Lennard-Jones Potential and Dummy Atom Settings to Overcome the AUTODOCK Limitation in Treating Flexible Ring Systems. - Stefano Forli; Maurizio Botta (J. Chem. Inf. Model., 2007)

Cyclin-dependent kinases 5 template: Useful for virtual screening. - Siripit Pitchuanchom; Chantana Boonyarat; Stefano Forli; Arthur J. Olson; Chavi Yenjai (Comput. Biol. Medicine, 2012)

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge. - Emilio Gallicchio; Nan-Jie Deng; Peng He; Lauren Wickstrom; Alexander L. Perryman; Daniel N. Santiago; Stefano Forli; Arthur J. Olson; Ronald M. Levy (J. Comput. Aided Mol. Des., 2014)

Blind prediction of HIV integrase binding from the SAMPL4 challenge. - David L. Mobley; Shuai Liu; Nathan M. Lim; Karisa L. Wymer; Alexander L. Perryman; Stefano Forli; Nan-Jie Deng; Justin Su; Kim Branson; Arthur J. Olson (J. Comput. Aided Mol. Des., 2014)

Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge. - Alexander L. Perryman; Daniel N. Santiago; Stefano Forli; Diogo Santos-Martins; Arthur J. Olson (J. Comput. Aided Mol. Des., 2014)

AutoDock4Zn: An Improved AutoDock Force Field for Small-Molecule Docking to Zinc Metalloproteins. - Diogo Santos-Martins; Stefano Forli; Maria João Ramos; Arthur J. Olson (J. Chem. Inf. Model., 2014)

A Virtual Screen Discovers Novel, Fragment-Sized Inhibitors of Mycobacterium tuberculosis InhA. - Alexander L. Perryman; Weixuan Yu; Xin Wang 067; Sean Ekins; Stefano Forli; Shao-Gang Li; Joel S. Freundlich; Peter J. Tonge; Arthur J. Olson (J. Chem. Inf. Model., 2015)

AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility. - Pradeep Anand Ravindranath; Stefano Forli; David S. Goodsell; Arthur J. Olson; Michel F. Sanner (PLoS Comput. Biol., 2015)

Fragment-Based Analysis of Ligand Dockings Improves Classification of Actives. - Richard K. Belew; Stefano Forli; David S. Goodsell; T. J. O'Donnell; Arthur J. Olson (J. Chem. Inf. Model., 2016)

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions. - Juan Pablo Arcon; Carlos P. Modenutti; Demian Avendaño; Elias D. López; Lucas A. Defelipe; Francesca Alessandra Ambrosio; Adrian Gustavo Turjanski; Stefano Forli; Marcelo A. Marti (Bioinform., 2019)

Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4. - Lea El-Khoury; Diogo Santos-Martins; Sukanya Sasmal; Jérôme Eberhardt; Giulia Bianco; Francesca Alessandra Ambrosio; Leonardo Solis-Vasquez; Andreas Koch 001; Stefano Forli; David L. Mobley (J. Comput. Aided Mol. Des., 2019)

D3R Grand Challenge 4: prospective pose prediction of BACE1 ligands with AutoDock-GPU. - Diogo Santos-Martins; Jérôme Eberhardt; Giulia Bianco; Leonardo Solis-Vasquez; Francesca Alessandra Ambrosio; Andreas Koch 001; Stefano Forli (J. Comput. Aided Mol. Des., 2019)

AutoGridFR: Improvements on AutoDock Affinity Maps and Associated Software Tools. - Yuqi Zhang 003; Stefano Forli; Anna Omelchenko; Michel F. Sanner (J. Comput. Chem., 2019)

Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network. - Junchao Xia; William F. Flynn; Emilio Gallicchio; Keith Uplinger; Jonathan D. Armstrong; Stefano Forli; Arthur J. Olson; Ronald M. Levy (J. Chem. Inf. Model., 2019)

Integrative modeling of the HIV-1 ribonucleoprotein complex. - David S. Goodsell; Andrew Jewett; Arthur J. Olson; Stefano Forli (PLoS Comput. Biol., 2019)

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research. - Scott LeGrand; Aaron Scheinberg; Andreas F. Tillack; Mathialakan Thavappiragasam; Josh Vincent Vermaas; Rupesh Agarwal; Jeff Larkin; Duncan Poole; Diogo Santos-Martins; Leonardo Solis-Vasquez; Andreas Koch 001; Stefano Forli; et al. (BCB, 2020)

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking. - Leonardo Solis-Vasquez; Diogo Santos-Martins; Andreas Koch 001; Stefano Forli (PDP, 2020)

Parallelizing Irregular Computations for Molecular Docking. - Leonardo Solis-Vasquez; Diogo Santos-Martins; Andreas F. Tillack; Andreas Koch 001; Jérôme Eberhardt; Stefano Forli (IA3@SC, 2020)

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. - Atanu Acharya; Rupesh Agarwal; Matthew B. Baker; Jérôme Baudry; Debsindhu Bhowmik; Swen Böhm; Kendall G. Byler; Sam Yen-Chi Chen; Leighton Coates; Connor J. Cooper; Omar Demerdash; Isabella Daidone; et al. (J. Chem. Inf. Model., 2020)

AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings. - Jérôme Eberhardt; Diogo Santos-Martins; Andreas F. Tillack; Stefano Forli (J. Chem. Inf. Model., 2021)

Improving Docking Power for Short Peptides Using Random Forest. - Michel F. Sanner; Leonard Dieguez; Stefano Forli; Ewa Lis (J. Chem. Inf. Model., 2021)

Structure-based virtual screening workflow to identify antivirals targeting HIV-1 capsid. - Qinfang Sun; Avik Biswas; R. S. K. Vijayan; Pierrick Craveur; Stefano Forli; Arthur J. Olson; Andres Emanuelli Castaner; Karen Kirby; Stefan G. Sarafianos; Nan-Jie Deng; Ronald M. Levy (J. Comput. Aided Mol. Des., 2022)

Benchmarking the performance of irregular computations in AutoDock-GPU molecular docking. - Leonardo Solis-Vasquez; Andreas F. Tillack; Diogo Santos-Martins; Andreas Koch 001; Scott LeGrand; Stefano Forli (Parallel Comput., 2022)

Ringtail: A Python Tool for Efficient Management and Storage of Virtual Screening Results. - Althea T. Hansel-Harris; Diogo Santos-Martins; Niccolò Bruciaferri; Andreas F. Tillack; Matthew Holcomb; Stefano Forli (J. Chem. Inf. Model., 2023)

Reactive Docking: A Computational Method for High-Throughput Virtual Screenings of Reactive Species. - Giulia Bianco; Matthew Holcomb; Diogo Santos-Martins; Andreas F. Tillack; Althea T. Hansel-Harris; Stefano Forli (J. Chem. Inf. Model., 2023)

CosolvKit: a Versatile Tool for Cosolvent MD Preparation and Analysis. - Niccolò Bruciaferri; Jérôme Eberhardt; Manuel A. Llanos; Johannes R. Loeffler; Matthew Holcomb; Monica L. Fernández-Quintero; Diogo Santos-Martins; Andrew B. Ward; Stefano Forli (J. Chem. Inf. Model., 2024)

A multidimensional dataset for structure-based machine learning. - Matthew Holcomb; Stefano Forli (Nat. Comput. Sci., 2024)

Synergy of machine learning and density functional theory calculations for predicting experimental Lewis base affinity and Lewis polybase binding atoms. - Hieu Huynh; Khanh Le; Linh Vu; Trang Nguyen; Matthew Holcomb; Stefano Forli; Hung Phan (J. Comput. Chem., 2024)