Integration of Ligand Field Molecular Mechanics in Tinker

The ligand field molecular mechanics (LFMM) method for transition-metal complexes has been integrated in Tinker, an easily available and popular molecular modeling software package. The capability to calculate LFMM potentials has been provided by extending the functional forms of the Tinker package as well as by integrating routines for calculating the ligand field stabilization energy (LFSE), which is central to LFMM. The capabilities of the implementation are illustrated by both static calculations on the two spin states of [Fe­(NH₃)₆]²⁺ and on [Cu­(NH₃)_<i>m</i>]²⁺ (<i>m</i> = 4, 5, 6) and dynamic (LFMD) simulations of an FeN₆-type spin-crossover compound. In addition to showing that results obtained with the Tinker-LFMM implementation are consistent with those of experiment and other computational methods and programs, we note that whereas LFMM is able to handle the conventional tetragonal Jahn–Teller distortion of the bond distances in [Cu­(NH₃)₆]²⁺, the LFSE term is also necessary in order to obtain even qualitatively correct coordination geometries for the two lower-coordinate copper complexes

Automated Building of Organometallic Complexes from 3D Fragments

A method for the automated construction of three-dimensional (3D) molecular models of organometallic species in design studies is described. Molecular structure fragments derived from crystallographic structures and accurate molecular-level calculations are used as 3D building blocks in the construction of multiple molecular models of analogous compounds. The method allows for precise control of stereochemistry and geometrical features that may otherwise be very challenging, or even impossible, to achieve with commonly available generators of 3D chemical structures. The new method was tested in the construction of three sets of active or metastable organometallic species of catalytic reactions in the homogeneous phase. The performance of the method was compared with those of commonly available methods for automated generation of 3D models, demonstrating higher accuracy of the prepared 3D models in general, and, in particular, a much wider range with respect to the kind of chemical structures that can be built automatically, with capabilities far beyond standard organic and main-group chemistry

Automated Design of Realistic Organometallic Molecules from Fragments

A method for the automated generation of realistic, synthetically accessible transition metal and organometallic complexes is described. Computational tools were designed to generate molecular fragments, preferably harvested from libraries of existing, stable compounds, to be used as building blocks for the construction of new molecules. These fragments are enriched with information about the number and type of possible connections to other fragments and are stored in library files. When connecting fragments in the subsequent building process, compatibility matrices, which define the connection rules between fragments, are used to delineate organometallic fragment spaces from which molecules can be generated in an automated fashion. The approach is flexible and allows ample structural variation at the same time as the combination of known fragments is easily restrained to avoid generation of exotic and unrealistic substructures and molecules. The method was tested in the generation of ruthenium complexes, with a given coordination environment, which can serve as candidates in catalyst development. The results demonstrate that molecules generated with the described method do not contain exotic arrangements of atoms and are by far more realistic than those obtained by the application of valence rules alone

Ring Closure To Form Metal Chelates in 3D Fragment-Based de Novo Design

We describe a method for the design of multicyclic compounds from three-dimensional (3D) molecular fragments. The 3D building blocks are assembled in a controlled fashion, and closable chains of such fragments are identified. Next, the ring-closing conformations of such formally closable chains are identified, and the 3D model of a cyclic or multicyclic molecule is built. Embedding this method in an evolutionary algorithm results in a de novo design tool capable of altering the number and nature of cycles in species such as transition metal compounds with multidentate ligands in terms of, for example, ligand denticity, type and length of bridges, identity of bridgehead terms, and substitution pattern. An application of the method to the design of multidentate nitrogen-based ligands for Fe­(II) spin-crossover (SCO) compounds is presented. The best candidates display multidentate skeletons new to the field of Fe­(II) SCO yet resembling ligands deployed in other fields of chemistry, demonstrating the capability of the approach to explore structural variation and to suggest unexpected and realistic molecules, including structures with cycles not found in the building blocks

Loss and Reformation of Ruthenium Alkylidene: Connecting Olefin Metathesis, Catalyst Deactivation, Regeneration, and Isomerization

Ruthenium-based olefin metathesis catalysts are used in laboratory-scale organic synthesis across chemistry, largely thanks to their ease of handling and functional group tolerance. In spite of this robustness, these catalysts readily decompose, via little-understood pathways, to species that promote double-bond migration (isomerization) in both the 1-alkene reagents and the internal-alkene products. We have studied, using density functional theory (DFT), the reactivity of the Hoveyda–Grubbs second-generation catalyst <b>2</b> with allylbenzene, and discovered a facile new decomposition pathway. In this pathway, the alkylidene ligand is lost, via ring expansion of the metallacyclobutane intermediate, leading to the spin-triplet 12-electron complex (SIMes)­RuCl₂ (^<b>3</b><b>R21</b>, SIMes = 1,3-bis­(2,4,6-trimethylphenyl)-4,5-dihydroimidazol-2-ylidene). DFT calculations predict ^<b>3</b><b>R21</b> to be a very active alkene isomerization initiator, either operating as a catalyst itself, via a η³-allyl mechanism, or, after spin inversion to give <b>R21</b> and formation of a cyclometalated Ru-hydride complex, via a hydride mechanism. The calculations also suggest that the alkylidene-free ruthenium complexes may regenerate alkylidene via dinuclear ruthenium activation of alkene. The predicted capacity to initiate isomerization is confirmed in catalytic tests using <i>p</i>-cymene-stabilized <b>R21</b> (<b>5</b>), which promotes isomerization in particular under conditions favoring dissociation of <i>p</i>-cymene and disfavoring formation of aggregates of <b>5</b>. The same qualitative trends in the relative metathesis and isomerization selectivities are observed in identical tests of <b>2</b>, indicating that <b>5</b> and <b>2</b> share the same catalytic cycles for both metathesis and isomerization, consistent with the calculated reaction network covering metathesis, alkylidene loss, isomerization, and alkylidene regeneration

Unsupervised Pattern Cognition Analysis (UPCA) and clustering of Ser hydrolases on the basis of BioGPS descriptors (global score).

<p>The enzymes are labelled according to their PDB code. Lipases are indicated in blue, esterases in green, amidases in red and proteases in cyan.</p

BioGPS Descriptors for Rational Engineering of Enzyme Promiscuity and Structure Based Bioinformatic Analysis

<div><p>A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space). The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of “pre-organized environment” able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS “roadmap”.</p></div

Unsupervised Pattern Cognition Analysis (UPCA) of BioGPS descriptors generated by O probe (H-bond donor capacity).

<p>The analyzed enzymes are labelled according to their PDB code and colored as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109354#pone-0109354-g003" target="_blank">figure 3</a>. Improved mutants are highlighted in black triangles whereas poor mutants are in pink triangles.</p

Unsupervised Pattern Cognition Analysis (UPCA) of BioGPS descriptors generated by H probe (shape).

<p>The enzymes are labelled according to their PDB code and colored as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109354#pone-0109354-g003" target="_blank">figure 3</a>. Improved mutants are highlighted in black triangles and poor mutants are in pink triangles.</p

Comparison of 1GVK (protease) and 2W22 (lipase) active site H-bond acceptor pseudo-MIFs.

<p>1GVK and 2W22 are represented as green and magenta cartoon respectively. 1GVK pseudo-MIFs are represented as green surfaces. 2W22 pseudo-MIFs are represented as magenta surfaces.</p