Loop Refinement by Localized Sampling and Minimization (SLAM)

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Loop Refinement by Localized Sampling and Minimization

(SLAM)Vageli Coutsias, Matt Jacobson,

Michael Wester, Lan Hua

(1) loops to be refined - given or by comparison with homologous proteins [ for homology modeling only: use PRIME to get templates. Identify loops

that show most variability among different templates. ] (2) use SPLAT to sample around the loops identified in (1). Sampling is

restricted to Ramachandran allowed regions (these are sampled with probability-usually .001 threshold) and screened for sterics with variable steric cutoff. Too large screens exclude interesting contacts from forming. Too small give high clash energies.

(3) use PLOP to minimize energy of the loop regions (including residues within a certain cutoff distance, mostly set at 7A).

(4) select lowest energy candidates without any obvious flaws (i.e. loops away in solvent, obvious burials of polar residues or hydrophobics blatantly pointing outwards) and resample around them with windowed sampling - usually +/-30 degrees, except for certain residues I wanted to maintain. I tried different strategies for the windowed sampling.

(5) iterate steps 3-4. Typically looked for a funnel-like distribution of RMSD from a reasonable minimum vs. energy to decide convergence. Only used systematically (but not completely due to time pressure) for R488.

Results

• R432: rmsd to native 1.0 (vs. 1.3 template)• R453: higher rmsd / correct secondary• R488: higher rmsd • T0479: rmsd to native 1.3

ConclusionAlthough sampling seems to have revealed the shape of

the loop including occasional secondary structure elements, special contacts & salt bridges formed that minimized well but forced the sampling into ranges far from the native. In subsequent work we should:

(1) include a stage of localized move MC to properly weigh minimum states by free energy estimates. Various constraints will allow to focus sampling and raise efficiency.

(2) Must include a Jacobian-based pruning of data to increase efficiency by cutting down on minimizations.

(3) Explore other global search & optimization methods to produce a map of the low minima.

(4) Add enforcing of position and orientation constraints

R432 = 3dai

Refinement of loop 85-92Small helix end perturbation

Broad sampling of loopCyan (model 1) is at 1.0A to native (purple)

Template (white) is at 1.3ALoop 85-92 is at 2.4 A (cyan) and 3.8 A (white)

Strategy: lowest energy structures from 1st batch start own narrower sampling branches. Best results of second iteration sampled again. Now low energy extension of helix at 90 was found, and it was selected in some of the new seed runs. Lowest

energy results from the fourth stage were chosen.

R453 = 3ded

• Loop in space. Found structure with a single-turn helix.

• Appears in chain A• Template, although closer in RMSD, lacks

this structure.• W:native, P:template, C:best model• Fig. 1: matched to chain D• Fig. 2: matched to chain A

Small twist around res35 (which is a Proline and res 37 is also a Proline) in both native and model structures. Interestingly, in the model structures the carbonyl oxygen of Pro37 seems to form hydrogen bond with OH of Tyr53, however no such hydrogen bond is formed in native structure and the initial best model. Probably such hydrogen bond formation pulls the loop turn (res35-40) in the model structure away from native structure.

R488 with ligand(D). 6k set, full 360 sampling of all residues (11-19) of TR488 with 6-ALA ligand(E) 3k set, 360 at pivots (1-5-7), +/-30 at LEU18, GLY19 (to preserve orientation of LEU sidechain), +/-60 at

other residues(F) 6k set, 360 at pivots (same), +/-30 at all other residuesStructure of minimum stable; a few structures withslightly lower energy ~2kcal, but ruined secondary structures (helices

or strands un-made)TOP candidate: T488_f_04930-opt.pdbShown with its precursors, d-06993 and e-01016Together with other f-batch structures of similar shape, but slightly

higher energies

d-, e-1016, f-4930 and other low-energy

F-structures; well converged shape R488

Although this model represents the height of the preformance of thealgorithm, it had a twist, which made the effort totally speculative:as a PDZ domain, it ought to have a binding pocket. My first set ofefforts did not take that into account, and I simply sampled/minimizedquite extensively, iterating several times until I arrived at a veryrobust-seeming loop. Then we noticed that the binding pocket was tootight, so we introduced a putative ligand and sampled again to allowfor its presense. I also restricted sampling to conformations thathad the LEU18 pointing inward.

The sidechain of LEU18 is pointing inward in native structure, initial best model and model structures. Asp13 points inward in both refined models, probably forming salt bridges with Lys11 (the distance betweenOD of Asp13 and NZ of Lys 11 is around 2.7 angstrom), which twist the loopinward. However Asp13 points outward in native structure and initial best model, and does not form salt bridge with Lys11.

Native (W), model 1 (C), model 2 (P), template (Y)

TO479 = 3dkz• Model T0479_3 (model 3) has the smallest rmsd

(1.3 A) and T0479_4 (mod 4) the largest (2.3 A).• Refining three loops: used various combinations

of minima from each refinement, on the assumption that the loops did not interact.

• Homology modeling using PRIME. Subsequent loop refinement using SPLAT(sampling)/PLOP(minimization).

• (fig1) Native (W) vs models 3 (Y), 4 (R)• (fig2) Native (W), 1(P), 2(C), 3(Y), 4(R), 5(B)

Loop Refinement by Localized Sampling and Minimization (SLAM)

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