Bulimia nervosa

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Bulimia_nervosa 

 

Bulimia nervosa
Other names	Bulimia
Loss of enamel (acid erosion) from the inside of the upper front teeth as a result of bulimia
Specialty	Psychiatry, clinical psychology
Symptoms	Eating a large amount of food in a short amount of time followed by vomiting or the use of laxatives, often normal weight
Complications	Breakdown of the teeth, depression, anxiety, substance use disorders, suicide
Causes	Genetic and environmental factors
Diagnostic method	Based on person's medical history
Differential diagnosis	Anorexia, binge eating disorder, Kleine-Levin syndrome, borderline personality disorder
Treatment	Cognitive behavioral therapy
Medication	Selective serotonin reuptake inhibitors, tricyclic antidepressant
Prognosis	Half recover over 10 years with treatment
Frequency	3.6 million (2015)

Bulimia nervosa, also known as simply bulimia, is an eating disorder characterized by binge eating followed by purging; and excessive concern with body shape and weight. The aim of this activity is to expel the body of calories eaten from the binging phase of the process. Binge eating refers to eating a large amount of food in a short amount of time. Purging refers to the attempts to get rid of the food consumed. This may be done by vomiting or taking laxatives. Other efforts to lose weight may include the use of diuretics, stimulants, water fasting, or excessive exercise. Most people with bulimia are at a normal weight. The forcing of vomiting may result in thickened skin on the knuckles, breakdown of the teeth and effects on metabolic rate and caloric intake which cause thyroid dysfunction. Bulimia is frequently associated with other mental disorders such as depression, anxiety, bipolar disorder and problems with drugs or alcohol. There is also a higher risk of suicide and self-harm. Clinical studies show a relationship between bulimia and vulnerable narcissism as caused by childhood 'parental invalidation' leading to a later need for social validation.

Bulimia is more common among those who have a close relative with the condition. The percentage risk that is estimated to be due to genetics is between 30% and 80%. Other risk factors for the disease include psychological stress, cultural pressure to attain a certain body type, poor self-esteem, and obesity. Living in a culture that promotes dieting and having parents that worry about weight are also risks. Diagnosis is based on a person's medical history; however, this is difficult, as people are usually secretive about their binge eating and purging habits. Further, the diagnosis of anorexia nervosa takes precedence over that of bulimia. Other similar disorders include binge eating disorder, Kleine-Levin syndrome, and borderline personality disorder.

Cognitive behavioral therapy is the primary treatment for bulimia. Antidepressants of the selective serotonin reuptake inhibitor (SSRI) or tricyclic antidepressant classes may have a modest benefit. While outcomes with bulimia are typically better than in those with anorexia, the risk of death among those affected is higher than that of the general population. At 10 years after receiving treatment about 50% of people are fully recovered.

Globally, bulimia was estimated to affect 3.6 million people in 2015. About 1% of young women have bulimia at a given point in time and about 2% to 3% of women have the condition at some point in their lives. The condition is less common in the developing world. Bulimia is about nine times more likely to occur in women than men. Among women, rates are highest in young adults. Bulimia was named and first described by the British psychiatrist Gerald Russell in 1979.

Signs and symptoms

How bulimia affects the body

 

The erosion on the lower teeth was caused by bulimia. For comparison, the upper teeth were restored with porcelain veneers.

Bulimia typically involves rapid and out-of-control eating, which may stop when the person is interrupted by another person or the stomach hurts from over-extension, followed by self-induced vomiting or other forms of purging. This cycle may be repeated several times a week or, in more serious cases, several times a day and may directly cause:

• Chronic gastric reflux after eating, secondary to vomiting
• Dehydration and hypokalemia due to renal potassium loss in the presence of alkalosis and frequent vomiting
• Electrolyte imbalance, which can lead to abnormal heart rhythms, cardiac arrest, and even death
• Esophagitis, or inflammation of the esophagus
• Mallory-Weiss tears
• Boerhaave syndrome, a rupture in the esophageal wall due to vomiting
• Oral trauma, in which repetitive insertion of fingers or other objects causes lacerations to the lining of the mouth or throat
• Russell's sign: calluses on knuckles and back of hands due to repeated trauma from incisors
• Perimolysis, or severe dental erosion of tooth enamel
• Swollen salivary glands (for example, in the neck, under the jaw line)
• Gastroparesis, or delayed gastric emptying
• Constipation or diarrhea
• Tachycardia or palpitations
• Hypotension
• Peptic ulcers
• Infertility
• Constant weight fluctuations are common
• Elevated blood sugar, cholesterol, and amylase levels may occur
• Hypoglycemia may occur after vomiting

These are some of the many signs that may indicate whether someone has bulimia nervosa:

• A fixation on the number of calories consumed
• A fixation on and extreme consciousness of one's weight
• Low self-esteem and/or self-harming
• Suicidal tendencies
• An irregular menstrual cycle in women
• Regular trips to the bathroom, especially soon after eating
• Depression, anxiety disorders and sleep disorders
• Frequent occurrences involving consumption of abnormally large portions of food
• The use of laxatives, diuretics, and diet pills
• Compulsive or excessive exercise
• Unhealthy/dry skin, hair, nails, and lips
• Fatigue, or exhaustion

As with many psychiatric illnesses, delusions can occur, in conjunction with other signs and symptoms, leaving the person with a false belief that is not ordinarily accepted by others.

People with bulimia nervosa may also exercise to a point that excludes other activities.

Interoceptive

People with bulimia exhibit several interoceptive deficits, in which one experiences impairment in recognizing and discriminating between internal sensations, feelings, and emotions. People with bulimia may also react negatively to somatic and affective states. In relation to interoceptive sensitivity, hyposensitive individuals may not detect feelings of fullness in a normal and timely fashion, and therefore are prone to eating more calories.

Examining from a neural basis also connects elements of interoception and emotion; notable overlaps occur in the medial prefrontal cortex, anterior and posterior cingulate, and anterior insula cortices, which are linked to both interoception and emotional eating.

Related disorders

People with bulimia are more likely than people without bulimia to have an affective disorder, such as depression or general anxiety disorder. One study found 70% had depression at some time in their lives (as opposed to 26% for adult females in the general population), rising to 88% for all affective disorders combined. Another study by the Royal Children's Hospital in Melbourne on a cohort of 2,000 adolescents similarly found that those meeting at least two of the DSM-IV criteria for bulimia nervosa or anorexia nervosa had a sixfold increase in risk of anxiety and a doubled risk for substance dependency. Some with anorexia nervosa exhibit episodes of bulimic tendencies through purging (either through self-induced vomiting or laxatives) as a way to quickly remove food in their system. There may be an increased risk for diabetes mellitus type 2. Bulimia also has negative effects on a person's teeth due to the acid passed through the mouth from frequent vomiting causing acid erosion, mainly on the posterior dental surface.

Research has shown that there is a relationship between bulimia and narcissism. According to a study by the Australian National University, eating disorders are more susceptible among vulnerable narcissists. This can be caused by a childhood in which inner feelings and thoughts were minimized by parents, leading to "a high focus on receiving validation from others to maintain a positive sense of self".

A study by the Psychopharmacology Research Program of the University of Cincinnati College of Medicine "leaves little doubt that bipolar and eating disorders--particularly bulimia nervosa and bipolar II disorder--are related." The research shows that most clinical studies indicate that patients with bipolar disorder have higher rates of eating disorders, and vice versa. There is overlap in phenomenology, course, comorbidity, family history, and pharmacologic treatment response of these disorders. This is especially true of "eating dysregulation, mood dysregulation, impulsivity and compulsivity, craving for activity and/or exercise".

Studies have shown a relationship between bulimia's effect on metabolic rate and caloric intake with thyroid dysfunction.

Causes

Biological

As with anorexia nervosa, there is evidence of genetic predispositions contributing to the onset of this eating disorder. Abnormal levels of many hormones, notably serotonin, have been shown to be responsible for some disordered eating behaviors. Brain-derived neurotrophic factor (BDNF) is under investigation as a possible mechanism.

There is evidence that sex hormones may influence appetite and eating in women and the onset of bulimia nervosa. Studies have shown that women with hyperandrogenism and polycystic ovary syndrome have a dysregulation of appetite, along with carbohydrates and fats. This dysregulation of appetite is also seen in women with bulimia nervosa. In addition, gene knockout studies in mice have shown that mice that have the gene encoding estrogen receptors have decreased fertility due to ovarian dysfunction and dysregulation of androgen receptors. In humans, there is evidence that there is an association between polymorphisms in the ERβ (estrogen receptor β) and bulimia, suggesting there is a correlation between sex hormones and bulimia nervosa.

Bulimia has been compared to drug addiction, though the empirical support for this characterization is limited. However, people with bulimia nervosa may share dopamine D2 receptor-related vulnerabilities with those with substance use disorders.

Dieting, a common behaviour in bulimics, is associated with lower plasma tryptophan levels. Decreased tryptophan levels in the brain, and thus the synthesis of serotonin, such as via acute tryptophan depletion, increases bulimic urges in currently and formerly bulimic individuals within hours.

Abnormal blood levels of peptides important for the regulation of appetite and energy balance are observed in individuals with bulimia nervosa, but it remains unknown if this is a state or trait.

In recent years, evolutionary psychiatry as an emerging scientific discipline has been studying mental disorders from an evolutionary perspective. If eating disorders, Bulimia nervosa in particular, have evolutionary functions or if they are new modern "lifestyle" problems is still debated.

Social

Media portrayals of an 'ideal' body shape are widely considered to be a contributing factor to bulimia. In a 1991 study by Weltzin, Hsu, Pollicle, and Kaye, it was stated that 19% of bulimics undereat, 37% of bulimics eat an average or normal amount of food, and 44% of bulimics overeat. A survey of 15- to 18-year-old high school girls in Nadroga, Fiji, found the self-reported incidence of purging rose from 0% in 1995 (a few weeks after the introduction of television in the province) to 11.3% in 1998. In addition, the suicide rate among people with bulimia nervosa is 7.5 times higher than in the general population.

When attempting to decipher the origin of bulimia nervosa in a cognitive context, Christopher Fairburn et al.'s cognitive-behavioral model is often considered the golden standard. Fairburn et al.'s model discusses the process in which an individual falls into the binge-purge cycle and thus develops bulimia. Fairburn et al. argue that extreme concern with weight and shape coupled with low self-esteem will result in strict, rigid, and inflexible dietary rules. Accordingly, this would lead to unrealistically restricted eating, which may consequently induce an eventual "slip" where the individual commits a minor infraction of the strict and inflexible dietary rules. Moreover, the cognitive distortion due to dichotomous thinking leads the individual to binge. The binge subsequently should trigger a perceived loss of control, promoting the individual to purge in hope of counteracting the binge. However, Fairburn et al. assert the cycle repeats itself, and thus consider the binge-purge cycle to be self-perpetuating.

In contrast, Byrne and Mclean's findings differed slightly from Fairburn et al.'s cognitive-behavioral model of bulimia nervosa in that the drive for thinness was the major cause of purging as a way of controlling weight. In turn, Byrne and Mclean argued that this makes the individual vulnerable to binging, indicating that it is not a binge-purge cycle but rather a purge-binge cycle in that purging comes before bingeing. Similarly, Fairburn et al.'s cognitive-behavioral model of bulimia nervosa is not necessarily applicable to every individual and is certainly reductionist. Every one differs from another, and taking such a complex behavior like bulimia and applying the same one theory to everyone would certainly be invalid. In addition, the cognitive-behavioral model of bulimia nervosa is very culturally bound in that it may not be necessarily applicable to cultures outside of Western society. To evaluate, Fairburn et al..'s model and more generally the cognitive explanation of bulimia nervosa is more descriptive than explanatory, as it does not necessarily explain how bulimia arises. Furthermore, it is difficult to ascertain cause and effect, because it may be that distorted eating leads to distorted cognition rather than vice versa.

A considerable amount of literature has identified a correlation between sexual abuse and the development of bulimia nervosa. The reported incident rate of unwanted sexual contact is higher among those with bulimia nervosa than anorexia nervosa.

When exploring the etiology of bulimia through a socio-cultural perspective, the "thin ideal internalization" is significantly responsible. The thin-ideal internalization is the extent to which individuals adapt to the societal ideals of attractiveness. Studies have shown that young females that read fashion magazines tend to have more bulimic symptoms than those females who do not. This further demonstrates the impact of media on the likelihood of developing the disorder. Individuals first accept and "buy into" the ideals, and then attempt to transform themselves in order to reflect the societal ideals of attractiveness. J. Kevin Thompson and Eric Stice claim that family, peers, and most evidently media reinforce the thin ideal, which may lead to an individual accepting and "buying into" the thin ideal. In turn, Thompson and Stice assert that if the thin ideal is accepted, one could begin to feel uncomfortable with their body shape or size since it may not necessarily reflect the thin ideal set out by society. Thus, people feeling uncomfortable with their bodies may cause suffering from body dissatisfaction and may develop a certain drive for thinness. Consequently, body dissatisfaction coupled with a drive for thinness is thought to promote dieting and negative effects, which could eventually lead to bulimic symptoms such as purging or bingeing. Binges lead to self-disgust which causes purging to prevent weight gain.

A study dedicated to investigating the thin ideal internalization as a factor of bulimia nervosa is Thompson's and Stice's research. Their study aimed to investigate how and to what degree media affects the thin ideal internalization. Thompson and Stice used randomized experiments (more specifically programs) dedicated to teaching young women how to be more critical when it comes to media, to reduce thin-ideal internalization. The results showed that by creating more awareness of the media's control of the societal ideal of attractiveness, the thin ideal internalization significantly dropped. In other words, less thin ideal images portrayed by the media resulted in less thin-ideal internalization. Therefore, Thompson and Stice concluded that media greatly affected the thin ideal internalization. Papies showed that it is not the thin ideal itself, but rather the self-association with other persons of a certain weight that decide how someone with bulimia nervosa feels. People that associate themselves with thin models get in a positive attitude when they see thin models and people that associate with overweight get in a negative attitude when they see thin models. Moreover, it can be taught to associate with thinner people.

Diagnosis

The onset of bulimia nervosa is often during adolescence, between 13 and 20 years of age, and many cases have previously suffered from obesity, with many sufferers relapsing in adulthood into episodic bingeing and purging even after initially successful treatment and remission. A lifetime prevalence of 0.5 percent and 0.9 percent for adult and adolescent sufferers, respectively, is estimated among the United States population. Bulimia nervosa may affect up to 1% of young women and, after 10 years of diagnosis, half will recover fully, a third will recover partially, and 10–20% will still have symptoms.

Adolescents with bulimia nervosa are more likely to have self-imposed perfectionism and compulsivity issues in eating compared to their peers. This means that the high expectations and unrealistic goals that these individuals set for themselves are internally motivated rather than by social views or expectations.

Criteria

Bulimia nervosa can be difficult to detect, compared to anorexia nervosa, because bulimics tend to be of average or slightly above average weight. Many bulimics may also engage in significantly disordered eating and exercise patterns without meeting the full diagnostic criteria for bulimia nervosa. Recently, the Diagnostic and Statistical Manual of Mental Disorders was revised, which resulted in the loosening of criteria regarding the diagnoses of bulimia nervosa and anorexia nervosa. The diagnostic criteria utilized by the DSM-5 includes repetitive episodes of binge eating (a discrete episode of overeating during which the individual feels out of control of consumption) compensated for by excessive or inappropriate measures taken to avoid gaining weight. The diagnosis also requires the episodes of compensatory behaviors and binge eating to happen a minimum of once a week for a consistent time period of 3 months. The diagnosis is made only when the behavior is not a part of the symptom complex of anorexia nervosa and when the behavior reflects an overemphasis on physical mass or appearance. Purging often is a common characteristic of a more severe case of bulimia nervosa.

Treatment

There are two main types of treatment given to those suffering with bulimia nervosa; psychopharmacological and psychosocial treatments.

Psychotherapy

There are several supported psychosocial treatments for bulimia. Cognitive behavioral therapy (CBT), which involves teaching a person to challenge automatic thoughts and engage in behavioral experiments (for example, in session eating of "forbidden foods") has a small amount of evidence supporting its use.

By using CBT people record how much food they eat and periods of vomiting with the purpose of identifying and avoiding emotional fluctuations that bring on episodes of bulimia on a regular basis. Barker (2003) states that research has found 40–60% of people using cognitive behaviour therapy to become symptom free. He states in order for the therapy to work, all parties must work together to discuss, record and develop coping strategies. Barker (2003) claims by making people aware of their actions they will think of alternatives. People undergoing CBT who exhibit early behavioral changes are most likely to achieve the best treatment outcomes in the long run. Researchers have also reported some positive outcomes for interpersonal psychotherapy and dialectical behavior therapy.

Maudsley family therapy, developed at the Maudsley Hospital in London for the treatment of anorexia has been shown promising results in bulimia.

The use of Cognitive Behavioral Therapy (CBT) has been shown to be quite effective for treating bulimia nervosa (BN) in adults, but little research has been done on effective treatments of BN for adolescents. Although CBT is seen as more cost-efficient and helps individuals with BN in self-guided care, Family Based Treatment (FBT) might be more helpful to younger adolescents who need more support and guidance from their families. Adolescents are at the stage where their brains are still quite malleable and developing gradually. Therefore, young adolescents with BN are less likely to realize the detrimental consequences of becoming bulimic and have less motivation to change, which is why FBT would be useful to have families intervene and support the teens. Working with BN patients and their families in FBT can empower the families by having them involved in their adolescent's food choices and behaviors, taking more control of the situation in the beginning and gradually letting the adolescent become more autonomous when they have learned healthier eating habits.

Medication

Antidepressants of the selective serotonin reuptake inhibitors (SSRI) class may have a modest benefit. This includes fluoxetine, which is FDA approved, for the treatment of bulimia, other antidepressants such as sertraline may also be effective against bulimia. Topiramate may also be useful but has greater side effects. Compared to placebo, the use of a single antidepressant has been shown to be effective.

Combining medication with counseling can improve outcomes in some circumstances. Some positive outcomes of treatments can include: abstinence from binge eating, a decrease in obsessive behaviors to lose weight and in shape preoccupation, less severe psychiatric symptoms, a desire to counter the effects of binge eating, as well as an improvement in social functioning and reduced relapse rates.

Alternative medicine

Some researchers have also claimed positive outcomes in hypnotherapy.

Epidemiology

Deaths due to eating disorders per million persons in 2012

  0-0

  1-1

  2-2

  3-3

  4–25

There is little data on the percentage of people with bulimia in general populations. Most studies conducted thus far have been on convenience samples from hospital patients, high school or university students. These have yielded a wide range of results: between 0.1% and 1.4% of males, and between 0.3% and 9.4% of females. Studies on time trends in the prevalence of bulimia nervosa have also yielded inconsistent results. According to Gelder, Mayou and Geddes (2005) bulimia nervosa is prevalent between 1 and 2 percent of women aged 15–40 years. Bulimia nervosa occurs more frequently in developed countries and in cities, with one study finding that bulimia is five times more prevalent in cities than in rural areas. There is a perception that bulimia is most prevalent amongst girls from middle-class families; however, in a 2009 study girls from families in the lowest income bracket studied were 153 percent more likely to be bulimic than girls from the highest income bracket.

There are higher rates of eating disorders in groups involved in activities which idealize a slim physique, such as dance, gymnastics, modeling, cheerleading, running, acting, swimming, diving, rowing and figure skating. Bulimia is thought to be more prevalent among Caucasians; however, a more recent study showed that African-American teenage girls were 50 percent more likely than Caucasian girls to exhibit bulimic behavior, including both binging and purging.

Country	Year	Sample size and type	% affected
Australia	2008	1,943 adolescents (ages 15–17)	1.0% male	6.4% female
Portugal	2006	2,028 high school students		0.3% female
Brazil	2004	1,807 students (ages 7–19)	0.8% male	1.3% female
Spain	2004	2,509 female adolescents (ages 13–22)		1.4% female
Hungary	2003	580 Budapest residents	0.4% male	3.6% female
Australia	1998	4,200 high school students	0.3% combined
United States	1996	1,152 college students	0.2% male	1.3% female
Norway	1995	19,067 psychiatric patients	0.7% male	7.3% female
Canada	1995	8,116 (random sample)	0.1% male	1.1% female
Japan	1995	2,597 high school students	0.7% male	1.9% female
United States	1992	799 college students	0.4% male	5.1% female

History

Etymology

The term bulimia comes from Greek βουλιμία boulīmia, "ravenous hunger", a compound of βοῦς bous, "ox" and λιμός, līmos, "hunger". Literally, the scientific name of the disorder, bulimia nervosa, translates to "nervous ravenous hunger".

Before the 20th century

Although diagnostic criteria for bulimia nervosa did not appear until 1979, evidence suggests that binging and purging were popular in certain ancient cultures. The first documented account of behavior resembling bulimia nervosa was recorded in Xenophon's Anabasis around 370 B.C, in which Greek soldiers purged themselves in the mountains of Asia Minor. It is unclear whether this purging was preceded by binging. In ancient Egypt, physicians recommended purging once a month for three days to preserve health. This practice stemmed from the belief that human diseases were caused by the food itself. In ancient Rome, elite society members would vomit to "make room" in their stomachs for more food at all-day banquets. Emperors Claudius and Vitellius both were gluttonous and obese, and they often resorted to habitual purging.

Historical records also suggest that some saints who developed anorexia (as a result of a life of asceticism) may also have displayed bulimic behaviors. Saint Mary Magdalen de Pazzi (1566–1607) and Saint Veronica Giuliani (1660–1727) were both observed binge eating—giving in, as they believed, to the temptations of the devil. Saint Catherine of Siena (1347–1380) is known to have supplemented her strict abstinence from food by purging as reparation for her sins. Catherine died from starvation at age thirty-three.

While the psychological disorder "bulimia nervosa" is relatively new, the word "bulimia," signifying overeating, has been present for centuries. The Babylon Talmud referenced practices of "bulimia," yet scholars believe that this simply referred to overeating without the purging or the psychological implications bulimia nervosa. In fact, a search for evidence of bulimia nervosa from the 17th to late 19th century revealed that only a quarter of the overeating cases they examined actually vomited after the binges. There was no evidence of deliberate vomiting or an attempt to control weight.

20th century

At the turn of the century, bulimia (overeating) was described as a clinical symptom, but rarely in the context of weight control. Purging, however, was seen in anorexic patients and attributed to gastric pain rather than another method of weight control.

In 1930, admissions of anorexia nervosa patients to the Mayo Clinic from 1917 to 1929 were compiled. Fifty-five to sixty-five percent of these patients were reported to be voluntarily vomiting to relieve weight anxiety. Records show that purging for weight control continued throughout the mid-1900s. Several case studies from this era reveal patients suffering from the modern description of bulimia nervosa. In 1939, Rahman and Richardson reported that out of their six anorexic patients, one had periods of overeating, and another practiced self-induced vomiting. Wulff, in 1932, treated "Patient D," who would have periods of intense cravings for food and overeat for weeks, which often resulted in frequent vomiting. Patient D, who grew up with a tyrannical father, was repulsed by her weight and would fast for a few days, rapidly losing weight. Ellen West, a patient described by Ludwig Binswanger in 1958, was teased by friends for being fat and excessively took thyroid pills to lose weight, later using laxatives and vomiting. She reportedly consumed dozens of oranges and several pounds of tomatoes each day, yet would skip meals. After being admitted to a psychiatric facility for depression, Ellen ate ravenously yet lost weight, presumably due to self-induced vomiting. However, while these patients may have met modern criteria for bulimia nervosa, they cannot technically be diagnosed with the disorder, as it had not yet appeared in the Diagnostic and Statistical Manual of Mental Disorders at the time of their treatment.

An explanation for the increased instances of bulimic symptoms may be due to the 20th century's new ideals of thinness. The shame of being fat emerged in the 1940s when teasing remarks about weight became more common. The 1950s, however, truly introduced the trend of aspiration for thinness.

In 1979, Gerald Russell first published a description of bulimia nervosa, in which he studied patients with a "morbid fear of becoming fat" who overate and purged afterward. He specified treatment options and indicated the seriousness of the disease, which can be accompanied by depression and suicide. In 1980, bulimia nervosa first appeared in the DSM-III.

After its appearance in the DSM-III, there was a sudden rise in the documented incidences of bulimia nervosa. In the early 1980s, incidences of the disorder rose to about 40 in every 100,000 people. This decreased to about 27 in every 100,000 people at the end of the 1980s/early 1990s. However, bulimia nervosa's prevalence was still much higher than anorexia nervosa's, which at the time occurred in about 14 people per 100,000.

In 1991, Kendler et al. documented the cumulative risk for bulimia nervosa for those born before 1950, from 1950 to 1959, and after 1959. The risk for those born after 1959 is much higher than those in either of the other cohorts.

Force field (chemistry)

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Force_field_(chemistry) 

A force field is used to minimize the bond stretching energy of this ethane molecule.

In the context of chemistry and molecular modelling, a force field is a computational method that is used to estimate the forces between atoms within molecules and also between molecules. More precisely, the force field refers to the functional form and parameter sets used to calculate the potential energy of a system of atoms or coarse-grained particles in molecular mechanics, molecular dynamics, or Monte Carlo simulations. The parameters for a chosen energy function may be derived from experiments in physics and chemistry, calculations in quantum mechanics, or both. Force fields are interatomic potentials and utilize the same concept as force fields in classical physics, with the difference that the force field parameters in chemistry describe the energy landscape, from which the acting forces on every particle are derived as a gradient of the potential energy with respect to the particle coordinates.

All-atom force fields provide parameters for every type of atom in a system, including hydrogen, while united-atom interatomic potentials treat the hydrogen and carbon atoms in methyl groups and methylene bridges as one interaction center. Coarse-grained potentials, which are often used in long-time simulations of macromolecules such as proteins, nucleic acids, and multi-component complexes, sacrifice chemical details for higher computing efficiency.

Functional form

Molecular mechanics potential energy function with continuum solvent.

The basic functional form of potential energy in molecular mechanics includes bonded terms for interactions of atoms that are linked by covalent bonds, and nonbonded (also termed noncovalent) terms that describe the long-range electrostatic and van der Waals forces. The specific decomposition of the terms depends on the force field, but a general form for the total energy in an additive force field can be written as

${\displaystyle \ E_{\text{total}}=E_{\text{bonded}}+E_{\text{nonbonded}}}$

where the components of the covalent and noncovalent contributions are given by the following summations:

${\displaystyle \ E_{\text{bonded}}=E_{\text{bond}}+E_{\text{angle}}+E_{\text{dihedral}}}$

${\displaystyle \ E_{\text{nonbonded}}=E_{\text{electrostatic}}+E_{\text{van der Waals}}}$

The bond and angle terms are usually modeled by quadratic energy functions that do not allow bond breaking. A more realistic description of a covalent bond at higher stretching is provided by the more expensive Morse potential. The functional form for dihedral energy is variable from one force field to another. Additional, "improper torsional" terms may be added to enforce the planarity of aromatic rings and other conjugated systems, and "cross-terms" that describe the coupling of different internal variables, such as angles and bond lengths. Some force fields also include explicit terms for hydrogen bonds.

The nonbonded terms are computationally most intensive. A popular choice is to limit interactions to pairwise energies. The van der Waals term is usually computed with a Lennard-Jones potential and the electrostatic term with Coulomb's law. However, both can be buffered or scaled by a constant factor to account for electronic polarizability. Studies with this energy expression have focused on biomolecules since the 1970s and were generalized to compounds across the periodic table in the early 2000s, including metals, ceramics, minerals, and organic compounds.

Bond stretching

As it is rare for bonds to deviate significantly from their reference values, the most simplistic approaches utilize a Hooke's law formula:

${\displaystyle E_{\text{bond}}={\frac {k_{ij}}{2}}(l_{ij}-l_{0,ij})^{2}}$

Where ${\displaystyle k_{ij}}$ is the force constant, ${\displaystyle l_{ij}}$ is the bond length and ${\displaystyle l_{0,ij}}$ is the value for the bond length between atoms ${\displaystyle i}$ and ${\displaystyle j}$ when all other terms in the force field are set to 0. The term ${\displaystyle l_{0,ij}}$ is often referred to as the equilibrium bond length, which may cause confusion. The equilibrium bond length is the value adopted in equilibrium at 298 K with all other force field terms and kinetic energy contributing. Therefore, ${\displaystyle l_{0,ij}}$ is often a few percent different from the actual bond length in experiments at 298 K.

The bond stretching constant ${\displaystyle k_{ij}}$ can be determined from the experimental Infrared spectrum, Raman spectrum, or high-level quantum mechanical calculations. The constant ${\displaystyle k_{ij}}$ determines vibrational frequencies in molecular dynamics simulations. The stronger the bond is between atoms, the higher is the value of the force constant, and the higher the wavenumber (energy) in the IR/Raman spectrum. The vibration spectrum according to a given force constant can be computed from short MD trajectories (5 ps) with ~1 fs time steps, calculation of the velocity autocorrelation function, and its Fourier transform.

Though the formula of Hooke's law provides a reasonable level of accuracy at bond lengths near the equilibrium distance, it is less accurate as one moves away. In order to model the Morse curve better one could employ cubic and higher powers.^[2][6] However, for most practical applications these differences are negligible and inaccuracies in predictions of bond lengths are on the order of the thousandth of an angstrom, which is also the limit of reliability for common force fields. A Morse potential can be employed instead to enable bond breaking and higher accuracy, even though it is less efficient to compute.

Electrostatic interactions

Electrostatic interactions are represented by a Coulomb energy, which utilizes atomic charges ${\displaystyle q_{i}}$ to represent chemical bonding ranging from covalent to polar covalent and ionic bonding. The typical formula is the Coulomb law:

${\displaystyle E_{\text{Coulomb}}={1 \over 4\pi \varepsilon _{0}}{\frac {q_{i}q_{j}}{r_{ij}}}}$

Where ${\displaystyle r_{ij}}$ is the distance between two atoms ${\displaystyle i}$ and ${\displaystyle j}$. The total Coulomb energy is a summation over all pairwise combinations of atoms and usually excludes 1, 2 bonded atoms, 1, 3 bonded atoms, as well as 1, 4 bonded atoms.

Atomic charges can make dominant contributions to the potential energy, especially for polar molecules and ionic compounds, and are critical to simulate the geometry, interaction energy, as well as the reactivity. The assignment of atomic charges often still follows empirical and unreliable quantum mechanical protocols, which often lead to several 100% uncertainty relative to physically justified values in agreement with experimental dipole moments and theory. Reproducible atomic charges for force fields based on experimental data for electron deformation densities, internal dipole moments, and an Extended Born model have been developed. Uncertainties <10%, or ±0.1e, enable a consistent representation of chemical bonding and up to hundred times higher accuracy in computed structures and energies along with physical interpretation of other parameters in the force field.

Parameterization

In addition to the functional form of the potentials, force fields define a set of parameters for different types of atoms, chemical bonds, dihedral angles, out-of-plane interactions, nonbond interactions, and possible other terms. Many parameter sets are empirical and some force fields use extensive fitting terms that are difficult to assign a physical interpretation. Atom types are defined for different elements as well as for the same elements in sufficiently different chemical environments. For example, oxygen atoms in water and an oxygen atoms in a carbonyl functional group are classified as different force field types. Typical force field parameter sets include values for atomic mass, atomic charge, Lennard-Jones parameters for every atom type, as well as equilibrium values of bond lengths, bond angles, and dihedral angles. The bonded terms refer to pairs, triplets, and quadruplets of bonded atoms, and include values for the effective spring constant for each potential. Most current force fields parameters use a fixed-charge model by which each atom is assigned one value for the atomic charge that is not affected by the local electrostatic environment.

Force field parameterizations for simulations with maximum accuracy and transferability, e.g., IFF, follow a well-defined protocol. The workflow may involve (1) retrieving an x-ray crystal structure or chemical formula, (2) defining atom types, (3) obtaining atomic charges, (4) assigning initial Lennard-Jones and bonded parameters, (5) computational tests of density and geometry relative to experimental reference data, (6) computational tests of energetic properties (surface energy, hydration energy) relative to experimental reference data, (7) secondary validation and refinement (thermal, mechanical, and diffusion properties). Major iterative loops occur between steps (5) and (4), as well as between (6) and (4)/(3). The chemical interpretation of the parameters and reliable experimental reference data play a critical role.

The parameters for molecular simulations of biological macromolecules such as proteins, DNA, and RNA were often derived from observations for small organic molecules, which are more accessible for experimental studies and quantum calculations. Thereby, multiple issues arise, such as (1) unreliable atomic charges from quantum calculations may affect all computed properties and internal consistency, (2) data different derived from quantum mechanics for molecules in the gas phase may not be transferable for simulations in the condensed phase, (3) use of data for small molecules and application to larger polymeric structures involves uncertainty, (4) dissimilar experimental data with variation in accuracy and reference states (e.g. temperature) can cause deviations. As a result, divergent force field parameters have been reported for biological molecules. Experimental reference data included, for example, the enthalpy of vaporization (OPLS), enthalpy of sublimation, dipole moments, and various spectroscopic parameters. Inconsistencies can be overcome by interpretation of all force field parameters and choosing a consistent reference state, for example, room temperature and atmospheric pressure.

Several force fields also include no clear chemical rationale, parameterization protocol, incomplete validation of key properties (structures and energies), lack of interpretation of parameters, and of a discussion of uncertainties. In these cases, large, random deviations of computed properties have been reported.

Methods

Some force fields include explicit models for polarizability, where a particle's effective charge can be influenced by electrostatic interactions with its neighbors. Core-shell models are common, which consist of a positively charged core particle, representing the polarizable atom, and a negatively charged particle attached to the core atom through a springlike harmonic oscillator potential. Recent examples include polarizable models with virtual electrons that reproduce image charges in metals and polarizable biomolecular force fields. By adding such degrees of freedom for polarizability, the interpretation of the parameters becomes more difficult and increases the risk towards arbitrary fit parameters and decreased compatibility. The computational expense increases due to the need to repeatedly calculate the local electrostatic field.

Polarizable models perform well when it captures essential chemical features and the net atomic charge is relatively accurate (within ±10%). In recent times, such models have been erroneously called "Drude Oscillator potentials". An appropriate term for these models is "Lorentz oscillator models" since Lorentz rather than Drude proposed some form of attachment of electrons to nuclei. Drude models assume unrestricted motion of the electrons, e.g., a free electron gas in metals.

Parameterization

Historically, many approaches to parameterization of a forcefield have been employed. Numerous classical forcefields relied on relatively intransparent parameterization protocols, for example, using approximate quantum mechanical calculations, often in the gas phase, with the expectation of some correlation with condensed phase properties and empirical modifications of potentials to match experimental observables. The protocols may not be reproducible and semi-automation often played a role to generate parameters, optimizing for speedy parameter generation and wide coverage, and not for chemical consistency, interpretability, reliability, and sustainability.

Similar, even more automated tools have become recently available to parameterize new force fields and assist users to develop their own parameter sets for chemistries which are not parameterized to date. Efforts to provide open source codes and methods include openMM and openMD. The use of semi-automation or full automation, without input from chemical knowledge, is likely to increase inconsistencies at the level of atomic charges, for the assignment of remaining parameters, and likely to dilute the interpretability and performance of parameters.

The Interface force field (IFF) assumes one single energy expression for all compounds across the periodic (with 9-6 and 12-6 LJ options) and utilizes rigorous validation with standardized simulation protocols that enable full interpretability and compatibility of the parameters, as well as high accuracy and access to unlimited combinations of compounds.

Transferability

Functional forms and parameter sets have been defined by the developers of interatomic potentials and feature variable degrees of self-consistency and transferability. When functional forms of the potential terms vary, the parameters from one interatomic potential function can typically not be used together with another interatomic potential function. In some cases, modifications can be made with minor effort, for example, between 9-6 Lennard-Jones potentials to 12-6 Lennard-Jones potentials. Transfers from Buckingham potentials to harmonic potentials, or from Embedded Atom Models to harmonic potentials, on the contrary, would require many additional assumptions and may not be possible.

Limitations

All interatomic potentials are based on approximations and experimental data, therefore often termed empirical. The performance varies from higher accuracy than density functional theory calculations, with access to million times larger systems and time scales, to random guesses depending on the force field. The use of accurate representations of chemical bonding, combined with reproducible experimental data and validation, can lead to lasting interatomic potentials of high quality with much less parameters and assumptions in comparison to DFT-level quantum methods.

Possible limitations include atomic charges, also called point charges. Most force fields rely on point charges to reproduce the electrostatic potential around molecules, which works less well for anisotropic charge distributions. The remedy is that point charges have a clear interpretation, and virtual electrons can be added to capture essential features of the electronic structure, such additional polarizability in metallic systems to describe the image potential, internal multipole moments in π-conjugated systems, and lone pairs in water. Electronic polarization of the environment may be better included by using polarizable force fields or using a macroscopic dielectric constant. However, application of one value of dielectric constant is a coarse approximation in the highly heterogeneous environments of proteins, biological membranes, minerals, or electrolytes.

All types of van der Waals forces are also strongly environment-dependent because these forces originate from interactions of induced and "instantaneous" dipoles (see Intermolecular force). The original Fritz London theory of these forces applies only in a vacuum. A more general theory of van der Waals forces in condensed media was developed by A. D. McLachlan in 1963 and included the original London's approach as a special case. The McLachlan theory predicts that van der Waals attractions in media are weaker than in vacuum and follow the like dissolves like rule, which means that different types of atoms interact more weakly than identical types of atoms. This is in contrast to combinatorial rules or Slater-Kirkwood equation applied for development of the classical force fields. The combinatorial rules state that the interaction energy of two dissimilar atoms (e.g., C...N) is an average of the interaction energies of corresponding identical atom pairs (i.e., C...C and N...N). According to McLachlan's theory, the interactions of particles in media can even be fully repulsive, as observed for liquid helium, however, the lack of vaporization and presence of a freezing point contradicts a theory of purely repulsive interactions. Measurements of attractive forces between different materials (Hamaker constant) have been explained by Jacob Israelachvili. For example, "the interaction between hydrocarbons across water is about 10% of that across vacuum". Such effects are represented in molecular dynamics through pairwise interactions that are spatially more dense in the condensed phase relative to the gas phase and reproduced once the parameters for all phases are validated to reproduce chemical bonding, density, and cohesive/surface energy.

Limitations have been strongly felt in protein structure refinement. The major underlying challenge is the huge conformation space of polymeric molecules, which grows beyond current computational feasibility when containing more than ~20 monomers. Participants in Critical Assessment of protein Structure Prediction (CASP) did not try to refine their models to avoid "a central embarrassment of molecular mechanics, namely that energy minimization or molecular dynamics generally leads to a model that is less like the experimental structure". Force fields have been applied successfully for protein structure refinement in different X-ray crystallography and NMR spectroscopy applications, especially using program XPLOR. However, the refinement is driven mainly by a set of experimental constraints and the interatomic potentials serve mainly to remove interatomic hindrances. The results of calculations were practically the same with rigid sphere potentials implemented in program DYANA (calculations from NMR data), or with programs for crystallographic refinement that use no energy functions at all. These shortcomings are related to interatomic potentials and to the inability to sample the conformation space of large molecules effectively. Thereby also the development of parameters to tackle such large-scale problems requires new approaches. A specific problem area is homology modeling of proteins. Meanwhile, alternative empirical scoring functions have been developed for ligand docking, protein folding, homology model refinement, computational protein design, and modeling of proteins in membranes.

It was also argued that some protein force fields operate with energies that are irrelevant to protein folding or ligand binding. The parameters of proteins force fields reproduce the enthalpy of sublimation, i.e., energy of evaporation of molecular crystals. However, protein folding and ligand binding are thermodynamically closer to crystallization, or liquid-solid transitions as these processes represent freezing of mobile molecules in condensed media. Thus, free energy changes during protein folding or ligand binding are expected to represent a combination of an energy similar to heat of fusion (energy absorbed during melting of molecular crystals), a conformational entropy contribution, and solvation free energy. The heat of fusion is significantly smaller than enthalpy of sublimation. Hence, the potentials describing protein folding or ligand binding need more consistent parameterization protocols, e.g., as described for IFF. Indeed, the energies of H-bonds in proteins are ~ -1.5 kcal/mol when estimated from protein engineering or alpha helix to coil transition data, but the same energies estimated from sublimation enthalpy of molecular crystals were -4 to -6 kcal/mol, which is related to re-forming existing hydrogen bonds and not forming hydrogen bonds from scratch. The depths of modified Lennard-Jones potentials derived from protein engineering data were also smaller than in typical potential parameters and followed the like dissolves like rule, as predicted by McLachlan theory.

Widely used force fields

Further information: Comparison of force field implementations, Molecular design software, and Comparison of software for molecular mechanics modeling

Different force fields are designed for different purposes. All are implemented in various computers software.

MM2 was developed by Norman Allinger mainly for conformational analysis of hydrocarbons and other small organic molecules. It is designed to reproduce the equilibrium covalent geometry of molecules as precisely as possible. It implements a large set of parameters that is continuously refined and updated for many different classes of organic compounds (MM3 and MM4).

CFF was developed by Arieh Warshel, Lifson, and coworkers as a general method for unifying studies of energies, structures, and vibration of general molecules and molecular crystals. The CFF program, developed by Levitt and Warshel, is based on the Cartesian representation of all the atoms, and it served as the basis for many subsequent simulation programs.

ECEPP was developed specifically for the modeling of peptides and proteins. It uses fixed geometries of amino acid residues to simplify the potential energy surface. Thus, the energy minimization is conducted in the space of protein torsion angles. Both MM2 and ECEPP include potentials for H-bonds and torsion potentials for describing rotations around single bonds. ECEPP/3 was implemented (with some modifications) in Internal Coordinate Mechanics and FANTOM.

AMBER, CHARMM, and GROMOS have been developed mainly for molecular dynamics of macromolecules, although they are also commonly used for energy minimizing. Thus, the coordinates of all atoms are considered as free variables.

Interface Force Field (IFF) was developed as the first consistent force field for compounds across the periodic table. It overcomes the known limitations of assigning consistent charges, utilizes standard conditions as a reference state, reproduces structures, energies, and energy derivatives, and quantifies limitations for all included compounds. It is compatible with multiple force fields to simulate hybrid materials (CHARMM, AMBER, OPLS-AA, CFF, CVFF, GROMOS).

Classical

• AMBER (Assisted Model Building and Energy Refinement) – widely used for proteins and DNA.
• CFF (Consistent Force Field) – a family of forcefields adapted to a broad variety of organic compounds, includes force fields for polymers, metals, etc.
• CHARMM (Chemistry at HARvard Molecular Mechanics) – originally developed at Harvard, widely used for both small molecules and macromolecules
• COSMOS-NMR – hybrid QM/MM force field adapted to various inorganic compounds, organic compounds, and biological macromolecules, including semi-empirical calculation of atomic charges NMR properties. COSMOS-NMR is optimized for NMR-based structure elucidation and implemented in COSMOS molecular modelling package.
• CVFF – also used broadly for small molecules and macromolecules.
• ECEPP – first force field for polypeptide molecules - developed by F.A. Momany, H.A. Scheraga and colleagues.
• GROMOS (GROningen MOlecular Simulation) – a force field that comes as part of the GROMOS software, a general-purpose molecular dynamics computer simulation package for the study of biomolecular systems. GROMOS force field A-version has been developed for application to aqueous or apolar solutions of proteins, nucleotides, and sugars. A B-version to simulate gas phase isolated molecules is also available.
• IFF (Interface Force Field) – First force field to cover metals, minerals, 2D materials, and polymers in one platform with cutting-edge accuracy and compatibility with many other force fields (CHARMM, AMBER, OPLS-AA, CFF, CVFF, GROMOS), includes 12-6 LJ and 9-6 LJ options
• MMFF (Merck Molecular Force Field) – developed at Merck for a broad range of molecules.
• OPLS (Optimized Potential for Liquid Simulations) (variants include OPLS-AA, OPLS-UA, OPLS-2001, OPLS-2005, OPLS3e, OPLS4) – developed by William L. Jorgensen at the Yale University Department of Chemistry.
• QCFF/PI – A general force fields for conjugated molecules.
• UFF (Universal Force Field) – A general force field with parameters for the full periodic table up to and including the actinoids, developed at Colorado State University. The reliability is known to be poor due to lack of validation and interpretation of the parameters for nearly all claimed compounds, especially metals and inorganic compounds.

Polarizable

• AMBER – polarizable force field developed by Jim Caldwell and coworkers.
• AMOEBA (Atomic Multipole Optimized Energetics for Biomolecular Applications) – force field developed by Pengyu Ren (University of Texas at Austin) and Jay W. Ponder (Washington University). AMOEBA force field is gradually moving to more physics-rich AMOEBA+.
• CHARMM – polarizable force field developed by S. Patel (University of Delaware) and C. L. Brooks III (University of Michigan). Based on the classical Drude oscillator developed by A. MacKerell (University of Maryland, Baltimore) and B. Roux (University of Chicago).
• CFF/ind and ENZYMIX – The first polarizable force field which has subsequently been used in many applications to biological systems.
• COSMOS-NMR (Computer Simulation of Molecular Structure) – developed by Ulrich Sternberg and coworkers. Hybrid QM/MM force field enables explicit quantum-mechanical calculation of electrostatic properties using localized bond orbitals with fast BPT formalism. Atomic charge fluctuation is possible in each molecular dynamics step.
• DRF90 developed by P. Th. van Duijnen and coworkers.
• IFF (Interface Force Field) – includes polarizability for metals (Au, W) and pi-conjugated molecules
• NEMO (Non-Empirical Molecular Orbital) – procedure developed by Gunnar Karlström and coworkers at Lund University (Sweden)
• PIPF – The polarizable intermolecular potential for fluids is an induced point-dipole force field for organic liquids and biopolymers. The molecular polarization is based on Thole's interacting dipole (TID) model and was developed by Jiali Gao Gao Research Group | at the University of Minnesota.
• Polarizable Force Field (PFF) – developed by Richard A. Friesner and coworkers.
• SP-basis Chemical Potential Equalization (CPE) – approach developed by R. Chelli and P. Procacci.
• PHAST - polarizable potential developed by Chris Cioce and coworkers.
• ORIENT – procedure developed by Anthony J. Stone (Cambridge University) and coworkers.
• Gaussian Electrostatic Model (GEM) – a polarizable force field based on Density Fitting developed by Thomas A. Darden and G. Andrés Cisneros at NIEHS; and Jean-Philip Piquemal at Paris VI University.
• Atomistic Polarizable Potential for Liquids, Electrolytes, and Polymers(APPLE&P), developed by Oleg Borogin, Dmitry Bedrov and coworkers, which is distributed by Wasatch Molecular Incorporated.
• Polarizable procedure based on the Kim-Gordon approach developed by Jürg Hutter and coworkers (University of Zürich)
• GFN-FF (Geometry, Frequency, and Noncovalent Interaction Force-Field) - a completely automated partially polarizable generic force-field for the accurate description of structures and dynamics of large molecules across the periodic table developed by Stefan Grimme and Sebastian Spicher at the University of Bonn.

Reactive

• EVB (Empirical valence bond) – this reactive force field, introduced by Warshel and coworkers, is probably the most reliable and physically consistent way to use force fields in modeling chemical reactions in different environments. The EVB facilitates calculating activation free energies in condensed phases and in enzymes.
• ReaxFF – reactive force field (interatomic potential) developed by Adri van Duin, William Goddard and coworkers. It is slower than classical MD (50x), needs parameter sets with specific validation, and has no validation for surface and interfacial energies. Parameters are non-interpretable. It can be used atomistic-scale dynamical simulations of chemical reactions. Parallelized ReaxFF allows reactive simulations on >>1,000,000 atoms on large supercomputers.

Coarse-grained

• DPD (Dissipative particle dynamics) - This is a method commonly applied in chemical engineering. It is typically used for studying the hydrodynamics of various simple and complex fluids which require consideration of time and length scales larger than those accessible to classical Molecular dynamics. The potential was originally proposed by Hoogerbrugge and Koelman  with later modifications by Español and Warren.  The current state of the art was well documented in a CECAM workshop in 2008. Recently, work has been undertaken to capture some of the chemical subtitles relevant to solutions. This has led to work considering automated parameterisation of the DPD interaction potentials against experimental observables.
• MARTINI – a coarse-grained potential developed by Marrink and coworkers at the University of Groningen, initially developed for molecular dynamics simulations of lipids, later extended to various other molecules. The force field applies a mapping of four heavy atoms to one CG interaction site and is parameterized with the aim of reproducing thermodynamic properties.
• SAFT - A top-down coarse-grained model developed in the Molecular Systems Engineering group at Imperial College London fitted to liquid phase densities and vapor pressures of pure compounds by using the SAFT equation of state.
• SIRAH – a coarse-grained force field developed by Pantano and coworkers of the Biomolecular Simulations Group, Institut Pasteur of Montevideo, Uruguay; developed for molecular dynamics of water, DNA, and proteins. Free available for AMBER and GROMACS packages.
• VAMM (Virtual atom molecular mechanics) – a coarse-grained force field developed by Korkut and Hendrickson for molecular mechanics calculations such as large scale conformational transitions based on the virtual interactions of C-alpha atoms. It is a knowledge based force field and formulated to capture features dependent on secondary structure and on residue-specific contact information in proteins.

Machine learning

• ANI is a transferable neural network potential, built from atomic environment vectors, and able to provide DFT accuracy in terms of energies.
• FFLUX (originally QCTFF)  A set of trained Kriging models which operate together to provide a molecular force field trained on Atoms in molecules or Quantum chemical topology energy terms including electrostatic, exchange and electron correlation.
• TensorMol, a mixed model, a Neural network provides a short-range potential, whilst more traditional potentials add screened long range terms.
• Δ-ML not a force field method but a model that adds learnt correctional energy terms to approximate and relatively computationally cheap quantum chemical methods in order to provide an accuracy level of a higher order, more computationally expensive quantum chemical model.
• SchNet a Neural network utilising continuous-filter convolutional layers, to predict chemical properties and potential energy surfaces.
• PhysNet is a Neural Network-based energy function to predict energies, forces and (fluctuating) partial charges.

Water

Main article: Water model

The set of parameters used to model water or aqueous solutions (basically a force field for water) is called a water model. Water has attracted a great deal of attention due to its unusual properties and its importance as a solvent. Many water models have been proposed; some examples are TIP3P, TIP4P, SPC, flexible simple point charge water model (flexible SPC), ST2, and mW. Other solvents and methods of solvent representation are also applied within computational chemistry and physics some examples are given on page Solvent model. Recently, novel methods for generating water models have been published.

Modified amino acids

• Forcefield_PTM – An AMBER-based forcefield and webtool for modeling common post-translational modifications of amino acids in proteins developed by Chris Floudas and coworkers. It uses the ff03 charge model and has several side-chain torsion corrections parameterized to match the quantum chemical rotational surface.
• Forcefield_NCAA - An AMBER-based forcefield and webtool for modeling common non-natural amino acids in proteins in condensed-phase simulations using the ff03 charge model. The charges have been reported to be correlated with hydration free energies of corresponding side-chain analogs.

Other

• LFMM (Ligand Field Molecular Mechanics) - functions for the coordination sphere around transition metals based on the angular overlap model (AOM). Implemented in the Molecular Operating Environment (MOE) as DommiMOE and in Tinker
• VALBOND - a function for angle bending that is based on valence bond theory and works for large angular distortions, hypervalent molecules, and transition metal complexes. It can be incorporated into other force fields such as CHARMM and UFF.