The document discusses various topics related to drug design and discovery including structure-based drug design, quantitative structure-activity relationships (QSAR), molecular docking, and de novo drug design. It provides details on the drug discovery process, strategies for structure-based design including pharmacophore identification and docking simulations, factors that govern drug design such as physicochemical properties, and methods for QSAR model development, validation, and applications in drug design.
SAR versus QSAR, History and development of QSAR, Types of physicochemical
parameters, experimental and theoretical approaches for the determination of
physicochemical parameters such as Partition coefficient, Hammet’s substituent
constant and Taft’s steric constant. Hansch analysis, Free Wilson analysis, 3D-QSAR
approaches like COMFA and COMSIA.
What is QSAR?, introduction to 3D QSAR, CoMFA, CoMSIA, Case Study on CoMFA contour maps analysis and CoMSIA interactive forces between ligand and receptor, various Statistical techniques involved in QSAR
SAR versus QSAR, History and development of QSAR, Types of physicochemical
parameters, experimental and theoretical approaches for the determination of
physicochemical parameters such as Partition coefficient, Hammet’s substituent
constant and Taft’s steric constant. Hansch analysis, Free Wilson analysis, 3D-QSAR
approaches like COMFA and COMSIA.
What is QSAR?, introduction to 3D QSAR, CoMFA, CoMSIA, Case Study on CoMFA contour maps analysis and CoMSIA interactive forces between ligand and receptor, various Statistical techniques involved in QSAR
PHARMACOHORE MAPPING AND VIRTUAL SCRRENING FOR RESEARCH DEPARTMENTShikha Popali
THE PHARMACOPHORE MAPPING AND VIRTUAL SCRRENING , THESE PRESENTATION INCLUDES THE DEATIL ACCOUNT ON PHARMACOPHORE, MAPPING, ITS IDENTIFIATION FEATURES, ITS CONFORMATIONAL SEARCH, INSILICO DRUG DESIGN, VIRTUAL SCREENING, PHARMACOPHORE BASED SCREENING
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)AkshayYadav176
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)
Concept of pharmacophore, Pharmacophore mapping, Identification of pharmacophore features and pharmacophore modeling, Conformation search used in pharmacophore mapping, Virtual screening.
The screening of chemical libraries with traditional methods, such as high-throughput screening (HTS), is expensive and time consuming. Quantitative structure–activity relation (QSAR) modeling is an alternative method that can assist in the selection of lead molecules by using the information from
reference active and inactive compounds. This approach requires good molecular descriptors that are representative of the molecular features responsible for the relevant molecular activity.
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Cadd and molecular modeling for M.PharmShikha Popali
THE CADD IS FOR THE DRUG DEVELOPMENT THE DIFFERENT STRATEGIES ARE MENTIONED LIKE QSAR MOLECULAR DOCKING, THE DIFFERENT DIMNSIONAL FORMS OF QSAR , THE ADVANCE SAR of it.
ADMET properties prediction using AI will accelerate the process of drug discovery.
This slide mostly focuses on using graph-based deep learning techniques to predict drug properties.
PHARMACOHORE MAPPING AND VIRTUAL SCRRENING FOR RESEARCH DEPARTMENTShikha Popali
THE PHARMACOPHORE MAPPING AND VIRTUAL SCRRENING , THESE PRESENTATION INCLUDES THE DEATIL ACCOUNT ON PHARMACOPHORE, MAPPING, ITS IDENTIFIATION FEATURES, ITS CONFORMATIONAL SEARCH, INSILICO DRUG DESIGN, VIRTUAL SCREENING, PHARMACOPHORE BASED SCREENING
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)AkshayYadav176
Pharmacophore Mapping and Virtual Screening (Computer aided Drug design)
Concept of pharmacophore, Pharmacophore mapping, Identification of pharmacophore features and pharmacophore modeling, Conformation search used in pharmacophore mapping, Virtual screening.
The screening of chemical libraries with traditional methods, such as high-throughput screening (HTS), is expensive and time consuming. Quantitative structure–activity relation (QSAR) modeling is an alternative method that can assist in the selection of lead molecules by using the information from
reference active and inactive compounds. This approach requires good molecular descriptors that are representative of the molecular features responsible for the relevant molecular activity.
THE ENERGY MINIMIZATION, FOR THE STUDENTS OF M.PHARM, B.PHARM AND OTHERS USEFUL FOR ACADEMIC TOO. THE PRESENT DATA IS MOST USEFUL FOR PHARMACY PURPOSE.
Cadd and molecular modeling for M.PharmShikha Popali
THE CADD IS FOR THE DRUG DEVELOPMENT THE DIFFERENT STRATEGIES ARE MENTIONED LIKE QSAR MOLECULAR DOCKING, THE DIFFERENT DIMNSIONAL FORMS OF QSAR , THE ADVANCE SAR of it.
ADMET properties prediction using AI will accelerate the process of drug discovery.
This slide mostly focuses on using graph-based deep learning techniques to predict drug properties.
Introduction of QSAR, Steps involved in QSAR, Hansch Analysis, Free Wilson Analysis, Mixed Approach method, Advantage,Disadvantage and Application of QSAR.
IOSR Journal of Applied Chemistry (IOSR-JAC) is an open access international journal that provides rapid publication (within a month) of articles in all areas of applied chemistry and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Chemical Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Insilico methods for design of novel inhibitors of Human leukocyte elastaseJayashankar Lakshmanan
Oral contributed paper “Insilico methods for design of novel inhibitors of Human leukocyte elastase” in the International conference on Systemics, Cybernetics and Informatics-2006
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
Computational modelling of drug disposition lalitajoshi9
computational modelling of drug disposition is the integral part of computer aided drug design. different kinds of tools being used in the prediction of drug disposition in human body. This topic in the CADD explains the details about the drug disposition, active transporters and tools.
THE DRUG DESIGN AND DEVELOPMENT BASED ON DRUG DISCOVERY ,HERE ITS NEED RATIONALE ARE EXPLAINED ALSO QSAR, MOLECULAR DOCKING ITS HISTORY NEED, STRUCTURE BASED DRUG DESIGN IN EASY WAY WE HAVE MENTIONED. THIS WILL MAKE READERS EASY TO COLLECT DATA AT A PLACE ALL OVER THIS IS FOR PHARMA STUDENTS, ACADEMICS, PROFESSIONL AND OST USEFUL FOR RESEARCHERS.
THANK YOU
HOPE YOU WILL LIKE AND SHARE
Acute scrotum is a general term referring to an emergency condition affecting the contents or the wall of the scrotum.
There are a number of conditions that present acutely, predominantly with pain and/or swelling
A careful and detailed history and examination, and in some cases, investigations allow differentiation between these diagnoses. A prompt diagnosis is essential as the patient may require urgent surgical intervention
Testicular torsion refers to twisting of the spermatic cord, causing ischaemia of the testicle.
Testicular torsion results from inadequate fixation of the testis to the tunica vaginalis producing ischemia from reduced arterial inflow and venous outflow obstruction.
The prevalence of testicular torsion in adult patients hospitalized with acute scrotal pain is approximately 25 to 50 percent
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
2. Contents:
Process of Drug Discovery
Drug Designing
Strategies of structure based drug design
Concept of Docking
QSAR and Drug Designing
QSAR Steps
Descriptors used in QSAR
De novo drug design
QSAR model Validation and statistical analysis
2D-QSAR and 3D-QSAR methods
Applications of QSAR
2
3. Process of Drug Discovery
The process of modern drug discovery starts with the identification of disease and
therapeutic target of interest , include phases , methodologies ,lead identification ,
characterization , formulation , pharmacological studies , PK profile , safety and
clinical studies.
General steps:
Target Selection or discovery
Lead discovery : Lead generation and Optimization
In vitro Studies
Pre-clinical and clinical studies.
A drug can be discovered from following approaches:
From natural sources
Screening
Chemical modification of known drugs
Observation of side effects
Rational
Serendipity
3
4. Drug Designing
Also referred as Rational drug design.
Inventive process of finding new medications or interventions based on the
knowledge of biological target.
More focussed approach that uses structural information about the drug receptor
or targets on one of its ligands as a basis to design , identify or create leads.
Types of Structure based drug design:
Receptor based drug design
Ligand based drug design
Factors Governing Drug design:
Relationships between physico-chemical features and biological properties that
need to be established retrospectively.
Quantitative structure-activity relationships (QSARs).
Disease etiologies and various biochemical processes involved.
4
5. Strategies Of Structure Based Drug Design
5
Pharmacophore
Identification
Pharmacophore
Modification
Fit for the
receptor
Potential Drug
Yes
No
Active site Identification
Ligand fragments growing
Fit for the
receptor
Complete
Growing
Potential Drug
Change Fragment
No
Yes
Yes
No
6. Concept of Docking
Docking refers to the ability to position a ligand in the active or a
designated site of a protein and calculate the specific binding affinities
and conformations at a receptor site .
Attempts to find the “best” matching between two molecules.
It includes finding the Right Key for the Lock .
Software for Docking: DOCK, AUTODOCK,AUTODOCK Vina.
6
https://en.wikipedia.org/wiki/Docking_(molecular)
7. Main tasks of docking tools:
Sampling of conformational (ligand) space.
Scoring protein-ligand complexes
Molecular Docking involves:
Identification of the ligand’s correct binding geometry (pose) in the
binding site (Binding Mode)
Molecular Docking Prediction of the binding affinity (Scoring
Function)
7
https://www.intechopen.com/books/protein-engineering-technology-and-application/protein-protein-and-protein-ligand-docking
8. QSAR and Drug designing
Attempts to correlate structural, chemical, and physical properties with
biological activity by providing scientific credible tools for predicting and
classifying biological activities of untested chemicals.
Involves the derivation of mathematical formula which relates the biological
activities of a group of compounds to their measurable physicochemical
parameters.
Depends on the theory of Lipinski Rule of Five: Drug Likeliness
Screening: Method for evaluating the drug-like properties of a compound.
Rule of five (RO5) is a rule of thumb to evaluate drug likeness or determine
if a chemical compound with a certain pharmacological or biological activity
has properties that would make it a active drug .
QSAR’s general mathematical form is represented by the following equation:
Biological Activity = f (Physicochemical Property)
-Activity is expressed as log(1/c). C is the minimum concentration required to
cause a defined biological response.
8
9. For a compound i , the linear equation that relates
molecular properties, x1, x2 .., xn to the desired activity, y
is :
yi= xi1b1+xi2b2+………….+xinbn+ei
Expressing the previous equation in a compact form for
the general case of n selected descriptors, the QSAR
equation results into:
yi=∑nxibi+ei
Where, b’s are linear slope that express the correlation of
particular molecular property xi with the activity yi of the
compound i ; and ei is a constant.
9
10. QSAR steps:
General stages of QSAR model Development:
1. Preparing molecules for QSAR study.
2. Collection, design and calculation of values for all descriptors for all ligands
in training sets.
3. Selecting descriptors that can properly relate chemical structure to biological
activities.
4. Creating model using training set : Quantitative description of structural
variation and choice of the QSAR model .
5. Applying statistical methods that correlate changes in structure with changes
in biological activity.
6. Synthesis and Biological testing .
7. Data analysis and Validation of the QSAR models (Internal and External).
8. Interpretation of results for the proposal of new compounds : Based on
statistical experimental design and multivariate data analysis.
Obtaining a good quality QSAR model with the ability to predict activity of
a chemical outside the training set depends upon many factors in the
approach and execution of each individual steps.
10
11. Descriptors/Parameters used in QSAR
Measure of the potential contribution of its group to a particular property of
the parent drug.
Numerical representation of chemical information encoded within a
molecular structure via mathematical procedure.
The information content of structure descriptors depends on two major
factors:
(1) The molecular representation of compounds.
(2) The algorithm which is used for the calculation of the descriptor.
The three major types of parameters initially suggested are :
(1) Hydrophobic : Partition coefficient (log P) ; Hansch’s substitution
constant (π )
(2) Electronic : Hammett constant ( σ, σ +, σ ) ; Taft’s inductive (polar)
constant ( σ*)
(3) Steric : Taft’s steric parameter (Es) ; Molar volume (MV)
11
12. Various types of Descriptors:
Constitutional descriptors
Geometrical descriptors
Charge descriptors
Topological descriptors
Polarizable parameters
Molecular descriptors
Connectivity indices
Functional group counts
Information indices
12
13. Lipophilicity or Hydrophobicity
It determines the
ability of the drug
molecule to cross the
biological membrane.
More the lipophilicity,
more will be the
biological activity.
Also important in
determining the
receptor interactions.
Partition Coefficient
The hydrophobic character of a
drug can be measured
experimentally by testing the
drug’s relative distribution in n-
octanol /water system.
This relative distribution is termed
as partition coefficient.
P = [drug]in n -octanol
[drug]in aqueous system
Hydrophobic compounds have
high P value whereas hydrophilic
compounds have a low P value.
13
14. Typically over a small range of log P , a straight line is
obtained :
log1/C= k1(log P)+k2
If graph is extended to very high log P values, then we get
a parabolic curve:
log1/C=-k1(log P)^2+k2logP+k3
14
15. Substituent hydrophobicity
constant
It is a measure of how hydrophobic a
substituent is in relative to hydrogen
which is calculated experimentally
for a standard compound such as
benzene with or without substituent
X.
π x= log Px-log PH
Where π x is the hydrophobicity
constant, Px is the partition coefficient
for the standard compound with the
substituent , PH is the partition
coefficient of the standard compound.
Steric Factors
Steric substitution constant : It is
a measure of the bulkiness of the
group it represents and it effects
on the closeness of contact
between the drug and receptor
site. It is much difficult to
quantify.
Namely :
1. Taft’s steric factor (Es)
2. Molar refractivity (MR)
3. Verloop sterimol parameter
15
16. Electronic Effects
Useful to measure the electronic effect of a substituent
Given by Hammett substitution constant: Measure of electron
withdrawing or electron donating ability of a substituent and is
determined by measuring the dissociation of a series of
substituted benzoic acid compared to the undissociated benzoic
acid itself.
Hammett constant takes into account both resonance and
inductive effects; thus, the value depends on whether the
substituent is para or meta substituted.
-ortho position not measured due to steric effects.
σx= log (Kx/K-benzoic acid)
Where σx is the Hammett constant , Kx is the dissociation
constant of substituted benzoic acid.
16
17. Hansch Analysis
Proposed that drug action could
be divided into 2 stages:
1) Transport of drug to site &
2) Binding of drug to site
Each of these stages depend
upon the physical and chemical
properties of the drug.
It attempts to mathematically
relate drug activity to
measurable chemical property.
Log 1/C = k1(partition
parameter) + k2(electronic
parameter)+ k3(steric
parameter) + k4
Free Wilson Approach
This method is based on the
assumption that the introduction of
a particular substituent at a
particular molecular position ,
always leads to a quantitatively
similar effect on biological potency
of the whole molecules and
expressed by the equation as
BA= μ+Σaj
For a series of chemical analogs ,
the biological activity is assumed to
be the sum of intrinsic activity of
the skeleton (μ) and the additive
contribution of the substituents (aj).
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18. De novo drug design
De novo means starting from the beginning.
Offers a broader exploration of chemical space and therefore makes it
possible to identify novel ligand scaffolds.
Design of novel chemical structures capable of interacting receptors
with known structures.
Approach to build a customized Ligand for a given receptor, involving
ligand optimization.
Ligand optimization can be done by analyzing protein active site
properties that could be probable area of contact by the ligand using
molecular modeling tools.
Types of de novo drug design :
1. Manual design
2. Automated design : Revolves around the scoring functions used to
estimate binding affinities .It is prone to generating structures which
are either difficult or impossible to synthesize.
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19. 19
De novo design Classes of design methods:
1. Methods that analyze active site
2. Methods that dock whole molecule
3. Methods that connect molecular fragments or atoms together to produce a
ligand:
Site- point connection methods
Fragment connection methods
Sequential build up methods
Random connection methods
Some de novo design methods are :
DOCK,AUTODOCK,CAVEAT,GRID,LUDI,SPROUT
http://www.medicilon.com/de-novo-drug-design/
20. Methods for validating
QSAR models:
Internal validation :
1. Least Squares Fit
2. Fit of the Model
3. Cross-validation
4. Bootstrapping
5. Randomization test (Y-
Scrambling model)
External validation
Statistical analysis methods for
predicting QSAR model :
Regression Analysis
Principle Component Analysis
Partial Least square Analysis
Clustered Analysis:
1. Hierchial Clustering
2. K-nearest neighboring method of
clustering
3. Artificial neuronal network
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21. 2D-QSAR Methods:
1. Free Energy Models : Hansch
Analysis
2. Mathematical Models :Free
Wilson Analysis, Fujita Ban
Modification
3. Other Statistical methods :
Discriminant Analysis ,
Principle component Analysis ,
Cluster Analysis , Combine
Multivariate Analysis , Factor
Analysis
4. Pattern Recognition
5. Topological Methods
6. Quantum Mechanical Method
3D - QSAR Methods:
1. Molecular shape analysis
(MSA)
2. Molecular topological
difference (MTD)
3. Comparative molecular
movement analysis (COMMA)
4. Hypothetical Active Site
Lattice (HASL)
5. Self Organizing Molecular
Field Analysis (SOMFA)
6. Comparative Molecular Field
Analysis (COMFA)
7. Comparative Molecular
Similarity Indices (COMSIA)
21
22. Applications of QSAR
Rational identification of new leads with
pharmacological or biocidal activity.
Identification of hazardous compounds at early
stages of product development.
Designing out of toxicity and side effects in
new compounds.
Prediction of variety of physio-chemical
properties of molecules.
22
23. References:
Medicinal Chemistry by Ashutosh Kar,Fourth Edition.
QSAR: Hansch Analysis and Related Approaches by Hugo
kubiany,VCH 1993.
A Review on Computational Methods in Developing Quantitative
Structure-Activity Relationship (QSAR);International Journal of Drug
Design and Discovery :Volume 3 • Issue 3 • July – September 2012.
815-836.
Validation of QSAR Models - Strategies and Importance ; International
Journal of Drug Design and Discovery: Volume 2, Issue 3 ,July –
September 2011. 511-519
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