Valliappan Kannappan

A chiral perspective on how we describe, teach, and encode molecular handedness in the age of artificial intelligence Prelude Chiral molecules are not flat drawings on paper (2D). They live in space (3D). They twist, reflect, and occupy three dimensions in ways that decide how they bind to receptors, how they are metabolized, and ultimately how they shape biological outcomes. This spatial reality—what chemists call chirality—has always been at the heart of pharmaceutical science. The …

🪞Why the Language of Chirality Must Evolve: When Molecules Speak in 3D and Models Listen in 2D🤖 Read More »

Can an AI truly understand a molecule if it cannot tell left from right? Artificial intelligence now shapes the earliest and most consequential stages of drug discovery, from virtual screening and ADMET prediction to generative molecular design. Yet many of these systems operate in an effectively achiral digital environment, where molecules are represented as flat graphs, strings, or feature vectors that often erase or blur stereochemical information. This article introduces the concept of chiral bias …

Teaching Machines to See in 3D: The Chiral Blind Spot in AI-Driven Drug Discovery Read More »

❓ Can AI truly be intelligent if it is stereo-blind? 🌀 On Visuals and Stereochemical TruthSome illustrations in this series are generated or assisted by AI to support conceptual understanding. These visuals are intentionally simplified and should not be read as stereochemically rigorous or chemically exact representations. Wherever stereochemical fidelity matters, it is addressed explicitly in the discussion—because in chemistry, especially in chiral systems, intuition must always yield to structure. The earlier episodes treated chiral …

Episode 5: Beyond Bias: Toward Chiral Intelligence Read More »

❓ How do we move from recognizing chiral bias to responsibly fixing it? On Visuals and Stereochemical TruthSome illustrations in this series are generated or assisted by AI to support conceptual understanding. These visuals are intentionally simplified and should not be read as stereochemically rigorous or chemically exact representations. Wherever stereochemical fidelity matters, it is addressed explicitly in the discussion—because in chemistry, especially in chiral systems, intuition must always yield to structure. The earlier parts …

Episode 4: Fixing the Bias: Data, Models and Generative Constraints Read More »

“When molecules have two hands but AI only sees one.” On Visuals and Stereochemical TruthSome illustrations in this series are generated or assisted by AI to support conceptual understanding. These visuals are intentionally simplified and should not be read as stereochemically rigorous or chemically exact representations. Wherever stereochemical fidelity matters, it is addressed explicitly in the discussion—because in chemistry, especially in chiral systems, intuition must always yield to structure. The first two parts of this …

Episode 3: When Algorithms Miss the Mirror: How Chiral Blind Spots Break the Pipeline? Read More »