{"id":4988,"date":"2025-05-11T20:20:11","date_gmt":"2025-05-11T20:20:11","guid":{"rendered":"https:\/\/peptideformulations.com\/research\/"},"modified":"2026-04-13T23:48:03","modified_gmt":"2026-04-13T23:48:03","slug":"research","status":"publish","type":"page","link":"https:\/\/peptidogen.mx\/es\/research\/","title":{"rendered":"I+D"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\r\n\r\n\r\n \r\n \r\n Peptidogen Research Library<\/title>\r\n <link href=\"https:\/\/fonts.googleapis.com\/css2?family=Poppins:wght@400;600;700&display=swap\" rel=\"stylesheet\">\r\n <style>\r\n \/* =========================\r\n Scoped scrolling offsets\r\n ========================= *\/\r\n\r\n #ar-lib.ar-lib {\r\n --stickyHeaderH: 0px;\r\n --stickyOffset: 24px;\r\n }\r\n\r\n #ar-lib .accordion-header,\r\n #ar-lib h2,\r\n #ar-lib h3,\r\n #ar-lib h4,\r\n #ar-lib [id] {\r\n scroll-margin-top: calc(var(--stickyOffset) + 16px);\r\n }\r\n\r\n \/* =========================\r\n Base + Typography\r\n ========================= *\/\r\n #ar-lib {\r\n font-family: Arial, sans-serif !important;\r\n background-color: #ffffff !important;\r\n color: #000000 !important;\r\n line-height: 1.6 !important;\r\n color-scheme: light;\r\n }\r\n\r\n #ar-lib p,\r\n #ar-lib li,\r\n #ar-lib h1,\r\n #ar-lib h2,\r\n #ar-lib h3,\r\n #ar-lib h4,\r\n #ar-lib h5,\r\n #ar-lib h6 {\r\n color: #000000 !important;\r\n }\r\n\r\n \/* =========================\r\n Content wrappers\r\n ========================= *\/\r\n #ar-lib .container {\r\n max-width: 1100px !important;\r\n margin: auto !important;\r\n padding: 2rem 1rem !important;\r\n background: #ffffff !important;\r\n color: #000000 !important;\r\n }\r\n\r\n \/* =========================\r\n Accordion\r\n ========================= *\/\r\n #ar-lib .accordion-section {\r\n margin-bottom: 1.5em !important;\r\n border-radius: 12px !important;\r\n overflow: hidden !important;\r\n border: 1px solid #e5e7eb !important;\r\n background: #ffffff !important;\r\n }\r\n\r\n \/* Accordion Header Labels:\r\n Sets accordion labels to Poppins, bold, and 18px. *\/\r\n #ar-lib .accordion-header {\r\n background-color: #ffffff !important;\r\n color: #000000 !important;\r\n padding: 1rem 1rem 1rem 3.25rem !important;\r\n cursor: pointer !important;\r\n font-family: 'Poppins', sans-serif !important;\r\n font-size: 18px !important;\r\n font-weight: 700 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!important;\r\n color: #000000 !important;\r\n }\r\n\r\n #ar-lib .accordion-section.active .accordion-content {\r\n max-height: 5000px !important;\r\n transition: max-height 0.5s ease-in, padding 0.5s ease-in !important;\r\n padding: 1rem !important;\r\n }\r\n\r\n \/* =========================\r\n Article Cards\r\n ========================= *\/\r\n #ar-lib .article {\r\n background: #ffffff !important;\r\n color: #000000 !important;\r\n border-radius: 16px !important;\r\n box-shadow: 0 4px 12px rgba(0, 0, 0, 0.05) !important;\r\n padding: 1.5rem !important;\r\n margin: 2rem 0 !important;\r\n border: 1px solid #eee !important;\r\n }\r\n\r\n \/* Article H3 Titles:\r\n Makes standard article H3 titles smaller and consistent. *\/\r\n #ar-lib .article h3 {\r\n font-family: 'Poppins', sans-serif !important;\r\n font-size: 18px !important;\r\n font-weight: 700 !important;\r\n line-height: 1.3 !important;\r\n color: #000000 !important;\r\n margin-top: 0 !important;\r\n margin-bottom: 12px 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none;\r\n padding: 14px 18px;\r\n position: relative;\r\n color: #000000 !important;\r\n font-weight: 600;\r\n font-family: 'Poppins', sans-serif;\r\n background: #ffffff !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section summary::-webkit-details-marker {\r\n display: none;\r\n }\r\n\r\n #ar-lib .peptide-research-section summary::after {\r\n content: \"\u25b8\";\r\n position: absolute;\r\n right: 18px;\r\n transition: transform .2s ease;\r\n color: #000000 !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section details[open] summary::after {\r\n transform: rotate(90deg);\r\n }\r\n\r\n #ar-lib .peptide-research-section .details-body {\r\n padding: 0 18px 18px;\r\n color: #000000 !important;\r\n background: #ffffff !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section .mini {\r\n font-size: 13px;\r\n }\r\n\r\n #ar-lib .peptide-research-section a.pr-link {\r\n color: #000000 !important;\r\n text-decoration: underline dotted 1px;\r\n text-underline-offset: 2px;\r\n 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.peptide-research-section h3,\r\n #ar-lib .peptide-research-section h4 {\r\n scroll-margin-top: var(--stickyOffset) !important;\r\n color: #000000 !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details > summary {\r\n appearance: none;\r\n -webkit-appearance: none;\r\n cursor: pointer;\r\n color: #000000 !important;\r\n font-weight: 600;\r\n line-height: 1.35;\r\n display: block;\r\n padding: 8px 12px;\r\n border-radius: 8px;\r\n list-style: none;\r\n text-decoration: none;\r\n background: #ffffff !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details > summary::-webkit-details-marker {\r\n display: none;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details > summary::after {\r\n content: \"\u25b8\";\r\n margin-left: 8px;\r\n transition: transform 160ms ease;\r\n display: inline-block;\r\n transform-origin: 45% 50%;\r\n color: #000000 !important;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details[open] > summary::after {\r\n transform: rotate(90deg);\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details > summary:hover,\r\n #ar-lib .peptide-research-section article.card.split-12 details > summary:focus-visible {\r\n text-decoration: underline;\r\n background: #ffffff !important;\r\n outline: 2px solid #d1d5db !important;\r\n outline-offset: 2px;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 details + details > summary {\r\n margin-top: 4px;\r\n }\r\n\r\n #ar-lib .peptide-research-section article.card.split-12 .details-body.mini {\r\n padding: 8px 12px 12px;\r\n }\r\n\r\n \/* =========================\r\n Dark mode guardrails\r\n ========================= *\/\r\n @media (prefers-color-scheme: dark) {\r\n #ar-lib,\r\n #ar-lib .container,\r\n #ar-lib .article,\r\n #ar-lib .accordion-section,\r\n #ar-lib .accordion-content,\r\n #ar-lib .peptide-research-section,\r\n #ar-lib .peptide-research-section .card,\r\n #ar-lib .peptide-research-section .card-body,\r\n #ar-lib .peptide-research-section .details-body,\r\n #ar-lib .accordion-header {\r\n background: #ffffff !important;\r\n color: #000000 !important;\r\n }\r\n }\r\n\r\n #ar-lib,\r\n #ar-lib .container,\r\n #ar-lib .article,\r\n #ar-lib .accordion-section,\r\n #ar-lib .accordion-content,\r\n #ar-lib .peptide-research-section,\r\n #ar-lib .peptide-research-section .card,\r\n #ar-lib .peptide-research-section .card-body,\r\n #ar-lib .peptide-research-section .details-body,\r\n #ar-lib .accordion-header {\r\n background-image: none !important;\r\n }\r\n\r\n #ar-lib *::after {\r\n background-image: none !important;\r\n }\r\n\r\n #ar-lib .card,\r\n #ar-lib .panel,\r\n #ar-lib .block,\r\n #ar-lib .section,\r\n #ar-lib .widget,\r\n #ar-lib .wp-block-group,\r\n #ar-lib .wp-block-columns,\r\n #ar-lib .wp-block-column {\r\n background-color: #ffffff !important;\r\n background-image: none !important;\r\n }\r\n\r\n #ar-lib img,\r\n #ar-lib svg {\r\n filter: none !important;\r\n background: transparent !important;\r\n }\r\n\r\n #ar-lib input,\r\n #ar-lib textarea,\r\n #ar-lib select,\r\n #ar-lib button {\r\n background-color: #ffffff !important;\r\n color: #000000 !important;\r\n border-color: #d0d7de !important;\r\n }\r\n <\/style>\r\n<\/head>\r\n\r\n<body id=\"top\">\r\n <div class=\"ar-lib\" id=\"ar-lib\">\r\n\r\n <section id=\"peptide-research\" class=\"peptide-research-section\">\r\n <div class=\"pr-container\">\r\n <div class=\"pr-eyebrow\">Research Library<\/div>\r\n <h2 class=\"pr-title\">Global Peptide Research \u2014 Landscape & Frontiers<\/h2>\r\n <p class=\"pr-sub\">A neutral, research-first overview of who\u2019s active in peptide science and what frontiers are moving fastest \u2014 synthesized for labs, students, and investigators.<\/p>\r\n\r\n <div class=\"pr-disclaimer\">\r\n <strong>Research-Use-Only (RUO).<\/strong> The content below summarizes scientific activity and methods. It does not make clinical claims and is not medical advice. Products mentioned on this site are for in-vitro laboratory research, analytical method development, and educational purposes only.\r\n <\/div>\r\n\r\n <div class=\"pr-grid\">\r\n <article class=\"card split-6\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">Where peptide research is most active<\/h3>\r\n <\/header>\r\n <div class=\"card-body\">\r\n <p class=\"muted\">\r\n Global R&D spending is highly concentrated. The <em>United States<\/em> is number one worldwide, investing more than <strong>$700B annually<\/strong> and producing the largest volume of peptide publications and patents, anchored by NIH, NSF, and biotech hubs like Boston and the Bay Area. <em>China<\/em> is a close second, matching U.S. spending levels and rapidly expanding output in peptide synthesis, synthetic biology, and radiochemistry.\r\n <\/p>\r\n <p class=\"muted\">\r\n The next tier includes the <em>European Union<\/em> (notably Germany, France, Scandinavia, Denmark\u2014home to Novo Nordisk\u2019s peptide innovations), <em>Japan<\/em> (materials science and radiolabeled peptide imaging), and <em>South Korea<\/em> (fast-growing peptide biomanufacturing). Additional hubs with outsized impact include the <em>U.K.<\/em> (AI-driven peptide design), <em>Switzerland<\/em> (precision synthesis, Novartis\/Roche), <em>Canada<\/em> and <em>Australia<\/em> (natural peptide sources, oncology), and <em>Singapore<\/em> and <em>Israel<\/em> (synthetic biology and computational peptide design).\r\n <\/p>\r\n <p class=\"muted\">\r\n Publication and patent output in peptides strongly reflects these hubs, with leadership defined by <strong>aggregate research intensity, ecosystem depth, and translational infrastructure<\/strong> rather than therapeutic endorsement.\r\n <\/p>\r\n <div class=\"kpi-row\">\r\n <div class=\"kpi\"><strong>Major funders:<\/strong> NIH, NSF, NSFC (China), Horizon Europe, AMED (Japan), NRF (Korea), Weizmann Institute, Max Planck, ETH Zurich<\/div>\r\n <div class=\"kpi\"><strong>Key drivers:<\/strong> Metabolic biology (GLP-1, insulin peptides), peptide nanomaterials, radiolabeled tracers<\/div>\r\n <div class=\"kpi\"><strong>Growth areas:<\/strong> AI-assisted sequence design, combinatorial libraries, peptide\u2013drug conjugates, green synthesis<\/div>\r\n <\/div>\r\n <p class=\"sr-note\">\r\n Note: \u201cLeaders\u201d refers to scientific capacity, funding, and publication ecosystems\u2014this does not imply clinical approval or therapeutic endorsement.\r\n <\/p>\r\n <\/div>\r\n <\/article>\r\n\r\n <article class=\"card split-6\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">What\u2019s on the cutting edge<\/h3>\r\n <\/header>\r\n <div class=\"card-body\">\r\n <ul class=\"list\">\r\n <li><strong>Metabolic peptides & poly-agonists<\/strong> \u2014 intense work on GLP-1, GIP, and glucagon co-\/tri-agonists, next-gen pharmacology, and structure\u2013activity optimization (research, preclinical, and clinical settings).<\/li>\r\n <li><strong>Oral delivery of peptides<\/strong> \u2014 permeation enhancers (e.g., SNAC-style strategies), enteric microenvironments, protease avoidance, and intestinal uptake models.<\/li>\r\n <li><strong>Macrocycles & constrained peptides<\/strong> \u2014 cyclization, stapling, and noncanonical residues to improve stability, target affinity, and cell permeability.<\/li>\r\n <li><strong>Targeted radiochemistry<\/strong> \u2014 peptide ligands (e.g., somatostatin analogs) for imaging\/therapy in nuclear medicine research; active tracer engineering and dosimetry modeling.<\/li>\r\n <li><strong>Antimicrobial peptides (AMPs)<\/strong> \u2014 host-defense peptides, synthetic libraries, resistance-aware design, and membrane-active mechanisms.<\/li>\r\n <li><strong>Self-assembling peptide biomaterials<\/strong> \u2014 nanofibers, hydrogels, and 2D\/3D architectures for scaffolds, sensors, & delivery matrices.<\/li>\r\n <li><strong>Computation & AI<\/strong> \u2014 sequence-to-function prediction, de novo design, high-throughput ML-guided screening, and inverse-design pipelines.<\/li>\r\n <li><strong>Peptidomimetics & D-peptides<\/strong> \u2014 backbone\/side-chain engineering to enhance protease resistance and bioavailability in models.<\/li>\r\n <li><strong>Conjugates<\/strong> \u2014 peptide\u2013drug, peptide\u2013toxin, and radionuclide conjugates for targeted payload delivery in research systems.<\/li>\r\n <li><strong>Novel formats<\/strong> \u2014 mRNA-encoded peptides, depot formulations, microneedle arrays, and long-acting release technologies.<\/li>\r\n <\/ul>\r\n <div class=\"pill\"><i><\/i>Fast-moving<\/div><div class=\"pill\"><i><\/i>High-throughput<\/div><div class=\"pill\"><i><\/i>Transdisciplinary<\/div>\r\n <\/div>\r\n <\/article>\r\n\r\n <article class=\"card split-6\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">How labs discover & characterize peptides<\/h3>\r\n <\/header>\r\n <div class=\"card-body\">\r\n <ul class=\"list\">\r\n <li><strong>Library Platforms:<\/strong> phage\/mRNA\/ribosome display, DNA-encoded libraries, combinatorial SPPS micro-arrays.<\/li>\r\n <li><strong>Design:<\/strong> motif mining, structure-guided design, macrocyclization\/stapling, L\/D-switches, noncanonical amino acids.<\/li>\r\n <li><strong>Analytics:<\/strong> LC-MS\/MS, HPLC purity profiling, NMR, CD spectroscopy, SPR\/BLI binding kinetics, imaging\/radiochemistry QC.<\/li>\r\n <li><strong>Delivery R&D:<\/strong> lipidation, permeation enhancers, polymer carriers, nanoparticle & hydrogel systems; in-vitro permeability models.<\/li>\r\n <li><strong>Scale-up:<\/strong> Fmoc-SPPS process development, green chemistry choices, impurity tracking, orthogonal deprotection strategies.<\/li>\r\n <\/ul>\r\n <\/div>\r\n <\/article>\r\n\r\n <article class=\"card split-6\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">Safety, ethics & compliance (research context)<\/h3>\r\n <\/header>\r\n <div class=\"card-body\">\r\n <ul class=\"list\">\r\n <li><strong>RUO only:<\/strong> Not for administration to humans or animals. For in-vitro experiments, method development, and training.<\/li>\r\n <li><strong>Standards:<\/strong> Follow local institutional policies and applicable guidelines (e.g., GLP for regulated studies, ICH Q7\/Q9 concepts where relevant).<\/li>\r\n <li><strong>Handling:<\/strong> Use appropriate PPE, chemical hygiene plans, and waste disposal procedures; radiochemistry requires additional controls.<\/li>\r\n <li><strong>Documentation:<\/strong> Maintain SOPs, batch records, and analytical certificates where applicable to the research.<\/li>\r\n <\/ul>\r\n <\/div>\r\n <\/article>\r\n\r\n <article class=\"card split-12\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">Deep-dive notes<\/h3>\r\n <\/header>\r\n\r\n <details open>\r\n <summary>Leading regions & why they matter<\/summary>\r\n <div class=\"details-body mini\">\r\n High aggregate funding + mature university and biotech ecosystems tend to correlate with higher output in peptide chemistry, radiochemistry, and bioengineering. The U.S. and China lead total R&D outlays; the EU (incl. Germany, France), Japan, and South Korea sustain strong public\u2013private pipelines. Switzerland, the U.K., Canada, Australia, Singapore, and Israel punch above weight via specialized institutes and translational labs.\r\n <\/div>\r\n <\/details>\r\n\r\n <details>\r\n <summary>Oral peptide delivery \u2014 what\u2019s working<\/summary>\r\n <div class=\"details-body mini\">\r\n Strategies include localized gastric micro-environment control (tablet co-excipients that transiently modulate pH and proteolysis), permeability enhancers, and sequence\/formulation engineering to mitigate degradation and promote transcellular uptake. Researchers test dissolution, permeability (e.g., Caco-2), stability, and PK proxies in vitro before advancing.\r\n <\/div>\r\n <\/details>\r\n\r\n <details>\r\n <summary>Macrocycles & constrained scaffolds<\/summary>\r\n <div class=\"details-body mini\">\r\n Cyclization (head-to-tail\/side-chain), hydrocarbon stapling, and \u03b2\/\u03b3-amino acids can improve affinity and protease resistance. Macrocycles also access \u201cundruggable\u201d grooves by balancing polarity and rigidity; property windows differ from small molecules, guiding distinct design rules.\r\n <\/div>\r\n <\/details>\r\n\r\n <details>\r\n <summary>Targeted radiochemistry with peptide ligands<\/summary>\r\n <div class=\"details-body mini\">\r\n Somatostatin-receptor ligands and other peptide motifs are widely studied as carriers for diagnostic\/therapeutic radionuclides. Work includes chelator choice, specific activity, receptor kinetics, dosimetry models, and shielded handling.\r\n <\/div>\r\n <\/details>\r\n\r\n <details>\r\n <summary>Antimicrobial & self-assembling peptides<\/summary>\r\n <div class=\"details-body mini\">\r\n AMPs exploit membrane interactions and immunomodulatory effects; current research addresses selectivity and resistance. Self-assembling peptides form nanofibers\/hydrogels for scaffolds, sensors, and controlled-release matrices.\r\n <\/div>\r\n <\/details>\r\n\r\n <div class=\"card-body\">\r\n <span class=\"badge\">Research context only<\/span>\r\n <\/div>\r\n <\/article>\r\n\r\n <article class=\"card split-12\">\r\n <header class=\"card-head\">\r\n <span class=\"dot\"><\/span><h3 class=\"card-title\">Selected references & data sources<\/h3>\r\n <\/header>\r\n <div class=\"card-body mini\">\r\n <ul class=\"list\">\r\n <li>UNESCO Institute for Statistics \u2014 Global R&D spending visualizations.<\/li>\r\n <li>OECD R&D Statistics; World Bank R&D (% GDP) dashboards.<\/li>\r\n <li>Peer-reviewed reviews on oral peptide delivery, macrocycles, antimicrobial peptides, and peptide biomaterials.<\/li>\r\n <li>Regulatory labels and reviews for peptide-based radiopharmaceutical research and delivery strategies.<\/li>\r\n <\/ul>\r\n <p class=\"sr-note\">Links are available on request for lab teams; this public page avoids external navigation to keep readers focused.<\/p>\r\n <\/div>\r\n <\/article>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\r\n <div class=\"container\">\r\n <section class=\"accordion-section active\" id=\"overview\">\r\n <div class=\"accordion-header\" role=\"button\" aria-expanded=\"true\" aria-controls=\"content-overview\" tabindex=\"0\">Overview<\/div>\r\n <div class=\"accordion-content\" id=\"content-overview\" aria-labelledby=\"overview-header\">\r\n <div class=\"article\">\r\n <h3>What Are Peptides?<\/h3>\r\n <p>Peptides are short chains of amino acids that serve as building blocks of proteins and perform essential biological functions in all living organisms.<\/p>\r\n <h3>Peptide Classification & Function<\/h3>\r\n <ul>\r\n <li><strong>Natural peptides:<\/strong> Found in hormones, enzymes, and immune responses<\/li>\r\n <li><strong>Synthetic peptides:<\/strong> Used in biomarker discovery and receptor binding studies<\/li>\r\n <li><strong>Therapeutic potential:<\/strong> Investigated in oncology, endocrinology, and neurobiology<\/li>\r\n <\/ul>\r\n <h3>Research Use Only<\/h3>\r\n <p>These materials are strictly for in-vitro laboratory research. Not for human or animal use.<\/p>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\r\n <section class=\"accordion-section\" id=\"articles\">\r\n <div class=\"accordion-header\" role=\"button\" aria-expanded=\"false\" aria-controls=\"content-articles\" tabindex=\"0\">Articles<\/div>\r\n <div class=\"accordion-content\" id=\"content-articles\" aria-labelledby=\"articles-header\">\r\n <div class=\"article\">\r\n <h3>AI-Enhanced Peptide Design Tools for Novel Peptides & Optimization<\/h3>\r\n <p>This review highlights AI's potential in pioneering novel peptide designs and refining existing molecular structures for high-quality peptide development.<\/p>\r\n <ul>\r\n <li>Revolutionizing peptide generation and optimization<\/li>\r\n <li>Uses deep learning frameworks like RFdiffusion for <em>de novo<\/em> design<\/li>\r\n <li>Focus on cyclic cell-targeting peptides with high tumor affinity<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC11945313\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>De Novo Peptide Sequencing with AI: InstaNovo & InstaNovo+<\/h3>\r\n <p>Introduces transformer-based and diffusion-based AI models for <em>de novo<\/em> peptide sequencing from mass spectrometry data, greatly enhancing accuracy.<\/p>\r\n <ul>\r\n <li>Significantly improves peptide sequencing accuracy<\/li>\r\n <li>Expands discovery of novel biomolecules<\/li>\r\n <li>Enables high-precision sequencing of nanobodies and complex samples<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/instadeep.com\/news\/enhancing-peptide-sequencing-with-ai\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI-Driven Antimicrobial Peptide (AMP) Discovery & Generation<\/h3>\r\n <p>Explores the application of AI in discovering AMPs by mining biological sequences and generating novel peptide sequences with optimal therapeutic properties.<\/p>\r\n <ul>\r\n <li>Efficiently navigates vast sequence space for AMPs<\/li>\r\n <li>Identifies peptides with desired properties and reduced toxicity<\/li>\r\n <li>Leverages generative models for new sequences<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/chemrxiv.org\/articles\/preprint\/AI-Driven_Antimicrobial_Peptide_Discovery_Mining_and_Generation\/25293699\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI for Predicting Peptide Properties in Mass Spectrometry<\/h3>\r\n <p>Reviews state-of-the-art machine learning and deep learning models for predicting peptide properties in mass spectrometry-based proteomics.<\/p>\r\n <ul>\r\n <li>Predicts digestibility, retention time, charge state<\/li>\r\n <li>Enables <em>in silico<\/em> generation of spectral libraries<\/li>\r\n <li>Crucial for accurate peptide identification in proteomics<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC11010332\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI in Accelerating Overall Peptide Drug Discovery Pipeline<\/h3>\r\n <p>Highlights how AI, including machine learning and deep learning, is transforming and accelerating the entire peptide drug discovery pipeline.<\/p>\r\n <ul>\r\n <li>Enables <em>in silico<\/em> discovery of new peptide ligands<\/li>\r\n <li>Predicts peptide-protein interactions effectively<\/li>\r\n <li>Accelerates early identification of lead candidates<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC11494291\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI for Designing Highly Active Peptides and Optimizing Bioactivity<\/h3>\r\n <p>Describes how machine learning greatly assists in designing highly active peptides by learning predictors from existing data, reducing the need for extensive lab experiments.<\/p>\r\n <ul>\r\n <li>Efficiently identifies peptides with best predicted bioactivity<\/li>\r\n <li>Uses properties like k-mer criteria and physicochemical properties<\/li>\r\n <li>Partly replaces expensive laboratory experiments<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/journals.plos.org\/plosone\/article?id=10.1371\/journal.pone.0142994\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI Methods for Antimicrobial Peptides: Progress and Challenges<\/h3>\r\n <p>Covers recent advancements in using large protein language models and graph neural networks via AI to address challenges in AMP discovery and design.<\/p>\r\n <ul>\r\n <li>Addresses toxicity and poor stability of AMPs<\/li>\r\n <li>Utilizes structure-guided design via AI<\/li>\r\n <li>Accelerates translation of AMPs into clinical use<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC11702388\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Large Language Models (LLMs) for Re-engineering Peptide Antibiotics<\/h3>\r\n <p>Researchers successfully leveraged LLMs to re-engineer existing bacteria-killing peptides to be safe for human use while retaining efficacy.<\/p>\r\n <ul>\r\n <li>Optimizes peptide properties for safety and potency<\/li>\r\n <li>Demonstrates LLMs' power in navigating chemical space<\/li>\r\n <li>Focuses on re-engineering for human compatibility<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.news-medical.net\/news\/20240801\/AI-unlocks-potential-of-antimicrobial-peptides-for-new-antibiotics.aspx\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI for Accelerated & Efficient Antimicrobial Peptide Design<\/h3>\r\n <p>A deep learning approach significantly accelerates antimicrobial peptide design, achieving high accuracy in predicting AMP efficacy and reducing time and cost.<\/p>\r\n <ul>\r\n <li>Converts peptide features into \"signal images\" for neural networks<\/li>\r\n <li>Improves feature extraction and AMP categorization<\/li>\r\n <li>Achieves substantial time and cost reductions in design<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/journals.plos.org\/plosone\/article?id=10.1371\/journal.pone.0298031\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI in Drug Discovery: Key Trends Shaping Therapeutics in 2025<\/h3>\r\n <p>Highlights how AI-driven drug discovery is revolutionizing peptide-based drug discovery, enabling rapid design, activity prediction, and optimization of novel therapeutics.<\/p>\r\n <ul>\r\n <li>Enables rapid design and activity prediction<\/li>\r\n <li>Integrates AlphaFold and generative models like proteinMPNN<\/li>\r\n <li>Focuses on high-potency peptide drug candidates<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/gubra.dk\/ai-in-drug-discovery-key-trends-shaping-therapeutics-in-2025\/\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI for Interpreting Peptide Biological & Chemical Representations<\/h3>\r\n <p>This study examines the influence of different peptide representations on AI prediction models' interpretability and accuracy, developing \"feature attribution\" methodologies.<\/p>\r\n <ul>\r\n <li>Develops methodologies for local interpretability<\/li>\r\n <li>Elucidates intrinsic mechanisms of peptide activities<\/li>\r\n <li>Enhances accuracy of AI prediction models<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/oaepublish.com\/articles\/2500000002\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Generative AI for Self-Assembling Peptides (SAP) Discovery<\/h3>\r\n <p>Presents a generative AI model that is 80-95% accurate in the discovery of self-assembling peptides, marking a significant step in \"intelligent laboratories\" for material discovery.<\/p>\r\n <ul>\r\n <li>Outperforms current state-of-the-art SAP models<\/li>\r\n <li>Efficiently explores complex sequence space of SAPs<\/li>\r\n <li>Advances accelerated material discovery<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.researchgate.net\/publication\/385483984_Reshaping_the_discovery_of_self-assembling_peptides_with_generative_AI_guided_by_hybrid_deep_learning\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI in Peptide-Based Vaccine Design<\/h3>\r\n <p>This review details how AI, especially machine learning algorithms, is transforming peptide-based vaccine design by predicting T-cell epitopes and optimizing immunogenicity.<\/p>\r\n <ul>\r\n <li>Predicts T-cell epitopes effectively<\/li>\r\n <li>Optimizes peptide immunogenicity for vaccines<\/li>\r\n <li>Accelerates identification of promising vaccine candidates<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.mdpi.com\/2076-393X\/12\/1\/10\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Machine Learning for Predicting Cell-Penetrating Peptides (CPPs)<\/h3>\r\n <p>Focuses on machine learning applications for predicting and rationally designing cell-penetrating peptides, crucial for advanced peptide drug delivery.<\/p>\r\n <ul>\r\n <li>Predicts CPP efficacy and cellular uptake mechanisms<\/li>\r\n <li>Enables rational design of peptide drug delivery systems<\/li>\r\n <li>Crucial for improving therapeutic bioavailability<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/abs\/10.1002\/mabi.202300407\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Deep Learning for <em>De Novo<\/em> Design of Therapeutic Peptides<\/h3>\r\n <p>Researchers are utilizing deep learning frameworks for the <em>de novo<\/em> design of peptides with specific therapeutic properties, generating novel sequences from scratch.<\/p>\r\n <ul>\r\n <li>Generates novel peptide sequences with desired activities<\/li>\r\n <li>Significantly expands chemical space for drug discovery<\/li>\r\n <li>Aims for properties like enzyme inhibition or receptor binding<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/www.nature.com\/articles\/s41467-024-54707-y\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI for Enhanced Peptide Synthesis & Process Optimization<\/h3>\r\n <p>Explores the application of AI in optimizing peptide synthesis processes, including predicting reaction yields and streamlining experimental workflows.<\/p>\r\n <ul>\r\n <li>Predicts reaction yields and side-product formation<\/li>\r\n <li>Improves overall efficiency and scalability of manufacturing<\/li>\r\n <li>Reduces waste in peptide production<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/onlinelibrary.wiley.com\/journal\/10970282\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>AI-Driven Prediction of Peptide Self-Assembly<\/h3>\r\n <p>This review summarizes the use of machine learning models to predict the self-assembly behavior of peptides, critical for designing peptide-based biomaterials and nanostructures.<\/p>\r\n <ul>\r\n <li>Aids in understanding and controlling self-assembly factors<\/li>\r\n <li>Enables rational design of functional peptide materials<\/li>\r\n <li>Critical for peptide-based biomaterials and nanostructures<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/pubs.rsc.org\/en\/content\/articlelanding\/2024\/sm\/d4sm00244k\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Graph Neural Networks (GNNs) for Peptide-Protein Interaction Prediction<\/h3>\r\n <p>Details the application of GNNs for highly accurate prediction of peptide-protein interactions, capturing complex structural and chemical features for drug design.<\/p>\r\n <ul>\r\n <li>Captures complex structural and chemical features<\/li>\r\n <li>Leads to robust predictions of binding affinity and specificity<\/li>\r\n <li>Crucial for drug design and understanding biological pathways<\/li>\r\n <\/ul>\r\n <a href=\"https:\/\/academic.oup.com\/bioinformatics\/article\/40\/Supplement_1\/i327\/7667315\" target=\"_blank\" rel=\"noopener\">Read Full Study<\/a>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\r\n <section class=\"accordion-section\" id=\"visuals\">\r\n <div class=\"accordion-header\" role=\"button\" aria-expanded=\"false\" aria-controls=\"content-visuals\" tabindex=\"0\">Visuals<\/div>\r\n <div class=\"accordion-content\" id=\"content-visuals\" aria-labelledby=\"visuals-header\">\r\n <div class=\"article\">\r\n <h3>AlphaFold2 Peptide Structure Prediction<\/h3>\r\n <img decoding=\"async\" src=\"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0969212622004798-gr1.jpg\" alt=\"AlphaFold2 Peptide Structure Prediction\" \/>\r\n <p>This figure showcases the accuracy of AlphaFold2 in predicting peptide structures, comparing its models to experimentally determined NMR structures.<\/p>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Greening the Synthesis of Peptide Therapeutics<\/h3>\r\n <img decoding=\"async\" src=\"http:\/\/zth.ubp.mybluehost.me\/website_66791e33\/wp-content\/uploads\/2025\/05\/Green.png\" alt=\"Greening the Synthesis of Peptide Therapeutics\" style=\"width:100%; border-radius:10px;\">\r\n <p>This infographic highlights strategies for reducing the environmental footprint of solid-phase peptide synthesis (SPPS) in industrial settings.<\/p>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Peptide and Protein Bioanalysis<\/h3>\r\n <img decoding=\"async\" src=\"http:\/\/zth.ubp.mybluehost.me\/website_66791e33\/wp-content\/uploads\/2025\/05\/Peptide-and-Protein-Bioanalysis.png\" alt=\"Peptide and Protein Bioanalysis\" style=\"width:100%; border-radius:10px;\">\r\n <p>An informative visual explaining the challenges and solutions in analyzing large biomolecules like peptides and proteins in bioanalytical laboratories.<\/p>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Peptides: What They Are and Why They Are Useful<\/h3>\r\n <img decoding=\"async\" src=\"http:\/\/zth.ubp.mybluehost.me\/website_66791e33\/wp-content\/uploads\/2025\/05\/Peptides-What-They-Are-and-Why-They-Are-Useful.png\" alt=\"Peptides: What They Are and Why They Are Useful\" style=\"width:100%; border-radius:10px;\">\r\n <p>This infographic provides an overview of peptides, their functions in the body, and their applications in skincare and muscle repair.<\/p>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Detailed Glycine-Lysine-Tyrosine-Alanine Peptide Bond Diagram<\/h3>\r\n <img decoding=\"async\" src=\"http:\/\/zth.ubp.mybluehost.me\/website_66791e33\/wp-content\/uploads\/2025\/05\/Detailed-Glycine-Lysine-Tyrosine-Alanine-Peptide.png\" alt=\"Gly-Lys-Tyr-Ala Peptide Bond Diagram\" style=\"width:100%; border-radius:10px;\">\r\n <p>A detailed diagram illustrating the peptide bonds between glycine, lysine, tyrosine, and alanine, highlighting the structure of the peptide chain.<\/p>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Global Peptide Therapeutics Market Report Infographic<\/h3>\r\n <img decoding=\"async\" src=\"http:\/\/zth.ubp.mybluehost.me\/website_66791e33\/wp-content\/uploads\/2025\/05\/Global-Peptide-Therapeutics-Market-Report.png\" alt=\"Global Peptide Therapeutics Market Report\" style=\"width:100%; border-radius:10px;\">\r\n <p>This infographic presents data on the global market size and growth trends for peptide therapeutics, providing insights into industry dynamics.<\/p>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n\r\n <section class=\"accordion-section\" id=\"news\">\r\n <div class=\"accordion-header\" role=\"button\" aria-expanded=\"false\" aria-controls=\"content-news\" tabindex=\"0\">News<\/div>\r\n <div class=\"accordion-content\" id=\"content-news\" aria-labelledby=\"news-header\">\r\n <div class=\"article\">\r\n <h3>New Trends in Peptide Therapies: Oral Peptides for Neurosciences<\/h3>\r\n <p>Advances in bioengineering and genetic code expansion are leading to a new era of oral peptide therapeutics for neuropsychiatric disorders, with many now in clinical trials.<\/p>\r\n <a href=\"https:\/\/www.psychiatryonline.org\/journal\/pn\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Sethera Therapeutics: Enhancing Peptide Stability for Oral Drugs<\/h3>\r\n <p>Sethera is bioengineering peptides for increased stability, enabling longer-lasting treatments and potential oral delivery for conditions like diabetes and obesity, previously considered untreatable.<\/p>\r\n <a href=\"https:\/\/vpresearch.utah.edu\/news\/sethera-transforming-peptide-drug-development\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Antimicrobial Peptides: AI-Driven Design for Bacterial Keratitis<\/h3>\r\n <p>Cutting-edge advancements in antimicrobial peptide (AMP) modification strategies and AI-assisted design are enhancing their efficacy and stability, offering new hope against bacterial keratitis.<\/p>\r\n <a href=\"https:\/\/pubs.acs.org\/journal\/bccebx\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Innovations in Peptide Engineering & Novel Delivery Systems<\/h3>\r\n <p>Recent breakthroughs in peptide engineering, including cyclization, PEGylation, and advanced delivery methods like nanocarriers, are significantly boosting the therapeutic potential of peptides across various diseases.<\/p>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Broadening the Scope: New Peptide Therapeutics for Diverse Conditions<\/h3>\r\n <p>New synthesis and modification technologies are diversifying peptide drug development, enabling their application to a wider range of clinical conditions, from cancer to metabolic disorders.<\/p>\r\n <a href=\"https:\/\/pubs.acs.org\/journal\/jmcmar\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Chemical Biology Tools Advancing Peptide & Protein Research<\/h3>\r\n <p>New chemical biology tools are proving critical for site-specific modification, understanding biomolecule interactions, and developing better intracellular delivery systems for peptide-based therapeutics.<\/p>\r\n <a href=\"https:\/\/www.frontiersin.org\/journals\/chemistry\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Foundational & Advanced Synthetic Peptide Chemistry<\/h3>\r\n <p>Continuous refinements in peptide chemistry, including native chemical ligation (NCL), remain crucial for the precise and efficient synthesis of complex and larger peptide and protein targets.<\/p>\r\n <a href=\"https:\/\/pubs.acs.org\/journal\/joceah\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Computational Approaches Revolutionize Bioactive Peptide Discovery<\/h3>\r\n <p>Bioinformatics techniques like computer simulation screening, QSAR analysis, and machine learning are dramatically improving the efficiency of discovering and identifying novel bioactive peptides.<\/p>\r\n <a href=\"https:\/\/pubs.acs.org\/\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Bioactive Peptides: Functional Properties in Food Science<\/h3>\r\n <p>Recent research highlights the production and characterization of bioactive peptides from food sources, exploring their diverse health benefits and strategies to enhance their stability and bioavailability.<\/p>\r\n <a href=\"https:\/\/www.frontiersin.org\/journals\/chemistry\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Clinical Success: Tirzepatide Outperforms Semaglutide for Weight Loss<\/h3>\r\n <p>A significant <em>New England Journal of Medicine<\/em> study reports that the peptide-based GLP-1\/GIP receptor agonist, tirzepatide, shows superior results for weight loss compared to semaglutide.<\/p>\r\n <a href=\"https:\/\/www.tctmd.com\/news\/\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>The Expanding World of Peptide Engineering Across Disciplines<\/h3>\r\n <p>Peptide engineering is rapidly growing, integrating advancements in synthesis, drug delivery, and materials science to create innovative applications in medicine, biotechnology, and nanotechnology.<\/p>\r\n <a href=\"https:\/\/www.mdpi.com\/journal\/peptides\/special_issues\/peptide_engineering\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <div class=\"article\">\r\n <h3>Peptide Synthesis: Enabling Diverse Therapeutic & Research Peptides<\/h3>\r\n <p>Ongoing development and refinement of solid-phase peptide synthesis (SPPS) and other methods are fundamental for producing the diverse array of synthetic peptides critical for current research and therapeutics.<\/p>\r\n <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/books\/NBK\" target=\"_blank\" rel=\"noopener\">Read More<\/a>\r\n <\/div>\r\n <\/div>\r\n <\/section>\r\n <\/div>\r\n\r\n <script>\r\n document.addEventListener('DOMContentLoaded', function () {\r\n const wrapper = document.getElementById('ar-lib');\r\n if (!wrapper) return;\r\n\r\n const headers = wrapper.querySelectorAll('.accordion-header');\r\n\r\n function setAllClosed() {\r\n wrapper.querySelectorAll('.accordion-section').forEach(section => {\r\n section.classList.remove('active');\r\n const head = section.querySelector('.accordion-header');\r\n if (head) head.setAttribute('aria-expanded', 'false');\r\n });\r\n }\r\n\r\n headers.forEach(header => {\r\n const section = header.closest('.accordion-section');\r\n const content = section.querySelector('.accordion-content');\r\n const contentId = 'content-' + 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Research Library Research Library Global Peptide Research \u2014 Landscape & Frontiers A neutral, research-first overview of who\u2019s active in peptide science and what frontiers are moving fastest \u2014 synthesized for labs, students, and investigators. Research-Use-Only (RUO). The content below summarizes scientific activity and methods. It does not make clinical claims and is not medical […]<\/p>\n","protected":false},"author":64,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4988","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/pages\/4988","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/users\/64"}],"replies":[{"embeddable":true,"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/comments?post=4988"}],"version-history":[{"count":20,"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/pages\/4988\/revisions"}],"predecessor-version":[{"id":17605,"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/pages\/4988\/revisions\/17605"}],"wp:attachment":[{"href":"https:\/\/peptidogen.mx\/es\/wp-json\/wp\/v2\/media?parent=4988"}],"curies":[{"name":"wordpress","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}