In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Neto, Lauro Ribeiro de Souza; Moreira-Filho, José Teófilo; Neves, Bruno J.; Maidana, Rocío Lucía Beatriz Riveros; Guimarães, Ana Carolina Ramos; Furnham, Nicholas; Andrade, Carolina Horta; Silva, Floriano Paes

doi:10.3389/fchem.2020.00093

Cited by 174 publications

(119 citation statements)

References 132 publications

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“…These methodologies provide indispensable information for the in silico screening of ligand fragments. 3,4 Thus, the combination of SBDD or FBDD with articial intelligence can lead to cost-effective and high-throughput drug development in the future.…”

Section: Introductionmentioning

confidence: 99%

Room-temperature crystallography using a microfluidic protein crystal array device and its application to protein–ligand complex structure analysis

et al. 2020

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Section: Introductionmentioning

confidence: 99%

Room-temperature crystallography using a microfluidic protein crystal array device and its application to protein–ligand complex structure analysis

et al. 2020

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“…To compare AutoGrow4 lead optimization to a more traditional similarity-based virtual screening (VS) approach [40,41], we generated a library of small molecules that are structurally similar to known PARPi. We downloaded the structures of ~2200 known PARPi from the BindingDB database [42,43] on March 14, 2020.…”

Section: Parpi-like Compounds: Autogrow4 Optimization Vs Similarity-mentioning

confidence: 99%

“…Similarity-based virtual screening (VS) is a popular technique for in silico ligand optimization [40,41]. One first generates a library of compounds that are chemically similar to known ligands.…”

Section: Autogrow4 Vs Other Docking Techniques For Lead Optimizationmentioning

confidence: 99%

AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization

2020

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We here present AutoGrow4, an open-source program for semi-automated computer-aided drug discovery. Auto-Grow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of pre-enumerated compounds. It is a useful tool for generating entirely novel drug-like molecules and for optimizing preexisting ligands. By leveraging recent computational and cheminformatics advancements, AutoGrow4 is faster, more stable, and more modular than previous versions. It implements new docking-program compatibility, chemical filters, multithreading options, and selection methods to support a wide range of user needs. To illustrate both de novo design and lead optimization, we here apply AutoGrow4 to the catalytic domain of poly(ADP-ribose) polymerase 1 (PARP-1), a well characterized DNA-damage-recognition protein. AutoGrow4 produces drug-like compounds with better predicted binding affinities than FDA-approved PARP-1 inhibitors (positive controls). The predicted binding modes of the AutoGrow4 compounds mimic those of the known inhibitors, even when AutoGrow4 is seeded with random small molecules. AutoGrow4 is available under the terms of the Apache License, Version 2.0. A copy can be downloaded free of charge from http://durra ntlab .com/autog row4.

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“…Natural product-like and druglike molecules can further expand the degree of scaffold diversity beyond PNPs by adding or changing heteroatoms, tuning ring size and linkers, as well as assembly of privileged substructures. Empirical scaffold reproducing and mimicking of natural products may be upgraded to systematic scaffold analysis and rational design under the guidance of computational chemistry, big data, and artificial intelligence (Yang et al, 2019;Neto et al, 2020). With further development of the above methods and emergence of novel strategies and technologies, the application of alkyne-involved one-pot cyclizations will be expanded for more diverse polycyclic scaffolds and finally proved to be powerful synthetic toolkit for both natural products and medicinal chemistry.…”

Section: Summary and Perspectivesmentioning

confidence: 99%

Recent Advances in Construction of Polycyclic Natural Product Scaffolds via One-Pot Reactions Involving Alkyne Annulation

Zheng

Hua

2020

Front. Chem.

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Polycyclic scaffolds are omnipresent in natural products and drugs, and the synthetic strategies and methods toward construction of these scaffolds are of particular importance. Compared to simple cyclic ring systems, polycyclic scaffolds have higher structure complexity and diversity, making them suitable for charting broader chemical space, yet bringing challenges for the syntheses. In this review, we surveyed progress in the past decade on synthetic methods for polycyclic natural product scaffolds, in which the key steps are one-pot reactions involving intermolecular or intramolecular alkyne annulation. Synthetic strategies of selected polycyclic carbocycles and heterocycles with at least three fused, bridged, or spiro rings are discussed with emphasis on the synthetic efficiency and product diversity. Recent examples containing newly developed synthetic concepts or toolkits such as collective and divergent total synthesis, gold catalysis, C-H functionalization, and dearomative cyclization are highlighted. Finally, several "privileged synthetic strategies" for "privileged polycyclic scaffolds" are summarized, with discussion of remained challenges and future perspectives.

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In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Cited by 174 publications

References 132 publications

Room-temperature crystallography using a microfluidic protein crystal array device and its application to protein–ligand complex structure analysis

Room-temperature crystallography using a microfluidic protein crystal array device and its application to protein–ligand complex structure analysis

AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization

Recent Advances in Construction of Polycyclic Natural Product Scaffolds via One-Pot Reactions Involving Alkyne Annulation

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