DFT 𝑱𝒂𝒄𝒐𝒃'𝒔 𝑳𝒂𝒅𝒅𝒆𝒓 COURSE LINK 1,999/-

🪜 𝑱𝒂𝒄𝒐𝒃'𝒔 𝑳𝒂𝒅𝒅𝒆𝒓 𝒐𝒇 𝑫𝑭𝑻: 𝑪𝒍𝒊𝒎𝒃𝒊𝒏𝒈 𝑻𝒐𝒘𝒂𝒓𝒅𝒔 𝑪𝒉𝒆𝒎𝒊𝒄𝒂𝒍 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲

If you've ever used Density Functional Theory (DFT), you've probably come across terms like LDA, GGA, meta-GGA, or hybrid functionals.

But have you ever wondered why they're described as steps on Jacob's Ladder? 🤔

The idea, proposed by John Perdew, is simple: each rung of the ladder brings us a little closer to the "heaven of chemical accuracy."

🪜 1st Rung – LDA (Local Density Approximation)
✔️ Fast and simple.
✔️ Assumes electrons behave like a uniform electron gas.
❌ Often overbinds atoms and molecules.

🪜 2nd Rung – GGA (Generalized Gradient Approximation)
✔️ Includes how the electron density changes in space.
✔️ Better geometries and energies than LDA.
📌 Popular examples: PBE, PW91.

🪜 3rd Rung – meta-GGA
✔️ Goes one step further by using kinetic energy density (or related quantities).
✔️ Improves accuracy without the full cost of hybrid functionals.
📌 Examples: SCAN, TPSS.

🪜 4th Rung – Hybrid Functionals
✔️ Mix DFT with a fraction of exact Hartree–Fock exchange.
✔️ Excellent for molecules, band gaps, and reaction energetics.
📌 Examples: PBE0, B3LYP, HSE06.

🪜 5th Rung – Double Hybrids
✔️ Combine hybrid DFT with perturbation theory.
✔️ Among the most accurate DFT methods—but also the most computationally expensive.
📌 Examples: B2PLYP, DSD-BLYP.

💡 The key takeaway?

Higher isn't always better.

The best functional is the one that balances accuracy, computational cost, and the property you're trying to predict.

🎓 𝐈𝐟 𝐲𝐨𝐮'𝐫𝐞 𝐣𝐮𝐬𝐭 𝐠𝐞𝐭𝐭𝐢𝐧𝐠 𝐬𝐭𝐚𝐫𝐭𝐞𝐝 𝐰𝐢𝐭𝐡 𝐃𝐅𝐓 𝐬𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐦𝐚𝐭𝐞𝐫𝐢𝐚𝐥𝐬, 𝐥𝐨𝐨𝐤 𝐧𝐨 𝐟𝐮𝐫𝐭𝐡𝐞𝐫!

𝐎𝐮𝐫 𝐛𝐞𝐠𝐢𝐧𝐧𝐞𝐫-𝐟𝐫𝐢𝐞𝐧𝐝𝐥𝐲 𝐫𝐞𝐜𝐨𝐫𝐝𝐞𝐝 𝐜𝐨𝐮𝐫𝐬𝐞 𝐨𝐧 𝐃𝐞𝐧𝐬𝐢𝐭𝐲 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐓𝐡𝐞𝐨𝐫𝐲 (𝐃𝐅𝐓) 𝐮𝐬𝐢𝐧𝐠 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐄𝐒𝐏𝐑𝐄𝐒𝐒𝐎 𝐭𝐚𝐤𝐞𝐬 𝐲𝐨𝐮 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 𝐭𝐨 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥 𝐬𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬.

𝐂𝐥𝐢𝐜𝐤 𝐭𝐨 𝐣𝐨𝐢𝐧

Comments

Curated Compendium of Drug Discovery

Drug discovery is a multidisciplinary process that integrates biology, chemistry, pharmacology , and cutting-edge technologies to identify and develop new therapeutic agents. From target identification to lead optimization and clinical evaluation, each stage requires precision, innovation, and collaboration. A curated list of drug discovery resources provides researchers, students, and professionals with a structured pathway to explore advancements, tools, and strategies that shape modern therapeutics. This compilation serves as a gateway to understanding the evolution of drug discovery, recent breakthroughs, and future directions, fostering knowledge-sharing and accelerating translational research. Databases and Chemical Libraries General Compound Libraries DrugBank - Comprehensive data on approved and investigational drugs. ZINC - Free compounds for screening. ChemSpider - Chemical structures and data. DrugSpaceX - Chemical and biological spaces. Mcule ...

Understanding NMR Spectroscopy and Chemical Shift Ranges for Functional Groups

Nuclear Magnetic Resonance ( NMR ) spectroscopy is one of the most powerful analytical tools in pharmaceutical chemistry. It helps chemists determine the structure, purity, and chemical environment of molecules by analyzing the behavior of nuclei (commonly ¹H or ¹³C ) when exposed to a strong magnetic field. In proton NMR ( ¹H-NMR ), the chemical shift (δ, in ppm) provides information about the type of hydrogen atoms present in a compound and their surrounding electronic environment. Depending on nearby atoms and functional groups, signals appear in specific regions of the spectrum — often referred to as upfield (shielded, lower δ values) or downfield (deshielded, higher δ values). The image above summarizes the characteristic δ ranges for different functional groups in ¹H-NMR. Let us break it down systematically: 1. Downfield Region (δ 12 – 6 ppm) Hydrogens in this region are strongly deshielded due to electronegative atoms or π-bond systems. Carboxylic Acids (–COOH) : δ 1...

Pushing the boundaries of computational drug discovery at Isomorphic Labs

The Isomorphic Labs Drug Design Engine (IsoDDE) has unlocked a new frontier in in-silico drug design, representing a significant evolution beyond AlphaFold 3. What IsoDDE delivers: 🔹 Massive accuracy leap on unconstrained structure prediction The engine more than doubles AlphaFold 3's accuracy on extremely challenging protein-ligand prediction tasks — including systems far outside the training distribution. 🔹 Best-in-class binding affinity prediction IsoDDE predicts how strongly small molecules bind to targets with accuracy that exceeds gold-standard physics-based methods, at a fraction of the computational cost and time. 🔹 Blind identification of novel binding pockets Even without existing structural data, the engine reveals previously unseen binding sites — just from an amino acid sequence — enabling drug designers to explore entirely new chemical action spaces. 🔹 Expanded support for complex biologics Beyond small molecules, the engine boosts prediction fidelity for...

NEOPHARMA NUTSHELL COMMUNITY

Search This Blog