An overview of scoring functions used for protein–ligand interactions in molecular docking

J Li, A Fu, L Zhang - Interdisciplinary Sciences: Computational Life …, 2019 - Springer
Currently, molecular docking is becoming a key tool in drug discovery and molecular
modeling applications. The reliability of molecular docking depends on the accuracy of the …

Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries

C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …

The impact of cross-docked poses on performance of machine learning classifier for protein–ligand binding pose prediction

C Shen, X Hu, J Gao, X Zhang, H Zhong… - Journal of …, 2021 - Springer
Abstract Structure-based drug design depends on the detailed knowledge of the three-
dimensional (3D) structures of protein–ligand binding complexes, but accurate prediction of …

Modern tools and techniques in computer-aided drug design

T Anwar, P Kumar, AU Khan - Molecular docking for computer-aided drug …, 2021 - Elsevier
Computer-aided drug design (CADD) has become an effective tool for the development of
therapeutics. CADD approaches parallelly assist the main drug discovery pipeline in many …

Application of machine learning techniques to predict binding affinity for drug targets: a study of cyclin-dependent kinase 2

G Bitencourt-Ferreira, A Duarte da Silva… - Current medicinal …, 2021 - benthamdirect.com
Background: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it
possible to develop targeted scoring functions for virtual screening aimed to identify new …

The rise of deep learning and transformations in bioactivity prediction power of molecular modeling tools

M Bule, N Jalalimanesh, Z Bayrami… - Chemical Biology & …, 2021 - Wiley Online Library
The search and design for the better use of bioactive compounds are used in many
experiments to best mimic compounds' functions in the human body. However, finding a cost …

[HTML][HTML] Advances in Artificial Intelligence (AI)-assisted approaches in drug screening

S Singh, H Gupta, P Sharma, S Sahi - Artificial Intelligence Chemistry, 2024 - Elsevier
Artificial intelligence (AI) is revolutionizing the current process of drug design and
development, addressing the challenges encountered in its various stages. By utilizing AI …

[HTML][HTML] Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities

S Vittorio, F Lunghini, P Morerio, D Gadioli… - Computational and …, 2024 - Elsevier
Molecular docking is a widely used technique in drug discovery to predict the binding mode
of a given ligand to its target. However, the identification of the near-native binding pose in …

Nonparametric chemical descriptors for the calculation of ligand-biopolymer affinities with machine-learning scoring functions

E Moman, MA Grishina, VA Potemkin - Journal of Computer-Aided …, 2019 - Springer
The computational prediction of ligand-biopolymer affinities is a crucial endeavor in modern
drug discovery and one that still poses major challenges. The choice of the appropriate …

Inhibiting two cellular mutant epidermal growth factor receptor tyrosine kinases by addressing computationally assessed crystal ligand pockets

JH Lee, WC Lin, TK Wen, C Wang… - Future Medicinal …, 2019 - Taylor & Francis
Aim: Blocking receptor tyrosine kinases is a useful strategy for inhibiting the overexpression
of EGFR. However, the quality of crystal pocket is an essential issue for virtually identifying …