scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/jcisd/BaurinBRCFPJRPGMH04 |
P356 | DOI | 10.1021/CI034260M |
P698 | PubMed publication ID | 15032546 |
P2093 | author name string | Baker R | |
Jordan A | |||
Richardson C | |||
Morley D | |||
Hubbard RE | |||
Chen I | |||
Potter A | |||
Baurin N | |||
Foloppe N | |||
Greaney P | |||
Parratt M | |||
Roughley S | |||
P2860 | cites work | SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules | Q28090714 |
Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges | Q28096294 | ||
Fast Calculation of Molecular Polar Surface Area as a Sum of Fragment-Based Contributions and Its Application to the Prediction of Drug Transport Properties | Q28842810 | ||
Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds | Q28842868 | ||
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings | Q28842973 | ||
Chemical information management in drug discovery: optimizing the computational and combinatorial chemistry interfaces. | Q30643833 | ||
Estimation of aqueous solubility of organic compounds with QSPR approach. | Q30733668 | ||
Selection criteria for drug-like compounds | Q30901599 | ||
Is there a difference between leads and drugs? A historical perspective | Q31017131 | ||
Optimizing the size and configuration of combinatorial libraries | Q31136115 | ||
Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules? | Q32032942 | ||
Estimation of aqueous solubility of chemical compounds using E-state indices | Q33843973 | ||
Prediction of intestinal permeability | Q34581541 | ||
Integration of virtual and high-throughput screening | Q34988235 | ||
Current trends in lead discovery: are we looking for the appropriate properties? | Q35054077 | ||
ADMET in silico modelling: towards prediction paradise? | Q35075770 | ||
Experimental and computational screening models for the prediction of intestinal drug absorption | Q40802302 | ||
Comparison of the NCI open database with seven large chemical structural databases. | Q42652302 | ||
Prediction of aqueous solubility of organic compounds by the general solubility equation (GSE). | Q43768709 | ||
Simultaneous prediction of aqueous solubility and octanol/water partition coefficient based on descriptors derived from molecular structure | Q43805832 | ||
Modeling aqueous solubility | Q44454055 | ||
Prediction of aqueous solubility and partition coefficient optimized by a genetic algorithm based descriptor selection method | Q47886757 | ||
Prediction of aqueous solubility for a diverse set of organic compounds based on atom-type electrotopological state indices | Q52067008 | ||
Improving the odds in discriminating "drug-like" from "non drug-like" compounds | Q52069878 | ||
Estimation of the aqueous solubility of organic molecules by the group contribution approach | Q52137482 | ||
Prediction of Physicochemical Parameters by Atomic Contributions | Q56432347 | ||
Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA | Q72741870 | ||
Estimation of aqueous solubility for a diverse set of organic compounds based on molecular topology | Q73887710 | ||
Absorption classification of oral drugs based on molecular surface properties | Q78896196 | ||
Lead generation--enhancing the success of drug discovery by investing in the hit to lead process | Q78898367 | ||
P433 | issue | 2 | |
P304 | page(s) | 643-651 | |
P577 | publication date | 2004-03-01 | |
P1433 | published in | Journal of Chemical Information and Computer Sciences | Q104614957 |
P1476 | title | Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds | |
P478 | volume | 44 |
Q30854803 | 'Metabolite-likeness' as a criterion in the design and selection of pharmaceutical drug libraries |
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Q33237551 | Assessing the scaffold diversity of screening libraries |
Q59444508 | CHAPTER 8. Discovery of NVP-AUY922 |
Q33382944 | CLEVER: pipeline for designing in silico chemical libraries. |
Q57002001 | Capter 11 Filtering in Drug Discovery |
Q45999839 | ChemMine. A compound mining database for chemical genomics. |
Q35059291 | Cheminformatic analysis of high-throughput compound screens. |
Q104493870 | Chemography: Searching for Hidden Treasures |
Q83983839 | Chemometrics |
Q80141780 | Collection and preparation of molecular databases for virtual screening |
Q27656518 | Combining hit identification strategies: fragment-based and in silico approaches to orally active 2-aminothieno[2,3-d]pyrimidine inhibitors of the Hsp90 molecular chaperone |
Q56983467 | Computational Tools for ADMET Profiling |
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Q33359104 | Investigation of the incidence of "undesirable" molecular moieties for high-throughput screening compound libraries in marketed drug compounds |
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Q28298611 | Navigating chemical space for biology and medicine |
Q30887386 | Optimizing the performance of in silico ADMET general models according to local requirements: MARS approach. solubility estimations as case study. |
Q38453607 | PharmaTrek: A Semantic Web Explorer for Open Innovation in Multitarget Drug Discovery |
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