Ram Samudrala

Ram Samudrala is a professor of computational biology and bioinformatics at the University at Buffalo, United States.[3] He researches protein folding, structure, function, interaction, design, and evolution.[4]

Ram Samudrala
Born (1972-03-23) March 23, 1972
Alma materOhio Wesleyan University, University of Maryland, Stanford University
Known forProtein structure prediction, free music philosophy
Awards
Scientific career
FieldsComputational biology
InstitutionsUniversity at Buffalo, University of Washington
Doctoral advisorJohn Moult
Other academic advisorsMichael Levitt
Websiteram.org
compbio.org

Education and career

Samudrala received his undergraduate degrees in Computing Science and Genetics from Ohio Wesleyan University as a Wesleyan Scholar, and completed his Ph.D. in Computational Biology with John Moult at the University of Maryland in 1997 as a Life Technologies Fellow.

From 1997-2000, he was a postdoctoral fellow with Michael Levitt at Stanford University. In 2001, Samudrala became the first faculty member to be recruited to the University of Washington under the Advanced Technology Initiative in Infectious Diseases created by the Washington State Legislature "as a bridge between cutting-edge research and education, and new economic activity."[5] He was promoted to associate professor in 2006. In 2014, he became professor and chief of the Division of Bioinformatics at the State University of New York, Buffalo.[6]

Research

Samudrala's research focuses on proteomics and he has regularly taken part in the CASP protein structure prediction challenges since their inception. His work with Moult and Levitt are among the first improvements of blinded protein structure prediction in both comparative and template free modelling categories.[7][8][9] With Moult, he was the first to develop and apply probabilistic and graph-theoretic methods to accurately predict interactions for comparative modelling of protein structures.[10][11] With Levitt, he developed a combined hierarchical approach for de novo structure prediction [12] as well as the Decoys 'R' Us database to evaluate discrimination functions.[13]

At the University of Washington, Samudrala's research group developed a series of algorithms and web server modules to predict protein structure,[14] function,[15] and interactions[16] known as Protinfo.[17][18] The group then applied these methods to organismal proteomes, creating a framework known as the Bioverse[19][20] for exploring the relationships among the atomic, molecular, genomic, proteomic, systems, and organismal worlds. The Bioverse framework performs analyses and predictions based on genomic sequence data to annotate and understand the interaction of protein sequence, structure, and function, both at the single molecule as well as at the systems levels. The framework was used to annotate the finished rice genome sequence published in 2005.[21]

Samudrala's group has also applied these methods to drug discovery, resulting in the Computational Analysis of Novel Drug Opportunities (CANDO) platform which ranks therapeutics for all indications by analysis and comparison of structural compound-proteome interaction signatures.[22][23][24][25] A combination of novel docking methods and/or its use in the CANDO platform has led to prospectively validated predictions of putative drugs against dengue,[26][27] dental caries, herpes, lupus, and malaria[28] along with indication-specific collaborators.[29]

Other areas of application include predicting HIV drug resistance/susceptibility;[30] nanobiotechnology, where small multifunctional peptides that bind to inorganic substrates are designed computationally;[31][32][33] and interactomics of several organisms, including the Nutritious Rice for the World (NRW) project.[34]

Awards and honours

Samudrala received a Searle Scholar Award which funds exceptional young scientists in 2002[1] and was named one of the world's top young innovators (TR100) by MIT Technology Review in 2003,[2][35][36] In 2005, he received a NSF CAREER Award[37] which recognizes "outstanding scientists and engineers who show exceptional potential for leadership at the frontiers of knowledge". In 2008, he received the Alberta Heritage Foundation for Medical Research Visiting Scientist Award and was awarded honorary diplomas from the cities of Casma and Yautan, Peru, for his work on vaccine discovery. In 2010, he received the NIH Director's Pioneer Award for the CANDO drug discovery platform.[23][22] In 2019, Samudrala was presented with a NIH NCATS ASPIRE Design Challenge Award,[38][6] which was followed by a NIH NCATS ASPIRE Reduction-to-Practice Award grand prize presented in 2022.[39] [40] [41]

Personal life

Samudrala is also a musician who has published and recorded work under the pseudonym TWISTED HELICES.[42] In 1994, he published the Free music Philosophy,[43] which predicted how the ease of copying and transmitting digital information by the Internet would lead to unprecedented violations of copyright laws and new models of distribution for music and other digital media.[44][45][46] His work in this area was reported as early as 1997 by diverse media outlets including Billboard,[47] and The New York Times.[48]

References
  1. Searle Scholar Award profile for Ram Samudrala
  2. MIT Technology Review Profile naming Ram Samudrala one of the world's top young innovators
  3. Ram Samudrala's personal web site
  4. Samudrala Computational Biology Group
  5. Roseth B. Funding forward vision. University Week, March 1 2001. Archived 2011-06-04 at the Wayback Machine
  6. Ram Samudrala's curriculum vitae
  7. Samudrala R, Pedersen JT, Zhou H, Luo R, Fidelis K, Moult J. Confronting the problem of interconnected structural changes in the comparative modelling of proteins. Proteins: Structure, Function, and Genetics 23: 327-336, 1995.
  8. Samudrala R, Moult J. Handling context-sensitivity in protein structures using graph theory: bona fide prediction. Proteins: Structure, Function, and Genetics 29S: 43-49, 1997.
  9. Samudrala R, Xia Y, Huang ES, Levitt M. Ab initio prediction of protein structure using a combined hierarchical approach. Proteins: Structure, Function, and Genetics S3: 194-198, 1999.
  10. Samudrala R, Moult J. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. Journal of Molecular Biology 275: 893-914, 1998.
  11. Samudrala R, Moult J. A graph-theoretic algorithm for comparative modelling of protein structure. Journal of Molecular Biology 279: 287-302, 1998.
  12. Xia Y, Huang ES, Levitt M, Samudrala R. Ab initio construction of protein tertiary structures using a hierarchical approach. Journal of Molecular Biology 300: 171-185, 2000.
  13. Samudrala R, Levitt M. Decoys 'R' Us: A database of incorrect protein conformations to improve protein structure prediction. Protein Science 9: 1399-1401, 2000.
  14. Liu T, Horst J, Samudrala R. A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction. Proteins: Structure, Function, and Bioinformatics 77: 220-234, 2009.
  15. Wang K, Horst J, Cheng G, Nickle D, Samudrala R. Protein meta-functional signatures from combining sequence, structure, evolution and amino acid property information. PLoS Computational Biology 4: e1000181, 2008.
  16. Kittichotirat W, Guerquin M, Bumgarner R, Samudrala R. Protinfo PPC: A web server for atomic level prediction of protein complexes. Nucleic Acids Research 37: W519-W525, 2009.
  17. Hung L-H, Samudrala R. PROTINFO: Secondary and tertiary protein structure prediction. Nucleic Acids Research 31: 3296-3299, 2003.
  18. Hung L-H, Ngan S-C, Liu T, Samudrala R. PROTINFO: New algorithms for enhanced protein structure prediction. Nucleic Acids Research 33: W77-W80, 2005.
  19. McDermott J, Samudrala R. BIOVERSE: Functional, structural, and contextual annotation of proteins and proteomes. Nucleic Acids Research 31: 3736-3737, 2003.
  20. McDermott J, Guerquin M, Frazier Z, Chang AN, Samudrala R. BIOVERSE: Enhancements to the framework for structural, functional, and contextual annotations of proteins and proteomes. Nucleic Acids Research 33: W324-W325, 2005.
  21. Yu J, Wang J, Lin W, Li S, Li H, Zhou J, ..., McDermott J, Samudrala R, Wang J, Wong GK. The genomes of Oryza sativa: A history of duplications. PLoS Biology 3: e38, 2005.
  22. 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.
  23. Computational analysis of novel drug opportunities (CANDO)
  24. 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, 2015. in press.
  25. Horst JA, Laurenzi A, Bernard B, Samudrala R. Computational multitarget drug discovery. "Polypharmacology "263-301, 2012.
  26. 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.
  27. 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, 2011.
  28. 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.
  29. Computational analysis of novel drug opportunities (CANDO) indications and collaborations
  30. 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.
  31. Cementomimetics-constructing a cementum-like biomineralized microlayer via amelogenin-derived peptides. Gungormus M, Oren EE, Horst JA, Fong H, Hnilova M, Somerman MJ, Snead ML, Samudrala R, Tamerler C, Sarikaya M. International Journal of Oral Sciences 2: 69-77, 2012.
  32. Oren EE, Tamerler C, Sahin D, Hnilova M, Seker UOS, Sarikaya M, Samudrala R. A novel knowledge-based approach for designing inorganic binding peptides. Bioinformatics 23: 2816-2822, 2007.
  33. Evans JS, Samudrala R, Walsh TR, Oren EE, Tamerler C. Molecular design of inorganic-binding polypeptides. MRS Bulletin 33: 514-518, 2008.
  34. Nutritious Rice for the World web site
  35. Kurian V. 10 Indian innovators in MIT list. The Hindu Business Line, October 4 2003.
  36. 10 of Indian Origin in MIT's Technology Review. Hindustan Times, March 1 2007. Archived 2010-08-23 at the Wayback Machine
  37. CAREER Award
  38. NIH HEAL Initiative issues awards to UB researchers to develop non-addictive painkillers, September 30 2019.
  39. "2020 NCATS ASPIRE Reduction-to-Practice Challenge Winners". NIH. October 28, 2021. Retrieved May 5, 2023.
  40. "Jacobs School Researchers Capture ASPIRE Challenge". University at Buffalo. February 21, 2023. Retrieved July 21, 2023.
  41. "Samudrala, Falls Get Funding for Various Research Projects". University at Buffalo. April 4, 2023. Retrieved July 21, 2023.
  42. TWISTED HELICES
  43. Free Music Philosophy
  44. Samudrala R. The future of music, 1997
  45. Story of a Revolution: Napster & the Music Industry. MusicDish, 2000
  46. Schulman BM. The song heard 'round the world: The copyright implications of MP3s and the future of digital music. Harvard Journal of Law and Technology 12: 3, 1999. Archived 2012-04-09 at the Wayback Machine
  47. Reece D. Industry grapples with MP3 dilemma. Billboard, July 18 1998.
  48. Napoli L. Fans of MP3 forced the issue. The New York Times, December 16 1998.
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