Michael Keiser, PhD

Associate Professor
Institute for Neurodegenerative Diseases
Keiser
[email protected]
Phone: +1 415 886-7651
675 Nelson Rising Lane, Rm 416A
UCSF Box 0518
San Francisco, CA 94158
United States

Links

Keiser Lab UCSF Profiles

Affiliations

Joint appointments

Department of Pharmaceutical Chemistry

External affiliations

Founder and COO, SeaChange Pharmaceuticals, Inc.

What I do

Our group investigates how drugs affect entire networks of proteins in the body at once to achieve their therapeutic effects, via computational predictions paired with experimental testing.

Departmental research area

computational biology and chemistry
chemical biology and medicinal chemistry

My research expertise

systems pharmacology, machine learning, forward polypharmacology, computational chemical biology, neurodegeneration, adverse drug reactions, network structure, chemical-genetic epistasis

Professional background

Degrees

PhD, Bioinformatics, University of California, San Francisco, 2009
Bachelors in Arts and Sciences, Slavic language and Literature/Computer Science, Stanford University, 2004
Masters, Russian and Eurasian Studies, Stanford University, 2004

Biography

Our lab investigates how small molecules perturb protein target networks to biological and therapeutic effect. In a forward polypharmacology campaign, we are using machine learning and computational methods such as the Similarity Ensemble Approach (SEA) to infer new combinations of targets underlying compound-induced phenotypes in cells and broader model systems. Thinking of each target as a musical note, we predict and test entire chords at a time via chemical-genetic epistasis experiments in models of complex diseases such as neurodegeneration.

These systems pharmacology inquiries tell us where current understanding of drug action is weak, and because we use human pharmacology to mine for mechanisms, we can apply the therapeutic chords we find directly to the prediction of patient drug responses, adverse drug reactions, and personalized medicine.

Research keywords

  • proteins
  • machine learning
  • Cerebral Amyloid Angiopathy
  • Organic Chemicals
  • Molecular Conformation
  • Amyloidogenic Proteins
  • Pharmaceutical Preparations
  • Small Molecule Libraries
  • Ligands
  • Preclinical Drug Evaluation
  • Drug Discovery
  • Adrenergic beta-1 Receptor Antagonists
  • Chemistry, Pharmaceutical
  • Plaque, Amyloid
  • Paroxetine
1. Creating Healthy and Inclusive Spaces – Equity and Inclusion Speaker Series
2. Update from the Dean – May 2019
3. Training computers to think more like scientists
4. Keiser receives $2.5 million to apply machine learning towards new therapies for Alzheimer’s, Parkinson’s
5. Shoichet receives DeLano Award for Computational Biosciences
6. Update from the Dean - Fall/Winter 2015
7. Most recent School of Pharmacy primary faculty hires, by department
8. Update from the Dean - Fall/Winter 2014
9. Computer models successfully predict drug side effects
1. Ben Barres Early Career Acceleration Award, Chan Zuckerberg Initiative, 2018
2. New Frontier Research Award, UCSF Program for Breakthrough Biomedical Research, 2016
3. Allen Distinguished Investigator, Paul G. Allen Family Foundation, 2015
4. Award for Research in Biological Mechanisms of Aging, Glenn Foundation, 2014
5. 40 Under Forty, SF Business Times, 2014
6. Frank M Goyan Award, UCSF, 2010
7. Top 10 Scientific Breakthroughs of 2009, Wired, 2009
8. Graduate Research Fellow, NSF, 2006-2009
9. Foreign Languages and Area Studies Fellow, US Dept. Education, 2003-2004

Publications

Connell W, Garcia K, Goodarzi H, Keiser MJ. Learning chemical sensitivity reveals mechanisms of cellular response. bioRxiv. 2023 Aug 28.
Wong DR, Magaki SD, Vinters HV, Yong WH, Monuki ES, Williams CK, Martini AC, DeCarli C, Khacherian C, Graff JP, Dugger BN, Keiser MJ. Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. Commun Biol. 2023 Jun 24; 6(1):668.
Morris JH, Soman K, Akbas RE, Zhou X, Smith B, Meng EC, Huang CC, Cerono G, Schenk G, Rizk-Jackson A, Harroud A, Sanders L, Costes SV, Bharat K, Chakraborty A, Pico AR, Mardirossian T, Keiser M, Tang A, Hardi J, Shi Y, Musen M, Israni S, Huang S, Rose PW, Nelson CA, Baranzini SE. The scalable precision medicine open knowledge engine (SPOKE): a massive knowledge graph of biomedical information. Bioinformatics. 2023 02 03; 39(2).
Wong DR, Magaki SD, Vinters HV, Yong WH, Monuki ES, Williams CK, Martini AC, DeCarli C, Khacherian C, Graff JP, Dugger BN, Keiser MJ. Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels. bioRxiv. 2023 Jan 17.
Fassio AV, Shub L, Ponzoni L, McKinley J, O'Meara MJ, Ferreira RS, Keiser MJ, de Melo Minardi RC. Prioritizing Virtual Screening with Interpretable Interaction Fingerprints. J Chem Inf Model. 2022 09 26; 62(18):4300-4318.
Wong DR, Conrad J, Johnson N, Ayers J, Laeremans A, Lee JC, Lee J, Prusiner SB, Bandyopadhyay S, Butte AJ, Paras NA, Keiser MJ. Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics. Nat Mach Intell. 2022 Jun; 4(6):583-595.
Wong DR, Tang Z, Mew NC, Das S, Athey J, McAleese KE, Kofler JK, Flanagan ME, Borys E, White CL, Butte AJ, Dugger BN, Keiser MJ. Deep learning from multiple experts improves identification of amyloid neuropathologies. Acta Neuropathol Commun. 2022 04 28; 10(1):66.
Baranzini SE, Börner K, Morris J, Nelson CA, Soman K, Schleimer E, Keiser M, Musen M, Pearce R, Reza T, Smith B, Herr BW, Oskotsky B, Rizk-Jackson A, Rankin KP, Sanders SJ, Bove R, Rose PW, Israni S, Huang S. A biomedical open knowledge network harnesses the power of AI to understand deep human biology. AI Mag. 2022; 43(1):46-58.
Young AT, Fernandez K, Pfau J, Reddy R, Cao NA, von Franque MY, Johal A, Wu BV, Wu RR, Chen JY, Fadadu RP, Vasquez JA, Tam A, Keiser MJ, Wei ML. Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models. NPJ Digit Med. 2021 Jan 21; 4(1):10.
Cáceres EL, Mew NC, Keiser MJ. Adding Stochastic Negative Examples into Machine Learning Improves Molecular Bioactivity Prediction. J Chem Inf Model. 2020 12 28; 60(12):5957-5970.
J. Pfau, A.T. Young, M. Wei, M.J. Keiser. 383 Assessing deep learning artefact bias using global saliency. Journal of Investigative Dermatology. 2020 Jul 1; 140(7):s49.
A.T. Young, J. Pfau, M.J. Keiser, M. Wei. 836 Calibration performance of deep neural networks for image classification declines on real-world, versus curated, test sets. Journal of Investigative Dermatology. 2020 Jul 1; 140(7):s109.
A.T. Young, J. Pfau, M.J. Keiser, M. Wei. 902 Assessing performance of deep neural networks used for image classification by stress testing. Journal of Investigative Dermatology. 2020 Jul 1; 140(7):s119.
Chuang KV, Gunsalus LM, Keiser MJ. Learning Molecular Representations for Medicinal Chemistry. J Med Chem. 2020 08 27; 63(16):8705-8722.
Vizcarra JC, Gearing M, Keiser MJ, Glass JD, Dugger BN, Gutman DA. Validation of machine learning models to detect amyloid pathologies across institutions. Acta Neuropathol Commun. 2020 04 28; 8(1):59.
Young AT, Xiong M, Pfau J, Keiser MJ, Wei ML. Artificial Intelligence in Dermatology: A Primer. J Invest Dermatol. 2020 08; 140(8):1504-1512.
Kober KM, Lee MC, Olshen A, Conley YP, Sirota M, Keiser M, Hammer MJ, Abrams G, Schumacher M, Levine JD, Miaskowski C. Differential methylation and expression of genes in the hypoxia-inducible factor 1 signaling pathway are associated with paclitaxel-induced peripheral neuropathy in breast cancer survivors and with preclinical models of chemotherapy-induced neuropathic pain. Mol Pain. 2020 Jan-Dec; 16:1744806920936502.
McCarroll MN, Gendelev L, Kinser R, Taylor J, Bruni G, Myers-Turnbull D, Helsell C, Carbajal A, Rinaldi C, Kang HJ, Gong JH, Sello JK, Tomita S, Peterson RT, Keiser MJ, Kokel D. Zebrafish behavioural profiling identifies GABA and serotonin receptor ligands related to sedation and paradoxical excitation. Nat Commun. 2019 09 09; 10(1):4078.
Tang Z, Chuang KV, DeCarli C, Jin LW, Beckett L, Keiser MJ, Dugger BN. Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline. Nat Commun. 2019 05 15; 10(1):2173.
Chuang KV, Keiser MJ. Comment on "Predicting reaction performance in C-N cross-coupling using machine learning". Science. 2018 11 16; 362(6416).
Chuang KV, Keiser MJ. Adversarial Controls for Scientific Machine Learning. ACS Chem Biol. 2018 10 19; 13(10):2819-2821.
Willsey AJ, Morris MT, Wang S, Willsey HR, Sun N, Teerikorpi N, Baum TB, Cagney G, Bender KJ, Desai TA, Srivastava D, Davis GW, Doudna J, Chang E, Sohal V, Lowenstein DH, Li H, Agard D, Keiser MJ, Shoichet B, von Zastrow M, Mucke L, Finkbeiner S, Gan L, Sestan N, Ward ME, Huttenhain R, Nowakowski TJ, Bellen HJ, Frank LM, Khokha MK, Lifton RP, Kampmann M, Ideker T, State MW, Krogan NJ. The Psychiatric Cell Map Initiative: A Convergent Systems Biological Approach to Illuminating Key Molecular Pathways in Neuropsychiatric Disorders. Cell. 2018 07 26; 174(3):505-520.
Kangway Chuang, Ziqi Tang, Michael Keiser, Laurel Beckett, Charlie S. DeCarli, Lee-Way Jin, Brittany N. Dugger. THE USE OF CONVOLUTIONAL NEURAL NETWORKS TO QUANTIFY AMYLOID PLAQUES IN POSTMORTEM HUMAN BRAIN. Alzheimer's & Dementia. 2018 Jul 1; 14(7):p1446.
Irwin JJ, Gaskins G, Sterling T, Mysinger MM, Keiser MJ. Predicted Biological Activity of Purchasable Chemical Space. J Chem Inf Model. 2018 01 22; 58(1):148-164.
Hindle SJ, Munji RN, Dolghih E, Gaskins G, Orng S, Ishimoto H, Soung A, DeSalvo M, Kitamoto T, Keiser MJ, Jacobson MP, Daneman R, Bainton RJ. Evolutionarily Conserved Roles for Blood-Brain Barrier Xenobiotic Transporters in Endogenous Steroid Partitioning and Behavior. Cell Rep. 2017 Oct 31; 21(5):1304-1316.
Axen SD, Huang XP, Cáceres EL, Gendelev L, Roth BL, Keiser MJ. A Simple Representation of Three-Dimensional Molecular Structure. J Med Chem. 2017 09 14; 60(17):7393-7409.
Bruni G, Rennekamp AJ, Velenich A, McCarroll M, Gendelev L, Fertsch E, Taylor J, Lakhani P, Lensen D, Evron T, Lorello PJ, Huang XP, Kolczewski S, Carey G, Caldarone BJ, Prinssen E, Roth BL, Keiser MJ, Peterson RT, Kokel D. Zebrafish behavioral profiling identifies multitarget antipsychotic-like compounds. Nat Chem Biol. 2016 07; 12(7):559-66.
Ruderfer DM, Charney AW, Readhead B, Kidd BA, Kähler AK, Kenny PJ, Keiser MJ, Moran JL, Hultman CM, Scott SA, Sullivan PF, Purcell SM, Dudley JT, Sklar P. Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach. Lancet Psychiatry. 2016 Apr; 3(4):350-7.
McCarroll MN, Gendelev L, Keiser MJ, Kokel D. Leveraging Large-scale Behavioral Profiling in Zebrafish to Explore Neuroactive Polypharmacology. ACS Chem Biol. 2016 Apr 15; 11(4):842-9.
Yee SW, Lin L, Merski M, Keiser MJ, Gupta A, Zhang Y, Chien HC, Shoichet BK, Giacomini KM. Prediction and validation of enzyme and transporter off-targets for metformin. J Pharmacokinet Pharmacodyn. 2015 Oct; 42(5):463-75.
Michael J. Keiser. In Silico Prediction of Drug Side Effects. Antitargets and Drug Safety. 2015 Apr 22; 19-44.
Lorberbaum T, Nasir M, Keiser MJ, Vilar S, Hripcsak G, Tatonetti NP. Systems pharmacology augments drug safety surveillance. Clin Pharmacol Ther. 2015 Feb; 97(2):151-8.
Lemieux GA, Keiser MJ, Sassano MF, Laggner C, Mayer F, Bainton RJ, Werb Z, Roth BL, Shoichet BK, Ashrafi K. In silico molecular comparisons of C. elegans and mammalian pharmacology identify distinct targets that regulate feeding. PLoS Biol. 2013 Nov; 11(11):e1001712.
Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J, Jenkins JL, Lavan P, Weber E, Doak AK, Côté S, Shoichet BK, Urban L. Large-scale prediction and testing of drug activity on side-effect targets. Nature. 2012 Jun 10; 486(7403):361-7.
Elisabet Gregori-Puigjané, Michael J. Keiser. Chapter 4. Designing Multi-Target Drugs. 2012 Jan 1; 50-65.
Laggner C, Kokel D, Setola V, Tolia A, Lin H, Irwin JJ, Keiser MJ, Cheung CY, Minor DL, Roth BL, Peterson RT, Shoichet BK. Chemical informatics and target identification in a zebrafish phenotypic screen. Nat Chem Biol. 2011 Dec 18; 8(2):144-6.
Keiser MJ, Irwin JJ, Shoichet BK. The chemical basis of pharmacology. Biochemistry. 2010 Dec 07; 49(48):10267-76.
Yadav PN, Abbas AI, Farrell MS, Setola V, Sciaky N, Huang XP, Kroeze WK, Crawford LK, Piel DA, Keiser MJ, Irwin JJ, Shoichet BK, Deneris ES, Gingrich J, Beck SG, Roth BL. The presynaptic component of the serotonergic system is required for clozapine's efficacy. Neuropsychopharmacology. 2011 Feb; 36(3):638-51.
Ferreira RS, Simeonov A, Jadhav A, Eidam O, Mott BT, Keiser MJ, McKerrow JH, Maloney DJ, Irwin JJ, Shoichet BK. Complementarity between a docking and a high-throughput screen in discovering new cruzain inhibitors. J Med Chem. 2010 Jul 08; 53(13):4891-905.
DeGraw AJ, Keiser MJ, Ochocki JD, Shoichet BK, Distefano MD. Prediction and evaluation of protein farnesyltransferase inhibition by commercial drugs. J Med Chem. 2010 Mar 25; 53(6):2464-71.
Thomas KL, Ellingrod VL, Bishop JR, Keiser MJ. A pilot study of the pharmacodynamic impact of SSRI drug selection and beta-1 receptor genotype (ADRB1) on cardiac vital signs in depressed patients: a novel pharmacogenetic approach. Psychopharmacol Bull. 2010; 43(1):11-22.
Keiser MJ, Setola V, Irwin JJ, Laggner C, Abbas AI, Hufeisen SJ, Jensen NH, Kuijer MB, Matos RC, Tran TB, Whaley R, Glennon RA, Hert J, Thomas KL, Edwards DD, Shoichet BK, Roth BL. Predicting new molecular targets for known drugs. Nature. 2009 Nov 12; 462(7270):175-81.
Adams JC, Keiser MJ, Basuino L, Chambers HF, Lee DS, Wiest OG, Babbitt PC. A mapping of drug space from the viewpoint of small molecule metabolism. PLoS Comput Biol. 2009 Aug; 5(8):e1000474.
Hert J, Irwin JJ, Laggner C, Keiser MJ, Shoichet BK. Quantifying biogenic bias in screening libraries. Nat Chem Biol. 2009 Jul; 5(7):479-83.
Keiser MJ, Hert J. Off-target networks derived from ligand set similarity. Methods Mol Biol. 2009; 575:195-205.
Jerome Hert, Michael J. Keiser, John J. Irwin, Tudor I. Oprea, Brian K. Shoichet. ChemInform Abstract: Quantifying the Relationships among Drug Classes. ChemInform. 2008 Jul 15; 39(29).
Hert J, Keiser MJ, Irwin JJ, Oprea TI, Shoichet BK. Quantifying the relationships among drug classes. J Chem Inf Model. 2008 Apr; 48(4):755-65.
Keiser MJ, Roth BL, Armbruster BN, Ernsberger P, Irwin JJ, Shoichet BK. Relating protein pharmacology by ligand chemistry. Nat Biotechnol. 2007 Feb; 25(2):197-206.