ライフサイエンスコーパス: drug discovery

1 ric cancer, and is an important biomarker in drug discovery.

2 ceptors in recombinant systems has precluded drug discovery.

3 repositioning and drug-target prediction in drug discovery.

4 g them attractive targets for small-molecule drug discovery.

5 nding applications in future structure-based drug discovery.

6 mall molecule modulators and structure-based drug discovery.

7 building blocks for medicinal chemistry and drug discovery.

8 Significant attrition limits drug discovery.

9 ding blocks for both synthetic chemistry and drug discovery.

10 and inform best practices in fragment-based drug discovery.

11 intelligence (AI) is becoming established in drug discovery.

12 s and promises a new therapeutic modality in drug discovery.

13 evolutionary studies and enable venom-driven drug discovery.

14 f how RNA is recognized and for RNA-targeted drug discovery.

15 bility is a key pharmacokinetic parameter in drug discovery.

16 ons pose substantial challenges for rational drug discovery.

17 assays in the early ADME profiling space in drug discovery.

18 cids play an important role in peptide based drug discovery.

19 ion annotation, disease gene prediction, and drug discovery.

20 earning, may represent an effective path for drug discovery.

21 ognized as an important facet of preclinical drug discovery.

22 g heterogeneity in disease, and facilitating drug discovery.

23 critical functional genomic information for drug discovery.

24 functional group in medicinal chemistry and drug discovery.

25 a new and exciting tool in neuroscience and drug discovery.

26 tion in images hold promise for accelerating drug discovery.

27 d to more commonly used structural motifs in drug discovery.

28 the future trends in the field of ophthalmic drug discovery.

29 and, indeed, has provided insight in modern drug discovery.

30 initiation, progression, and relapse and for drug discovery.

31 of compound lipophilicity is a key aspect of drug discovery.

32 S-CoV-2) could accelerate vaccine design and drug discovery.

33 and that they can be informative for future drug discovery.

34 aluable tool for cell signaling research and drug discovery.

35 and have therefore often been overlooked in drug discovery.

36 ts compound repurposing at scale rather than drug discovery.

37 raged to inspect target innovation trends in drug discovery.

38 drug-target interaction is a key element in drug discovery.

39 peutic index is a major challenge for cancer drug discovery.

40 orins providing potential targets for modern drug discovery.

41 is an emerging approach in modern anticancer drug discovery.

42 e among the most common chemotypes in modern drug discovery.

43 s well as highlight opportunities for future drug discovery.

44 embrane fusion and is a validated target for drug discovery.

45 aracterization for molecular informatics and drug discovery.

46 platform for effective disease modeling and drug discovery.

47 of intraligand NOEs in ligand screening for drug discovery.

48 toward RNR inhibition that are relevant for drug discovery.

49 how it is coherent with the new paradigm of drug discovery.

50 anistic studies of signaling pathways and in drug discovery.

51 ties offered by teixobactin in the domain of drug discovery.

52 time and reduce the cost compared to de novo drug discovery.

53 a central challenge in RNA biochemistry and drug discovery.

54 and fertile field in medicinal chemistry and drug discovery.

55 iscovered that is amenable to small-molecule drug discovery.

56 Our findings may provide new insights for drug discovery.

57 cales, and further accelerate the process of drug discovery.

58 blishing their place in the biologics arm of drug discovery.

59 lications in chemical biological and peptide drug discovery.

60 f-function carriers for target validation in drug discovery.

61 target identification is a major obstacle in drug discovery.

62 ity and structure-property relationships for drug discovery.

63 ese human based cell assays for pre-clinical drug discovery.

64 n (MoA) prediction and other applications in drug discovery.

65 ges of targeting enzyme/product complexes in drug discovery.

66 ut protein-ligand interactions is central to drug discovery.

67 o protein targets is crucially important for drug discovery.

68 ing it a promising target for antiretroviral drug discovery.

69 blocks is of great importance, especially in drug discovery.

70 as a precedent for future viroporin-targeted drug discovery.

71 (AI) tools are increasingly being applied in drug discovery.

72 organic molecules, particularly exploited in drug discovery.

73 eractions (PPIs) is a promising strategy for drug discovery.

74 oteins that have evaded previous attempts at drug discovery.

75 ns together with recent advances and gaps in drug discovery.

76 important tools in preclinical research and drug discovery.

77 of applying graph convolutional networks to drug discovery.

78 gating and will facilitate organism-specific drug discovery.

79 longstanding challenges in natural products drug discovery.

80 stance, and to continue the pursuit of novel drug discovery.

81 ical diagnostics, functional proteomics, and drug discovery.

82 document the relevance of peptidomimetics in drug discovery.

83 ical processes is an important first step of drug discovery.

84 hold great promise for disease modeling and drug discovery.

85 in vivo and may offer an important tool for drug discovery.

86 uch as structural biology, cell imaging, and drug discovery.

87 ases (NDs) and how this can be exploited for drug discovery.

88 h potential in natural product synthesis and drug discovery.

89 rging as a powerful approach for therapeutic drug discovery.

90 resulting in many useful drugs eliminated in drug discovery.

91 ch are important for medicinal chemistry and drug discovery.

92 also as bioisosteres of beta-amino acids in drug discovery.

93 hesis technologies to enable next-generation drug discovery.

94 become essential tasks in the early stage of drug discovery.

95 nsporter-mediated uptake, are challenging in drug discovery.

96 g molecules by Mtb remains elusive, limiting drug discovery.

97 olecular diagnostics, therapy monitoring and drug discovery.

98 ogenic pathways, paving the way for targeted drug discoveries.

99 the most popular chemical reaction used for drug discovery(1).

100 recently emerged as a successful strategy in drug discovery across disease indications.

101 have nominated DUBs as a promising class for drug discovery across diverse therapeutic areas.

102 ve PPIs of N protein could be applied toward drug discovery against CoV diseases.

103 One of the promising targets for drug discovery against dengue and other flaviviruses is

104 ening assays, used routinely in antimalarial drug discovery, against the whole organism.

105 ay an important role in medicinal chemistry, drug discovery, agrochemistry, coordination chemistry, a

106 ty of in silico methodologies for allosteric drug discovery and boost the development of conformation

107 lity of mitophagy pathways and prospects for drug discovery and consider intervention points for mito

108 abolomics and small molecule identification, drug discovery and design, chemical forensics, and beyon

109 uld be valuable molecular targets for cancer drug discovery and development against PCa.

110 ns (ADRs) are a common cause of attrition in drug discovery and development and drug-induced liver in

111 The model-informed drug discovery and development paradigm is now well esta

112 and clinical trial end points throughout the drug discovery and development process is crucial to hel

113 to be informative at multiple stages of the drug discovery and development process.

114 In drug discovery and development, computational studies ca

115 allenges the current paradigm of traditional drug discovery and development, which usually takes year

116 Dose is predicted at many stages in drug discovery and development.

117 g response, having profound implications for drug discovery and development.

118 cetylene group has been broadly exploited in drug discovery and development.

119 ies and impact of photochemical reactions in drug discovery and development.

120 y libraries and will support efforts in both drug discovery and development.

121 view recent applications to pharmacology and drug discovery and discuss possible guidelines for the p

122 on of the unique advantages of the fields of drug discovery and drug delivery is invaluable for the a

123 ification studies during the later stages of drug discovery and even in a clinical setting.

124 review summarizes the limitations of current drug discovery and explores the potential of (19)F NMR i

125 using mass spectrometry (MS) is important in drug discovery and formulation development and as part o

126 , extending from environmental monitoring to drug discovery and industrial biotechnology.

127 Recent studies on neural drug discovery and injectable hydrogels provide a potent

128 olutional networks and their applications in drug discovery and molecular informatics.

129 ps all over the world, frequently applied in drug discovery and natural product synthesis, most resea

130 ould find wide application in the context of drug discovery and natural product synthesis.

131 lecules and natural products is critical for drug discovery and organic chemistry.

132 improve genetic diagnosis, drive phenotypic drug discovery and pave the way toward precision medicin

133 During drug discovery and prior to the first human dose of a no

134 laS has broad applications in areas, such as drug discovery and protein-interface design.

135 the PROTAC technology and its application to drug discovery and provide examples where PROTACs have e

136 hemical compound libraries facilitating both drug discovery and repurposing.

137 technique that can bring tremendous value to drug discovery and research of intermolecular interactio

138 ng of in vitro models of the liver to aid in drug discovery and study of liver pathophysiology.

139 etabolites has become a major technology for drug discovery and studying microbiome ecology.

140 novel techniques, and strategies applied in drug discovery and the better knowledge of molecular pro

141 small molecules suitable for fragment-based drug discovery and the cystic fibrosis C2-corrector clin

142 pective focuses on various aspects of ocular drug discovery and the recent advances therein.

143 ent of improved infectious model systems for drug discovery and the study of the HBV life cycle.

144 ural substrates of proteases is critical for drug discovery and to understand protease biology.

145 iaturized devices replacing animal models in drug discovery and toxicology studies.

146 et engagement confirmation is a challenge to drug discovery and translation due to lack of bioassay t

147 iester 1 is a novel chiral synthon useful in drug discovery and was instrumental in the generation of

148 extraction-based MSI in biological research, drug discovery, and clinical studies.

149 y of droplet sorting to protein engineering, drug discovery, and diagnostic workflows.

150 ing to the key roles of amines in synthesis, drug discovery, and materials science.

151 s nanobody development, mutational analysis, drug discovery, and studies of GPCR chaperoning.

152 oward developing biomedical microdevices for drug discovery, antibiotic resistance assessment, and me

153 e developed a novel integrated computational drug discovery approach by seamlessly combining DTI pred

154 This inverse drug discovery approach identified a compound that coval

155 Here, we propose the application of a drug discovery approach originally developed for cancer

156 ication of a structure-guided fragment-based drug discovery approach to the design of a new class of

157 r knowledge by application of computer-aided drug discovery approaches reduces time and financial exp

158 New approaches to drug discovery are unlocking enormous therapeutic potent

159 lthough it provides invaluable resources for drug discovery as well as understanding of disease mecha

160 he microbiome represents a vast resource for drug discovery, as its members engage in constant confli

161 These findings are critical for rational drug discovery, as limiting a virtual screen to a single

162 The data suggest a general approach of drug discovery based on the design of allosteric modulat

163 Small molecules continue to dominate drug discovery because of their ease of use, lower cost

164 receptors (NRs) are high-interest targets in drug discovery because of their involvement in numerous

165 Chirality is important in drug discovery because stereoselective drugs can amelior

166 n factor activity is a long-standing goal in drug discovery but hampered by the difficulties associat

167 identify active conformers in peptide-based drug discovery, but they usually require multiple routes

168 We believe this improves efficiency in drug discovery by enabling exploration of broad physicoc

169 Crucially, drug discovery campaigns focusing on SHP2 would greatly

170 For drug discovery, cow immunisations harness the immune sys

171 ane proteins with an unprecedented impact in drug discovery/development strategies.

172 s such as high-throughput/content screening, drug discovery, disease modeling, and personalized medic

173 amework may be expanded to make an impact in drug discovery, drug safety screening for a variety of c

174 entific knowledge and accelerate progress in drug discovery.Dual Perspectives Companion Paper: Studyi

175 The assay is a valuable complement for drug discovery efforts and will support a better underst

176 In addition, drug discovery efforts are also focusing on strategies t

177 InhA has been the focus of numerous drug discovery efforts as this is the target of the firs

178 Current drug discovery efforts focus on identifying lead compoun

179 ium channel as a promising target for future drug discovery efforts in mood disorders.

180 Consequent probe and drug discovery efforts over the past 15 years have resul

181 Therefore, future antimalarial drug discovery efforts seeking to identify plasmepsin in

182 Drug discovery efforts targeting beta-adrenergic signali

183 e, we have provided an up-to-date account of drug discovery efforts targeting selected enzymes (MbtI,

184 on of endogenous and tool ligands, and guide drug discovery efforts that target GPR52.

185 sistant mutant kinases are valuable tools in drug discovery efforts, but the prediction of mutants ac

186 These insights have enabled computational drug discovery efforts, with some evidence of success in

187 rstanding of which can substantially advance drug discovery efforts.

188 ility of using G((q)) proteins as targets in drug discovery efforts.

189 represent potential starting points for DMD drug discovery efforts.

190 y for the identification of binders in early drug-discovery efforts.

191 The evolution of drug discovery exploded in the early 20th century with t

192 rein, we present a two-phase, fragment-based drug discovery (FBDD) effort in which we first identifie

193 Fragment-based drug discovery (FBDD) has grown and matured to a point w

194 Fragment-based drug discovery (FBDD) permits efficient sampling of the

195 The ocular drug discovery field has evidenced significant advanceme

196 In order to facilitate rapid drug discovery, flexible, sensitive, and high-throughput

197 od for chronic pain treatment and energizing drug discovery focused on S1P signaling.

198 secretase, which may not only accelerate our drug discovery for AD but also advance our understanding

199 nd its complexity has delayed the process of drug discovery for many years compared to other drug cla

200 eurotransmitter receptor assembly and unlock drug discovery for the previously elusive alpha6beta4 re

201 e most successful strategy in anti-infective drug discovery for the treatment of such problematic inf

202 an deafness genes TMIE/TMEM132e, and enables drug discovery for this elusive nAChR implicated in prev

203 ion in DDIs and toxicities as well as enable drug discovery for transporters as pharmacology targets.

204 The Alzheimer's Drug Discovery Foundation and the National Institute on

205 Alzheimer Drug Discovery Foundation, European Research Council, Sw

206 ternal validation with molecules relevant to drug discovery from the public domain.

207 ine into proteins and fragment libraries for drug discovery has become increasingly common.

208 Chagas drug discovery has been hampered by a lack of validated

209 he utility of combining these approaches for drug discovery has been lacking.

210 wo decades ago, their application for use in drug discovery has been limited due to inherent library

211 le contraception, however a major barrier to drug discovery has been the lack of validated targets an

212 Rational drug discovery has greatly accelerated the development o

213 their potential utility in cell therapy and drug discovery has not been reported.

214 For decades, traditional drug discovery has used natural product and synthetic ch

215 n is imperative for cancer immunotherapy and drug discovery; however, most existing imaging agents po

216 cancer mechanisms and starting compounds for drug discovery; however, there is a notable lack of vali

217 e how computational methods can help advance drug discovery in a setting with more limited resources

218 nd places the PAS domain as a new target for drug discovery in EAG and related channels.

219 ion from the domains of synthetic chemistry, drug discovery, inorganic chemistry, and materials scien

220 Fragment-based drug discovery is a strategy widely used in both academi

221 However, continued tuberculosis drug discovery is critical to address the global health

222 uantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable

223 Although structure-based virtual drug discovery is revolutionizing the conventional high-

224 its application in molecular informatics and drug discovery is still limited.

225 Part of the problem with AD drug discovery is that transgenic mouse models have been

226 riety of applications, including sensing and drug discovery, it has been so far limited to the use of

227 he valuable contribution of animal models to drug discovery, it remains difficult to conduct mechanis

228 y raise the hope that researchers working in drug discovery may be able to potentially strike G(q) on

229 ent of drug molecules: the rise of 'rational drug discovery' methodology in the 1970s, followed by th

230 from a different perspective with respect to drug discovery, new MCR-based disconnections and often h

231 However, structure-based drug discovery of specific Artemis inhibitors has been h

232 Drug discovery organizations can choose from several ope

233 voidance" strategies have been inserted into drug discovery paradigms, which include the exclusion of

234 They have garnered widespread interest in drug discovery, particularly in oncology, as discriminat

235 In the end, the success of a drug discovery partnership will depend in large part on

236 rget are the most important factors in early drug discovery phase.

237 rial lead compounds that could help fill the drug discovery pipeline in response to the growing antib

238 To accelerate the cardiac drug discovery pipeline, we set out to develop a platfor

239 d credentials the model as a new preclinical drug discovery platform.

240 ng translational avenue to merge omics-based drug discovery platforms with patient-specific disease s

241 verse producer taxa with as yet unrecognized drug discovery potential.

242 his necessitates different approaches to the drug discovery process.

243 ctivity that is useful for many steps in the drug discovery process.

244 ligands and receptors are often ignored in a drug discovery process.

245 tor interactions are poor candidates for the drug discovery process.

246 ese systems is to inspire and accelerate the drug discovery process.

247 are showing great potential in improving the drug discovery process.

248 in target space at an early stage during the drug discovery process.

249 and only the best compounds progress in the drug discovery process.

250 t would bypass the time-consuming and costly drug-discovery process.

251 Aiming to make the drug discovery processes faster and less expensive, we d

252 ch skeletal ring systems is of importance to drug discovery programmes and natural product synthesis.

253 This platform will now allow for major drug discovery programmes that address the critical gap

254 SP surfaces form a powerful tool for driving drug discovery programs forward.

255 sed scaffolds with potential applications in drug discovery programs.

256 e successful development of aldehydes within drug discovery programs.

257 rapeutic effect is a critical aspect for all drug discovery programs.

258 up has advanced to implementation in several drug discovery programs.

259 are likely to be of interest to early-stage drug discovery programs.

260 od was successfully used in several 'inverse drug discovery' programs that use high-throughput techni

261 s that are still underrepresented in today's drug discovery projects, and only few examples can be fo

262 Modern small-molecule drug discovery relies on the selective targeting of biol

263 The approach to drug discovery represented by these 872 data sets charac

264 e with nanoliter-dispensing robotics to meet drug discovery requirements for the screening of large a

265 However, rapid drug discovery requires efficient methods to identify no

266 widely recognised as a necessary strategy in drug discovery research.

267 investigated to enhance the productivity of drug-discovery research.

268 ned to assume a more prominent role in early drug discovery's search for active chemical matter.

269 isen to the apparent level of stardom on the drug discovery scene.

270 been studied intensively, which has enabled drug discovery scientists to learn how it may be possibl

271 rtunities that cancer resistance presents to drug discovery scientists, with a focus on small molecul

272 plex biotherapeutics present challenges from drug discovery, screening, and development perspectives.

273 h community is encouraged to pursue these as drug discovery starting points for COVID-19.

274 eloping novel therapies by leveraging modern drug discovery strategies including computational drug r

275 caffold family worthy of inclusion in modern drug discovery strategies, demonstrated by the discovery

276 es represent the goal of modern medicine, as drug discovery strives to move away from one-cure-for-al

277 n of effective pro-apoptotic agents involves drug discovery studies (addressing the bioavailability,

278 he key points of interest for functional and drug discovery studies.

279 human-relevant platform for ALS research and drug discovery studies.

280 ar and an excellent platform for preclinical drug discovery studies.

281 an important framework for structure-guided drug discovery targeting MCTs.

282 igand interactions is facilitating efficient drug discovery targeting metalloenzymes.

283 e related research, particularly involved in drug discovery targeting metalloenzymes.

284 Drug discovery targeting Nef-mediated kinase activation

285 its mechanism of action and the potential of drug discovery targeting this receptor is limited by the

286 Comprehensive drug discovery techniques allowing high-throughput scree

287 t of improved mixture-based, high-throughput drug discovery techniques.

288 ently, dose predictions can be made early in drug discovery to enable drug design.

289 e-based virtual screening and fragment-based drug discovery to identify compounds likely to bind PRLR

290 olutional neural network for structure-based drug discovery, to identify inhibitors targeting asparta

291 Drug discovery usually begins with a high-throughput scr

292 ntists and educators working in the areas of drug discovery, vaccine design, and biomedical and biote

293 To support this approach to drug discovery, we characterize the orientational prefer

294 As a first step in drug discovery, we conducted an unbiased chemical screen

295 To aid mitigation of this risk in early drug discovery, we developed a physiologically based in

296 as a paradigm-shifting target in Alzheimer's drug discovery, we explore glucosylpolyphenols as blocke

297 e present and future value of simulation for drug discovery, we review key applications of advanced m

298 life science, biomedicine, biotechnology and drug discovery where protein associations are studied.

299 on the 'grand challenges' in small-molecule drug discovery with AI and the approaches to address the

300 to engage in structure- and mechanism-driven drug discovery with the potential to develop more isofor