Database extraction of residue-specific empirical potentials building a

Database extraction of residue-specific empirical potentials building a

Database extraction of residue-specific empirical potentials building a complete set of energy parameters including distance and angle dependence of interresidue interactions estimation of secondary structure propensities of amino acids utility in fold recognition, homology modeling and/or threading 02/02/20 Underlying principle: Inverse Boltzmann law Energies --> Probabilities (Boltzmann) Probabilities --> Energies (inverse Boltzmann) Boltzmann law: Pi ~ exp (-Ei/RT) Inverse Boltzmann: Ei = -RTlnPi + ct Two types of interaction: Long-range (close in space, not in sequence)

Short-range (sequential neighbors) Long-range are the most important dominant interactions in folding Residue-specific interactions 2 (b) [Arg, Lys] EAB/RT 1 0 -1 [Arg, Ser] -2 [Arg, Asp] -3

Interactions of hydrophobic residues 2 4 6 distance () 8 10 Interactions between charged/polar residues Residue-Residue Interactions (from Protein Structures) Effective solvent-mediated contact potential = exy + e00 ex0 eyo Residue-specific distributions of # of neighbors 0.3 Tot

Gly Ala Leu Glu Pro Frequencie s 0.2 0.1 0.0 0 5 10 # Neighbors 15 Short-range (bonded) interactions Coupling between consecutive dihedral angles in the virtual bond model

Comparison of predicted and experimental helical propensities 0.8 0.6 M Q 0.4 -E T 0 -0.2 S C N 0.2

A-GLY + V L Y I - ( , ) (kcal/mol) A F F W G 0

0.2 - G 0.4 0.6 0.8 (kcal/mol) Abscissa values from helix-coil transition [O'Neil and deGrado (1990)] For more info... Bahar, Kaplan and Jernigan, Proteins 1998 Comparison of predicted and experimental -strand propensities 2.5 E X

( + - , ) = 0.37 + 3.08 G R= 0.90 I C 2 A +

- - E ( , )/RT V K 1.5 W F H R N A M T D Q

L Y E S 1 0.3 0.35 0.4 - 0.45 G 0.5 0.55

(kcal/mol) Experimental (abscissa) values from [Kim and Berg (1993)] 0.6 Use of potentials for discriminating correct folds amongst misfolded structures Ozkan, B. & Bahar, I. "Recognition of native structure from complete enumeration of low resolution models with constraints" Proteins: Structure, Function & Genetics 32, 211-222, 1998. Long distance effects can be taken care by whole sentence exponential model. Spatial, not sequential, correlations are important in controlling folding, misfolding, interactions. Can we select features/attributes that characterize the 3-d topology of contacts? Multi-body geometry-dependent interactions? Keskin, O. , Bahar, I. , Badredtinov, A., Ptitsyn, O. B., & Jernigan, R. L. Protein Science 7, 2578-2586, 1998.

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