03. Biology 101

Let's look in room, other way around.

To all my Computer Science friends, I am going to try to explain what we are trying to achieve by this project without using any biological jargon. However, you are expected to have a basic idea of the following:

1. proteins, proteomics, amino acids.

2. genes, genomics, genetics.

3. dna, rna, replication, transcription, reverse transcription.

4. homology modelling, protein threading, gene threading, multiple sequence alignment.

Knowledge about the following is optional, but helpful:

1. cells, tissues, nucleus, ribosomes, mitochondria, mitochondrial dna, cell wall, cell membrane, membrane proteins.

2. nf-kb, pellino proteins,

Knowledge about the workings of the following software would help you get up and running in no time:

1. clustal, clustal-x/w/o

2. CN3D

3. pymol

4. ugene

5. modeller

6. hmmer

7. ncbi-blast

Histology and Anatomy Basics:

https://en.wikipedia.org/wiki/Lymph_node

https://en.wikipedia.org/wiki/B-cell_receptor

https://en.wikipedia.org/wiki/Antibody

https://en.wikipedia.org/wiki/Receptor_(biochemistry)

https://en.wikipedia.org/wiki/Transmembrane_protein

https://en.wikipedia.org/wiki/Cell_membrane

https://en.wikipedia.org/wiki/Stromal_cell

https://en.wikipedia.org/wiki/Epithelium

https://en.wikipedia.org/wiki/B_cell

https://en.wikipedia.org/wiki/V(D)J_recombination

https://en.wikipedia.org/wiki/T_cell

https://en.wikipedia.org/wiki/T_cell_receptor

https://en.wikipedia.org/wiki/Recombination-activating_gene

https://en.wikipedia.org/wiki/Natural_killer_T_cell

https://en.wikipedia.org/wiki/Plasma_cell

https://en.wikipedia.org/wiki/Memory_B_cell

https://en.wikipedia.org/wiki/Apoptosis

https://en.wikipedia.org/wiki/Programmed_cell_death

Biochemistry Basics:

https://en.wikipedia.org/wiki/Amine

https://en.wikipedia.org/wiki/Carboxylic_acid

https://en.wikipedia.org/wiki/Glycine

https://en.wikipedia.org/wiki/Thiol

https://en.wikipedia.org/wiki/Cysteine

https://en.wikipedia.org/wiki/Adenosine_triphosphate

https://en.wikipedia.org/wiki/HECT_domain

https://en.wikipedia.org/wiki/SCF_complex

https://en.wikipedia.org/wiki/F-box_protein

https://en.wikipedia.org/wiki/MicroRNA

https://en.wikipedia.org/wiki/Gene_silencing

https://en.wikipedia.org/wiki/RNA_interference

https://en.wikipedia.org/wiki/Skp1

https://en.wikipedia.org/wiki/Cullin

https://en.wikipedia.org/wiki/RBX1

https://en.wikipedia.org/wiki/Signal_transduction

https://en.wikipedia.org/wiki/Caspase

Genomics and Protemics:

https://en.wikipedia.org/wiki/Protein%E2%80%93protein_interaction

https://en.wikipedia.org/wiki/Protein_folding

https://en.wikipedia.org/wiki/NF-%CE%BAB

https://en.wikipedia.org/wiki/Ubiquitin#Ubiquitination_.28ubiquitylation.29

https://en.wikipedia.org/wiki/Proteasome

https://en.wikipedia.org/wiki/Leucine-rich_repeat

https://en.wikipedia.org/wiki/WD40_repeat

https://en.wikipedia.org/wiki/DNA_repair

https://en.wikipedia.org/wiki/Translation_(biology)

https://en.wikipedia.org/wiki/Post-translational_modification

https://en.wikipedia.org/wiki/Cytokine

https://en.wikipedia.org/wiki/NFKB1

https://en.wikipedia.org/wiki/NFKB2

https://en.wikipedia.org/wiki/RELA

https://en.wikipedia.org/wiki/RELB

https://en.wikipedia.org/wiki/Tumor_necrosis_factor_alpha

https://en.wikipedia.org/wiki/IL1B

https://en.wikipedia.org/wiki/RANK

https://en.wikipedia.org/wiki/IKK2

https://en.wikipedia.org/wiki/IRAK1

https://en.wikipedia.org/wiki/Tumor_necrosis_factor_receptor

https://en.wikipedia.org/wiki/Toll-like_receptor

https://en.wikipedia.org/wiki/Ubiquitin_ligase

https://en.wikipedia.org/wiki/Ubiquitin-conjugating_enzyme

https://en.wikipedia.org/wiki/Isopeptide_bond

https://en.wikipedia.org/wiki/N-terminus

https://en.wikipedia.org/wiki/Ubiquitin_B

https://en.wikipedia.org/wiki/Ubiquitin_C

https://en.wikipedia.org/wiki/Ubiquitin-activating_enzyme

https://en.wikipedia.org/wiki/Ubiquitin-conjugating_enzyme

https://en.wikipedia.org/wiki/Ubiquitin_ligase

https://en.wikipedia.org/wiki/Ubiquitin_A-52_residue_ribosomal_protein_fusion_product_1

https://en.wikipedia.org/wiki/RPS27A

https://en.wikipedia.org/wiki/Endocytosis

https://en.wikipedia.org/wiki/Interleukin_6

https://en.wikipedia.org/wiki/Interleukin_8

https://en.wikipedia.org/wiki/Ubiquitin_A-52_residue_ribosomal_protein_fusion_product_1

https://en.wikipedia.org/wiki/RPS27A

https://en.wikipedia.org/wiki/Anaphase-promoting_complex

https://en.wikipedia.org/wiki/MAP3K14

https://en.wikipedia.org/wiki/Bcl-2

https://en.wikipedia.org/wiki/TRAF1

https://en.wikipedia.org/wiki/TRAF2

https://en.wikipedia.org/wiki/Phosphoinositide_3-kinase

https://en.wikipedia.org/wiki/Protein_kinase_B

https://en.wikipedia.org/wiki/Ras_subfamily

https://en.wikipedia.org/wiki/Mitogen-activated_protein_kinase_kinase

https://en.wikipedia.org/wiki/Extracellular_signal-regulated_kinases

https://en.wikipedia.org/wiki/Amyloid_precursor_protein

https://en.wikipedia.org/wiki/Amyloid_beta

https://en.wikipedia.org/wiki/Tau_protein

https://en.wikipedia.org/wiki/Chromosome_21_(human)

https://en.wikipedia.org/wiki/Down_syndrome

Neurosciences Basics:

https://en.wikipedia.org/wiki/Neurotrophin

https://en.wikipedia.org/wiki/Neuron

https://en.wikipedia.org/wiki/Glutamate_receptor

https://en.wikipedia.org/wiki/Synapse

https://en.wikipedia.org/wiki/Sensory_neuron

https://en.wikipedia.org/wiki/Axon_hillock

https://en.wikipedia.org/wiki/Voltage-gated_ion_channel

https://en.wikipedia.org/wiki/Ion_transporter

https://en.wikipedia.org/wiki/Glutamate_receptor

Breast Cancer Basics:

https://en.wikipedia.org/wiki/Cancer

https://en.wikipedia.org/wiki/Breast_cancer

https://en.wikipedia.org/wiki/Breast_cancer_screening

https://en.wikipedia.org/wiki/Preventive_mastectomy

https://en.wikipedia.org/wiki/Ionizing_radiation

https://en.wikipedia.org/wiki/Hormone_replacement_therapy

https://en.wikipedia.org/wiki/Ductal_carcinoma_in_situ

https://en.wikipedia.org/wiki/Tamoxifen

https://en.wikipedia.org/wiki/Raloxifene

https://en.wikipedia.org/wiki/Hormonal_therapy_(oncology)

Parkinson's Disease Basics:

https://en.wikipedia.org/wiki/Parkinson%27s_disease

https://en.wikipedia.org/wiki/Dopamine_agonist

https://en.wikipedia.org/wiki/Amantadine

https://en.wikipedia.org/wiki/Anticholinergic

https://en.wikipedia.org/wiki/Acetylcholinesterase_inhibitor

https://en.wikipedia.org/wiki/Quetiapine

https://en.wikipedia.org/wiki/Aspirin

https://en.wikipedia.org/wiki/Nonsteroidal_anti-inflammatory_drug

https://en.wikipedia.org/wiki/Meta-analysis

Alzheimer's Disease Basics:

https://en.wikipedia.org/wiki/Alzheimer%27s_disease

https://en.wikipedia.org/wiki/Hyperphosphorylation

https://en.wikipedia.org/wiki/Senile_plaques

Targeted Therapy Basics:

https://en.wikipedia.org/wiki/Targeted_therapy

https://en.wikipedia.org/wiki/Proteasome_inhibitor

https://en.wikipedia.org/wiki/Imatinib

https://en.wikipedia.org/wiki/Dermatofibrosarcoma_protuberans

https://en.wikipedia.org/wiki/Gefitinib

https://en.wikipedia.org/wiki/Erlotinib

https://en.wikipedia.org/wiki/Sorafenib

https://en.wikipedia.org/wiki/Sunitinib

https://en.wikipedia.org/wiki/Dasatinib

https://en.wikipedia.org/wiki/Lapatinib

https://en.wikipedia.org/wiki/Nilotinib

https://en.wikipedia.org/wiki/Bortezomib

Basic Bioinformatics:

https://www.youtube.com/watch?v=eZfyWdHnzR0

https://www.youtube.com/watch?v=eF40NMhpuGc

https://www.youtube.com/watch?v=uDp7LGZJn6Q

https://sites.google.com/site/structurepredictiontools/Home/tutorials-3/biology101

Homology modelling Basics:

https://www.youtube.com/watch?v=meNEUTn9Atg&list=PLC482A348BCB4401A

https://www.youtube.com/watch?v=rTNvPDUFmoQ&index=3&list=PLC482A348BCB4401A

https://www.youtube.com/watch?v=TTtrk0Ue-Cg&index=4&list=PLC482A348BCB4401A

https://www.youtube.com/watch?v=3BTRVtsmXpw&list=PLC482A348BCB4401A&index=5

https://www.youtube.com/watch?v=8O3qEtH76OA&index=6&list=PLC482A348BCB4401A

https://www.youtube.com/watch?v=hd2YaygJC-w&index=9&list=PLC482A348BCB4401A

https://www.youtube.com/watch?v=TZM8EzHW6MA&index=7&list=PLC482A348BCB4401A

Advanced References:

https://sites.google.com/site/structurepredictiontools/Home/abstract/citations/references

https://sites.google.com/site/structurepredictiontools/Home/abstract/citations/untitledpost

Follow the instructions atSystem Setup and System Config to set up your workstation.

I have tried to explain the stuff in a FAQ fashion, so that if anybody has further questions, they can give me a shout at Discussions page and I'll add the question with its answer here...

Q1. what is our topic of interest.

Our topic of interest is Proteins. I plan to include genes as well, at a later time, but for now, the solution would provide a platform for fellow researcher to perform their dry lab research as well as showcase their activity.

Q2. what we are building.

We are building a website portal (think facebook/linkedin/Yahoo). the way these sites try to give out different services from a single platform. Google follows a different philosophy. It wants to keep its platform clean and modular, so has different websites for different purposes. (Think on the lines, if facebook and facebook messenger were hosted on two different sites, just like google plus and gmail). So, in our scenario, we are building a website portal that will provide toolsets to researchers who aim towards using a computational workbench for designing various drug formulations using the various online databases.

Q3. yeah right! so... what are WE building. English please...

yeah.. so, we are building a platform that will help you perform homology modelling/protein threading.

To put it simply, let us say you want to buy a shoe for your nephew. but neither of you know his correct size. So you ask him to draw the outline of his foot on a paper and email you the picture of the impression. Then you take a printout of that impression and try to put different shoes on the impression, the one that fits, is your nephew's size. (The whole process might turn out to be easier than it sounds). So, what did you do here. you took an imprint of a known target (your nephew's foot) and used that as a template (an imprint of the foot) to find the right object (the shoe) that fits the target.

That's what we do in homology modelling. we take a target, usually, a pathogen or the tissue that is attacked and then take a template, that is to say, a similar tissue with known diagnosis, and then try to model a cure based on that template. let us say you are targeting the common cold virus. if you look at the virus structure http://www.ncbi.nlm.nih.gov/Structure/mmdb/mmdbsrv.cgi?uid=12345, (a detailed analysis of the structure goes here: http://www.ncbi.nlm.nih.gov/pubmed/2156077) you'll find that the virus is spherical with some spikes on its surface. These spikes are the 'receptors' that attach themselves to various tissues inside the human body for multiplication, and in turn, give us the cold. The cold virus starts out the attack by attaching itself over the soft palate, just between the nose and the throat. Then, with favorable environmental condition (that is to say a drop in room temperature), it moves down to the pharynx > larynx > trachea, and subsequently to the bronchi in the lungs (which is the point when you start coughing out sputum). During its journey, it breaks down the cells and makes our immune system of the naso-pharyngeal tract, thus making it vulnerable to other diseases like, asthma and flu. So, we can have any of these as the target, i.e., the cold virus itself, or any of its infecting tissues. Each of these tissues to which the virus attaches itself, have specific spots to which the virus receptors bind. So, it we engineer a drug that mimics the virus attaching receptor, the drug would competitively bind to those sites, displacing the virus, thus inhibiting its impact. On the other hand, if the drug binds to the virus receptors itself, even then, the receptors are engaged and cannot bind to the target tissues, thus avoid catching cold. In another approach, the formulation can be engineered in a way that disintegrates the virus, in the process killing it. In real life, however, things are not really that simple. to take a dig at the real life complications that the cold virus presents, take a look at http://news.wisc.edu/22246 A detailed discussion of a possible solution is provided at http://www.rcsb.org/pdb/101/motm.do?momID=20 Most of the issues come up due to selective attachment of its receptors. discussed in detail at http://www.ncbi.nlm.nih.gov/pubmed/23297216 Also, the upper palate has only been recently discovered as being the site of initiation of infection.

However, at times, things tend to get a bit complicated if the complete template structure is not available. So, upto now, we had a known target structure (be it the cold virus or the naso-pharyngeal tract). What if the target structure is not known. Imagine the situation like this. Your nephew starts to take an impression of his foot but his clumsy hands missed out bits and parts of the feet where maneuvering around was a little tricky. Also, the pencil nib broke as he was reaching the end. but that what he chose to send you (since he was already bored). Now you have an impression of his foot, but that is a bit vague with missing areas and dotted lines that fail to give a complete picture of his foot. But still, you can take the half-impression and then try to complete the broken lines in the form of a complete foot impression based on your observation of a regular kid's foot and then venture out to a shoe store trying to align a shoe that 'kinda' fits. Similarly, in case of proteins, when you do not have a perfect template, you take what you have and venture out to perform protein threading. you take the amino acid sequence of the unknown protein, try to align it with the known structures to get a match. All these known structures are usually archieved by ncbi. after you have got a match, you take the known structure as the template and try to model your own unknown protein sequence based on that template. so coming back to our common cold example, let us say that we do not know how the actual virus looks like. So we take the amino acid sequences of what we know and then try to model it along the repository of all the known structures. Now let us assume, that in our search of the protein sequence similarity, we found the flu virus to be pretty similar to the cold virus. So, we take the flu virus structure, and try to create a cold virus strucuture based on the folds of the consituent amino acids to get a rough idea of how the virus might loook like. Then we perform experiments to confirm our model against actual effects of virus infection.

Q4. Hmm... I think I am getting a grip. Can you give me a real example of what you are going to do?

All right, let us move on to something more challenging - breast cancer. Self renewing breast cancer stem cells are known to be the key actors during tumour malignancy and in treatment resistance and relapse. NF-kB is known to play critical roles in inflammation, immunity and apoptosis avoidance. Constant activation of NF-kB, via both Classical and Alternate pathways, is a common feature found in most breast cancer tumours. This deregulated NF-kB activation results in nuclear localisation of the nuclear factor protein complexes that have transcription ability, viz., p50/RelA and p52/RelB, leading to a disruption in the balance between cell proliferation and apoptosis, that in turn leads the tumour to become cancerous.

Classical Activation Pathway:

The classical pathway is activated by pro-inflammatory cytokines, such as, TNFα or IL-1β. The binding of TNFα to TNFR1 triggers attachment of adaptor proteins, viz., TRADD, RIP and TRAF2 to the membrane. Then, TRAF2 mediates the recruitment of the IκB kinase (IKK) complex, composed of IKKα, IKKβ and NEMO to the TNFR1 signalling complex. The scaffold proteins TAB2 and TAB3 subsequently bind to Lys63-polyubiquitylated substrates, such as receptor-interacting protein (RIP)1, resulting in TAK1 and then IKKβ activation. NEMO actually exerts its essential role in NF-κB activation by integrating upstream IKK-activating signals. Basically whenever, a receptor comes to attach itself to the IKK complex, it does so at the NEMO end or to the I-kappa end that is configured by NEMO. LUBAC, composed of HOIL-1L and HOIP, binds NEMO and conjugates linear chains of ubiquitin on the IKK complex. The ubiquitin-binding motif of NEMO, referred to as the UBAN motif, is required to sense linear chains of ubiquitin. Activation of IKKβ leads to IκBα phosphorylation and polyubiquitylation and its subsequent degradation through the proteasome pathway. Then, the heretodimer p50-p65 binds to specific κB sites and activates a variety of NF-κB target genes coding for pro-inflammatory cytokines (IL-6) and chemokines.

In relation to Breast Cancer:

In case of tumour cell lines on mammary fat pads, NF-kB is mostly activated in ER-/- amd ErbB2+/+ tumours. In these studies, NBD peptide blocked heregulin-mediated NF-kB activation and induced apoptosis prepferentially in proliferating cells. Tumour latency and tumour burden are found to reduced in defined windows during polyoma middle T oncogene (PyVT) tumourigenesis. These findings are in agreement with data showing the requirement of NF-κB for the induction and maintenance of the epithelial-mesenchymal transition (EMT), a process that critically controls breast cancer progression [2,3]. Indeed, the MCF10A immortalized cell line, which is derived from normal mammary epithelial cells, undergoes EMT when overexpressing the NF-κB protein p65.

These data strongly suggest that NF-κB regulates breast tumour progression independently of its effects on mammary development.

Alternate Activation Pathway:

This pathway relies on the recruitment of the heterodimer TRAF2-TRAF3 to the CD40 receptor. TRAF3 is required to connect the E3 ligases c-IAP1/2 to NIK for its activation, that in turn phosphorylates inhibitory p100, whose partial proteolysis leads to generation of p52, that moves into the nucleus as a heterodimer with RelB to regulate the expression of genes involved in lymphoid organogenesis or coding for chemokines (BLC (B lymphocyte chemokine)) or cytokines (BAFF (B-cell activating factor)).

In relation to Breast Cancer:

Increased p52/RelB activity was also observed in mouse mammary tumours induced by 7,12-dimethylbenz(a)anthracene (DMBA). p100/p52 was found to be specifically overexpressed in the mammary epithelium by using the β-lactoglobulin milk protein promoter in mouse models. [4] This mouse model not only showed a delay in mammary development but also a transient reduction in ductal branching during pregnancy. Matrix metalloproteinase (Mmp)-2, Mmp-9 and cyclooxygenase (Cox)-2 turned out to be overexpressed in these transgenic mice. Constitutive p100 over expression causes an aberrant phenotype, as shown by the thickening of primary ducts, loss of epithelial cell organization and small areas of hyperplastic growth. Finally, an increase in p100/p52 expression was also observed in PyVT mice when tumour development is observed. Importantly, no change of nuclear p65 was detected in this mouse model, suggesting that the phenotypeobserved was exclusively the result of a deregulated alternative NF-κB-activating pathway. Interestingly, RelB, that is an integral part of p52/RelB dimer, is required for the maintenance of the mesenchymal phenotype of ERα-negative Hs578T breast cancer cells.

In-vitro studies:

NF-κB appears to be activated during differentiation of the mammary colony-forming cells in which luminal progenitor cells can be found whereas the mammary stem-like basally located cells do not show any marked activity. Self-renewing breast cancer stem cells are the subject of intensive research as key actors responsible for perpetuating tumour existence and for treatment resistance and relapse - both in cases of chemotherapy and radiotherapy. These cells can be isolated by virtue of their expression of the cell surface markers epithelial-specific antigen (ESA) and CD44 and the absence of expression of CD24. Aldehyde dehydrogenase expression has also been used to enrich for tumour-initiating cells. Moreover, the membrane bound receptor tyrosine kinase Her2, which activates NF-kB via the canonical pathway, and is overexpressed in 30% of breast cancers, also critically controls the cancer stem-cell population. This approach was elegant as NF-κB activation through the canonical pathway was only suppressed in mammary epithelial cells but not in inflammatory cells, blood vessels or adipocytes, where this transcription factor

most likely contributes to tumour development. Moreover, NF-κB suppression was inducible to circumvent the requirement of this transcription factor in normal ductal development.

Interestingly, a transient activation of the kinase oncoprotein Src in MCF10A cells results in phenotypic transformation that includes the formation of multiple foci, the ability to form colonies in soft agar and tumours in xenografts as well as mammosphere formation.

For a detailed discussion follow the links:

https://en.wikipedia.org/wiki/Protein_structure_prediction

https://en.wikipedia.org/wiki/Homology_modeling

http://www.proteinstructures.com/Modeling/Modeling/homology-modeling1A.html

http://www.proteinstructures.com/Structure/Structure/proteinstructure-databases2.html

For reference, follow Citations.

For additional references of breast cancer association with nf-kb pathway:

[1] Shostak and Chariot Breast Cancer Research 2011, 13:214, NF-κB, stem cells and breast cancer: the links get stronger

[2] Huber MA, Azoitei N, Baumann B, Grunert S, Sommer A, Pehamberger H, Kraut N, Beug H, Wirth T J Clin Invest 2004, 114:569-581, NF-kappa B is essential for epithelialmesenchymal transition and metastasis in a model of breast cancer progression.

[3] Chua HL, Bhat-Nakshatri P, Clare SE, Morimiya A, Badve S, Nakshatri H, Oncogene 2007, 26:711-724, NF-kappa B represses E-cadherin expression and enhances epithelial to mesenchymal transition of mammary epithelial cells: potential involvement of ZEB-1 and ZEB-2.

[4] Connelly L, Robinson-Benion C, Chont M, Saint-Jean L, Li HJ, Polosukhin VV, Blackwell TS, Yull FE, J Biol Chem 2007, 282:10028-10035, A transgenic model reveals important roles for the NF-kappa B alternative pathway (p100/p52) in mammary development and links to tumorigenesis.