Article
Chemistry, Multidisciplinary
Lina Dong, Xiaoyang Qu, Binju Wang
Summary: This study focuses on improving the performance and transferability of predicting protein-ligand binding affinities. By combining different features and utilizing a machine learning model, a new scoring function XLPFE has been developed, which demonstrated excellent performance across various protein-ligand complex structures.
Article
Multidisciplinary Sciences
Isabella A. Guedes, Andre M. S. Barreto, Diogo Marinho, Eduardo Krempser, Melaine A. Kuenemann, Olivier Sperandio, Laurent E. Dardenne, Maria A. Miteva
Summary: Scoring functions are crucial for in silico drug discovery, but accurate prediction of binding affinity remains a challenge. Developing scoring functions based on precise physics-based descriptors is necessary to improve prediction accuracy.
SCIENTIFIC REPORTS
(2021)
Article
Chemistry, Medicinal
Xiaoyang Qu, Lina Dong, Jinyan Zhang, Yubing Si, Binju Wang
Summary: This study incorporates the features extracted from protein-bound waters into machine learning-based scoring functions using the HydraMap method. The results show that this approach consistently improves the performance of the scoring functions, including their scoring, ranking, and docking power.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Biochemistry & Molecular Biology
Leilei Liang, Qingchuan Zheng
Summary: alpha-TOH is a potent antioxidant that is closely related to human health. The metabolism of CYP4F2 plays a crucial role in regulating the concentrations of alpha-TOH. Through simulation experiments and mutation simulations, the key interactions between CYP4F2 and alpha-TOH were investigated, providing insights into the regulatory mechanism of CYP4F2 on the metabolism of alpha-TOH.
JOURNAL OF CELLULAR BIOCHEMISTRY
(2023)
Article
Chemistry, Medicinal
Chao Yang, Yingkai Zhang
Summary: In this study, the robustness and applicability of machine-learning scoring functions were further improved by expanding the training set, developing meaningful features, using a linear empirical scoring function as the baseline, and applying extreme gradient boosting (XGBoost) with Delta-machine learning. The new scoring function demonstrated superior performance in scoring and ranking in various structure types and showed reliability and robustness in virtual screening applications.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Biochemical Research Methods
Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Haiyang Zhong, Gaoang Wang, Xiaojun Yao, Lei Xu, Dongsheng Cao, Tingjun Hou
Summary: Research has shown that machine learning-based scoring functions outperform classical scoring functions in predicting protein-ligand binding affinity. Gradient boosting decision tree and random forest achieved the best predictions in most cases. The superiority of machine learning-based scoring functions is fully guaranteed when the training set contains sufficient similar targets.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Viet-Khoa Tran-Nguyen, Muhammad Junaid, Saw Simeon, Pedro J. Ballester
Summary: Structure-based virtual screening (SBVS) via docking has been effectively used to discover active molecules for therapeutic targets. Artificial intelligence, particularly machine learning, has been utilized to build scoring functions (SFs) for SBVS. This article presents a comprehensive protocol for building and evaluating these SFs to enhance SBVS performance.
Article
Biochemical Research Methods
Zechen Wang, Liangzhen Zheng, Sheng Wang, Mingzhi Lin, Zhihao Wang, Adams Wai-Kin Kong, Yuguang Mu, Yanjie Wei, Weifeng Li
Summary: Recently reported machine learning- or deep learning-based scoring functions (SFs) have shown promising performance in predicting protein-ligand binding affinities and have great application prospects. However, accurately differentiating between highly similar ligand conformations, including the native binding pose, remains challenging. Thus, this study presents a fully differentiable, end-to-end framework (DeepRMSD+Vina) for ligand pose optimization based on a hybrid scoring function and traditional AutoDock Vina. The evaluation results demonstrate that DeepRMSD+Vina outperforms most existing SFs and shows high potential in drug design and discovery.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Maria Kadukova, Karina Dos Santos Machado, Pablo Chacon, Sergei Grudinin
Summary: This study introduces a novel coarse-grained potential based on a 3D joint probability distribution function that depends only on the pairwise orientation and position between protein backbone and ligand atoms. Despite its simplicity, this approach demonstrates competitive results in docking and screening tasks compared to state-of-the-art scoring functions.
Article
Chemistry, Medicinal
Yanjun Li, Daohong Zhou, Guangrong Zheng, Xiaolin Li, Dapeng Wu, Yaxia Yuan
Summary: This study proposes two new features based on the static structure of protein-ligand complexes to complement current scoring functions for accurate prediction of protein-ligand binding affinity. These features characterize the geometry-shape matching and dynamic stability of protein-ligand binding. By combining these new features with classical scoring functions, the DyScore model achieves state-of-the-art performance in distinguishing active and decoy ligands, especially in early recognition.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Mathematics
Dessislava Jereva, Petko Alov, Ivanka Tsakovska, Maria Angelova, Vassia Atanassova, Peter Vassilev, Nikolay Ikonomov, Krassimir Atanassov, Ilza Pajeva, Tania Pencheva
Summary: This study evaluates the performance of different types of scoring functions implemented in molecular modeling software packages. The results show that the performance of scoring functions varies depending on the protein target, and none of the studied scoring functions can accurately predict the binding affinities of the compounds.
Article
Chemistry, Medicinal
Lim Heo, Sangwoo Park, Chaok Seok
Summary: The article presents a novel method, GalaxyWater-wKGB, for predicting water positions on the protein surface, based on a statistical potential incorporating the generalized Born model. This method is accurate and rapid due to the effective statistical treatment, providing a more precise description of specific protein atom-water interactions compared to traditional methods.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Biochemistry & Molecular Biology
Chandan Sarkar, Mohnad Abdalla, Milon Mondal, Abul Bashar Ripon Khalipha, Nasir Ali
Summary: Ebselen, an active selenoorganic compound, shows potential inhibitory activity against various viral infections including SARS-CoV-2. The study reveals that Ebselen exhibits high affinity to selected drug targets of SARS-CoV-2, suggesting its candidacy for COVID-19 treatment.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2022)
Article
Biochemistry & Molecular Biology
Mateusz Zalewski, Sebastian Kmiecik, Michal Kolinski
Summary: This study proposes an MD-based scoring approach to identify high-accuracy protein-peptide models from CG docking simulations. The accuracy of the scoring can be significantly affected by the quality of the reconstructed protein receptor structures.
Article
Biochemical Research Methods
Mingwei Pang, Wangqiu He, Xufeng Lu, Yuting She, Liangxu Xie, Ren Kong, Shan Chang
Summary: This study proposes a docking method that combines template-based modeling and a scoring function for ligand binding prediction in CASP15. Among the 21 targets, successful predictions were obtained for 14 targets in the top 5 submissions, and partially successful predictions were obtained for 4 targets. Particularly, the method successfully predicted the binding of most ligands for the most complex target, H1114. Analysis of failed systems revealed that conformational changes in the receptor protein may cause large structural deviations in ligand binding prediction. In summary, the hybrid docking scheme efficiently addresses the challenges in ligand binding prediction in CASP15.
BMC BIOINFORMATICS
(2023)
Article
Multidisciplinary Sciences
Tatu Pantsar, Philipp D. Kaiser, Mark Kudolo, Michael Forster, Ulrich Rothbauer, Stefan A. Laufer
Summary: Target residence time is crucial for the pharmacological activity of small molecule inhibitors. This study used molecular dynamics simulations to gain insight into the underlying causes of inhibitor residence time at the molecular level. The results highlight the importance of protein conformational stability, solvent exposure, buried surface area of the ligand, and binding site resolvation energy for residence time.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Medicinal
Milla Kurki, Antti Poso, Piia Bartos, Markus S. Miettinen
Summary: This study investigates the impact of the OPLS3e force field on POPC bilayers under varying hydration and ion concentrations. The results demonstrate that OPLS3e performs similarly to CHARMM36, accurately simulating the behavior of lipid molecules. However, it overestimates the binding affinity of cations in ion-rich systems.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Medicinal
Vinicius Goncalves Maltarollo, Ekaterina Shevchenko, Igor Daniel de Miranda Lima, Elio A. Cino, Glaucio Monteiro Ferreira, Antti Poso, Thales Kronenberger
Summary: This study used molecular dynamics to investigate the effects of inhibitors on tetramerization of the enzyme FabI. The results suggest that multimerization is essential for the integrity of the catalytic site and that inhibitor binding enables multimerization by stabilizing the substrate binding loop. AFN-1252 induces unique conformational changes affecting monomer-monomer interfaces and allows more water molecules to enter the binding site.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Medicine, Research & Experimental
Johanna Huttunen, Thales Kronenberger, Ahmed B. Montaser, Adela Kralova, Tetsuya Terasaki, Antti Poso, Kristiina M. Huttunen
Summary: This study explored the interactions between L-type amino acid transporter 1 (LAT1)-utilizing prodrugs and sodium-coupled neutral amino acid transporter 2 (SNAT2). It was found that the cellular uptake of LAT1-utilizing prodrugs in MCF-7 cells was mediated by SNATs, which increased at higher pH, decreased in the absence of sodium, and was inhibited by a SNAT-inhibitor. Docking, molecular dynamics simulations, and analysis confirmed the chemical features supporting the interactions of the studied compounds with SNAT2.
MOLECULAR PHARMACEUTICS
(2023)
Article
Medicine, Research & Experimental
Katayun Bahrami, Juulia Järvinen, Tuomo Laitinen, Mika Reinisalo, Paavo Honkakoski, Antti Poso, Kristiina M. Huttunen, Jarkko Rautio
Summary: In this study, a series of LAT1-targeted drug-phenylalanine conjugates were evaluated. Through in vitro studies and induced-fit docking, it was concluded that smaller compounds were preferred for uptake by LAT1. The flexibility of the ligand played a crucial role in determining the transportability and interactions with LAT1. Introducing polar groups enhanced interactions, while compounds with a carbamate bond in the para-position of the aromatic ring displayed efficient transport efficiencies. The findings of this study have implications for designing CNS or antineoplastic drug candidates and discovering LAT1 inhibitors for cancer therapy.
MOLECULAR PHARMACEUTICS
(2023)
Article
Chemistry, Medicinal
Lukas Imberg, Simon Platte, Catharina Erbacher, Constantin G. Daniliuc, Svetlana A. Kalinina, Wolfgang Doerner, Antti Poso, Uwe Karst, Dmitrii Kalinin
Summary: To combat thrombosis, we synthesized a series of amide-functionalized acylated 1,2,4-triazol-5-amines and found that one compound effectively inhibits FXIIa while another compound effectively inhibits thrombin. Mass-shift experiments and molecular modeling studies confirmed that the inhibition of FXIIa and thrombin by these compounds is through a covalent mechanism. In plasma coagulation tests, these compounds showed anticoagulant properties mainly affecting the intrinsic blood coagulation pathway associated with thrombosis but with minimal impact on hemostasis.
ACS PHARMACOLOGY & TRANSLATIONAL SCIENCE
(2022)
Article
Chemistry, Medicinal
Renne Leini, Tatu Pantsar
Summary: The KRAS SII-P is a successful tool for targeting KRAS with small molecules, as proven by the development of FDA-approved drugs and engagement with multiple mutants. A conserved water molecule in the pocket plays an important role, and its energetics and behavior were studied in the presence of inhibitors. The results highlight the significance of this water molecule in designing new inhibitors.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Teodor Dimitrov, Athina Anastasia Moschopoulou, Lennart Seidel, Thales Kronenberger, Mark Kudolo, Antti Poso, Christian Geibel, Pascal Woelffing, Daniel Dauch, Lars Zender, Dieter Schollmeyer, Juergen Bajorath, Michael Forster, Stefan Laufer
Summary: The ATM kinase is an important regulator of the cellular response to DNA double-strand breaks and is considered a promising target in cancer treatment. This study introduces a new class of specific benzimidazole-based ATM inhibitors with high potency against the isolated enzyme and favorable selectivity within related kinases. These inhibitors show strong enzymatic and cellular activities, as well as promising pharmacokinetic properties and selectivities within the PIKK and PI3K families.
JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Pharmacology & Pharmacy
Glaucio Valdameri, Diogo Henrique Kita, Julia de Paula Dutra, Diego Lima Gomes, Arun Kumar Tonduru, Thales Kronenberger, Bruno Gavinho, Izadora Volpato Rossi, Mariana Mazetto de Carvalho, Basile Peres, Ingrid Fatima Zattoni, Fabiane Gomes de Moraes Rego, Geraldo Picheth, Rilton Alves de Freitas, Antti Poso, Suresh V. Ambudkar, Marcel Ramirez, Ahcene Boumendjel, Vivian Rotuno Moure
Summary: Inhibition of ABC transporters is a promising strategy to overcome multidrug resistance in cancer. This study identified a potent ABCG2 inhibitor called chromone 4a (C4a) that exhibits selectivity towards ABCG2. C4a effectively inhibited the efflux of different substrates mediated by ABCG2 and showed potential for drug delivery using liposomes and extracellular vesicles (EVs) in overcoming poor water solubility.
Article
Chemistry, Medicinal
Glaucio Monteiro Ferreira, Thales Kronenberger, Vinicius Goncalves Maltarollo, Antti Poso, Fernando de Moura Gatti, Vitor Medeiros Almeida, Sandro Roberto Marana, Carla Duque Lopes, Daiane Yukie Tezuka, Sergio de Albuquerque, Flavio da Silva Emery, Gustavo Henrique Goulart Trossini
Summary: The etiological agent of Chagas disease, Trypanosoma cruzi, relies on precise epigenetic regulation during host transitions. In this study, we used molecular modelling and experimental validation to discover new inhibitors from commercially available compound libraries. Six inhibitors were selected from virtual screening and validated on the recombinant Sir2 enzyme. The most potent inhibitor (CDMS-01, IC50 = 40 mu M) was chosen as a potential lead compound.
Article
Chemistry, Medicinal
Toni Sivula, Laxman Yetukuri, Tuomo Kalliokoski, Heikki Kasnanen, Antti Poso, Ina Pohner
Summary: The emergence of ultra-large screening libraries poses a challenge for docking-based virtual screening. Machine learning-boosted strategies like HASTEN combine rapid ML prediction with the brute-force docking to increase screening throughput. In our case study, we observed a significant reduction in docking experiments by 99% using HASTEN, resulting in shorter screening time.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Organic
Xiaodan Ouyang, Paul M. D'Agostino, Matti Wahlsten, Endrews Delbaje, Jouni Jokela, Perttu Permi, Greta Gaiani, Antti Poso, Piia Bartos, Tobias A. M. Gulder, Hannu Koistinen, David P. Fewer
Summary: In this study, a comparative bioinformatic analysis was used to identify radiosumin biosynthetic gene clusters in the genomes of 13 filamentous cyanobacteria. The entire biosynthetic gene cluster was captured and expressed in Escherichia coli. High-resolution liquid chromatography-mass spectrometry, nuclear magnetic resonance spectroscopy, and chemical degradation analysis revealed the chemical structure of novel radiosumins produced by cyanobacteria. Radiosumin C was found to inhibit human trypsin isoforms selectively.
ORGANIC & BIOMOLECULAR CHEMISTRY
(2023)
Article
Chemistry, Medicinal
Karoline B. Waitman, Larissa C. de Almeida, Marina C. Primi, Jorge A. E. G. Carlos, Claudia Ruiz, Thales Kronenberger, Stefan Laufer, Marcia Ines Goettert, Antti Poso, Sandra V. Vassiliades, Vinicius A. M. de Souza, Monica F. Z. J. Toledo, Neuza M. A. Hassimotto, Michael D. Cameron, Thomas D. Bannister, Leticia Costa-Lotufo, Joa o A. Machado-Neto, Mauricio T. Tavares, Roberto Parise-Filho
Summary: A series of hybrid inhibitors combining pharmacophores of known kinase inhibitors and benzohydroxamate HDAC inhibitors were synthesized and evaluated for their anticancer activity and pharmacokinetic properties. Compounds 4d-f exhibited promising cytotoxicity against hematological cells and moderate activity against solid tumor models. Compound 4d showed potent inhibition of multiple kinase targets and had stable interactions with HDAC and members of the JAK family. These compounds showed selective cytotoxicity with minimal effects on non-tumorigenic cells and favorable pharmacokinetic profiles.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2024)
Article
Chemistry, Medicinal
Alp Bayrak, Florian Mohr, Kyra Kolb, Martyna Szpakowska, Ekaterina Shevchenko, Valerie Dicenta, Anne-Katrin Rohlfing, Mark Kudolo, Tatu Pantsar, Marcel Guenther, Agnieszka A. Kaczor, Antti Poso, Andy Chevigne, Thanigaimalai Pillaiyar, Meinrad Gawaz, Stefan A. Laufer
Summary: This study reports the discovery and development of first-in-class ACKR3 agonists, which demonstrated superagonistic properties in a fi-arrestin recruitment assay. Through structure-activity relationship studies, novel compounds with selective activity against ACKR3 were identified, showing potential as candidates for the treatment of platelet-mediated thrombosis.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Azam Rashidian, Enni-Kaisa Mustonen, Thales Kronenberger, Matthias Schwab, Oliver Burk, Stefan A. Laufer, Tatu Pantsar
Summary: In this study, the authors used molecular dynamics simulations and experimental methods to investigate the mechanism of action of a newly identified compound 100 as a PXR antagonist. The results provide insights into the conformational changes in the PXR ligand binding domain induced by compound 100, and reveal the ligand-specific influence on different regions of PXR-LBD. This research is important for understanding the function of PXR and guiding drug design.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)