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Nieto-Jimenez, C.

Publications and source records attributed to Nieto-Jimenez, C..

2 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↗

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↗