computational prediction of binding affinity between psychotropic drugs and neural cytoskeleton...

Computational Prediction of Binding Affinity between Psychotropic Drugs and Neural

Cytoskeleton Elements

R. PIZZI1, T. RUTIGLIANO1, A. FERRAROTTI 2 and M. PREGNOLATO2

1Computer Science Department, University of Milan2Department of Drug Sciences, University of Pavia

8th International Conference on APPLIED MATHEMATICS, SIMULATION, MODELLING. Florence, 2014

• Tubulin is a globular protein and the fundamental component of microtubules.

• It is composed by two similar units, alpha and beta tubulin, bound very tightly together

• .

INTRO

INTRO

• Microtubules are cylindrical polymers composed by aligned tubulin dimers, alpha and beta-tubulins, that polymerize in a helix that creates the microtubule.


• Microtubules (MTs) constitute the cytoskeleton of all the eukaryotic cells and are supposed to be involved in many key cellular functions.

• MTs are claimed to possess peculiar functional properties that are under study.

INTRO

Properties of microtubules

• In the last decades many studies have been carried out that claim peculiar MTs quantum properties

• Some hints and many theories seem to suggest that MTs may be involved in the consciuosness process.

• Sir Roger Penrose, one of the major physicists of our age, maintains that inside MTs quantum superposition is sustained at room temperature, allowing a quantum computation that gives rise to consciousness.

• Many scientists (e.g. Hameroff, Tuszinsky) support this or other similar theories.

Properties of microtubules

• The present research follows other studies of our group that with direct in-vitro experiments and structural bioinformatics simulations have shown peculiar behavior of MTs

• By means of specific physical measures of resonance and birefringence, that we also replicated in silico, we assessed a structural sensitivity of MTs in presence of electromagnetic field.


INTRO Project background

tubulin, despite its symmetric structure, seems to have different internal forces that tend to resist a dynamic stabilization. However, in presence of electric field, although it tends to squash, it does not show any particular reaction.

MTs react sharply to electromagnetic fields both in the experimental tests and in the simulations, showing to move and orient themselves along the field.

The different behavior between microtubules and tubulin suggests that the tubular antenna-like shape of MTs is

responsible of their peculiar properties

INTRO


- Our previous researches show that the peculiar properties of MTs could be due to their biological structure.

- The present research aims to investigate with structural bioinformatics simulations the different behavior of tubulin and MTs in presence of consciousness-altering drugs

- We meant to search for hints of a biological functional relationship between MTs and consciousness.

A deeper study of psychoactive drugs and their binding to tubulin and MTs structures may help us to better understand interactions and mechanisms.

We examined:- A depressant drug (heroin)- A stimulant drug (cocaine)- A hallucinogen drug (LSD)

INTRO Our aim


Psychoactive drugs. Courtesy of Derek Snider.

INTRO Our aim


Psychoactive drugs. Courtesy of Derek Snider.

To explore differences in binding with psychoactive drugs we performed:

1. Molecular Dynamics (MD) to carry out conformation

optimization in water medium of cocaine, heroin, LSD 2. Docking procedures between structures (MTs and tubulin) and

above mentioned drugs


INTRO Our aim

Material and Methods I step: MD

Molecular Dynamics (MD):

• Configurations are generated by application of the Newton equations of motion to all atoms simultaneously over a small time step to determine the new atomic positions and velocities

• The force field is formed by the sum of molecular bonds and electrostatic forces

• The total energy determines the evolution of this dynamical systems


MD:We used the Ascalaph Designer software

This software combines Molecular Dynamics simulation in liquid phase (with explicit water molecules) with a graphical interface



MD: Ascalaph Designer

• flexible tool with many possible parameterizations for the force fields

• various dynamical optimization techniques• graphical interface with many interactive methods for the

development of molecular models• quantum computation• ab initio computational chemistry



M D on ligands (psychoactive drugs):

1. The construction of the chemical structures was performed using the Ascalaph Designer ab-initio Free Drawing

2. The next step was the optimization, i.e. the energy minimization, of all the built chemical structures (energy minimization algorithm: conjugate gradient method, stop conditions: gradient value = 0.001 and iteration number = 100)



• Most biological functions are mediated by interactions between proteins and ligands

• The bond with a ligand can induce a conformational change that influences the activity or accessibility of other binding domains

• We studied interactions between MTs, tubulin and drugs using HEX Protein Docking, a molecular docking software that allows both calculation and 3D visualization

Source: http://hex.loria.fr/

Material and Methods II step: docking


• Docking algorithm:

• The algorithm determines the geometric and electrostatic complementarity between two molecular structures

• It projects the molecule in a 3D grid, performing a distinction between surface and interior atoms. Then it evaluates the overlapping degree of the molecular penetration relative to all the possible orientations of the molecule ligand around the macromolecolar structure.



• HEX algorithm:it uses an FFT evolution called SPF (Spherical Polar Fourier): Each molecule is modelled in three dimensions using parametric

functions that encode both the surface spatial potential distribution and their spherical polar coordinates



The procedure searches for the best docking solution on the basis of a rigid 6-dimensional search on a rotational grid.

HEX Clustering Docking Results

• It uses a clustering algorithm to group spatially similar docking orientations:

• Each docking solution is first ordered by energy, and the lowest energy solution is considered the seed orientation for the first cluster.

• Then the list of possible orientation is ordered on the basis of the intermolecular RMS distance between alpha-carbon chains

• The process is repeated starting from the next lowest unassigned orientation, until all solutions have been assigned to a cluster.

Material and methodsDocking tool



Material and Methods models

TUBULIN (PDB 1JFF)MICROTUBULES (NANO-D

research group at INRIA Grenoble-Rhone-Alpes )


Material and Methods models

LIGANDS:

cocaine LSD

heroin

• As control ligand we used taxol, a toxic substance that increases microtubule polymerization by binding to the filament and stabilizing it.

• Taxol lacks in psychotropic characteristics, and is typically associated with Tubulin in the databanks

• Ligands (cocaine, LSD , heroin, taxol) were subjected to docking using HEX.


Results

Results

Taxol in tubulin Taxol in MT

Taxol positions:


Results

C.LSD ligand in MTs

A.Cocaine ligand in MTs

B.Heroin ligand in MTs

Alpha helix

Beta sheet

MTs


Results

Alpha helix

Beta sheet

• MT the two ligands heroin e cocaine are close to a kind of niche (perhaps the access way).

• cocaine, compared to heroin, seems to penetrate further into the structure

•heroin assumes a more superficial position, moving in the direction of an alpha helix.


Results

Alpha helix

Beta sheet

•heroin and cocain are positioned both at Chain A.

•The third ligand, LSD, shows a completely different position with respect to the other two ligands

•LSD assumes a superficial position in contact with the two Chains and an alpha helix

Results

C.LSD ligand in Tubulin

B.Heroin ligand in Tubulin

A.Cocaine ligand in Tubulin


Alpha helix

Beta sheet

Tubulin

Results


Alpha helix

Beta sheet

Results

•cocaine and heroin show similar behavior:•they don’t appear to come in contact with any secondary structure, •they are present in a niche and positioned between chain A and B. •LSD takes a position similar to the other ligands, •LSD it is even more superficial and is only present at the level of one chain.

Different observations have been made for tubulin:

Conclusions

• We conclude that cocaine and heroin have similar localization in the tubulin structure, but not identical localization in MTs

• LSD, however, assumes a completely different position compared to other ligands in both tubulin and in MT structures

• The difference of the LSD behavior is evident in MT structure.

• The control structure, Taxol, has a position completely different from the psychoactive substances, both in MT and in tubulin, suggesting that psychoactive substances have a different and specific role


Conclusions• As already amply demonstrated in our previous works, the MT

tubular structure shows to have an important functional role that cannot be found in the only tubulin structure.

• Mainstream science is used to consider other structures as targets for psychotrope substances

• In our study MTs show to bind the drugs more deeply than tubulin

• It can be hypothesized that MT are not just storage proteins but play an active role in the binding of the psychotrope drugs

Conclusions• In the future we aim to widen the study with other similar

substances

• If their binding sites should reveal to be similar to those found for heroin, cocain, LSD, our hypothesis of an active role of MTs in the cosciousness process.

• Studies on complete sets of MTs with many copies of ligands could be realized by adopting in the future powerful PC clusters or a Supercomputer facility.

• A deeper study of consciousness-altering drugs and their binding to tubulin and MTs may help us to understand the complex biological interface between conscious and unconscious state

• The worldwide research on the functional role of MTs is indeed still open and evolving.

Conclusions


References• R. Pizzi , S. Fiorentini , G. Strini , M. Pregnolato, Exploring structural and

dynamical properties of Microtubules by means of artificial neural networks. In: Complexity Science, Living Systems and Reflexing Interfaces: New Models and Perspectives, IGI Global New York, 2012, pp. 78-91

• R. Pizzi , G. Strini , S. Fiorentini, V. Pappalardo and M. Pregnolato, Evidences of new biophysical properties of Microtubules, In: Focus on artificial neural networks, Nova Science, 2010, pp. 191-207.

• R. Pizzi , S. Fiorentini (2009). Artificial Neural Networks Identify the Dynamic Organization of Microtubules and Tubulin Subjected to Electromagnetic Field. In: Recent Advances in Applied Computer Science. Genova, 17-19 Oct 2009, p. 103-106, ISBN: 978-960-474-127-4