6 research outputs found
DENOPTIM: Software for Computational de Novo Design of Organic and Inorganic Molecules
A general-purpose software package, termed DE Novo OPTimization of In/organic Molecules (DENOPTIM), for de novo design and virtual screening of functional molecules is described. Molecules of any element and kind, including metastable species and transition states, are handled as chemical objects that go beyond valence-rules representations. Synthetic accessibility of the generated molecules is ensured via detailed control of the kinds of bonds that are allowed to form in the automated molecular building process. DENOPTIM contains a combinatorial explorer for screening and a genetic algorithm for global optimization of user-defined properties. Estimates of these properties may be obtained to form the fitness function (figure of merit or scoring function) from external molecular modeling programs via shell scripts. Examples of a range of different fitness functions and DENOPTIM applications, including an easy-to-do test case, are described. DENOPTIM is available as Open Source from https://github.com/denoptim-project/DENOPTIM.acceptedVersio
Molassembler: Molecular graph construction, modification and conformer generation for inorganic and organic molecules
We present the graph-based molecule software Molassembler for building
organic and inorganic molecules. Molassembler provides algorithms for the
construction of molecules built from any set of elements from the periodic
table. In particular, poly-nuclear transition metal complexes and clusters can
be considered. Structural information is encoded as a graph. Stereocenter
configurations are interpretable from Cartesian coordinates into an abstract
index of permutation for an extensible set of polyhedral shapes. Substituents
are distinguished through a ranking algorithm. Graph and stereocenter
representations are freely modifiable and chiral state is propagated where
possible through incurred ranking changes. Conformers are generated with full
stereoisomer control by four spatial dimension Distance Geometry with a
refinement error function including dihedral terms. Molecules are comparable by
an extended graph isomorphism and their representation is canonicalizeable.
Molassembler is written in C++ and provides Python bindings.Comment: 81 pages, 26 figures, 3 table
Computational Ligand Descriptors for Catalyst Design
Ligands,
especially phosphines and carbenes, can play a key role
in modifying and controlling homogeneous organometallic catalysts,
and they often provide a convenient approach to fine-tuning the performance
of known catalysts. The measurable outcomes of such catalyst modifications
(yields, rates, selectivity) can be set into context by establishing
their relationship to steric and electronic descriptors of ligand
properties, and such models can guide the discovery, optimization,
and design of catalysts. In this review we present a survey of calculated
ligand descriptors, with a particular focus on homogeneous organometallic
catalysis. A range of different approaches to calculating steric and
electronic parameters are set out and compared, and we have collected
descriptors for a range of representative ligand sets, including 30
monodentate phosphorus(III) donor ligands, 23 bidentate P,P-donor
ligands, and 30 carbenes, with a view to providing a useful resource
for analysis to practitioners. In addition, several case studies of
applications of such descriptors, covering both maps and models, have
been reviewed, illustrating how descriptor-led studies of catalysis
can inform experiments and highlighting good practice for model comparison
and evaluation
Structure generation and de novo design using reaction networks
This project is concerned with de novo molecular design whereby novel molecules are built in silico and evaluated against properties relevant to biological activity, such as physicochemical properties and structural similarity to active compounds. The aim is to encourage cost-effective compound design by reducing the number of molecules requiring synthesis and analysis.
One of the main issues in de novo design is ensuring that the molecules generated are synthesisable. In this project, a method is developed that enables virtual synthesis using rules derived from reaction sequences. Individual reactions taken from reaction databases were connected to form reaction networks. Reaction sequences were then extracted by tracing paths through the network and used to create ‘reaction sequence vectors’ (RSVs) which encode the differences between the start and end points of th esequences. RSVs can be applied to molecules to generate virtual products which are
based on literature precedents.
The RSVs were applied to structure-activity relationship (SAR) exploration using examples taken from the literature. They were shown to be effective in expanding the chemical space that is accessible from the given starting materials. Furthermore, each virtual product is associated with a potential synthetic route. They were then applied in de novo design scenarios with the aim of generating molecules that are predicted to be active using SAR models. Using a collection of RSVs with a set of small molecules as starting materials for de novo design proved that the method was capable of producing
many useful, synthesisable compounds worthy of future study.
The RSV method was then compared with a previously published method that is based on individual reactions (reaction vectors or RVs). The RSV approach was shown to be considerably faster than de novo design using RVs, however, the diversity of products was more limited
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