Method development
Molecular Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors
WU tags: *CXCL12_LIG*
Description

Fragment-based drug discovery (FBDD) has been proposed as an alternative to classical high-throughput screening techniques, in which milions of compounds are screened to find potential drugs. Instead, in FBDD, the smaller size of the compounds allows us to reduce screening libraries to only hundreds of compounds. In this work we apply molecular dynamics (MD) and a Markov State Model (MSM) framework to screen a library of 129 compounds against the protein CXCL12, a chemokine related to many diseases such as cancer methastasis. We are able to identify up to 8 fragments with millimolar affinity that bind to two pockets of the chemokine, named sY7 and H1S68. This work paves the way for the introduction of MD-based techniques in mainstream drug discovery pipelines.
Publications
- Martinez-Rosell G, Harvey MJ, De Fabritiis G. Molecular Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors. J Chem Inf Model. 2018 Feb 26. doi: 10.1021/acs.jcim.7b00625
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 1,729,897,300.00 |
![]() | 2 | RaymondFO* | 1,505,662,625.00 |
![]() | 3 | Retvari Zoltan | 1,139,283,575.00 |
![]() | 4 | Rion Family | 950,791,400.00 |
![]() | 5 | jjch | 941,778,375.00 |
![]() | 6 | HA-SOFT, s.r.o. | 907,387,500.00 |
![]() | 7 | Acey Pilot | 808,675,025.00 |
![]() | 8 | caffeineyellow5 | 796,997,950.00 |
![]() | 9 | Beyond | 713,431,075.00 |
![]() | 10 | neilp62 | 656,984,750.00 |
Insights from Fragment Hit Binding Assays by Molecular Simulations
WU tags: *XA*, (10|18|27|29|31)x*
Description

Novel drugs can be rationally designed by growing and linking small molecule fragments. However, because fragments are fast and promiscuous experimentalists commonly have contradictory hits when using different techniques. In this work, we run 2.1 milliseconds of total simulation time in GPUgrid. By analyzing the trajectories with Markov state models, we are able to simultaneously predict poses, kinetics, and affinities for a library of 42 fragments against a known protease. Specifically, the target protease is factor XA, a protein involved in the coagulation pathway whose inhibition is used to treat thrombosis. The results accurately reproduced previous crystallographic, kinetic and thermodynamic data, and showed our method can be useful to recapitulate experimental data in other targets.
Publications
- N. Ferruz, M. J. Harvey, J. Mestres and G. De Fabritiis, Insights from Fragment Hit Binding Assays by Molecular Simulations, J. Chem. Inf. Model., 2015, 55, pp 2200-2205
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Erik Postnieks | 1,037,914,550.00 |
![]() | 2 | Stoneageman | 359,155,850.00 |
![]() | 3 | IFRS | 298,344,725.00 |
![]() | 4 | Retvari Zoltan | 298,201,600.00 |
![]() | 5 | flashawk | 186,546,625.00 |
![]() | 6 | Venec | 176,527,525.00 |
![]() | 7 | Roald | 169,022,700.00 |
![]() | 8 | Grzegorz Roman Granowski | 167,628,975.00 |
![]() | 9 | RaymondFO* | 155,470,125.00 |
![]() | 10 | comfortw | 124,323,425.00 |
Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods
WU tags: R(L|C)
Description

Fast and accurate identification of active compounds is essential for effective use of virtual screening workflows. Here, we have compared the ligand-ranking efficiency of the linear interaction energy (LIE) method against standard docking approaches. Using a trypsin set of 1549 compounds, we performed 12,250 molecular dynamics simulations. The LIE method proved effective but did not yield results significantly better than those obtained with docking codes. The entire database of simulations is released.
Publications
- G. Lauro, N. Ferruz, S. Fulle, M. J. Harvey, P. W. Finn, and G. De Fabritiis,Reranking Docking Poses Using Molecular Simulations and Approximate Free Energy Methods, J. Chem. Inf. Model., 2014, 54 (8), pp 2185–2189
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | RaymondFO* | 14,447,300.00 |
![]() | 2 | Erik Postnieks | 12,647,675.00 |
![]() | 3 | Retvari Zoltan | 9,795,825.00 |
![]() | 4 | IFRS | 9,135,500.00 |
![]() | 5 | Bedrich Hajek | 9,101,550.00 |
![]() | 6 | Venec | 8,415,500.00 |
![]() | 7 | PERPLEXER ~ Thomas Huettinger | 7,125,175.00 |
![]() | 8 | flashawk | 7,092,300.00 |
![]() | 9 | steinrar | 6,546,661.00 |
![]() | 10 | STE\/E | 6,091,013.00 |
On-the-Fly Learning and Sampling of Ligand Binding by High-Throughput Molecular Simulations
WU tags: BenAdapt
Description

The most important information that can be taken out of a protein-ligand binding simulation is the binding poses of the ligand, the binding pathways and the free energy of binding. However in classical sampling simulations lots of simulation time is wasted re-sampling areas of low interest which might not lie on the binding pathway or have already been sampled adequately. Therefore, we proposed a adaptive sampling method by which it is possible to sample more strongly along the binding pathway of a ligand and thus achieved a 10 times speedup on the estimation of the binding free energy of the ligand compared to classical sampling.
Publications
- S. Doerr and G. De Fabritiis, On-the-Fly Learning and Sampling of Ligand Binding by High-Throughput Molecular Simulations, J. Chem. Theory Comput., 10 (5), 2064-2069, (2014)
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 17,694,500.00 |
![]() | 2 | RaymondFO* | 9,307,400.00 |
![]() | 3 | IFRS | 8,786,400.00 |
![]() | 4 | Retvari Zoltan | 6,772,200.00 |
![]() | 5 | flashawk | 6,071,100.00 |
![]() | 6 | HA-SOFT, s.r.o. | 5,639,400.00 |
![]() | 7 | Venec | 5,520,600.00 |
![]() | 8 | Rick A. Sponholz | 5,366,400.00 |
![]() | 9 | dominik | 4,821,000.00 |
![]() | 10 | Grzegorz Roman Granowski | 4,597,400.00 |
Kinetic Characterization of Fragment Binding in AmpC beta-Lactamase by High-Throughput Molecular Simulations
WU tags: 2HDQ
Description

Small molecules used in fragment-based drug discovery form multiple, promiscuous binding complexes difficult to capture experimentally. Here, we identify such binding poses and their associated energetics and kinetics using molecular dynamics simulations on AmpC β-lactamase. Only one of the crystallographic binding poses was found to be thermodynamically favorable; however, the ligand shows several binding poses within the pocket. This study demonstrates free-binding molecular simulations in the context of fragment-to-lead development and its potential application in drug design.
Publications
- P. Bisignano*, S. Doerr*, M. J. Harvey, A. D. Favia, A. Cavalli, and G. De Fabritiis, Kinetic Characterization of Fragment Binding in AmpC beta-Lactamase by High-Throughput Molecular Simulations, J. Chem. Info. Model., 54 (2), 362-366, 2014
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 24,067,500.00 |
![]() | 2 | IFRS | 14,355,000.00 |
![]() | 3 | Retvari Zoltan | 12,825,000.00 |
![]() | 4 | RaymondFO* | 12,420,000.00 |
![]() | 5 | flashawk | 12,220,000.00 |
![]() | 6 | Venec | 11,376,875.00 |
![]() | 7 | Bedrich Hajek | 8,505,000.00 |
![]() | 8 | Grzegorz Roman Granowski | 8,077,500.00 |
![]() | 9 | underwater | 8,055,000.00 |
![]() | 10 | werdwerdus | 6,401,250.00 |
Free binding of inhibitor benzamidine to enzyme trypsin
WU tags: TRYP, PYRT
Description
Identification of inhibitor molecules (drugs) that bind to enzymes or other proteins (targets) has been, and will be, the principal goal in drug discovery processes. Computational biologists/biochemists develop computational methods that span from ligand binding pose prediction to ligand binding affinity calculations, to aid in the quest for finding new, better and safer drugs. With our experiments, we show for the first time, a complete process of binding of a drug-like molecule to its target protein. Our molecules are used as a toy model in a proof-of-concept study for future and more relevant cases. In addition to reproduction of crystallographic ligand binding pose (also tackled by much cheaper but more coarse-grained techniques named 'computational docking'), we show the complete pathway of binding that the inhibitor follows from the solvent to the pocket where it binds. We detect several amino-acids in trypsin that consistently interact with benzamidine as it binds, which indicates that there is a prefered pathway for benzamidine to bind and therefore inhibit the function of trypsin. The principal outcome of this work is that with Molecular Dynamics simulations, it is now possible to study full binding events, being able to visualize and quantify the whole process of binding with a single computational experiment. We are confident that this achievement will allow a much deeper understanding of the processes of binding for small drug-like molecules which may then lead to the design of new, better and safer drugs.
Publications
- I. Buch, T. Giorgino and G. De Fabritiis, Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations, Proc. Natl. Acad. Sci. USA 108(25), 10184-10189 (2011)
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 15,732,027.00 |
![]() | 2 | Retvari Zoltan | 5,832,012.00 |
![]() | 3 | escape | 5,443,161.00 |
![]() | 4 | whizbang | 4,093,559.00 |
![]() | 5 | tng* | 3,846,724.00 |
![]() | 6 | Bikermatt | 3,768,642.00 |
![]() | 7 | dataman | 3,575,314.00 |
![]() | 8 | netwraith | 3,510,954.00 |
![]() | 9 | comfortw | 3,481,642.00 |
![]() | 10 | dak1640 | 3,236,762.00 |
Molecular simulations of the SH2 and ligand peptide binding affinity
WU tags: pYEEI, SH2
Description
The SH2 is a protein domain involved in protein-protein interactions. This particular domain plays a major role in cell communication on the sigalling processes for cell growth and development. However, the end goal for running such simulations is not to expand the knowldege on this particular system, but to use it as a model for developing methods to calculate protein-protein binding affinities.
Such methods will be very useful, for example, in the study of why certain wrong forms of proteins stop interacting with other partner proteins, as a way to give explanation to diseases in which these sort of mechanisms occur.
Publications
- I. Buch, S. K. Sadiq and G. De Fabritiis, Optimized potential of mean force calculations of standard binding free energy, J. Chem. Theory Comput., 7, 1765–1772 (2011)
- I. Buch, M. J. Harvey, T. Giorgino, D. P. Anderson and G. De Fabritiis, High-throughput all-atom molecular dynamics simulations using distributed computing, J. Chem. Inf. and Mod. 50, 397 (2010)
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 76,590,546.00 |
![]() | 2 | dak1640 | 36,161,500.00 |
![]() | 3 | Grzegorz Roman Granowski | 31,711,633.00 |
![]() | 4 | whizbang | 25,439,249.00 |
![]() | 5 | comfortw | 21,920,469.00 |
![]() | 6 | 123bob | 20,694,903.00 |
![]() | 7 | tng* | 20,332,716.00 |
![]() | 8 | dajeepster | 20,182,204.00 |
![]() | 9 | CNT - IQE | 19,654,731.00 |
![]() | 10 | Oleg Tchij | 18,806,232.00 |
Forward-Reverse Steered Molecular Dynamics
WU tags: GA
Description
Potassium ion permeation in Gramicidin A. We are giving workunits comprising full-atom simulations of gramidicin A for ion transport, a total of 30,000 atoms. Each workunit lasts less than one day and you have to complete it before 4 days.
Publications
- T. Giorgino and G. De Fabritiis, A high-throughput steered molecular dynamics study on the free energy profile of ion permeation through gramicidin A, J. Chem. Theory Comput.,7 , 1943–1950 (2011)
Badge | Rank | Name | Credit |
---|---|---|---|
![]() | 1 | Stoneageman | 4,713,395.00 |
![]() | 2 | dak1640 | 3,857,211.00 |
![]() | 3 | GPUGRID Role account | 3,350,192.00 |
![]() | 4 | Oleg Tchij | 3,212,435.00 |
![]() | 5 | Grzegorz Roman Granowski | 3,163,300.00 |
![]() | 6 | CNT - IQE | 2,107,085.00 |
![]() | 7 | 123bob | 1,990,814.00 |
![]() | 8 | X-Files 27 | 1,609,954.00 |
![]() | 9 | kevint | 1,506,964.00 |
![]() | 10 | netwraith | 1,353,994.00 |