Conformation preference parameters

Chou and Fasman started out with the calculation of conformation preference parameters which represent a measure for the tendency of an amino add to be part of an a-helical, extended or random coil region. Depending on the values of these parameters, they attribute each residue to one of the following six classes ... 

Table 1. Conformational preference parameters P, and Pp (based on data from 29 proteins >)...

Many efforts were made to refine the methodology of the prediction algorithms. The aid of computers became indisp isable when known parameters were supplemented by values obtained from the statistical study of di- and tripeptide units Lifson and Sander discriminated between parallel and antiparallel P-pleated sheets and Geisow and Roberts demonstrated that conformational preference parameters vary with the protein class Despite these refinements the improvement of the prediction accuracy must be considered minor. The upper limit of exclusively statistical algorithms appears to be in the order of 60-70%... 

Palau and co workers proposed a sdieme with elements of purely statistical methods (conformational preference parameters) and structure-stabilizing factors ( weighting factors ) The wei ting factors modify the conformational preference parameters by taking into account e.g. hydrophobic interactions with )-structural regions or the occurrence of hydrophobic triplets in the helical positions 1-2-5 and 1-4-5. Additional parameters can be introduced into the prediction scheme. 

At a first glance, this result seems to generally support the validity of the conformational preference parameters in prediction schemes. However, the statistical analysis of proteins favors the P-structure potential of L-Val over its helix-indudng power. Provided these theoretical prediction methods could be applied not only to proteins but also, in a first approximation, to synthetic oligopeptides, a stable p-strudure for Boc-(L-Ala)s-(L-Val)2-(L-Ala)3-NH-POE-M in TFE should have been expected. The experimental outcome of a partial a-helical conformation for this sequence in TFE points to limitations of the prediction rules which rely on the assumpticm of a dominance of short-range interactions. Consequently, prediction of peptide ctmforma-tion requires more informations than the preference parameters of the constituting amino acids alone. 

Much controversy is found in the literature regarding the conformational preference of the six-membered ring piperidine (5)4 5. However, most experimental evidence is consistent with a predominance of the H-equatorial conformer by 0.25-0.74 kealmol-1. As noted above, the C—C—N—H and C—C—N—lp torsional parameters were adjusted to reproduce an intermediate value of 0.30 kcal mol-1. MM2 calculations of this system have revealed, perhaps contrary to chemical intuition, that most of the energy difference between the H-axial and H-equatorial conformers results from torsional energy while the 1,3-diaxial interactions have only a negligible contribution5. 

Evidently, Es parameters cannot be used when strong conformational preferences exist, and for heteroaromatics ortho-steric parameters are required. 

Our algorithm can give partial answer to the question what attributes are optimal predictors for specific folding motifs. Kyte-Doolittle type hydropathy values and Chou-Fasman type conformational preferences are two obvious answers to the question what amino acid attributes are good predictors for majority of transmembrane helices. Indeed, three such scales MODKD, KYTDO and CPREF (Table 4), are on the very top of the list of the best amino acid scales (Table 5). Performance parameters that punish overprediction (A-j y and Qp) give advantage to hydropathy values. Modifications to the Kyte-Doolittle values in the MODKD... 

Structural Structural moieties often have a role in maintaining a preferred conformation and parameters such as size and bond angle play a key role in achieving this. Typically, this is particularly relevant for moieties that are embedded deep within the overall chemical structure. Scaffold hopping can be seen as an example of this, where the relative geometries of the exit vectors have a very low tolerance to modification. 

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