Computational Structure-Based Drug Discovery (CSBDD) involves drug design based on the three-dimensional structure of the biomolecular target, in most cases a protein. While the Quantum Chemical (better known as Quantum Mechanics or QM) methods discussed in section 2.2 are useful for studying the properties of isolated drug-like molecules and for limited studies on simple models of a protein’s binding site, it is usually desirable to also perform simulations on the whole protein in the presence of water when applying CSBDD.
Although some pioneering efforts have been made in applying semi-empirical methods to this end, doing so puts severe constraints on the simulation timescale, and semi-empirical energy functions have weaknesses, such as poor treatment of dispersion interactions. Therefore, the method of choice for protein simulations remains Molecular Mechanics (MM) force fields, which approximate the quantum mechanical energy surface with a classical mechanical model, thereby decreasing the computational cost of simulations is large system by orders of magnitude. Furthermore, MM potential energy functions allow for a relatively accurate representation of dispersion interactions, which current QM methods only start recovering at the MP2 and higher levels of theory.
A computer that uses molecules to solve problems uses 10,000 times less energy than a conventional computer. If made larger, these bio-computers could efficiently solve complex logistics problems that normally require a lot of time and energy. This relationship broke around 15 years ago, meaning that computers that perform large computations aren’t as energy-efficient. This subsection will focus mainly on the class I the sum of bonded and non-bonded energy terms, as given by equation 1. This potential energy function, whose terms are described, covers the vast majority of force fields used in CSBDD.
The subject of quantum computing brings together ideas from classical information theory, computer science, and quantum physics. This review aims to summarize not just quantum computing, but the whole subject of quantum information theory. Information can be identified as the most general thing which must propagate from a cause to an effect. It therefore has a fundamentally important role in the science of physics. However, the mathematical treatment of information, especially information processing, is quite recent, dating from the mid-20th century. This has meant that the full significance of information as a basic concept in physics is only now being discovered. This is especially true in quantum mechanics. The theory of quantum information and computing puts this significance on a firm footing, and has led to some profound and exciting new insights into the natural world. Among these are the use of quantum states to permit the secure transmission of classical information (quantum cryptography), the use of quantum entanglement to permit reliable transmission of quantum states (teleportation), the possibility of preserving quantum coherence in the presence of irreversible noise processes (quantum error correction), and the use of controlled quantum evolution for efficient computation (quantum computation). The common theme of all these insights is the use of quantum entanglement as a computational resource.
It turns out that information theory and quantum mechanics fit together very well. In order to explain their relationship, this review begins with an introduction to classical information theory and computer science, including Shannon's theorem, error correcting codes, Turing machines and computational complexity. The principles of quantum mechanics are then outlined, and the Einstein experiment described. The EPR-Bell correlations, and quantum entanglement in general, form the essential new ingredient which distinguishes quantum from classical information theory and, arguably, quantum from classical physics.
Basic quantum information ideas are next outlined, including data compression, quantum gates, the 'no cloning' property and teleportation. Quantum cryptography is briefly sketched. The universal quantum computer (QC) is described, based on the Church-Turing principle and a network model of computation. Algorithms for such a computer are discussed, especially those for finding the period of a function, and searching a random list. Such algorithms prove that a QC of sufficiently precise construction is not only fundamentally different from any computer which can only manipulate classical information, but can compute a small class of functions with greater efficiency. This implies that some important computational tasks are impossible for any device apart from a QC.
To build a universal QC is well beyond the abilities of current technology. However, the principles of quantum information physics can be tested on smaller devices. The current experimental situation is reviewed, with emphasis on the linear ion trap, high-Q optical cavities, and nuclear magnetic resonance methods. These allow coherent control in a Hilbert space of eight dimensions and should be extendable up to a thousand or more dimensions. Among other things, these systems will allow the feasibility of quantum computing to be assessed. Such experiments are so difficult that it seemed likely until recently that a practically useful QC was actually ruled out by considerations of experimental imprecision and the unavoidable coupling between any system and its environment. However, a further fundamental part of quantum information physics provides a solution to this impasse. This is quantum error correction.
An introduction to quantum error correction is provided. The evolution of the QC is restricted to a carefully chosen subspace of its Hilbert space. Errors are almost certain to cause a departure from this subspace. Quantum error correction provides a means to detect and undo such departures without upsetting the quantum computation. This achieves the apparently impossible, since the computation preserves quantum coherence even though during its course in the computer will have relaxed spontaneously many times.
The review concludes with an outline of the main features of quantum information physics and avenues for future research.
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