Computer aided drug design (CADD) uses computer modeling to help design and discover new drug molecules. It involves designing molecules that are complementary in shape and charge to bind to a biomolecular target like a protein. This can help drugs activate or inhibit the target to produce therapeutic effects. CADD is not a direct route to new drugs but provides information to guide and coordinate drug discovery experiments in a more efficient manner. It is hoped CADD can help save time and money in the drug development process.
Are you using phenotypic screening as a way to discover new drugs or would you like to know more about this approach?
• Outline the steps to take when building this approach in Reaxys.
• Demonstrate how pharmacological targets involved in cell based assay can be easily identified in Reaxys with their mechanisms of action
Are you using phenotypic screening as a way to discover new drugs or would you like to know more about this approach?
• Outline the steps to take when building this approach in Reaxys.
• Demonstrate how pharmacological targets involved in cell based assay can be easily identified in Reaxys with their mechanisms of action
Drug Discovery: Target Identification and Validation Lindsay Rosenwald
For many years, pharmaceutical research companies have developed new drugs using a standard drug discovery process. The process usually begins with extensive medical research about a particular disease, which provides researchers with a better understanding of the disease and how it affects the body. The next step of the drug discovery process typically involves target identification and target validation.
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
This document presents an overview of the AI applications in life sciences. The presentation highlights various steps in drug development and AI applications. Also, discusses Alzheimer’s disease and obstacles to develop drugs. Finally, presents details of AI in target identification for AD.
This disclaimer informs readers know that the views, thoughts, and opinions expressed in the presentation belong solely to the author, and not to the author’s employer, organization, committee or other group or individual.
Speaker: Wendy Hill, Gap Strategies. Part of the MaRS Best Practices Series.This session, led by seasoned industry experts, will explore how to effectively set up your pre-clinical POC studies, address pre-clinical safety requirements and issues, and give you an overview of the manufacturing standards required for Phase I studies
More information: http://www.marsdd.com/Events/Event-Calendar/Best-Practices-Series/ind-05132008.html
Drug Discovery: Target Identification and Validation Lindsay Rosenwald
For many years, pharmaceutical research companies have developed new drugs using a standard drug discovery process. The process usually begins with extensive medical research about a particular disease, which provides researchers with a better understanding of the disease and how it affects the body. The next step of the drug discovery process typically involves target identification and target validation.
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
This document presents an overview of the AI applications in life sciences. The presentation highlights various steps in drug development and AI applications. Also, discusses Alzheimer’s disease and obstacles to develop drugs. Finally, presents details of AI in target identification for AD.
This disclaimer informs readers know that the views, thoughts, and opinions expressed in the presentation belong solely to the author, and not to the author’s employer, organization, committee or other group or individual.
Speaker: Wendy Hill, Gap Strategies. Part of the MaRS Best Practices Series.This session, led by seasoned industry experts, will explore how to effectively set up your pre-clinical POC studies, address pre-clinical safety requirements and issues, and give you an overview of the manufacturing standards required for Phase I studies
More information: http://www.marsdd.com/Events/Event-Calendar/Best-Practices-Series/ind-05132008.html
INTRODUCTION
A PERFECT THERAPEUTIC DRUG
DRUG DISCOVERY- HISTORY
MODERN DRUG DISCOVERY
BIOINFORATICS IN DRUG DISCOVERY
DRUG DISCOVERY BASED ON BIOINFORMATIC TOOLS
BIOINFORMATICS IN COMPUTER-AIDED DRUG DISCOVERY
ECONOMICS OF DRUG DISCOVERY
CONCLUSION
REFERENCES
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!
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
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.
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfJim Jacob Roy
Cardiac conduction defects can occur due to various causes.
Atrioventricular conduction blocks ( AV blocks ) are classified into 3 types.
This document describes the acute management of AV block.
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.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
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Title: Sense of Smell
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 primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
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.
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.
2. DRUG DESIGN
It is the inventive process of finding new
medications based on the knowledge of a biological target.
The drug is most commonly an organic small molecule that
activates or inhibits the function of a biomolecule such as
a protein, which in turn results in a therapeutic benefit to
the patient.
In the most basic sense, drug design involves the design of
small molecules that are complementary in shape and charge
to the biomolecular target with which they interact and
therefore will bind to it.
3. TERMS TO BE KNOWN
LIGAND
PHARMACOPHORE
MOLECULAR DOCKING
LEAD IDENTIFICATION
4. Drug Discovery & Development
Identify disease
Isolate protein
involved in
disease (2-5 years)
Find a drug effective
against disease protein
(2-5 years)
Preclinical testing
(1-3 years)
Formulation &
Scale-up
Human clinical trials
(2-10 years)
FDA approval
(2-3 years)
5. modern drug discovery process
Target
identification
Target
validation
Lead
identification
Lead
optimization
Preclinical
phase
Drug
discovery
2-5 years
• Drug discovery is an expensive process involving high R & D cost and extensive
clinical testing.
• A typical development time is estimated to be 10-15 years.
6-9 years
6. Design, development and commercialization of a
drug is a tedious, time-consuming and cost-intensive process
Timeline in a drug discovery project.
7. Medicinal chemists today are facing a serious challenge because of the
increased cost and enormous amount of time taken to discover a new drug,
and also because of fierce competition amongst different drug companies.
INTRODUCTION
It needs approximately 300 to 350 million US $ and 12-13 years
for a drug to reach the market.
Considering both the potential benefits to human health and the enormous
costs in time and money of drug discovery.
technique that increases the efficiency of any stage of the drug
discovery enterprise will be highly prized.
8. Computer-aided drug design (CADD) is one of these tools which can be used
to increase the efficiency of the drug discovery process. CADD cannot, however,
maximize its utility in isolation and will not do so. Rather, it can form a
valuable partnership with experiment by providing estimates when experiments
are difficult, expensive, or impossible, and by coordinating the experimental data
available.
A close coupling between computational chemists and experimentalists allows
information to flow immediately and directly between the two. This helps CADD
chemists to better understand the details of the problem and to refine their
approach. It also provides valuable information for the experimentalist, it helps
to guide further experimental planning and potentially makes this process more
efficient
CADD is, however, not a direct route to new drugs, but it provides a somewhat
more detailed map to the goal. The hope is that by providing bit and pieces of
information, and by helping to coordinate the information, CADD will help to
save days and money for drug discovery projects
9. • Random, trial and error
• Time consuming
• Very expensive
• Extremely low yield ( 1 in 100,000)
• Target specific and structure-based
• Fast and automatic
• Very low cost
• High success rate
Computer-based Design
Traditional Drug Screening
10. Identify target disease
Study Interesting Compounds
Detection the Molecular Bases for Disease
Rational Drug Design Techniques
Refinement of Compounds
Quantitative Structure Activity Relationships (QSAR)
Solubility of Molecule
Drug Testing
11. Identify Target Disease
know all about the disease
A real drug needs to be developed
drug must influence the target protein
INSILICO methods
12. 1.One needs to identify and study the lead
compounds that have some activity against a disease.
2. These compounds provide a starting point for refinement of the
chemical structures.
3. This process can be enhanced using software tools that explore
related compounds (bioisosteres) to the lead candidate.
OpenEye’s WABE is one such tool.
4. Lead optimization tools such as WABE offer a rational approach
to drug design that can reduce the time and expense of
searching for related compounds.
Study Interesting Compounds
13. 1. Traditionally, the primary way of determining what compounds
would be tested computationally was provided by the researchers'
understanding of molecular interactions.
2. A second method is the brute force testing of large numbers of
compounds from a database of available structures.
Detect the Molecular Bases for Disease
known actives structures founddatabase
14. Rational drug design techniques:-
1.These techniques attempt to reproduce the researchers' understanding
of how to choose likely compounds built into a software package that is
capable of modeling a very large number of compounds in an automated
way.
2. Many different algorithms have been used for this type of testing,
many of which were adapted from artificial intelligence applications.
3.The complexity of biological systems makes it very difficult to
determine the structures of large biomolecules.
4. Ideally experimentally determined (x-ray or NMR) structure is
desired, but biomolecules are very difficult to crystallize
15. Refinement of compounds
Once you got a number of lead compounds have been found,
computational and laboratory techniques have been very successful in
refining the molecular structures to give a greater drug activity and
fewer side effects.
Done both in the laboratory and computationally by examining the
molecular structures to determine which aspects are responsible for
both the drug activity and the side effects.
16. Quantitative Structure Activity Relationships
(QSAR):-
1.Computational technique should be used to detect the functional
group in your compound in order to refine your drug.
2. QSAR consists of computing every possible number that can
describe a molecule then doing an enormous curve fit to find out
which aspects of the molecule correlate well with the drug activity or
side effect severity.
3. This information can then be used to suggest new chemical
modifications for synthesis and testing
17. Solubility of Molecule:-
1. One need to check whether the target molecule is water soluble or
readily soluble in fatty tissue will affect what part of the body it becomes
concentrated in.
2. The ability to get a drug to the correct part of the body is an
important factor in its potency.
3. Ideally there is a continual exchange of information between the
researchers doing QSAR studies, synthesis and testing.
4. These techniques are frequently used and often very successful since
they do not rely on knowing the biological basis of the disease which can
be very difficult to determine.
18. 1. Once a drug has been shown to be effective by an initial assay
technique, much more testing must be done before it can be given to
human patients.
2. Animal testing is the primary type of testing at this stage. Eventually,
the compounds, which are deemed suitable at this stage, are sent on to
clinical trials.
3. In the clinical trials, additional side effects may be found and human
dosages are determined.
Drug Testing
19. Identify disease
Isolate protein
Find drug
Preclinical testing
GENOMICS, PROTEOMICS & BIOPHARM.
HIGH THROUGHPUT SCREENING
MOLECULAR MODELING
VIRTUAL SCREENING
COMBINATORIAL CHEMISTRY
IN VITRO & IN SILICO ADME MODELS
Potentially producing many more targets
and “personalized” targets
Screening up to 100,000 compounds a
day for activity against a target protein
Using a computer to
predict activity
Rapidly producing vast numbers
of compounds
Computer graphics & models help improve activity
Tissue and computer models begin to replace animal testing
20.
21. Impact of new technology on drug discovery
• The last few years have seen a number of
“revolutionary” new technologies:
– Gene chips, genomics.
– Bioinformatics & Molecular biology
– protein structures
– High-throughput screening & assays
– Docking
– Combinatorial chemistry
– In-vitro ADME testing
• How do we make it all work for us?
22. Information generated at different points in the Drug Design process
Gene chip experiments
Project selection decisions
Assay protocols
Series selection decisions
SAR studies
Protein structures
Combinatorial Expts.
Pharmacophores
ADME studies
Toxicology studies
Scaleup reactions
Lead cmpd decisions
Clinical Trials data
Doctor/patient studies
Marketing, surveys, etc
23. For workstations, minicomputers, and supercomputers (SGI, Sun,
Cray, etc.)
AMBER — Peter Kollman and coworkers, UCSF
Computer assisted model building, energy minimization,
molecular dynamics, and free energy perturbation calculations.
Midas Plus — UCSF Computer Graphics Laboratory
CHARMM — Martin Karplus and cowrokers, Harvard
QUANTA/CHARMm — Molecular Simulations Inc. (MSI)
molecular/drug design, QSAR, quantum chemistry,
X-ray & NMR data analysis
Insight/DISCOVER — Biosym, Inc.
Now MSI and Biosym became Accelrys Inc.
SYBYL — Tripos, Inc.
ECEPP — (Harold Scheraga and coworkers, Cornell)
MM3 — (Norman Allinger and coworkers, Georgia)
Software for General Purpose Molecular Modeling
34. hydrogen bonds
(directed interactions
π interactions
hydrophobic
contacts
explicitly placed
water molecules
ligand and protein
flexibility
Terms Contributing to Ligand Binding
35.
36.
37. Pharmaceutical Research Software
Spartan is a powerful tool for computer aided drug design. The easy-
to-use interface delivers a new suite of molecular modelling features
as well as quantum calculation tools for chemists working in drug
discovery.
38. 1. SVMProt: Protein function prediction software
http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi
2. INVDOCK: Drug target prediction software
3. MoViES: Molecular vibrations evaluation server
http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl
Software developed
39. PHARMACO informatics database developed
1.Therapeutic target database
http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp
2. Drug adverse reaction target database
http://xin.cz3.nus.edu.sg/group/drt/dart.asp
3. Drug ADME associated protein database
http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp
4. Kinetic data of biomolecular interactions database
http://xin.cz3.nus.edu.sg/group/kdbi.asp
5. Computed ligand binding energy database
http://xin.cz3.nus.edu.sg/group/CLiBE/CLiBE.asp