Fragment-to-lead tailored in silico design
Tài liệu tham khảo
Erlanson, 2016, Twenty years on: the impact of fragments on drug discovery, Nat Rev Drug Discov, 15, 605, 10.1038/nrd.2016.109
Hopkins, 2004, Ligand efficiency: a useful metric for lead selection, Drug Discov Today, 9, 430, 10.1016/S1359-6446(04)03069-7
Hann, 2001, Molecular complexity and its impact on the probability of finding leads for drug discovery, J Chem Inf Comput Sci, 41, 856, 10.1021/ci000403i
Polishchuk, 2013, Estimation of the size of drug-like chemical space based on GDB-17 data, J Comput Aided Mol Des, 27, 675, 10.1007/s10822-013-9672-4
Ruddigkeit, 2012, Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17, J Chem Inf Model, 52, 2864, 10.1021/ci300415d
Schneider, 2005, Computer-based de novo design of drug-like molecules, Nat Rev Drug Discov, 4, 649, 10.1038/nrd1799
Kutchukian, 2010, De novo design: balancing novelty and confined chemical space, Expert Opin Drug Discov, 5, 789, 10.1517/17460441.2010.497534
Irwin, 2005, ZINC - A free database of commercially available compounds for virtual screening, J Chem Inf Model, 45, 177, 10.1021/ci049714+
Sterling, 2015, ZINC 15 - ligand discovery for everyone, J Chem Inf Model, 55, 2324, 10.1021/acs.jcim.5b00559
Lyu, 2019, Ultra-large library docking for discovering new chemotypes, Nature, 566, 224, 10.1038/s41586-019-0917-9
Barril, 2017, Computer-aided drug design: time to play with novel chemical matter, Expert Opin Drug Discov, 12, 977, 10.1080/17460441.2017.1362386
Walters, 2018, Virtual chemical libraries, J Med Chem, 62, 1116, 10.1021/acs.jmedchem.8b01048
Schneider, 2000, De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks, J Comput Aided Mol Des, 14, 487, 10.1023/A:1008184403558
Douguet, 2005, LEA3D: a computer-aided ligand design for structure-based drug design, J Med Chem, 48, 2457, 10.1021/jm0492296
Lewell, 1998, RECAP - Retrosynthetic Combinatorial Analysis Procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry, J Chem Inf Comput Sci, 38, 511, 10.1021/ci970429i
Nishibata, 1993, Confirmation of usefulness of a structure construction program based on three-dimensional receptor structure for rational lead generation, J Med Chem, 36, 2921, 10.1021/jm00072a011
Bohm, 1992, The computer program LUDI: a new method for the de novo design of enzyme inhibitors, J Comput Mol Des, 6, 61, 10.1007/BF00124387
Gillet, 1994, SPROUT: recent developments in the de novo design of molecules, J Chem Inf Comput Sci, 34, 207, 10.1021/ci00017a027
Kutchukian, 2009, FOG: fragment optimized growth algorithm for the de novo generation of molecule: occupying druglike chemical space, J Chem Inf Model, 49, 1630, 10.1021/ci9000458
Pierce, 2004, BREED: generating novel inhibitors through hybridization of known ligands. Application to CDK2, P38, and HIV protease, J Med Chem, 47, 2768, 10.1021/jm030543u
Murcko, 1993, CONCEPTS: new dynamic algorithm for de novo drug suggestion, J Comput Chem, 14, 1184, 10.1002/jcc.540141008
Ji, 2003, Structure-based de novo design, synthesis, and biological evaluation of non-azole inhibitors specific for lanosterol 14α-demethylase of fungi, J Med Chem, 46, 474, 10.1021/jm020362c
Chang, 2016, Discovery of novel inhibitors of Aurora kinases with indazole scaffold: in silico fragment-based and knowledge-based drug design, Eur J Med Chem, 124, 186, 10.1016/j.ejmech.2016.08.026
Warner, 2006, Identification of a lead small-molecule inhibitor of the Aurora kinases using a structure-assisted, fragment-based approach, Mol Cancer Ther, 5, 1764, 10.1158/1535-7163.MCT-05-0524
Böhm, 1999, Combinatorial docking and combinatorial chemistry: design of potent non- peptide thrombin inhibitors, J Comput Aided Mol Des, 13, 51, 10.1023/A:1008040531766
Boehm, 2000, Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening, J Med Chem, 43, 2664, 10.1021/jm000017s
Honma, 2001, A novel approach for the development of selective Cdk4 inhibitors: library design based on locations of Cdk4 specific amino acid residues, J Med Chem, 44, 4628, 10.1021/jm010326y
Kandil, 2009, Discovery of a novel HCV helicase inhibitor by a de novo drug design approach, Bioorganic Med Chem Lett, 19, 2935, 10.1016/j.bmcl.2009.04.074
Ni, 2009, Discovering potent small molecule inhibitors of cyclophilin A using de novo drug design approach, J Med Chem, 52, 5295, 10.1021/jm9008295
Barone, 2001, A new and simple approach to chemical complexity. Application to the synthesis of natural products, J Chem Inf Comput Sci, 41, 269, 10.1021/ci000145p
Honma, 2001, Structure-based generation of a new class of potent Cdk4 inhibitors: New de novo design strategy and library design, J Med Chem, 44, 4615, 10.1021/jm0103256
Proschak, 2009, From molecular shape to potent bioactive agents II: fragment-based de novo design, ChemMedChem, 4, 45, 10.1002/cmdc.200800314
Hartenfeller, 2012, Dogs: reaction-driven de novo design of bioactive compounds, PLoS Comput Biol, 8, 1, 10.1371/journal.pcbi.1002380
Hartenfeller, 2011, A collection of robust organic synthesis reactions for in silico molecule design, J Chem Inf Model, 51, 3093, 10.1021/ci200379p
Cox, 2016, A poised fragment library enables rapid synthetic expansion yielding the first reported inhibitors of PHIP(2), an atypical bromodomain, Chem Sci, 7, 2322, 10.1039/C5SC03115J
Roughley, 2011, The medicinal chemist’s toolbox: an analysis of reactions used in the pursuit of drug candidates, J Med Chem, 54, 3451, 10.1021/jm200187y
Whittaker, 2009, Picking up the pieces with FBDD or FADD: invest early for future success, Drug Discov Today, 14, 623, 10.1016/j.drudis.2009.05.011
Wang, 2016, Comprehensive evaluation of ten docking programs on a diverse set of protein–ligand complexes: the prediction accuracy of sampling power and scoring power, Phys Chem Chem Phys, 18, 12964, 10.1039/C6CP01555G
Park, 2018, Systematic computational design and identification of low picomolar inhibitors of aurora kinase A, J Chem Inf Model, 58, 700, 10.1021/acs.jcim.7b00671
Xiang, 2018, Discovery and optimization of 1-(1H-indol-1-yl)ethanone derivatives as CBP/EP300 bromodomain inhibitors for the treatment of castration-resistant prostate cancer, Eur J Med Chem, 147, 238, 10.1016/j.ejmech.2018.01.087
Martin, 2016, Structure-based design of an in vivo active selective BRD9 inhibitor, J Med Chem, 59, 4462, 10.1021/acs.jmedchem.5b01865
Hale, 2015, From fragments to leads: novel bacterial NAD+-dependent DNA ligase inhibitors, Tetrahedron Lett, 56, 3108, 10.1016/j.tetlet.2014.12.067
Ahmed-Belkacem, 2016, Fragment-based discovery of a new family of non-peptidic small-molecule cyclophilin inhibitors with potent antiviral activities, Nat Commun, 7, 10.1038/ncomms12777
Bennett, 2018, Design, synthesis and biological evaluation of novel 4-phenylisoquinolinone BET bromodomain inhibitors, Bioorganic Med Chem Lett, 28, 1811, 10.1016/j.bmcl.2018.04.016
Bronner, 2017, A unique approach to design potent and selective cyclic adenosine monophosphate response element binding protein, binding protein (CBP) inhibitors, J Med Chem, 60, 10151, 10.1021/acs.jmedchem.7b01372
He, 2015, Cefsulodin inspired potent and selective inhibitors of mPTPB, a virulent phosphatase from Mycobacterium tuberculosis, ACS Med Chem Lett, 6, 1231, 10.1021/acsmedchemlett.5b00373
Majewski, 2020, Structural stability predicts the binding mode of protein-ligand complexes, J Chem Inf Model, 6, 1644, 10.1021/acs.jcim.9b01062
Rachman, 2018, Predicting how drug molecules bind to their protein targets, Curr Opin Pharmacol, 42, 34, 10.1016/j.coph.2018.07.001
Lorthiois, 2017, Discovery of highly potent and selective small-molecule reversible factor d inhibitors demonstrating alternative complement pathway inhibition in vivo, J Med Chem, 60, 5717, 10.1021/acs.jmedchem.7b00425
Vulpetti, 2017, Structure-based library design and fragment screening for the identification of reversible complement factor d protease inhibitors, J Med Chem, 60, 1946, 10.1021/acs.jmedchem.6b01684
Gawehn, 2018, Advancing drug discovery via GPU-based deep learning, Expert Opin Drug Discov, 13, 579, 10.1080/17460441.2018.1465407
Dudek, 2006, Computational methods in developing quantitative structure-activity relationships (QSAR): a review, Comb Chem High Throughput Screen, 9, 213, 10.2174/138620706776055539
Yang, 2010, Pharmacophore modeling and applications in drug discovery: challenges and recent advances, Drug Discov Today, 15, 444, 10.1016/j.drudis.2010.03.013
Olivecrona, 2017, Molecular de-novo design through deep reinforcement learning, J Cheminform, 9, 1, 10.1186/s13321-017-0235-x
Skalic, 2019, Shape-based generative modeling for de novo drug design, J Chem Inf Model, 59, 1205, 10.1021/acs.jcim.8b00706
Segler, 2018, Generating focused molecule libraries for drug discovery with recurrent neural networks, ACS Cent Sci, 4, 120, 10.1021/acscentsci.7b00512
Jin, 2018, Junction tree variational autoencoder for molecular graph generation, 35th Int Conf Mach Learn ICML 2018, 3632
Gómez-Bombarelli, 2018, Automatic chemical design using a data-driven continuous representation of molecules, ACS Cent Sci, 4, 268, 10.1021/acscentsci.7b00572
Coley, 2018, Machine learning in computer-aided synthesis planning, Acc Chem Res, 51, 1281, 10.1021/acs.accounts.8b00087
Segler, 2018, Planning chemical syntheses with deep neural networks and symbolic AI, Nature, 555, 604, 10.1038/nature25978
Coley, 2019, A robotic platform for flow synthesis of organic compounds informed by AI planning, Science (80-), 365, 1, 10.1126/science.aax1566
Szymkuć, 2016, Computer-assisted synthetic planning: the end of the beginning, Angew Chem Int Ed, 55, 5904, 10.1002/anie.201506101
Gottipati, 2020, Learning to navigate the synthetically accessible chemical space using reinforcement learning, ArXiv, 1
Ertl, 2009, Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions, J Cheminform, 1, 1, 10.1186/1758-2946-1-8
Imrie, 2020, Deep generative models for 3D linker design, J Chem Inf Model, 6, 1983, 10.1021/acs.jcim.9b01120
Bilsland, 2021, Automated generation of novel fragments using screening data, a dual SMILES autoencoder, transfer learning and syntax correction, J Chem Inf Model, 10.1021/acs.jcim.0c01226
Lipinski, 2012, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv Drug Deliv Rev, 64, 4, 10.1016/j.addr.2012.09.019
van de Waterbeemd, 2003, ADMET in silico modelling: towards prediction paradise?, Nat Rev Drug Discov, 2, 192, 10.1038/nrd1032
Artis, 2009, Scaffold-based discovery of indeglitazar, a PPAR pan-active anti-diabetic agent, Proc Natl Acad Sci U S A, 106, 262, 10.1073/pnas.0811325106
Yang, 2019, Concepts of artificial intelligence for computer-assisted drug discovery, Chem Rev, 119, 10520, 10.1021/acs.chemrev.8b00728
Besnard, 2012, Automated design of ligands to polypharmacological profiles, Nature, 492, 215, 10.1038/nature11691
Gupta, 2018, Generative recurrent networks for de novo drug design, Mol Inform, 37
Batiste, 2018, Chemical space expansion of bromodomain ligands guided by in silico virtual couplings (AutoCouple), ACS Cent Sci, 4, 180, 10.1021/acscentsci.7b00401
Chevillard, 2018, Binding-site compatible fragment growing applied to the design of β 2 -Adrenergic receptor ligands, J Med Chem, 61, 1118, 10.1021/acs.jmedchem.7b01558
Hoffer, 2018, Integrated strategy for lead optimization based on fragment growing: the diversity-oriented-target-focused-synthesis approach, J Med Chem, 61, 5719, 10.1021/acs.jmedchem.8b00653
Li, 2020, Fragment-based computational method for designing GPCR ligands, J Chem Inf Model, 60, 4339, 10.1021/acs.jcim.9b00699
Wang, 2000, LigBuilder: a multi-purpose program for structure-based drug design, J Mol Model, 6, 498, 10.1007/s0089400060498
Kolb, 2008, Structure-based tailoring of compound libraries for high-throughput screening: discovery of novel EphB4 kinase inhibitors, Proteins Struct Funct Genet, 73, 11, 10.1002/prot.22028
Sabbah, 2020, Fragment-based design of Mycobacterium tuberculosis InhA inhibitors, J Med Chem, 63, 4749, 10.1021/acs.jmedchem.0c00007
Kwiatkowski, 2018, Fragment-based drug discovery of potent protein kinase C iota inhibitors, J Med Chem, 61, 4386, 10.1021/acs.jmedchem.8b00060
Heightman, 2018, Fragment-based discovery of a potent, orally bioavailable inhibitor that modulates the phosphorylation and catalytic activity of ERK1/2, J Med Chem, 61, 4978, 10.1021/acs.jmedchem.8b00421
Wang, 2018, Discovery of potent 2-Aryl-6,7-dihydro-5 H-pyrrolo[1,2- a]imidazoles as WDR5-WIN-Site inhibitors using fragment-based methods and structure-based design, J Med Chem, 61, 5623, 10.1021/acs.jmedchem.8b00375
Drapier, 2018, Enhancing action of positive allosteric modulators through the design of dimeric compounds, J Med Chem, 61, 5279, 10.1021/acs.jmedchem.8b00250
Korepanova, 2018, Fragment-based discovery of a potent NAMPT inhibitor, Bioorganic Med Chem Lett, 28, 437, 10.1016/j.bmcl.2017.12.023
Chen, 2017, Fragment-based design, synthesis, biological evaluation, and SAR of 1H-benzo[d]imidazol-2-yl)-1H-indazol derivatives as potent PDK1 inhibitors, Bioorganic Med Chem Lett, 27, 5473, 10.1016/j.bmcl.2017.10.041
Benmansour, 2017, Discovery of novel dengue virus NS5 methyltransferase non-nucleoside inhibitors by fragment-based drug design, Eur J Med Chem, 125, 865, 10.1016/j.ejmech.2016.10.007
Mesleh, 2016, Fragment-based discovery of DNA gyrase inhibitors targeting the ATPase subunit of GyrB, Bioorganic Med Chem Lett, 26, 1314, 10.1016/j.bmcl.2016.01.009
Jordan, 2016, Fragment-linking approach using 19F NMR spectroscopy to obtain highly potent and selective inhibitors of β-Secretase, J Med Chem, 59, 3732, 10.1021/acs.jmedchem.5b01917
Kavanagh, 2016, Fragment-based approaches to the development of Mycobacterium tuberculosis CYP121 inhibitors, J Med Chem, 59, 3272, 10.1021/acs.jmedchem.6b00007
Davies, 2016, Monoacidic inhibitors of the kelch-like ECH-associated protein 1: nuclear factor erythroid 2-related factor 2 (KEAP1:NRF2) protein-Protein interaction with high cell potency identified by fragment-based discovery, J Med Chem, 59, 3991, 10.1021/acs.jmedchem.6b00228
Shipe, 2015, Discovery and optimization of a series of pyrimidine-based phosphodiesterase 10A (PDE10A) inhibitors through fragment screening, structure-based design, and parallel synthesis, J Med Chem, 58, 7888, 10.1021/acs.jmedchem.5b00983
Ritzén, 2016, Fragment-based discovery of 6-arylindazole JAK inhibitors, ACS Med Chem Lett, 7, 641, 10.1021/acsmedchemlett.6b00087
Rasina, 2016, Fragment-based discovery of 2-aminoquinazolin-4(3H)-ones as novel class nonpeptidomimetic inhibitors of the plasmepsins I, II, and IV, J Med Chem, 59, 374, 10.1021/acs.jmedchem.5b01558
Burdick, 2015, Fragment-based discovery of potent ERK2 pyrrolopyrazine inhibitors, Bioorganic Med Chem Lett, 25, 4728, 10.1016/j.bmcl.2015.08.048
George, 2015, Discovery of selective and orally bioavailable protein kinase Cθ (PKCθ) inhibitors from a fragment hit, J Med Chem, 58, 222, 10.1021/jm500669m
Fjellström, 2015, Creating novel activated factor XI inhibitors through fragment based lead generation and structure aided drug design, PLoS One, 10, 10.1371/journal.pone.0113705
Bertrand, 2015, The discovery of in vivo active mitochondrial branched-chain aminotransferase (BCATm) inhibitors by hybridizing fragment and HTS hits, J Med Chem, 58, 7140, 10.1021/acs.jmedchem.5b00313
Burke, 2015, Discovery of tricyclic indoles that potently inhibit Mcl-1 using fragment-based methods and structure-based design, J Med Chem, 58, 3794, 10.1021/jm501984f
Christopher, 2015, Fragment and structure-based drug discovery for a class C GPCR: discovery of the mGlu5 negative allosteric modulator HTL14242 (3-Chloro-5-[6-(5-fluoropyridin-2-yl)pyrimidin-4-yl]benzonitrile), J Med Chem, 58, 6653, 10.1021/acs.jmedchem.5b00892
Picaud, 2015, 9 H -purine scaffold reveals induced-fit pocket plasticity of the brd9 bromodomain, J Med Chem, 58, 2718, 10.1021/jm501893k
Cheney, 2015, Discovery of novel P1 groups for coagulation factor VIIa inhibition using fragment-based screening, J Med Chem, 58, 2799, 10.1021/jm501982k
Halgren, 2009, Identifying and characterizing binding sites and assessing druggability, J Chem Inf Model, 49, 377, 10.1021/ci800324m
Kovalenko, 1998, Three-dimensional density profiles of water in contact with a solute of arbitrary shape: a RISM approach, Chem Phys Lett, 290, 237, 10.1016/S0009-2614(98)00471-0
Carcache, 2018, Optimizing a weakly binding fragment into a potent RORγt inverse agonist with efficacy in an in vivo inflammation model, J Med Chem, 61, 6724, 10.1021/acs.jmedchem.8b00529
Cross, 2016, Discovery of pyrazolopyridones as a novel class of gyrase B inhibitors using structure guided design, ACS Med Chem Lett, 7, 374, 10.1021/acsmedchemlett.5b00368
Abel, 2008, Role of the active-site solvent in the thermodynamics of factor Xa ligand binding, J Am Chem Soc, 130, 2817, 10.1021/ja0771033
Matsui, 2017, Discovery and structure-guided fragment-linking of 4-(2,3-dichlorobenzoyl)-1-methyl-pyrrole-2-carboxamide as a pyruvate kinase M2 activator, Bioorg Med Chem, 25, 3540, 10.1016/j.bmc.2017.05.004
Böttcher, 2019, Fragment-based discovery of a chemical probe for the PWWP1 domain of NSD3, Nat Chem Biol, 15, 822, 10.1038/s41589-019-0310-x
Meine, 2018, Indole-3-carbonitriles as DYRK1A inhibitors by fragment-based drug design, Molecules, 23, 1, 10.3390/molecules23020064
Schulz, 2018, Phenylthiomethyl ketone-based fragments show selective and irreversible inhibition of enteroviral 3C proteases, J Med Chem, 61, 1218, 10.1021/acs.jmedchem.7b01440
Dawidowski, 2017, Inhibitors of PEX14 disrupt protein import into glycosomes and kill Trypanosoma parasites, Science (80-), 355, 1416, 10.1126/science.aal1807
McCoull, 2017, Discovery of pyrazolo[1,5-a]pyrimidine B-cell lymphoma 6 (BCL6) binders and optimization to high affinity macrocyclic inhibitors, J Med Chem, 60, 4386, 10.1021/acs.jmedchem.7b00359
Di Lello, 2017, Discovery of small-molecule inhibitors of ubiquitin specific protease 7 (USP7) using integrated NMR and in silico techniques, J Med Chem, 60, 10056, 10.1021/acs.jmedchem.7b01293
Liu, 2017, Structure-guided discovery of novel, potent, and orally bioavailable inhibitors of lipoprotein-associated phospholipase A2, J Med Chem, 60, 10231, 10.1021/acs.jmedchem.7b01530
Rudling, 2017, Fragment-based discovery and optimization of enzyme inhibitors by docking of commercial chemical space, J Med Chem, 60, 8160, 10.1021/acs.jmedchem.7b01006
Adams, 2016, Fragment-based drug discovery of potent and selective MKK3/6 inhibitors, Bioorganic Med Chem Lett, 26, 1086, 10.1016/j.bmcl.2015.11.054
McKinney, 2016, Antibacterial FabH inhibitors with mode of action validated in Haemophilus influenzae by in vitro resistance mutation mapping, ACS Infect Dis, 2, 456, 10.1021/acsinfecdis.6b00053
Woolford, 2016, Fragment-based approach to the development of an orally bioavailable lactam inhibitor of lipoprotein-associated phospholipase A2 (Lp-PLA2), J Med Chem, 59, 10738, 10.1021/acs.jmedchem.6b01427
Woolford, 2016, Exploitation of a novel binding pocket in human lipoprotein-associated phospholipase A2 (Lp-PLA2) discovered through X-ray fragment screening, J Med Chem, 59, 5356, 10.1021/acs.jmedchem.6b00212
Lanz, 2015, Merging allosteric and active site binding motifs: de novo generation of target selectivity and potency via natural-product-derived fragments, ChemMedChem, 10, 451, 10.1002/cmdc.201402478
Chessari, 2015, Fragment-based drug discovery targeting inhibitor of apoptosis proteins: discovery of a non-alanine lead series with dual activity against cIAP1 and XIAP, J Med Chem, 58, 6574, 10.1021/acs.jmedchem.5b00706
Zech, 2016, Novel small molecule inhibitors of choline kinase identified by fragment-based drug discovery, J Med Chem, 59, 671, 10.1021/acs.jmedchem.5b01552
Marchand, 2017, Discovery of inhibitors of four bromodomains by fragment-anchored ligand docking, J Chem Inf Model, 57, 2584, 10.1021/acs.jcim.7b00336
Zhao, 2012, Discovery of a novel chemotype of tyrosine kinase inhibitors by fragment-based docking and molecular dynamics, ACS Med Chem Lett, 3, 834, 10.1021/ml3001984
Xu, 2016, Discovery of CREBBP bromodomain inhibitors by high-throughput docking and hit optimization guided by molecular dynamics, J Med Chem, 59, 1340, 10.1021/acs.jmedchem.5b00171
Unzue, 2016, Fragment-based design of selective nanomolar ligands of the CREBBP bromodomain, J Med Chem, 59, 1350, 10.1021/acs.jmedchem.5b00172
Pardon, 2018, Nanobody-enabled reverse pharmacology on G-Protein-Coupled receptors, Angew Chem Int Ed, 57, 5292, 10.1002/anie.201712581
Park, 2016, Application of fragment-based de novo design to the discovery of selective picomolar inhibitors of glycogen synthase Kinase-3 Beta, J Med Chem, 59, 9018, 10.1021/acs.jmedchem.6b00944
Murray, 2015, Fragment-based discovery of potent and selective DDR1/2 inhibitors, ACS Med Chem Lett, 6, 798, 10.1021/acsmedchemlett.5b00143
Heikkilä, 2006, The first de novo designed inhibitors of Plasmodium falciparum dihydroorotate dehydrogenase, Bioorg Med Chem Lett, 16, 88, 10.1016/j.bmcl.2005.09.045
Davies, 2009, Structure-based design, synthesis, and characterization of inhibitors of human and Plasmodium falciparum dihydroorotate dehydrogenases, J Med Chem, 52, 2683, 10.1021/jm800963t
Mok, 2013, Discovery of biphenylacetamide-derived inhibitors of BACE1 using de novo structure-based molecular design, J Med Chem, 56, 1843, 10.1021/jm301127x
Rogers-Evans, 2004, Identification of novel cannabinoid receptor ligands via evolutionary de novo design and rapid parallel synthesis, QSAR Comb Sci, 23, 426, 10.1002/qsar.200410012
Wolber, 2005, LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters, J Chem Inf Model, 45, 160, 10.1021/ci049885e
Yuan, 2020, LigBuilder V3: a multi-target de novo drug design approach, Front Chem, 8, 1, 10.3389/fchem.2020.00142
Pearce, 2017, A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density, Nat Commun, 8, 24, 10.1038/ncomms15123
Zhavoronkov, 2021, 0
Doppelt-Azeroual, 2017, ReGaTE: registration of galaxy tools in Elixir, Gigascience, 6, 1, 10.1093/gigascience/gix022
Perez, 2020, FragPELE: dynamic ligand growing within a binding site. A novel tool for hit-to-lead drug design, J Chem Inf Model, 60, 1728, 10.1021/acs.jcim.9b00938
Jorgensen, 2009, Efficient drug lead discovery and optimization, Acc Chem Res, 42, 724, 10.1021/ar800236t