Michael K. Gilson

About

Michael K. Gilson, Ph.D., M.D., is a Professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences, where he also serves as Chair in Computer-Aided Drug Design and Co-Director of the UCSD Center for Drug Discovery Innovation. His research focuses on computer simulations of molecules to facilitate drug discovery, aiming to improve the realism, speed, and accuracy of these simulations through methods and software development. He manages BindingDB, an open database containing over 2 million measured protein-small molecule binding data points for more than 1 million compounds, and actively engages in molecular design and synthesis projects related to cancer and anesthesia. Gilson's academic background includes an A.B. in Bioengineering from Harvard College, a Ph.D. in Biochemistry and Molecular Biophysics from Columbia University, and an M.D. from Columbia University College of Physicians and Surgeons. His notable contributions include the development of statistical thermodynamics of protein-drug binding, structure-based development of mutation-resistant HIV-protease inhibitors, and the invention of the Mining Minima technology for computer-aided drug design. He has held leadership roles such as serving on the Executive Committee of the UC Drug Discovery Consortium and co-founding VeraChem LLC. His work has been recognized through awards including the Howard Hughes Medical Institute Physician Research Fellowship and the Endowed Chair in Computer-Aided Drug Design at UC…

Research topics

• Computer Science
• Physics
• Statistical physics
• Mathematics
• Quantum mechanics
• Chemistry
• Classical mechanics
• Physical chemistry
• Materials science
• Reliability engineering

Selected publications

• Non-bonded force field model with advanced restrained electrostatic potential charges (RESP2)

  Communications Chemistry · 2020 · 295 citations

  Senior authorCorresponding

  The restrained electrostatic potential (RESP) approach is a highly regarded and widely used method of assigning partial charges to molecules for simulations. RESP uses a quantum-mechanical method that yields fortuitous overpolarization and thereby accounts only approximately for self-polarization of molecules in the condensed phase. Here we present RESP2, a next generation of this approach, where the polarity of the charges is tuned by a parameter, δ, which scales the contributions from gas- and…

  DOI

• Development and Benchmarking of Open Force Field v1.0.0—the Parsley Small-Molecule Force Field

  Journal of Chemical Theory and Computation · 2021 · 167 citations

  We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of…

  DOI

• The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations

  Journal of Computer-Aided Molecular Design · 2020 · 137 citations

  Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing chall…

  DOI

• The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks

  Journal of Chemical Information and Modeling · 2025-02-14 · 11 citations

  reviewOpen access

  Computational tools for structure-based drug design (SBDD) are widely used in drug discovery and can provide valuable insights to advance projects in an efficient and cost-effective manner. However, despite the importance of SBDD to the field, the underlying methodologies and techniques have many limitations. In particular, binding pose and activity predictions (P-AP) are still not consistently reliable. We strongly believe that a limiting factor is the lack of a widely accepted and established…

  PublisherOA PDFDOI

• Revisiting the Plasmodium falciparum druggable genome using predicted structures and data mining

  npj Drug Discovery. · 2025-03-04 · 10 citations

  articleOpen access

  Abstract Identification of novel drug targets is a key component of modern drug discovery. While antimalarial targets are often identified through the mechanism of action studies on phenotypically derived inhibitors, this method tends to be time- and resource-consuming. The discoverable target space is also constrained by existing compound libraries and phenotypic assay conditions. Leveraging recent advances in protein structure prediction, we systematically assessed the Plasmodium falciparum ge…

  PublisherOA PDFDOI

Recent grants

• NIH Grant R41GM062050

  NIH · $100k · 2002

• AN OPEN RESOURCE TO ADVANCE COMPUTER-AIDED DRUG DESIGN

  NIH · $3.6M · 2014–2020

• BindingDB: Data and Tools for Drug Discovery, Chemical Biology and Systems Pharmacology

  NIH · $6.9M · 2004–2021

Frequent coauthors

• David L. Mobley

  University of California, Irvine

  64 shared

• Niel M. Henriksen

  56 shared

• Tom Kurtzman

  The Graduate Center, CUNY

  45 shared

• John D. Chodera

  42 shared

• Ray Luo

  University of California, Irvine

  41 shared

• Jian Yin

  40 shared

• Andrew T. Fenley

  Virginia Tech

  39 shared

• Michael R. Shirts

  University of Colorado Boulder

  38 shared

Education

• M.D.

  Columbia University Vagelos College of Physicians and Surgeons

  1989

• Ph.D., Biochemistry and Molecular Biophysics

  Columbia University

  1988

• A.B., Bioengineering

  Harvard College

  1981

Awards & honors

• Howard Hughes Medical Institute Physician Research Fellowshi…
• Distinguished Lecture in Computational and Mathematical Biol…
• Endowed Chair in Computer-Aided Drug Design, UC San Diego, 2…
• 5th Annual Kollman Lectureship, UC San Francisco, 2016

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