Research Summary

My research and training efforts are geared toward applications of computation to drug discovery, with an emphasis on making use of multiple methods and data types, exploiting synergy between protein structural data, chemical/target annotation information, and ligand binding affinity data. My laboratory has a particular focus on cancer-related therapeutic discovery, as are part of many collaborators that make use of our computational methods.

I have been at the forefront of computer-aided drug discovery (CADD) since the early 1990's, beginning in biotechnology start-ups such as Arris Pharmaceutical and continuing for over 20 years at UCSF. The central areas of research in the lab are: (1) methods for docking small molecules to proteins using empirically derived scoring functions; (2) methods for inducing the shape of a protein binding pocket given the structures and affinities of ligands that bind the pocket competitively; (3) generalized surface-based approaches to computing molecular similarity, both among small molecules and among proteins; and (4) approaches for very fast conformational search, including macrocycles, optionally including context from NMR restraints or fitting X-ray density maps. All of the approaches share their roots in the use of sophisticated computational algorithms involving object representation, function optimization, and search. My formal training at the PhD-level in Computer Science has been a distinct advantage in this work.

The following highlight recent work that is particularly relevant to the themes within the lab: synergy of diverse methods and data types for drug discovery. (1) We made use of a fast generalization of our ligand-based similarity approach (looking at small molecule surfaces from the outside) to instead quantify the similarity of protein binding sites (by looking at binding cavities from the inside). This approach (called PSIM) was shown to support characterization of proteins of unknown function. Using PSIM combined with other data, we developed hybrid approaches for (2) ligand affinity prediction, (3) prediction of polypharmacology, and (4) bioactive small molecule pose prediction.

Research Funding

  • August 5, 1999 - May 31, 2023 - Cancer Center Support Grant , Co-Investigator . Sponsor: NIH, Sponsor Award ID: P30CA082103
  • January 1, 2013 - March 31, 2021 - Binding-Site Modeling with Multiple-Instance Machine-Learning , Principal Investigator . Sponsor: NIH, Sponsor Award ID: R01GM101689
  • July 1, 2005 - June 30, 2015 - Data-Driven Approaches for Molecular Docking , Principal Investigator . Sponsor: NIH, Sponsor Award ID: R01GM070481

Education

University of Minnesota, St. Paul, MN, BS, 1986, Biochemistry
University of Minnesota, Minneapolis, MN, BS, 1986, Computer Science
Carnegie Mellon University, Pittsburgh, PA, MS, 1989, Computer Science
Carnegie Mellon University, Pittsburgh, PA, PhD, 1991, Computer Science

Honors & Awards

  • 2010
    Levinthal Lecturer, Eleventh International CUP Symposium in Molecular Modeling

Selected Publications

  1. Samaddar A, van Nispen J, Armstrong A, Song E, Voigt M, Murali V, Krebs J, Manithody C, Denton C, Ericsson AC, Jain AK. Lower systemic inflammation is associated with gut firmicutes dominance and reduced liver injury in a novel ambulatory model of parenteral nutrition. Ann Med. 2022 Dec; 54(1):1701-1713.  View on PubMed
  2. Gao Q, Cleves AE, Wang X, Liu Y, Bowen S, Williamson RT, Jain AN, Sherer E, Reibarkh M. Solution cis-Proline Conformation of IPCs Inhibitor Aureobasidin A Elucidated via NMR-Based Conformational Analysis. J Nat Prod. 2022 May 27.  View on PubMed
  3. Yadav J, Das S, Karthikeyan D, Chug R, Jyoti A, Srivastava VK, Jain A, Kumar S, Sharma V, Kaushik S. Identification of Protein drug targets of Biofilm formation and Quorum sensing in multidrug resistant Enterococcus faecalis. Curr Protein Pept Sci. 2022 May 26.  View on PubMed
  4. Warren A, McCarthy C, Andiapen M, Crouch M, Finney S, Hamilton S, Jain A, Jones D, Proudfoot A. Early quantitative infrared pupillometry for prediction of neurological outcome in patients admitted to intensive care after out-of-hospital cardiac arrest. Br J Anaesth. 2022 05; 128(5):849-856.  View on PubMed
  5. Demir OM, Little CD, Jabbour R, Rahman H, Sayers M, Ahmed A, Connolly MJ, Kanyal R, MacCarthy P, Wilson SJ, Dalby M, Jain A, Malik I, Rakhit R, Perera D. Impact of COVID-19 pandemic on the management of nonculprit lesions in patients presenting with ST-elevation myocardial infarction: Outcomes from the pan-London heart attack centers. Catheter Cardiovasc Interv. 2022 02; 99(2):391-396.  View on PubMed
  6. Rathod KS, Comer K, Casey-Gillman O, Moore L, Mills G, Ferguson G, Antoniou S, Patel R, Fhadil S, Damani T, Wright P, Ozkor M, Das D, Guttmann OP, Baumbach A, Archbold RA, Wragg A, Jain AK, Choudry FA, Mathur A, Jones DA. Early Hospital Discharge Following PCI for Patients With STEMI. J Am Coll Cardiol. 2021 12 21; 78(25):2550-2560.  View on PubMed
  7. Jones TN, Kelham M, Rathod KS, Knight CJ, Proudfoot A, Jain AK, Wragg A, Ozkor M, Rees P, Guttmann O, Baumbach A, Mathur A, Jones DA. Validation of the CREST score for predicting circulatory-aetiology death in out-of-hospital cardiac arrest without STEMI. Am J Cardiovasc Dis. 2021; 11(6):723-733.  View on PubMed
  8. Cleves AE, Johnson SR, Jain AN. Synergy and Complementarity between Focused Machine Learning and Physics-Based Simulation in Affinity Prediction. J Chem Inf Model. 2021 12 27; 61(12):5948-5966.  View on PubMed
  9. Frain K, Rathod KS, Tumi E, Chen Y, Hamshere S, Choudry F, Akhtar MM, Curtis M, Amersey R, Guttmann O, O'Mahony C, Jain A, Wragg A, Baumbach A, Mathur A, Jones DA, Rees P. The impact of the COVID-19 pandemic on the delivery of primary percutaneous coronary intervention in STEMI. Am J Cardiovasc Dis. 2021; 11(5):647-658.  View on PubMed
  10. Rathod KS, Jones DA, Jain AK, Lim P, MacCarthy PA, Rakhit R, Lockie T, Kalra S, Dalby MC, Malik IS, Whitbread M, Firoozi S, Bogle R, Redwood S, Cooper J, Gupta A, Lansky A, Wragg A, Mathur A, Ahluwalia A. The influence of biological age and sex on long-term outcome after percutaneous coronary intervention for ST-elevation myocardial infarction. Am J Cardiovasc Dis. 2021; 11(5):659-678.  View on PubMed
  11. Srivastava VK, Kaushik S, Bhargava G, Jain A, Saxena J, Jyoti A. A Bioinformatics Approach for the Prediction of Immunogenic Properties and Structure of the SARS-COV-2 B.1.617.1 Variant Spike Protein. Biomed Res Int. 2021; 2021:7251119.  View on PubMed
  12. Sanghvi K, Wang Y, Daemen J, Mathur A, Jain A, Dohad S, Sapoval M, Azizi M, Mahfoud F, Lurz P, Sayer J, Levy T, Zagoria R, Loening AM, Coleman L, Craig D, Horesh-Bar M, Kirtane AJ. Renal artery variations in patients with mild-to-moderate hypertension from the RADIANCE-HTN SOLO trial. Cardiovasc Revasc Med. 2021 Sep 30.  View on PubMed
  13. Brueckner AC, Deng Q, Cleves AE, Lesburg CA, Alvarez JC, Reibarkh MY, Sherer EC, Jain AN. Conformational Strain of Macrocyclic Peptides in Ligand-Receptor Complexes Based on Advanced Refinement of Bound-State Conformers. J Med Chem. 2021 03 25; 64(6):3282-3298.  View on PubMed
  14. Jain AN, Cleves AE, Brueckner AC, Lesburg CA, Deng Q, Sherer EC, Reibarkh MY. XGen: Real-Space Fitting of Complex Ligand Conformational Ensembles to X-ray Electron Density Maps. J Med Chem. 2020 09 24; 63(18):10509-10528.  View on PubMed
  15. Cleves AE, Jain AN. Structure- and Ligand-Based Virtual Screening on DUD-E+: Performance Dependence on Approximations to the Binding Pocket. J Chem Inf Model. 2020 09 28; 60(9):4296-4310.  View on PubMed
  16. Cleves AE, Johnson SR, Jain AN. Electrostatic-field and surface-shape similarity for virtual screening and pose prediction. J Comput Aided Mol Des. 2019 10; 33(10):865-886.  View on PubMed
  17. Jain AN, Cleves AE, Gao Q, Wang X, Liu Y, Sherer EC, Reibarkh MY. Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen. J Comput Aided Mol Des. 2019 06; 33(6):531-558.  View on PubMed
  18. Cleves AE, Jain AN. Quantitative surface field analysis: learning causal models to predict ligand binding affinity and pose. J Comput Aided Mol Des. 2018 07; 32(7):731-757.  View on PubMed
  19. Cleves AE, Jain AN. ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs. J Comput Aided Mol Des. 2017 May; 31(5):419-439.  View on PubMed
  20. Cleves AE, Jain AN. Extrapolative prediction using physically-based QSAR. J Comput Aided Mol Des. 2016 Feb; 30(2):127-52.  View on PubMed

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