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Carney DW, Leffler AE, Bell JA, Chandrasinghe AS, Cheng C, Chang E, Dornford A, Dougan DR, Frye LL, Grimes ME, Knehans T, Knight JL, Komandla M, Lane W, Li H, Newman SR, Phimister K, Saikatendu KS, Silverstein H, Vafaei S. Exploiting high-energy hydration sites for the discovery of potent peptide aldehyde inhibitors of the SARS-CoV-2 main protease with cellular antiviral activity. Bioorg Med Chem 2024; 103:117577. [PMID: 38518735 DOI: 10.1016/j.bmc.2023.117577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 03/24/2024]
Abstract
Small-molecule antivirals that prevent the replication of the SARS-CoV-2 virus by blocking the enzymatic activity of its main protease (Mpro) are and will be a tenet of pandemic preparedness. However, the peptidic nature of such compounds often precludes the design of compounds within favorable physical property ranges, limiting cellular activity. Here we describe the discovery of peptide aldehyde Mpro inhibitors with potent enzymatic and cellular antiviral activity. This structure-activity relationship (SAR) exploration was guided by the use of calculated hydration site thermodynamic maps (WaterMap) to drive potency via displacement of waters from high-energy sites. Thousands of diverse compounds were designed to target these high-energy hydration sites and then prioritized for synthesis by physics- and structure-based Free-Energy Perturbation (FEP+) simulations, which accurately predicted biochemical potencies. This approach ultimately led to the rapid discovery of lead compounds with unique SAR that exhibited potent enzymatic and cellular activity with excellent pan-coronavirus coverage.
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Affiliation(s)
- Daniel W Carney
- Takeda Development Center Americas, Inc, 9625 Towne Centre Drive, San Diego, CA 92121, United States.
| | - Abba E Leffler
- Schrödinger, Inc, 1540 Broadway, New York, NY 10036, United States.
| | - Jeffrey A Bell
- Schrödinger, Inc, 1540 Broadway, New York, NY 10036, United States
| | | | - Cecilia Cheng
- Schrödinger, Inc, 9868 Scranton Road, Suite 3200, San Diego, CA 92121, United States
| | - Edcon Chang
- Takeda Development Center Americas, Inc, 9625 Towne Centre Drive, San Diego, CA 92121, United States
| | - Adam Dornford
- Schrödinger, Inc, 1 Main St, 11th Floor, Cambridge, MA 02142, United States
| | - Douglas R Dougan
- Takeda Development Center Americas, Inc, 9625 Towne Centre Drive, San Diego, CA 92121, United States
| | - Leah L Frye
- Schrödinger, Inc, 101 SW Main Street, Suite 1300, Portland, OR 97204, United States
| | - Mary E Grimes
- Schrödinger, Inc, 101 SW Main Street, Suite 1300, Portland, OR 97204, United States
| | - Tim Knehans
- Schrödinger GmbH, Glücksteinallee 25, 68163 Mannheim, Germany
| | | | - Mallareddy Komandla
- Takeda Development Center Americas, Inc, 9625 Towne Centre Drive, San Diego, CA 92121, United States
| | - Weston Lane
- Treeline Biosciences, 500 Arsenal Way, Watertown, MA 02472, United States
| | - Hubert Li
- Schrödinger, Inc, 9868 Scranton Road, Suite 3200, San Diego, CA 92121, United States
| | - Sophia R Newman
- Schrödinger, Inc, 101 SW Main Street, Suite 1300, Portland, OR 97204, United States
| | - Katalin Phimister
- Schrödinger Technologies Limited, 1st Floor West, Davidson House, Forbury Square, Reading RG1 3EU, United Kingdom
| | - Kumar S Saikatendu
- Takeda Development Center Americas, Inc, 9625 Towne Centre Drive, San Diego, CA 92121, United States
| | - Hercules Silverstein
- Schrödinger, Inc, 101 SW Main Street, Suite 1300, Portland, OR 97204, United States
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2
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Haufe Y, Kuruva V, Samanani Z, Lokaj G, Kamnesky G, Shadamarshan P, Shahoei R, Katz D, Sampson JM, Pusch M, Brik A, Nicke A, Leffler AE. Basic Residues at Position 11 of α-Conotoxin LvIA Influence Subtype Selectivity between α3β2 and α3β4 Nicotinic Receptors via an Electrostatic Mechanism. ACS Chem Neurosci 2023; 14:4311-4322. [PMID: 38051211 DOI: 10.1021/acschemneuro.3c00506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023] Open
Abstract
Understanding the determinants of α-conotoxin (α-CTX) selectivity for different nicotinic acetylcholine receptor (nAChR) subtypes is a prerequisite for the design of tool compounds to study nAChRs. However, selectivity optimization of these small, disulfide-rich peptides is difficult not only because of an absence of α-CTX/nAChR co-structures but also because it is challenging to predict how a mutation to an α-CTX will alter its potency and selectivity. As a prototypical system to investigate selectivity, we employed the α-CTX LvIA that is 25-fold selective for the α3β2 nAChR over the related α3β4 nAChR subtype, which is a target for nicotine addiction. Using two-electrode voltage clamp electrophysiology, we identified LvIA[D11R] that is 2-fold selective for the α3β4 nAChR, reversing the subtype preference. This effect is specifically due to the change in charge and not shape of LvIA[D11R], as substitution of D11 with citrulline retains selectivity for the α3β2 nAChR. Furthermore, LvIA[D11K] shows a stronger reversal, with 4-fold selectivity for the α3β4 nAChR. Motivated by these findings, using site-directed mutagenesis, we found that β2[K79A] (I79 on β4), but not β2[K78A] (N78 on β4), largely restores the potency of basic mutants at position 11. Finally, to understand the structural basis of this effect, we used AlphaFold2 to generate models of LvIA in complex with both nAChR subtypes. Both models confirm the plausibility of an electrostatic mechanism to explain the data and also reproduce a broad range of potency and selectivity structure-activity relationships for LvIA mutants, as measured using free energy perturbation simulations. Our work highlights how electrostatic interactions can drive α-CTX selectivity and may serve as a strategy for optimizing the selectivity of LvIA and other α-CTXs.
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Affiliation(s)
- Yves Haufe
- Faculty of Medicine, Walther Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Munich 80539, Germany
| | - Veeresh Kuruva
- Schulich Faculty of Chemistry, Technion-Israel Institute of Technology, Haifa 3200008, Israel
| | - Ziyana Samanani
- Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States
| | - Gonxhe Lokaj
- Faculty of Medicine, Walther Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Munich 80539, Germany
| | - Guy Kamnesky
- Schulich Faculty of Chemistry, Technion-Israel Institute of Technology, Haifa 3200008, Israel
| | - PranavKumar Shadamarshan
- Faculty of Medicine, Walther Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Munich 80539, Germany
| | - Rezvan Shahoei
- Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States
| | - Dana Katz
- Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States
| | - Jared M Sampson
- Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States
| | - Michael Pusch
- Istituto di Biofisica, CNR, Via De Marini 6, Genova 16149, Italy
| | - Ashraf Brik
- Schulich Faculty of Chemistry, Technion-Israel Institute of Technology, Haifa 3200008, Israel
| | - Annette Nicke
- Faculty of Medicine, Walther Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Munich 80539, Germany
| | - Abba E Leffler
- Schrödinger, Inc., 1540 Broadway, New York, New York 10036, United States
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3
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Bos PH, Houang EM, Ranalli F, Leffler AE, Boyles NA, Eyrich VA, Luria Y, Katz D, Tang H, Abel R, Bhat S. AutoDesigner, a De Novo Design Algorithm for Rapidly Exploring Large Chemical Space for Lead Optimization: Application to the Design and Synthesis of d-Amino Acid Oxidase Inhibitors. J Chem Inf Model 2022; 62:1905-1915. [PMID: 35417149 DOI: 10.1021/acs.jcim.2c00072] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The lead optimization stage of a drug discovery program generally involves the design, synthesis, and assaying of hundreds to thousands of compounds. The design phase is usually carried out via traditional medicinal chemistry approaches and/or structure-based drug design (SBDD) when suitable structural information is available. Two of the major limitations of this approach are (1) difficulty in rapidly designing potent molecules that adhere to myriad project criteria, or the multiparameter optimization (MPO) problem, and (2) the relatively small number of molecules explored compared to the vast size of chemical space. To address these limitations, we have developed AutoDesigner, a de novo design algorithm. AutoDesigner employs a cloud-native, multistage search algorithm to carry out successive rounds of chemical space exploration and filtering. Millions to billions of virtual molecules are explored and optimized while adhering to a customizable set of project criteria such as physicochemical properties and potency. Additionally, the algorithm only requires a single ligand with measurable affinity and a putative binding model as a starting point, making it amenable to the early stages of an SBDD project where limited data are available. To assess the effectiveness of AutoDesigner, we applied it to the design of novel inhibitors of d-amino acid oxidase (DAO), a target for the treatment of schizophrenia. AutoDesigner was able to generate and efficiently explore over 1 billion molecules to successfully address a variety of project goals. The compounds generated by AutoDesigner that were synthesized and assayed (1) simultaneously met not only physicochemical criteria, clearance, and central nervous system (CNS) penetration (Kp,uu) cutoffs but also potency thresholds and (2) fully utilize structural data to discover and explore novel interactions and a previously unexplored subpocket in the DAO active site. The reported data demonstrate that AutoDesigner can play a key role in accelerating the discovery of novel, potent chemical matter within the constraints of a given drug discovery lead optimization campaign.
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Affiliation(s)
- Pieter H Bos
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Evelyne M Houang
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Fabio Ranalli
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Abba E Leffler
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Nicholas A Boyles
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Volker A Eyrich
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Yuval Luria
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Dana Katz
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Haifeng Tang
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Robert Abel
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Sathesh Bhat
- Schrödinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
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Shan Y, Mysore VP, Leffler AE, Kim ET, Sagawa S, Shaw DE. How does a small molecule bind at a cryptic binding site? PLoS Comput Biol 2022; 18:e1009817. [PMID: 35239648 PMCID: PMC8893328 DOI: 10.1371/journal.pcbi.1009817] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 01/07/2022] [Indexed: 12/15/2022] Open
Abstract
Protein-protein interactions (PPIs) are ubiquitous biomolecular processes that are central to virtually all aspects of cellular function. Identifying small molecules that modulate specific disease-related PPIs is a strategy with enormous promise for drug discovery. The design of drugs to disrupt PPIs is challenging, however, because many potential drug-binding sites at PPI interfaces are “cryptic”: When unoccupied by a ligand, cryptic sites are often flat and featureless, and thus not readily recognizable in crystal structures, with the geometric and chemical characteristics of typical small-molecule binding sites only emerging upon ligand binding. The rational design of small molecules to inhibit specific PPIs would benefit from a better understanding of how such molecules bind at PPI interfaces. To this end, we have conducted unbiased, all-atom MD simulations of the binding of four small-molecule inhibitors (SP4206 and three SP4206 analogs) to interleukin 2 (IL2)—which performs its function by forming a PPI with its receptor—without incorporating any prior structural information about the ligands’ binding. In multiple binding events, a small molecule settled into a stable binding pose at the PPI interface of IL2, resulting in a protein–small-molecule binding site and pose virtually identical to that observed in an existing crystal structure of the IL2-SP4206 complex. Binding of the small molecule stabilized the IL2 binding groove, which when the small molecule was not bound emerged only transiently and incompletely. Moreover, free energy perturbation (FEP) calculations successfully distinguished between the native and non-native IL2–small-molecule binding poses found in the simulations, suggesting that binding simulations in combination with FEP may provide an effective tool for identifying cryptic binding sites and determining the binding poses of small molecules designed to disrupt PPI interfaces by binding to such sites. Small-molecule drugs typically function by binding to and modulating the biological activity of their protein targets. Drug-binding sites resemble pockets or grooves on the surface of the target protein, and are generally present even when the drug is not bound. In the case of “cryptic” binding sites, however, the pocket or groove only takes shape during the drug-binding process, prior to which the geometric features of a typical binding site are absent. Cryptic sites commonly occur at protein-protein interfaces, for example, so targeting such sites could facilitate the design of drugs capable of modulating specific protein-protein interactions—an approach with great therapeutic potential. In practice, targeting cryptic sites is typically difficult, in part because much less is known about how small molecules bind to cryptic sites than to conventional sites. In the work reported here, we used molecular dynamics simulations to study the process of a drug binding at a cryptic binding site, and showed that simulations are capable of predicting the location and geometry of a drug binding. The improved understanding of how small molecules bind at cryptic sites afforded by approaches like the one presented here could aid the rational design of small molecules that target such sites.
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Affiliation(s)
- Yibing Shan
- D. E. Shaw Research, New York, New York, United States of America
- * E-mail: (YS); (DES)
| | | | - Abba E. Leffler
- D. E. Shaw Research, New York, New York, United States of America
| | - Eric T. Kim
- D. E. Shaw Research, New York, New York, United States of America
| | - Shiori Sagawa
- D. E. Shaw Research, New York, New York, United States of America
| | - David E. Shaw
- D. E. Shaw Research, New York, New York, United States of America
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America
- * E-mail: (YS); (DES)
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Katz D, DiMattia MA, Sindhikara D, Li H, Abraham N, Leffler AE. Potency- and Selectivity-Enhancing Mutations of Conotoxins for Nicotinic Acetylcholine Receptors Can Be Predicted Using Accurate Free-Energy Calculations. Mar Drugs 2021; 19:367. [PMID: 34202022 PMCID: PMC8306581 DOI: 10.3390/md19070367] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 06/18/2021] [Accepted: 06/22/2021] [Indexed: 01/18/2023] Open
Abstract
Nicotinic acetylcholine receptor (nAChR) subtypes are key drug targets, but it is challenging to pharmacologically differentiate between them because of their highly similar sequence identities. Furthermore, α-conotoxins (α-CTXs) are naturally selective and competitive antagonists for nAChRs and hold great potential for treating nAChR disorders. Identifying selectivity-enhancing mutations is the chief aim of most α-CTX mutagenesis studies, although doing so with traditional docking methods is difficult due to the lack of α-CTX/nAChR crystal structures. Here, we use homology modeling to predict the structures of α-CTXs bound to two nearly identical nAChR subtypes, α3β2 and α3β4, and use free-energy perturbation (FEP) to re-predict the relative potency and selectivity of α-CTX mutants at these subtypes. First, we use three available crystal structures of the nAChR homologue, acetylcholine-binding protein (AChBP), and re-predict the relative affinities of twenty point mutations made to the α-CTXs LvIA, LsIA, and GIC, with an overall root mean square error (RMSE) of 1.08 ± 0.15 kcal/mol and an R2 of 0.62, equivalent to experimental uncertainty. We then use AChBP as a template for α3β2 and α3β4 nAChR homology models bound to the α-CTX LvIA and re-predict the potencies of eleven point mutations at both subtypes, with an overall RMSE of 0.85 ± 0.08 kcal/mol and an R2 of 0.49. This is significantly better than the widely used molecular mechanics-generalized born/surface area (MM-GB/SA) method, which gives an RMSE of 1.96 ± 0.24 kcal/mol and an R2 of 0.06 on the same test set. Next, we demonstrate that FEP accurately classifies α3β2 nAChR selective LvIA mutants while MM-GB/SA does not. Finally, we use FEP to perform an exhaustive amino acid mutational scan of LvIA and predict fifty-two mutations of LvIA to have greater than 100X selectivity for the α3β2 nAChR. Our results demonstrate the FEP is well-suited to accurately predict potency- and selectivity-enhancing mutations of α-CTXs for nAChRs and to identify alternative strategies for developing selective α-CTXs.
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Affiliation(s)
- Dana Katz
- Schrödinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (M.A.D.); (D.S.); (H.L.)
| | - Michael A. DiMattia
- Schrödinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (M.A.D.); (D.S.); (H.L.)
| | - Dan Sindhikara
- Schrödinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (M.A.D.); (D.S.); (H.L.)
| | - Hubert Li
- Schrödinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (M.A.D.); (D.S.); (H.L.)
| | | | - Abba E. Leffler
- Schrödinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (M.A.D.); (D.S.); (H.L.)
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Katz D, Sindhikara D, DiMattia M, Leffler AE. Potency-Enhancing Mutations of Gating Modifier Toxins for the Voltage-Gated Sodium Channel Na V1.7 Can Be Predicted Using Accurate Free-Energy Calculations. Toxins (Basel) 2021; 13:193. [PMID: 33800031 PMCID: PMC8002187 DOI: 10.3390/toxins13030193] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 01/28/2023] Open
Abstract
Gating modifier toxins (GMTs) isolated from venomous organisms such as Protoxin-II (ProTx-II) and Huwentoxin-IV (HwTx-IV) that inhibit the voltage-gated sodium channel NaV1.7 by binding to its voltage-sensing domain II (VSDII) have been extensively investigated as non-opioid analgesics. However, reliably predicting how a mutation to a GMT will affect its potency for NaV1.7 has been challenging. Here, we hypothesize that structure-based computational methods can be used to predict such changes. We employ free-energy perturbation (FEP), a physics-based simulation method for predicting the relative binding free energy (RBFE) between molecules, and the cryo electron microscopy (cryo-EM) structures of ProTx-II and HwTx-IV bound to VSDII of NaV1.7 to re-predict the relative potencies of forty-seven point mutants of these GMTs for NaV1.7. First, FEP predicted these relative potencies with an overall root mean square error (RMSE) of 1.0 ± 0.1 kcal/mol and an R2 value of 0.66, equivalent to experimental uncertainty and an improvement over the widely used molecular-mechanics/generalized born-surface area (MM-GB/SA) RBFE method that had an RMSE of 3.9 ± 0.8 kcal/mol. Second, inclusion of an explicit membrane model was needed for the GMTs to maintain stable binding poses during the FEP simulations. Third, MM-GB/SA and FEP were used to identify fifteen non-standard tryptophan mutants at ProTx-II[W24] predicted in silico to have a at least a 1 kcal/mol gain in potency. These predicted potency gains are likely due to the displacement of high-energy waters as identified by the WaterMap algorithm for calculating the positions and thermodynamic properties of water molecules in protein binding sites. Our results expand the domain of applicability of FEP and set the stage for its prospective use in biologics drug discovery programs involving GMTs and NaV1.7.
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Affiliation(s)
| | | | | | - Abba E. Leffler
- Schrӧdinger, Inc., 120 West 45th St., New York, NY 10036, USA; (D.K.); (D.S.); (M.D.)
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7
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Shah B, Sindhikara D, Borrelli K, Leffler AE. Water Thermodynamics of Peptide Toxin Binding Sites on Ion Channels. Toxins (Basel) 2020; 12:toxins12100652. [PMID: 33053750 PMCID: PMC7599640 DOI: 10.3390/toxins12100652] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/21/2020] [Accepted: 10/09/2020] [Indexed: 12/20/2022] Open
Abstract
Peptide toxins isolated from venomous creatures, long prized as research tools due to their innate potency for ion channels, are emerging as drugs as well. However, it remains challenging to understand why peptide toxins bind with high potency to ion channels, to identify residues that are key for activity, and to improve their affinities via mutagenesis. We use WaterMap, a molecular dynamics simulation-based method, to gain computational insight into these three questions by calculating the locations and thermodynamic properties of water molecules in the peptide toxin binding sites of five ion channels. These include an acid-sensing ion channel, voltage-gated potassium channel, sodium channel in activated and deactivated states, transient-receptor potential channel, and a nicotinic receptor whose structures were recently determined by crystallography and cryo-electron microscopy (cryo-EM). All channels had water sites in the peptide toxin binding site, and an average of 75% of these sites were stable (low-energy), and 25% were unstable (medium or high energy). For the sodium channel, more unstable water sites were present in the deactivated state structure than the activated. Additionally, for each channel, unstable water sites coincided with the positions of peptide toxin residues that previous mutagenesis experiments had shown were important for activity. Finally, for the sodium channel in the deactivated state, unstable water sites were present in the peptide toxin binding pocket but did not overlap with the peptide toxin, suggesting that future experimental efforts could focus on targeting these sites to optimize potency.
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Affiliation(s)
- Binita Shah
- Schrödinger, Inc. 120 W. 45th St, New York, NY 10036, USA; (B.S.); (D.S.); (K.B.)
- PhD Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Dan Sindhikara
- Schrödinger, Inc. 120 W. 45th St, New York, NY 10036, USA; (B.S.); (D.S.); (K.B.)
| | - Ken Borrelli
- Schrödinger, Inc. 120 W. 45th St, New York, NY 10036, USA; (B.S.); (D.S.); (K.B.)
| | - Abba E. Leffler
- Schrödinger, Inc. 120 W. 45th St, New York, NY 10036, USA; (B.S.); (D.S.); (K.B.)
- Correspondence:
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8
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Abstract
The mechanism of ion channel voltage gating-how channels open and close in response to voltage changes-has been debated since Hodgkin and Huxley's seminal discovery that the crux of nerve conduction is ion flow across cellular membranes. Using all-atom molecular dynamics simulations, we show how a voltage-gated potassium channel (KV) switches between activated and deactivated states. On deactivation, pore hydrophobic collapse rapidly halts ion flow. Subsequent voltage-sensing domain (VSD) relaxation, including inward, 15-angstrom S4-helix motion, completes the transition. On activation, outward S4 motion tightens the VSD-pore linker, perturbing linker-S6-helix packing. Fluctuations allow water, then potassium ions, to reenter the pore; linker-S6 repacking stabilizes the open pore. We propose a mechanistic model for the sodium/potassium/calcium voltage-gated ion channel superfamily that reconciles apparently conflicting experimental data.
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9
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Alfano AB, Leffler AE, Wriggers W, Herman T, Epifano A, Hickey J, LaCosta W, Li S, Meiring H, Temares D, Van Besien A, Zhou A, De L, O'Mara D. Physical models designed to demonstrate the folding pathway of FiP35 WW domain as predicted by molecular dynamics (MD) simulations using Anton, an MD dedicated supercomputer: 2011 Pingry School S.M.A.R.T. Team Project. FASEB J 2011. [DOI: 10.1096/fasebj.25.1_supplement.909.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | - Tim Herman
- Center for Biomolecular ModelingMSOEMilwaukeeWI
| | | | | | | | | | | | | | | | | | - Luke De
- The Pingry SchoolMartinsvilleNJ
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10
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Hao J, Rapp PR, Leffler AE, Leffler SR, Janssen WGM, Lou W, McKay H, Roberts JA, Wearne SL, Hof PR, Morrison JH. Estrogen alters spine number and morphology in prefrontal cortex of aged female rhesus monkeys. J Neurosci 2006; 26:2571-8. [PMID: 16510735 PMCID: PMC6793646 DOI: 10.1523/jneurosci.3440-05.2006] [Citation(s) in RCA: 213] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Long-term cyclic treatment with 17beta-estradiol reverses age-related impairment in ovariectomized rhesus monkeys on a test of cognitive function mediated by the prefrontal cortex (PFC). Here, we examined potential neurobiological substrates of this effect using intracellular loading and morphometric analyses to test the possibility that the cognitive benefits of hormone treatment are associated with structural plasticity in layer III pyramidal cells in PFC area 46. 17beta-Estradiol did not affect several parameters such as total dendritic length and branching. In contrast, 17beta-estradiol administration increased apical and basal dendritic spine density, and induced a shift toward smaller spines, a response linked to increased spine motility, NMDA receptor-mediated activity, and learning. These results document that, although the aged primate PFC is vulnerable in the absence of factors such as circulating estrogens, it remains responsive to long-term cyclic 17beta-estradiol treatment, and that increased dendritic spine density and altered spine morphology may contribute to the cognitive benefits of such treatment.
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