{"id":1149437,"date":"2025-10-08T08:00:00","date_gmt":"2025-10-08T15:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=1149437"},"modified":"2026-02-05T08:28:12","modified_gmt":"2026-02-05T16:28:12","slug":"small-molecules","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/small-molecules\/","title":{"rendered":"Small molecules"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background- card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"563\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized.jpg\" class=\"attachment-full size-full\" alt=\"3D illustration Atoms structure. Science or medical background with molecules and atoms. Medical background for banner or flyer. Structure at the atomic level\" style=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized.jpg 1000w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-300x169.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-768x432.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-655x368.jpg 655w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-343x193.jpg 343w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-240x135.jpg 240w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-640x360.jpg 640w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2023\/10\/shutterstock_763388227_resized-960x540.jpg 960w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/lab\/microsoft-research-ai-for-science\/\" class=\"icon-link icon-link--reverse mb-2\" data-bi-cN=\"MSR AI for Science\">\n\t\t\t\t\t\t\t\t\t<span class=\"c-glyph glyph-chevron-left\" aria-hidden=\"true\"><\/span>\n\t\t\t\t\t\t\t\t\tMSR AI for Science\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 class=\"wp-block-heading\" id=\"small-molecules\">Small molecules<\/h1>\n\n\n\n<p>Bringing scale, speed, and precision to molecular discovery with AI<\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p>We work on accelerating the discovery of small molecules through AI at all steps of the Design-Make-Test cycle. This includes models to predict molecular properties, generative models to design new molecules with the required properties, and models to predict how molecules can be synthesized.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"retrochimera\">RetroChimera<\/h2>\n\n\n\n<p>RetroChimera is a predictive model designed to assist in chemical synthesis. Given a target product molecule, either represented as molecular graphs or as a sequence of characters (SMILES), it generates multiple plausible chemical reactions that could produce the desired compound. Each reaction consists of a set of reactant molecules, represented either as molecular edits or as character strings, generated de novo.<br>The model is intended to support the synthesis of drug-like small molecules and is being shared with the research community to encourage reproducibility and stimulate further exploration in this domain.<br>RetroChimera is aimed at domain experts who possess the expertise to critically assess the quality of its outputs before applying them in practice.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-pill\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-white-color has-blue-background-color has-text-color has-background has-link-color wp-element-button\" href=\"https:\/\/ai.azure.com\/catalog\/models\/RetroChimera\">RetroChimera model on Foundry<\/a><\/div>\n<\/div>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"Chimera: Accurate synthesis prediction by ensembling models with... | Microsoft Research Forum\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube-nocookie.com\/embed\/FvziVbhHVSE?feature=oembed&rel=0\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"syntheseus\">Syntheseus<\/h2>\n\n\n\n<p>Syntheseus is a modular Python library for retrosynthetic planning that constructs synthesis routes for target molecules by repeatedly applying reaction prediction models and assembling the results into reaction trees. It supports integration with various reaction models and search algorithms, making it a flexible tool for automated chemical synthesis planning.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-pill\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-white-color has-black-background-color has-text-color has-background has-link-color wp-element-button\" href=\"https:\/\/github.com\/microsoft\/syntheseus\" target=\"_blank\" rel=\"noreferrer noopener\">Synthesues on GitHub<\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"moler\">MoLeR<\/h2>\n\n\n\n<p>MoLeR is a generative model for molecular graphs based on a variational autoencoder, enabling the creation of novel molecules with specified substructures or scaffolds. It is designed to support scaffold-constrained generation and exploration of chemical diversity for applications like drug discovery.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-pill\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-white-color has-black-background-color has-text-color has-background has-link-color wp-element-button\" href=\"https:\/\/github.com\/microsoft\/molecule-generation\" target=\"_blank\" rel=\"noreferrer noopener\">MoLeR on GitHub<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">news<\/span>\n\t\t\t<a href=\"https:\/\/www.marktechpost.com\/2024\/12\/16\/this-ai-paper-from-microsoft-and-novartis-introduces-chimera-a-machine-learning-framework-for-accurate-and-scalable-retrosynthesis-prediction\/\" data-bi-cN=\"This AI Paper from Microsoft and Novartis Introduces Chimera: A Machine Learning Framework for Accurate and Scalable Retrosynthesis Prediction\" target=\"_blank\" rel=\"noopener noreferrer\" data-external-link=\"true\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>This AI Paper from Microsoft and Novartis Introduces Chimera: A Machine Learning Framework for Accurate and Scalable Retrosynthesis Prediction<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-open-in-new-tab\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n\n\n\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Publication<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/chemist-aligned-retrosynthesis-by-ensembling-diverse-inductive-bias-models\/\" data-bi-cN=\"Chemist-aligned retrosynthesis by ensembling diverse inductive bias models\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>Chemist-aligned retrosynthesis by ensembling diverse inductive bias models<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n\n\n\n<div class=\"annotations \" data-bi-aN=\"citation\">\n\t<article class=\"annotations__list card depth-16 bg-body p-4 \">\n\t\t<div class=\"annotations__list-item\">\n\t\t\t\t\t\t<span class=\"annotations__type d-block text-uppercase font-weight-semibold text-neutral-300 small\">Publication<\/span>\n\t\t\t<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/chimera-accurate-retrosynthesis-prediction-by-ensembling-models-with-diverse-inductive-biases\/\" data-bi-cN=\"Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases\" data-external-link=\"false\" data-bi-aN=\"citation\" data-bi-type=\"annotated-link\" class=\"annotations__link font-weight-semibold text-decoration-none\"><span>Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases<\/span>&nbsp;<span class=\"glyph-in-link glyph-append glyph-append-chevron-right\" aria-hidden=\"true\"><\/span><\/a>\t\t\t\t\t<\/div>\n\t<\/article>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n\n\n<div style=\"padding-bottom:32px; padding-top:32px\" class=\"wp-block-msr-immersive-section alignfull row wp-block-msr-immersive-section\">\n\t\n\t<div class=\"container\">\n\t\t<div class=\"wp-block-msr-immersive-section__wrapper col-lg-11 col-xl-9 px-0 m-auto\">\n\t\t\t<h2 class=\"wp-block-heading has-text-align-center has-white-color has-text-color has-link-color wp-elements-9b29f3b10f16e11bfb68c7a30a83f686\" id=\"work-with-us-1\">Work with us<\/h2>\n\n\n\n<p class=\"has-text-align-center has-white-color has-text-color has-link-color wp-elements-88989855b724b88c8331ca9e108dbbf0\">Check out our open roles<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-16018d1d wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a data-bi-type=\"button\" class=\"wp-block-button__link has-text-align-left wp-element-button\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/lab\/microsoft-research-ai-for-science\/opportunities\/\">See careers<\/a><\/div>\n<\/div>\t\t<\/div>\n\t<\/div>\n\n\t<img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"667\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2.jpg\" class=\"wp-block-msr-immersive-section__background-image\" alt=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2.jpg 1000w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-300x200.jpg 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-768x512.jpg 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/careers-banner-2-240x160.jpg 240w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Bringing scale, speed, and precision to molecular discovery with AI We work on accelerating the discovery of small molecules through AI at all steps of the Design-Make-Test cycle. This includes models to predict molecular properties, generative models to design new molecules with the required properties, and models to predict how molecules can be synthesized. RetroChimera [&hellip;]<\/p>\n","protected":false},"featured_media":976242,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1149437","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[1112385,1149496,1159207],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Rosa De Rosa","user_id":44078,"people_section":"Section name 0","alias":"rosaderosa"},{"type":"user_nicename","display_name":"Victor Garc\u00eda Satorras","user_id":41832,"people_section":"Section name 0","alias":"victorgar"},{"type":"user_nicename","display_name":"John Gardner","user_id":44089,"people_section":"Section name 0","alias":"johngardner"},{"type":"user_nicename","display_name":"Jose Garrido Torres","user_id":43904,"people_section":"Section name 0","alias":"josegarri"},{"type":"user_nicename","display_name":"Jean Helie","user_id":43983,"people_section":"Section name 0","alias":"jehelie"},{"type":"user_nicename","display_name":"Guoqing Liu","user_id":40438,"people_section":"Section name 0","alias":"guoqingliu"},{"type":"user_nicename","display_name":"Krzysztof Maziarz","user_id":38955,"people_section":"Section name 0","alias":"krmaziar"},{"type":"user_nicename","display_name":"Felix Pultar","user_id":44085,"people_section":"Section name 0","alias":"felixpultar"},{"type":"user_nicename","display_name":"Marwin Segler","user_id":40300,"people_section":"Section name 0","alias":"marwinsegler"},{"type":"user_nicename","display_name":"Shoko Ueda","user_id":41913,"people_section":"Section name 0","alias":"shokoueda"},{"type":"user_nicename","display_name":"Elise van der Pol","user_id":41749,"people_section":"Section name 0","alias":"evanderpol"}],"msr_research_lab":[851467],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149437","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":13,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149437\/revisions"}],"predecessor-version":[{"id":1151552,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1149437\/revisions\/1151552"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/976242"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1149437"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1149437"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1149437"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1149437"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=1149437"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}