BioSolveIT have issued a new desktop app that gives easy and graphical access to searches in infinitely large chemical spaces of tangible molecules. The new infiniSee finds molecules based on a fuzzy pharmacophore-like similarity to an input query.

Users can swiftly mine from 5 billion (5 x 10⁹) Enamine REAL Space (not to be confused with the ten times smaller REAL database) — or use the company’s free KnowledgeSpace that is based on publically available building blocks and published reactions. More spaces are in the making, and the company has previously helped several pharmas create in-house spaces (Evotec, AstraZeneca, Merck etc.)

The output can be either directly purchased from BioSolveIT’s partner Enamine; alternatively users can synthesize the results themselves with a very high likelihood due to the setup of the chemical spaces. Classical library searches can certainly also be performed, these are processed quickly with parallel computing strategies that exploit multi-node architectures on standard computers and laptops.

Goodies include a forced match of user-selected subgroups; likewise very helpful is the 2D color-coding of molecular sketches that help the user understand the computed similarities. Results can be exported as SD files, remarkably with 3D coordinates on demand, or as CSV files for post-processing with a text editor. Queries may be masked to maintain IP safety.

Dark and light schemes are supported, and the software runs under Mac OSX, Windows 64bit, and Linux, not requiring any access to the external world, so that no user information is conveyed across the net.

The website and links to fully functional test installations is at https://www.biosolveit.de/infiniSee

DOCK 6.9 has been released.

This is a release of the new ligand searching method DOCKDN: De Novo design using fragment-based assembly. De novo design can be used to explore vast areas of chemical space in computational lead discovery. DOCKDN is an iterative fragment growth method, in which new molecules are built using rules for allowable connections based on known molecules.

For full information on what is new in DOCK 6.9

http://dock.compbio.ucsf.edu/DOCK6/newin_6.9.txt

 

Inte:Ligand have just announced the release of LigandScout 4.3.

The LigandScout software suite comprises the most user friendly molecular design tools available to chemists and modelers worldwide. The platform seamlessly integrates computational technology for designing, filtering, searching and prioritizing molecules for synthesis and biological assessment.

This is a significant update and expands LigandScout's molecular dynamics support. This update also now includes halogen binding as a new pharmacophoric element. In addition plotting has received an upgrade.

Furthermore, LigandScout 4.3 Expert introduces a completely new set of features summarized under the term Remote Execution. It is now possible to screen large compound libraries on remote High Performance Computing directly from within the graphical LigandScout user interface.

It can be downloaded here http://www.inteligand.com/ligandscout4/downloads/LigandScout43macos20181012.dmg

You can read about the technology behind LigandScout here DOI and there is a review of an earlier version here.

In addition there are now over 40 LigandScout nodes for KNIME.

KNIME Analytics Platform is the open source software for creating data science applications, workflows and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone.

 

cluster_mols is a PyMOL plugin that allows the user to quickly select compounds from a virtual screen to be purchased or synthesized.

The most up to date version (recommended) of clustermols is available through BitBucket at: https://bitbucket.org/mpb21/clustermols_py/overview

This plugin has a number of dependencies that are required. And it is currently only supported on Linux and OSX.

Baumgartner, Matthew (2016) IMPROVING RATIONAL DRUG DESIGN BY INCORPORATING NOVEL BIOPHYSICAL INSIGHT. Doctoral Dissertation, University of Pittsburgh.

 

In the previous workflow I described docking a set of ligands with known activity into a target protein, in this workflow we will be using a set of ligands from the ZINC dataset searching for novel ligands. Once docked the workflow moves on to finding vendors and selecting subsets for purchase.

 

Whilst high-throughput screening (HTS) has been the starting point for many successful drug discovery programs the cost of screening, the lack of access to a large diverse sample collection, or the low throughput of the primary assay may preclude HTS as a starting point and identification of a smaller selection of compounds with a higher probability of being a hit may be desired. Directed or Virtual screening is a computational technique used in drug discovery research designed to identify potential hits for evaluation in primary assays. It involves the rapid in silico assessment of large libraries of chemical structures in order to identify those structures that most likely to be active against a drug target. The in silico screen can be based on known ligand similarity or based on docking ligands into the desired binding site.

In this workflow I'll be looking at using docking to identify potential hits.

I've updated the description to give more information about preparing the target protein.

 

A publication currently in press, SwissSimilarity: A Web Tool for Low to Ultra High Throughput Ligand-Based Virtual Screening DOI describes a new web tool for virtual screening of vast virtual libraries.

SwissSimilarity is a new web tool for rapid ligand-based virtual screening of small to unprecedented ultralarge libraries of small molecules. Screenable compounds include drugs, bioactive and commercial molecules, as well as 205 million of virtual compounds readily synthesizable from commercially available synthetic reagents. Predictions can be carried out on-the-fly using six different screening approaches, including 2D molecular fingerprints as well as superpositional and fast nonsuperpositional 3D similarity methodologies. SwissSimilarity is part of a large initiative of the SIB Swiss Institute of Bioinformatics to provide online tools for computer-aided drug design, such as SwissDock, SwissBioisostere or SwissTargetPrediction with which it can interoperate, and is linked to other well-established online tools and databases. User interface and backend have been designed for simplicity and ease of use, to provide proficient virtual screening capabilities to specialists and nonexperts in the field.

The website is at http://www.swisssimilarity.ch.

One thing to bear in mind is that any potential hits from screening virtual libraries will require synthetic chemistry resources to make the molecules for confirmation!

 

ZINC is a free database of commercially-available compounds for virtual screening. ZINC contains over 100 million purchasable compounds in ready-to-dock, 3D formats. Sterling and Irwin, J. Chem. Inf. Model, 2015. This is an invaluable resource for any type of virtual screening or for anyone looking to create a physical screening or fragment collection.

Once you have done the virtual screening you will rapidly realise that the really time-consuming a tedious part now lies ahead. Finding out which vendors stock a particular molecule and then ordering them. Looking up the vendor details for individual compounds is extremely tedious and so this Vortex script may be very useful.

Many more scripts, iPython notebooks and tutorials can be found here.

 

DOCK 6 is written in C++ and is functionally separated into independent components, allowing a high degree of program flexibility. Accessory programs are written in C and Fortran 77. Source code for all programs is provided. Read the FAQ for details of installation under MacOSX.

Allen, W. J.; Balius, T. E.; Mukherjee, S.; Brozell, S. R.; Moustakas, D. T.; Lang, P. T.; Case, D. A.; Kuntz, I. D.; Rizzo, R. C. DOCK 6: Impact of New Features and Current Docking Performance. J. Comput. Chem. Submitted.