The document discusses structure-based in-silico virtual screening protocols. It describes virtual screening as using computer methods to discover new ligands based on a target protein's biological structure. The main goal is to reduce the enormous chemical space of potential compounds to a manageable number with the highest likelihood of becoming drug candidates. Molecular docking is a key method, involving sampling potential ligand positions in the protein's binding site and scoring the interactions. The document also discusses force field, empirical, and knowledge-based scoring functions used to evaluate docking poses. Applications mentioned include designing Hsp90 inhibitors for cancer treatment and identifying novel BACE1 inhibitors.

1. Prepared by-
Sandipan Choudhury
2nd semester, M.Pharm
STRUCTURE BASED IN-SILICO
VIRTUAL SCREENING
PROTOCOLS

2. In silico: is a word used to mean experimentation
performed by computer and is related to the more
commonly known terms in vivo and in vitro.
Virtual screening: uses computer based methods to
discover new ligand on the bases of biological
structure.
The main goal of the virtual screening is the
reduction of the enormous virtual chemical space of
small organic molecules to synthesize and/or screen
against a specific target protein, to a manageable
number of the compound that inhibit the highest
chance to lead to a drug candidate.

3. VIRTUAL SCREENING IN DRUG
DESIGN

4. VIRTUAL SCREENING PROTOCOLS

5. METHODS OF STRUCTURE BASED
DRUG DESIGN
 Molecular docking:
-Molecular docking helps to predict ligand-based
receptor interaction
-This method studies the binding mode and the position
of the ligand in a protein’s binding site
- Molecular docking has two main phases:
(1) Sampling (2) Scoring

6. 1. Sampling:
 Geometry-based methods: divide the binding cavity and
also the ligand to set of spheres. Then the software
combines position of ligand-spheres and cavity-sphere
 Hash functions: transform information about ligand and
receptor to a hash key. In the second recognition step, hash
keys are matched and best combinations are evaluated

7.  Incremental construction methods: are first algorithms that
respect ligand flexibility. The software divides the ligand
along each rotatable bond. Then the first fragment is
placed and its best pose is the base for addition
 Genetic method: uses principles of evolutionary biology to
locking for the best solution. It starts with zero generation
of randomly created solutions. The next generations are
created as combination of best-evaluated individuals from
parent generation with some impact of random mutations.

8.  Simulated annealing: is a part of molecular dynamic
methods. The system is cooled during the simulation run,
the energy is decreased and system is approaching the
local minimum of energy. Using Monte Carlo algorithm
particularly solves the dependence of the result on a
starting position. It enables to overcome energetic barriers
and to find global energetic minimum.

9. 2. SCORING
 Scoring is sometimes presented as a separate method of
structure-based drug design but it is irreplaceable part of
molecular docking. In the docking approaches, it is the
second phase and it follows the sampling.
 There are three basic scoring methodologies based on
different theories-
1. Force field scoring
2.Emperical scoring functions
3. Knowledge-based scoring functions

10.  Force- field scoring functions:The force-field based
scoring uses classical molecular mechanistic calculations.
All these scoring functions have similar formulas based on
sum of partial energies (bond interactions, van der Waals
interactions, electrostatics interactions, angle bending,
out-of-plane bending, torsion interactions and others)

11. Advantages:
 speed of computation
 strong physical basis and
 good theoretical description.
Disadvantages:
 exclusion of the entropy parameters such as
desolvation energy and restriction of ligand flexibility

12. Emperical scoring functions:
Empirical scoring functions: calculate the binding
energy as a sum of particular increments (e.g. ionic
interactions, hydrogen bonds, π-interactions,
desolvation, lipophilic interactions). Proportional
weight of these increments is defined by their
coefficients.
Values of the coefficients are determined on training
set of protein-ligand complexes using multiple linear
regression

13.  Advantage :
The main advantage of this method is inclusion of
enthalpy and entropy contribution.
 Disadvantage:
Dependance on used training set.

14.  Knowledge-based scoring functions:
The third possibility is using of knowledge-based scoring
functions. They are based on statistical investigation of
protein-ligand complexes. The theory assumes that
frequency of distance of two specific atom types is
proportional to its favour. Partial increment of an atom-
type pair can be calculated as:

15.  where kB is the Boltzmann constant,
 T is the thermodynamic temperature,
 gij is the distribution function for atom-type pair
 ij and r is the distance between atoms i and j

16. Advantage:
This method is relatively fast.
Disadvantage:
Poor physical theoretical-physical basis.

17. APPLICATIONS:
 Structure-based and in silico design of Hsp90
inhibitors:The molecular chaperone Hsp90 is
responsible for activation and stabilization of
several oncoproteins in cancer cells,and has
emerged as an important target in cancer
treatment because of this pivotal role .Interest
have arisen around structure based design of
small molecules aimed at inhibiting the
chaperone activity of Hsp90.
 Hybrid Structure-Based Virtual Screening
Protocol for the identification of Novel BACE1
Inhibitors.

18. Conclusions:
 The choice of a method is highly case dependent and
there is no simple manual describing which method is the
right one. Each method has its advantages or
disadvantages. Combination of two or more computational
methods is usually a favorable tool for drug design
purposes
 It seems that it is possible to use VS methods in design
of new drugs for military purposes including e.g.
acetylcholinesterase or butyrylcholinesterase reactivators
for antidotal treatment. In this case, the use of VS could
help to develop molecules tailor-made for enzyme
structure.

19. As such, a designed highly active reactivator could be
applied for pseudocatalytic scavenging or treatment of
intoxications caused by organophosphorus nerve agents.