The three-dimensional conformations adopted by a free ligand in solution impact bioactivity and physicochemical properties. Solution 1D NMR spectra inherently contain information on ligand conformational flexibility and three-dimensional shape, as well as the propensity of the free ligand to fully preorganize into the bioactive conformation. Herein we discuss some key learnings, distilled from our experience developing potent and selective synthetic macrocyclic inhibitors, including Mcl-1 clinical candidate AZD5991. Case studies have been selected from recent oncology research projects, demonstrating how 1D NMR conformational signatures can complement X-ray protein-ligand structural information to guide medicinal chemistry optimization. Learning to extract free ligand conformational information from routinely available 1D NMR signatures has proven to be fast enough to guide medicinal chemistry decisions within design cycles for compound optimization.
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http://dx.doi.org/10.1021/acs.jmedchem.9b00716 | DOI Listing |
Cytotherapy
December 2024
Department of Internal Medicine I: Hematology with Stem Cell Transplantation, Hemostaseology and Medical Oncology, Ordensklinikum Linz-Elisabethinen, Linz, Austria; Medical Faculty, Johannes Kepler University, Linz, Austria.
Background Aims: In HLA-identical hematopoietic stem cell transplantation (HSCT), HLA-C1 group killer cell immunoglobulin-like receptor (KIR) ligands have been linked to graft-versus-host disease, whereas C2 homozygosity was associated with increased relapses. The differential impact of the recipients versus the donor's HLA-C KIR ligands cannot be determined in HLA-identical HSCT but may be elucidated in the haploidentical setting, in which HLA-C (including the HLA-C KIR ligand group) mismatching is frequently present.
Methods: We retrospectively investigated the effect of recipient versus donor C1 ligand content on survival and complications in post-transplant cyclophosphamide (PTCy)-based haploidentical HSCT (n = 170).
J Immunother Cancer
January 2025
Department of Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Background: Immune checkpoint inhibitors (ICIs) are recommended to treat patients with deficient mismatch repair/microsatellite instability high (dMMR/MSI-H) metastatic colorectal cancer (mCRC). Pivotal trials have fixed a maximum ICI duration of 2 years, without a compelling rationale. A shorter treatment duration has the potential to improve patients' quality of life and reduce both toxicity and cost without compromising efficacy.
View Article and Find Full Text PDFInt J Pharm
January 2025
Institute of Biochemistry and Molecular Biology, School of Life Sciences, Lanzhou University, Lanzhou, Gansu 730000, China. Electronic address:
Kisspeptins function as endogenous ligands for the G protein-coupled receptor GPR54. While the primary role of the Kisspeptin/GPR54 signaling pathway pertains to reproduction, several studies have shown that GPR54 is highly expressed in breast cancer, and we further confirmed this result that GPR54 expression is significantly upregulated in breast cancer cells. Based on this finding, we developed a liposomal drug delivery system utilizing the Kisspeptin/GPR54 system to treat breast cancer after confirming the safety of Kp-10-228.
View Article and Find Full Text PDFJ Thorac Oncol
January 2025
Washington University School of Medicine, St. Louis, Missouri.
Introduction: The phase 2 TROPiCS-03 study evaluated the efficacy/safety of sacituzumab govitecan (SG) as second-line treatment in patients with previously treated extensive-stage small cell lung cancer (ES-SCLC).
Methods: TROPiCS-03 (NCT03964727) is a multicohort, open-label, phase 2 basket study in solid tumors, including ES-SCLC. Adults with ES-SCLC that progressed after one prior line of platinum-based chemotherapy and anti-programmed death-(ligand) 1 (PD-[L]1) therapy received SG 10 mg/kg on days 1 and 8 of a 21-day cycle.
J Chem Theory Comput
January 2025
Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several times more computationally demanding than MM simulations, so there is a trade-off between speed and accuracy. One possible compromise are hybrid machine learning/molecular mechanics (ML/MM) approaches with mechanical embedding that treat the intramolecular interactions of the ligand at the ML level and the protein-ligand interactions at the MM level.
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