Related Experiment Video
Updated: Feb 11, 2026
06:10
Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
1.5K
Recent advances in automated protein design and its future challenges
Dani Setiawan1, Jeffrey Brender2, Yang Zhang1,3
1a Department of Computational Medicine and Bioinformatics , University of Michigan , Ann Arbor , MI , USA.
Expert Opinion on Drug Discovery
|April 27, 2018
Summary
Automated protein design uses computational methods to engineer novel protein structures and functions. This approach offers advanced protein engineering capabilities for drug discovery and basic biological research.
Area of Science:
- Computational biology
- Protein engineering
- Drug discovery
Background:
- Protein structure and function are dictated by amino acid sequences.
- Understanding protein folding rules enables targeted modification of protein properties.
- Traditional protein engineering faces limitations in achieving complex or novel designs.
Purpose of the Study:
- To provide an overview of recent advances in computer-aided protein design.
- To explore the application of automated protein design in drug development and biological research.
- To identify future challenges in automated protein design methodologies.
Main Methods:
- Computational analysis of mutation effects on protein structure and function.
- Methodological advancements in computer-aided protein design.
- Exploration of novel protein scaffold creation for therapeutic applications.
Main Results:
- Automated protein design allows for more complex protein modifications than experimental methods.
- This technology can address challenges beyond traditional protein engineering.
- Novel protein scaffolds can be designed for drug development.
Conclusions:
- Automated protein design is a promising protein engineering technique, especially for complex targets.
- It serves as a valuable research tool for exploring basic biology and aiding drug discovery.
- Challenges remain in addressing solubility and immunogenicity for direct therapeutic applications.
Related Concept Videos
02:01Factorial Design
14.1K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
14.1K
02:01Group Design
10.7K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
10.7K
02:22Overview of Advanced Functional Groups
30.2K
Functional groups are groups of atoms with specific chemical properties that occur within organic molecules and are sometimes denoted as “R”. Functional groups can “functionalize” a compound by enabling it to adopt different physical and chemical properties.
Types of Advanced Functional Groups
The table below summarizes some of the major functional groups in organic chemistry.
30.2K
00:56Extraction: Advanced Methods
1.2K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.2K
01:25Design Example: Designing a Residential Plumbing System
1.1K
The design of residential plumbing systems requires carefully evaluating water demand, flow rates, and pressure dynamics to ensure both efficiency and reliability. The nature of water flow within pipes is defined by its Reynolds number, which classifies flow as either laminar (smooth) or turbulent.
1.1K
01:18Design Example: Designing Water Slide
638
When designing a water slide, controlling the speed of water flow is crucial for rider safety while maintaining an exciting experience. As water flows down the slide, gravity causes it to accelerate, with its speed at the bottom depending on the height from which it starts. The higher the slide, the more potential energy the water has at the top, which is converted into kinetic energy as it descends, increasing its speed.
Bernoulli's principle determines the water's velocity along the slide....
Bernoulli's principle determines the water's velocity along the slide....
638