{"id":2659,"date":"2024-10-23T12:22:01","date_gmt":"2024-10-23T10:22:01","guid":{"rendered":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/?p=2659"},"modified":"2024-10-23T12:22:21","modified_gmt":"2024-10-23T10:22:21","slug":"sarel-fleishman-computational-design-of-enzyme-repertoires","status":"publish","type":"post","link":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/sarel-fleishman-computational-design-of-enzyme-repertoires\/","title":{"rendered":"Sarel Fleishman &#8211; Computational design of enzyme repertoires"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;3.22&#8243;][et_pb_row _builder_version=&#8221;3.22.1&#8243; border_color_all=&#8221;#3255c9&#8243; border_style_all=&#8221;groove&#8221;][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_text _builder_version=&#8221;3.22.1&#8243; min_height=&#8221;11px&#8221; custom_margin=&#8221;||-25px|||&#8221; custom_padding=&#8221;||0px|||&#8221;]<\/p>\n<p class=\"et_pb_module_header\"><span style=\"color: #3255c9\">Sarel Fleishman<\/span><\/p>\n<p><span style=\"color: #3255c9\">November 2, 2022, at 4 PM<\/span><\/p>\n<p><span style=\"color: #3255c9\">Online (Zoom)<\/span><\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;3.22.1&#8243;][\/et_pb_column][\/et_pb_row][et_pb_row custom_padding=&#8221;44px|||||&#8221; custom_margin=&#8221;80px||80px&#8221; _builder_version=&#8221;3.22.1&#8243;][et_pb_column type=&#8221;2_3&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_text _builder_version=&#8221;3.22.1&#8243; custom_margin=&#8221;-51px|||||&#8221; custom_padding=&#8221;0px|||||&#8221;]<\/p>\n<h3><strong>Abstract<\/strong><\/h3>\n<p>&nbsp;<\/p>\n<p>We recently developed methods that combine phylogenetic analysis and Rosetta atomistic design calculations to design highly optimized variants of natural proteins. Our methods have been used by thousands of users worldwide to generate stable therapeutic enzymes, vaccine immunogens, and highly active enzymes for a range of needs in basic and applied research. We now present a machine-learning strategy to design and economically synthesize millions of active-site variants that are likely to be stable, foldable and active. We applied this approach to the chromophore-binding pocket of GFP to generate more than 16,000 active designs that comprise as many as eight mutations in the active site.<\/p>\n<p>The designs exhibit extensive and potentially useful changes in every experimentally measured parameter, including brightness, stability and pH sensitivity. We also applied this strategy to design millions of glycoside hydrolases that exhibit significant backbone changes in the active site. Here too, we isolated more than 10,000 catalytically active and very diverse designs. Contrasting active and inactive designs illuminates areas for improving enzyme design methodology. This new approach to high-throughput design allows the systematic exploration of sequence and structure spaces of enzymes, binders and other functional proteins.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_video_slider _builder_version=&#8221;3.22.1&#8243;][et_pb_video_slider_item src=&#8221;https:\/\/www.youtube.com\/watch?v=h-tYuIdD8_k&#8221; src_webm=&#8221;https:\/\/www.youtube.com\/watch?v=h-tYuIdD8_k&#8221; _builder_version=&#8221;3.22.1&#8243; show_image_overlay=&#8221;off&#8221;][\/et_pb_video_slider_item][\/et_pb_video_slider][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_row _builder_version=&#8221;3.22.1&#8243;][et_pb_column type=&#8221;1_3&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_image src=&#8221;https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-content\/uploads\/sites\/27\/2022\/10\/12143F326-7-1.jpg&#8221; align=&#8221;center&#8221; _builder_version=&#8221;3.22.1&#8243; custom_margin=&#8221;20px|125px||||&#8221;][\/et_pb_image][\/et_pb_column][et_pb_column type=&#8221;2_3&#8243; _builder_version=&#8221;3.22.1&#8243;][et_pb_text _builder_version=&#8221;3.22.1&#8243; custom_padding=&#8221;0px|||||&#8221;]<\/p>\n<h3><strong>Dr. Sarel Fleishman <br \/><\/strong>(Weizmann Institute of Science)<strong><br \/><\/strong><br \/><strong><br \/><\/strong><\/h3>\n<p>Sarel Fleishman is an associate professor at the Weizmann Institute of Science. His research team develops a computational protein-design methodology to address both fundamental and \u201creal-world\u201d challenges in biochemistry and protein engineering. As a postdoc with David Baker in Seattle (2007-2011), Sarel developed the first accurate methods for designing protein binders, culminating in the design of broad-specificity influenza inhibitors. At the Weizmann Institute (2011-), his team developed protein design methods to the level of accuracy and reliability required to design large and complex proteins such as enzymes, antibodies, and vaccine immunogens \u2014 a protein that was designed in the Fleishman lab has recently been approved for mass production as a vaccine for malaria. Among Sarel\u2019s academic awards was the Clore Ph.D. Fellowship (2003-2006), the Science Magazine award for a young molecular biologist (2008), a postdoctoral fellowship (2006-2009) and a career-development award (2012-2015) from the Human Frontier Science Program, European Research Council Starting and Consolidator Grants (ongoing), the Alon Fellowship, the Henri Gutwirth Prize, and the Weizmann Scientific Council Award.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row custom_margin=&#8221;120px||&#8221; _builder_version=&#8221;3.22.1&#8243; locked=&#8221;off&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;3.0.47&#8243;][et_pb_divider _builder_version=&#8221;3.22.1&#8243;][\/et_pb_divider][et_pb_text admin_label=&#8221;\u00c0 lire aussi&#8221; _builder_version=&#8221;3.22.1&#8243; z_index_tablet=&#8221;500&#8243;]<\/p>\n<h2><span class=\"st\">Other distinguished lectures<br \/><\/span><\/h2>\n<p>[\/et_pb_text][et_pb_blog posts_number=&#8221;4&#8243; include_categories=&#8221;65&#8243; show_author=&#8221;off&#8221; show_date=&#8221;off&#8221; show_pagination=&#8221;off&#8221; module_id=&#8221;page_type_blog&#8221; _builder_version=&#8221;3.22.1&#8243; header_level=&#8221;h4&#8243; border_width_bottom_fullwidth=&#8221;1px&#8221; border_color_bottom_fullwidth=&#8221;rgba(51,51,51,0.18)&#8221; custom_padding=&#8221;||50px|&#8221; z_index_tablet=&#8221;500&#8243;][\/et_pb_blog][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sarel Fleishman November 2, 2022, at 4 PM Online (Zoom) &nbsp;Abstract &nbsp; We recently developed methods that combine phylogenetic analysis and Rosetta atomistic design calculations to design highly optimized variants of natural proteins. Our methods have been used by thousands of users worldwide to generate stable therapeutic enzymes, vaccine immunogens, and highly active enzymes for&hellip; <a class=\"continue\" href=\"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/sarel-fleishman-computational-design-of-enzyme-repertoires\/\">Lire la suite<span> Sarel Fleishman &#8211; Computational design of enzyme repertoires<\/span><\/a><\/p>\n","protected":false},"author":560,"featured_media":1139,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[53,1,65],"tags":[],"class_list":["post-2659","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-53","category-diip","category-distinguished-lectures"],"_links":{"self":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2659","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/users\/560"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/comments?post=2659"}],"version-history":[{"count":3,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2659\/revisions"}],"predecessor-version":[{"id":2663,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2659\/revisions\/2663"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media\/1139"}],"wp:attachment":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media?parent=2659"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/categories?post=2659"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/tags?post=2659"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}