Protein design

The Top7

[[File:1FSVblue-1ZAAred.png|FSD-1 (shown in blue, PDB id: 1FSV) was the first de novo computational design of a full protein.<ref name="dahiyat1997">

Common protein design programs use rotamer libraries to simplify the conformational space of protein side chains. This animation loops through all the rotamers of the isoleucine amino acid based on the Penultimate Rotamer Library (total of 7 rotamers).

Comparison of various potential energy functions. The most accurate energy are those that use quantum mechanical calculations, but these are too slow for protein design. On the other extreme, heuristic energy functions are based on statistical terms and are very fast. In the middle are molecular mechanics energy functions that are physically-based but are not as computationally expensive as quantum mechanical simulations.<ref name="Boas"/>

[[File:Water-hbond-vrc01-gp120.png|left|Water-mediated hydrogen bonds play a key role in protein–protein binding. One such interaction is shown between residues D457, S365 in the heavy chain of the HIV-broadly-neutralizing antibody VRC01 (green) and residues N58 and Y59 in the HIV envelope protein GP120 (purple).<ref name="wu2010">

based on deriving energy values

Protein design is the process of creating new proteins or altering the structures of existing proteins to have new, desired properties. This field combines elements of biochemistry, molecular biology, biophysics, and computational biology to understand protein folding and structure-function relationships, with the ultimate goal of designing proteins with specific functions. These designed proteins have applications in medicine, biotechnology, and materials science.

Overview

Protein design involves the prediction and design of protein structures that perform specific functions. This is achieved by understanding the principles of protein structure and folding, which are dictated by the sequence of amino acids that make up the protein. The process often uses computational methods to model proteins and predict how changes in amino acid sequences will affect the protein's structure and function.

Methods

Several methods are employed in protein design, including:

• Rational Design: This method uses detailed knowledge of the structure and function of a protein to make specific changes to its amino acid sequence.
• Directed Evolution: This technique mimics natural evolutionary processes in the lab, using methods such as DNA shuffling to generate a library of protein variants, which are then screened for desired traits.
• De Novo Design: This approach involves designing proteins from scratch, using principles of protein structure and stability without relying on natural protein sequences as templates.
• Computational Protein Design: This method uses computer algorithms to predict the amino acid sequences that will fold into a desired structure.

Applications

Protein design has a wide range of applications, including:

• Enzyme Design: Designing enzymes with novel catalytic activities or specificities for use in industrial processes or chemical synthesis.
• Therapeutic Proteins: Designing proteins with therapeutic properties, such as novel antibodies, hormones, or enzymes for use in treating diseases.
• Biomaterials: Designing proteins that can form new materials with specific mechanical properties or biological functions.
• Synthetic Biology: Creating new proteins to be used in synthetic biology applications, such as biosensors or novel metabolic pathways.

Challenges

Despite significant advances, protein design faces several challenges, including:

• Predicting how changes in amino acid sequence will affect protein folding and stability.
• Designing proteins that are not only stable and functional but also can be efficiently produced and purified.
• Overcoming the complexity of designing proteins that interact with other molecules or systems in predictable ways.

Future Directions

The future of protein design is promising, with ongoing research focusing on improving computational methods for protein design, exploring new applications in medicine and industry, and understanding the fundamental principles of protein structure and function. Advances in artificial intelligence and machine learning are also expected to play a significant role in accelerating protein design research.

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