Scientific Publications

Scientists at Silicon Therapeutics are among the leading voices in the field of quantum physics, molecular simulations and applications of computation to drug discovery.

Members of our senior science team are the lead authors for some of the most innovative and frequently cited publications appearing in prestigious industry journals, with over 200 peer-reviewed articles and over 20,000 citations. 

Insights and expertise of our visionary scientists enable us to address difficult protein targets through a fundamental understanding of disease at the atomic level. We believe our thought leadership—coupled with our integrated in-house experimental efforts in chemistry and biology and our high-performance computing environment—will lead to design and delivery of new safe and effective medicines to improve the lives of patients.

Highlighted Scientific Publications

  • Rigorous Free Energy Simulations in Virtual Screening

    J. Chem. Inf. Model. 2020

    Most Read

    Virtual high throughput screening (vHTS) in drug discovery is a powerful approach to identify hits: when applied successfully, it can be much faster and cheaper than experimental high-throughput screening approaches. However, mainstream vHTS tools have significant limitations: ligand-based methods depend on knowledge of existing chemical matter, while structure-based tools such as docking involve significant approximations

  • Fully Integrated FPGA Molecular Dynamics Simulations

    SC ’19, November 17–22

    The implementation of Molecular Dynamics (MD) on FPGAs has received substantial attention. Previous work, however, has consisted of either proof-of-concept implementations of components, usually the range-limited force; full systems, but with much of the work shared by the host CPU; or prototype demonstrations, e.g., using OpenCL, that neither implement a whole system nor have competitive

  • Optimal Measurement Network of Pairwise Differences

    J. Chem. Inf. Model. 2019, 59, 11, 4720–4728

    When both the difference between two quantities and their individual values can be measured or computationally predicted, multiple quantities can be determined from the measurements or predictions of select individual quantities and select pairwise differences. These measurements and predictions form a network connecting the quantities through their differences. Here, I analyze the optimization of such

  • Molecular Simulations Minimally Restrained by Experimental Data

    J. Chem. Phys. 150, 154121 (2019)

    One popular approach to incorporating experimental data into molecular simulations is to restrain the ensemble average of observables to their experimental values. Here, I derive equations for the equilibrium distributions generated by restrained ensemble simulations and the corresponding expected values of observables. My results suggest a method to restrain simulations so that they generate distributions

  • Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations

    J. Chem. Inf. Model. 2017, 57, 12, 2911–2937

    Most ReadWidely Cited

    Accurate in silico prediction of protein–ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently,

  • Large-Scale Computational Screening Identifies First in Class Multitarget Inhibitor of EGFR Kinase and BRD4

    Sci Rep 5, 16924

    Inhibition of cancer-promoting kinases is an established therapeutic strategy for the treatment of many cancers, although resistance to kinase inhibitors is common. One way to overcome resistance is to target orthogonal cancer-promoting pathways. Bromo and Extra-Terminal (BET) domain proteins, which belong to the family of epigenetic readers, have recently emerged as promising therapeutic targets in

  • Water Networks Contribute to Enthalpy/Entropy Compensation in Protein–Ligand Binding

    J. Am. Chem. Soc. 2013, 135, 41, 15579–15584

    The mechanism (or mechanisms) of enthalpy–entropy (H/S) compensation in protein–ligand binding remains controversial, and there are still no predictive models (theoretical or experimental) in which hypotheses of ligand binding can be readily tested. Here we describe a particularly well-defined system of protein and ligands—human carbonic anhydrase (HCA) and a series of benzothiazole sulfonamide ligands with

  • Mechanism of the Hydrophobic Effect in the Biomolecular Recognition of Arylsulfonamides by Carbonic Anhydrase

    PNAS November 1, 2011 108 (44) 17889-17894

    Widely Cited

    The hydrophobic effect—a rationalization of the insolubility of nonpolar molecules in water—is centrally important to biomolecular recognition. Despite extensive research devoted to the hydrophobic effect, its molecular mechanisms remain controversial, and there are still no reliably predictive models for its role in protein–ligand binding. Here we describe a particularly well-defined system of protein and ligands—carbonic

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