RESEARCH: HALOGENASES
FOLDING PROJECT #19206 PROFILE
PROJECT TEAM
Manager(s): Tanner DeanInstitution: University of Illinois
WORK UNIT INFO
Atoms: 3,298Core: 0xa8
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Many drugs use halogens (like fluorine). Adding these can be tricky and create harmful waste. Scientists are studying enzymes called halogenases that do this naturally better. This project uses computer models to predict how well different enzymes add halogens to various molecules.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Approximately 40 percent of drugs approved or currently in clinical testing contain halogens (F, Cl, Br, or I) as pharmaceutically active ligand substituents.
This makes the halogenation of chemical scaffolds an issue of particular interest to medicinal chemists when attempting to synthesize potential drug candidates.
Many of the current methods for halogenation are difficult to control the regioselectivity or produce toxic byproducts during the reaction.
Due to these issues; halogenases, a class of enzymes that catalyze highly regioselective halogenation of various molecules in nature, have been studied as a means to improve existing halogenation methods with less toxic byproducts and higher regioselectivity of reaction.
By utilizing Relative Binding Free Energy calculations (RBFE) across a number of common organic molecule scaffolds, our goal is to better predict the probability and site of halogenation for various common chemical scaffolds across a number of halogenases.
RELATED TERMS GLOSSARY AI BETA
halogens
Elements fluorine (F), chlorine (Cl), bromine (Br), and iodine (I).
Halogens are elements in Group 17 of the periodic table. They're highly reactive and commonly used as substituents in pharmaceuticals because they can influence a drug's properties. In drug development, understanding how halogens interact with molecules is crucial for designing effective and safe medications.
pharmaceutically active ligand
A molecule that binds to a biological target (like a receptor) and produces a pharmacological effect.
In pharmaceuticals, a 'pharmaceutically active ligand' is a molecule designed to interact with specific targets in the body. This interaction can trigger various effects, like pain relief or disease treatment. Medicinal chemists work to design these ligands, aiming for high effectiveness and minimal side effects.
scaffold
A basic molecular framework used as a starting point for synthesizing new compounds.
In drug design, a 'scaffold' is like the foundational structure of a molecule. Chemists use existing scaffolds and modify them to create new drugs with desired properties. Think of it like building blocks; different combinations can lead to unique molecules with specific effects.
regioselectivity
The ability of a chemical reaction to produce a desired product at a specific position on a molecule.
In chemistry, 'regioselectivity' is about controlling where a reaction happens on a molecule. It's important because different positions can lead to different products with varying effects. For drug development, precise regioselectivity ensures that the active ingredient binds correctly and produces the intended outcome.
halogenases
Enzymes that catalyze the regiospecific halogenation of organic molecules.
Halogenases are special enzymes that add halogens (like chlorine or bromine) to other molecules in a controlled way. This process is crucial for various biological functions and has applications in drug development. Scientists study these enzymes to develop new methods for synthesizing pharmaceuticals with higher efficiency and precision.
Relative Binding Free Energy (RBFE)
Relative Binding Free Energy calculations
RBFE calculations are a computational tool used in drug discovery to predict how well a molecule will bind to its target. By simulating the interactions between molecules, researchers can identify promising drug candidates and optimize their design for better efficacy.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:26:08|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:26:08|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|---|---|---|---|---|
| 1 | EPYC 7V12 64-CORE | 64 | 5,266 | 337,024 | AMD |
| 2 | CORE I9-10900X CPU @ 3.70GHZ | 20 | 14,803 | 296,060 | Intel |
| 3 | 11TH GEN CORE I7-11700K @ 3.60GHZ | 16 | 14,144 | 226,304 | Intel |
| 4 | RYZEN 7 PRO 4750G | 16 | 13,965 | 223,440 | AMD |
| 5 | CORE I5-4590 CPU @ 3.30GHZ | 4 | 17,407 | 69,628 | Intel |
| 6 | CORE I5-7400 CPU @ 3.00GHZ | 4 | 16,184 | 64,736 | Intel |
| 7 | CORE I5-4570 CPU @ 3.20GHZ | 4 | 14,799 | 59,196 | Intel |
| 8 | CORE I5-6600K CPU @ 3.50GHZ | 4 | 14,377 | 57,508 | Intel |