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Paniagua-Herranz, L.

Publications and source records attributed to Paniagua-Herranz, L..

3 recordsLinked to original sources

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↗

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↗

Purinergic Receptor P2Y13 Controls Activation and Mode of Division in Subependymal Adult Neural Stem Cells

The subependymal zone (SEZ) of the mammalian brain is the most active germinal area that continues to generate newborn neurons throughout life. This area harbors a population of neural stem cells (NSCs) that can be found in different states of activation, each differing in proliferative capacity and molecular signature: quiescent NSCs (qNSCs), primed NSCs (pNSCs), and activated NSCs (aNSCs). There is currently a void in terms of the specific markers available to effectively discern between these transient states. Likewise, the molecular signaling mechanisms controlling the transition from quiescence to activation remain largely unexplored, as do the factors influencing the decision between differentiation and self-renewal during NSC division. Here, we present evidence that the metabotropic P2Y13 purinergic receptor plays a critical role in regulating adult neurogenesis. We found that P2Y13 is specifically expressed in NSCs within the adult SEZ and that its levels can be used to distinguish qNSCs from aNSCs. Functionally, P2Y13 signaling promotes NSC activation, enhancing lineage progression, while dampening their self-renewal capacity. Conversely, pharmacological blockade or genetic silencing of the P2Y13 receptor favors NSC quiescence. Thus, we identified the metabotropic P2Y13 purinergic receptor as a pivotal modulator of NSC dynamics, influencing both the balance between NSC quiescence and activation and the mode of NSC division at the subependymal zone.

neuroscience↗