In molecular biology and pharmacology, a small molecule is a low molecular weight (<900 Daltons) organic compound that may help regulate a biological process, with a size on the order of 10−9 m. Most drugs are small molecules.
The upper molecular weight limit for a small molecule is approximately 900 Daltons, which allows for the possibility to rapidly diffuse across cell membranes so that they can reach intracellular sites of action. In addition, this molecular weight cutoff is a necessary but insufficient condition for oral bioavailability. Finally, a lower molecular weight cutoff of 500 Daltons (as part of the «rule of five») has been recommended for small molecule drug development candidates based on the observation that clinical attrition rates are significantly reduced if the molecular weight is kept below this 500 Dalton limit.
Pharmacology usually restricts the term to a molecule that binds to a specific biopolymer—such as protein or nucleic acid—and acts as an effector, altering the activity or function of the biopolymer. Small molecules can have a variety of biological functions, serving as cell signaling molecules, as drugs in medicine, as pesticides in farming, and in many other roles. These compounds can be natural (such as secondary metabolites) or artificial (such as antiviral drugs); they may have a beneficial effect against a disease (such as drugs) or may be detrimental (such as teratogens and carcinogens). Biopolymers such as nucleic acids and proteins, and polysaccharides (such as starch or cellulose) are not small molecules—though their constituent monomers—ribo- or deoxyribonucleotides, amino acids, and monosaccharides, respectively—are often considered small molecules. Very small oligomers are also usually considered small molecules, such as dinucleotides, peptides such as the antioxidant glutathione, and disaccharides such as sucrose.
Small molecules may also be used as research tools to probe biological function as well as leads in the development of new therapeutic agents. Some can inhibit a specific function of a multifunctional protein or disrupt protein—protein interactions.
The first step of determining that morphine may affect the immune system was to establish that the opiate receptors known to be expressed on cells of the central nervous system are also expressed on cells of the immune system. One study successfully showed that dendritic cells, part of the innate immune system, display opiate receptors. Dendritic cells are responsible for producing cytokines, which are the tools for communication in the immune system. This same study showed that dendritic cells chronically treated with morphine during their differentiation produce more interleukin-12 (IL-12), a cytokine responsible for promoting the proliferation, growth, and differentiation of T-cells (another cell of the adaptive immune system) and less interleukin-10 (IL-10), a cytokine responsible for promoting a B-cell immune response (B cells produce antibodies to fight off infection).
The 3D structures of biomolecular targets are obtained from X-ray crystallography and NMR. In parallel, information about the structural dynamics and electronic properties about ligands are obtained from calculations. This has encouraged the rapid development of the structure-based drug design. Current methods for structure-based drug design can be divided roughly into two categories. The first category is about «finding» ligands for a given receptor, which is usually referred as database searching. In this case, a large number of potential ligand molecules are screened to find those fitting the binding pocket of the receptor. This method is usually referred as ligand-based drug design. The key advantage of database searching is that it saves synthetic effort to obtain new lead compounds. Another category of structure-based drug design methods is about «building» ligands, which is usually referred as receptor-based drug design. In this case, ligand molecules are built up within the constraints of the binding pocket by assembling small pieces in a stepwise manner. These pieces can be either individual atoms or molecular fragments. The key advantage of such a method is that novel structures, not contained in any database, can be suggested.
Further studies on the effects of morphine on the immune system have shown that morphine influences the production of neutrophils and other cytokines. Since cytokines are produced as part of the immediate immunological response (inflammation), it has been suggested that they may also influence pain. In this way, cytokines may be a logical target for analgesic development. Recently, one study has used an animal model (hind-paw incision) to observe the effects of morphine administration on the acute immunological response. Following hind-paw incision, pain thresholds and cytokine production were measured. Normally, cytokine production in and around the wounded area increases in order to fight infection and control healing (and, possibly, to control pain), but pre-incisional morphine administration (0.1-10.0 mg/kg) reduced the number of cytokines found around the wound in a dose-dependent manner. The authors suggest that morphine administration in the acute post-injury period may reduce resistance to infection and may impair the healing of the wound.
In contrast to traditional methods of drug discovery, which rely on trial-and-error testing of chemical substances on cultured cells or animals, and matching the apparent effects to treatments, rational drug design begins with a hypothesis that modulation of a specific biological target may have therapeutic value. In order for a biomolecule to be selected as a drug target, two essential pieces of information are required. The first is evidence that modulation of the target will have therapeutic value. This knowledge may come from, for example, disease linkage studies that show an association between mutations in the biological target and certain disease states. The second is that the target is «drugable». This means that it is capable of binding to a small molecule and that its activity can be modulated by the small molecule.
The main pharmacological effects of digoxin are on the heart. Extracardiac effects are responsible for some of the therapeutic and many of the adverse effects (see above). It exerts a mechanical effects as it increases myocardial contractility; however, the duration of the contractile response is just slightly increased. Overall, the heart rate is decreased, while blood pressure is increased resulting in an net increase in stroke volume, leading to increased tissue perfusion. This causes the myocardium to work more efficiently, with optimised haemodynamics and the ventricular function curve is improved.
Computer-aided drug design uses computational chemistry to discover, enhance, or study drugs and related biologically active molecules. The most fundamental goal is to predict whether a given molecule will bind to a target and if so how strongly. Molecular mechanics or molecular dynamics are most often used to predict the conformation of the small molecule and to model conformational changes in the biological target that may occur when the small molecule binds to it. Semi-empirical, ab initio quantum chemistry methods, or density functional theory are often used to provide optimized parameters for the molecular mechanics calculations and also provide an estimate of the electronic properties (electrostatic potential, polarizability, etc.) of the drug candidate that will influence binding affinity.
In pharmacology, the term mechanism of action (MOA) refers to the specific biochemical interaction through which a drug substance produces its pharmacological effect. A mechanism of action usually includes mention of the specific molecular targets to which the drug binds, such as an enzyme or receptor. Receptor sites have specific affinities for drugs based on the chemical structure of the drug, as well as the specific action that occurs there. Drugs that do not bind to receptors produce their corresponding therapeutic effect by simply interacting with chemical or physical properties in the body. Common examples of drugs that utilize this method are antacids and laxatives.
Ideally, the computational method will be able to predict affinity before a compound is synthesized and hence in theory only one compound needs to be synthesized, saving enormous time and cost. The reality is that present computational methods are imperfect and provide, at best, only qualitatively accurate estimates of affinity. In practice it still takes several iterations of design, synthesis, and testing before an optimal drug is discovered. Computational methods have accelerated discovery by reducing the number of iterations required and have often provided novel structures.
For example, the mechanism of action of aspirin involves irreversible inhibition of the enzyme cyclooxygenase, therefore suppressing the production of prostaglandins and thromboxanes, thereby reducing pain and inflammation. However, some drug mechanisms of action are still unknown. For example, phenytoin is used to treat symptoms of epileptic seizures, but the mechanism by which this is achieved is still unknown, despite the fact that the drug has been in use for many years.