Preface from the Authors

Philosophy

Writing a textbook is an enormous task. This is especially true for a biochemistry text, given the field's inherently interdisciplinary nature. Our insight into the biochemical bases for the biological world has exploded over time. Somehow that has to be presented in and integrated into a textbook, which attempts to explain life from a structure/function perspective.

Any book by default reflects the strengths, weaknesses, interests and biases of the writers. We have tried to select and explain topics that are perhaps most difficult for students to understand, but even those choices reflect in part the difficulties that authors have had to overcome throughout the years in their own understanding of the field. At the same time, we see our students struggling with the same content and concepts that we did as students. There is broad consensus among biochemists about which concepts are most difficult. Loertscher et al. have described these as threshold concepts and most are fundamental concepts in chemistry. Examples include Gibbs free energy, the difference between rapid equilibrium and the steady state, the thermodynamics of macromolecular structure formation, the physical basis of interactions, and in addition biomolecular visualization literacy.

At the same time, the biological complexities of the emergent properties of the cell, organs and organisms from a myriad of interacting molecules in space and time is truly humbling. Such complexity must increasingly be probed by mathematical models and the use of machine learning and artificial intelligence. Hence we have not shied away from the inclusion of mathematics and modeling of complex interconnected pathways. This is the future of biochemistry. Some material might be presented in too little depth for some. Again this reflects our backgrounds and experiences. Likewise, some material might be presented in too much depth for faculty adopters and students. We don’t view this as a problem since users can pick and choose the content they wish. We chose to write a text that extends students and is challenging.

No one can know all of biology and all of chemistry (an obvious statement). Each of us is predominately stronger in one field than the other. Think of yourself looking at the field of biochemistry with glasses containing a "biology-centric" lense and a "chemistry-centric" lens. We all have a dominant eye, which sees the world more clearly. Which lens is most comfortable to you as you study biochemistry?

If you have ever tried to see the world through glasses containing just one lens, the world looks distorted and incomplete. The same with biochemistry. It will become clearer to you if you correct your vision to include both a biological and chemistry lens. Adding even more lenses, including mathematics, computer sciences and physics, would offer a much better and clearer understanding (think of the compound lens of the fly)! In addition, most biochemistry texts might be considered protein centric and give less attention to other classes of molecules such as lipids and nucleic acids. Coverage of the latter topics might seem underrepresented in this book in the eyes of a lipid or nucleic acid chemist.

Fundamentals of Biochemistry is a classical textbook given its coverage and depth. It follows the arrangements and sequence of typical commercial textbooks to allow easier adoption by faculty and for ease of use by students. We have tried to not focus too much on human biochemistry, which is most likely emphasized in many biochemistry courses. Yet in reality, students who take biochemistry are often in a pre-medical track. We hope to populate chapters with problems based on the research literature to enable a more problem-solving approach.

We have deliberately chosen to incorporate graphs and some text from published materials that can be shared through Creative Common licenses. It would not have been possible to create a text without using such materials, as we did not have a publishing company supporting our work. We have done our best to attribute materials not directly made by us to the original authors. We apologize if we neglected to give attribution to those who sources we have used. The complexities of writing a book over many years in what free time we could devote to the project increases the likelihood of such omissions. In reality, we view ourselves as authors (of original materials) and compilers (of materials licensed through Creative Commons) of this textbook.

This book, as with any first edition text, will contain many mistakes. We hope these most are in the form of typos and grammatical errors. Given our backgrounds and the limitations of our own knowledge, there will also likely be conceptual mistakes. We ask for your forgiveness for these and ask you to help correct them.

Key Features

This text covers a full year sequence of biochemistry. The book could serve traditional and ACS-certified majors, traditional and ASBMB-certified majors, as well as students taking a one-semester course. Characteristic of all LibreText books, Fundamentals of Biochemistry will be open to everyone via the internet and completely free, as all should have access to knowledge. It is comprehensive and topical, as new materials are easily added. The text is divided into five"books" and given the number of image and interactive models, it is best used online. Each chapter and section can be printed as a PDF file if needed. The LibreText collections of books have served 223 million students and saved them $31 million, an undue burden for our students and society.

An online text has some advantages in addition to cost over hardback textbooks. Chief among these are embedded interactivity and ease of updating. Here are some of the differentiating features of Fundamentals of Biochemistry:

• Interactive 2D mathematical graphs with sliders that allow users to change mathematical constants with immediate update of graphs;
• Interactive molecular models using iCn3D (https://www.ncbi.nlm.nih.gov/Structure/icn3d/full.html) that allows students to view and interact with rendered structures;
• Embedded VCell (https://vcell.org/) models that allow users to display time course graphs for simple to complex reactions;
• Animations to accompany some of the VCell progress curve graphs;
• Chapter sections on metabolic control analyses;
• Constant addition of new materials such as RNA glycans, SARS-CoV-2 structures, etc.
• Literature-based guided assessments (described below)

Volume 4 contains two chapter not found in traditional biochemistry text books.  This include chapter on the Abiotic Origins of Life and Biochemistry and Climate Change.  It also contains an extensive chapter on Biosignaling - Capstone for Volume I

Interactive mathematical graphs

These offer clear advantages over static graphs (which we also choose to incorporate). Key constants in the mathematical equation can be changed using sliders with updated graphs shown in real time. For example, users can change rate constants, dissociation constants, and other parameter in way that change the apparent form of the graph. This will make the constants less abstract and give users insight into their fundamental meaning. An example is the graph for the concentration of the macromolecule:ligand complex (ML) vs free ligand (L) shown below. L₀ and M₀ are the total ligand and macromolecule concentrations, respectively.

If \(L_0 \ll M_0\), then the equations simplifies to:

\[ML = \dfrac{(M_0)(L_0)}{K_D + L} \nonumber \]

This is a graph for a hyperbola. If \(K_D \gg L\) (equivalent to L << K_D ) then the equation becomes

\begin{equation}
[\mathrm{ML}]=\left(\frac{\mathrm{M}_{0}}{\mathrm{~K}_{\mathrm{D}}}\right) \mathrm{L}
\end{equation}

Under these conditions, ML is a linear function of L. Now change the slider for K_D in the interactive graph and see how the initial hyperbola changes into an apparently linear function when L << K_D.

Now if a reader who had fully explored this interactive graph conducted an actual binding analysis in the lab and got a linear plot of ML vs L, they might immediately recognize that they need to increase the ligand concentration to cover the full binding curve.

Use of iCn3D

iCn3D interactive molecular models are found in most chapters and sections. These models have been rendered to illustrate key points related to structure/function and are not presented just as attractive images. Users must interact with each model to enhance their understanding of the structure and function. Users can either click on the image and see an interactive popup model of the structure or use a link to go to a larger model in a separate window. Mouse instructions are given on each page of the popup window.

An example of an interactive iCn3D model presented in the book is the human nucleosome (3afa). Each iCn3D structure includes a Protein Data Bank (PDB) 4-digit alphanumeric code. We choose not to directly include iCn3D interactive models directly on the page. The size of the structure and the script necessary to produce the desired rendering make the load time for the page too long (especially when more than one model is present on a given page. Instead, users can click on the image and a popup of the fully rendered model will appear. The user can modify the rendered model by clicking the top menu bar icon (=) and selecting from the dropdown menu. This requires some knowledge of the iCn3D GUI. Alternatively, the user can click the link in the legend underneath the image to get an expanded new window of the model directly through the full iCn3D user webpage.

Explore the model of the nucleosome below. This structure shows how doubled-stranded DNA is packed around an octamer of pairs of 4 basic proteins called histones that are found in the eukaryotic nucleus. One member of each pair of histones is shown in cartoon rendering, while the other member of the pair is shown in the same color but in spacefill rendering. Each strand of DNA is shown in a different shade of gray.

Figure \(\PageIndex{10}\): Human nucleosome (3afa). (Copyright; author via source).
Click the image for a popup or use this external link: https://structure.ncbi.nlm.nih.gov/i...B2SwQHYDLj4BJ6

Simply viewing the image will not lead to enhanced insight into the structure. Users should hover over key groups and rotate the model to help identify interactions. Labeled and interactive computer models offer key advantages over static 2D images. Using additional menu items to further interrogate the structure over and above the rendered image offered will lead to increased insight.

A note on images: Many of the static structures of biomolecules are made with PyMOL. The rest are made with iCn3D. Efforts have been made to use appropriate colors for those who are color-blind.

Embedded Virtual Cell (VCell) models

VCell (Virtual Cell) is a platform for the mathematical modeling of cell biological systems. Our use of it is to display product vs time progress curves for simple to more complicated reactions. It can do so much more than that, however. For example, it can be used to model the concentrations of all metabolites in full metabolic and signal transduction pathways. We introduce it in this book to allow users to alter the rate, kinetic, and dissociation constants, etc., and see the effects on the output of simple to more complex reactions. Given the complexity of the biological world and its interactions, mathematical modeling of biological processes is essential to fully understanding it. Most readers do not have the mathematical and computer skills to create and run models on their own. Vcell does that for you. We will explain in general the mathematical equations used in Vcell to model many reactions throughout this book. We hope that interested readers will become more familiar with Vcell and explore it for their own uses in courses and eventually in this own research.

Modeling is very important especially when our intuitions are insufficient to account for observed results. Take for example the reactions of three enzymes involved in cell signaling in the mitogen activated protein kinase (MAPK) cascade system as illustrated in the scheme below. (We will explore this in more detail later in the text).

A protein kinase is an enzyme that covalently transfers a terminal phosphate (P) from ATP to a protein. Line 1 shows one protein kinase, MAPKKK, that is phosphorylated (by another kinase not shown) to become MAPKKK-P. MAPKKK-Pin turn is an active protein kinase that doubly phosphorylates MAPKK (line 2) to form MAPKK-PP. MAPKK-PP is in turn yet another downstream kinase, which doubly phosphorylates MAPK to form MAPK-PP. These phosphorylation reactions are shown in green in the reaction diagram. If you plot the concentration of MAPKKK (the starting enzyme with a cellular concentration set to 100 nM and MAPK-PP (initial concentration of MAPK is 300 nM) vs time for a specific set of conditions, you get the very predictable graph shown in the left panel below. However, if you allow the final product of the cascade (MAPK-PP), to inhibit the very first reaction in the cascade (Rx 1 forward, red blunt arrow), you get the remarkable oscillatory graph shown in the right panel of the figure.

There is simply no way to predict the observed oscillatory behavior for the system from simple intuition as was possible for the reaction scheme without feedback inhibition. Vcell allows these types of calculations, which greatly informs our understanding of biological interactions in complicated biological pathways. (The Virtual Cell was developed with funding from the National Institute of General Medical Sciences (NIGMS) as a Biomedical Technology Research Resource at the Center for Cell Analysis and Modeling (CCAM).

Animations

Science is difficult for most students. Let's pick chemistry as an example and consider one of its simplest reactions, that of hydrogen chloride and water, to form the hydronium ion and chloride. We know such a mixture as hydrochloric acid. Chemists use every resource available to them to understand and explain reactions. These encompass the macroscopic, nanoscopic, mathematical, and symbolic realms, as shown in the figure below.

Some need words to best understand a difficult concept. Others need images. Most need multiple modalities. For that reason, we have incorporated animations of relevant physical and chemical reactions for which we also have embedded Vcell models. These animations were created by Hui Liu (Anne) and Shraddha Nayak from Janet Iwasa's lab. In addition, we have incorporated metabolic flux animations created by Nayak for key metabolic pathways.

We hope that all the different learning modalities we incorporate into Fundamentals of Biochemistry will help users comprehend this amazing yet difficult field.

Literature-based Guided Assessments (LGAs)

Assessment questions are typically given at the end of chapters in traditional biochemistry texts.  As they are targeted to specific chapters, they are more likely to address ideas expressed in a chapter and less likely to be summative across chapters. In addition, although specific questions may use data and findings from the research literature, the questions are less likely to intentionally address learning goals tied to students’ abilities to read and understand research papers, an arguably difficult task.  Finally, the question when tied to specific chapters might not be relevant to larger issues of the day, such as the development of new antivirals targeting pandemic viruses.

To address these issues, we have developed a new approach for assessment questions housed in this book.  We have created LGAs with data, graphs, and images derived from 1 or more research papers (with the correct Creative Commons permissions).  The LGAs also serve as a way for students to read and explore the research literature in a guided way.  We have written traditional LGAs and those based on the world's greatest challenges (and problems). These include climate change, trauma, information integrity, and addiction.  More will be added in the future.

Much of the content covered in biochemistry classes is in service to the premedical curriculum, which focuses almost exclusively on human health as opposed to the emerging notion of “one health".  The LGAs linked to global challenges allow us to cover in an organized way the  “underserved” areas (based on traditional biochemistry courses) in biochemistry. 

Acknowledgments

We greatly appreciate the help of Leslie Loew, Ion Moreau, Jonathan Karr, Bilal Shaikh, and Henry Agnew in integrating Vcell into Fundamentals of Biochemistry. In addition we thank Bartholmew Jardine and Herbert Sauro for the development and use of the Minisidewider software for interactive mathematical simulations in the book.  Finally, we greatly appreciate the help of Hui Liu (Anne), Shraddha Nayak, and Janet Iwasa in creating the animations that accompany the VCell and other models.

References

2. VCell :

• Schaff, J., C. C. Fink, B. Slepchenko, J. H. Carson, and L. M. Loew. 1997. A general computational framework for modeling cellular structure and function. Biophysical journal 73:1135-1146. PMC1181013
• Cowan, A. E., Moraru, II, J. C. Schaff, B. M. Slepchenko, and L. M. Loew. 2012. Spatial modeling of cell signaling networks. Methods Cell Biol 110:195-221. PMC3288182

3. https://upload.wikimedia.org/wikiped...nannotated.svg

4. iCn3D: Wang J, Youkharibache P, Zhang D, Lanczycki CJ, Geer RC, Madej T, Phan L, Ward M, Lu S, Marchler GH, Wang Y, Bryant SH, Geer LY, Marchler-Bauer A. iCn3D, a Web-based 3D Viewer for Sharing 1D/2D/3D Representations of Biomolecular Structures. Bioinformatics. 2020 Jan 1;36(1):131-135. (Epub 2019 June 20.) doi: 10.1093/bioinformatics/btz502. [PubMed PMID: 31218344]

5. The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC.