Preface

The structure and function of biological macromolecules and their ligands are crucial for understanding physiology, pathological physiology, molecular pharmacology, and drug design. The fact that molecules consist of atoms and the theory of chemical bonding developed slowly. Now, it is clear that understanding the structure and function of biological macromolecules requires experimental and computational approaches that are tightly interconnected. Currently, no high-resolution protein and nucleic acid structures can be obtained without refinement that, by definition, involves biomolecular simulation.

A Greek philosopher, Democritus (~460-370 B.C.E.), first gave the idea that all matter consists of atoms, the smallest particles that cannot be subdivided into smaller substances. In the 1800s, the theories of molecular structures were modeled using equal and unequal spheres. The first physical molecular model by August Wilhelm von Hofmann in the year 1865 showed that the size of the carbon atom was different from that of hydrogen or chlorine atoms using methane, ethane, and methyl chloride as models. After the introduction of stereochemistry, Jacobus Henricus van’t Hoff built the three-dimensional model of tetrahedral molecules in the year 1874. Some 20 years later, electron was discovered by Joseph John Thomson, who was later awarded the Nobel Prize in Physics in 1906 “for his theoretical and experimental investigations on the conduction of electricity by gases”, which explain the various sizes of different atoms. Later, physicist Ernest Rutherford proved his discovery of the existence of protons and published an article titled “Collision of α particles with light atoms. IV. An anomalous effect in nitrogen” in Philosophical Magazine Series 6, 37 (1919) 581-587. His work earned him the Nobel Prize in Chemistry in 1908 “for his investigations of the disintegration of the elements and the chemistry of radioactive substances”. The Nobel Prize in Physics (1933) was awarded to Erwin Schrödinger and Paul Adrien Maurice Dirac “for the discovery of new productive forms of atomic theory”. The key results from Schrödinger and Dirac’s study have made the landmark in modern-day’s quantum mechanics calculation. Berni J. Alder and Tom E. Wainwright performed the first molecular dynamics (MD) simulation of simple gases. The MD simulation of the first protein was reported in 1977.

When a molecular system is too large to represent explicitly all electrons in the calculation, one must proceed with molecular mechanics, and on top of that, thermal averaging by molecular dynamics simulation is typically necessary. Molecular mechanics uses classical mechanics to calculate a system of molecules and apply the algebraic expression for the total energy of a system without computing the total electron density. It is thus feasible and faster with the assumption that the Born-Oppenheimer approximation is valid. This has led to the simulation of a 58 amino acids bovine pancreatic trypsin inhibitor that showed this protein has an internal motion of a fluid-like nature. One of the important conclusions has been made- the dynamic fluctuation of the protein needs to be included and applied in the biological processes modeling. The fundamentals that enable the protein simulations were recognized by the Nobel Prize in Chemistry (2013), which was awarded to Martin Karplus, Michael Levitt and Arieh Warshel “for the development of multiscale models for complex chemical systems”. Earlier, in relation to simulation, the Nobel Prize in Chemistry (1998) was awarded to Walter Kohn and John A. Pople “for his development of the density-functional theory” and “for his development of computational methods in quantum chemistry”, respectively. The revolution of computational simulations to mirror real life has thus become crucial for the consequences of advancements in chemistry nowadays.

All living things are made of cells with the basic chemical elements i.e., carbon, hydrogen and nitrogen, that account for most of the mass in an organism. Hence, the study of chemical processes within the cell elucidates the molecular basis of biological activities i.e., molecular interactions/recognition, mechanisms, modification and synthesis. Biological macromolecules that are made up of monomers of amino acids, lipids, nucleotides and sugars are involved in such biological activities to carry out life processes. The conformation of these macromolecules determines their biological activities especially proteins that perform a vast array of the organism’s functions. The discovery of X-rays in the year 1895 by Wilhelm Conrad Röntgen that earned him the Nobel Prize in Physics 1901 provided crystallographers with a powerful tool to “see” atoms from crystals. The three-dimensional structure of the protein has been extensively studied. Max Ferdinand Perutz and John Cowdery Kendrew were awarded the Nobel Prize for Chemistry in 1962 “for their studies on the structures of globular proteins”. In the same year, the Nobel Prize in Physiology or Medicine was also awarded to Francis Harry Compton Crick, James Dewey Watson and Maurice Hugh Frederick Wilkins “for their discoveries concerning the molecular structure of nucleic acids and its significance for information transfer in living material”. Their discovery of the double helix molecular structure of nucleic acids has since been used to postulate the base pairing of nucleic acids. Dorothy Crowfoot Hodgkin received the Nobel Prize in Chemistry in 1964 “for her determinations by X-ray techniques of the structures of important biochemical substances”. Their works have since initiated the development of techniques to improve the structure solving of biological macromolecules. The experimentally solved biological molecules have thus been deposited in the Protein Data Bank (PDB), which was established in the year 1971.

Considering the challenges in the crystallization process, nuclear magnetic resonance (NMR) spectroscopy of biological molecules in solution was developed, and Kurt Wüthrich was awarded the Nobel Prize in Chemistry in 2002 “for his development of nuclear magnetic resonance spectroscopy for determining the three-dimensional structure of biological macromolecules in solution”. With technology progression, large biological complexes that cannot be captured by X-ray crystallography are now able to be imaged using cryo-electron microscopy (cryo-EM) technology pioneered by Jacques Dubochet, Joachim Frank and Richard Henderson, who were awarded the Nobel Prize in Chemistry in 2017 “for developing cryo-electron microscopy for the high-resolution structure determination of biomolecules in solution”. As of May 2023, all the above-mentioned experimentally solved biological molecules have accumulated to more than 200,000 structures in RCSB PDB- the worldwide three-dimensional structure repository database.

Together with the biological processes modeling, these biological structures' determination has laid the groundwork for computation simulation on the biological system to close the sequence-structure gap whereby the behavior of biological macromolecules can be more accurately predicted. The combination of wet laboratory experiments and dry laboratory calculations enables the structure-property relationship to be hypothesized, thus revolutionizing the design of new medicines and novel medical interventions. Years back, biomedical research was an experimental investigation that could only be performed by in vitro and in vivo means. Nowadays, breakthroughs have been made in the processing, analysis and interpretation of biomedical data when biology is combined with the disciplines of chemistry, physics, computer science, information technology, mathematics and statistics. Converting biomedical data into meaningful information involves scripting and executing programs. These programs were developed from theoretical calculation together with artificial intelligence, thus enabling the access and management of various biological information, including raw sequence data, structures and images. The algorithm's development has also allowed the relationship measurement amongst biological information in order to increase the understanding of biological processes.

The life activities of an individual start from the transcription of DNA into RNA to protein translation and expression, which leads toward complex biological pathways and networks. Hence, any alteration in the processes can lead to various medical diseases and affect the life of the individual. Additional external factors, such as pathogens, further worsen the conditions due to multifactorial diseases, thus challenging the management and treatment of the diseases. Biomedical research driven by computational approaches has demonstrated its practical value as analysis without bias can be structured to narrow down the knowledge gaps. As the year progresses, the techniques also progress. The advances in the future will dwarf those of the past. The advances in biomolecular structure determination and simulation techniques have significantly improved the quality of life in the past century and will continue to make sense in the process of life in the coming centuries.

This book first narrates the computational tools that were generally used in biomedical research in sequence and structure studies. The computational tools in biological cellular activity and system biology are also summarized. The overall picture of molecular modeling in related biomedical research with examples has shown increased practicality in studying a wide variety of problems.

In the following chapter, the big data interpretation is included. The genomic data analysis on expression data, circular RNAs, RNA interference, and microglial brain-derived neurotrophic factor are explained in this chapter. A list of publicly available databases for genomic data is also listed. Several diseases are used as examples in data analysis, specifically RNAs that aid the targeted therapies.

The development of computer-based algorithms and protocols has accelerated the pace of closing the gap in sequence-structure knowledge of biomolecules. Thus, the theory of developing various algorithms for solving the 3D structure of biomolecules is also described in this book. Besides, the description of tertiary structure prediction protocol, protein structure refinement via molecular dynamics simulation, and quality assessment of predicted structure is detailed. Other than that, the algorithms for DNA sequence computing are compared. The algorithm for docking and molecular dynamics simulations are also included in this book.

Proteins, ranging from antibodies, enzymes, and hormones to contractile/storage/ storage/transport proteins, are essential parts of an organism and are involved in practically every process within the cells. The chapter on the application of protein modeling in this book overviews protein structure determination and protein modeling. The application of protein modeling is also reviewed to highlight the importance of structural elucidation in the structure-function relationship of protein in the biomedical field.

Besides, proteins are not rigid molecules and their conformational flexibility has various degrees. The conformation flexibility, especially in the binding site, is vital for the catalysis activities and molecular recognition with their binders. This book also includes a chapter on the dynamics of biomoleculars, hence further providing the applications of molecular recognition in drug development process.

Atomistic biomolecular simulation can be very helpful in studying the biomedical system when coupled to its function. Other than biomedical systems, this approach is increasingly being used in various fields. The molecular modeling and simulation have altered the research tactic by choosing the experiment with the highest probability of success rate prior to the actual experiment. Although molecular modeling complements experiments and can provide detailed time-based information at the molecular level, all techniques have limitations. These limitations/problems need to be addressed clearly prior to simulation. The computing of total entropies and entropy differences i.e., protein-inhibitor binding or protein folding, is yet to be solved. Insufficient experimental data is also one of the limitations through which the simulation predictions are validated. The development of a force field is usually limited to a class or type of molecules or environment; the choice of force field in the simulation of globular protein in solution is different than that of membrane protein in lipid bilayer simulation. In addition, biological events range from femto- to mili-seconds and seconds for the atomic fluctuation and side chain motion to the protein folding/unfolding. The search and sampling of a system is, therefore, another limitation in the simulation of biological systems. The challenges of biological simulation are the balance between force field, sampling and computational power and the ability to model the phenomena of interest that is dependent on the type of process.

This book not only targets researchers in industry and academics but also serves as a guide for graduates and undergraduates who wish to apply computational approaches in their biomedical research. This book covers the basic to detailed description and application of computational modeling and simulation in biomedical research and thus may be useful as reference material for learning important research topics.

I would like to thank Professor Dr. Janez Mavri from the Laboratory of Computational Biochemistry and Drug Design, National Institute of Chemistry, Ljubljana, Slovenia, for stimulating the discussion of this preface.