BAGIM is an active community of Boston area scientists bringing together people from diverse fields of modeling and informatics to impact life and health sciences. BAGIM strives to create a forum for great scientific discussions covering a wide range of topics including data management, visualization, computational chemistry, drug discovery, protein structure, molecular modeling, structure-based drug design, data mining, software tools, and the sharing of goals and experiences. Our community is made up of participants from academia, government, and industry whose goal is to engage in the discussion of science involving a synthesis of theory and technology. Discussions sponsored by BAGIM are targeted to the needs and interests of informatics scientists, computational chemists, medicinal chemists, and statisticians. BAGIM also provides opportunities for networking within these disciplines as well as an arena for the dissemination of information of specific interest to the membership.

Wednesday, May 24, 2023

Kyle Martin - In-silico antibody developability: Dynamic Profile Predictions

 We are happy to announce our latest event being sponsored with Discngine. We welcome Kyle Martin, Postdoctoral Fellow, Boehringer Ingelheim. This will be a in-person event.

Title: In-silico antibody developability: Embedding Dynamics in Intrinsic Physicochemical Profiles Prediction

Date: May 18, 2023
Time: Event time: 5:30 - 8:00PM - Talk promptly starts at 6 pm ET with Q&A immediately afterwards. Please arrive early.
Location: Residence Inn Boston Cambridge

Abstract: To bring an antibody-based medicine to the market, it needs to be stable, safe, and easy to manufacture. Following the concept of holistic in silico developability, Kyle Martin and colleagues have evaluated the molecular properties of antibody-based biotherapeutics in the market, including conformational flexibility of the Fvs using molecular dynamics (MD) simulations. In this event, you will learn how the Developability Navigator In Silico (DENIS) allows researchers to compare monoclonal antibody (mAb) candidates for their similarity with market-stage biotherapeutics in terms of physicochemical properties and conformational stability. This advanced computational tool promises to accelerate the progress of biotherapeutic drug candidates from discovery into early development by predicting drug properties in different aqueous environments.

Presenter: Kyle Martin, Postdoctoral Fellow, Boehringer Ingelheim

Bio: Dr. Martin got his PhD in biophysics from the University of Idaho in 2020 where his research ranged from predicting Ebola virus escape mutants to protein stability in the subsurface ocean of Saturn’s moon Titan. He started his postdoctoral research at Boehringer Ingelheim in 2020. His postdoctoral research has focused on antibody design via in-silico tools including molecular dynamics and predictive models. He’s published 2 papers as a co-author and 1 paper as a main author while at Boehringer.

Reference: https://pubs.acs.org/doi/10.1021/acs.molpharmaceut.2c00838

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