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Deep Learning Combined with Quantitative Structure‒Activity Relationship Accelerates De Novo Design of Antifungal Peptides.

• Authors : Yin K; Zhengzhou Key Laboratory of Functional Molecules for Biomedical Research, Henan University of Technology, Zhengzhou, Henan, 450001, P. R. China.; College of Information Science and Engineering, Henan University of Technology, Zhengzhou, Henan, 450001, P. R. China.

Subjects: Deep Learning* ; Antifungal Agents*/Antifungal Agents*/Antifungal Agents*/pharmacology ; Antifungal Agents*/Antifungal Agents*/Antifungal Agents*/chemistry

• Source: Advanced science (Weinheim, Baden-Wurttemberg, Germany) [Adv Sci (Weinh)] 2025 Apr; Vol. 12 (13), pp. e2412488. Date of Electronic Publication: 2025 Feb 08.Publisher: WILEY-VCH Country of Publication: Germany NLM ID: 101664569 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2198-3844

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مطالعه ارتباط کمی ساختار - فعالیت برخی از داروهای مهارکننده آنزیم مبدل آنژیوتانسین I در کنترل فشارخون بر اساس روش بهینه سازی مونت کارلو.

• Authors : شهرام لطفی¹ ; شهین احمدی²; علی عظیمی³

• Source: Journal of Ilam University of Medical Sciences. 2025, Vol. 33 Issue 2, p26-44. 19p.

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Three-Dimensional Quantitative Structure-Activity Relationship Study of Transient Receptor Potential Vanilloid 1 Channel Antagonists Reveals Potential for Drug Design Purposes.

• Authors : Gianibbi B; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy.; Visibelli A

Subjects: Quantitative Structure-Activity Relationship* ; TRPV Cation Channels*/TRPV Cation Channels*/TRPV Cation Channels*/antagonists & inhibitors ; TRPV Cation Channels*/TRPV Cation Channels*/TRPV Cation Channels*/metabolism

• Source: International journal of molecular sciences [Int J Mol Sci] 2024 Jul 21; Vol. 25 (14). Date of Electronic Publication: 2024 Jul 21.Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067

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Quantitative Structure-Activity Relationship Analysis of Angiotensin-Converting Enzyme Inhibitory Pentapeptides Based on Amino Acid Descriptors

• Authors : GUO Xingchen, LI Yuhao, MA Jinpu, ZHANG Yuxuan, LI Huaxin, YANG Jutian, FAN Peiru, GAO Dandan

Subjects: angiotensin-converting enzyme; peptides; partial least squares

• Source: Shipin Kexue, Vol 45, Iss 13, Pp 38-48 (2024)

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A Simple Machine Learning-Based Quantitative Structure–Activity Relationship Model for Predicting pIC 50 Inhibition Values of FLT3 Tyrosine Kinase.

• Authors : Alcázar, Jackson J.¹ (AUTHOR) ; Sánchez, Ignacio¹ (AUTHOR); Merino, Cristian¹ (AUTHOR)

• Source: Pharmaceuticals (14248247). Jan2025, Vol. 18 Issue 1, p96. 18p.

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Quantitative Structure-Activity Relationship in the Series of 5-Ethyluridine, N2-Guanine, and 6-Oxopurine Derivatives with Pronounced Anti-Herpetic Activity.

• Authors : Khairullina V; Institute of Chemistry and Defence in Emergency Situations, Ufa University of Science and Technology, 50076 Ufa, Russia.; Martynova Y

Subjects: Quantitative Structure-Activity Relationship* ; Herpesvirus 1, Human*; Guanine/Guanine/Guanine/chemistry

• Source: Molecules (Basel, Switzerland) [Molecules] 2023 Nov 22; Vol. 28 (23). Date of Electronic Publication: 2023 Nov 22.Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049

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Quantitative Structure–Activity Relationship (QSAR) Modeling of Chiral CCR2 Antagonists with a Multidimensional Space of Novel Chirality Descriptors.

• Authors : Natarajan, Ramanathan¹ (AUTHOR) ; Natarajan, Ganapathy S.² (AUTHOR) ; Basak, Subhash C.³ (AUTHOR)

Subjects: *Principal components analysis; *Environmental toxicology; *Chemokine receptors

• Source: Molecules. Jan2025, Vol. 30 Issue 2, p307. 14p.

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Topological regression as an interpretable and efficient tool for quantitative structure-activity relationship modeling

• Authors : Ruibo Zhang; Daniel Nolte; Cesar Sanchez-Villalobos

Subjects: 0303 health sciences; 03 medical and health sciences; Deep Learning

• Source: Nat CommunNature Communications, Vol 15, Iss 1, Pp 1-13 (2024)

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Computational transformation in drug discovery: A comprehensive study on molecular docking and quantitative structure activity relationship (QSAR).

• Authors : Shah, Manan¹ ; Patel, Maanit²; Shah, Monit³

• Source: Intelligent Pharmacy. Oct2024, Vol. 2 Issue 5, p589-595. 7p.

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Application of Machine Learning in the Development of Fourth Degree Quantitative Structure–Activity Relationship Model for Triclosan Analogs Tested against Plasmodium falciparum 3D7

• Authors : Railton Marques de Souza Guimarães; Ivo Henrique Provensi Vieira; Fabrício Berton Zanchi

Subjects: Chemistry; QD1-999

• Source: ACS OmegaACS Omega, Vol 9, Iss 44, Pp 44436-44447 (2024)

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