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Stampelou M, Ladds G, Kolocouris A. Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A 3 Receptor. J Phys Chem B 2024; 128:914-936. [PMID: 38236582 DOI: 10.1021/acs.jpcb.3c05986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.
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Affiliation(s)
- Margarita Stampelou
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Graham Ladds
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
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2
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Stampolaki M, Stylianakis I, Zgurskaya HI, Kolocouris A. Study of SQ109 analogs binding to mycobacterium MmpL3 transporter using MD simulations and alchemical relative binding free energy calculations. J Comput Aided Mol Des 2023; 37:245-264. [PMID: 37129848 DOI: 10.1007/s10822-023-00504-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 04/03/2023] [Indexed: 05/03/2023]
Abstract
N-geranyl-N΄-(2-adamantyl)ethane-1,2-diamine (SQ109) is a tuberculosis drug that has high potency against Mycobacterium tuberculosis (Mtb) and may function by blocking cell wall biosynthesis. After the crystal structure of MmpL3 from Mycobacterium smegmatis in complex with SQ109 became available, it was suggested that SQ109 inhibits Mmpl3 mycolic acid transporter. Here, we showed using molecular dynamics (MD) simulations that the binding profile of nine SQ109 analogs with inhibitory potency against Mtb and alkyl or aryl adducts at C-2 or C-1 adamantyl carbon to MmpL3 was consistent with the X-ray structure of MmpL3 - SQ109 complex. We showed that rotation of SQ109 around carbon-carbon bond in the monoprotonated ethylenediamine unit favors two gauche conformations as minima in water and lipophilic solvent using DFT calculations as well as inside the transporter's binding area using MD simulations. The binding assays in micelles suggested that the binding affinity of the SQ109 analogs was increased for the larger, more hydrophobic adducts, which was consistent with our results from MD simulations of the SQ109 analogues suggesting that sizeable C-2 adamantyl adducts of SQ109 can fill a lipophilic region between Y257, Y646, F260 and F649 in MmpL3. This was confirmed quantitatively by our calculations of the relative binding free energies using the thermodynamic integration coupled with MD simulations method with a mean assigned error of 0.74 kcal mol-1 compared to the experimental values.
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Affiliation(s)
- Marianna Stampolaki
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece
- Department of NMR-Based Structural Biology, Max Planck Institute for Multidisciplinary Sciences, Am Faßberg 11, 37077, Göttingen, Germany
| | - Ioannis Stylianakis
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece
| | - Helen I Zgurskaya
- Department of Chemistry and Biochemistry, University of Oklahoma, Stephenson Life Sciences Research Center, 101 Stephenson Parkway, Norman, OK, 73019-5251, USA
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771, Athens, Greece.
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Pal S, Kumar A, Vashisth H. Role of Dynamics and Mutations in Interactions of a Zinc Finger Antiviral Protein with CG-rich Viral RNA. J Chem Inf Model 2023; 63:1002-1011. [PMID: 36707411 PMCID: PMC10129844 DOI: 10.1021/acs.jcim.2c01487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Zinc finger antiviral protein (ZAP) is a host antiviral factor that selectively inhibits the replication of a variety of viruses. ZAP recognizes the CG-enriched RNA sequences and activates the viral RNA degradation machinery. In this work, we investigated the dynamics of a ZAP/RNA complex and computed the energetics of mutations in ZAP that affect its binding to the viral RNA. The crystal structure of a mouse-ZAP/RNA complex showed that RNA interacts with the zinc finger 2 (ZF2) and ZF3 domains. However, we found that due to the dynamic behavior of the single-stranded RNA, the terminal nucleotides C1 and G2 of RNA change their positions from the ZF3 to the ZF1 domain. Moreover, the electrostatic interactions between the zinc ions and the viral RNA provide further stability to the ZAP/RNA complex. We also provide structural and thermodynamic evidence for seven residue pairs (C1-Arg74, C1-Arg179, G2-Arg74, U3-Lys76, C4-Lys76, G5-Arg95, and U6-Glu204) that show favorable ZAP/RNA interactions, although these interactions were not observed in the ZAP/RNA crystal structure. Consistent with the observations from the mouse-ZAP/RNA crystal structure, we found that four residue pairs (C4-Lys89, C4-Leu90, C4-Tyr108, and G5-Lys107) maintained stable interactions in MD simulations. Based on experimental mutagenesis studies and our residue-level interaction analysis, we chose seven residues (Arg74, Lys76, Lys89, Arg95, Lys107, Tyr108, and Arg179) for individual alanine mutations. In addition, we studied mutations in those residues that are only observed in the crystal structures as interacting with RNA (Tyr98, Glu148, and Arg170). Out of these 10 mutations, we found that the Ala mutation in each of the five residues Arg74, Lys76, Lys89, Lys107, and Glu148 significantly reduced the binding affinity of ZAP to RNA.
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Affiliation(s)
- Saikat Pal
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire03824, United States
| | - Amit Kumar
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire03824, United States
| | - Harish Vashisth
- Department of Chemical Engineering, University of New Hampshire, Durham, New Hampshire03824, United States
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4
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Stampelou M, Suchankova A, Tzortzini E, Dhingra L, Barkan K, Lougiakis N, Marakos P, Pouli N, Ladds G, Kolocouris A. Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure-Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations. J Med Chem 2022; 65:13305-13327. [PMID: 36173355 DOI: 10.1021/acs.jmedchem.2c01123] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]pyridines L2-L10, A15, and A17 as low-micromolar to low-nanomolar A1R/A3R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A1R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L2506.51 to alanine increased the binding affinity of A17 at A1R. We explored the structure-activity relationships against A1R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor-membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies.
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Affiliation(s)
- Margarita Stampelou
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Anna Suchankova
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Efpraxia Tzortzini
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Lakshiv Dhingra
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Kerry Barkan
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Nikolaos Lougiakis
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Panagiotis Marakos
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Nicole Pouli
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
| | - Graham Ladds
- Department of Pharmacology, University of Cambridge, Tennis Court Road, Cambridge CB2 1PD, U.K
| | - Antonios Kolocouris
- Laboratory of Medicinal Chemistry, Section of Pharmaceutical Chemistry, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Panepistimiopolis-Zografou, 15771 Athens, Greece
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Abstract
A major advancement has recently occurred in the ability to predict protein secondary structure from sequence using artificial neural networks. This new accessibility to high-quality predicted structures provides a big opportunity for the protein design community. It is particularly welcome for membrane protein design, where the scarcity of solved structures has been a major limitation of the field for decades. Here, we review the work done to date on the membrane protein design and set out established and emerging tools that can be used to most effectively exploit this new access to structures.
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Affiliation(s)
- Shahin Sowlati-Hashjin
- Institute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, Canada, M5S 3E2
| | - Aanshi Gandhi
- Institute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, Canada, M5S 3E2
| | - Michael Garton
- Institute of Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, Canada, M5S 3E2
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6
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Abstract
Introduction: Halogens have a prominent role in drug design. Often used as a mean to improve ADME properties, they are also becoming a tool in protein-ligand recognition given their ability to form a non-covalent interaction, termed halogen bond, where halogens act as electrophilic species interacting with electron-rich partners. Rational drug design of halogen-bonding lead molecules requires an accurate description of halocarbon-protein complexes by computational tools though not all methods are able to tackle this non-covalent interaction. Areas covered: The authors present a review of computational methodologies that can be used to properly describe halogen bonds in the context of protein-ligand complexes, providing also insights on how these methods can be used in the context of computer-aided drug design. Expert opinion: Although in the last few years many computational tools, ranging from fast screening methods to the more expensive QM calculations, have been developed to tackle the halogen bonding phenomenon, they are not yet standard in the literature. This will eventually change as official software distributions are including support for halogen bonding in their methods. Tackling desolvation of halogenated species seems to be a good strategy to improve the accuracy of computational methods, that will be more commonly used prior to laboratory work in the future.
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Affiliation(s)
- Paulo J Costa
- a Centro de Quı́mica e Bioquı́mica, Departamento de Quı́mica e Bioquı́mica , Faculdade de Ciências da Universidade de Lisboa, Campo Grande , Lisboa , Portugal.,b University of Lisboa, Faculty of Sciences , BioISI - Biosystems & Integrative Sciences Institute , Lisboa , Portugal
| | - Rafael Nunes
- a Centro de Quı́mica e Bioquı́mica, Departamento de Quı́mica e Bioquı́mica , Faculdade de Ciências da Universidade de Lisboa, Campo Grande , Lisboa , Portugal.,b University of Lisboa, Faculty of Sciences , BioISI - Biosystems & Integrative Sciences Institute , Lisboa , Portugal
| | - Diogo Vila-Viçosa
- a Centro de Quı́mica e Bioquı́mica, Departamento de Quı́mica e Bioquı́mica , Faculdade de Ciências da Universidade de Lisboa, Campo Grande , Lisboa , Portugal.,b University of Lisboa, Faculty of Sciences , BioISI - Biosystems & Integrative Sciences Institute , Lisboa , Portugal
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7
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Garton M, Corbi-Verge C, Hu Y, Nim S, Tarasova N, Sherborne B, Kim PM. Rapid and accurate structure-based therapeutic peptide design using GPU accelerated thermodynamic integration. Proteins 2019; 87:236-244. [PMID: 30520126 DOI: 10.1002/prot.25644] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 10/30/2018] [Accepted: 11/29/2018] [Indexed: 11/07/2022]
Abstract
Peptide-based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side-chains was found to be less accurate than for non-charged, and use of a more complex 3-step TI protocol was found to boost accuracy in these cases. Using the 3-step protocol for non-charged side-chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non-canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability.
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Affiliation(s)
- Michael Garton
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada
| | - Carles Corbi-Verge
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada
| | - Yuan Hu
- Merck & Co., Inc., Kenilworth, New Jersey.,Alkermes Inc., Waltham, Massachusetts
| | - Satra Nim
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada
| | - Nadya Tarasova
- Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute-Frederick, Frederick, Maryland
| | | | - Philip M Kim
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Canada.,Department of Computer Science, University of Toronto, Toronto, Canada
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8
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Shekhar MS, Venkatachalam T, Sharma CS, Pratap Singh H, Kalra S, Kumar N. Computational investigation of binding mechanism of substituted pyrazinones targeting corticotropin releasing factor-1 receptor deliberated for anti-depressant drug design. J Biomol Struct Dyn 2018; 37:3226-3244. [DOI: 10.1080/07391102.2018.1513379] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
| | - T. Venkatachalam
- Department of Pharmaceutical Chemistry, Annai JKK Sampoorani Ammal College of Pharmacy, Namakkal, Tamil Nadu, India
| | - Chandra Shekhar Sharma
- Department of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ University, Udaipur, Rajasthan, India
| | - Hemendra Pratap Singh
- Department of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Bhupal Nobles’ University, Udaipur, Rajasthan, India
| | - Sourav Kalra
- Centre for Human Genetics & Molecular Medicine, Central University of Punjab, Bhatinda, Punjab, India
| | - Neeraj Kumar
- Department of Pharmaceutical Chemistry, Geetanjali University, Udaipur, Rajasthan, India
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9
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Na S, Steinbrecher T, Koslowski T. Thermodynamic integration network approach to ion transport through protein channels: Perspectives and limits. J Comput Chem 2018; 39:2539-2550. [DOI: 10.1002/jcc.25615] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 03/27/2018] [Accepted: 09/03/2018] [Indexed: 12/20/2022]
Affiliation(s)
- Sehee Na
- Fakultät für Chemie und Pharmazie, Institut für Physikalische ChemieUniversität Freiburg Albertstraße 23a, 79104, Freiburg im Breisgau Germany
| | | | - Thorsten Koslowski
- Fakultät für Chemie und Pharmazie, Institut für Physikalische ChemieUniversität Freiburg Albertstraße 23a, 79104, Freiburg im Breisgau Germany
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10
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Mermelstein DJ, Lin C, Nelson G, Kretsch R, McCammon JA, Walker RC. Fast and flexible gpu accelerated binding free energy calculations within the amber molecular dynamics package. J Comput Chem 2018. [PMID: 29532496 DOI: 10.1002/jcc.25187] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD-based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Daniel J Mermelstein
- Department of Chemistry & Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093
| | - Charles Lin
- Department of Chemistry & Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093.,GlaxoSmithKline PLC, 1250 S. Collegeville Rd, Collegeville, Pennsylvania, 19426
| | - Gard Nelson
- NantBioscience, Inc., 9920 Jefferson Boulevard, Culver City, California, 90232
| | - Rachael Kretsch
- Department of Chemistry & Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093.,Harvey Mudd College, 301 Platt Blvd, Claremont, California, 91711
| | - J Andrew McCammon
- Department of Chemistry & Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093
| | - Ross C Walker
- Department of Chemistry & Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093.,GlaxoSmithKline PLC, 1250 S. Collegeville Rd, Collegeville, Pennsylvania, 19426
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Kumar R, Jade D, Gupta D. A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics. J Biomol Struct Dyn 2018; 37:931-943. [PMID: 29468945 DOI: 10.1080/07391102.2018.1444509] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
5-HydroxyTriptamine 2A antagonists are potential targets for treatment of various cerebrovascular and cardiovascular disorders. In this study, we have developed and performed a unique screening pipeline for filtering ZINC database compounds on the basis of similarities to known antagonists to determine novel small molecule antagonists of 5-HydroxyTriptamine 2A. The screening pipeline is based on 2D similarity, 3D dissimilarity and a combination of 2D/3D similarity. The shortlisted compounds were docked to a 5-HydroxyTriptamine 2A homology-based model, and complexes with low binding energies (287 complexes) were selected for molecular dynamics (MD) simulations in a lipid bilayer. The MD simulations of the shortlisted compounds in complex with 5-HydroxyTriptamine 2A confirmed the stability of the complexes and revealed novel interaction insights. The receptor residues S239, N343, S242, S159, Y370 and D155 predominantly participate in hydrogen bonding. π-π stacking is observed in F339, F340, F234, W151 and W336, whereas hydrophobic interactions are observed amongst V156, F339, F234, V362, V366, F340, V235, I152 and W151. The known and potential antagonists shortlisted by us have similar overlapping molecular interaction patterns. The 287 potential 5-HydroxyTriptamine 2A antagonists may be experimentally verified.
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Key Words
- , tanimoto coefficient
- 2D similarity
- 2D, two-dimensional space
- 2D/3D screening
- 3D similarity
- 3D, three-dimensional space
- 5HT
- 5HT, 5-HydroxyTryptamine
- ADHD, attention deficit hyperactivity disorders
- BLAST, basic local alignment search tool
- CNS, central nervous system
- Cl ions, chloride ions
- DOPE, discrete optimized protein energy
- G-protein coupled receptor
- GPCRs, G protein-coupled receptors
- HB, hydrogen bond
- HBA, hydrogen bond acceptors
- HBD, hydrogen bond donors
- JC virus, John Cunningham virus
- Ki, equilibrium dissociation constant for the ligand
- LBVS, ligand-based virtual screening
- MD, molecular dynamic
- MSD, mean square displacement
- MW, molecular weight
- NHB, number of hydrogen bonds
- OCD, obsessive compulsive disorder
- P5/P95, percentile calculation
- PAINS, Pan assay interference compounds
- PDB, protein data bank
- PLIP, protein–ligand interaction profiler
- PME, Particle Mesh Ewald
- PNS, peripheral nervous system
- POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine
- RMSD, root mean square deviation
- RMSF, root mean square fluctuations
- Rg, radius of gyration
- SASA, solvent accessible surface area
- SCA, stochastic clustering algorithm
- SD, steepest descent
- SDF, structure data file
- SPC, single point charge
- SPD, simple point charge
- SSE, secondary structure elements
- Sn-1/sn-2, Stereospecific number
- TM, Transmembrane
- TPSA, topological polar surface area
- drug discovery
- fs, femtosecond
- kJ/mol, kilo Joule per mol
- kcal/mol, kilocalorie per mole sn-1
- ligand-based virtual screening
- nm, nanomolar
- ns, nanosecond
- Å Ångström
- β2-AR, β2 adrenergic receptor
- μM, micromolar
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Affiliation(s)
- Rakesh Kumar
- a Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB) , Aruna Asaf Ali Marg, New Delhi 110067 , India
| | - Dhananjay Jade
- a Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB) , Aruna Asaf Ali Marg, New Delhi 110067 , India
| | - Dinesh Gupta
- a Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB) , Aruna Asaf Ali Marg, New Delhi 110067 , India
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12
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Garton M, Sayadi M, Kim PM. A computational approach for designing D-proteins with non-canonical amino acid optimised binding affinity. PLoS One 2017; 12:e0187524. [PMID: 29108013 DOI: 10.1371/journal.pone.0187524] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Accepted: 10/21/2017] [Indexed: 01/08/2023] Open
Abstract
Redesigning protein surface topology to improve target binding holds great promise in the search for highly selective therapeutics. While significant binding improvements can be achieved using natural amino acids, the introduction of non-canonical residues vastly increases sequence space and thus the chance to significantly out-compete native partners. The potency of protein inhibitors can be further enhanced by synthesising mirror image, D-amino versions. This renders them non-immunogenic and makes them highly resistant to proteolytic degradation. Current experimental design methods often preclude the use of D-amino acids and non-canonical amino acids for a variety of reasons. To address this, we build an in silico pipeline for D-protein designs featuring non-canonical amino acids. For a test scaffold we use an existing D-protein inhibitor of VEGF: D-RFX001. We benchmark the approach by recapitulating previous experimental optimisation with canonical amino acids. Subsequent incorporation of non-canonical amino acids allows designs that are predicted to improve binding affinity by up to -7.18 kcal/mol.
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13
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Kumar N, Mishra SS, Sharma CS, Singh HP, Kalra S. In silico binding mechanism prediction of benzimidazole based corticotropin releasing factor-1 receptor antagonists by quantitative structure activity relationship, molecular docking and pharmacokinetic parameters calculation. J Biomol Struct Dyn 2017; 36:1691-1712. [PMID: 28521603 DOI: 10.1080/07391102.2017.1332688] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Despite the various research efforts toward the treatment of stress-related disorders, the drug has not yet launched last 20 years. Corticotropin releasing factor-1 receptor antagonists have been point of great interest in stress-related disorders. In the present study, we have selected benzazole scaffold-based compounds as corticotropin releasing factor-1 antagonists and performed 2D and 3D QSAR studies to identify the structural features to elucidating the binding mechanism prediction. The best 2D QSAR model was obtained through multiple linear regression method with r2 value of .7390, q2 value of .5136 and pred_r2 (predicted square correlation coefficient) value of .88. The contribution of 2D descriptor, T_2_C_1 was 60% (negative contribution) and 4pathClusterCount was 40.24% (positive contribution) in enhancing the activity. Also 3D QSAR model was statistically significant with q2 value of .9419 and q2_se (standard error of internal validation) value of .19. Statistical parameters results prove the robustness and significance of both models. Further, molecular docking and pharmacokinetic analysis was performed to explore the scope of investigation. Docking results revealed that the all benzazole compounds show hydrogen bonding with residue Asn283 and having same hydrophobic pocket (Phe286, Leu213, Ile290, Leu287, Phe207, Arg165, Leu323, Tyr327, Phe284, and Met206). Compound B14 has higher activity compare to reference molecules. Most of the compounds were found within acceptable range for pharmacokinetic parameters. This work provides the extremely useful leads for structural substituents essential for benzimidazole moiety to exhibit antagonistic activity against corticotropin releasing factor-1 receptors.
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Affiliation(s)
- Neeraj Kumar
- a Department of Pharmaceutical Chemistry , Geetanjali College of Pharmacy , Udaipur 313001 , India
| | - Shashank Shekhar Mishra
- b Department of Pharmaceutical Chemistry, Bhupal Nobles' College of Pharmacy , Bhupal Nobles' University , Udaipur 313001 , India
| | - Chandra Shekhar Sharma
- b Department of Pharmaceutical Chemistry, Bhupal Nobles' College of Pharmacy , Bhupal Nobles' University , Udaipur 313001 , India
| | - Hamendra Pratap Singh
- b Department of Pharmaceutical Chemistry, Bhupal Nobles' College of Pharmacy , Bhupal Nobles' University , Udaipur 313001 , India
| | - Sourav Kalra
- c Centre for Human Genetics & Molecular Medicine , Central University of Punjab , Bhatinda 151001 , India
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Panman W, Japrung D, Pongprayoon P. Exploring the interactions of a DNA aptamer with human serum albumins: simulation studies. J Biomol Struct Dyn 2016; 35:2328-2336. [PMID: 27600390 DOI: 10.1080/07391102.2016.1224733] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Wanwisa Panman
- a School of Science , Walailak University , Nakhon Si Thammarat 80161 , Thailand
| | - Deanpen Japrung
- b National Nanotechnology Center, National Science and Technology Development Agency, Thailand Science Park , Pathumthani 12120 , Thailand
| | - Prapasiri Pongprayoon
- c Faculty of Science, Department of Chemistry , Kasetsart University , Chatuchak, Bangkok 10900 , Thailand.,d Center for Advanced Studies in Nanotechnology and Its Applications in Chemical , Food and Agricultural Industries, Kasetsart University , Bangkok 10900 , Thailand.,e Computational Biomodelling Laboratory for Agricultural Science and Technology (CBLAST) , Kasetsart University , Bangkok 10900 , Thailand
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15
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Jacob K S, Ganguly S, Kumar P, Poddar R, Kumar A. Homology model, molecular dynamics simulation and novel pyrazole analogs design of Candida albicans CYP450 lanosterol 14 α-demethylase, a target enzyme for antifungal therapy. J Biomol Struct Dyn 2016; 35:1446-1463. [PMID: 27142238 DOI: 10.1080/07391102.2016.1185380] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Candida albicans infections and their resistance to clinically approved azole drugs are major concerns for human. The azole antifungal drugs inhibit the ergosterol synthesis by targeting lanosterol 14α-demethylase of cytochrome P450 family. The lack of high-resolution structural information of fungal pathogens has been a barrier for the design of modified azole drugs. Thus, a preliminary theoretical molecular dynamic study is carried out to develop and validate a simple homologous model using crystallographic structure of the lanosterol 14α-demethylase of Mycobacterium tuberculosis (PDB ID-1EA1) in which the active site residues are substituted with that of C. albicans (taxid 5476). Further, novel designed pyrazole analogs (SGS1-16) docked on chimeric 1EA1 and revealed that SGS-16 show good binding affinity through non-bonding interaction with the heme, which is different from the leading azole antifungals. The ADME-T results showed these analogs can be further explored in design of more safe and effective antifungal agents.
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Affiliation(s)
- Sony Jacob K
- a Department of Pharmaceutical Sciences and Technology , Birla Institute of Technology, Mesra , Ranchi , Jharkhand 835215 , India
| | - Swastika Ganguly
- a Department of Pharmaceutical Sciences and Technology , Birla Institute of Technology, Mesra , Ranchi , Jharkhand 835215 , India
| | - Pravin Kumar
- b Department of Bio-Engineering , Birla Institute of Technology, Mesra , Ranchi , Jharkhand 835215 , India
| | - Raju Poddar
- b Department of Bio-Engineering , Birla Institute of Technology, Mesra , Ranchi , Jharkhand 835215 , India
| | - Anoop Kumar
- a Department of Pharmaceutical Sciences and Technology , Birla Institute of Technology, Mesra , Ranchi , Jharkhand 835215 , India
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