Mark your calendars - Second BMMP Seminar 2026 - 7th August 2026

[Ragothaman Yennamalli]

Dear all,

We will have our second seminar of BMMP's this season with Dr. Shruthi Viswanath from NCBS-TIFR.

Details of the Seminar:
Title: Integrative Structural Biology in the AI era
Date: 7th August 2026, Friday
Time: 4:00-5:00 PM (India Standard Time)
Format: GMeet: https://tinyurl.com/shruthiV-NCBS 

Abstract: Integrative structure determination allows us to determine the structures of large macromolecular assemblies by combining data from complementary experimental methods with physical principles, statistical inference, and prior models. In our group, we apply these methods to characterize several assemblies: chromatin remodeling assemblies, assemblies at cell-cell junctions, and mitochondrial complexes. We also develop computational methods for more accurate, precise, and efficient structure prediction of large macromolecular assemblies.

In this talk I will discuss the molecular architecture of the outer dense plaque of the cardiac desmosome that mediates cell-cell adhesion and signaling in cardiac cells. The structure was based on cryo-ET and immuno-EM maps, X-ray structures, biochemical assays, homology models, and bioinformatics predictions, and validated by independent super-resolution imaging, tomography, and biochemical studies. The structure highlights the role of the disordered N-terminus of plakophilin in desmosome assembly. The structure helped identify novel protein-protein interfaces that are validated by biochemical and functional studies in the Ballestrem lab. Finally, our structure will rationalize dozens of cardiac disease mutations associated with desmosomal subunits.

I will also discuss our recent method development efforts, specifically in deep learning, for two broad areas. One, we are interested in identifying binding sites for disordered regions (IDRs) of proteins. We have developed Disobind, a deep-learning method to predict binding regions for IDRs in large assemblies. We are currently extending the method to predict interactions in fuzzy complexes. Two, we are trying to predict antibody-chain pairing via deep learning on antibody sequences. Chain pairing is a  problem that is encountered in vaccine development that requires time-consuming and costly experiments - with an in silico alternative we are trying to decrease the time to market for monoclonal antibodies. 

We look forward to your participation in what promises to be an enlightening and engaging session. Please share them among your students and encourage them to participate.

Thanks and Regards,
Ragothaman

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Ragothaman M Yennamalli, Ph.D.

Associate Professor,

School of Computational and Integrative Sciences.

Jawaharlal Nehru University,

New Delhi - 110067.

https://yennamalli-lab.in/

https://www.jnu.ac.in/content/ragothaman

Indian Ambassador, Biophysical Society USA

Chair, Publications Committee, ISCB USA

Executive Committee Member, APBioNet

Associate Editor, Computational and Structural Biotechnology Journal

Associate Editor, Bioinformatics and Biology Insights

Special Issue Editor, Biophysical Journal

Editorial Board, BMC Bioinformatics

Editorial Board, Scientific Reports

Early Career Researcher Review Board, Protein Science

"When you can do the common things of life in an uncommon way, you will command the attention of the world." -George Washington Carver
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