Sudhanshu Shanker

Sudhanshu Shanker has expertise in structural bioinformatics, with a focus on developing theoretical models to address critical biological challenges. His research spans multiple domains, emphasizing the creation of innovative computational solutions.

He completed his Ph.D. at Jawaharlal Nehru University, where he developed Monte Carlo-based methods for biomolecular structure optimization and a density clustering method for analyzing hydration networks around non-Watson-Crick base pairs in RNA.

As a postdoctoral fellow at Kyoto University, Japan, he worked on a JSPS sponsored project on supramolecular polymerization and self-assembly systems. He later moved to Johns Hopkins University as a postdoctoral researcher in a Rosetta developer lab, where he focused on protein-carbohydrate interactions and developed CAPSIF, the first 3D-UNet and EGNN-based carbohydrate interaction site predictor. Subsequently, at The Scripps Research Institute, he led the development of AutoDock CrankPep V1.1, a state-of-the-art peptide docking method.

His current research interests lie in computational glycosciences, with a focus on developing new methods to study glycan-protein interactions and exploring the role of glycosylation in cancer and autoimmune diseases.

• Ph.D. (2010-2016) in Computational Biology and Bioinformatics; Jawaharlal Nehru University, New Delhi.
• M.Sc. (2005-2008) in Bioinformatics; University of Allahabad, Allahabad, Uttar Pradesh.
• B.Sc. (2000-2004) in Botany & Chemistry; University of Allahabad, Allahabad, Uttar Pradesh

Publications

• Canner S.W., Shanker S., Gray J.J., “Structure-Based Neural Network Protein-Carbohydrate Interaction Predictions at the Residue Level”, Front. Bioinform. 3, 2023. https://doi.org/10.3389/fbinf.2023.1186531
• Shanker S., Sanner M., “Predicting Protein–Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking”, J. Chem. Inf. Model. 63 (10), 2023. https://doi.org/10.1021/acs.jcim.3c00602

• Li M., Zheng X., Shanker S., Jaroentomeechai T., Kocer I., Byrne J., Cox E.C., Fu Q., Zhang S., Labonte J.W., Gray J.J., DeLisa M.P., “Fine-mapping the consequences of site-specific glycan installation by shotgun scanning glycomutagenesis”, PNAS 118(39) e2107440118, 2021. https://doi.org/10.1073/pnas.2107440118

• Yamamoto T., Arefi H.H., Shanker S., Sato H., and Hiraoka S., “Self-Assembly of Nanocubic Molecular Capsules via Solvent-Guided Formation of Rectangular Blocks”, J. Phys. Chem. Lett. 9(20): 6082-6088, 2018. https://doi.org/10.1021/acs.jpclett.8b02624

• Shanker S., Bandyopadhyay P., “How Mg2+ ion and water network affect the stability and structure of non-Watson-Crick base pairs in E coli Loop E RNA: A Molecular Dynamics and Reference Interaction Site Model (RISM) study”, Journal of Biomolecular Structure and Dynamics 35 (10): 2103-2122, 2017. https://doi.org/10.1080/07391102.2016.1213186

• Shrivastava R., Rakshit A., Shanker S., Vig L., Bandyopadhyay P., “A combination of Monte Carlo Temperature Basin Paving and graph theory: water cluster low energy structures and completeness of search”, Journal of Chemical Sciences: 1-10, 2016. https://doi.org/10.1007/s12039-016-1135-8

• Shanker S., Bandyopadhyay P., “Determination of low energy structures of a small RNA hairpin using Monte Carlo based techniques”, J. Biosciences 37(3): 533-538., 2012. https://doi.org/10.1007/s12038-012-9209-3
• Furtado J.P., Rahalkar A.P., Shanker S., Bandyopadhyay P., Gadre S.R., “Facilitating Minima Search for Large Water Clusters at MP2 level via Molecular Tailoring”, J. Phys. Chem. Lett. 3, 2253-2258, 2012. https://doi.org/10.1021/jz300663u

• Shanker S., Bandyopadhyay P., “Monte Carlo Temperature Basin Paving with Effective Fragment Potential: An Efficient and Fast Method for Finding Low Energy Structures of Water Clusters (H2O)20 and (H2O)25”, J. Phys. Chem. A, 115 (42): 11866-11875., 2011. https://doi.org/10.1021/jp2073864
• Chaturvedi N., Shanker S., Singh V.K., Sinha D., Pandey P.N., “Hidden Markov model for the prediction of transmembrane proteins using MATLAB”, Bioinformation 7(8): 418-421, 2011. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3280443/

Non-Peer Reviewed

• Shanker S., Li M., Zheng X., Labonte J.W., DeLisa M.P., Gray J.J, “Geometric and energy calculations to predict protein stability and activity changes due to site-specific glycosylation”, Glycobiology 30(12): 1110-1110, 2020 : Conference Abstract.

• Shanker S., Bandyopadhyay P., “Interplay of Water molecules and Mg2+ ions in stability of non-Watson-Crick base pairs”, Journal of Biomolecular Structure and Dynamics 33: 57-58, 2015 : Conference Abstract. https://doi.org/10.1080/07391102.2015.1032705

• Postdoc Associate | Scripps Research Institute, La Jolla, USA
  Supervisor: Prof. Michel F. Sanner | 8/2022-11/2023
• Postdoc Researcher | Johns Hopkins University, Baltimore, USA
  Supervisor: Prof. Jeffrey J. Gray | 11/2018-7/2022
• Postdoc Researcher | Kyoto University, Kyoto, Japan
  Supervisor: Prof. Hirofumi Sato, Dr. Takeshi Yamamoto | 10/2016-10/2018

• Developing hybrid methods that integrate deep learning and physics-based approaches for biomolecular interaction analysis.
• Designing and advancing tools for the modeling and study of protein-carbohydrate interactions.
• Exploring the development of carbohydrate-based therapeutics.
• Investigating the role of aberrant glycosylation in autoimmune diseases and cancer.