Shailesh Kumar Panday

Position

Postdoctoral Associate

Address

Stephenson Life Sciences Research Center 3005, 101 Stephenson Parkway, Norman, OK 73019-5251, USA

Phone

+1-864-207-0387

E-mail

shaileshp51 at gmail.com





RESEARCH INTERESTS

Molecular modeling of biomolecular interaction processes and development and implementation of novel techniques for simulation of biological macromolecule


EDUCATION & EMPLOYMENT


2003-2006 B. Sc. (Physics, Chemistry and Mathmetics), V.B.S.P.U. Jaunpur, UP, India



2006-2009 M.C.A. G.B.T.U, Lucknow, India



2011-2013 M.Tech. (Computational and Systems Biology), Jawaharlal Nehru University, New Delhi, India



2013-2019, PhD (Computational Biology and Bioinformatics), Jawaharlal Nehru University, New Delhi, India



March 2019-Feb 2022, Post Doctoral Research Associate, Clemson University, Clemson, SC, USA



March 2022-, Post Doctoral Research Associate, University of Oklahoma, Norman, OK, USA



PUBLICATIONS

  1. Khan, T.; Panday, S. K.; Ghosh, I. ProLego: Tool for Extracting and Visualizing Topological Modules in Protein Structures. BMC Bioinformatics 2018, 19 (1), 167. https://doi.org/10.1186/s12859-018-2171-9.
  2. Panday, S. K.; Sturlese, M.; Salmaso, V.; Ghosh, I.; Moro, S. Coupling Supervised Molecular Dynamics (SuMD) with Entropy Estimations To Shine Light on the Stability of Multiple Binding Sites. ACS Med. Chem. Lett. 2019, 10 (4), 444–449. https://doi.org/10.1021/acsmedchemlett.8b00490.
  3. Li, C.; Jia, Z.; Chakravorty, A.; Pahari, S.; Peng, Y.; Basu, S.; Koirala, M.; Panday, S. K.; Petukh, M.; Li, L.; Alexov, E. DelPhi Suite: New Developments and Review of Functionalities. J. Comput. Chem. 2019, 40 (28), 2502–2508. https://doi.org/10.1002/jcc.26006.
  4. Panday, S. K.; Shashikala, M. H. B.; Chakravorty, A.; Zhao, S.; Alexov, E. Reproducing Ensemble Averaged Electrostatics with Super-Gaussian-Based Smooth Dielectric Function: Application to Electrostatic Component of Binding Energy of Protein Complexes. Commun. Inf. Syst. 2019, 19 (4), 405–423. https://doi.org/10.4310/CIS.2019.v19.n4.a4.
  5. Chakravorty, A.; Panday, S.; Pahari, S.; Zhao, S.; Alexov, E. Capturing the Effects of Explicit Waters in Implicit Electrostatics Modeling: Qualitative Justification of Gaussian-Based Dielectric Models in DelPhi. J. Chem. Inf. Model. 2020, 60 (4), 2229–2246. https://doi.org/10.1021/acs.jcim.0c00151.
  6. Panday, S. K.; Ghosh, I. Application and Comprehensive Analysis of Neighbor Approximated Information Theoretic Configurational Entropy Methods to Protein-Ligand Binding Cases. J. Chem. Theory Comput. 2020, 16 (12), 7581–7600. https://doi.org/10.1021/acs.jctc.0c00764.
  7. Shashikala, H. B. M.; Chakravorty, A.; Panday, S. K.; Alexov, E. BION-2: Predicting Positions of Non-Specifically Bound Ions on Protein Surface by a Gaussian-Based Treatment of Electrostatics. Int. J. Mol. Sci. 2020, 22 (1), 272. https://doi.org/10.3390/ijms22010272.
  8. Li, G.; Panday, S. K.; Alexov, E. SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability. Int. J. Mol. Sci. 2021, 22 (2), 606. https://doi.org/10.3390/ijms22020606.
  9. Li, G.; Panday, S. K.; Peng, Y.; Alexov, E. SAMPDI-3D: Predicting the Effects of Protein and DNA Mutations on Protein–DNA Interactions. Bioinformatics 2021, No. August, 1–6. https://doi.org/10.1093/bioinformatics/btab567.
  10. Panday, S. K.; Ghosh, I. In Silico Structure-Based Prediction of Receptor–Ligand Binding Affinity: Current Progress and Challenges. In Challenges and Advances in Computational Chemistry and Physics; 2019; Vol. 27, pp 109–175. https://doi.org/10.1007/978-3-030-05282-9_5.