Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

Is primary surgery of breast cancer patients consistent with German guidelines? Twelve-year trend of population-based clinical cancer registry data.

This population-based analysis aimed to describe the 12-year trend of primary surgery following the introduction of national guidelines for the management of breast cancer in Germany, thus the implementation of breast-conserving surgery (BCS) for pT1/2-tumours and the implementation of sentinel lymph node biopsy (SLNB). Cancer registry data from 72 742 breast cancer patients diagnosed between 1999 and 2010 in four different regions in Germany were used. Descriptive statistics and multivariate logistic regression analysis were conducted. Between 1999 and 2010, rates of BCS for pT1/2-tumours rose from 60.5% to 79.9%, rates of SLNB increased rapidly from 0.4% to 79.0%. Both surgical therapies were already adherent to the respective guidelines, although some regional differences could be observed: in 1999-2003, the chance of BCS was 2.6-fold higher [odds ratio (OR) 2.6] in the western regions than in the eastern regions, but this difference decreased over time (2004-2007 OR 1.6; 2008-2010 OR 1.2). A similar pattern was observable for SLNB: in 1999-2003, the chance of receiving SLNB was 4.4-fold higher in the western regions, but these rates converged (2004-2007 OR 3.7; 2008-2010 OR 1.5). The further increase of BCS- and SLNB rates after publication of guidelines and the reduction of regional differences may also be attributable to guideline implementation.

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

We present a supercomputer-driven pipeline for in-silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. We also describe preliminary results obtained for 23 systems involving eight protein targets of the proteome of SARS CoV-2. THe MD performed is temperature replica-exchange enhanced sampling, making use of the massively parallel supercomputing on the SUMMIT supercomputer at Oak Ridge National Laboratory, with which more than 1ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to ten configurations of each of the 23 SARS CoV-2 systems using AutoDock Vina. We also demonstrate that using Autodock-GPU on SUMMIT, it is possible to perform exhaustive docking of one billion compounds in under 24 hours. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and AI methods to cluster MD trajectories and rescore docking poses.

Synthesis of 2,3-dihydroindoles, indoles, and anilines by transition metal-free amination of aryl chlorides.

Aliphatic and aromatic amines react with 2- and 3-chlorostyrene in the presence of potassium tert-butoxide to give N-substituted 2,3-dihydroindoles in good yields. The combination of this domino-amination protocol with a suitable dehydrogenation reaction gives access to pharmacologically interesting indoles in a one-pot procedure. Overall product yields of N-substituted indoles >50% are obtained by this method starting from commercially available substrates. In addition to the intramolecular base-promoted amination of aromatic C-Cl bonds, metal-free intermolecular aminations of aryl chlorides with primary and secondary amines are described. The use of potassium tert-butoxide as base allows the synthesis of various anilines in good to excellent yields. Due to the formation of aryne intermediates, either N-substituted anilines or meta-substituted anilines are produced with excellent selectivities.

A convenient rhodium-catalyzed intermolecular hydroamination procedure for terminal alkynes.

The first rhodium-catalyzed intermolecular hydroamination of alkynes is presented. Terminal alkynes react efficiently with anilines in the presence of cationic rhodium(I) catalysts under very mild reaction conditions (e.g., base and acid free at room temperature) to yield up to 99% of the corresponding imines. An easy one-pot protocol for the synthesis of secondary amines was developed by combining this alkyne amination reaction with in situ addition of organolithium reagents.