Native deviations in main-chain geometrical parameters seems crucial for structural integrity of proteins. These deviations are non-random, strategic and context dependent and it seems extremely difficult to predict them given the native main- and side-chain torsion angle profiles of a given structure. In this work, proteins of diverse folds and lengths were gathered spanning the four major protein classes and ranging from ~50 to ~375 residues in chain length and the structures rebuilt by (successive forth atom fixations) reverting all main-chain bond lengths, angles and ω-torsions to their corresponding unimodal ideal values (as tabulated in relevant repositories), while retaining native values for all other dihedral angles (φ, ψ, χ). To much of our surprise, this led to such large-scale distortions in the idealized structures (with
respect to the original native model) that often their (C
α) RMSDs
exceeded 10 Å
(Fig. 1). Although the degree of structural
distortions is estimated by the RMSDs, its effect on packing and electrostatics
can be conveniently assessed using the CP measures
[1, 2]. The distortions were more
pronounced for larger polypeptide chains (~100 residues or more in length) due
to the accumulation of a higher number of angular idealizations. Also, proteins
containing greater β-sheet content had more severe deformations most probably
rationalized by the distribution in N-C
α-C (τ)
angle with respect to secondary structure. Little or no improvement was observed in
the quality of the rebuilt structures by either retaining native ω values or
utilizing ideal values (for bond angles) derived from a conformation dependent
library (CDL)
(Fig. 2) (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2810841/). Energy minimization of these idealized structures did not improve the (C
α)
RMSDs (calculated at a one-to-one atomic correspondence
subsequent to superposition) between native and
idealized coordinates, which in some instances could not even be superposed
onto each other (
Table 1).
Thus, in summary, in no case could the original structure be reconstituted by
any form of energy minimization of the idealized coordinates. Calculations
using both unimodal and CDL ideal values were repeated on a larger dataset of ultrahigh resolution (≤ 1 Ǻ) structures, which gave a similar pattern of results. Attempts are being carried out to device strategies to predict these deviations in a structure jammed with its native torsion angles.

Fig. 1. Distortions
in the native fold due to the reversal of all main-chain bond lengths, angles
and ω-torsions to their corresponding
(unimodal) ideal values. (A) the native structure of
cyclophilin from L. donovani (2HAQ)
and (B) its corresponding idealized structure (Cα-RMSD: 12.86
Ǻ, calculated at one-to-one atomic correspondence).
Fig. 2. Effect of CDL-idealization probed by CP. Distribution for (A) the native polypeptide chain
(1PGS) and (B) its corresponding idealized structure generated utilizing
CDL ideal values.
Table 1. Structural distortions due to
idealization as reflected in the RMSDs.
PDB ID
|
RMSD (Ǻ) a
|
Idealized
vs. native
|
Idealized
& Energy Minimized
vs. native b
|
1AKO
|
13.98
|
-c
|
1BGF
|
7.30
|
6.77
|
1CEM
|
16.61
|
17.35
|
1CHD
|
22.42
|
22.18
|
1CKA
|
3.05
|
3.10
|
1ERZ
|
24.44
|
22.78
|
1HBQ
|
22.60
|
-
|
1IFC
|
11.30
|
11.48
|
1LMB
|
4.56
|
4.56
|
1MKB
|
-
|
-
|
1MLA
|
23.33
|
22.05
|
1PDO
|
4.56
|
5.29
|
1PGS
|
-
|
-
|
1SFP
|
-
|
-
|
1SRV
|
13.82
|
-
|
1STN
|
18.02
|
18.10
|
1UBI
|
4.31
|
4.14
|
2CPL
|
12.52
|
12.58
|
2END
|
7.64
|
7.41
|
2LIS
|
9.09
|
9.11
|
a RMSDs calculated between Cα
atoms of idealized (all main-chain bond lengths, bond angles and ω)
and the native coordinates (calculated at a one-to-one atomic correspondence)
subsequent to superposition by Dali server.
b The same calculation was repeated for
energy minimized coordinates subsequent to idealization.
c ‘-’ stands for non-superposable
structures.
References:
Sankar Basu, Dhananjay Bhattacharyya, and Rahul Banerjee*
Biophysical Journal, 2012, 102 (11) : 2605-2614
3. Applications of the complementarity plot in error detection and structure validation of proteins
Sankar Basu, Dhananjay Bhattacharyya, and Rahul Banerjee*
Indian Journal of Biochemistry and Biophysics, 2014, 51 (June) : 188-200
Sankar Basu*, Dhananjay Bhattacharyya, and Rahul Banerjee*
Journal of Bioinformatics and Intelligent Control, 2013, 2 (4) : 321-323