Docking is used to predict the binding of two molecules and evaluate their interaction energy. It involves representing molecules, exploring possible configurations, and ranking them by binding energy using a scoring system. There are two main categories: protein-protein docking treats both molecules as rigid, while protein-ligand docking allows flexibility in the ligand. AutoDock software is commonly used for docking via genetic algorithms and other search methods to minimize energy between a protein and ligand. Docking preparation involves adding hydrogens, assigning charges and merging atoms for both molecules. The results can provide insight into protein interactions and rational drug design.
Energy minimization methods - Molecular ModelingChandni Pathak
Methods to minimize the energy of molecules during drug designing - Computational chemistry. According to the PCI syllabus, B.Pharm 8th Sem - Computer-Aided Drug Design (CADD).
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
Energy minimization methods - Molecular ModelingChandni Pathak
Methods to minimize the energy of molecules during drug designing - Computational chemistry. According to the PCI syllabus, B.Pharm 8th Sem - Computer-Aided Drug Design (CADD).
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
Protein docking is used to check the structure, position and orientation of a protein when it interacts with small molecules like ligands. Protein receptor-ligand motifs fit together tightly, and are often referred to as a lock and key mechanism. There are both high specificity and induced fit within these interfaces with specificity increasing with rigidity. The foremost thing that we need to start with a docking search is the sequence of our protein of interest. (Halperin et al., 2002).
Protein-protein interactions occur between two proteins that are similar in size. The interface between the two molecules tends to be flatter and smoother than those in interfaces of these interactions do not have the ability to alter protein-ligand interactions. Protein-protein interactions are usually more rigid, the conformation in order to improve binding and ease movement. (Smith and Sternberg, 2002).
The process of drug development has revolved around a screening approach, as nobody knows which compound or approach could serve as a drug or therapy. Such almost blind screening approach is very time-consuming and laborious. The goal of structure-based drug design is to find chemical structures fitting in the binding pocket of the receptor. Based on the three-dimensional structure of the target protein, it can automatically build ligand molecules within the binding pocket and subsequently screen them (Weil et al., 2004).
A homology model of the housefly voltage-gated sodium channel was developed to predict the location of binding sites for the insecticides fenvalerate, a synthetic pyrethroid, and DDT, an early generation organochlorine. The model successfully addresses the state-dependent affinity of pyrethroid insecticides. (O’Reilly et al., 2006).
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein.
Finding PDB files of molecules, locating binding sites, positioning ligand to a macromolecule, building grid and grid parameter file, performing molecular docking, and analysis of docking results by looking over various energy parameters and uses in drug discovery technology.
PRESENTED BY: HARSHPAL SINGH WAHI, SHIKHA D. POPALI
USEFUL FOR PHARMACY STUDENTS AND ACADEMICS, INDUSTRIALS FOR MOLECULE DEVELOPMENT, MODELING, DRUG DISCOVERY, COMPUTATIONAL TOOLS, MOLECULAR DOCKING ITS TYPES, FACTORS AFFECTING, DIFFERENT STAGES, QSAR ADVANTAGES, NEED
Protein docking is used to check the structure, position and orientation of a protein when it interacts with small molecules like ligands. Protein receptor-ligand motifs fit together tightly, and are often referred to as a lock and key mechanism. There are both high specificity and induced fit within these interfaces with specificity increasing with rigidity. The foremost thing that we need to start with a docking search is the sequence of our protein of interest. (Halperin et al., 2002).
Protein-protein interactions occur between two proteins that are similar in size. The interface between the two molecules tends to be flatter and smoother than those in interfaces of these interactions do not have the ability to alter protein-ligand interactions. Protein-protein interactions are usually more rigid, the conformation in order to improve binding and ease movement. (Smith and Sternberg, 2002).
The process of drug development has revolved around a screening approach, as nobody knows which compound or approach could serve as a drug or therapy. Such almost blind screening approach is very time-consuming and laborious. The goal of structure-based drug design is to find chemical structures fitting in the binding pocket of the receptor. Based on the three-dimensional structure of the target protein, it can automatically build ligand molecules within the binding pocket and subsequently screen them (Weil et al., 2004).
A homology model of the housefly voltage-gated sodium channel was developed to predict the location of binding sites for the insecticides fenvalerate, a synthetic pyrethroid, and DDT, an early generation organochlorine. The model successfully addresses the state-dependent affinity of pyrethroid insecticides. (O’Reilly et al., 2006).
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein.
Finding PDB files of molecules, locating binding sites, positioning ligand to a macromolecule, building grid and grid parameter file, performing molecular docking, and analysis of docking results by looking over various energy parameters and uses in drug discovery technology.
PRESENTED BY: HARSHPAL SINGH WAHI, SHIKHA D. POPALI
USEFUL FOR PHARMACY STUDENTS AND ACADEMICS, INDUSTRIALS FOR MOLECULE DEVELOPMENT, MODELING, DRUG DISCOVERY, COMPUTATIONAL TOOLS, MOLECULAR DOCKING ITS TYPES, FACTORS AFFECTING, DIFFERENT STAGES, QSAR ADVANTAGES, NEED
A QSAR is a mathematical relationship between a biological activity of a molecular system and its geometric and chemical characteristics.
QSAR attempts to find consistent relationship between biological activity and molecular properties, so that these “rules” can be used to evaluate the activity of new compounds.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Cancer cell metabolism: special Reference to Lactate Pathway
Docking
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DOCKING
HYPERCHEM
2. DOCKING
Docking is finding the binding geometry of two
interacting molecules with known structures.
In other words, docking can be defined as the
prediction of the optimal physical configuration and
energy between two molecules.
3. The two molecules receptor and ligand can be:
- two proteins
- a protein and a drug
- a nucleic acid and a drug
The docking problem optimizes:
1.binding between two molecules such that
their orientation maximizes the interaction.
2. Evaluates the total energy of interactions
such that for the best binding configuration,
the binding energy is maximum.
3. The resultant structural changes brought
about the interaction.
4. CATEGORIES OF DOCKING
Protein Protein Docking:
- Both molecules are rigid.
-Interaction produces no changes in
conformation.
-Similar to lock and key model.
Protein Ligand Docking:
-Ligand is flexible but the receptor protein is
rigid.
-Interaction produces conformational
changes in the ligand.
6. Docking uses “search and score” method
It involves:
Finding useful ways of representing the molecules and
molecular properties.
Exploration of the configuration spaces available for
interaction between ligand and receptor.
Evaluate and rank configurations using a scoring
system, in this case the binding energy
7. Rigid Vs Flexible Docking
Rigid body docking:
No modification in bond angles, lengths and torsion
angles of the components.
Flexible docking:
Takes in to the conformational changes.
8. Importance of Docking
It is extreme relevance in cellular biology, where
function is accomplished by proteins interacting with
themselves and with other molecular components.
It is the key to rational drug design.
Virtual screening.
Pose prediction.
9. AUTODOCK SOFTWARE
Developed by AJ Olson’s group in 1990.
AutoDock uses free energy of the docking molecules using 3D potential-
grids
Uses heuristic search to minimize the energy.
Search Algorithms used:
Simulated Annealing
Genetic Algorithm
Lamarckian GA (GA+LS hybrid)
10. Algorithms overview
Stimulated Annealing:
-Based on temperature effects
- Start with high temperature and global search
-Lower temperatures local search
Genetic Algorithm:
- Charles Darwin theories of Evolution
Genotype→Phenotype
Lamarckin Algorithm:
- Jean-Baptiste De Lamarck
Phenotype→Genotype
12. AutoDock uses grid-
based docking
Ligand-protein
interaction energies
are pre-calculated
and then used as a
look-up table during
simulation
Grid maps are
constructed based on
atoms of interest in
ligand (here CANOSH)
Docking Preparation – Grid
13. Steps involved:
Start with crystal coordinates of target receptor.
Generate molecular surface for receptor.
Generate spheres to fill the active site of the
receptor. The spheres become potential locations for
ligand atoms.
Sphere centers are then matched to the ligand
atoms, to determine possible orientations for the
ligand.
Find the top scoring orientation.
14. Example:
Target receptor - HIV 1 protease
Active site - Aspartyl groups
Ligand:
Protease inhibitors – ritonavir, lopinavir.
Nelfinavir.
15. HYPERCHEM
Hyperchem is a powerful program that enables us to
do high quality molecular calculations.
16. Steps involved
Draw simple and complex molecular structures, including
crystals, carbohydrates, peptides and nucleic acid
sequences
Display these structures in various different renderings
including ball and stick and space filling structures
Apply simple valence rules to generate idealized geometries
Perform molecular mechanics energy minimization
calculations to produce more realistic geometries
17. Visualize the results of the MO calculations with 2-D and
3-D renderings of individual orbitals, electron densities,
total charge and spin density and electrostatic potential
Calculate and visualize vibrational spectra
Calculate electronic spectra
Perform molecular dynamics simulations
Incorporate the results of orbital and vibrational spectral
calculations into interactive web pages
18.
19.
20.
21. Example entry
Open the periodic table and select carbon. Go to the display
menu and under labels select symbol. Now place six carbon
atoms on the screen and connect them in a ring. Double clicking
one of the bonds in the ring will convert the ring to an aromatic
ring.
Go to the build menu and select add hydrogen and then
model build. If you choose just the former, you still have a
planar arrangement of carbons, now each with one
hydrogen. If you double click the bagel, you will generate a
structure based on simple valence rules. If you choose the
combined action above, hydrogens are added and the
model is built at the same time.
