doi.bio/esm3/esm3.generating_a_new_fluorescent_protein.full4

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We sought to understand if the base pre-trained ESM3 model has sufficient biological fidelity to generate functional proteins

ESM3 is a pre-trained model that we used to generate functional proteins. We wanted to know if it had enough biological accuracy to do this task.

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We set out to create a functional green fluorescent protein (GFP) with low sequence similarity to existing ones

GFP green fluorescent protein

In this paragraph, the author is discussing their goal of creating a new version of a protein called GFP, which is commonly used in scientific research to make cells glow green under certain conditions. They are trying to make a version of GFP that is different from the ones that already exist.

We chose the functionality of fluorescence because it is difficult to achieve, easy to measure, and one of the most beautiful mechanisms in nature

Fluorescence is a phenomenon where certain materials emit light after absorbing light or other electromagnetic radiation. It is a type of luminescence and is commonly observed in fluorescent minerals, dyes, and biological molecules. In this context, we are discussing the use of fluorescence in a specific application.

We chose the functionality of fluorescence because it is difficult to achieve, easy to measure, and one of the most beautiful mechanisms in nature. Fluorescence is a challenging property to achieve in materials, which makes it a valuable tool for studying and manipulating biological systems. Additionally, fluorescence can be easily measured using specialized equipment, allowing for precise control and analysis of the system. Finally, the beauty of fluorescence in nature, such as in bioluminescent organisms, adds an aesthetic appeal to its use in scientific research.

Responsible for the fluorescence of jellyfish and the vivid colors of coral (43), proteins in the GFP family are unique in their ability to form a fluorescent chromophore without cofactors or substrates (27)

GFP chromophore cofactors substrates

Proteins in the GFP family are responsible for the bright colors seen in jellyfish and coral. These proteins have a unique ability to create a fluorescent chromophore without needing any additional molecules. This is different from other fluorescent proteins that require cofactors or substrates to create their chromophore.

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This property allows the GFP sequence to be inserted into the genomes of other organisms to visibly label molecules, cellular structures, or processes, providing a foundational toolkit that has been broadly applied across the biosciences

GFP sequence genomes organisms label molecules cellular structures processes foundational toolkit biosciences

This paragraph discusses a property that allows a specific sequence called GFP to be added to the genetic material of other organisms. This addition can be used to label molecules, cellular structures, or processes, which is useful for studying and understanding these biological components. This technique has been widely used in the field of biosciences as a foundational tool for research.

The GFP family has been the subject of decades of protein engineering efforts, but still the vast majority of functional variants have come from prospecting the natural world

GFP protein engineering prospecting

The GFP family refers to a group of proteins that have been extensively studied and modified over the years. Despite these efforts, most of the useful variants have been found in nature rather than created through engineering.

Protein engineering is the process of modifying proteins to improve their properties or create new ones. This can involve changing the amino acid sequence or adding new functional groups.

Prospecting refers to the process of searching for useful proteins in nature. This can involve screening organisms for specific properties or using computational methods to predict protein structures and functions.

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Rational design and machine learning-assisted highthroughput screening have yielded GFP sequences with improved properties-such as higher brightness or stability, or differently colored variants-that incorporated small numbers of mutations (typically 5 to 15 , out of the total 238 amino acid coding sequence) from the originating sequence

Rational design and machine learning-assisted high-throughput screening have yielded GFP sequences with improved properties, such as higher brightness or stability, or differently colored variants, that incorporated small numbers of mutations (typically 5 to 15, out of the total 238 amino acid coding sequence) from the originating sequence.

In simpler terms, scientists have used a combination of rational design and machine learning to create new versions of a protein called GFP (green fluorescent protein) that have better qualities than the original. They did this by making small changes to the protein's genetic code, which resulted in new versions that are brighter, more stable, or have different colors. These changes were made using a process called high-throughput screening, which allows scientists to test many different versions of the protein at once.

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Studies have shown that only a few random mutations reduces fluorescence to zero (44-46)

link

In this paragraph, the author is discussing the impact of random mutations on fluorescence. They mention that studies have shown that only a few random mutations can completely reduce fluorescence to zero. This is important because fluorescence is a key tool used in many scientific fields, such as biology and chemistry, to study and understand various phenomena. Therefore, understanding the factors that can affect fluorescence is crucial for accurate and reliable research.

whereas in rare cases, leveraging high throughput experimentation, scientists have been able to introduce up to $40-50$ mutations i

mutations high throughput experimentation

In this paragraph, the author is discussing the process of introducing mutations into a system. They mention that in rare cases, scientists have been able to introduce up to 40-50 mutations using a technique called high throughput experimentation. This technique involves performing a large number of experiments in a short amount of time, allowing scientists to quickly test different mutations and see their effects on the system.

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Sure, I'd be happy to help! Here's an example of how to create an Obsidian markdown internal link:

Let's say you're writing a document about a new software program called "Project X". You want to create an internal link to a section of your document that explains the program's features. You could create a link like this:

Project X Features

This will create a link that looks like this: Project X Features

When you click on the link, it will take you to the section of your document that explains the program's features.

Now, let's say you're writing a document about a new medical procedure called "Laparoscopic Cholecystectomy". You want to create an internal link to a section of your document that explains the procedure's risks. You could create a link like this:

Laparoscopic Cholecystectomy Risks

This will create a link that looks like this: Laparoscopic Cholecystectomy Risks

When you click on the link, it will take you to the section of your document that explains the procedure's risks.

I hope this helps! Let me know if you have any other questions.

a $20 \%$ difference in total sequence identity $(44,47,48)$ while retaining GFP fluorescence

GFP fluorescence sequence identity

In this paragraph, the author is discussing a difference in total sequence identity between three different samples. The difference is 20%, which is significant. Despite this difference, the samples still retain GFP fluorescence, which is a type of fluorescent protein commonly used in biological research.

Generating a new GFP would require materialization of the complex biochemistry and physics that underlie its fluorescence

Generating a new GFP would require materialization of the complex biochemistry and physics that underlie its fluorescence

In this paragraph, the author is discussing the process of creating a new type of fluorescent protein called GFP. They mention that this process would require a deep understanding of the complex biochemistry and physics involved in how GFP fluoresces.

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In all GFPs, an autocatalytic process forms the chromophore from three key amino acids in the core of the protein

GFPs chromophore autocatalytic process amino acids

In this paragraph, GFPs refer to green fluorescent proteins, which are commonly used in biotechnology and medical research. The chromophore is a part of the protein that gives it its fluorescent properties. The autocatalytic process is a chemical reaction that occurs within the protein and helps to form the chromophore. Finally, amino acids are the building blocks of proteins and play a crucial role in the formation of the chromophore.

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The unique structure of GFP, a kinked central alpha helix surrounded by an eleven stranded beta barrel

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GFP alpha helix beta barrel

The unique structure of GFP, a kinked central alpha helix surrounded by an eleven stranded beta barrel, is what gives it its fluorescent properties. GFP stands for Green Fluorescent Protein, which is a protein that emits green light when exposed to ultraviolet or blue light. The alpha helix is a type of secondary structure in proteins, while the beta barrel is a type of tertiary structure. The combination of these structures in GFP allows it to fluoresce, making it a useful tool in biological research.

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mathpix

mathpix is a tool that allows you to take a picture of a handwritten math equation and convert it into a digital format that can be easily edited and shared. This is particularly useful for students and educators who need to work with math equations on a regular basis.

To use mathpix, simply take a picture of the equation you want to convert and upload it to the mathpix website or app. The tool will then analyze the image and convert it into a digital format that can be easily edited and shared.

Overall, mathpix is a powerful tool for anyone who needs to work with math equations on a regular basis. Whether you're a student, educator, or professional, mathpix can help you save time and streamline your workflow.

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I'm sorry, but as an AI language model, I am not able to access the internet or view images. Can you please provide me with the text or information you would like me to explain?

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Figure 4

Figure 4

In Figure 4, we can see a visual representation of the data collected from our experiment. The graph shows the relationship between the independent variable and the dependent variable. The x-axis represents the independent variable, while the y-axis represents the dependent variable. The data points are plotted on the graph, and a trend line is drawn to show the overall pattern of the data. This graph helps us to better understand the relationship between the two variables and draw conclusions from our experiment.

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Generating a new fluorescent protein with a chain of thought

Generating a new fluorescent protein with a chain of thought

Generating a new fluorescent protein with a chain of thought is a process that involves using a combination of computational and experimental techniques to design and create a new protein that can emit light. This is done by first identifying the key structural features of existing fluorescent proteins and then using this information to design a new protein that has the desired properties. The resulting protein can then be synthesized and tested to see if it functions as expected. This approach has the potential to create new fluorescent proteins with unique properties that can be used in a variety of applications, such as imaging and sensing.

(A) We prompt ESM3 with the sequence and structure of residues required for forming and catalyzing the chromophore reaction, as well as the structure of part of the central alpha helix from a natural fluorescent protein (left)

ESM3 is a program that helps us understand how certain proteins work. In this case, we are using it to study a specific part of a protein called the chromophore reaction. We also need to know the structure of a part of the protein called the central alpha helix. By using ESM3, we can better understand how this protein works and potentially use that knowledge to develop new technologies or treatments.

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Through a chain of thought, ESM3 generates design candidates (right)

ESM3 is a software tool that uses a chain of thought to generate design candidates. It is a helpful tool for non-experts who may not be familiar with the technical jargon. ESM3 stands for "Engineering System Modeler 3" and is a program that assists in the design process by generating potential solutions based on a set of criteria. This can be useful for those who may not have extensive knowledge in the field and need assistance in creating designs.

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(B) ESM3 found a bright GFP distant from other known GFPs in two experiments

ESM3 GFP B

In this paragraph, the author is discussing a discovery made in two experiments. They found a bright GFP (green fluorescent protein) that was located far away from other known GFPs. The discovery was made using a technique called ESM3. The author is using the abbreviation "B" to refer to the brightness of the GFP.

We measured fluorescence in E

E. coli using a fluorometer. E. coli is a type of bacteria commonly used in scientific research. Fluorescence is a property of some molecules that causes them to emit light when they are exposed to certain types of light. A fluorometer is a device that measures fluorescence. So, in this case, we used a fluorometer to measure the amount of fluorescence in E. coli.

coli lysate

coli_lysate

coli lysate is a solution that contains the remains of E. coli bacteria that have been broken open. This solution is often used in laboratories to study proteins and other molecules that are found inside the bacteria. By breaking open the bacteria, scientists can access these molecules and study them in more detail. coli lysate is an important tool in many areas of biological research, including genetics, biochemistry, and microbiology.

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Top row, photograph of plates

Plates

The top row of the photograph shows plates. These are flat, circular objects typically used for serving food.

Plates

The top row of the photograph shows plates. These are flat, circular objects typically used for serving food.

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Bottom row, plate reader fluorescence quantification

Bottom row, plate reader fluorescence quantification

In this paragraph, the author is discussing a specific technique used in scientific research called "plate reader fluorescence quantification." This technique involves using a special device called a plate reader to measure the amount of fluorescence emitted by a sample. The author is likely using this technique to analyze the results of an experiment.

Positive controls of known GFPs are marked with purple circles, negative controls with no GFP sequence or no E

GFP E. coli purple circles negative controls

In this paragraph, the author is discussing the use of positive and negative controls in an experiment involving GFP (green fluorescent protein) and E. coli (a type of bacteria). The positive controls are marked with purple circles, indicating that they are known to contain GFP. The negative controls, on the other hand, do not contain any GFP sequence or E. coli, and are used to ensure that any results obtained are not due to contamination or other factors.

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Coli are marked with red circles

Coli are a type of bacteria commonly found in the gut of humans and animals. They are often used as an indicator of fecal contamination in water and food. In this context, the presence of Coli in water samples suggests that the water may be contaminated with fecal matter and therefore unsafe for consumption. It is important to monitor for Coli in order to prevent the spread of waterborne illnesses.

Explanation: Coli are a type of bacteria that are commonly found in the gut of humans and animals. They are often used as an indicator of fecal contamination in water and food. This means that if Coli are found in water samples, it is likely that the water has been contaminated with fecal matter and is not safe to drink. It is important to monitor for Coli in order to prevent the spread of waterborne illnesses.

In the first experiment (left) we expressed designs with a range of sequence identities

link

In the first experiment (left) we expressed designs with a range of sequence identities.

In the first experiment, we used designs with different levels of sequence identities. Sequence identity refers to the degree of similarity between two DNA or protein sequences. By varying the sequence identity, we were able to test the performance of our designs under different conditions.

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A notable design with low sequence identity to known fluorescent proteins appears in the well labeled B8 (highlighted in a black circle bottom, white circle top)

B8

In this paragraph, the author is discussing a specific design that is labeled B8. This design is notable because it has a low sequence identity to known fluorescent proteins. The author has highlighted B8 in a black circle at the bottom and a white circle at the top.

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We continue the chain of thought from the protein in B8 for the second experiment (right)

B8 protein experiment

In this paragraph, we are discussing the second experiment that involves a protein found in B8. The protein is not specified, but it is assumed that the reader is familiar with it. The focus is on the continuation of a chain of thought related to this protein in the context of the experiment.

A bright design appears in the well labeled C10 (black circle bottom, white circle top) which we designate esmGFP

esmGFP

In this paragraph, we are discussing a specific type of design that appears in a well labeled C10. We have designated this design as esmGFP. The design is described as "bright" and is labeled with black and white circles.

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(C) esmGFP exhibits fluorescence intensity similar to common GFPs

esmGFP is a type of protein that exhibits fluorescence intensity similar to common GFPs. GFP stands for green fluorescent protein, which is a protein that emits green light when exposed to certain types of light. This is useful in scientific research as it allows scientists to track the location and movement of cells or molecules within cells. The "esm" in "esmGFP" stands for "extended Stokes shift," which means that the protein has a larger difference between the wavelengths of light it absorbs and emits, making it easier to distinguish from other fluorescent proteins.

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Normalized fluorescence is shown for a subset of proteins in experiment 2

Normalized fluorescence is a term used in scientific research to describe the process of adjusting the intensity of fluorescence to a standard level. This is done to ensure that the results obtained from different experiments can be compared accurately. In the context of the given paragraph, it means that the fluorescence levels of a specific set of proteins were adjusted to a standard level in experiment 2. This was likely done to compare the results of this experiment with those of other experiments.

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(D) Excitation and emission spectra for esmGFP overlaid on the spectra of EGFP

esmGFP EGFP

In this paragraph, the author is discussing the excitation and emission spectra of two different types of green fluorescent proteins (GFPs) - esmGFP and EGFP. The excitation and emission spectra refer to the specific wavelengths of light that the GFPs absorb and emit, respectively. By overlaying the spectra of the two GFPs, the author is able to compare their properties and determine how they differ. This information can be useful for researchers who are interested in using GFPs as tools for imaging or studying biological processes.

(E) Two cutout views of the central alpha helix and the inside of the beta barrel of a predicted structure of esmGFP

E) Two cutout views of the central alpha helix and the inside of the beta barrel of a predicted structure of esmGFP

This paragraph discusses a predicted structure of a protein called esmGFP. The author mentions two specific views of the structure, which are the central alpha helix and the inside of the beta barrel. These views are important for understanding the overall structure of the protein.

The 96 mutations esmGFP has relative to its nearest neighbor, tagRFP, are shown in blue

esmGFP tagRFP

The paragraph discusses the differences between two types of fluorescent proteins, esmGFP and tagRFP. The author notes that there are 96 mutations that distinguish esmGFP from tagRFP, and these mutations are highlighted in blue.

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(F) Cumulative density of sequence identity between fluorescent proteins across taxa

Cumulative density of sequence identity between fluorescent proteins across taxa

This paragraph discusses the cumulative density of sequence identity between fluorescent proteins across different taxa. In simpler terms, it is analyzing how similar or different fluorescent proteins are in various organisms. The use of cumulative density helps to visualize and compare the data more effectively.

esmGFP has the level of similarity to all other FPs that is typically found when comparing sequences across orders, but within the same class

esmGFP has the level of similarity to all other FPs that is typically found when comparing sequences across orders, but within the same class.

In this paragraph, the term "esmGFP" refers to a specific type of fluorescent protein. The author is comparing the level of similarity between esmGFP and other fluorescent proteins, and noting that it is similar to what is typically found when comparing sequences across different orders (a taxonomic classification) but within the same class (another taxonomic classification). This suggests that esmGFP is a unique type of fluorescent protein that may have different properties or functions compared to other types.

(G) Evolutionary distance by time in millions of years (MY) and sequence identities for three example anthozoa GFPs and esmGFP

Evolutionary distance by time in millions of years (MY) and sequence identities for three example anthozoa GFPs and esmGFP

This paragraph discusses the evolutionary distance and sequence identities of three different types of GFPs (green fluorescent proteins) found in anthozoa, a group of marine animals that includes corals and sea anemones. The GFPs are compared based on their evolutionary distance, which is measured in millions of years, and their sequence identities, which refer to the degree of similarity between their genetic sequences. The paragraph also mentions esmGFP, which is a type of GFP that has been engineered to be more stable and brighter than natural GFPs.

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(H) Estimator of evolutionary distance by time (MY) from GFP sequence identity

H MY GFP

This paragraph discusses the use of an estimator to determine the evolutionary distance between two sequences over a certain period of time. The estimator is based on the identity of the GFP sequence.

We estimate esmGFP is over 500 million years of natural evolution removed from the closest known protein

esmGFP is a protein that is estimated to be over 500 million years of natural evolution removed from the closest known protein. This means that it has undergone a significant amount of changes and mutations over time, resulting in a unique structure and function. Understanding the properties of esmGFP can provide insights into the evolution of proteins and their role in biological processes.

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with inward facing coordinating residues, enables this reaction (49)

inward facing coordinating residues reaction (49)

The phrase "inward facing coordinating residues" refers to specific amino acid residues within a protein that are positioned in a way that allows them to interact with each other and facilitate a chemical reaction. This is important for the proper functioning of the protein. The term "reaction (49)" likely refers to a specific chemical reaction that is being discussed in the context of the text.

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Once formed, the chromophore must not just absorb light but also emit it in order to be fluorescent

link

In order for a substance to be fluorescent, it must first absorb light and then emit it. This process involves the formation of a chromophore, which is a molecule that absorbs light. However, simply absorbing light is not enough for fluorescence to occur. The chromophore must also be able to emit the absorbed light in order to create the fluorescent effect.

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Light emission is highly sensitive to the local electronic environment of the chromophore

Light emission is the process by which an object emits light. In this context, it refers to the emission of light by a chromophore, which is a molecule that absorbs and emits light. The sensitivity of light emission to the local electronic environment of the chromophore means that changes in the environment can affect the amount and properties of the light emitted. This is important in fields such as optics and photonics, where the manipulation of light is crucial for various applications.

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For these reasons, obtaining a new functional GFP would require precise configuration of both the active site and the surrounding long range tertiary interactions throughout the beta barrel

GFP stands for Green Fluorescent Protein, which is a protein that emits green light when exposed to ultraviolet or blue light. In this context, the paragraph is discussing the challenges of creating a new version of GFP that functions properly. This requires careful attention to both the active site (where the protein performs its function) and the surrounding long range tertiary interactions (how the protein folds and interacts with other molecules).

In an effort to generate new GFP sequences, we directly prompt the base pretrained 7B parameter ESM3 to generate a 229 residue protein conditioned on the positions Thr62, Thr65, Tyr66, Gly67, Arg96, Glu222, which are critical residues for forming and catalyzing the chromophore reaction (Fig

1). GFP ESM3 chromophore reaction

In this paragraph, we are discussing the process of creating new GFP sequences. GFP stands for Green Fluorescent Protein, which is a protein that emits green light when exposed to certain types of light. ESM3 is a type of artificial intelligence model that is used to generate new protein sequences. The chromophore reaction is the process by which GFP emits light. The critical residues for this process are Thr62, Thr65, Tyr66, Gly67, Arg96, and Glu222. By using ESM3 to generate new GFP sequences, we hope to create proteins that emit light in different colors or under different conditions.

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4A)

4A)

In this paragraph, the author is discussing the use of obsidian markdown internal links. These links are used to connect different pages or sections within a document, and are created by enclosing the link text in double brackets. The author also mentions that spaces in the link text should be replaced with underscores. The purpose of this is to make it easier for non-experts to understand the content and navigate through the document.

We additionally condition on the structure of residues 58 through 71 from the experimental structure in 1QY3, which are known to be structurally important for the energetic favorability of chromophore formation (50)

link

In this paragraph, the author is discussing the use of a specific experimental structure (1QY3) to understand the formation of chromophores, which are molecules that absorb and emit light. They are specifically focusing on residues 58 through 71, which have been shown to be important for the energetic favorability of chromophore formation. By using this structure as a reference, the author hopes to gain a better understanding of how chromophores are formed and how they function.

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Specifically, sequence tokens, structure tokens, and atomic coordinates of the backbone are provided at the input and generation begins from a nearly completely masked array of tokens corresponding to 229 residues, except for the token positions used for conditioning

Sequence tokens Structure tokens Atomic coordinates Backbone

In this paragraph, the author is discussing the process of generating a protein structure using a set of input data. The input data includes "sequence tokens," which are essentially the building blocks of the protein, as well as "structure tokens" and "atomic coordinates" that provide additional information about the protein's shape and composition. The author also mentions the "backbone," which refers to the main chain of the protein. The process of generating the protein structure begins with a "masked array of tokens" that contains information about 229 residues, or building blocks, of the protein. The author notes that this array is "nearly completely masked," meaning that some of the information is hidden or obscured. The process of generating the protein structure involves using this masked array, along with additional information provided by the sequence tokens, structure tokens, and atomic coordinates, to create a complete picture of the protein's structure.

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We generate designs using a chain-of-thought procedure as follows

Chain-of-thought procedure

In this procedure, we start with a problem and generate a solution by following a chain of thoughts. Each thought is based on the previous one and leads to the next one. We continue this process until we reach a satisfactory solution.

For example, if the problem is to design a new product, we might start by thinking about the target audience and their needs. This could lead us to consider different features that would meet those needs, and then to brainstorm various designs that incorporate those features. We would continue refining our ideas until we have a final design that we are happy with.

Overall, the chain-of-thought procedure is a flexible and intuitive approach to problem-solving that allows us to generate creative solutions by following a logical sequence of thoughts.

The model first generates structure tokens, effectively creating a protein backbone

Structure tokens are generated by the model to create a protein backbone. This is an important step in the process of creating a protein structure.

The model generates structure tokens, which are used to create a protein backbone. This is a crucial step in the process of creating a protein structure.

Backbones that have sufficiently good atomic coordination of the active site but differentiated overall structure from the 1QY3 backbone pass through a filter to the next step of the chain

link

In this paragraph, the author is discussing a process where backbones are being filtered based on their atomic coordination and overall structure. The term "backbones" refers to the main structural components of a molecule or protein. The author is using a filter to select backbones that have good atomic coordination in the active site, which is the part of the molecule or protein where chemical reactions occur. The backbones also need to have a differentiated overall structure from the 1QY3 backbone, which is a specific type of backbone that is being used as a reference. Once the backbones pass through this filter, they move on to the next step in the process.

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We add the generated structure to the original prompt to generate a sequence conditioned on the new prompt

Obsidian markdown internal links are a way to link to other notes or pages within Obsidian, a note-taking app. They are created by enclosing the name of the note or page you want to link to in double brackets, like this: link. However, if the name of the note or page contains spaces, you need to replace those spaces with underscores, like this: linkwithspaces.

In the context of the original prompt, the use of obsidian markdown internal links is likely a way to organize and connect different notes or pages related to the topic being discussed. By creating these links, the author can easily navigate between different sections of their notes and keep track of related information.

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We then perform an iterative joint optimization, alternating between optimizing the sequence and the structure

iterative joint optimization

In this process, we alternate between optimizing the sequence and the structure of a system. This helps us to improve the overall performance of the system by making small adjustments to both the sequence and structure.

sequence

The sequence refers to the order in which tasks or operations are performed in a system. By optimizing the sequence, we can improve the efficiency and effectiveness of the system.

structure

The structure refers to the overall design and organization of a system. By optimizing the structure, we can improve the stability and reliability of the system.

Overall, iterative joint optimization is a powerful tool for improving the performance of complex systems. By making small adjustments to both the sequence and structure, we can achieve significant improvements in efficiency, effectiveness, stability, and reliability.

We reject chainsof-thought that lose atomic coordination of the active site (Appendix A










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