BioCode: Learn Bioinformatics

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Updated: May 14, 2026 at 8:35 PM

BioCode: Learn Bioinformatics

A platform that provides you basics to advanced knowledge and skills of bioinformatics so you can analyze real-life datasets with ease.

@biocodeltd is a dedicated channel for platform and advanced with regular updates in Coding and Programming

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

Feel free to get in touch if you're working on single cell genomics projects.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

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On the left, simulation data tracking stability, and on the right, the 3D structure of the Protein-Polyphenol complex we're studying via molecular docking with Desmond.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

Polyphenols are natural compounds found in plants, and many are actively being investigated by scientists for their potential anti-cancer properties.

Some well-known examples include:

-Curcumin: Found in turmeric, studied for its anti-inflammatory and antioxidant effects.
-Resveratrol: Found in grapes, red wine, and berries, researched for its potential to interfere with cancer cell growth and survival pathways.
-EGCG (Epigallocatechin gallate): The major polyphenol in green tea, investigated for inhibiting tumor growth and angiogenesis (blood vessel formation).
-Quercetin: Found in onions, apples, berries, and capers, studied for inducing apoptosis (programmed cell death) in cancer cells.
-Genistein: Found in soy products, researched for its effects on hormone-related cancers and cell signaling.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

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Single-cell RNA-sequencing has opened groundbreaking new opportunities in health and life sciences, especially cancer and complex diseases.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

It lets us see what's happening in individual cells, vital for understanding complex diseases.

Why single-cell analysis helps find biomarkers:

-Spot rare cells: Finds important cells hidden in the noise.
-Cell-specific insights: Shows how disease affects different cell types uniquely.
-Find disease subtypes: Helps group patients better based on their cells.
-Track cell changes: Sees how cells evolve during illness or treatment.
-Map local environments: Crucial for understanding complex areas like tumors.

This tech speeds up biomarker discovery for better diagnostics and treatments! #SingleCell #Biomarkers

#ComplexDiseases

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

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Protein-protein docking is a computational technique used to predict the 3D structure of protein complexes. It plays a crucial role in drug discovery by identifying potential drug targets and understanding protein interactions. This information can be used to design drugs that disrupt or enhance these interactions, leading to new therapeutic strategies.

Some web servers that you can use:
• ZDOCK: A widely used program that employs a fast Fourier transform (FFT)-based search algorithm to explore the conformational space of two proteins.
• ClusPro: A web server that combines docking and clustering algorithms to predict protein complex structures.
HADDOCK: A flexible docking program that incorporates experimental data and restraints to improve the accuracy of predictions. GRAMM: A docking program that uses a geometric hashing algorithm to identify potential binding sites and orientations.
• PatchDock: An algorithm geared towards lock-and-key docking

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

Let's consider the interaction between PD-1 (Programmed cell death protein 1) and PD-L1 (Programmed death-ligand 1). PD-1 is a receptor found on T cells, and PD-L1 is a ligand found on some normal cells and cancer cells. When PD-L1 binds to PD-1, it sends a signal to the T cell to stop attacking the cell. This is a normal mechanism that prevents the immune system from attacking healthy cells. However, cancer cells can hijack this mechanism to evade the immune system. Using protein-protein docking tools like ZDOCK or ClusPro, researchers can predict the 3D structure of the PD-1/PD-L1 complex. This information can be used to design drugs that disrupt the interaction between PD-1 and PD-L1, thereby restoring the ability of T cells to attack cancer cells. For example, a drug might be designed to bind to PD-1 and prevent PD-L1 from binding to it. This would block the signal that tells the T cell to stop attacking, and the T cell would then be able to kill the cancer cell.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

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Drugs aren't always designed to work on proteins. In fact, some of the most important drugs have been designed to work against DNA 🧬.

Examples:
1. Doxorubicin: An anthracycline antibiotic used in cancer treatment. It works by intercalating (inserting) between DNA strands, disrupting DNA replication and cell division.
2. Cisplatin: A platinum-based chemotherapy drug. It damages DNA by forming crosslinks, which interfere with DNA repair and replication, ultimately leading to cell death.
3. Azathioprine: An immunosuppressant. Its active metabolite incorporates into DNA, inhibiting purine synthesis and thus affecting cell proliferation, particularly of immune cells.

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BioCode: Learn Bioinformatics

May 24, 2026, 01:44 AM

Want to create such visualizations yourself?

Get the hexokinase structure.
Show the protein as a cartoon.
Color different parts of the protein differently.
Show any bound molecules as sticks.
Highlight important amino acids as spheres (optional).
Set a background color.
Position and zoom the molecule to get a good view.
Render and save the image as a high dpi

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