Altman et al. JACS 2008, Presented By Swati Jain

Drug Resistance Mutations in drug target – selective lower inhibitor affinity – maintenance of normal function. Approach – drugs for known resistant mutants. Problems – potential to introduce new drug resistant mutations. New techniques – not induce viable mutations, work with unknown modes of resistance.

Substrate envelope Hypothesis Figure taken from : Altman et al. JACS (19)

Inverse Inhibitor Design Algorithm Generate substrate envelope. Select scaffolds. Choose functional groups. Generate conformational ensembles. Place scaffold in the substrate envelope – single and pair-wise energies - DEE/A* - energy ranked compounds. Refine the list - more accurate energy functions.

HIV-1 Protease as target model Homodimer – each subunit made up of 99 amino acids. Well studied protein Aspartic protease: Asp-Thr-Gly active site. Figure taken from Wikipedia.

Known HIV-1 Substrates and Inhibitor Figure taken from King et al. Chem bio

Substrate and Maximal Envelope

Scaffold and functional groups Functional Groups Amprenavir scaffold Carboxylic acids – R1. Primary amines - R2. Sulfonyl chlorides – R3 Criterion: < four rotatable bonds. (ignoring the bond to the active group). Figure taken from : Altman et al. JACS (19)

Conformational Ensembles Hydrogen atoms placed at attachment sites for both scaffold and functional groups. Geometry Optimization. Scaffold and Functional Groups: Sampling dihedral angles about each rotatable bond. (every 30 degrees for sp3-sp3, sp2-sp3 and every 45 degrees for sp2-sp2 bond).

Energy calculations Substrate bound protease structure Inactivating mutation reversed. Assigned force field parameters. Substrate envelope placed inside the active site. Three components: Van der Waal’s packing term, screened electrostatic interaction term, Desolvation penalties for both ligand and receptor.

Grid based energy calculations Receptor shape and charges fixed. Basis points within the ligand – points of cubic grid inside substrate envelope. Van der Waal’s energies – each atom type at each grid point. Electrostatic – 1 electron charge at each grid point. Desolvation – change in solvation potential for all grid points when one grid point is charged.

Energy calculations contd … Van der Waal’s energy – interpolating energies from grid points. Electrostatic and desolvation – projecting partial charges to grid points. Figure taken from Wikipedia.

Scoring function Constant term – Binding energy of blunt scaffold + receptor desolvation term. Self energy of functional group – Binding energy with receptor + desolvation between functional group and scaffold. Pair wise energies – desolvation penalties between two functional groups. Clashes – energy infinite.

Scaffold into the Envelope Placed the scaffold in the envelope. Scaffold position accepted – all atoms within the envelope + required hydrogen bonding + no clashes. For each scaffold placement – discrete ensembles of every functional group attached – self energies. Pairs of functional groups attached – pair wise energies.

DEE/A* Self and pair wise energies sum to the total energy calculated. For each scaffold (backbone) conformation – ensemble (rotamers) of functional groups (side- chains) and the self and pair wise energy contribution to the total energy. Used DEE/A* to generate the list of energy ranked conformations. A common list for all scaffold positions.

Hierarchical energy functions Assumption – energies calculated using substrate envelope. Generated list re-evaluated. More sophisticated energy function – true molecular surface. Higher Grid resolution.

First Round Design Design repeated eight times Tight and loose substrate envelope Doubly deprotonated and deprotonated protease structure. Rigid and flexible scaffold placement. 20 compounds selected based on robustness to parameters. 15 synthesized and tested.

First round Inhibitor Affinities Figure taken from : Altman et al. JACS (19)

Second round design Selection of functional groups – based on successful compounds from the first round. Inhibitor bound protease structure used for the design. Only doubly-deprotonated protease structure. Tighter definition of substrate envelope. 36 compounds synthesized and tested.

Second round design results Figure taken from : Altman et al. JACS (19)

Binding Affinities – Drug resistant protease inhibitorWTM1M2M3M4 worst fold loss ritonavir ND55 saquinavir ND1385 indinavir ND189 nelfinavir ND68 lopinavir ND1220 amprenavir atazanavir ND11 tipranavir ND0.36 darunavir b ND6 11c ND8 12h ND8 12j ND13

Binding Affinities – Drug resistant protease inhibitorWTM1M2M3M4 worst fold loss 27a b ND40 28a b ND63 29a b a b d c

Correlation between calculated and observed binding free energies Figure taken from : Altman et al. JACS (19)

Crystal structures of the inhibitors Structures done – four first round, five second round. Scaffold preserved hydrogen bonding network. First round inhibitors – mostly inside substrate envelope except one functional group. Second round inhibitors – Mostly inside substrate envelope with one exception.

Predicted and Determined structures Figure taken from : Altman et al. JACS (19)

Substrate envelope Figure taken from : Altman et al. JACS (19)

Crystal structures – Relation to Resistance profile. Figure taken from : Altman et al. JACS (19)

Testing the algorithm for separating binders and non-binders Figure taken from: Huggins et al. Proteins 75:

Differences from earlier algorithm Geometry Optimization of the Protein structure. Scaffold and side groups - the set of known binders and non binders. Maximal envelope Torsion angle of the bond attaching functional group to scaffold – 10 degrees. Minimization.

Enrichment for binders Figure taken from: Huggins et al. Proteins 75:

Contribution of electrostatic energy Figure taken from: Huggins et al. Proteins 75:

Explicit water model Figure taken from: Huggins et al. Proteins 75:

Issues and Improvement Inhibitors have lower binding energies outside the substrate envelope – factors beyond substrate envelope important. Finer Sampling - better results – generates too many placements. Scoring functions – minimization gives better results – MinDEE??. Flexible receptor. Certain functional groups and solubility prediction.