Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation

Selective Pharmacological Targeting of a DEAD Box RNA Helicase

RNA helicases represent a large family of proteins implicated in many biological processes including ribosome biogenesis, splicing, translation and mRNA degradation. However, these proteins have little substrate specificity, making inhibition of selected helicases a challenging problem. The prototypical DEAD box RNA helicase, eIF4A, works in conjunction with other translation factors to prepare mRNA templates for ribosome recruitment during translation initiation. Herein, we provide insight into the selectivity of a small molecule inhibitor of eIF4A, hippuristanol. This coral-derived natural product binds to amino acids adjacent to, and overlapping with, two conserved motifs present in the carboxy-terminal domain of eIF4A. Mutagenesis of amino acids within this region allowed us to alter the hippuristanol-sensitivity of eIF4A and undertake structure/function studies. Our results provide an understanding into how selective targeting of RNA helicases for pharmacological intervention can be achieved

The C-terminal domain of eukaryotic initiation factor 5 promotes start codon recognition by its dynamic interplay with eIF1 and eIF2 beta

Recognition of the proper start codon on mRNAs is essential for protein synthesis, which requires scanning and involves eukaryotic initiation factors (eIFs) eIF1, eIF1A, eIF2, and eIF5. The carboxyl terminal domain (CTD) of eIF5 stimulates 43S preinitiation complex (PIC) assembly; however, its precise role in scanning and start codon selection has remained unknown. Using nuclear magnetic resonance (NMR) spectroscopy, we identified the binding sites of eIF1 and eIF2β on eIF5-CTD and found that they partially overlapped. Mutating select eIF5 residues in the common interface specifically disrupts interaction with both factors. Genetic and biochemical evidence indicates that these eIF5-CTD mutations impair start codon recognition and impede eIF1 release from the PIC by abrogating eIF5-CTD binding to eIF2β. This study provides mechanistic insight into the role of eIF5-CTD's dynamic interplay with eIF1 and eIF2β in switching PICs from an open to a closed state at start codons.publishedVersio

Interatomic potentials and solvation parameters from protein engineering data for buried residues

Van der Waals (vdW) interaction energies between different atom types, energies of hydrogen bonds (H‐bonds), and atomic solvation parameters (ASPs) have been derived from the published thermodynamic stabilities of 106 mutants with available crystal structures by use of an originally designed model for the calculation of free‐energy differences. The set of mutants included substitutions of uncharged, inflexible, water‐inaccessible residues in α‐helices and β‐sheets of T4, human, and hen lysozymes and HI ribonuclease. The determined energies of vdW interactions and H‐bonds were smaller than in molecular mechanics and followed the “like dissolves like” rule, as expected in condensed media but not in vacuum. The depths of modified Lennard‐Jones potentials were −0.34, −0.12, and −0.06 kcal/mole for similar atom types (polar–polar, aromatic–aromatic, and aliphatic–aliphatic interactions, respectively) and −0.10, −0.08, −0.06, −0.02, and nearly 0 kcal/mole for different types (sulfur–polar, sulfur–aromatic, sulfur–aliphatic, aliphatic–aromatic, and carbon–polar, respectively), whereas the depths of H‐bond potentials were −1.5 to −1.8 kcal/mole. The obtained solvation parameters, that is, transfer energies from water to the protein interior, were 19, 7, −1, −21, and −66 cal/moleÅ 2 for aliphatic carbon, aromatic carbon, sulfur, nitrogen, and oxygen, respectively, which is close to the cyclohexane scale for aliphatic and aromatic groups but intermediate between octanol and cyclohexane for others. An analysis of additional replacements at the water–protein interface indicates that vdW interactions between protein atoms are reduced when they occur across water.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106915/1/111984_ftp.pd

LED‐Illuminated NMR Spectroscopy: A Practical Tool for Mechanistic Studies of Photochemical Reactions

This Concept article highlights the development of a novel analytical tool, LED-NMR (a combination of in situ light illumination using a light-emitting diode and NMR spectroscopy) and its variant UVNMR (LED-NMR coupled with UV/Vis absorption spectroscopy), as well as their applications in the mechanistic investigation of light-induced transformations. The utility of these new tools has been demonstrated by providing rich kinetic and structural data of reaction species offering mechanistic insights into photochemical and photocatalytic reactions. Furthermore, NMR actinometry has been recently developed as a practical and simple method for quantum yield measurements. Quantum yield is an important parameter in photo-induced processes, but is rarely measured in practice because of the barriers associated with traditional actinometry. These new tools and techniques streamline measurements of the quantum efficiency while affording informative mechanistic insights into photochemical reactions. We anticipate these techniques will enable chemists to further advance the rapidly emerging photochemistry field

Facile Quantum Yield Determination via NMR Actinometry

A simplified approach to quantum yield (ϕ) measurement using in situ LED NMR spectroscopy has been developed. The utility and performance of NMR actinometry has been demonstrated for the well-known chemical actinometers potassium ferrioxalate and <i>o</i>-nitrobenzaldehyde. A novel NMR-friendly actinometer, 2,4-dinitrobenzaldehyde, has been introduced for both 365 and 440 nm wavelengths. The method has been utilized successfully to measure the quantum yield of several recently published photochemical reactions

Complex macrocycle exploration: parallel, heuristic, and constraint-based conformer generation using ForceGen.

ForceGen is a template-free, non-stochastic approach for 2D to 3D structure generation and conformational elaboration for small molecules, including both non-macrocycles and macrocycles. For conformational search of non-macrocycles, ForceGen is both faster and more accurate than the best of all tested methods on a very large, independently curated benchmark of 2859 PDB ligands. In this study, the primary results are on macrocycles, including results for 431 unique examples from four separate benchmarks. These include complex peptide and peptide-like cases that can form networks of internal hydrogen bonds. By making use of new physical movements ("flips" of near-linear sub-cycles and explicit formation of hydrogen bonds), ForceGen exhibited statistically significantly better performance for overall RMS deviation from experimental coordinates than all other approaches. The algorithmic approach offers natural parallelization across multiple computing-cores. On a modest multi-core workstation, for all but the most complex macrocycles, median wall-clock times were generally under a minute in fast search mode and under 2 min using thorough search. On the most complex cases (roughly cyclic decapeptides and larger) explicit exploration of likely hydrogen bonding networks yielded marked improvements, but with calculation times increasing to several minutes and in some cases to roughly an hour for fast search. In complex cases, utilization of NMR data to constrain conformational search produces accurate conformational ensembles representative of solution state macrocycle behavior. On macrocycles of typical complexity (up to 21 rotatable macrocyclic and exocyclic bonds), design-focused macrocycle optimization can be practically supported by computational chemistry at interactive time-scales, with conformational ensemble accuracy equaling what is seen with non-macrocyclic ligands. For more complex macrocycles, inclusion of sparse biophysical data is a helpful adjunct to computation