Biology subjects

Ocana, A.

Publications and source records attributed to Ocana, A..

14 recordsLinked to original sources

bioRxiv2026

PepSpace: An Automated, Physics-Driven Directed Evolution Platform for the De Novo Design of Specific Peptide Binders and Condensate Modulators

Intrinsically disordered proteins, topologically complex protein surfaces, and biomolecular condensates regulate essential cellular processes but remain difficult to drug with conventional small molecules. Here, we present PepSpace, a physics-driven directed-evolution platform coupling residue-resolution coarse-grained molecular dynamics with a multi-objective genetic algorithm. PepSpace designs peptide binders by rewarding target engagement while penalizing peptide self-association and off-target binding. Evaluated alongside deep-learning generative models across multiple targets, PepSpace-designed peptides achieve predicted interaction strengths up to two orders of magnitude greater than machine-learning designs, while reproducing experimentally observed binding hierarchies and revealing distinct binding modes. For PIEZO1, PepSpace designs 25-mer peptides that preferentially engage a defined 30-residue intracellular beam epitope while suppressing interactions with the remainder 2,547-residues of the protein. For CHERP biomolecular condensates, dual-action peptides weaken native intermolecular contacts and destabilize the condensed phase. PepSpace provides a physically grounded framework for de novo peptide design against dynamic protein targets and biomolecular condensates, with explicit control over specificity, solubility, and collective interactions.

biophysics↗

bioRxiv2026

Size Control of hnRNPK-based Nucleolar Condensates by RNA-Regulated Fusion Dynamics

Nucleoli are liquid-like condensates whose size is actively conserved--they remain small, numerous, and resistant to coalescence--yet the molecular mechanisms that constrain their fusion remain poorly understood. Heterogeneous nuclear ribonucleoprotein K (hnRNPK), an RNA-binding protein implicated in nucleolar organization and cancer, interacts directly with the scaffold protein Nucleolin. Combining residue-resolution coarse-grained simulations with biochemical experiments, we find that hnRNPK and Nucleolin condense through distinct interaction networks--a localized cation-{pi}/electrostatic hotspot in hnRNPK versus broadly distributed electrostatic contacts in Nucleolin, reorganized upon co-assembly. To probe how RNAs reshape these condensates, we develop and validate, against re-entrant phase-separation experiments and AlphaLISA binding data, a nucleotide-resolution coarse-grained model for single-stranded RNA. Using this framework, we show that RNA is asymmetrically and preferentially recruited by hnRNPK over Nucleolin, an asymmetry that grows stronger when the two proteins compete for the same RNAs. This selective recruitment sustains a dynamic fission-fusion equilibrium: hnRNPK-containing condensates repeatedly fuse and split rather than coalescing into a single condensate, whereas Nucleolin-containing and ternary condensates fuse into one dominant cluster. These results reveal a molecular mechanism, grounded in sequence-encoded, RNA-controlled fusion dynamics, by which nucleolar condensates conserve a controlled, non-coalescing size despite their liquid-like character.

biophysics↗

bioRxiv2026

Prognostic stratification by LGR5 expression identifies surface-accessible, structurally ligandable and condensate-forming targets in colorectal cancer

Background: LGR5 marks colorectal cancer stem cells and is associated with poor outcome, but its expression on normal intestinal stem cells has constrained direct therapeutic targeting, and the molecular landscape of LGR5-high tumors remains incompletely defined. A transcriptional signature is not itself a set of drug targets: its constituent genes differ in whether and how they can be engaged pharmacologically, a distinction rarely applied systematically to a tumor-defined gene set. Methods: We stratified 396 colorectal tumors from The Cancer Genome Atlas by LGR5 expression and compared transcriptional, somatic mutation, and copy number profiles between LGR5-high and LGR5-low groups using non-parametric testing with combined significance and effect-size thresholds. Genome-wide CRISPR knockout data were interrogated to test genetic dependency. Each signature gene was then triaged by pharmacological tractability rather than essentiality, along three axes: surface accessibility, from surfaceome annotation and membrane topology; cavity ligandability, from pocket detection on predicted structures using three independent algorithms; and condensate propensity, from saturation concentration prediction and coarse-grained molecular dynamics simulation. Results: LGR5-high tumors displayed a coordinated program spanning Wnt signaling, stemness, and matrix remodeling, arising on an APC-mutant background with co-occurring IGF2 amplification. No constituent gene scored as a selective dependency. The three axes partitioned the signature with minimal overlap and nominated three candidates engaged by orthogonal modalities: ENPP3, a single-pass ectoenzyme presenting an accessible ectodomain and carrying clinical antibody-drug conjugate precedent; PLCB4, combining a well-defined catalytic pocket with additional predicted ligandable sites; and NKD1, accessible by neither route but undergoing RNA-stabilized homotypic phase separation, unlike SATB1 and MEX3A. Simulations further indicated that NKD1 partitions into DVL2-containing condensates and reduces DVL2-Wnt contacts, suggesting a biophysical basis for its negative-feedback role. Conclusions: LGR5 expression defines a colorectal cancer subset that is pharmacologically tractable despite the absence of genetic dependency. Triaging by modality rather than essentiality converts descriptive tumor signatures into stratified, experimentally testable therapeutic hypotheses, including condensate-directed modulation of NKD1 as a route to targets inaccessible by antibody- or pocket-based approaches.

molecular biology↗

bioRxiv2026

Charge-Driven Fibril Recognition and Covalent Disruption of Aβ42 byPaddlewheel Diruthenium Complexes

The inhibition of A{beta}42 ({beta}-amyloid) fibril formation is a key therapeutic strategy in Alzheimers disease research. Paddlewheel diruthenium complexes have shown promising activity against A{beta}42 aggregation and preformed fibril disaggregation, yet their molecular mode of action remains poorly understood. In this work, we perform atomistic simulations to explore how charge modulation influences the interactions of three analogous paddlewheel diruthenium complexes, the parent neutral complex [Ru2Cl(D-p-FPhF)(O2CCH3)3], and its anionic [Ru2Cl2(D-p-FPhF)(O2CCH3)3]- and cationic [Ru2(D-p-FPhF)(O2CCH3)3]+ counterparts (D-p-FPhF- is the N,N -bis(4-fluorophenyl)formamidinato ligand) with A{beta}42. Our results indicate that electrostatic tuning governs binding affinity and the extent of interaction across the A{beta}42 fibril surface. As the complexes charge changes from -1 to +1, the interaction pattern shifts from localized contacts to widespread, multi-site engagement encompassing key charged, aromatic, and hydrophobic regions of A{beta}42. This enhanced binding correlates with longer-lived, thermodynamically stable interactions at the fibril interface, which effectively lower the free energy penalty for fibril disassembly. Overall, our findings propose a mechanism in which charge-dependent activation through ligand exchange enhances fibril recognition and promotes disruptive binding modes, demonstrating the potential of charge-tunable diruthenium complexes as therapeutic modulators of A{beta}42 fibril stability.

biophysics↗

bioRxiv2026

RNA synthesis and degradation regulate biomolecular condensates through non-equilibrium feedback

Transcriptional condensates operate far from equilibrium, where continuous RNA synthesis and degradation dynamically reshape condensate composition. To investigate how RNA synthesis regulates condensate properties at sub-molecular resolution, we introduce REACT-RNA, a chemically specific coarse-grained molecular dynamics framework that explicitly couples RNA polymerisation, degradation, and nucleotide fluxes to sequence-dependent protein-RNA phase behaviour. Using FUS and MED1 as model systems, we show that RNA growth remodels condensate phase behaviour by altering RNA length distributions and intermolecular connectivity. Sustained RNA polymerisation drives re-entrant condensate dissolution, even of aged gel-like condensates, whereas RNA degradation stabilises long-lived non-equilibrium condensates containing excess RNA and negative charge beyond that tolerated at equilibrium. Our results suggest that RNA synthesis, degradation, and nucleotide fluxes drive transcriptional condensates out of thermodynamic equilibrium while condensates in turn promote reactive molecular configurations that favour RNA production, enabling transient accumulation of excess RNA and negative charge beyond equilibrium electroneutrality constraints during bursts of transcription.

biophysics↗

bioRxiv2026

RNA2PS: A sequence-specific coarse-grained RNA model linking structure, thermodynamics and phase separation

RNA plays a central role in the formation and regulation of biomolecular condensates, yet a quantitative understanding of how RNA sequence, structure, and thermodynamics jointly determine phase behaviour, particularly in repeat expansion RNAs, remains incomplete. Here, we introduce RNA2PS, a sequence-specific RNA coarse-grained model for phase-separation that predicts RNA structure from sequence, achieving quantitative agreement for both single-stranded conformations and duplex helical geometry relative to crystallographic PDB structures. RNA2PS represents each nucleotide by two beads that separate the phosphate-ribose backbone from the base. This representation decouples electrostatic interactions from directional base pairing, while explicitly incorporating strand polarity (5' [->] 3') and local sequence context at the trimer level. Canonical and wobble base pairing are modelled through a multi-body potential with sequence-dependent coordination. Importantly, RNA2PS captures sequence-dependent duplex stability at the nearest-neighbour level and reproduces experimental melting temperatures across a diverse set of sequences. RNA2PS shows that phase separation of trinucleotide repeat RNAs is governed by transient inter-strand duplexes that form reversible cross-links. Competition between intra- and intermolecular base pairing regulates the density of labile RNA-RNA interactions, giving rise to strong sequence- and length-dependent differences in condensation that reproduce cellular RNA foci formation. Overall, RNA2PS provides a near-quantitative predictive framework that links sequence-encoded hybridization thermodynamics to mesoscale condensation of pure RNA sequences.

biophysics↗

bioRxiv2026

Computational mapping of antibody-receptor energy landscapes to predict membrane internalization

Antibody internalization is critical for the action of antibody-drug conjugates, yet antibody discovery pipelines typically prioritize binding affinity rather than functional internalization. Here we show that molecular dynamics simulations can map the binding energy landscape between antibody clones and the membrane protein JAM-A, enabling computational predictions of antibody internalization. Using the sequences of newly generated anti-JAM-A monoclonal antibodies (mAbs), we perform atomistic potential-of-mean force simulations to evaluate the binding free energy to the JAM-A receptor and their interaction fingerprint at residue-level resolution. We find that internalizing mAb derived from different hybridomas exhibit a unique membrane-oriented contact topology that promotes cooperative receptor-receptor interactions, lowering the energetic barrier for early endocytic events. Reconstruction of the receptor binding energy landscape further reveals that electrostatic interactions between charged residues and multivalent cation-{pi} and polar interactions correlate with successful mAb internalization in ovarian cancer cells. In contrast, strong binding affinity of the fragment antigen-binding domain correlates with poor internalization. Together, our results establish molecular dynamics-guided clonal selection as a predictive framework for optimizing internalizing therapeutic antibodies and provide mechanistic insight into how antibody binding reshapes membrane-proximal receptor energetics to drive endocytosis.

biophysics↗

bioRxiv2026

Interplay between Local Diffusion, Concentration, and Inter-Protein Alignment Promotes Cross-β-Sheet Transitions at Condensate Interfaces

The interface separating a biomolecular condensate from its surroundings is increasingly recognised as a unique physical and chemical environment that actively regulates condensate behaviour. It controls surface tension, molecular organisation and chemical reactivity, and is also where pathological ageing often begins, with several proteins nucleating cross-{beta}-sheet fibrils preferentially at condensate surfaces. But does ageing emerge there because of protein-specific chemistry, or a more general physical mechanism? Using coarse-grained molecular dynamics simulations, we show that cross-{beta}-sheet nucleation generically occurs preferentially at condensate interfaces across systems of increasing chemical complexity, from simple homopolymers to patterned amphiphilic sequences. In all systems studied, interface-driven ageing has a common physical origin and can be further modulated, but not driven, by protein sequence. Specifically, terminal domains at the condensate interface gain mobility while remaining densely packed and mutually aligned, creating favourable conditions for {beta}-sheet nucleation. Ageing is amplified in amphiphilic sequences, where hydrophilic regions act as surfactants facing the dilute phase, while aggregation-prone hydrophobic domains cluster just beneath the surface, concentrating the nucleation there. This surfactant-like organisation lowers the interfacial free energy, which falls systematically as sequence asymmetry grows. By linking molecular interactions to mesoscale behaviour, these results cast the interface as a central regulator of ageing and reveal a sequence-independent physical mechanism for the liquid-to-solid transition underlying pathological aggregation in biomolecular condensates.

biophysics↗

bioRxiv2026

Condensate-Driven Transcriptional Reprogramming Defines Core Vulnerabilities in Esophageal and Gastric Cancers

Biomolecular condensates organize key nuclear functions by compartmentalizing biomolecules, yet their contribution to gastrointestinal tumorigenesis remains poorly defined. Integrating multi-omics profiling, functional genomics, and molecular dynamics simulations, we reveal that esophageal and gastric cancers share a condensate-enriched transcriptional program driven by intrinsically disordered proteins involved in transcription, RNA processing, and replication stress. Transcriptomic analyses identify a hyperactive transcriptional state with upregulation of condensate-associated genes, including TOPBP1 and CHERP. Dependency mapping demonstrates that these proteins are essential for tumor cell viability, defining a conserved condensate core across different tumor types. Machine-learned predictions and residue-resolution coarse-grained simulations confirm that TOPBP1 and CHERP undergo phase separation through homotypic interactions mediated by intrinsically disordered regions, with saturation concentrations below 2 {micro}M, consistent with spontaneous condensate formation observed in vitro. Together, these findings establish condensate organization as a fundamental mesoscale principle in upper gastrointestinal cancers and nominate condensate scaffolds as tractable therapeutic vulnerabilities.

bioinformatics↗

bioRxiv2025

Benchmarking Free Energy Computational Methods for Revealing the Interactions Driving PARP1 Selective Inhibition

Accurate prediction of inhibitor selectivity across protein paralogues remains a central challenge in computational drug discovery. Here, we systematically benchmark three computational methods--Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA), free energy perturbation (FEP) and potential of mean force (PMF) calculations--in their ability to recapitulate PARP1 versus PARP2 selectivity for eight clinically relevant PARP enzyme inhibitors used in ovarian, breast and prostate tumors among others. We demonstrate how MM/PBSA calculations offer rapid and qualitative insights, but show pronounced sensitivity to the chosen static conformational pose, being particularly challenging for ligands with subtle energetic differences between distinct protein paralogues. In contrast, both FEP and PMF calculations using atomistic models with explicit solvent result in substantially improved agreement with experimental binding affinities. The FEP method exhibits the strongest quantitative correlation with experimental binding free energy differences, remarkably reproducing selectivity trends even among nearly isoenergetic complexes. Notably, our structural contact analysis reveals how contact connectivity controls ligand selectivity, providing valuable mechanistic and molecular insight into the key residues that stabilize each inhibitor in both protein enzymes. Together, our multi-method computational study contributes to elucidate potential chemical modifications across the ligand chemical space to enhance potency and specificity, informing the future design and evaluation of selective inhibitors for precision oncology, including therapies targeting homologous recombination-deficient cancers.

bioinformatics↗

bioRxiv2025

Active Liposomal Targeting for Head and Neck Squamous Cell Carcinoma Treatment

Head and neck squamous cell carcinoma (HNSCC) is a major oncological challenge due to its high recurrence rates, biological heterogeneity, and poor long-term survival outcomes. Despite advances in surgery and radiotherapy, chemotherapeutic options are limited. Cisplatin (CDDP) remains the mainstay, while small molecule inhibitors, such as the selective PI3K inhibitor Alpelisib, are still under clinical evaluation. However, systemic side effects and suboptimal tumor specificity hamper the clinical utility of both standard and novel specific therapies. In this study, we developed passive- and active-targeting liposomes encapsulating Cisplatin (CDDP) and Alpelisib. To achieve active targeting, the anti-epidermal growth factor receptor (EGFR) antibody Cetuximab was conjugated to the liposome surface. All formulations were characterized based on size, morphology, encapsulation efficiency, and drug release profiles. In vitro assays demonstrated that liposomal encapsulation preserved the cytotoxic effects of both CDDP and Alpelisib in HNSCC cell lines, with CDDP showing adequate encapsulation efficiency for in vivo evaluation. In vivo near-infrared fluorescence imaging demonstrated that active-targeting liposomes achieved greater tumor accumulation and a better tumor-to-spleen ratio compared to passive formulations. Tumor growth by CDDP-loaded activetargeting liposomes was comparable to that of the free drug, likely due to the hydrophilic nature and rapid release of CDDP from liposomes in physiological conditions. Importantly, blood chemistry analysis indicated a favorable toxicity profile for the targeted liposomal formulation. These findings highlight the potential of liposome-based targeted strategies to improve therapeutic outcomes in HNSCC and underscore the value of nanotechnology in the development of next-generation oncological therapies.

cancer biology↗

bioRxiv2025

Decoding PARP1 Selectivity: Atomistic Insights for Next-Generation Cancer Inhibitors

Selective inhibition of PARP1 represents a promising strategy to improve the therapeutic index of PARP inhibitors, a class of anticancer agents that exploit defects in DNA repair pathways. While PARP inhibitors have shown remarkable clinical benefit, particularly in BRCA-mutated tumors, the lack of discrimination between PARP1 and its close homolog PARP2, often leads to hematological toxicity and limits treatment efficacy. Thus, achieving molecular selectivity for PARP1 remains a central challenge in the rational design of safer and more potent inhibitors. To explore the molecular determinants of ligand selectivity, we focus on four clinically relevant PARP inhibitors--two PARP1-selective (saruparib and NMS-P118) and two non-selective (veliparib and olaparib) inhibitors--and perform atomistic potential-of-mean-force calculations of the PARP1 catalytic binding domain in the presence of these molecules. Our simulations near-quantitatively capture the experimental relative binding preferences, demonstrating that our approach reliably reflects selectivity patterns. Based on these findings, we analyze protein-ligand contact frequencies to identify the stabilizing interaction network and contact connectivity inducing protein selectivity. The most frequent protein-inhibitor contacts are primarily mediated by tyrosine triads and electrostatic interactions, showing a cooperative complex network of intermolecular contacts which strongly relies on protein multivalency. To dissect the decisive role of individual residues across the binding site, we also perform targeted mutagenesis of the PARP1 catalytic pocket in complex with saruparib, replacing several active-site amino acids by glycines. Progressively increasing the number of mutations markedly reduces binding stability, with distinct residue combinations exerting two primary effects: destabilization of the final bound state and the emergence of energetic barriers along the ligand association pathway. Together, our results provide a coherent mechanistic framework for understanding PARP1 selectivity and informs the rational design of next-generation inhibitors with improved efficacy and safety.

molecular biology↗

bioRxiv2021

TRIB1 regulates tumour growth via controlling tumour-associated macrophage phenotypes and is associated with breast cancer survival and treatment response

Molecular mechanisms that regulate tumour-associated macrophage (TAM) phenotype and function are incompletely understood. Here, we show that the pseudokinase TRIB1 is highly expressed by TAMs in breast cancer and that its expression correlates with response to chemotherapy and patient survival. We used immune-competent murine models of breast cancer to characterise the consequences of altered (reduced or elevated) myeloid Trib1 expression on tumour growth and composition of stromal immune cells. We found that both overexpression and knockout of myeloid Trib1 promote tumour growth, albeit through distinct molecular mechanisms. Myeloid Trib1 deficiency resulted in an early accelearation of tumour growth, paired with a selective reduction in perivascular macrophage numbers in vivo and enhanced oncogenic cytokine expression in vitro. In contrast, elevated levels of Trib1 in myeloid cells led to an increase in mammary tumour volume at late stages, together with a reduction of NOS2 expressing macrophages and an overall reduction of these cells in hypoxic tumour regions. In addition, we show that myeloid Trib1 is a previously unknown, negative regulator of the anti-tumour cytokine IL-15 and that increased expression of myeloid Trib1 leads to reduced IL-15 levels in mammary tumours, with a consequent reduction in the number of T-cells, that are key to anti-tumour immune responses. Together, these results define the different roles of TRIB1 in human breast cancer and provide a mechanistic understanding for the importance of myeloid TRIB1 expression levels in the development of this disease. SignificanceTRIB1 expression is strongly associated with response to chemotherapy in breast cancer patients with aggressive tumours. This protein is also highly expressed by tumour-associated macrophages. Thus, we used myeloid-specific alterations of Trib1 expression in mice (Trib1mKO and Trib1mTg), and characterised consequent changes in the growth rate and tumour microenvironment of mammary tumours. Both Trib1mKO and Trib1mTg enhanced tumour growth, but at different stages of tumour growth and via distinct mechanisms. Trib1mKO significantly increased the expression of oncogenic cytokines, such as IL6, IL10, CCL20, PD-L1, and VEGF. In contrast, Trib1mTg accelerated at the later stage of tumour growth via inhibition of hypoxic TAMs in the TME, as well as by reduced IL-15 expression thus leading to impaired naive and cytotoxic T cell infiltration. These data define TRIB1 as a potential novel marker of therapeutic responses in breast cancer, as well as a key mechanistic regulator of the anti-tumour cytokine, IL-15 in myeloid cells.

cancer biology↗

bioRxiv2018

Epigenetic mutational landscape in breast cancer: role of the histone methyltransferase gene KMT2D in triple negative tumors

PurposeEpigenetic regulating proteins like histone methyltransferases produce variations in several functions, some of them associated with the generation of oncogenic processes. Mutations of genes involved in these functions have been recently associated with cancer, and strategies to modulate their activity are currently in clinical development.\n\nMethodsBy using data extracted from the METABRIC study, we searched for mutated genes linked with detrimental outcome in invasive breast carcinoma (n = 772). Then, we used downstream signatures for each mutated gene to associate that signature with clinical prognosis using the online tool \"Genotype-2-Outcome\" (http://www.g-2-o.com). Next, we performed functional annotation analyses to classify genes by functions, and focused on those associated with the epigenetic machinery.\n\nResultsWe identified KMT2D, SETD1A and SETD2, included in the lysine methyltransferase activity function, as linked with poor prognosis in invasive breast cancer. KMT2D, which codes for a histone methyltransferase that acts as a transcriptional regulator, was mutated in 6% of triple negative breast tumors and found to be linked to poor survival. Genes regulated by KMT2D included RAC3, KRT23, or KRT14, among others, which are involved in cell communication and signal transduction. Finally, low expression of KMT2D at the transcriptomic level, which mirror what happens when KMT2D is mutated and functionally inactive, confirmed its prognostic value.\n\nConclusionIn the present work, we describe epigenetic modulating genes which are found to be mutated in breast cancer. We identify the histone methyltransferase KMT2D, which is mutated in 6% of triple negative tumors and linked with poor survival.

cancer biology↗