News & Events

Journal Cover of Organic & Biomolecular Chemistry

posted Jan 4, 2018, 7:46 AM by Emilio Gallicchio

Congratulations to students Danielle Hirsch and Rajat Pal whose paper and artistic rendering of an hydroxytropolone bound to an enzyme of the herpes simplex virus has made the journal cover of Organic & Biomolecular Chemistry

Release of the AGBNP1 OpenMM Plugin for GPUs

posted Oct 27, 2017, 11:37 AM by Emilio Gallicchio   [ updated Oct 27, 2017, 11:46 AM ]

The AGBNP (Analytic Generalized Born plus Non-Polar) implicit solvent model is our main solvation force field for alchemical binding free energy calculations. Following the development of the GaussVol algorithm for GPUs, we have just completed the implementation of the AGBNP model version 1 on GPUs as part of the OpenMM library. As we reported earlier, the GPU code is up to 100 times faster than our best CPU implementation. While lacking some of the advanced features of AGBNP2 (solvent-excluded volume representation and hydration sites), this milestone moves us closer to a full port of our alchemical binding free energy software stack to GPU devices. The GPU port of AGBNP2 is underway. 

Support from the National Science Foundation is gratefully acknowledged

Prof. Emilio Gallicchio presents at the Henry Wasser Award ceremony..!!

posted Sep 27, 2017, 7:49 AM by Rajat Kumar Pal   [ updated Oct 23, 2017, 11:29 AM ]

Prof. Emilio Gallicchio, the recipient of the Henry Wasser Award from CUNY will be presenting at the award ceremony at the CUNY Graduate Center, NY on Friday, October 20, 2017..!!

After the award ceremony on Oct 20, 2017!
In the picture : On the left, Dr. Richard Magliozzo, in the middle, Dr. Emilio Gallicchio and to the right , Dr. Manfred Phillip


posted Aug 23, 2017, 3:14 PM by Emilio Gallicchio   [ updated Aug 24, 2017, 6:34 AM ]

The Computers in Chemistry Division of the American Chemical Society awarded Prof. Emilio Gallicchio of Brooklyn College the NVIDIA GPU Best Poster Award at the 254th ACS National Meeting & Exposition in Washington DC. Prof. Gallicchio's poster is entitled "Efficient GPU/OpenMM implementation of the AGBNP solvation model for macromolecular binding"


Emilio Gallicchio,, Denise Kilburg, Baofeng Zhang
Brooklyn College, Brooklyn, NY, and Doctoral Programs in Chemistry and Biochemistry, Graduate Center of the City University of New York, New York, NY

The poster describes the GPU implementation of the Analytic Generalized Born plus Non-Polar implicit solvent model (AGBNP) for the OpenMM molecular simulation package. As part of this work, novel recursive computational geometry algorithms have been developed to estimate volumes and surface areas of macromolecules. The Generalized Born pairwise descreening algorithm has been formulated to take advantage of the GPU architecture. The GPU implementation is 50 to 100 times faster than our best CPU implementation. Illustrative applications to binding free energy calculations are presented. OpenMM plugin:

The generous donation of an impressive Titan Xp GPU by NVIDIA is greatly appreciated. We will put it to good use!

Professor Gallicchio is awarded the Henry Wasser Award from CUNY!

posted Jul 6, 2017, 2:28 PM by Rajat Kumar Pal   [ updated Jul 6, 2017, 2:29 PM ]

Professor Gallicchio is the recipient of the 2017 Henry Wasser award from the CUNY Academy. This award is given to outstanding CUNY Assistant Professors by the CUNY Academy for the Humanities and Sciences. Congratulations Dr. Gallicchio!

Presentation on Analytic Model of Binding @CECAM

posted Jun 19, 2017, 2:44 PM by Emilio Gallicchio

I have had the opportunity to present our recent development of an analytic probabilistic model of alchemical binding at the "Beyond Kd's" CECAM conference organized by Sereina Riniker, Lyna Luo, and Chris Chipot at Lausanne in Switzerland. One of the aims of this project is to extract physical parameters such as the volume of the binding site and the local dielectric constant of the binding site from binding free energy profiles. 

Click below to view the slides of the presentation. Feedback is welcome.

A Novel Surface Area Algorithm for GPUs added to OpenMM

posted Jan 8, 2017, 8:08 AM by Emilio Gallicchio   [ updated Jan 8, 2017, 9:30 AM ]

Surface area of a moleculeAfter a year-long effort, we finally developed an efficient implementation of the Gaussian-based volume and surface area model for GPUs. The work, performed in collaboration with Peter Eastman Vijay Pande at Stanford University, is described in a recent publication to appear in the Journal of Computational Chemistry: 

Baofeng Zhang, Denise Kilburg, Peter Eastman, Vijay S. Pande, Emilio Gallicchio. Efficient Gaussian Density Formulation of Volume and Surface Areas of Macromolecules on Graphical Processing Units. J. Comp. Chem. (2017). pdf of submitted manuscript

Volume and surface area of macromolecules are employed in medicinal chemistry to measure structural similarity and complementarity of compounds. They are also the basis of many implicit models of non-polar solvation, which is our primary interest.

With this algorithm we were able to achieve a 50- to 100-fold speed-up on GPU's relative to our best CPU implementation. more ->

The GaussVol code is freely available on github as a plugin of the OpenMM molecular mechanics package.

Support from the National Science Foundation is gratefully acknowledged

Publication on binding free energy study of RNase H inhibitors

posted Sep 18, 2016, 8:16 AM by Emilio Gallicchio   [ updated Sep 18, 2016, 8:25 AM ]

Our collaboration with the group of Ryan Murelli here at Brooklyn College, and John A Beutler and Stuart F Le Grice at NCI, aimed at identifying  α-hydroxytropolones derivatives capable of inhibiting the RNase H enzyme of the HIV virus is now described in two recent publications (below).

The computational work has been made possible by the WEB computational grid at Brooklyn College maintained by the ITS office at Brooklyn College. Additional computing has been performed on the NSF XSEDE SuperMIC cluster at LSU. Thanks!

Good job done! to Baofeng Zhang who completed his postdoctoral residency in the lab.

Baofeng Zhang, Michael P. D'Erasmo, Ryan P. Murelli, Emilio Gallicchio. Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase. ACS Omega. 2016. pdf of submitted manuscript

Ryan P Murelli, Michael P D'Erasmo, Danielle R Hirsch, C Meck, T Masaoka, JA Wilson, Baofeng Zhang, Rajat K Pal, Emilio Gallicchio, John A Beutler, Stuart F Le Grice. Synthetic α-hydroxytropolones as inhibitors of HIV reverse transcriptase ribonuclease H activity. MedChemComm. 2016. doi:10.1039/C6MD00238B

Support from the National Science Foundation is gratefully acknowledged


posted Sep 7, 2016, 6:20 AM by Emilio Gallicchio   [ updated Sep 7, 2016, 6:24 AM ]

We are happy to announce that a team of CUNY investigators led by our laboratory and including Prof. Lauren Wickstrom (Borough of Manhattan Community College), Prof. Tom Kurtzman (Lehman College), and Prof. Wayne Harding (Hunter College) has been awarded a 1-year Interdisciplinary Research Grant award of $39,500 by the CUNY Office of Research to conduct theoretical and experimental studies of the inhibition of the D3 dopamine receptor:

A Combined Treatment of Hydration and Dynamical Effects for the Modeling of Protein-Ligand Binding Thermodynamics

Summary. The project seeks to develop an improved computational protocol for the study of protein-drug interactions marrying the accuracy of detailed explicit solvation models with the versatility of implicit solvation approaches, and to validate it experimentally on the important D3 dopamine receptor drug target. The work will lead to improved descriptions of the displacement of water molecules from the protein surface and of the dynamical response of molecular conformations upon binding. Current computer models of molecular binding lack in one or both of these critical elements. The primary aim of the project is to exploit the unique and complementary expertise of our team of investigators at CUNY to establish a proof-of-concept base and acquire sufficient preliminary data to compete for federal funding at the national level.

The team will work to develop a custom parameterization of the AGBNP solvation model for the D3 dopamine receptor using accurate Hydration Site Analysis data obtained from explicit solvent simulations. The resulting model will be employed to predict binding constants of a virtual library of D3 inhibitors using the BEDAM alchemical methodology. The most promising identified inhibitors will be synthesized and essayed for binding.  Selective inhibition of the dopamine D3 receptor is a promising therapeutic approach for the treatment of drug abuse disorders. Building on the methodology employed in our recent participation to the SAMPL5 blinded challenge, the project will for the first time attempt to apply a model combining enclosed hydration effects and a dynamical description of binding to a complex protein receptor system.

The award will help fund the research of Rajat Pal, a Ph.D. student in our lab, for the next year. Thanks!

Publication on SAMPL5 host-guest blinded challenge

posted Aug 24, 2016, 12:50 PM by Emilio Gallicchio   [ updated Sep 24, 2016, 9:38 AM ]

Our contribution to the SAMPL5 blinded challenge is now described in a paper to appear in the Journal of Computer Aided Molecular Design:

Rajat Kumar Pal, Kamran Haider, Divya Kaur, William Flynn, Junchao Xia,  Ronald M Levy, Tetiana Taran,* Lauren Wickstrom,  Tom Kurtzman, Emilio Gallicchio. A Combined Treatment of Hydration and Dynamical Effects for the Modeling of Host-Guest Binding Thermodynamics: The SAMPL5 Blinded Challenge. J. Comp. Aided. Mol. Des. 2016. pdf of submitted manuscript *Undergraduate student.

The computational work has been performed on WEB computational grid at Brooklyn College maintained by the ITS office at Brooklyn College, and on the NSF XSEDE SuperMIC cluster at LSU. Thanks!

Support from the National Science Foundation is gratefully acknowledged

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