Ram Samudrala's publications related to therapeutic discovery

These are our publications related to therapeutic discovery. See also a complete list of our publications chronologically ordered or a list organised by areas of research.

  1. Schuler J, Falls Z, Mangione W, Hudson M, Bruggemann L, Samudrala R. Evaluating performance of drug repurposing technologies. Drug Discovery Today 2020. * invited. https://doi.org/10.1101/2020.12.03.410274
  2. Mangione W, Falls Z, Chopra G, Samudrala R. cando.py: Open source software for predictive bioanalytics of large scale drug-protein-disease data. Journal of Chemical Information and Modeling 60: 4131-4136, 2020. *
  3. Mangione W, Falls Z, Melendy T, Chopra G, Samudrala R. Shotgun drug repurposing biotechnology to tackle epidemics and pandemics. Drug Discovery Today 25: 1126-1128, 2020. *
  4. Fine J, Konc J, Samudrala R, Chopra G. CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials. Journal of Chemical Information and Modeling 60: 1509-1527, 2020. *
  5. Fine J, Lackner R, Samudrala R, Chopra G. Computational chemoproteomics to understand the role of selected psychoactives in treating mental health indications. Scientific Reports 9, 1315, 2019. *
  6. Schuler J, Samudrala R. Fingerprinting CANDO: Increased accuracy with structure and ligand based shotgun drug repurposing. ACS Omega 4: 17393-17403, 2019. *
  7. Schuler J, Mangione W, Samudrala R, Ceusters W. Foundations for a realism-based drug repurposing ontology. Proceedings of the 10th International Conference on Biomedical Ontology, 2019.
  8. Falls Z, Mangione W, Schuler J, Samudrala R. Exploration of interaction scoring criteria in the CANDO platform. BMC Research Notes 12: 318, 2019. *
  9. Mangione W, Samudrala R. Identifying protein features responsible for improved drug repurposing accuracies using the CANDO platform: Implications for drug design. Molecules 24: 167, 2019. *
  10. Schuler J, Hudson M, Schwartz D, Samudrala R. A systematic review of computational drug discovery, development, and repurposing for Ebola Virus Disease Treatment. Molecules 22: E1777, 2017.
  11. Chopra C, Kaushik S, Elkin PL, Samudrala R. Combating Ebola with repurposed therapeutics using the CANDO platform. Molecules 21: 1537, 2016. *
  12. Craig JK, Risler JK, Loesch KA, Dong W, Baker D, Barrett LK, Subramanian S, Samudrala R, Van Voorhis WC. Mycobacterium cytidylate kinase appears to be an undruggable target. Journal of Biomolecular Design 21: 695-700, 2016.
  13. Chopra G, Samudrala R. Exploring polypharmacology in drug discovery and repurposing using the CANDO platform. Current Pharmaceutical Design 22: 3109-3123 2016.
  14. Manocheewa S, Mittler JE, Samudrala R, Mullins JI. Composite sequence-structure stability models as screening tools for identifying vulnerable targets for HIV drug and vaccine development. Viruses 7: 5718-5735, 2015.
  15. Sethi G, Chopra G, Samudrala R. Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform. Mini Reviews in Medicinal Chemistry, 15: 705-717, 2015.
  16. Minie M, Chopra G, Sethi G, Horst J, White G, Roy A, Hatti K, Samudrala R. CANDO and the infinite drug discovery frontier. Drug Discovery Today 19: 1353-1363, 2014. *
  17. Lertkiatmongkol P, Assawamakin A, White G, Chopra G, Rongnoparut P, Samudrala R, Tongsima S. Distal effect of amino acid substitutions in CYP2C9 polymorphic variants causes differences in interatomic interactions against (S)-warfarin. PLoS One 8: e74053, 2013.
  18. Strategic protein target analysis for developing drugs to stop dental caries. Horst JA, Pieper U, Sali A, Zhan L, Chopra G, Samudrala R, Featherstone JD. Advances in Dental Research 24: 86-93, 2012. *
  19. Horst JA, Laurenzi A, Bernard B, Samudrala R. Computational multitarget drug discovery. Polypharmacology 263-301, 2012. *
  20. Nicholson CO, Costin JM, Rowe DK, Lin L, Jenwitheesuk E, Samudrala R, Isern S, Michael SF. Viral entry inhibitors block dengue antibody-dependent enhancement in vitro. Antiviral Research 89: 71-74 2010. *
  21. Movahedzadeh F, Balaubramanian V, Bernard B, Iyer S, Samudrala R, Franzblau SG, Balganesh TS. Anti-tuberculosis agents: A rational approach for discovery and development. Genomic and computational tools for emerging infectious diseases, 2010.
  22. Costin JM, Jenwitheesuk E, Lok S-M, Hunsperger E, Conrads KA, Fontaine KA, Rees CR, Rossmann MG, Isern S, Samudrala R, Michael SF. Structural optimization and de novo design of dengue virus entry inhibitory peptides. PLoS Neglected Tropical Diseases 4: e721, 2010. *
  23. Bernard B, Samudrala R. A generalized knowledge-based discriminatory function for biomolecular interactions. Proteins: Structure, Function, and Bioinformatics 76: 115-128, 2009.
  24. Jenwitheesuk E, Horst JA, Rivas K, Van Voorhis WC, Samudrala R. Novel paradigms for drug discovery: Computational multitarget screening. Trends in Pharmacological Sciences 29: 62-71, 2008. [Accompanying cover.] *
  25. Samudrala R, Jenwitheesuk E. Identification of potential HIV-1 targets of minocycline. Bioinformatics 23: 2797-2799, 2007.
  26. Wang K, Mittler J, Samudrala R. Comment on "Evidence for positive epistatis in HIV-1". Science 312: 848b, 2006.
  27. Jenwitheesuk E, Samudrala R. Identification of potential multitarget antimalarial drugs. Journal of the American Medical Association 294: 1490-1491, 2005. *
  28. Jenwitheesuk E, Samudrala R. Heptad-repeat-2 mutations enhance the stability of the enfuvirtide-resistant HIV-1 gp41 hairpin structure. Antiviral Therapy 10: 893-900, 2005. *
  29. Jenwitheesuk E, Wang K, Mittler J, Samudrala R. PIRSpred: A webserver for reliable HIV-1 protein-inhibitor resistance/susceptibility prediction. Trends in Microbiology 13: 150-151, 2005.
  30. Jenwitheesuk E, Samudrala R. Virtual screening of HIV-1 protease inhibitors against human cytomegalovirus protease using docking and molecular dynamics. AIDS 19: 529-533, 2005.
  31. Jenwitheesuk E, Samudrala R. Prediction of HIV-1 protease inhibitor resistance using a protein-inhibitor flexible docking approach. Antiviral Therapy 10: 157-166, 2005.
  32. Jenwitheesuk E, Wang K, Mittler J, Samudrala R. Improved accuracy of HIV-1 genotypic susceptibility interpretation using a consensus approach. AIDS 18: 1858-1859, 2004.
  33. Jenwitheesuk E, Samudrala R. Identifying inhibitors of the SARS coronavirus proteinase. Bioorganic & Medicinal Chemistry Letters 13: 3989-3992, 2003. [Most Cited Paper 2003 - 2006 Award.] *
  34. Jenwitheesuk E, Samudrala R. Improved prediction of HIV-1 protease-inhibitor binding energies by molecular dynamics simulations. BMC Structural Biology 3: 2, 2003. *
  35. Wang K, Jenwitheesuk E, Samudrala R, Mittler J. Simple linear model provides highly accurate genotypic predictions of HIV-1 drug resistance. Antiviral Therapy 9: 343-352, 2004.
  36. Wang K, Samudrala R, Mittler J. Weak agreement between predictions of ``reduced susceptibility'' from Antivirogram and PhenoSense assays. Journal of Clinical Microbiology 42: 2353-2354, 2004.
  37. Wang K, Samudrala R, Mittler J. HIV-1 genotypic drug resistance interpretation algorithms need to include hypersusceptibility mutations. Journal of Infectious Diseases 190: 2055-2056, 2004.
  38. Wang K, Samudrala R, Mittler J. Antivirogram or PhenoSense: a comparison of their reproducibility and an analysis of their correlation. Antiviral Therapy 9: 703-712, 2004.
  39. Protein inhibitor resistance/susceptibility prediction (PIRSpred) web server module
  40. Computational analysis of novel drug opportunities (CANDO) platform

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