Sandeep Kumar

Structured disorder and conformational selection.

Traditionally, molecular disorder has been viewed as local or global instability. Molecules or regions displaying disorder have been considered inherently unstructured. The term has been routinely applied to cases for which no atomic coordinates can be derived from crystallized molecules. Yet, even when it appears that the molecules are disordered, prevailing conformations exist, with population times higher than those of all alternate conformations. Disordered molecules are the outcome of rugged energy landscapes away from the native state around the bottom of the funnel. Ruggedness has a biological function, creating a distribution of structured conformers that bind via conformational selection, driving association and multimolecular complex formation, whether chain‐linked in folding or unlinked in binding. We classify disordered molecules into two types. The first type possesses a hydrophobic core. Here, even if the native conformation is unstable, it still has a large enough population time, enabling its experimental detection. In the second type, no such hydrophobic core exists. Hence, the native conformations of molecules belonging to this category have shorter population times, hindering their experimental detection. Although there is a continuum of distribution of hydrophobic cores in proteins, an empirical, statistically based hydrophobicity function may be used as a guideline for distinguishing the two disordered molecule types. Furthermore, the two types relate to steps in the protein folding reaction. With respect to protein design, this leads us to propose that engineering‐optimized specific electrostatic interactions to avoid electrostatic repulsion would reduce the type I disordered state, driving the molten globule (MG) → native (N) state. In contrast, for overcoming the type II disordered state, in addition to specific interactions, a stronger hydrophobic core is also indicated, leading to the denatured → MG → N state. Proteins 2001;44:418–427.

HELANAL: A Program to Characterize Helix Geometry in Proteins

Abstract A detailed analysis of structural and position dependent characteristic features of helices will give a better understanding of the secondary structure formation in globular proteins. Here we describe an algorithm that quantifies the geometry of helices in proteins on the basis of their Cα atoms alone. The Fortran program HELANAL can extract the helices from the PDB files and then characterises the overall geometry of each helix as being linear, curved or kinked, in terms of its local structural features, viz. local helical twist and rise, virtual torsion angle, local helix origins and bending angles between successive local helix axes. Even helices with large radius of curvature are unambiguously identified as being linear or curved. The program can also be used to differentiate a kinked helix and other motifs, such as helix-loop-helix or a helix-turn-helix (with a single residue linker) with the help of local bending angles. In addition to these, the program can also be used to characterise the helix start and end as well as other types of secondary structures.

Dissecting α-helices: Position-specific analysis of α-helices in globular proteins

An analysis of the amino acid distributions at 15 positions, viz., N“, N′, Ncap, N1, N2, N3, N4, Mid, C4, C3, C2, C1, Ccap, C′, and C” in 1,131 α‐helices reveals that each position has its own unique characteristics. In general, natural helix sequences optimize by identifying the residues to be avoided at a given position and minimizing the occurrence of these avoided residues rather than by maximizing the preferred residues at various positions. Ncap is most selective in its choice of residues, with six amino acids (S, D, T, N, G, and P) being preferred at this position and another 11 (V, I, F, A, K, L, Y, R, E, M, and Q) being strongly avoided. Ser, Asp, and Thr are all more preferred at Ncap position than Asn, whose role at helix N‐terminus has been highlighted by earlier analyses. Furthermore, Asn is also found to be almost equally preferred at helix C‐terminus and a novel structural motif is identified, involving a hydrogen bond formed by Nδ2 of Asn at Ccap or C1 position, with the backbone carbonyl oxygen four residues inside the helix. His also forms a similar motif at the C‐terminus. Pro is the most avoided residue in the main body (N4 to C4 positions) and at C‐ter‐minus, including Ccap of an α‐helix. In 1,131 α‐helices, no helix contains Pro at C3 or C2 positions. However, Pro is highly favoured at N1 and C′. The doublet X‐Pro, with Pro at C′ position and extended backbone conformation for the X residue at Ccap, appears to be a common structural motif for termination of α‐helices, in addition to the Schellman motif. Main body of the helix shows a high preference for aliphatic residues Ala, Leu, Val, and Ile, while these are avoided at helix termini. A propensity scale for amino acids to occur in the middle of helices has been obtained. Comparison of this scale with several previously reported scales shows that this scale correlates best with the experimentally determined values. Proteins 31:460–476, 1998.

Electrostatic Strengths of Salt Bridges in Thermophilic and Mesophilic Glutamate Dehydrogenase Monomers

Here we seek to understand the higher frequency of occurrence of salt bridges in proteins from thermophiles as compared to their mesophile homologs. We focus on glutamate dehydrogenase, owing to the availability of high resolution thermophilic (from Pyrococcus furiosus) and mesophilic (from Clostridium symbiosum) protein structures, the large protein size and the large difference in melting temperatures. We investigate the location, statistics and electrostatic strengths of salt bridges and of their networks within corresponding monomers of the thermophilic and mesophilic enzymes. We find that many of the extra salt bridges which are present in the thermophilic glutamate dehydrogenase monomer but absent in the mesophilic enzyme, form around the active site of the protein. Furthermore, salt bridges in the thermostable glutamate dehydrogenase cluster within the hydrophobic folding units of the monomer, rather than between them. Computation of the electrostatic contribution of salt bridge energies by solving the Poisson equation in a continuum solvent medium, shows that the salt bridges in Pyrococcus furiosus glutamate dehydrogenase are highly stabilizing. In contrast, the salt bridges in the mesophilic Clostridium symbiosum glutamate dehydrogenase are only marginally stabilizing. This is largely the outcome of the difference in the protein environment around the salt bridges in the two proteins. The presence of a larger number of charges, and hence, of salt bridges contributes to an electrostatically more favorable protein energy term. Our results indicate that salt bridges and their networks may have an important role in resisting deformation/unfolding of the protein structure at high temperatures, particularly in critical regions such as around the active site. Proteins 2000;38:368–383. Published 2000 Wiley‐Liss, Inc.

Geometrical and sequence characteristics of α-helices in globular proteins

Understanding the sequence-structure relationships in globular proteins is important for reliable protein structure prediction and de novo design. Using a database of 1131

Different Roles of Electrostatics in Heat and in Cold: Adaptation by Citrate Synthase

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Folding Funnels and Conformational Transitions Via Hinge-Bending Motions

-helices with nonidentical sequences from 205 nonhomologous globular protein chains, we have analyzed structural and sequence characteristics of

Structural and sequence characteristics of long alpha helices in globular proteins.

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Contribution of salt bridges toward protein thermostability.

helices. We find that geometries of more than 99% of all the

Protein Folding and Function: The N-Terminal Fragment in Adenylate Kinase

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