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HIV-1 Protease Inhibitors from Inverse Design in the Substrate Envelope Exhibits Subnanomolar Binding to Drug Resistant Variants. Altman et al. JACS 2008, 130 6099-6113 Presented By Swati Jain. Drug Resistance.
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HIV-1 Protease Inhibitors from Inverse Design in the Substrate Envelope Exhibits Subnanomolar Binding to Drug Resistant Variants Altman et al. JACS 2008, 130 6099-6113 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 2008 130 (19) 6099-6113
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 11 1333-1338.
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 2008 130 (19) 6099-6113
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 2008 130 (19) 6099-6113
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 2008 130 (19) 6099-6113
Correlation between calculated and observed binding free energies Figure taken from : Altman et al. JACS 2008 130 (19) 6099-6113
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 2008 130 (19) 6099-6113
Substrate envelope Figure taken from : Altman et al. JACS 2008 130 (19) 6099-6113
Crystal structures – Relation to Resistance profile. Figure taken from : Altman et al. JACS 2008 130 (19) 6099-6113
Testing the algorithm for separating binders and non-binders Figure taken from: Huggins et al. Proteins 75: 168-186.
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: 168-186.
Contribution of electrostatic energy Figure taken from: Huggins et al. Proteins 75: 168-186.
Explicit water model Figure taken from: Huggins et al. Proteins 75: 168-186.
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.