Results 211 to 220 of about 952,013 (342)

Computer vision as a new paradigm for monitoring of solution and solid phase peptide synthesis. [PDF]

Chem Sci, 2023
Yan C, Fyfe C, Minty L, Barrington H, Jamieson C, Reid M.   +5 more
europepmc   +1 more source

Studies on Peptides. XXII. Synthesis of the partially Protected Pentadecapeptide related to Monkey and Human β-Melanocyte-stimulating Hormones

, 1969
Haruaki Yajima, Yoshio Okada, HIROKI KAWATANI, Nariakira Mizokami   +3 more
openalex   +2 more sources

Synthesis of Peptides of ,β-Amino-acids. Part III [PDF]

, 1965
A. B. Sen, M. S. Yajnik
openalex   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Fundamental Aspects of SPPS and Green Chemical Peptide Synthesis. [PDF]

J Pept Sci
Kent SBH.
europepmc   +1 more source

Practical Protocols for Solid-Phase Peptide Synthesis 4.0. [PDF]

Methods Protoc, 2022
de la Torre BG, Albericio F.
europepmc   +1 more source

Synthesis and Biological Activity of Peptides Related to Eledoisin. II. Hexapeptide Amides ContainingN-Methylamino Acids [PDF]

, 1973
Hiroshi Sugano, Ko Higaki, Muneji Miyoshi   +2 more
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

PEPTIDE SYNTHESIS IN VIVO

Journal of Biological Chemistry, 1947
David M. Greenberg, Felix Friedberg, Theodore Winnick   +2 more
openaire   +2 more sources

Synthetic ramoplanin analogues are accessible by effective incorporation of arylglycines in solid-phase peptide synthesis. [PDF]

Chem Sci, 2023
Marschall E, Cass RW, Prasad KM, Swarbrick JD, McKay AI, Payne JAE, Cryle MJ, Tailhades J.   +7 more
europepmc   +1 more source