Results 1 to 10 of about 18,735,434 (313)

Sequence-based drug design as a concept in computational drug design

Nature Communications, 2023
Drug development based on target proteins has been a successful approach in recent decades. However, the conventional structure-based drug design (SBDD) pipeline is a complex, human-engineered process with multiple independently optimized steps. Here, we
Lifan Chen, Zisheng Fan, Jie Chang, Ruirui Yang, Hui Hou, Hao Guo, Yinghui Zhang, Tianbiao Yang, Chenmao Zhou, Qibang Sui, Zhengyang Chen, Chen Zheng, Xinyue Hao, Keke Zhang, Rongrong Cui, Zehong Zhang, Hudson Ma, Yiluan Ding, Naixia Zhang, Xiaojie Lu, Xiaomin Luo, Hualiang Jiang, Sulin Zhang, Mingyue Zheng   +23 more
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Structure-based drug design with equivariant diffusion models [PDF]

Nature Computational Science, 2022
Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets.
Arne Schneuing, Yuanqi Du, Charles Harris, Arian R. Jamasb, Ilia Igashov, Weitao Du, T. Blundell, Pietro Li'o, Carla P. Gomes, Max Welling, Michael M. Bronstein, B. Correia   +11 more
semanticscholar   +1 more source

Drug design on quantum computers [PDF]

Nature Physics, 2023
The promised industrial applications of quantum computers often rest on their anticipated ability to perform accurate, efficient quantum chemical calculations.
R. Santagati, A. Aspuru‐Guzik, R. Babbush, M. Degroote, Leticia Gonzalez, E. Kyoseva, Nikolaj Moll, M. Oppel, R. Parrish, N. Rubin, Michael Streif, C. Tautermann, Horst Weiss, N. Wiebe, Clemens Utschig-Utschig   +14 more
semanticscholar   +1 more source

Structure-based drug design with geometric deep learning [PDF]

Current Opinion in Structural Biology, 2022
Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands.
Clemens Isert, Kenneth Atz, G. Schneider
semanticscholar   +1 more source

Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis

Pharmaceuticals, 2023
In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology.
Sarfaraz K. Niazi, Zamara Mariam
semanticscholar   +1 more source

Quality Evaluation of Pulsatilla chinensis Total Saponin Extracts via Quantitative Analysis of Multicomponents by Single Marker Method Combined with Systematic Quantified Fingerprint Method

Journal of Analytical Methods in Chemistry, 2022
Chinese medicine extracts are complex in composition. The combination of the quantitative analysis of multicomponents by single marker (QAMS) and the systematic quantified fingerprint method (SQFM) can be used for better quantitative analysis.
Long Chen, Suzhen Liu, Shuhan Feng, Liangliang Zhou, Zhenhua Chen   +4 more
doaj   +1 more source

Artificial intelligence in multi-objective drug design.

Current Opinion in Structural Biology, 2023
The factors determining a drug's success are manifold, making de novo drug design an inherently multi-objective optimisation (MOO) problem. With the advent of machine learning and optimisation methods, the field of multi-objective compound design has ...
Sohvi Luukkonen, Helle W. van den Maagdenberg, M. Emmerich, Gerard J. P. van Westen   +3 more
semanticscholar   +1 more source

Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach

Journal of Cheminformatics, 2022
Motivation Application of chemical named entity recognition (CNER) algorithms allows retrieval of information from texts about chemical compound identifiers and creates associations with physical–chemical properties and biological activities.
O. A. Tarasova, A. V. Rudik, N. Yu. Biziukova, D. A. Filimonov, V. V. Poroikov   +4 more
doaj   +1 more source

Advancements in small molecule drug design: A structural perspective.

Drug Discovery Today, 2023
In this review, we outline recent advancements in small molecule drug design from a structural perspective. We compare protein structure prediction methods and explore the role of the ligand binding pocket in structure-based drug design.
Ke Wu, Eduard Karapetyan, John Schloss, J. Vadgama, Yong Wu   +4 more
semanticscholar   +1 more source

A Guide to In Silico Drug Design

Pharmaceutics, 2022
The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or ...
Yiqun Chang, Bryson A. Hawkins, Jonathan J. Du, P. Groundwater, D. Hibbs, Felcia Lai   +5 more
semanticscholar   +1 more source