated with ensemble-level geometric and novel contact-network properties, together with per-sequence pi pi and cation pi contact frequencies linked to phase-separation propensity. We show that CALVADOS 2 ensembles agree strongly with an orthogonal structural reference across the full dataset,with both held out taxa performing above the dataset median, and that direct comparison against a second independently parameterized force field reveals no systematic scaling-exponent bias. We find that cross taxon training data improves out-of-distribution ensemble prediction in two independent architectures despite training on one third the data. Positive degree assortativity is conserved across all taxonomic groups, suggesting that hub topology in disordered protein contact networks is a conserved physical feature of sequence-encoded disorder rather than an evolutionary contingency

biophysics↗

Do AI Structure Predictors Capture Bound-State Disorder? A Benchmark on Fuzzy Protein Complexes

Fuzzy protein complexes, in which an intrinsically disordered protein (IDP) retains conformational disorder upon binding, pose a fundamental challenge for structure predictors trained on ordered systems, where crystal structures capture only the most ordered ensemble snapshot, making standard benchmarking metrics misleading. Here, we present the first systematic evaluation of AlphaFold3 (AF3), AlphaFold2-Multimer (AF2MM), Chai-1, and Boltz-2 on a curated dataset of fuzzy complexes from FuzDB, benchmarked against DockQ against PDB structures and NOE violation rates against manually curated BMRB restraint files, the first comprehensive collection of this kind. Across all four predictors, approximately 30% of NOE restraints were violated with nearly identical distributions regardless of predictor architecture or training data. DockQ scores fell uniformly within the Acceptable range, with AF3 marginally higher but exhibiting NOE violation rates equivalent to the weakest-performing model. Ensemble-level analysis using a first-principles implementation of the Hadzi thermodynamic model revealed that AF3 uniquely achieves near-zero mean helicity bias, in contrast to systematic overconfidence in the other predictors, yet all four models show poor per-residue helicity correlation with thermodynamic expectations. DockQ rankings reflect training data similarity to crystal structures rather than physical accuracy, and no current predictor captures fuzzy complex ensemble behavior. The FuzzyBench-NOE dataset, comprising NOE restraint files, predicted structures, interface hotspot annotations, and Hadzi-DSSP analysis outputs, is released on Zenodo (https://doi.org/10.5281/zenodo.20470556). Significance StatementNo benchmark exists for fuzzy protein complexes, where IDPs retain disorder upon binding. We show that four state-of-the-art structure predictors violate 30% of experimental NMR distance restraints invariantly regardless of architecture, while DockQ, the standard metric, is entirely uncorrelated with this failure. Ensemble-level analysis using the Ha[d]zi thermodynamic model reveals systematic helicity overconfidence across all predictors. Taken together, our findings imply that standard geometric metrics are fundamentally misleading for disordered systems, thus necessitating ensemble-aware evaluation.

biophysics↗

HO-3867 mediated modulation of Extracellular vesicles and Tumor microenvironment: A novel immunotherapeutic strategy for ovarian cancer

IntroductionOvarian cancer (OC) remains the most lethal gynecologic malignancy, with poor long-term survival, largely due to its diagnosis at advanced stages and its high rate of recurrence with resistance to platinum therapies. This study evaluates the therapeutic efficacy of HO-3867, a STAT3 inhibitor, and bevacizumab, an anti-VEGF antibody, alone and in combination in an immunocompetent (IC) syngeneic ovarian cancer progression model. MethodsThe ability of HO-3867 to induce macrophage polarization was assessed in RAW264.7 cells, while its impact on anti-tumor immunity was evaluated in splenocytes co-cultured with ID8 and OC ascites cells. Immune modulation, including cytokine induction, extracellular vesicle (EV) release, and endosomal sorting complex required for transport (ESCRT) protein expression, was analyzed in-vitro and using in-vivo OC model. The therapeutic effects of HO-3867 and bevacizumab were examined in vivo by measuring ascites volume, EV secretion levels, and immune cell populations via flow cytometry. ResultsOur results demonstrate that combination therapy significantly reduced ascites accumulation, and limited peritoneal disease spread in ovarian cancer mouse models. EV analysis revealed a decrease in total EVs and CD9+ subpopulations, which correlated with the associated ESCRT proteins involved in EV formation and secretion implicating EVs in tumor progression and immune modulation. Flow cytometry analysis of ascites immune cell populations showed that combination therapy reduced myeloid-derived suppressor cells (MDSCs) and their PD-L1 expression, while enhancing CD8+ T cell cytotoxicity via granzyme B secretion. Cytokine profiling revealed upregulation of IFN-{gamma} and downregulation of IL-6, IL-10 and CXCL-2 suggesting enhanced anti-tumor immune response. Furthermore, HO-3867 promoted macrophage polarization toward tumoricidal M1 phenotype and reduced MDSC expansion in-vitro, enhancing anti-tumor immunity. ConclusionHO-3867 and bevacizumab synergistically reprogram the tumor microenvironment, inhibit EV-mediated progression, and enhance antitumor immunity. These findings support its immunomodulatory potential in ovarian cancer ascites, offering a promising therapeutic strategy.

cancer biology↗