26 papers · ranked by Valyu relevance
Fernanda I. Saldívar-González, C. Sebastian Huerta-García, José L. Medina-Franco
Virtual compound libraries are increasingly being used in computer-assisted drug discovery applications and have led to numerous successful cases. This paper aims to examine the fundamental concepts of library design and describe how to enumerate virtual libraries using open source tools. To exemplify the enumeration…
Dionisio A. Olmedo, Armando A. Durant-Archibold, José Luis López-Pérez, Jose L. Medina-Franco
Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a…
Beatriz Suay-García, Jose I. Bueso-Bordils, Antonio Falcó, Gerardo M. Antón-Fos + 3 more
'Gerardo M. Antón-Fos' 'Pedro A. Alemán-López' 'Gary A. Piazza' 'Jia-Zhong Li'] Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as…
Gergely Takács, Dávid Havasi, Márk Sándor, Zsolt Dohánics + 2 more
Chemical Libraries - Novel Starting Points for Drug Discovery Authors: ['Gergely Takács' 'Dávid Havasi' 'Márk Sándor' 'Zsolt Dohánics' 'György T. Balogh' 'Róbert Kiss'] The advancement of in silico technologies such as library enumeration and synthetic feasibility prediction has made drug discovery pipelines rely more…
Domiziana Cecchini, AkshatKumar Nigam, Ming Tang, Joana Reis + 43 more
Identifying potent lead molecules for specific targets remains a major bottleneck in drug discovery. As structural information about proteins becomes increasingly available, ultra-large virtual screenings (ULVSs) which computationally evaluate billions of molecules offer a powerful way to accelerate early-stage drug…
Melvin J Yu
Background There is a growing body of literature describing the properties of marketed drugs, the concept of drug-likeness and the vastness of chemical space. In that context, enumerative combinatorics with simple atomic components may be useful in the conception and design of structurally novel compounds for expanding…
Megan Stanley, Marwin Segler
Computational techniques, including virtual screening, de novo design, and generative models, play an increasing role in expediting DMTA cycles for modern molecular discovery. However, computationally proposed molecules must be synthetically feasible for laboratory testing. In this perspective, we offer a succinct…
Kairi Furui, Masahito Ohue
—Learning-to-rank, a machine learning technique widely used in information retrieval, has recently been applied to the problem of ligand-based virtual screening to accelerate the early stages of new drug development. Ranking prediction models learn based on ordinal relationships, making them suitable for integrating…
María Virginia Sabando, Pavol Ulbrich, Matías Nicolás Selzer, Jan Byška + 5 more
*These authors contributed equally. - • M. V. Sabando, I. Ponzoni, and A. J. Soto are with the Institute for Computer Science and Engineering (UNS–CONICET) and with the Department of Computer Science and Engineering, Universidad Nacional del Sur, Bah´ıa Blanca, Argentina. E-mails: virginia.sabando@cs.uns.edu.ar…
N. Arul Murugan, Artur Podobas, Davide Gadioli, Emanuele Vitali + 2 more
'Gianluca Palermo' 'Stefano Markidis'] Drug discovery is the most expensive, time demanding and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high affinity binding and specificity…
Thomas Descoteaux, Rafael Najmanovich
NRGRank is a coarse-grained structurally-informed software capable of performing ultra-massive virtual screening with accuracy comparable to docking-based methodologies but with 100 fold speed increase. NRGRank is based on a coarse-grained evaluation of pairwise atom-type pseudo-energy interactions that implicitly…
Sebastian Raschka, Anne M. Scott, Nan Liu, Santosh Gunturu + 3 more
While the advantage of screening vast databases of molecules to cover greater molecular diversity is often mentioned, in reality, only a few studies have been published demonstrating inhibitor discovery by screening more than a million compounds for features that mimic a known three-dimensional ligand. Two factors…
Atsuto Seko, Atsushi Togo, Hiroyuki Hayashi, Koji Tsuda + 2 more
'Laurent Chaput' 'Isao Tanaka'] Compounds of low lattice thermal conductivity (LTC) are essential for seeking thermoelectric materials with high conversion efficiency. Some strategies have been used to decrease LTC. However, such trials have yielded successes only within a limited exploration space. Here we report the…
Huikun Zhang, Spencer S. Ericksen, Ching-pei Lee, Gene E. Ananiev + 7 more
Prediction of compounds that are active against a desired biological target is a common step in drug discovery efforts. Virtual screening methods seek some active-enriched fraction of a library for experimental testing. Where data are too scarce to train supervised learning models for compound prioritization, initial…
Seth F. Vigneron, Shohei Ohno, Joao Braz, Joseph Y. Kim + 9 more
Large library docking of tangible molecules has revealed potent ligands across many targets. While make-on-demand libraries now exceed 75 billion enumerated molecules, their synthetic routes are dominated by a few reaction types, reducing diversity and inevitably leaving many interesting bioactive-like chemotypes…
Michael J. Wasko, Kendy A. Pellegrene, Jeffry D. Madura, Christopher K. Surratt
'Christopher K. Surratt'] Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly…
Shengchao Liu, Moayad Alnammi, Spencer S. Ericksen, Andrew F. Voter + 4 more
Virtual (computational) high-throughput screening provides a strategy for prioritizing compounds for experimental screens, but the choice of virtual screening algorithm depends on the dataset and evaluation strategy. We consider a wide range of ligand-based machine learning and docking-based approaches for virtual…
Li-hsing Wang, Andreas Evers, Peter Monecke, Thorsten Naumann
In pharmaceutical industry ligand based approaches like scaffold hopping, scaffold decoration and me-too approaches, are used to generate lead structures in discovery projects. We use several tools to generate novel lead structures, such as BROOD [1]. BROOD is a software tool which explores chemical space around query…
Authors not listed
Fragment-based drug discovery (FBDD) is a key strategy employed in the hit-to-lead phase of pharmaceu-tical development. The rate limiting step of this process is often identifying and optimising synthetic chem-istry suitable for fragment elaboration, especially in 3-dimensions (3-D). To address this limitation, we…
Daniel V. Samarov, J. S. Marron, Yufeng Liu, Chris Grulke + 1 more
'Alexander Tropsha'] > Drug discovery is the process of identifying compounds which have potentially meaningful biological activity. A major challenge that arises is that the number of compounds to search over can be quite large, sometimes numbering in the millions, making experimental testing intractable. For this…
Authors not listed
Triarylboranes (BAr3) is one of the most important classes of Lewis acid catalyst. However, their molecular design still largely relies on the typical experimental trial-and-error strategy. Here, we introduced the virtual borane (VB) method—a novel computational approach for design of triarylborane catalysts—based on…
Authors not listed
Heteroaromatics are the basis for many pharmaceuticals. The ability to modify these structures through selective core-atom transformations, or "skeletal edits", can dramatically expand the landscape for drug discovery and development. However, despite the importance of core-atom modifications, the quantitative impact…
Gaiane Panina
It is known that the k-faces of the permutohedron Πn can be labeled by (all possible) linearly ordered partitions of the set [n] = {1, ..., n} into (n − k) non-empty parts. The incidence relation corresponds to the refinement: a face F contains a face F ′ whenever the label of F ′ refines the label of F.
Sharon Pinus, Jérôme Genzling, Mihai Burai-Patrascu, Nicolas Moitessier
Computational asymmetric catalysis has seen an impressive rise in the last twenty years, thanks to advancements in algorithm and method development for predicting catalyst enantioselectivity. These methods/algorithms describe reactions that can be categorized into two groups: reactions where 1) knowledge of the…
Alla Katsnelson
Products Supernatural Authors: Alla Katsnelson As these capabilities add up, chemists are able to be more ambitious in their synthetic planning and to explore variations in the chemical structures in ways that were not previously conceivable. In an example of such work [published earlier this year](), Andrew Myers at…
Authors not listed
High-throughput virtual screening campaigns are invaluable for surveying the combinatorial space of possible transition metal complexes (TMCs), but they rely on accurate metal–ligand connectivity for meaningful results. Here, we curate a dataset of 70,069 unique ligands of known coordination from experimental…