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In a series of eight lectures, this course will explore the digital nature of biology at the molecular scale.
The course will focus on novel interactions in protein/ligand associations, in particular, on the role of the hydrophobic effect in protein/ligand associations.
Protein interactions are discrete in nature even though hydrophobic effects are non-specific in general. There is a useful analogy with the duality between the analog and digital nature of computer chips. We refer to this study as the Digital Biology Project. We pursue basic biophysical issues but we also apply our ideas to biomedical problems, e.g., to contribute to the understanding of antibody binding and to drug design.
The course will primarily utilize data-mining as a tool both to understand basic biophysics and to explain protein-ligand associations. It will explore the connections among the following well known but seemingly contradictory facts:
Proteins are highly specific (and deterministic, or repeatable) in the way that they interact in many of their functions which involve other proteins and other ligands
The hydrophobic effect, which is highly non-specific, is critical in protein-ligand interaction
In the process of explaining this seeming contradiction, we must confront three other facts about biomolecular systems:
Electrical gradients in proteins are among the strongest in nature, but they get modulated by the dielectric effect of water
The dielectric properties of water are among the strongest in nature
Hydrophobic groups in proteins cause large changes in the dielectric properties of water
These facts make for the strange world in which proteins struggle for survival in an aqueous environment. The course will describe the use of datamining to understand the biophysics of proteins, and we will review basic structural information about water. We will also discuss some changes at the quantum level caused by the large-scale hydrophobic and electronic environment.
Implications for protein folding models will be discussed.
No particular background beyond high-school chemistry and advanced calculus will be assumed. All prerequisites will be provided in the class. We will explore issues in computer science, applied mathematics, physical chemistry and biomedical applications. It is hoped that people from different disciplines will participate.
The course will be based on a forthcoming book to be distributed to the class.
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GUEST SPEAKER SCHEDULE:
Tuesday, November 3rd:;Tatiana Orlova -; Hydrogen bonds in protein structure
Thursday, November 5th:;;Ariel Fernandez Stigliano -; The dehydron as a catalytic device
Lecturer : Ridgway Scott, University of Chicago
Dates : October 8th, 20th, 22nd / November 3rd, 5th, 10th, 12th, 24th
Time : 12:40PM - 2:10 PM
In a series of eight lectures, this course will explore the digital nature of biology at the molecular scale.
The course will focus on novel interactions in protein/ligand associations, in particular, on the role of the hydrophobic effect in protein/ligand associations.
Protein interactions are discrete in nature even though hydrophobic effects are non-specific in general. There is a useful analogy with the duality between the analog and digital nature of computer chips. We refer to this study as the Digital Biology Project. We pursue basic biophysical issues but we also apply our ideas to biomedical problems, e.g., to contribute to the understanding of antibody binding and to drug design.
The course will primarily utilize data-mining as a tool both to understand basic biophysics and to explain protein-ligand associations. It will explore the connections among the following well known but seemingly contradictory facts:
Proteins are highly specific (and deterministic, or repeatable) in the way that they interact in many of their functions which involve other proteins and other ligands
The hydrophobic effect, which is highly non-specific, is critical in protein-ligand interaction
In the process of explaining this seeming contradiction, we must confront three other facts about biomolecular systems:
Electrical gradients in proteins are among the strongest in nature, but they get modulated by the dielectric effect of water
The dielectric properties of water are among the strongest in nature
Hydrophobic groups in proteins cause large changes in the dielectric properties of water
These facts make for the strange world in which proteins struggle for survival in an aqueous environment. The course will describe the use of datamining to understand the biophysics of proteins, and we will review basic structural information about water. We will also discuss some changes at the quantum level caused by the large-scale hydrophobic and electronic environment.
Implications for protein folding models will be discussed.
No particular background beyond high-school chemistry and advanced calculus will be assumed. All prerequisites will be provided in the class. We will explore issues in computer science, applied mathematics, physical chemistry and biomedical applications. It is hoped that people from different disciplines will participate.
The course will be based on a forthcoming book to be distributed to the class.
-
GUEST SPEAKER SCHEDULE:
Tuesday, November 3rd:;Tatiana Orlova -; Hydrogen bonds in protein structure
Thursday, November 5th:;;Ariel Fernandez Stigliano -; The dehydron as a catalytic device
Lecturer : Ridgway Scott, University of Chicago
Dates : October 8th, 20th, 22nd / November 3rd, 5th, 10th, 12th, 24th
Time : 12:40PM - 2:10 PM
In a series of eight lectures, this course will explore the digital nature of biology at the molecular scale.
The course will focus on novel interactions in protein/ligand associations, in particular, on the role of the hydrophobic effect in protein/ligand associations.
Protein interactions are discrete in nature even though hydrophobic effects are non-specific in general. There is a useful analogy with the duality between the analog and digital nature of computer chips. We refer to this study as the Digital Biology Project. We pursue basic biophysical issues but we also apply our ideas to biomedical problems, e.g., to contribute to the understanding of antibody binding and to drug design.
The course will primarily utilize data-mining as a tool both to understand basic biophysics and to explain protein-ligand associations. It will explore the connections among the following well known but seemingly contradictory facts:
Proteins are highly specific (and deterministic, or repeatable) in the way that they interact in many of their functions which involve other proteins and other ligands
The hydrophobic effect, which is highly non-specific, is critical in protein-ligand interaction
In the process of explaining this seeming contradiction, we must confront three other facts about biomolecular systems:
Electrical gradients in proteins are among the strongest in nature, but they get modulated by the dielectric effect of water
The dielectric properties of water are among the strongest in nature
Hydrophobic groups in proteins cause large changes in the dielectric properties of water
These facts make for the strange world in which proteins struggle for survival in an aqueous environment. The course will describe the use of datamining to understand the biophysics of proteins, and we will review basic structural information about water. We will also discuss some changes at the quantum level caused by the large-scale hydrophobic and electronic environment.
Implications for protein folding models will be discussed.
No particular background beyond high-school chemistry and advanced calculus will be assumed. All prerequisites will be provided in the class. We will explore issues in computer science, applied mathematics, physical chemistry and biomedical applications. It is hoped that people from different disciplines will participate.
The course will be based on a forthcoming book to be distributed to the class.
-
GUEST SPEAKER SCHEDULE:
Tuesday, November 3rd:;Tatiana Orlova -; Hydrogen bonds in protein structure
Thursday, November 5th:;;Ariel Fernandez Stigliano -; The dehydron as a catalytic device
Lecturer : Ridgway Scott, University of Chicago
Dates : October 8th, 20th, 22nd / November 3rd, 5th, 10th, 12th, 24th
Time : 12:40PM - 2:10 PM
In a series of eight lectures, this course will explore the digital nature of biology at the molecular scale.
The course will focus on novel interactions in protein/ligand associations, in particular, on the role of the hydrophobic effect in protein/ligand associations.
Protein interactions are discrete in nature even though hydrophobic effects are non-specific in general. There is a useful analogy with the duality between the analog and digital nature of computer chips. We refer to this study as the Digital Biology Project. We pursue basic biophysical issues but we also apply our ideas to biomedical problems, e.g., to contribute to the understanding of antibody binding and to drug design.
The course will primarily utilize data-mining as a tool both to understand basic biophysics and to explain protein-ligand associations. It will explore the connections among the following well known but seemingly contradictory facts:
Proteins are highly specific (and deterministic, or repeatable) in the way that they interact in many of their functions which involve other proteins and other ligands
The hydrophobic effect, which is highly non-specific, is critical in protein-ligand interaction
In the process of explaining this seeming contradiction, we must confront three other facts about biomolecular systems:
Electrical gradients in proteins are among the strongest in nature, but they get modulated by the dielectric effect of water
The dielectric properties of water are among the strongest in nature
Hydrophobic groups in proteins cause large changes in the dielectric properties of water
These facts make for the strange world in which proteins struggle for survival in an aqueous environment. The course will describe the use of datamining to understand the biophysics of proteins, and we will review basic structural information about water. We will also discuss some changes at the quantum level caused by the large-scale hydrophobic and electronic environment.
Implications for protein folding models will be discussed.
No particular background beyond high-school chemistry and advanced calculus will be assumed. All prerequisites will be provided in the class. We will explore issues in computer science, applied mathematics, physical chemistry and biomedical applications. It is hoped that people from different disciplines will participate.
The course will be based on a forthcoming book to be distributed to the class.
-
GUEST SPEAKER SCHEDULE:
Tuesday, November 3rd:;Tatiana Orlova -; Hydrogen bonds in protein structure
Thursday, November 5th:;;Ariel Fernandez Stigliano -; The dehydron as a catalytic device
Lecturer : Ridgway Scott, University of Chicago
Dates : October 8th, 20th, 22nd / November 3rd, 5th, 10th, 12th, 24th
Time : 12:40PM - 2:10 PM
In a series of eight lectures, this course will explore the digital nature of biology at the molecular scale.
The course will focus on novel interactions in protein/ligand associations, in particular, on the role of the hydrophobic effect in protein/ligand associations.
Protein interactions are discrete in nature even though hydrophobic effects are non-specific in general. There is a useful analogy with the duality between the analog and digital nature of computer chips. We refer to this study as the Digital Biology Project. We pursue basic biophysical issues but we also apply our ideas to biomedical problems, e.g., to contribute to the understanding of antibody binding and to drug design.
The course will primarily utilize data-mining as a tool both to understand basic biophysics and to explain protein-ligand associations. It will explore the connections among the following well known but seemingly contradictory facts:
Proteins are highly specific (and deterministic, or repeatable) in the way that they interact in many of their functions which involve other proteins and other ligands
The hydrophobic effect, which is highly non-specific, is critical in protein-ligand interaction
In the process of explaining this seeming contradiction, we must confront three other facts about biomolecular systems:
Electrical gradients in proteins are among the strongest in nature, but they get modulated by the dielectric effect of water
The dielectric properties of water are among the strongest in nature
Hydrophobic groups in proteins cause large changes in the dielectric properties of water
These facts make for the strange world in which proteins struggle for survival in an aqueous environment. The course will describe the use of datamining to understand the biophysics of proteins, and we will review basic structural information about water. We will also discuss some changes at the quantum level caused by the large-scale hydrophobic and electronic environment.
Implications for protein folding models will be discussed.
No particular background beyond high-school chemistry and advanced calculus will be assumed. All prerequisites will be provided in the class. We will explore issues in computer science, applied mathematics, physical chemistry and biomedical applications. It is hoped that people from different disciplines will participate.
The course will be based on a forthcoming book to be distributed to the class.
