Progressive Deterioration About Mental Status In Old Age Biology Essay

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Scientific articles quotes progressive deterioration about mental status in old age has been observed and briefed throughout the history. Until 1906, the exact reason of this mental deterioration was not clear.

In 1906, German physician, Dr.Alois Alzheimer's performed a brain autopsy in one of his patients died due to severe memory problems, confusion and difficulty in understanding questions. He noted highly dense aggregated structures around the nerve cells (neuritic plaques) and twisted bands of structures inside the nerve cells (neurofibrillary tangles). Hence the name of this degenerative disorder bears his name (Alzheimer's disease research association, 2010)

Scientific discovery of this degenerative disorder was founded out 100 years ago. During 1960s, scientists found out the relation between the decline in cognition and presence of plaques and neurofibrillary tangles in the brain. Scientists recognized this (Alzheimer's) as a disease and it is not a part of aging.

In 1990's the research on molecular level study of neuronal degeneration and susceptibility genes. Scientists worked on finding out genetic, environmental, and other risk factors responsible for the formation of amyloid plaques and neurofibrillary tangles.

FDA approved drugs were currently used to treat only the cognitive symptoms of the AD, and these drugs only slows the progressive decline in cognition.

Progressive changes in molecular environment of neurons and neurodegeneration has its implication in psychological functioning. Degenerative diseases are the diseases of grey matter characterized by the progressive loss of neurons which is associated with secondary changes in white matter of brain. The pattern of neuronal loss is selective, affecting one or more group of neurons leaving others intact. They arise without any clear inciting event in a patient without previous neurologic deficits.

The major critical degenerative diseases are Alzheimer's disease and Pick disease. Their clinical manifestation is seemed to be "dementia".

Dementia is the progressive loss of cognition independent of the state of attention resulting from diseases of the brain (Gilroy, 1985).It may be due to,

Therapeutic drug use (e.g. Atropine, Phenytoin,etc.,)

Metabolic systemic disorders (e.g. Acid-base disorders, hypo - ,hyperglycemia , haematological disorders ,Pulmonary insufficiency, Hypopituitarism, Cardiac dysfunction, Hepatolenticular degeneration)

Intracranial disorders(e.g. cerebrovascular insufficiency, chronic meningitis or encephalitis, neurosyphilis, HIV, Epilepsy,tumor,abscess,subdural hematomas, multiple sclerosis, normal pressure hydrocephalus)

Deficiency states (e.g. vitamin B 12 deficiency, folate deficiency, niacin or pellagra)

Collagen - vascular disorders : Systemic lupus erythematosus, temporal arteritis, sarcoidosis, Behcet's syndrome)

Exogenous intoxication: (e.g. Alcohol, Carbon monoxide, organophosphates, toluene, trichloroethylene , carbon disulfide, lead, mercury, arsenic, thallium, manganese)

Dementia is not part of normal aging and always represents a pathologic process. The present study investigates on the Alzheimer's disease where dementia is one of the clinical manifestations.

Alzheimer's disease - the most common form of dementia caused by progressive neuronal degeneration with pathological features showing the presence of amyloid plaques and neurofibrillary tangles, primarily affecting middle-aged and elderly individuals in whom it is cause of 70 percent of cases of dementia.(Perry et al.,2003)


The accurate etiology of Alzheimer's disease is unknown. The salient pathological features are the presence of amyloid plaques and neurofibrillary tangles. The "amyloid cascade hypothesis"(Hardy, 1991) is mainly investigated by the researchers and the search for cause of Alzheimer's disease is still going on. The amyloid cascade hypothesis is supported by the study of early-onset Alzheimer's disease due to genetic factors. The mutation leads to increased formation of a particular form of a small protein fragment called A-Beta (Aβ).The past and ongoing researches are focusing on the ways to slow down Alzheimer's disease is to decrease the amount of this protein in the brain, where it is one of the probable causative known.


Physicians keenly observe the following signs for complete evaluation

Loss of memory

Difficulty in familiar tasks performance.

Language problem

Disorientation in time and place

Decreased judgment

Abstract thinking problem

Misplacing things

Mood or behaviour changes

Personality changes

Loss of initiative.


Early stage:

In the first stages of Alzheimer's disease the memory problems initially observed as "normal part of aging" are. One of the common memory problems seen is short-term memory in early stage of Alzheimer's disease.

Personality changes like less spontaneity, lack of interest, and withdrawing from social interactions.

As the disease progresses:

Problems in intellectual functions develop.

Disturbances in behaviour and appearance.

Later in the course of this disorder:

Patient might be Confused or disoriented

Unable to define their place where they live or to name a place

Patients may wander

Unable to engage in conversation


Lose bladder and bowel control (Gilroy et al, 1995).

Final stages of the disease:

Death may follow due to pneumonia or problems of deteriorated conditions. Persons in their later age of life may be prone to die from other diseases (e.g. heart disease) rather than due to Alzheimer's disease.


Early onset AD

Late onset AD

Familial AD

Early onset Alzheimer's: (EOAD)

It is a rare form of AD affecting the people before age 65. This type is seen in less than 10% of all AD patients. (Alzheimer's association, 2007) They experiences premature aging, so those people with Down syndrome are specifically at risk of this type. It is linked with a genetic defect on chromosome 14, where this is not the case in late onset AD. These chromosomal defects can undergo mutation of three genes namely presenilin1, presenilin2, and amyloid precursor protein (Selkoe, 2001). Myoclonus is one of the prevalent condition in AD seen in patients with early onset AD.

Late onset:

Persons with over the age of 65 may also prone to Alzheimer's. Late-onset Alzheimer's increases two folds for every 5 years after the age of sixty five. Though it is not hereditary and this sporadic Alzheimer's can affect any elderly person. On average people live roughly eight to ten years after diagnosis. Sometimes patients with sporadic Alzheimer are if they are associated with other diseases their life time reduces and lead to death.E4 type of gene is responsible for producing the apo lipoprotein. (Robin et al, 1999)

Familial Alzheimer's:

Familial Alzheimer's is entirely inherited. The affected families may show their inheritance to their off springs at least of two generations. It is rare, less than 1% of cases of Alzheimer's disease have FAD. Histological examination shows familial AD is indiscernible from other forms of AD. Amyloid protein forms plaques and neurofibrillary tangles that progress through the memory centers of the brain. The uniqueness of plaque is rare or uncharacteristic of AD. Due to mutation in one of the genes that generates abnormal protein with functional abilities, instead of the incapable gene products. Mutation in different genes like the amyloid precursor protein gene and the presenilin 1 and presenilin 2 genes have been discovered in patients with EOFAD (Selkoe, 2001). The products of these genes interact with the proteins in molecular level and involve in signal transduction between cells.


The present management for the treatment of Alzheimer's is symptomatic. The acetylcholine esterase inhibitors were gaining importance in the management. Increasing the muscarinic function of the brain was clinical approach (Johnston, 1992).

The inhibition of AchE increases the Ach at the vicinity of neuronal Ach receptor.

Among the inhibitors physostigmine improved response in animal models of learning and causes mild transitory improvement in memory of patients with AD. Due to its short half -life and tendency of generating the symptoms of systemic cholinergic excess at therapeutic doses its use limited. Tacrine, donepzil, Rivastigmine, and Galantamine was approved by FDA in the treatment of AD (Mayeux, 1999).

Tacrine is one of the centrally acting AchE inhibitor (Freeman and Dawson, 1991). Oral Tacrine in combination with lecithin increases the memory performance (Chatellier and Lacombelz, 1990). Clinically tacrine is less in use because of its significant side effects like abdominal cramping, anorexia, nausea, vomiting, diarrhoea , elevation of serum transaminases and thus dose- limiting(Alzheimer's association, 2004).

Memantine, NMDA glutamate-receptor antagonist is an alternative in the management of AD.

The disease management of present scenario focuses on AchE inhibition and formation of new memories (Alzheimer's association, 2007). The existing Ach molecules are prevented from degradation and there by act on intact Ach receptors by the use of AchE inhibitors.


Acetyl choline esterase is one of the neurotransmitter in the peripheral nervous system and central nervous system. It is dominantly present in the somatic nervous system.

Choline and acetyl Co-A in the presence of choline acetyltransferase leads to the formation of Acetylcholine (Ach).

Acetyl choline in presence of acetyl cholinesterase converted into inactive metabolite choline and acetate. More amount of enzyme was found to be present in the synaptic cleft. The clearance of free acetylcholine occurs rapidly at the synaptic cleft for the proper muscle function.

Excess amount of Ach is found at the neuromuscular junction due to the inhibition of AchE by neurotoxins. This leads to paralysis of the respiratory muscles and ceasing of the heart functioning.

Acetylcholine at the synaptic cleft as well at autonomic ganglia involve in the cell signalling through second messengers. Degradation of Ach by acetyl cholinesterase leads to Myasthenia gravis, Alzheimer's disease, and Glaucoma.

The thorough study on the molecular basis, the pathological signs of neuronal degeneration (biomarkers) paves the way for treating AD.


AchE falls into two structural classes namely homomeric oligomers and heteromeric forms. Homomeric oligomers with catalytic subunits are soluble in cell. The presence of hydrophobic amino acids sequence makes it to be associated with the glycophospholipid (outer membrane of the cell).Heterologous type is found in neuronal synapse as a tetramer with catalytic subunits of disulfide- linked to lipid with molecular weight of 20,000 Daltons and they found to be attached to the outer surface of the cell membrane through glycophospholipid.

Fig: I 3-dimensional structural image (ribbon-like) of Acetylcholine esterase

From the 3-dimensional structure of AchE, the active site was found to be present at the centerosymmetric to each subunit and present at the base of the gorge about 20Å in depth (Sussman et al, 1995). Serine 203, Histidine 447, and glutamate 334 were the amino acid residue of catalytic triad lies at the base of the gorge.

The serine hydroxyl group is highly nucleophilic due to the charge relay system involving the carboxyl group from glutamate, the Imidazole on the Histidine; this resembles the catalytic mechanism of hydrolases.

AchE forms a tetrahedral intermediate (acyl enzyme) with the substrate (Ach) and this conjugate concomitantly release the choline part of the substrate followed by the formation of acetate (CH3COO-) and active enzyme (AchE). One AchE molecule hydrolyses 600,000 acetylcholine molecules per minute.


The exact molecular basis of AD is complex but the evidence for possible mechanism of neuronal degeneration is available.

The human brain is the remarkable organ with complex, chemical and electrical process occurs. The various processes like speaking, moving, seeing, remembering, feeling emotions and taking decision were executed by different parts of the brain.

In normal healthy brain, billion of cells called neurons constantly communicate with one and another. The messages from each neurons travel along the axons as the electric charges to the end of neuron. The electrical charges releases chemical messengers called neurotransmitters, they move across the microscopic gapes or synapses between neurons. They find receptors on dendrites on the post synaptic neuron (next neurons) and bind to it. This cellular circuit enables communication within the brain. Healthy neurotransmission is necessary for the proper functioning of the brain.

In AD, the disruption of the intricate interplay occurs by compromising the ability of neurons to communicate with one another and on overtime destroys memory and thinking skills. The scientific research revealed some other brain changes that take places in brain, showing abnormal structures of biological hallmarks called beta amyloid and tangles (Arnold et al., 1991; Braak, 1994).

In the forebrain (nucleus basalis of Meynert) the subcortical cholinergic neurons degeneration that provide cholinergic innervations to the whole cerebral cortex and atrophy are anatomical basis of the cholinergic deficit (Johnston, 1992)

The selective deficiency of acetylcholine as well as the observation that central cholinergic antagonists such as atropine can induce a confusional state that bears some resemblance to the dementia of AD, has given rise to the "cholinergic hypothesis," which proposes that a deficiency of acetylcholine is critical in the genesis of the symptoms of AD (Perry,1986).

C:\Users\Karthik\Pictures\alzheime disease.jpg

Fig IV: Neuronal pathways and signalling of parasympathetic nerve fibres

Involved in normal versus Alzheimer's disease

The specific proteins in the neuronal cell membrane are processed differently. Normally an enzyme called alpha secretase sniffs a part of amyloid precursor protein (APP) releasing a fragment. Similarly, a second enzyme called gamma secretase also sniffs remaining portion of APP. The released fragment doesn't cause any harm to neurons. In AD, the different enzyme called beta secretase performs the first sniff of APP and followed remaining part of APP sniffing by gamma secretase which is a short fragment called beta amyloid. These short fragments combine together and become toxic thereby interfering with the functioning of the neurons. As the number of fragments (beta amyloid) adding upon increases, they become insoluble and eventually results in the beta amyloid plaque formation.

The modification of Tau protein leads to the formation of neurofibrillary tangles. In normal brain cells, tau stabilizes structures critical to the cells in terminal transport system. Nutrients and other soluble cargo are carried up and down in the structures called microtubules to all parts of the neurons. In AD the abnormal tau proteins separates from the microtubule, and combine together to form strands called neurofibrillary tangles inside the neurons. This tangle formation disables the neuronal transport system and destroying the cells.

In certain regions of the brain the neurons get disconnected from each other and eventually die, causing memory loss. As these processes continues the brain shrinks and loses its function.


The computer aided drug designing and searching the existing molecule for the ailment of other diseases and disorders are being the scenario used in insilico studies. CADD is generally a ligand- based or target-based method.

Ligand -based methods is the conventional quantitative structure activity relationship studies (Martin et al, 1989).

Comparative molecular field analysis (CoMFA) is based entirely on experimental structure activity relationship for ligands or enzyme inhibitors (Cramer et al, 1988).

Using insilico studies it is possible to study the entire nature of the ligand properties (flexibility, physic-chemical properties, etc) can be studied. The target might be a enzyme, a cell receptor, or genetic sequence (peptides), it can be designed and used for the CADD studies.

Homology modelling is computer assisted program where it is used for the generation of homologue structure of a protein or enzyme if the experimental structure is not available (Weinstein et al, 2005).

Molecular docking is an important computer assisted techniques used for the ligand-protein, protein-protein docking. Enzyme inhibition studies are one of molecular docking technique using appropriate ligands designed.

Absorption, distribution, metabolism, excretion studies of the ligand designed and docked can also be studied using insilico methods in which the simulations are stored in the databases.(Frieser et al,2002)

Using docking techniques it is possible to find out the exact conformation of the ligand and its binding sites with the protein. Analysis of the docked ligands and their synthesis through appropriate methods leads to the discovery of a ligand to a particular target.

Library of chemical compounds

X-ray, NMR , Homology model, etc.,

Target structureEnrichment

Enriched library

Set of targets Receptor structure preparation

(e.g. addition of flexibility)


Successfully docked compounds


Complexes validation

Lead optimization Accurate free energy calculations

Drug candidates

Experimental Testing


Fig: VIII Drug Design Process. Schematic representation of the protocol commonly

followed during a drug design process.Steps within brackets are not always performed.


Molecular docking screens large databases of small molecules by orienting them in the binding site of protein. Top ranked molecules may be tested for binding affinity in vitro, and may become lead compounds, hence the starting point for drug development and optimization.

The conformational and orientational sampling of the drug in the protein site is complex. The model of the protein site itself is complex; often the receptor is kept completely rigid. Perfect ligands above poor compounds are done by using scoring function. Difference of large values with large uncertainties is the net energy of binding, and when ligand binds to the protein it is difficult to calculate the desolvation. (Lydia et al, 2005)

Molecular docking is divided into two types:

Two types of molecular docking are in practice:

1. Ligand - protein docking.

2. Protein - protein docking.

The correct conformation of a ligand and its receptor are done by docking techniques. The prediction of binding mode of a ligand within a receptor is of great importance in modern structure based drug design. Docking is used in virtual screening methods in order to reduce enormous amount of compounds, those includes compounds with high binding affinities. Entropic and enthalpic factors influence the process of binding a molecule to its target receptor (Folkers et al, 1998).

There are some other factors which influence the binding are,

The ligand and receptor mobility,

The effect of protein environment on the charge distribution over the ligand and their interactions with the surrounding water molecules,

The docking technique requires three dimensional structures of both ligand and protein. In some cases the experimentally determined structure will not be available for the docking process; in such cases closely related 3-D protein homologue is designed. Homology modelling (HM) or sequence threading techniques were used to generate models of protein structure but the structures created through HM are not as good as experimentally developed structures. (Ojanen et al, 2004)

Molecular docking solved through two problems, the search algorithm and scoring functions. The search algorithm creates an optimum number of configurations that includes the binding modes determined experimentally. These configurations were evaluated using scoring functions to distinguish the experimental binding modes from all other modes explored through search algorithm.


The searching algorithms are used for the optimization of molecular geometrics (Kaapro 2004) the commonly used were:

Molecular dynamics

Monte carlo methods

Genetic algorithms

Fragment- based methods

Point complementary methods

Distance geometry methods

Tabu searches

Systemic searches

Molecular dynamics (MD):

In this the enzymes or protein is kept rigid, and the ligand move freely to explore its conformational space. The conformations generated are then docked into the protein and a molecular dynamic simulation consisting of a simulated annealing protocol is performed. Less molecular dynamic energy minimization steps takes place using simulated annealing and the energy generated from molecular dynamics runs are used for ranking the overall scoring. Finding out the global minimum energy of a docked complex is difficult by using molecular dynamics. (Gasteiger, 1980)

Monte Carlo methods (MCM):

This method generates configuration of system by making random changes in position of the species present together with their orientation and conformation. Monte Carlo simulation comprises of first equilibration phase followed by production phase. During equilibration appropriate thermodynamics and structural quantities such as mean square displacements, order parameters are monitored, until they acquire stable values.MC simulation is applied to atomic system, because it is necessary to consider only the translational degrees of freedom (Brooks, 1985). In case of rigid non-spherical molecules, the molecules must be translated and its orientation with respect to coordinate axes must be changed. For flexible molecules Monte Carlo simulation are often difficult to perform. One of the method utilizing Monte Carlo simulation is simulated annealing method (Metropolis, 1953), which is a global optimization technique. It explores various states of a configuration space by generating small random changes in the current state and then accepting or rejecting each new state. Programs using MC methods are AutoDock, ProDock, ICM, MCDOCK, Dock Vision, QXP and Affinity.

Genetic algorithm (GA):

Genetic algorithms as global optimizers can be grouped with simplex and stochastic methods. Subset of the force field, the van der Waals, electrostatic, torsional, and constraint energy terms, were used by the fitness function and the energy of the important atoms in the super molecule were calculated.van der Waals energy term is important, the remaining are optional.

The genetic terminologies are stored in the databases in such a way that genetic algorithm borrow methodology and terminology from biological evolution. It is an iterative process in which the most-fit members of a population will have the best chance of propagating themselves into future generations. This directs the process, which gives GA a performance advantage over other global optimization methods. Successive generations can be created through Generational and Steady state GA. The GA starts off with a random population (each value in every chromosome is set to a random number). Genetic operations (cross over & mutation) are then applied iteratively to the population. Each of the genetic operations takes information from parent chromosomes and assembles this information in child chromosomes. The child chromosome then replaces the worst members of the population. The selection of parent chromosome is biased towards those of high fitness, i.e. a 'fit' chromosome is more likely to be a parent than an 'unfit' one (Kothekar, 2005).

Fragment based methods:

In this ligand is divided into fragments, then fragment portions are used for docking. Those divided fragments again linked together and once again performed for docking. The importance of functional groups in the ligand should be known, so it is easy to choose the fragments essential for these methods. The fragment selection should be in such a way that it should possess dominant interactions with the receptor (Kaapro, 2005). Programs utilizing fragment based methods are FlexX and DOCK

Point complementary method:

This method is based on evaluation of shape and chemical complementarity between interacting ligands and receptors. (Essex, 2002)

Distance geometry methods:

When different structural information is expressed as intra- or intermolecular distances, it is possible in distance geometry formalism which allows these distances to be assembled and 3-D structures consistent with them to be calculated. Program utilizing distance geometry method in docking problem is DockIt.

Tabu searches:

The above methods are based on stochastic process, in which new states are randomly generated from an initial state (current solution). These new solutions are then scored and ranked in ascending order. The new states are then scored and then ranked in ascending order. Best new solution is then chosen as the current new solution and the same process is then repeated again. To avoid loops and ensure diversity of the current solution a Tabu list is used. This list acts as a memory. It contains information about previous current solution and a new solution is rejected if it reminds a previous solution too much. For e.g. docking algorithm using Tabu search is PRO_LEADS.

Systematic searches:

In this all molecules are assumed to be rigid and the interaction energy is evaluated from a force field model. Constraints and restraints can be used to reduce the dimensionality of the problem. The bond length and bond angles can be constrained by using SHAKE algorithm (Karplus, 1983). In SHAKE method for conserving the constraints, after each minimization step constraints are satisfied by adding the displacement vectors to the position vectors for the particle, which results from the unconstrained minimization.

Minimum potential energy would occur in any system under condition of low kinetic energy. Optimization procedure necessitates search of the combination of these variables that gives lowest energy (global minima) or the most stable structure. The systematic search method does not use internal potential. The bond lengths and bond angles are held fixed. The conformational space is scanned with the given mesh size (grid search method) and boundary conditions.

For many atom molecules, the number of degrees of freedom is large. It is therefore necessary to restrict the number of variables. This can be done by keeping the bond lengths and bond angles fixed (rigid geometry approach), and vary only the torsional angles (torsional space minimization). The simplest way is to vary two torsional angles at a time and plot two dimensional isoenergy contour maps or conformational maps (Ramachandran et al, 1963), and these plots were known as Ramachandran plot.

Using these plots, it is possible to list out the minima (combination of torsional angles) and generate geometries for each combination. The same procedure can be repeated for the next pair of torsional angles, using these geometries and it can be extended to couple of torsional angles.


Currently using Docking methods utilize the scoring functions to know the rank of particular conformation of protein -ligand after the completion of docking program. Scoring performed as,

Full scoring function to rank a protein-ligand conformation

System is modified by search algorithm after full scoring

(Applying the same scoring function again)

Rank the new structure.

Scoring function used commonly:

1. Force field methods

2. Empirical free energy scoring functions

3. Knowledge- based potential of mean force. The present thesis utilizes AutoDock4.2 in which force field methods and their models are utilized.


Geometry of molecule can be approximated effectively from the inclusion of all interacting forces. Bonded interactions are represented by spring forces, and non-bonded interactions as van der Waals interaction (via, experimental observations). Optimization of energy minimum gives the geometry of the ligand and its interaction with the target.

Total energy = set of potential energy functions

Total energy minimum lacks exact energy, providing only potential energy function , some other parameters which hides in the role of creating energy maximum is the torsional free energy(geometry). In addition to this, atom types and atom charges is needed. So in order to assign all these and bring out the global minimum the following parameters are required which collectively had known as force fields. They are

1. Potential energy functions

2. Parameters for function terms

3 .Atom types & atom charges

4. Atom-typing, parameter generation, and functional form assigning rules.

The table quoted below is an example of parameters (values highlighted) obtained through force field used in AutoDock 4.2 for the optimization of free energy (global minima).

DOCKED: USER DPF = kaempferol.dpf


DOCKED: USER Estimated Free Energy of Binding = -6.90 kcal/mol [=(1)+(2)+(3)-(4)]

DOCKED: USER Estimated Inhibition Constant, Ki = 8.78 uM


DOCKED: USER (1) Final Intermolecular Energy = -8.39 kcal/mol

DOCKED: USER vdW + Hbond + desolv Energy = -8.07 kcal/mol

DOCKED: USER Electrostatic Energy = -0.32 kcal/mol

DOCKED: USER (2) Final Total Internal Energy = -0.36 kcal/mol

DOCKED: USER (3) Torsional Free Energy = +1.49 kcal/mol

DOCKED: USER (4) Unbound System's Energy [=(2)] = -0.36 kcal/mol


Table: An example of parameters (values highlighted) obtained through force field used in

AutoDock 4.2 for the optimization of free energy (global minima).

Force field models are used to generate accurate predictions to difficult problems by interpolating and extrapolating from relatively simple experimental set of molecules. Examples for force field models:

Classical force field model:

"Assisted Model Building with Energy Refinement" - AMBER (Weiner et al ,1984)

"Chemistry at Harvard Macromolecules mechanics"- CHARMm (Brooks et al,1983)

"Consistent Valence Force Field"- CVFF (Hagler,1979)

Second generation force field:

"Consistent Force Field" -CFF (Warshel et al,1970)

"Condensed phase Optimized Molecular Potentials for Atomistic Simulation Studies" -COMPASS (Karplus,1970)

Generalized force field models:

"Extensible Systematic Force Field"- ESFF

"Universal Force Field" -UFF

The molecular geometrics and optimization for the global minimum has its implications in molecular modelling and docking softwares.



AutoDock (versions 3.0, 4.0, 4.2.)















AutoDock 4.2:

They utilize Monte Carlo simulated annealing and Lamarckian genetic algorithm (LGA) to create a set of possible conformations. LGA is used as a global optimizer and energy minimization as a local search method. For the evaluation of possible orientations, AMBER force field model in conjunction with free energy scoring function is used.

Versions of AutoDock: The auto dock is developed by the Scripps research institute; the current version is AutoDock 4.2 has all packages of 3.0, & 4.0, where the mode is changeable according to the availability.

Steps involved in AutoDock calculations:

Coordinate files preparation

Atomic affinities (Auto Grid) calculation

Docking of ligands with protein

Analysis of results

Theory involved in AutoDock:

Semi empirical free energy force field is used to evaluate conformations during docking. The ligand and protein stay in an unbound conformation. Then binding is evaluated in two steps by force field.

Intra molecular energetics estimation:

Force field evaluates intra-molecular energetics during the transition from their unbounded states to the conformation of both ligand and protein in to the form of bound state.

Inter molecular energetics estimation:

Force field evaluates inter-molecular energetics of combining the ligand (L) & protein (P) in their bound conformation.

Fig: Energetics between ligand and protein

Six pair-wise evaluations (V) and conformation entropy lost upon binding (ΔS conf) is calculated by:

ΔG= (VbL-L - VubL-L) + (VbP-P - VubP-P) + (VbP-L - VubP-L +ΔSconf )

Where, ΔG=change in free energy.

The pair-wise energetic terms (V) includes evaluation for dispersion/repulsion, hydrogen bonding, electrostatics, and desolvation.

It is expressed as,

Where, W=weighting constants,

C = A maximal well depth of 5kcal/mol at 1.9Å for hydrogen bonds with oxygen and nitrogen

D = A maximal well depth of 1kcal/mol at 2.5 Å for hydrogen bonds with sulphur.

E (t) = directionality based on the angle't' from ideal H-bonding geometry.

Where S= Salvation parameter; v= volume of atoms surrounding a given atom; σ = distance weighing factor with value of 3.5 Å.

Fig: Viewing Grids in AutoDockTools

Fig: Graph of Auto Dock Potentials

The dispersion/repulsion potential is for interaction between two carbon atoms. The hydrogen bond potential which extends down to a minimum about 2 kcal/mol is shown for an oxygen-hydrogen interaction. The electrostatic potential is shown for interaction of two oppositely charged atoms with a full atomic charge. The desolvation potential is shown for a carbon atom, with approximately 10 atoms displacing water at each distance.


X-ray crystallography

Structure-based drug design

Lead optimization

Virtual screening (HTS)

Combinatorial library design

Protein-protein docking

Chemical mechanism studies