{"id":98668,"date":"2024-09-26T15:58:31","date_gmt":"2024-09-26T13:58:31","guid":{"rendered":"https:\/\/www.pcb.ub.edu\/una-nueva-herramienta-computacional-identifica-mas-de-32-000-puntos-de-interes-farmacologico-el-proteoma-humano\/"},"modified":"2024-09-30T16:57:35","modified_gmt":"2024-09-30T14:57:35","slug":"una-nueva-herramienta-computacional-identifica-mas-de-32-000-puntos-de-interes-farmacologico-el-proteoma-humano","status":"publish","type":"post","link":"https:\/\/www.pcb.ub.edu\/es\/una-nueva-herramienta-computacional-identifica-mas-de-32-000-puntos-de-interes-farmacologico-el-proteoma-humano\/","title":{"rendered":"Una nueva herramienta computacional identifica m\u00e1s de 32.000 puntos de inter\u00e9s farmacol\u00f3gico el proteoma humano"},"content":{"rendered":"

Cient\u00edficos del IRB Barcelona<\/a>, con sede en el Parque Cient\u00edfico de Barcelona, han desarrollado PocketVec, una metodolog\u00eda innovadora para detectar y caracterizar sitios farmacol\u00f3gicamente aprovechables en prote\u00ednas humanas. Al mapear m\u00e1s de 32.000 sitios de uni\u00f3n en 20.000 dominios proteicos, este trabajo -publicado en Nature Communications- ofrece una visi\u00f3n integral que va m\u00e1s all\u00e1 de la simple secuencia gen\u00e9tica para centrarse en las interacciones moleculares, lo que constituye un recurso sin precedentes para la comunidad cient\u00edfica y\u00a0abre la puerta a nuevas oportunidades en descubrimiento de f\u00e1rmacos.<\/strong><\/p>\n

La identificaci\u00f3n de sitios farmacol\u00f3gicamente accionables ha sido un desaf\u00edo durante mucho tiempo en la investigaci\u00f3n biom\u00e9dica. Tradicionalmente, la caracterizaci\u00f3n de estos sitios ha dependido de t\u00e9cnicas experimentales costosas y lentas, como la cristalograf\u00eda de rayos X o la Resonancia Magn\u00e9tica Nuclear (RMN).<\/p>\n

Cient\u00edficos liderados por el\u00a0Dr. Patrick Aloy<\/strong>, investigador ICREA del IRB Barcelona han desarrollado una herramienta computacional, denominada PocketVec, que facilita la identificaci\u00f3n y caracterizaci\u00f3n de sitios de uni\u00f3n en prote\u00ednas humanas. Estos sitios, conocidos como \u00abbolsillos farmacol\u00f3gicamente aprovechables\u00bb, son \u00e1reas clave en las prote\u00ednas donde peque\u00f1as mol\u00e9culas pueden unirse y modular su funci\u00f3n, lo que es crucial en el dise\u00f1o de nuevos f\u00e1rmacos. El estudio ha sido publicado en la revista\u00a0Nature Communications<\/em>\u00a0y representa un avance significativo en la bioinform\u00e1tica aplicada al descubrimiento de f\u00e1rmacos.<\/p>\n

PocketVec emplea un enfoque innovador basado en el \u00abcribado virtual inverso\u00bb de mol\u00e9culas peque\u00f1as, para generar descriptores vectoriales de los sitios de uni\u00f3n de prote\u00ednas, facilitando comparaciones y an\u00e1lisis a gran escala. Estos descriptores permiten identificar similitudes entre bolsillos que no se pueden detectar mediante comparaciones basadas \u00fanicamente en la secuencia o la estructura, abriendo nuevas oportunidades para el descubrimiento de f\u00e1rmacos. Adem\u00e1s, al utilizar tanto estructuras proteicas experimentales como modelos predictivos generados por la herramienta AlphaFold2, los investigadores han sido capaces de identificar bolsillos en prote\u00ednas que previamente no hab\u00edan sido analizadas.<\/p>\n

\"\"<\/p>\n

\u00abEste supera algunas de las limitaciones m\u00e1s importantes de las herramientas existentes, permiti\u00e9ndonos analizar m\u00e1s de 32.000 sitios de uni\u00f3n en el proteoma humano. Adem\u00e1s, los descriptores generados podr\u00edan ser clave para entrenar modelos de machine learning, lo que abrir\u00eda nuevas oportunidades para el descubrimiento de f\u00e1rmacos\u00bb, explica el\u00a0Dr. Aloy<\/strong>, jefe del\u00a0laboratorio de Bioinform\u00e1tica Estructural y Biolog\u00eda de Redes<\/a>\u00a0del IRB Barcelona.<\/p>\n

\u00abNuestro enfoque podr\u00eda cambiar la forma en que priorizamos los objetivos para el desarrollo de nuevos f\u00e1rmacos, ya que expande significativamente el espacio farmacol\u00f3gico humano, revelando bolsillos de prote\u00ednas previamente no considerados como aprovechables desde el punto de vista farmacol\u00f3gico\u00bb, explica Arnau Comajuncosa-Creus<\/strong>, primer autor del estudio y estudiante de doctorado en el mismo laboratorio.<\/p>\n

La herramienta es de acceso abierto y est\u00e1 accesible en este enlace: https:\/\/gitlabsbnb.irbbarcelona.org\/acomajuncosa\/pocketvec<\/a><\/p>\n

\u00bb M\u00e1s informaci\u00f3n: web del IRB Barcelona [+]<\/a><\/strong><\/p>\n

\u00bb Art\u00edculo de referencia:<\/strong>\u00a0Comajuncosa-Creus, A., Jorba, G., Barril, X.\u00a0et al.<\/i>\u00a0Comprehensive detection and characterization of human druggable pockets through binding site descriptors.\u00a0Nat Commun\u00a015<\/b>, 7917 (2024).\u00a0DOI:\u00a010.1038\/s41467-024-52146-3\u00a0<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Cient\u00edficos del IRB Barcelona, con sede en el Parque Cient\u00edfico de Barcelona, han desarrollado PocketVec, una metodolog\u00eda innovadora para detectar y caracterizar sitios farmacol\u00f3gicamente aprovechables en prote\u00ednas humanas. 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