Computer-aided, systematic search of peptide conformations constrained by NMR data

Area of Science:

• Computational chemistry
• Structural biology
• Organic chemistry

Background:

• Conformational analysis of medium-sized rings is computationally challenging.
• Experimental data, such as Nuclear Magnetic Resonance (NMR) measurements, are crucial for validating structural models.
• Previous methods lacked comprehensive exploration of the conformational space for these ring systems.

Purpose of the Study:

• To develop an efficient computer program for exhaustive conformational exploration of medium-sized rings (8-22 members).
• To integrate experimental NMR data, including dihedral angles (Karplus equation) and Nuclear Overhauser Effect (NOE) close contacts, into the conformational search.
• To demonstrate the program's utility by applying it to a cyclic hexapeptide somatostatin analogue.

Main Methods:

• Development of a novel computational algorithm for conformational searching.
• Implementation of methods to incorporate dihedral angle constraints derived from the Karplus equation.
• Integration of Nuclear Overhauser Effect (NOE) data to identify close spatial contacts.
• Application of the program to a specific cyclic hexapeptide somatostatin analogue.

Main Results:

• The program allows for exhaustive exploration of the conformational landscape of medium-sized rings.
• Successful integration of experimental NMR data (dihedral angles and NOE contacts) refines conformational possibilities.
• Efficient computational principles ensure high performance in exploring complex conformational spaces.
• The study demonstrates the program's effectiveness in analyzing the structure of a somatostatin analogue.

Conclusions:

• The developed computer program provides a powerful tool for detailed conformational analysis of medium-sized rings.
• Integration of experimental NMR data significantly enhances the accuracy and reliability of conformational predictions.
• This approach is valuable for studying complex cyclic molecules, including peptide analogues relevant to drug discovery.