ICBDD 2025

1) Resources, Citations, other Supporting Information

Predict Drug-Resistant Mutations

Rhapsody-2

• Banerjee A, Bogetti AT, Bahar I. Accurate identification and mechanistic evaluation of pathogenic missense variants with Rhapsody-2. Proc Natl Acad Sci U S A. 2025 May 6;122(18):e2418100122. doi: 10.1073/pnas.2418100122. Epub 2025 May 2. PMID: 40314982; PMCID: PMC12067267.
• L. Ponzoni, & I. Bahar, Structural dynamics is a determinant of the functional significance of missense variants, Proc. Natl. Acad. Sci. U.S.A. 115 (16) 4164-4169, https://doi.org/10.1073/pnas.1715896115 (2018).
• Luca Ponzoni, Daniel A Peñaherrera, Zoltán N Oltvai, Ivet Bahar, Rhapsody: predicting the pathogenicity of human missense variants, Bioinformatics, Volume 36, Issue 10, May 2020, Pages 3084–3092, https://doi.org/10.1093/bioinformatics/btaa127
• Rhapsody server

Direct Coupling Analysis

• Potts Model Visualized
• GitHub Code
• Balakrishnan, S., Kamisetty, H., Carbonell, J. G., Lee, S. I., & Langmead, C. J. (2011). Learning generative models for protein fold families. Proteins: Structure, Function, and Bioinformatics, 79(4), 1061-1078.
• Ekeberg, M., Lövkvist, C., Lan, Y., Weigt, M., & Aurell, E. (2013). Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models. Physical Review E, 87(1), 012707.
• Hopf, T. A., Ingraham, J. B., Poelwijk, F. J., Schärfe, C. P., Springer, M., Sander, C., & Marks, D. S. (2017). Mutation effects predicted from sequence co-variation. Nature Biotechnology, 35(2), 128-135.
• Liu, D.C., Nocedal, J. On the limited memory BFGS method for large scale optimization. Mathematical Programming 45, 503–528 (1989). https://doi.org/10.1007/BF01589116
• Buchfink, B., Reuter, K. & Drost, HG. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods 18, 366–368 (2021). https://doi.org/10.1038/s41592-021-01101-x

Drug-Resistant Mutations

• Soverini, S., Abruzzese, E., Bocchia, M. et al. Next-generation sequencing for BCR-ABL1 kinase domain mutation testing in patients with chronic myeloid leukemia: a position paper. J Hematol Oncol 12, 131 (2019).
• Experimental and clinical evidence of asciminib-resistant mutations provided by our collaborator, Neil Shah M.D. Ph.D. (UCSF)

Counter Drug Resistance through Allostery

• Leyte-Vidal, A., DeFilippis, R., Outhwaite, I.R. et al. Absence of ABL1 exon 2-encoded SH3 residues in BCR::ABL1 destabilizes the autoinhibited kinase conformation and confers resistance to asciminib. Leukemia 38, 2046–2050 (2024). https://doi.org/10.1038/s41375-024-02353-0

Movies

MD tracjectory reveals SH3 domain disscoation :

zt4_ztrj5.mp4

MD tracjectory reveals SH3 domain disscoation :

zt1_ztrj5.mp4

AlphaFold

• Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021). https://doi.org/10.1038/s41586-021-03819-2

ProDy

• Zhang S, Krieger JM, Zhang Y, Kaya C, Kaynak B, Mikulska-Ruminska K, Doruker P, Li H, Bahar I ProDy 2.0: Increased scale and scope after 10 years of protein dynamics modelling with Python 2021 Bioinformatics 37(20):3657-3659
• Bakan A, Meireles LM, Bahar I ProDy: Protein Dynamics Inferred from Theory and Experiments 2011 Bioinformatics 27(11):1575-1577
• Bakan A, Dutta A, Mao W, Liu Y, Chennubhotla C, Lezon TR, Bahar I Evol and ProDy for Bridging Protein Sequence Evolution and Structural Dynamics 2014 Bioinformatics 30(18):2681-2683

Elastic Network Model

• Anisotropy of fluctuation dynamics of proteins with an elastic network model. Atilgan, AR, Durrell, SR, Jernigan, RL, Demirel, MC, Keskin, O. & Bahar, I. Biophys. J. 80, 505-515, (2001).
• Eyal E,Lum G, Bahar I (2015) The anisotropic Network Model web server at 2015 (ANM 2.0), Bioinformatics 31:1487-9
• Interactive ANM Server

Essential Site Scanning Analysis

• Kaynak B.T., Bahar I., Doruker P. Essential site scanning analysis: A new approach for detecting sites that modulate the dispersion of protein global motions Comput Struct Biotechnol J 2020 18:1577–1586.

Druggability Simulation

• Bakan A, Nevins N, Lakdawala AS, Bahar I Druggability Assessment of Allosteric Proteins by Dynamics Simulations in the Presence of Probe Molecules J Chem Theory Comput 2012 8(7):2435-2447.

Pharmmaker

• Lee JY, Li H, Krieger JM, Bahar I Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations 2019 Protein Science 29(1):76-86

2) Funding Support

• Medical Scientist Training Program (T32-GM158461)
• Chemical Biology Training Program (T32-GM136572)

3) Acknowledgement

• Seeliger Group at Stony Brook University
• Shah Group at UCSF