A number of research labs are involved in running and enhancing F@h.
BOWMAN LAB (@drGregBowman), UNIVERSITY of Pennsylvania
The Bowman lab combines computer simulations and experiments to understand the mechanisms of allostery (i.e. long-range communication between different parts of a protein) and to exploit this insight to control proteins’ functions with drugs and mutations. Examples of ongoing projects include (1) understanding how mutations give rise to antibiotic resistance, (2) designing allosteric drugs to combat antibiotic resistant infections, (3) understanding allosteric networks in G proteins and designing allosteric anti-cancer drugs, and (4) understanding and interfering with the mechanisms of Ebola infection. To rapidly converge on predictive models, we iterate between using simulations to gain mechanistic insight, conducting our own experimental tests of our models, and refining our simulations/analysis based on feedback from experiments. We also develop enhanced sampling algorithms for modeling rare events that are beyond the reach of existing simulation methodologies.
CHODERA LAB, MEMORIAL SLOAN-KETTERING CANCER CENTER
The Chodera lab at the Sloan-Kettering Institute uses Folding@home to better understand how we can design more effective therapies for cancer and other diseases.
Their mission is to completely redesign the way that therapeutics—especially anticancer drugs—are designed using computers, graphics processors (GPUs), distributed computing, robots, and whatever technology we can get our hands on. They are striving to make the design of new cancer drugs much more of an engineering science, where state-of-the-art computer models quantitatively and accurately predict many aspects of drug behavior before they are synthesized. Chodera Lab certainly won’t get there overnight—lots of hard work is needed to improve algorithms, force fields, and theory. But by tapping into the enormous computing resources of F@h, they can more rapidly make predictions and then test them in the laboratory (with robots!) to quickly make improvements through learning from each cycle of prediction and validation.
VOELZ LAB, TEMPLE UNIVERSITY
Vincent Voelz lab at Temple University’s Chemistry Department focuses on using transferrable, all-atom simulations for prediction and design of biomolecular dynamics and function. In particular, their interests include in silico prediction and design of proteins, peptide mimetics (e.g. peptoids), and binding sequences for cell signaling peptides.
CSELS, WASHINGTON UNIVERSITY IN ST. LOUIS
The Center for Science and Engineering of Living Systems (CSELS) pronounced “cells,” brings together investigators from engineering and basic sciences for whom the cell is the fundamental unit of interest. Our goals are to model, design and manipulate cells and cellular matter at multiple scales in order to understand how cellular level phenotypes come about as the result of coordinated, regulated, collective interactions at the sub-cellular and extra-cellular levels.
Hanson/Cossio Lab, Flatiron institute
The Hanson/Cossio lab at the Flatiron Institute focuses on developing and using mathematical approaches to understand the molecular mechanisms involved in key biological processes. The team is developing theoretical and computational algorithms to unravel these underlying mechanisms using molecular dynamics simulations
HUANG LAB, UW-Madison
Xuhui Huang’s lab at the University of Wisconsin at Madison is interested in conformational change, which is crucial for a wide range of biological processes including biomolecular folding and the operation of key cellular machinery.
SHUKLA GROUP, UNIVERSITY OF ILLINOIS
The Shukla group is focused on developing and using novel atomistic simulation approaches for understanding complex biological processes. The key areas of current interest include understanding behavior of key cellular signaling proteins involved in cancer for drug design & development, stress and energy signaling enzymes in plants etc.
DELEMOTTE GROUP, KTH ROYAL INSTITUTE OF TECHNOLOGY
Delemotte’s group is interested in the cell membrane proteins.
The cellular membrane acts as a barrier to isolate the cell’s inside from the outside world. To communicate with its environment, the cell uses membrane proteins that facilitate the transport and permeation of otherwise impermeant species. Dysfunction of these proteins lead to diseases such as epilepsy, heart arrhythmias or paralysis. These proteins are also privileged drug targets since they are accessible from the outside of the cell.
Recent developments in structural biology have provided us with static structures of these exquisite molecular machines, yielding the first insights into how these proteins may perform their function. We provide further insight into their function and regulation by their environment by using molecular dynamics simulations.
MEY Group, University of Edinburgh
The Mey research group is developing new methods using molecular simulations and machine learning to study the dynamics of proteins and how they interact with small molecules. In particular, they look at proteins called metalloenzymes; these are proteins that use metal ions, such as Zinc, Magnesium or Iron to catalyse a certain reaction. A challenge they are interested in is to find ways to inhibit these enzymes’ function. Why is this important? Because many metalloenzymes play a role in disease. For example, certain metalloenzymes are responsible for antibiotic resistances. Understanding how they work and how to regulate these enzymes in resistant bacteria will help with the fight against antibiotic resistance.
LINDAHL LAB, STOCKHOLM UNIVERSITY
Erik Lindahl’s group is well known as a primary developer of Gromacs, a powerful MD code that is frequently used in Folding@home. He also has interests in lipid membrane biophysics and viral fusion, leading to many collaborations on that front as well.
Other past and present collaborators include:
KASSON LAB, UNIVERSITY OF VIRGINIA
Kasson Lab at U. Va works on lipid membrane biophysics, especially as it has a role in viral infection. Dr. Kasson has worked extensively on the SMP core for Folding@home.
IZAGUIRRE LAB, NOTRE DAME
The Izaguirre lab is interested in problems at the interface between biology, computer science, and applied mathematics. Their lab has developed the Protomol MD package, and we have integrated that package into Folding@home. Protomol is a great package for testing and developing new algorithms. Particularly, Protomol implements the Normal Mode Langevin method for doing Long Timestep Molecular Dynamics (LTMD). This allows timesteps hundreds to thousands of times longer than conventional molecular dynamics. We are running Folding@home projects using LTMD to explore the effect of mutations on protein folding. Future projects will explore the effects of conformational dynamics in function and protein aggregation. Also, in the future, LTMD will be fully incorporated into OpenMM to benefit from hundred-fold speedups from GPU acceleration.
SHIRTS LAB, UNIVERSITY OF VIRGINIA
Michael Shirts’s group at the University of Virginia develops new simulation methodology and uses simulations to predict thermodynamic properties for small molecules. They are collaborating with us to develop new versions of the Gromacs core and general Gromacs core development.
SNOW LAB, COLORADO STATE UNIVERSITY
The Snow lab at Colorado State has developed a new scientific core to run SHARPEN on Folding@home. These upcoming projects will test the performance of new algorithms for high-resolution protein structure prediction and also for the design of libraries of enzymes.
SORIN LAB, CSULB
Eric Sorin’s group at CSULB uses simulation to study protein folding and other related areas. They are collaborating with us to develop new force field ports for Gromacs.
ZAGROVIC LAB, MEDITERRANEAN INSTITUTE FOR LIFE SCIENCES
Bojan Zagrovic’s lab at the Mediterranean Institute for Life Sciences in Croatia is interested in many related areas, including unstructured proteins and experimental structure refinement. His group is helping out Folding@home with new client development.