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Up Directory CCL 24.02.15 3D Antibody Modeling in Orion Webinar
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To: chemistry-request at ccl.net
Date: Mon Jan 22 11:12:18 2024
Subject: 24.02.15 3D Antibody Modeling in Orion Webinar
3D antibody modeling in Orion Webinar hosted by The Antibody Society and presented by OpenEye, Cadence Molecular Sciences' Jesper Sorensen. 

Register here: https://webinars-antibodysociety.org/store/seminar/seminar.php?seminar=197635

Presenting this session is Dr. Jesper Sorensen, Head of Biomodeling at OpenEye, Cadedence Molecular Sciences. Jesper received his Ph.D. in Nanochemistry from Aarhus University in Denmark and subsequently did a post-doc in Prof. Rommie Amaro’s lab at UC San Diego in California. He then joined Dart Neurosciences, as a scientific software developer. Jesper joined OpenEye in 2018, co-developing the Spruce toolkit for protein structure preparation. He now manages a team of developers focused on advancing drug discovery tools for biologics.

About this session 

OpenEye's suite of antibody modeling tools, accessed via the cloud platform Orion, includes Specifica’s state-of-the-art antibody sequence analysis tool (AbXtract) and a set of open-source tools.

In this webinar, Dr. Jesper Sorensen will guide viewers through the process of modeling antibody structure on Orion, beginning with sequences from a selection campaign analyzed using AbXtract, or from internal or public databases. Full 3D structures are then generated with the AI-driven structure predictor ImmuneBuilder (requiring only around 100 ms per structure when predicting at the multi-thousand scale). From these structures, a wide variety of physico-chemical properties are calculated to enable the selection of those antibodies most likely to be successfully developed into human therapies. Structural diversity in the complementarity-determining region (CDR) can be further explored using knowledge-based loop modeling, while short trajectory and enhanced sampling molecular dynamics are used to explore global conformational diversity.

Structural families within computed conformational ensembles can be identified by clustering using 3D similarity based on a physically rigorous shape and chemical feature distribution within the CDRs. Individual sequences can be further optimized by single or multi-point mutations and/or loop replacement, and these new hypotheses can be submitted to further rounds of physico-chemical property calculation and conformational exploration, allowing rapid profiling of a wide variety of candidate antibodies.
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