Publications by authors named "Zied Gaieb"

21 Publications

  • Page 1 of 1

Development of Dimethylisoxazole-Attached Imidazo[1,2-]pyridines as Potent and Selective CBP/P300 Inhibitors.

J Med Chem 2021 05 19;64(9):5787-5801. Epub 2021 Apr 19.

Center for Green Chemistry and Department of Chemistry, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, Massachusetts 02125, United States.

The use of epigenetic bromodomain inhibitors as anticancer therapeutics has transitioned from targeting bromodomain extraterminal domain (BET) proteins into targeting non-BET bromodomains. The two most relevant non-BET bromodomain oncology targets are cyclic AMP response element-binding protein (CBP) and E1A binding protein P300 (EP300). To explore the growing CBP/EP300 interest, we developed a highly efficient two-step synthetic route for dimethylisoxazole-attached imidazo[1,2-]pyridine scaffold-containing inhibitors. Our efficient two-step reactions enabled high-throughput synthesis of compounds designed by molecular modeling, which together with structure-activity relationship (SAR) studies facilitated an overarching understanding of selective targeting of CBP/EP300 over non-BET bromodomains. This led to the identification of a new potent and selective CBP/EP300 bromodomain inhibitor, UMB298 (compound , CBP IC 72 nM and bromodomain 4, BRD4 IC 5193 nM). The SAR we established is in good agreement with literature-reported CBP inhibitors, such as CBP30, and demonstrates the advantage of utilizing our two-step approach for inhibitor development of other bromodomains.
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http://dx.doi.org/10.1021/acs.jmedchem.0c02232DOI Listing
May 2021

Role of Electrostatic Hotspots in the Selectivity of Complement Control Proteins Toward Human and Bovine Complement Inhibition.

Front Mol Biosci 2021 16;8:618068. Epub 2021 Mar 16.

Department of Bioengineering, University of California, Riverside, CA.

Poxviruses are dangerous pathogens, which can cause fatal infection in unvaccinated individuals. The causative agent of smallpox in humans, , is closely related to the bovine , yet the molecular basis of their selectivity is currently incompletely understood. Here, we examine the role of the electrostatics in the selectivity of the smallpox protein SPICE and vaccinia protein VCP toward the human and bovine complement protein C3b, a key component of the complement immune response. Electrostatic calculations, in-silico alanine-scan and electrostatic hotspot analysis, as introduced by Kieslich and Morikis (. 2012), are used to assess the electrostatic complementarity and to identify sites resistant to local perturbation where the electrostatic potential is likely to be evolutionary conserved. The calculations suggest that the bovine C3b is electrostatically prone to selectively bind its VCP ligand. On the other hand, the human isoform of C3b exhibits a lower electrostatic complementarity toward its SPICE ligand. Yet, the human C3b displays a highly preserved electrostatic core, which suggests that this isoform could be less selective in binding different ligands like SPICE and the human Factor H. This is supported by experimental cofactor activity assays revealing that the human C3b is prone to bind both SPICE and Factor H, which exhibit diverse electrostatic properties. Additional investigations considering mutants of SPICE and VCP that revert their selectivity reveal an "electrostatic switch" into the central modules of the ligands, supporting the critical role of the electrostatics in the selectivity. Taken together, these evidences provide insights into the selectivity mechanism of the complement regulator proteins encoded by the and to circumvent the complement immunity and exert their pathogenic action. These fundamental aspects are valuable for the development of novel vaccines and therapeutic strategies.
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http://dx.doi.org/10.3389/fmolb.2021.618068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020814PMC
March 2021

Disease-related mutations in PI3Kγ disrupt regulatory C-terminal dynamics and reveal a path to selective inhibitors.

Elife 2021 Mar 4;10. Epub 2021 Mar 4.

Department of Biochemistry and Microbiology, University of Victoria, Victoria, Canada.

Class I Phosphoinositide 3-kinases (PI3Ks) are master regulators of cellular functions, with the class IB PI3K catalytic subunit (p110γ) playing key roles in immune signalling. p110γ is a key factor in inflammatory diseases and has been identified as a therapeutic target for cancers due to its immunomodulatory role. Using a combined biochemical/biophysical approach, we have revealed insight into regulation of kinase activity, specifically defining how immunodeficiency and oncogenic mutations of R1021 in the C-terminus can inactivate or activate enzyme activity. Screening of inhibitors using HDX-MS revealed that activation loop-binding inhibitors induce allosteric conformational changes that mimic those in the R1021C mutant. Structural analysis of advanced PI3K inhibitors in clinical development revealed novel binding pockets that can be exploited for further therapeutic development. Overall, this work provides unique insights into regulatory mechanisms that control PI3Kγ kinase activity and shows a framework for the design of PI3K isoform and mutant selective inhibitors.
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http://dx.doi.org/10.7554/eLife.64691DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955810PMC
March 2021

A potential interaction between the SARS-CoV-2 spike protein and nicotinic acetylcholine receptors.

Biophys J 2021 03 18;120(6):983-993. Epub 2021 Feb 18.

Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, United Kingdom. Electronic address:

Changeux et al. (Changeux et al. C. R. Biol. 343:33-39.) recently suggested that the SARS-CoV-2 spike protein may interact with nicotinic acetylcholine receptors (nAChRs) and that such interactions may be involved in pathology and infectivity. This hypothesis is based on the fact that the SARS-CoV-2 spike protein contains a sequence motif similar to known nAChR antagonists. Here, we use molecular simulations of validated atomically detailed structures of nAChRs and of the spike to investigate the possible binding of the Y674-R685 region of the spike to nAChRs. We examine the binding of the Y674-R685 loop to three nAChRs, namely the human α4β2 and α7 subtypes and the muscle-like αβγδ receptor from Tetronarce californica. Our results predict that Y674-R685 has affinity for nAChRs. The region of the spike responsible for binding contains a PRRA motif, a four-residue insertion not found in other SARS-like coronaviruses. The conformational behavior of the bound Y674-R685 is highly dependent on the receptor subtype; it adopts extended conformations in the α4β2 and α7 complexes but is more compact when bound to the muscle-like receptor. In the α4β2 and αβγδ complexes, the interaction of Y674-R685 with the receptors forces the loop C region to adopt an open conformation, similar to other known nAChR antagonists. In contrast, in the α7 complex, Y674-R685 penetrates deeply into the binding pocket in which it forms interactions with the residues lining the aromatic box, namely with TrpB, TyrC1, and TyrC2. Estimates of binding energy suggest that Y674-R685 forms stable complexes with all three nAChR subtypes. Analyses of simulations of the glycosylated spike show that the Y674-R685 region is accessible for binding. We suggest a potential binding orientation of the spike protein with nAChRs, in which they are in a nonparallel arrangement to one another.
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http://dx.doi.org/10.1016/j.bpj.2021.01.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889469PMC
March 2021

A multiscale coarse-grained model of the SARS-CoV-2 virion.

Biophys J 2021 03 28;120(6):1097-1104. Epub 2020 Nov 28.

Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics and James Franck Institute, The University of Chicago, Chicago, Illinois. Electronic address:

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and ongoing development of a largely "bottom-up" coarse-grained (CG) model of the SARS-CoV-2 virion. Data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data become publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.
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http://dx.doi.org/10.1016/j.bpj.2020.10.048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695975PMC
March 2021

AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics.

bioRxiv 2020 Nov 20. Epub 2020 Nov 20.

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.

Acm Reference Format: Lorenzo Casalino , Abigail Dommer , Zied Gaieb , Emilia P. Barros , Terra Sztain , Surl-Hee Ahn , Anda Trifan , Alexander Brace , Anthony Bogetti , Heng Ma , Hyungro Lee , Matteo Turilli , Syma Khalid , Lillian Chong , Carlos Simmerling , David J. Hardy , Julio D. C. Maia , James C. Phillips , Thorsten Kurth , Abraham Stern , Lei Huang , John McCalpin , Mahidhar Tatineni , Tom Gibbs , John E. Stone , Shantenu Jha , Arvind Ramanathan , Rommie E. Amaro . 2020. AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics. In .
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http://dx.doi.org/10.1101/2020.11.19.390187DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7685317PMC
November 2020

The flexibility of ACE2 in the context of SARS-CoV-2 infection.

Biophys J 2021 03 13;120(6):1072-1084. Epub 2020 Nov 13.

Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California. Electronic address:

The coronavirus disease 2019 (COVID-19) pandemic has swept over the world in the past months, causing significant loss of life and consequences to human health. Although numerous drug and vaccine development efforts are underway, there are many outstanding questions on the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral association to angiotensin-converting enzyme 2 (ACE2), its main host receptor, and host cell entry. Structural and biophysical studies indicate some degree of flexibility in the viral extracellular spike glycoprotein and at the receptor-binding domain (RBD)-receptor interface, suggesting a role in infection. Here, we perform explicitly solvated, all-atom, molecular dynamics simulations of the glycosylated, full-length, membrane-bound ACE2 receptor in both an apo and spike RBD-bound state to probe the intrinsic dynamics of the ACE2 receptor in the context of the cell surface. A large degree of fluctuation in the full-length structure is observed, indicating hinge bending motions at the linker region connecting the head to the transmembrane helix while still not disrupting the ACE2 homodimer or ACE2-RBD interfaces. This flexibility translates into an ensemble of ACE2 homodimer conformations that could sterically accommodate binding of the spike trimer to more than one ACE2 homodimer and suggests a mechanical contribution of the host receptor toward the large spike conformational changes required for cell fusion. This work presents further structural and functional insights into the role of ACE2 in viral infection that can potentially be exploited for the rational design of effective SARS-CoV-2 therapeutics.
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http://dx.doi.org/10.1016/j.bpj.2020.10.036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661960PMC
March 2021

Beyond Shielding: The Roles of Glycans in the SARS-CoV-2 Spike Protein.

ACS Cent Sci 2020 Oct 23;6(10):1722-1734. Epub 2020 Sep 23.

Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 28,000,000 infections and 900,000 deaths worldwide to date. Antibody development efforts mainly revolve around the extensively glycosylated SARS-CoV-2 spike (S) protein, which mediates host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2). Similar to many other viral fusion proteins, the SARS-CoV-2 spike utilizes a glycan shield to thwart the host immune response. Here, we built a full-length model of the glycosylated SARS-CoV-2 S protein, both in the open and closed states, augmenting the available structural and biological data. Multiple microsecond-long, all-atom molecular dynamics simulations were used to provide an atomistic perspective on the roles of glycans and on the protein structure and dynamics. We reveal an essential structural role of -glycans at sites N165 and N234 in modulating the conformational dynamics of the spike's receptor binding domain (RBD), which is responsible for ACE2 recognition. This finding is corroborated by biolayer interferometry experiments, which show that deletion of these glycans through N165A and N234A mutations significantly reduces binding to ACE2 as a result of the RBD conformational shift toward the "down" state. Additionally, end-to-end accessibility analyses outline a complete overview of the vulnerabilities of the glycan shield of the SARS-CoV-2 S protein, which may be exploited in the therapeutic efforts targeting this molecular machine. Overall, this work presents hitherto unseen functional and structural insights into the SARS-CoV-2 S protein and its glycan coat, providing a strategy to control the conformational plasticity of the RBD that could be harnessed for vaccine development.
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http://dx.doi.org/10.1021/acscentsci.0c01056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523240PMC
October 2020

A Multiscale Coarse-grained Model of the SARS-CoV-2 Virion.

bioRxiv 2020 Oct 2. Epub 2020 Oct 2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations, however, are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and on-going development of a largely "bottom-up" coarse-grained (CG) model of the SARS-CoV-2 virion. Structural data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data becomes publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.

Significance Statement: This study reports the construction of a molecular model for the SARS-CoV-2 virion and details our multiscale approach towards model refinement. The resulting model and methods can be applied to and enable the simulation of SARS-CoV-2 virions.
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http://dx.doi.org/10.1101/2020.10.02.323915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536869PMC
October 2020

Simulations support the interaction of the SARS-CoV-2 spike protein with nicotinic acetylcholine receptors and suggest subtype specificity.

bioRxiv 2020 Jul 21. Epub 2020 Jul 21.

Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK.

Changeux . recently suggested that the SARS-CoV-2 spike (S) protein may interact with nicotinic acetylcholine receptors (nAChRs). Such interactions may be involved in pathology and infectivity. Here, we use molecular simulations of validated atomically detailed structures of nAChRs, and of the S protein, to investigate this 'nicotinic hypothesis'. We examine the binding of the Y674-R685 loop of the S protein to three nAChRs, namely the human α4β2 and α7 subtypes and the muscle-like αβγδ receptor from . Our results indicate that Y674-R685 has affinity for nAChRs and the region responsible for binding contains the PRRA motif, a four-residue insertion not found in other SARS-like coronaviruses. In particular, R682 has a key role in the stabilisation of the complexes as it forms interactions with loops A, B and C in the receptor's binding pocket. The conformational behaviour of the bound Y674-R685 region is highly dependent on the receptor subtype, adopting extended conformations in the α4β2 and α7 complexes and more compact ones when bound to the muscle-like receptor. In the α4β2 and αβγδ complexes, the interaction of Y674-R685 with the receptors forces the loop C region to adopt an open conformation similar to other known nAChR antagonists. In contrast, in the α7 complex, Y674-R685 penetrates deeply into the binding pocket where it forms interactions with the residues lining the aromatic box, namely with TrpB, TyrC1 and TyrC2. Estimates of binding energy suggest that Y674-R685, forms stable complexes with all three nAChR subtypes, but has highest affinity for the muscle-type receptor. Analyses of the simulations of the full-length S protein show that the Y674-R685 region is accessible for binding, and suggest a potential binding orientation of the S protein with nAChRs.
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http://dx.doi.org/10.1101/2020.07.16.206680DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386492PMC
July 2020

An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models.

Front Mol Biosci 2020 24;7:93. Epub 2020 Jun 24.

Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, United States.

Protein-ligand binding affinity is a key pharmacodynamic endpoint in drug discovery. Sole reliance on experimental design, make, and test cycles is costly and time consuming, providing an opportunity for computational methods to assist. Herein, we present results comparing random forest and feed-forward neural network proteochemometric models for their ability to predict pIC50 measurements for held out generic Bemis-Murcko scaffolds. In addition, we assess the ability of conformal prediction to provide calibrated prediction intervals in both a retrospective and semi-prospective test using the recently released Grand Challenge 4 data set as an external test set. In total, random forest and deep neural network proteochemometric models show quality retrospective performance but suffer in the semi-prospective setting. However, the conformal predictor prediction intervals prove to be well-calibrated both retrospectively and semi-prospectively showing that they can be used to guide hit discovery and lead optimization campaigns.
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http://dx.doi.org/10.3389/fmolb.2020.00093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328444PMC
June 2020

Shielding and Beyond: The Roles of Glycans in SARS-CoV-2 Spike Protein.

bioRxiv 2020 Jun 11. Epub 2020 Jun 11.

Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA.

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 7,000,000 infections and 400,000 deaths worldwide to date. Antibody development efforts mainly revolve around the extensively glycosylated SARSCoV-2 spike (S) protein, which mediates the host cell entry by binding to the angiotensin-converting enzyme 2 (ACE2). In the context of vaccine design, similar to many other viruses, the SARS-CoV-2 spike utilizes a glycan shield to thwart the host immune response. Here, we built a full-length model of glycosylated SARS-CoV-2 S protein, both in the open and closed states, augmenting the available structural and biological data. Multiple microsecond-long, all-atom molecular dynamics simulations were used to provide an atomistic perspective on the glycan shield and the protein structure, stability, and dynamics. End-to-end accessibility analyses outline a complete overview of the vulnerabilities of the glycan shield of SARS-CoV-2 S protein, which can be harnessed for vaccine development. In addition, a dynamic analysis of the main antibody epitopes is provided. Finally, beyond shielding, a possible structural role of N-glycans at N165 and N234 is hypothesized to modulate and stabilize the conformational dynamics of the spike's receptor binding domain, which is responsible for ACE2 recognition. Overall, this work presents hitherto unseen functional and structural insights into the SARS-CoV-2 S protein and its glycan coat, which may be exploited by therapeutic efforts targeting this essential molecular machine.
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http://dx.doi.org/10.1101/2020.06.11.146522DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302197PMC
June 2020

Comparison of commonly used solid tumor targeted gene sequencing panels for estimating tumor mutation burden shows analytical and prognostic concordance within the cancer genome atlas cohort.

J Immunother Cancer 2020 03;8(1)

Pathology, UC San Diego, La Jolla, California, USA.

Background: Tumor mutation burden (TMB) is a biomarker frequently reported by clinical laboratories, which is derived by quantifying of the number of single nucleotide or indel variants (mutations) identified by next-generation sequencing of tumors. TMB values can inform prognosis or predict the response of a patient's tumor to immune checkpoint inhibitor therapy. Methods for the calculation of TMB are not standardized between laboratories, with significant variables being the gene content of the panels sequenced and the inclusion or exclusion of synonymous variants in the calculations. The impact of these methodological differences has not been investigated and the concordance of reported TMB values between laboratories is unknown.

Methods: Sequence variant lists from more than 9000 tumors of various types were downloaded from The Cancer Genome Atlas. Variant lists were filtered to include only appropriate variant types (ie, non-synonymous only or synonymous and non-synonymous variants) within the genes found in five commonly used targeted solid tumor gene panels as well as an in-house gene panel. Calculated TMB was paired with corresponding overall survival (OS) data of each patient.

Results: Regression analysis indicates high concordance of TMB as derived from the examined panels. TMB derived from panels was consistently and significantly lower than that derived from a whole exome. TMB, as derived from whole exome or the examined panels, showed a significant correlation with OS in the examined data.

Conclusions: TMB derived from the examined gene panels was analytically equivalent between panels, but not between panels and whole-exome sequencing. Correlation between TMB and OS is significant if TMB method-specific cut-offs are used. These results suggest that TMB values, as derived from the gene panels examined, are analytically and prognostically equivalent.
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http://dx.doi.org/10.1136/jitc-2020-000613DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174068PMC
March 2020

D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

J Comput Aided Mol Des 2020 02 23;34(2):99-119. Epub 2020 Jan 23.

Drug Design Data Resource, University of California, San Diego, La Jolla, CA, 92093, USA.

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.
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http://dx.doi.org/10.1007/s10822-020-00289-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261493PMC
February 2020

D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings.

J Comput Aided Mol Des 2019 01 10;33(1):1-18. Epub 2019 Jan 10.

Drug Design Data Resource, University of California, San Diego, La Jolla, CA, 92093, USA.

The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1, and included both pose-prediction and affinity-ranking components. GC3 was structured much like the prior challenges GC2015 and GC2. First, Stage 1 tested pose prediction and affinity ranking methods; then all available crystal structures were released, and Stage 2 tested only affinity rankings, now in the context of the available structures. Unique to GC3 was the addition of a Stage 1b self-docking subchallenge, in which the protein coordinates from all of the cocrystal structures used in the cross-docking challenge were released, and participants were asked to predict the pose of CatS ligands using these newly released structures. We provide an overview of the outcomes and discuss insights into trends and best-practices.
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http://dx.doi.org/10.1007/s10822-018-0180-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472484PMC
January 2019

Dissecting Distinct Roles of NEDDylation E1 Ligase Heterodimer APPBP1 and UBA3 Reveals Potential Evolution Process for Activation of Ubiquitin-related Pathways.

Sci Rep 2018 07 4;8(1):10108. Epub 2018 Jul 4.

Department of Bioengineering, Center for Bioengineering Research, Bourns College of Engineering, University of California at Riverside, 900 University Avenue, Riverside, CA, 92521, USA.

Despite the similar enzyme cascade in the Ubiquitin and Ubiquitin-like peptide(Ubl) conjugation, the involvement of single or heterodimer E1 activating enzyme has been a mystery. Here, by using a quantitative Förster Resonance Energy Transfer (FRET) technology, aided with Analysis of Electrostatic Similarities Of Proteins (AESOP) computational framework, we elucidate in detail the functional properties of each subunit of the E1 heterodimer activating-enzyme for NEDD8, UBA3 and APPBP1. In contrast to SUMO activation, which requires both subunits of its E1 heterodimer AOS1-Uba2 for its activation, NEDD8 activation requires only one of two E1 subunits, UBA3. The other subunit, APPBP1, only contributes by accelerating the activation reaction rate. This discovery implies that APPBP1 functions mainly as a scaffold protein to enhance molecular interactions and facilitate catalytic reaction. These findings for the first time reveal critical new mechanisms and a potential evolutionary pathway for Ubl activations. Furthermore, this quantitative FRET approach can be used for other general biochemical pathway analysis in a dynamic mode.
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http://dx.doi.org/10.1038/s41598-018-28214-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031683PMC
July 2018

D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

J Comput Aided Mol Des 2018 01 4;32(1):1-20. Epub 2017 Dec 4.

Drug Design Data Resource, University of California, San Diego, La Jolla, CA, 92093, USA.

The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank ( http://www.pdb.org ), and in affinity ranking and scoring of bound ligands.
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http://dx.doi.org/10.1007/s10822-017-0088-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767524PMC
January 2018

Conformational heterogeneity in CCR7 undergoes transitions to specific states upon ligand binding.

J Mol Graph Model 2017 06 13;74:352-358. Epub 2017 Apr 13.

Department of Bioengineering, University of California, Riverside 92521, USA. Electronic address:

Ligand-binding to G protein-coupled receptors (GPCRs) acts as the local driving force that initiates signal transduction through the receptor and mediates its conformational transitions and interactions with various intracellular effectors. In a recent study, We have shown that the binding of ligands CCL19 and CCL21 to CCR7 induces biased triggering of side chain-based molecular switches, which coordinate concerted transmembrane helical domain motions and transitioning of the receptor to distinct conformational states (Gaieb, Z., D.D. Lo, and D. Morikis. 2016. Molecular Mechanism of Biased Ligand Conformational Changes in CC Chemokine Receptor 7. Journal of Chemical Information and Modeling. 56: 1808-1822, DOI: 10.1021/acs.jcim.6b00367). To complement our previous study, we compare the results of the free (apo) CCR7 microsecond molecular dynamics simulations to those of the ligand-bound CCR7, and show that the apo receptor is found in conformational heterogeneity that only exhibits random fluctuations and lacks the coordinated helical motions seen in ligand-bound receptors. We conclude that ligand binding is responsible for coordinating the stochastic conformational nature of CCR7 into specific conformational states, initiated and propagated by specific physicochemical events.
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http://dx.doi.org/10.1016/j.jmgm.2017.04.012DOI Listing
June 2017

Detection of Side Chain Rearrangements Mediating the Motions of Transmembrane Helices in Molecular Dynamics Simulations of G Protein-Coupled Receptors.

Comput Struct Biotechnol J 2017 14;15:131-137. Epub 2017 Jan 14.

Department of Bioengineering, University of California, Riverside 92521, USA.

Structure and dynamics are essential elements of protein function. Protein structure is constantly fluctuating and undergoing conformational changes, which are captured by molecular dynamics (MD) simulations. We introduce a computational framework that provides a compact representation of the dynamic conformational space of biomolecular simulations. This method presents a systematic approach designed to reduce the large MD simulation spatiotemporal datasets into a manageable set in order to guide our understanding of how protein mechanics emerge from side chain organization and dynamic reorganization. We focus on the detection of side chain interactions that undergo rearrangements mediating global domain motions and vice versa. Side chain rearrangements are extracted from side chain interactions that undergo well-defined abrupt and persistent changes in distance time series using Gaussian mixture models, whereas global domain motions are detected using dynamic cross-correlation. Both side chain rearrangements and global domain motions represent the dynamic components of the protein MD simulation, and are both mapped into a network where they are connected based on their degree of coupling. This method allows for the study of allosteric communication in proteins by mapping out the protein dynamics into an intramolecular network to reduce the large simulation data into a manageable set of communities composed of coupled side chain rearrangements and global domain motions. This computational framework is suitable for the study of tightly packed proteins, such as G protein-coupled receptors, and we present an application on a seven microseconds MD trajectory of CC chemokine receptor 7 (CCR7) bound to its ligand CCL21.
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http://dx.doi.org/10.1016/j.csbj.2017.01.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5271675PMC
January 2017

Molecular Mechanism of Biased Ligand Conformational Changes in CC Chemokine Receptor 7.

J Chem Inf Model 2016 09 26;56(9):1808-22. Epub 2016 Aug 26.

Department of Bioengineering, ‡Division of Biomedical Sciences, School of Medicine, University of California , Riverside, California 92521, United States.

Biased ligand binding to G protein-coupled receptors enables functional selectivity of intracellular effectors to mediate cellular function. Despite the significant advances made in characterizing the conformational states (transmembrane helical arrangements) capable of discriminating between G protein and arrestin binding, the role of the ligand in stabilizing such conformations remains unclear. To address this issue, we simulate microsecond dynamics of CC chemokine receptor 7 (CCR7) bound to its native biased ligands, CCL19 and CCL21, and detect a series of molecular switches that are mediated by various ligand-induced allosteric events. These molecular switches involve three tyrosine residues (Y112(3.32), Y255(6.51), and Y288(7.39)), three phenylalanine residues (F116(3.36), F208(5.47), and F248(6.44)), and a polar interaction between Q252(6.48) and R294(7.45) in the transmembrane domain of CCR7. Conformational changes within these switches, particularly hydrogen bond formation between Y112(3.32) and Y255(6.51), lead to global helical movements in the receptor's transmembrane helices and contribute to the transitioning of the receptor to distinct states. Ligand-induced helical movements in the receptor highlight the ability of biased ligands to stabilize the receptor in different states through a dynamic network of allosteric events.
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http://dx.doi.org/10.1021/acs.jcim.6b00367DOI Listing
September 2016

Electrostatic Interactions between Complement Regulator CD46(SCR1-2) and Adenovirus Ad11/Ad21 Fiber Protein Knob.

Mol Biol Int 2015 19;2015:967465. Epub 2015 Aug 19.

Department of Bioengineering, University of California, Riverside, CA 92521, USA.

Adenoviruses bind to a variety of human cells to cause infection. Both the B2 adenovirus 11 and B1 adenovirus 21 use protein knobs to bind to complement regulator CD46(SCR1-2) in order to gain entry into host cells. In each complex, the two proteins are highly negatively charged but bind to each other at an interface with oppositely charged surface patches. We computationally generated single-alanine mutants of charged residues in the complexes CD46(SCR1-2)-Ad11k and CD46(SCR1-2)-Ad21k. We used electrostatic clustering and Poisson-Boltzmann free energy calculations to propose a hypothesis on the role of electrostatics in association. Our results delineate specific interfacial electrostatic interactions that are critical for association in both CD46(SCR1-2)-Ad11k and CD46(SCR1-2)-Ad21k. These results will serve as a predictive tool in the selection of mutants with desired binding affinity in experimental mutagenesis studies. This study will also serve as a foundation for the design of inhibitors to treat adenovirus infections.
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http://dx.doi.org/10.1155/2015/967465DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4556874PMC
September 2015