Results 181 to 190 of about 31,763 (232)

QSAR and scaffold-based optimization of HMGR inhibitors using cheminformatics and machine learning. [PDF]

Front Bioinform
Antony P, Baby B, Vijayan R.
europepmc   +1 more source

Dual PTP1B/DPP4 Inhibitory Potential of <i>Agathosma betulina</i>, <i>Cymbopogon citratus</i>, and <i>Artemisia afra</i>: Structure-Based Modeling of Phytochemical Leads and Essential Oil Bioassays. [PDF]

Comput Struct Biotechnol J
Adedirin O, Sabiu S.
europepmc   +1 more source

Machine Learning-Based QSAR Models for Discovery of Inhibitors Targeting <i>Leishmania infantum</i> Amastigotes. [PDF]

Pharmaceuticals (Basel)
Flores-Balmaseda N, Rojas-Vargas JA, Rojas-Socarrás S, Pérez-Giménez F, Torrens F, Castillo-Garit JA.   +5 more
europepmc   +1 more source

Assessment of mutagenic potential of puberulic acid contaminated in red yeast rice (beni-koji) health food supplements. [PDF]

Mutagenesis
Sugiyama KI, Furuhama A, Horibata K, Tsuda M, Izawa K, Tsuji G, Demizu Y, Matsushita K, Toyoda T, Hirabayashi Y, Saito Y, Honma M.   +11 more
europepmc   +1 more source

QSAR-Guided and Fragment-Based Drug Design of Monoterpenoid Inhibitors Targeting Ebola Virus Glycoprotein. [PDF]

Int J Mol Sci
Ait Lahcen N, Liman W, Zekri S, Ait Lahcen A, Alanazi AS, Alanazi MM, Delaite C, Maatallah M, Cherqaoui D.   +8 more
europepmc   +1 more source

An Explainable 2D-QSAR Machine Learning Approach for Predicting COX-2 Inhibitory Activity Using Molecular Fingerprints. [PDF]

Pharmaceuticals (Basel)
Ouassaf M, Alhatlani BY.
europepmc   +1 more source

Discovery of Structurally Distinct Covalent KRAS G12C Inhibitor Scaffolds Through Large-Scale In Silico Screening and Experimental Validation. [PDF]

Cancers (Basel)
Weiss GJ, Loftus JC, Mallery DW, Tran NL.   +3 more
europepmc   +1 more source

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QSAR: Then and Now

Current Topics in Medicinal Chemistry, 2002
AbstractFor Abstract see ChemInform Abstract in Full Text.
C D, Selassie, S B, Mekapati, R P, Verma
openaire   +2 more sources

QSAR and ADME

Bioorganic & Medicinal Chemistry, 2004
The prediction from structure of ADME (absorption, distribution, metabolism, elimination) of drug candidates is an important goal to achieve since it can considerably reduce the cost of drug development. Using our database of 10,700 QSAR, we are now reaching the point where we can make many useful comparisons that illustrate how ADME is a practical way
Corwin, Hansch, Albert, Leo, Suresh Babu, Mekapati, Alka, Kurup   +3 more
openaire   +2 more sources