1
|
Duan G, Ji C, Zhang JZH. Developing an effective polarizable bond method for small molecules with application to optimized molecular docking. RSC Adv 2020; 10:15530-15540. [PMID: 35495446 PMCID: PMC9052371 DOI: 10.1039/d0ra01483d] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 03/31/2020] [Indexed: 12/20/2022] Open
Abstract
Electrostatic interaction plays an essential role in protein-ligand binding. Due to the polarization effect, electrostatic interactions are largely impacted by their local environments. However, traditional force fields use fixed point charge-charge interactions to describe electrostatic interactions but is unable to include the polarization effect. The lack of the polarization effect in the force field representation can result in substantial error in biomolecular studies, such as molecular dynamics and molecular docking. Docking programs usually employ traditional force fields to estimate the binding energy between a ligand and a protein for pose selection or scoring. The intermolecular interaction energy mainly consists of van der Waals and electrostatic interaction in the force field representation. In the current study, we developed an Effective Polarizable Bond (EPB) method for small organic molecules and applied this EPB method to optimize protein-ligand docking in computational tests for a variety of protein-ligand systems. We tested the method on a set of 38 cocrystallized structures taken from the Protein Data Bank (PDB) and found that the maximum error was reduced from 7.98 Å to 2.03 Å when using EPB Dock, providing strong evidence that the use of EPB charges is important. We found that our optimized docking approach with EPB charges could improve the docking performance, sometimes dramatically, and the maximum error was reduced from 12.88 Å to 1.57 Å in Optimized Docking (in the case of 1fqx). The average RMSD decreased from 2.83 Å to 1.85 Å. Further investigations showed that the use of the EBP method could enhance intermolecular hydrogen bonding, which is a major contributing factor to improved docking performance. Developed tools for the calculation of the polarized ligand charge from a protein-ligand complex structure with the EPB method are freely available on GitHub (https://github.com/Xundrug/EPB).
Collapse
Affiliation(s)
- Guanfu Duan
- Shanghai Engineering Research Center for Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University Shanghai 200062 China
| | - Changge Ji
- Shanghai Engineering Research Center for Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University Shanghai 200062 China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai Shanghai 200062 China
| | - John Z H Zhang
- Shanghai Engineering Research Center for Molecular Therapeutics and New Drug Development, Shanghai Key Laboratory of Green Chemistry & Chemical Process, School of Chemistry and Molecular Engineering, East China Normal University Shanghai 200062 China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai Shanghai 200062 China
- Department of Chemistry, New York University NY NY 10003 USA
- Collaborative Innovation Center of Extreme Optics, Shanxi University Taiyuan Shanxi 030006 China
| |
Collapse
|
2
|
Abstract
AbstractDuring three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.
Collapse
|
3
|
Novel selective, potent naphthyl TRPM8 antagonists identified through a combined ligand- and structure-based virtual screening approach. Sci Rep 2017; 7:10999. [PMID: 28887460 PMCID: PMC5591244 DOI: 10.1038/s41598-017-11194-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2017] [Accepted: 07/21/2017] [Indexed: 02/03/2023] Open
Abstract
Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predominant mammalian cold temperature thermosensor and it is activated by cold temperatures and cooling compounds, such as menthol and icilin. Because of its role in cold allodynia, cold hyperalgesia and painful syndromes TRPM8 antagonists are currently being pursued as potential therapeutic agents for the treatment of pain hypersensitivity. Recently TRPM8 has been found in subsets of bladder sensory nerve fibres, providing an opportunity to understand and treat chronic hypersensitivity. However, most of the known TRPM8 inhibitors lack selectivity, and only three selective compounds have reached clinical trials to date. Here, we applied two virtual screening strategies to find new, clinics suitable, TRPM8 inhibitors. This strategy enabled us to identify naphthyl derivatives as a novel class of potent and selective TRPM8 inhibitors. Further characterization of the pharmacologic properties of the most potent compound identified, compound 1, confirmed that it is a selective, competitive antagonist inhibitor of TRPM8. Compound 1 also proved itself active in a overreactive bladder model in vivo. Thus, the novel naphthyl derivative compound identified here could be optimized for clinical treatment of pain hypersensitivity in bladder disorders but also in different other pathologies.
Collapse
|
4
|
Mirzaei H, Zarbafian S, Villar E, Mottarella S, Beglov D, Vajda S, Paschalidis IC, Vakili P, Kozakov D. Energy Minimization on Manifolds for Docking Flexible Molecules. J Chem Theory Comput 2016; 11:1063-76. [PMID: 26478722 DOI: 10.1021/ct500155t] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
In this paper, we extend a recently introduced rigid body minimization algorithm, defined on manifolds, to the problem of minimizing the energy of interacting flexible molecules. The goal is to integrate moving the ligand in six dimensional rotational/translational space with internal rotations around rotatable bonds within the two molecules. We show that adding rotational degrees of freedom to the rigid moves of the ligand results in an overall optimization search space that is a manifold to which our manifold optimization approach can be extended. The effectiveness of the method is shown for three different docking problems of increasing complexity. First, we minimize the energy of fragment-size ligands with a single rotatable bond as part of a protein mapping method developed for the identification of binding hot spots. Second, we consider energy minimization for docking a flexible ligand to a rigid protein receptor, an approach frequently used in existing methods. In the third problem, we account for flexibility in both the ligand and the receptor. Results show that minimization using the manifold optimization algorithm is substantially more efficient than minimization using a traditional all-atom optimization algorithm while producing solutions of comparable quality. In addition to the specific problems considered, the method is general enough to be used in a large class of applications such as docking multidomain proteins with flexible hinges. The code is available under open source license (at http://cluspro.bu.edu/Code/Code_Rigtree.tar) and with minimal effort can be incorporated into any molecular modeling package.
Collapse
|
5
|
|
6
|
Neves BJ, Muratov E, Machado RB, Andrade CH, Cravo PVL. Modern approaches to accelerate discovery of new antischistosomal drugs. Expert Opin Drug Discov 2016; 11:557-67. [PMID: 27073973 DOI: 10.1080/17460441.2016.1178230] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects. AREAS COVERED Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors. EXPERT OPINION Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.
Collapse
Affiliation(s)
- Bruno Junior Neves
- a LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia , Universidade Federal de Goiás , Goiânia , Brazil
| | - Eugene Muratov
- b Laboratory for Molecular Modeling, Eshelman School of Pharmacy , University of North Carolina , Chapel Hill , NC , USA
| | - Renato Beilner Machado
- c GenoBio - Laboratory of Genomics and Biotechnology, Instituto de Patologia Tropical e Saúde Pública , Universidade Federal de Goiás , Goiânia , Brazil
| | - Carolina Horta Andrade
- a LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia , Universidade Federal de Goiás , Goiânia , Brazil
| | - Pedro Vitor Lemos Cravo
- c GenoBio - Laboratory of Genomics and Biotechnology, Instituto de Patologia Tropical e Saúde Pública , Universidade Federal de Goiás , Goiânia , Brazil.,d Instituto de Higiene e Medicina Tropical , Universidade Nova de Lisboa , Lisbon , Portugal
| |
Collapse
|
7
|
Karthick V, Nagasundaram N, Doss CGP, Chakraborty C, Siva R, Lu A, Zhang G, Zhu H. Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus. Infect Dis Poverty 2016; 5:12. [PMID: 26888469 PMCID: PMC4757971 DOI: 10.1186/s40249-016-0105-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 01/28/2016] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The Ebola virus is highly pathogenic and destructive to humans and other primates. The Ebola virus encodes viral protein 40 (VP40), which is highly expressed and regulates the assembly and release of viral particles in the host cell. Because VP40 plays a prominent role in the life cycle of the Ebola virus, it is considered as a key target for antiviral treatment. However, there is currently no FDA-approved drug for treating Ebola virus infection, resulting in an urgent need to develop effective antiviral inhibitors that display good safety profiles in a short duration. METHODS This study aimed to screen the effective lead candidate against Ebola infection. First, the lead molecules were filtered based on the docking score. Second, Lipinski rule of five and the other drug likeliness properties are predicted to assess the safety profile of the lead candidates. Finally, molecular dynamics simulations was performed to validate the lead compound. RESULTS Our results revealed that emodin-8-beta-D-glucoside from the Traditional Chinese Medicine Database (TCMD) represents an active lead candidate that targets the Ebola virus by inhibiting the activity of VP40, and displays good pharmacokinetic properties. CONCLUSION This report will considerably assist in the development of the competitive and robust antiviral agents against Ebola infection.
Collapse
Affiliation(s)
- V Karthick
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - N Nagasundaram
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - C George Priya Doss
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.,Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, Tamil Nadu, India
| | - Chiranjib Chakraborty
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.,Department of Bioinformatics, School of Computer and Information Sciences, Galgotias University, Noida, India
| | - R Siva
- Department of Biotechnology, School of Biosciences and Technology, VIT University, Vellore, Tamil Nadu, India
| | - Aiping Lu
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Ge Zhang
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Hailong Zhu
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
| |
Collapse
|
8
|
Nybond S, Ghemtio L, Nawrot DA, Karp M, Xhaard H, Tammela P. Integrated In Vitro–In Silico Screening Strategy for the Discovery of Antibacterial Compounds. Assay Drug Dev Technol 2015; 13:25-33. [DOI: 10.1089/adt.2014.625] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Susanna Nybond
- Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Leo Ghemtio
- Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Dorota A. Nawrot
- Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Matti Karp
- Department of Chemistry and Bioengineering, Tampere University of Technology, Tampere, Finland
| | - Henri Xhaard
- Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
- Division of Pharmaceutical Chemistry and Technology, University of Helsinki, Helsinki, Finland
| | - Päivi Tammela
- Centre for Drug Research, Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| |
Collapse
|
9
|
Alderson RG, De Ferrari L, Mavridis L, McDonagh JL, Mitchell JBO, Nath N. Enzyme informatics. Curr Top Med Chem 2014; 12:1911-23. [PMID: 23116471 DOI: 10.2174/156802612804547353] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Revised: 09/12/2012] [Accepted: 09/15/2012] [Indexed: 12/18/2022]
Abstract
Over the last 50 years, sequencing, structural biology and bioinformatics have completely revolutionised biomolecular science, with millions of sequences and tens of thousands of three dimensional structures becoming available. The bioinformatics of enzymes is well served by, mostly free, online databases. BRENDA describes the chemistry, substrate specificity, kinetics, preparation and biological sources of enzymes, while KEGG is valuable for understanding enzymes and metabolic pathways. EzCatDB, SFLD and MACiE are key repositories for data on the chemical mechanisms by which enzymes operate. At the current rate of genome sequencing and manual annotation, human curation will never finish the functional annotation of the ever-expanding list of known enzymes. Hence there is an increasing need for automated annotation, though it is not yet widespread for enzyme data. In contrast, functional ontologies such as the Gene Ontology already profit from automation. Despite our growing understanding of enzyme structure and dynamics, we are only beginning to be able to design novel enzymes. One can now begin to trace the functional evolution of enzymes using phylogenetics. The ability of enzymes to perform secondary functions, albeit relatively inefficiently, gives clues as to how enzyme function evolves. Substrate promiscuity in enzymes is one example of imperfect specificity in protein-ligand interactions. Similarly, most drugs bind to more than one protein target. This may sometimes result in helpful polypharmacology as a drug modulates plural targets, but also often leads to adverse side-effects. Many chemoinformatics approaches can be used to model the interactions between druglike molecules and proteins in silico. We can even use quantum chemical techniques like DFT and QM/MM to compute the structural and energetic course of enzyme catalysed chemical reaction mechanisms, including a full description of bond making and breaking.
Collapse
Affiliation(s)
- Rosanna G Alderson
- Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland, UK
| | | | | | | | | | | |
Collapse
|