The Fenlix Motor: A Validated Computational Pipeline for Kinase Inhibitor Selectivity Prediction — Four Disease Cases, One Geometric Principle
Fuente:
Zenodo
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Recurso digital |
| Publicado: |
Zenodo
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866901112875909120 |
|---|---|
| author | Pirolo, Andres |
| author_facet | Pirolo, Andres |
| contents | <p>Four diseases. Four candidates. One principle.</p> <p>The Fenlix Motor — a three-stage computational pipeline for kinase inhibitor selectivity prediction — has identified minimal structural modifications that produce consistent selectivity improvements across four independent disease targets: pancreatic cancer (KRAS G12D), Chagas disease (TcCLK1), antiarrhythmic toxicity reduction (DYRK1B), and autism spectrum disorder (DYRK1A/CDK5).</p> <p>The pattern that emerges is geometric: in three of four cases, a functional group at the meta (3) position of the distal aromatic ring reaches non-conserved hinge residues at the optimal distance (4.0–4.5 Å) for productive non-covalent interactions. The ortho position is sterically blocked. The para position reaches solvent. The meta position reaches the hinge.</p> <p>Four candidates identified: B02_3F (1.34×), E02_3NH2 (1.24×), A01_2Br (1.23×), B01_noEt (1.25×). Each differs from its reference compound by one atom or one functional group. Each prediction is crystallographically anchored in RCSB PDB structures.</p> <p>The complete pipeline runs on accessible mobile hardware at zero cost. No institutional infrastructure required.</p> <p>Academic use: unrestricted. Commercial use: written authorization required. Contact: apirolo@abc.gob.ar</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19267105 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Fenlix Motor: A Validated Computational Pipeline for Kinase Inhibitor Selectivity Prediction — Four Disease Cases, One Geometric Principle Pirolo, Andres Medicinal Chemistry Drug Discovery Computational Biology Bioinformatics Biochemistry Autism Spectrum Disorder Amiodarone Pancreatic Cancer <p>Four diseases. Four candidates. One principle.</p> <p>The Fenlix Motor — a three-stage computational pipeline for kinase inhibitor selectivity prediction — has identified minimal structural modifications that produce consistent selectivity improvements across four independent disease targets: pancreatic cancer (KRAS G12D), Chagas disease (TcCLK1), antiarrhythmic toxicity reduction (DYRK1B), and autism spectrum disorder (DYRK1A/CDK5).</p> <p>The pattern that emerges is geometric: in three of four cases, a functional group at the meta (3) position of the distal aromatic ring reaches non-conserved hinge residues at the optimal distance (4.0–4.5 Å) for productive non-covalent interactions. The ortho position is sterically blocked. The para position reaches solvent. The meta position reaches the hinge.</p> <p>Four candidates identified: B02_3F (1.34×), E02_3NH2 (1.24×), A01_2Br (1.23×), B01_noEt (1.25×). Each differs from its reference compound by one atom or one functional group. Each prediction is crystallographically anchored in RCSB PDB structures.</p> <p>The complete pipeline runs on accessible mobile hardware at zero cost. No institutional infrastructure required.</p> <p>Academic use: unrestricted. Commercial use: written authorization required. Contact: apirolo@abc.gob.ar</p> |
| title | The Fenlix Motor: A Validated Computational Pipeline for Kinase Inhibitor Selectivity Prediction — Four Disease Cases, One Geometric Principle |
| topic | Medicinal Chemistry Drug Discovery Computational Biology Bioinformatics Biochemistry Autism Spectrum Disorder Amiodarone Pancreatic Cancer |
| url | https://doi.org/10.5281/zenodo.19267105 |