MCHM3001 · From Molecules to Therapeutics
In-Silico Drug Design
Lecture 11 of MCHM3001 is the computer-aided-design chapter, and it directly underpins the assessed in-silico docking assignment. It covers where leads come from, the pharmacophore concept, the structure-based workflow from crystal structure to docked pose, scoring functions, and the physical-chemistry drivers of ADME (ionisation, logP). Percentage-ionisation and logP calculations are examinable, and pose interpretation is assessed in the docking figure task.
What this chapter covers
- 01Sources of leads: side-effect optimisation, serendipity, natural-ligand similarity, 'someone else's lead'
- 02CADD types: ligand-based (pharmacophore, SAR, bioisosteres — no 3D structure needed) versus structure-based (docking, virtual screening — needs 3D)
- 03Pharmacophore = common 3D arrangement of features (HBD/HBA, hydrophobe, ring) defined by distances and angles
- 04SBDD workflow: obtain and correct a protein structure → define the binding site → prepare a library → conformational search → dock → analyse the hit list
- 05Docking tools: RCSB PDB, Schrödinger Maestro, LigPrep, Glide and the Glide Score, accuracy levels (HTVS/SP/XP), the ZINC library
- 06Scoring functions evaluate steric and electrostatic complementarity to rank compounds
- 07Ionisation: pKa = −log₁₀Ka; %ionised(acid) = 100/(1 + 10^(pKa−pH)); %ionised(base) = 100/(1 + 10^(pH−pKa)); pH = pKa at 50%
- 08Partition coefficient logP = [X]octanol/[X]aqueous; rotatable bonds; Lipinski + Veber developability
Percentage ionisation of a weak acid in stomach versus blood
- +1Stomach: substitute pKa − pH = 4.5 − 2.0 = 2.5, so %ionised = 100/(1 + 10^2.5) = 100/(1 + 316) = 100/317 ≈ 0.3%.
- +1So in the stomach the acid is ~0.3% ionised, i.e. ~99.7% in the neutral, un-ionised form.
- +1Blood: pKa − pH = 4.5 − 7.4 = −2.9, so %ionised = 100/(1 + 10^(−2.9)) = 100/(1 + 0.00126) ≈ 99.9% ionised.
- +1Interpret: only the neutral form crosses membranes by passive diffusion, so a weak acid is absorbed where it is largely un-ionised — the acidic stomach — and becomes trapped in its ionised form once it reaches the neutral pH of blood.
Key terms
- Pharmacophore
- The common three-dimensional arrangement of features (H-bond donor/acceptor, hydrophobe, aromatic ring) shared by active molecules, specified by inter-feature distances and angles; the basis of ligand-based screening.
- Structure-based drug design (SBDD)
- Design that uses a 3D protein structure: prepare and correct the structure, define the binding site, dock a prepared library, score for complementarity, and analyse the hit list.
- Docking / Glide Score
- Computationally placing a ligand in a binding site and scoring the pose; the Glide Score ranks steric and electrostatic complementarity, run at accuracy levels HTVS, SP or XP that trade speed for precision.
- Percentage ionisation
- The fraction of a drug in its charged form at a given pH: %ionised(acid) = 100/(1 + 10^(pKa−pH)), %ionised(base) = 100/(1 + 10^(pH−pKa)); the two are 50% when pH = pKa.
- Partition coefficient (logP)
- log of the ratio of a neutral compound's concentration in octanol to that in water; a core lipophilicity descriptor governing permeability, solubility and metabolic stability.
- ZINC library
- A large, free database of purchasable compounds in ready-to-dock 3D form, commonly used as the input library for virtual screening.
In-Silico Drug Design FAQ
How do you decide between ligand-based and structure-based design?
It comes down to whether you have a 3D structure of the target. With a solved structure (X-ray, cryo-EM, NMR) you can use structure-based methods — dock candidates into the actual binding site and run virtual screening. Without one, you use ligand-based methods: build a pharmacophore from known actives and exploit structure-activity relationships and bioisosteres. Many projects use both as structures become available.
Why does the pH of a compartment change how much drug is absorbed?
Only the neutral, un-ionised form of a drug crosses membranes efficiently by passive diffusion. A weak acid is neutral below its pKa and ionised above it, so it is absorbed where the pH keeps it un-ionised (an acid absorbs well in the acidic stomach) and becomes trapped once it reaches a compartment where it ionises. Computing percentage ionisation in each compartment predicts where absorption happens.
What makes a good docking figure for the in-silico assignment?
Clarity and precision. The assessed figure should show the optimised ligand in the binding site at high resolution with clutter removed, the key interactions (H-bonds, cation-pi, pi-pi stacking, electrostatics) clearly marked, and a concise legend that defines every symbol — the opposite of a 'bowl of spaghetti' with a detached caption. It is one A4 page: a 300-dpi figure plus a legend of no more than 200 words.
Can AI help me with the in-silico design material in MCHM3001?
Yes. Sia can compute percentage ionisation for acids and bases, explain logP and rotatable-bond limits, walk through the SBDD workflow from crystal structure to scored pose, and help you critique a docking figure against the marking criteria. It explains the method and checks your working; it does not do the graded assignment for you, and University of Sydney academic-integrity rules apply.
Exam move
Split your effort between the concepts and the two calculations. Be able to draw the SBDD workflow (structure → prepare → define site → dock → score → analyse) and to define a pharmacophore precisely (features plus distances and angles). Then drill percentage ionisation until you never mix up the acid exponent (pKa − pH) with the base exponent (pH − pKa), and practise reasoning from logP to solubility and permeability. Because the docking assignment is assessed, study a few good versus bad pose figures against the rubric so you can both make and critique one. When the ionisation direction confuses you, ask Sia for a worked acid and a worked base side by side.
Working through In-Silico Drug Design in MCHM3001? Sia is AskSia’s AI Chemistry tutor — ask any MCHM3001 In-Silico Drug Design question and get a clear, step-by-step explanation grounded in how MCHM3001 is taught and assessed. Read this chapter free, then take your hardest questions to Sia.
