PROTAC-induced Protein Functional Dynamics in Targeted Protein Degradation

PROteolysis TArgeting Chimeras (PROTACs) are small molecules that induce target protein degradation via the ubiquitin-proteasome system. PROTACs recruit the target protein and E3 ligase; a critical first step is forming a ternary complex. However, while the formation a ternary complex is crucial, it may not always guarantee successful protein degradation. The dynamics of the PROTAC-induced degradation complex play a key role in ubiquitination and subsequent degradation. In this study, we computationally modelled protein complex structures and dynamics associated with a series of PROTACs featuring different linkers to investigate why these PROTACs, all of which formed ternary complexes with Cereblon (CRBN) E3 ligase and the target protein bromodomain-containing protein 4 (BRD4 BD1 ), exhibited varying degrees of degradation potency. We constructed the degradation machinery complexes with Culling-Ring Ligase 4A (CRL4A) E3 ligase scaffolds. Through atomistic molecular dynamics simulations, we illustrated how PROTAC-dependent protein dynamics facilitate the arrangement of surface lysine residues of BRD4 BD1 into the catalytic pocket of E2/ubiquitin for ubiquitination. Despite featuring identical warheads in this PROTAC series, the linkers were found to affect the residue-interaction networks, and thus governing the essential motions of the entire degradation machine for ubiquitination. These findings offer a dynamic perspective on ligand-induced protein degradation, providing insights to guide future PROTAC design endeavors.

Selective recognition and discrimination of single isomeric changes in peptide strands with a host : guest sensing array

An indirect competitive binding mechanism can be exploited to allow a combination of cationic fluorophores and water-soluble synthetic receptors to selectively recognize and discriminate peptide strands containing a single isomeric residue in the backbone. Peptide isomerization occurs in long-lived proteins and has been linked with diseases such as Alzheimer's, cataracts and cancer, so isomers are valuable yet underexplored targets for selective recognition. Planar cationic fluorophores can selectively bind hydrophobic, Trp-containing peptide strands in solution, and when paired with receptors that provide a competitive host for the fluorophore, can form a differential sensing array that enables selective discrimination of peptide isomers. Residue variations such as D- and L-Asp, D- and L-isoAsp, D-Ser and D-Glu can all be recognized, simply by their effects on the folded structure of the flexible peptide. Molecular dynamics simulations were applied to determine the most favorable conformation of the peptide : fluorophore conjugate, indicating that favorable π-stacking with internal tryptophan residues in a folded binding pocket enables micromolar binding affinity.

What Strengthens Protein-Protein Interactions: Analysis and Applications of Residue Correlation Networks

Identifying residues critical to protein-protein binding and efficient design of stable and specific protein binders are challenging tasks. Extending beyond the direct contacts in a protein-protein binding interface, our study employs computational modeling to reveal the essential network of residue interactions and dihedral angle correlations critical in protein-protein recognition. We hypothesized that mutating residues exhibiting highly correlated dynamic motion within the interaction network could efficiently optimize protein-protein interactions to create tight and selective protein binders. We tested this hypothesis using the ubiquitin (Ub) and MERS coronaviral papain-like protease (PLpro) complex, since Ub is a central player in multiple cellular functions and PLpro is an antiviral drug target. Our designed ubiquitin variant (UbV) hosting three mutated residues displayed a ∼3,500-fold increase in functional inhibition relative to wild-type Ub. Further optimization of two C-terminal residues within the Ub network resulted in a KD of 1.5 nM and IC50 of 9.7 nM for the five-point Ub mutant, eliciting 27,500-fold and 5,500-fold enhancements in affinity and potency, respectively, as well as improved selectivity, without destabilizing the UbV structure. Our study highlights residue correlation and interaction networks in protein-protein interactions, and introduces an effective approach to design high-affinity protein binders for cell biology research and future therapeutics.

Key Amino Acid Residues of Mitochondrial Transcription Factor A Synergize with Abasic (AP) Site Dynamics To Facilitate AP-Lyase Reactions

Human mitochondrial DNA (mtDNA) encodes 37 essential genes and plays a critical role in mitochondrial and cellular functions. mtDNA is susceptible to damage by endogenous and exogenous chemicals. Damaged mtDNA molecules are counteracted by the redundancy, repair, and degradation of mtDNA. In response to difficult-to-repair or excessive amounts of DNA lesions, mtDNA degradation is a crucial mitochondrial genome maintenance mechanism. Nevertheless, the molecular basis of mtDNA degradation remains incompletely understood. Recently, mitochondrial transcription factor A (TFAM) has emerged as a factor in degrading damaged mtDNA containing abasic (AP) sites. TFAM has AP-lyase activity, which cleaves DNA at AP sites. Human TFAM and its homologs contain a higher abundance of Glu than that of the proteome. To decipher the role of Glu in TFAM-catalyzed AP-DNA cleavage, we constructed TFAM variants and used biochemical assays, kinetic simulations, and molecular dynamics (MD) simulations to probe the functional importance of E187 near a key residue K186. Our previous studies showed that K186 is a primary residue to cleave AP-DNA via Schiff base chemistry. Here, we demonstrate that E187 facilitates β-elimination, key to AP-DNA strand scission. MD simulations showed that extrahelical confirmation of the AP lesion and the flexibility of E187 in TFAM-DNA complexes facilitate AP-lyase reactions. Together, highly abundant Lys and Glu residues in TFAM promote AP-DNA strand scission, supporting the role of TFAM in AP-DNA turnover and implying the breadth of this process across different species.

Modeling structural interconversion in Alzheimers' amyloid beta peptide with classical and intrinsically disordered protein force fields

A comprehensive understanding of the aggregation mechanism in amyloid beta 42 (Aβ42) peptide is imperative for developing therapeutic drugs to prevent or treat Alzheimer's disease. Because of the high flexibility and lack of native tertiary structures of Aβ42, molecular dynamics (MD) simulations may help elucidate the peptide's dynamics with atomic details and collectively improve ensembles not seen in experiments. We applied microsecond-timescale MD simulations to investigate the dynamics and conformational changes of Aβ42 by using a newly developed Amber force field (ff14IDPSFF). We compared the ff14IDPSFF and the regular ff14SB force field by examining the conformational changes of two distinct Aβ42 monomers in explicit solvent. Conformational ensembles obtained by simulations depend on the force field and initial structure, Aβ42^α-helix or Aβ42^β-strand. The ff14IDPSFF sampled a high ratio of disordered structures and diverse β-strand secondary structures; in contrast, ff14SB favored helicity during the Aβ42^α-helix simulations. The conformations obtained from Aβ42^β-strand simulations maintained a balanced content in the disordered and helical structures when simulated by ff14SB, but the conformers clearly favored disordered and β-sheet structures simulated by ff14IDPSFF. The results obtained with ff14IDPSFF qualitatively reproduced the NMR chemical shifts well. In-depth peptide and cluster analysis revealed some characteristic features that may be linked to early onset of the fibril-like structure. The C-terminal region (mainly M35-V40) featured in-registered anti-parallel β-strand (β-hairpin) conformations with tested systems. Our work should expand the knowledge of force field and structure dependency in MD simulations and reveals the underlying structural mechanism-function relationship in Aβ42 peptides. Communicated by Ramaswamy H. Sarma.

GeomBD3: Brownian Dynamics Simulation Software for Biological and Engineered Systems

GeomBD3 is a robust Brownian dynamics simulation package designed to easily handle natural or engineered systems in diverse environments and arrangements. The software package described herein allows users to design, execute, and analyze BD simulations. The simulations use all-atom, rigid molecular models that diffuse according to overdamped Langevin dynamics and interact through electrostatic, Lennard-Jones, and ligand desolvation potentials. The program automatically calculates molecular association rates, surface residence times, and association statistics for any number of user-defined association criteria. Users can also extract molecular association pathways, diffusion coefficients, intermolecular interaction energies, intermolecular contact probability maps, and more using the provided supplementary analysis scripts. We detail the use of the package from start to finish and apply it to a protein-ligand system and a large nucleic acid biosensor. GeomBD3 provides a versatile tool for researchers from various disciplines that can aid in rational design of engineered systems or play an explanatory role as a complement to experiments. GeomBD version 3 is available on our website at http://chemcha-gpu0.ucr.edu/geombd3/ and KBbox at https://kbbox.h-its.org/toolbox/methods/molecular-simulation/geombd/.

Imaging active site chemistry and protonation states: NMR crystallography of the tryptophan synthase α-aminoacrylate intermediate

NMR-assisted crystallography-the integrated application of solid-state NMR, X-ray crystallography, and first-principles computational chemistry-holds significant promise for mechanistic enzymology: by providing atomic-resolution characterization of stable intermediates in enzyme active sites, including hydrogen atom locations and tautomeric equilibria, NMR crystallography offers insight into both structure and chemical dynamics. Here, this integrated approach is used to characterize the tryptophan synthase α-aminoacrylate intermediate, a defining species for pyridoxal-5'-phosphate-dependent enzymes that catalyze β-elimination and replacement reactions. For this intermediate, NMR-assisted crystallography is able to identify the protonation states of the ionizable sites on the cofactor, substrate, and catalytic side chains as well as the location and orientation of crystallographic waters within the active site. Most notable is the water molecule immediately adjacent to the substrate β-carbon, which serves as a hydrogen bond donor to the ε-amino group of the acid-base catalytic residue βLys87. From this analysis, a detailed three-dimensional picture of structure and reactivity emerges, highlighting the fate of the L-serine hydroxyl leaving group and the reaction pathway back to the preceding transition state. Reaction of the α-aminoacrylate intermediate with benzimidazole, an isostere of the natural substrate indole, shows benzimidazole bound in the active site and poised for, but unable to initiate, the subsequent bond formation step. When modeled into the benzimidazole position, indole is positioned with C3 in contact with the α-aminoacrylate Cβ and aligned for nucleophilic attack. Here, the chemically detailed, three-dimensional structure from NMR-assisted crystallography is key to understanding why benzimidazole does not react, while indole does.

Proteome-Wide Characterizations of N6-Methyl-Adenosine Triphosphate- and N6-Furfuryl-Adenosine Triphosphate-Binding Capabilities of Kinases

Kinases catalyze the transfer of the γ-phosphate group from adenosine triphosphate (ATP) to their protein and small-molecule substrates, and this phosphorylation is a crucial element of multiple cell signaling pathways. Herein, we employed isotope-coded ATP acyl-phosphate probes, in conjunction with a multiple-reaction monitoring (MRM)-based targeted proteomic method for proteome-wide identifications of endogenous kinases that can bind to two N6-modified ATP derivatives, N6-methyl-ATP (N6-Me-ATP), and N6-furfuryl-ATP (a.k.a. kinetin triphosphate, KTP). We found that, among the ∼300 quantified kinases, 27 and 18 are candidate kinases that can bind to KTP and N6-Me-ATP, respectively. Additionally, GSK3α and GSK3β are among the kinases that can bind to both ATP analogues. Moreover, the in vitro biochemical assay showed that GSK3β could employ N6-Me-ATP but not KTP as the phosphate group donor to phosphorylate its substrate peptide. Molecular modeling studies provided insights into the differences between N6-Me-ATP and KTP in enabling the GSK3β-mediated phosphorylation. Together, our chemoproteomic approach led to the identification of endogenous kinases that can potentially be targeted by the two ATP analogues. The approach should be generally applicable for assessing endogenous kinases targeted by other ATP and purine analogues.

Substitution of a Surface-Exposed Residue Involved in an Allosteric Network Enhances Tryptophan Synthase Function in Cells

Networks of noncovalent amino acid interactions propagate allosteric signals throughout proteins. Tryptophan synthase (TS) is an allosterically controlled bienzyme in which the indole product of the alpha subunit (αTS) is transferred through a 25 Å hydrophobic tunnel to the active site of the beta subunit (βTS). Previous nuclear magnetic resonance and molecular dynamics simulations identified allosteric networks in αTS important for its function. We show here that substitution of a distant, surface-exposed network residue in αTS enhances tryptophan production, not by activating αTS function, but through dynamically controlling the opening of the indole channel and stimulating βTS activity. While stimulation is modest, the substitution also enhances cell growth in a tryptophan-auxotrophic strain of Escherichia coli compared to complementation with wild-type αTS, emphasizing the biological importance of the network. Surface-exposed networks provide new opportunities in allosteric drug design and protein engineering, and hint at potential information conduits through which the functions of a metabolon or even larger proteome might be coordinated and regulated.

Molecular Mechanics Study of Flow and Surface Influence in Ligand-Protein Association

Ligand–protein association is the first and critical step for many biological and chemical processes. This study investigated the molecular association processes under different environments. In biology, cells have different compartments where ligand–protein binding may occur on a membrane. In experiments involving ligand–protein binding, such as the surface plasmon resonance and continuous flow biosynthesis, a substrate flow and surface are required in experimental settings. As compared with a simple binding condition, which includes only the ligand, protein, and solvent, the association rate and processes may be affected by additional ligand transporting forces and other intermolecular interactions between the ligand and environmental objects. We evaluated these environmental factors by using a ligand xk263 binding to HIV protease (HIVp) with atomistic details. Using Brownian dynamics simulations, we modeled xk263 and HIVp association time and probability when a system has xk263 diffusion flux and a non-polar self-assembled monolayer surface. We also examined different protein orientations and accessible surfaces for xk263. To allow xk263 to access to the dimer interface of immobilized HIVp, we simulated the system by placing the protein 20Å above the surface because immobilizing HIVp on a surface prevented xk263 from contacting with the interface. The non-specific interactions increased the binding probability while the association time remained unchanged. When the xk263 diffusion flux increased, the effective xk263 concentration around HIVp, xk263–HIVp association time and binding probability decreased non-linearly regardless of interacting with the self-assembled monolayer surface or not. The work sheds light on the effects of the solvent flow and surface environment on ligand–protein associations and provides a perspective on experimental design.

Modeling Effects of Surface Properties and Probe Density for Nanoscale Biosensor Design: A Case Study of DNA Hybridization near Surfaces

Electrochemical biosensors have extremely robust applications while offering ease of preparation, miniaturization, and tunability. By adjusting the arrangement and properties of immobilized probes on the sensor surface to optimize target-probe association, one can design highly sensitive and efficient sensors. In electrochemical nucleic acid biosensors, a self-assembled monolayer (SAM) is widely used as a tunable surface with inserted DNA or RNA probes to detect target sequences. The effects of inhomogeneous probe distribution across surfaces are difficult to study experimentally due to inadequate resolution. Regions of high probe density may inhibit hybridization with targets, and the magnitude of the effect may vary depending on the hybridization mechanism on a given surface. Another fundamental question concerns diffusion and hybridization of DNA taking place on surfaces and whether it speeds up or hinders molecular recognition. We used all-atom Brownian dynamics simulations to help answer these questions by simulating the hybridization process of single-stranded DNA (ssDNA) targets with a ssDNA probe on polar, nonpolar, and anionic SAMs at three different probe surface densities. Moreover, we simulated three tightly packed probe clusters by modeling clusters with different interprobe spacing on two different surfaces. Our results indicate that hybridization efficiency depends strongly on finding a balance that allows attractive forces to steer target DNA toward probes without anchoring it to the surface. Furthermore, we found that the hybridization rate becomes severely hindered when interprobe spacing is less than or equal to the target DNA length, proving the need for a careful design to both enhance target-probe association and avoid steric hindrance. We developed a general kinetic model to predict hybridization times and found that it works accurately for typical probe densities. These findings elucidate basic features of nanoscale biosensors, which can aid in rational design efforts and help explain trends in experimental hybridization rates at different probe densities.

Insights Into Dynamics of Inhibitor and Ubiquitin-Like Protein Binding in SARS-CoV-2 Papain-Like Protease

Covid-19 is caused by a novel form of coronavirus for which there are currently no vaccines or anti-viral drugs. This virus, termed SARS-CoV-2 (CoV2), contains Papain-like protease (PLpro) involved in viral replication and immune response evasion. Drugs targeting this protease therefore have great potential for inhibiting the virus, and have proven successful in older coronaviruses. Here, we introduce two effective inhibitors of SARS-CoV-1 (CoV1) and MERS-CoV to assess their potential for inhibiting CoV2 PLpro. We ran 1 μs molecular dynamics (MD) simulations of CoV2, CoV1, and MERS-CoV ligand-free PLpro to characterize the dynamics of CoV2 PLpro, and made comparisons between the three to elucidate important similarities and differences relevant to drug design and ubiquitin-like protein binding for deubiquitinating and deISGylating activity of CoV2. Next, we simulated the inhibitors bound to CoV1 and CoV2 PLpro in various poses and at different known binding sites to analyze their binding modes. We found that the naphthalene-based ligand shows strong potential as an inhibitor of CoV2 PLpro by binding at the putative naphthalene inhibitor binding site in both computational predictions and experimental assays. Our modeling work suggested strategies to improve naphthalene-based compounds, and our results from molecular docking showed that the newly designed compounds exhibited improved binding affinity. The other ligand, chemotherapy drug 6-mercaptopurine (6MP), showed little to no stable intermolecular interaction with PLpro and quickly dissociated or remained highly mobile. We demonstrate multiple ways to improve the binding affinity of the naphthalene-based inhibitor scaffold by engaging new residues in the unused space of the binding site. Analysis of CoV2 PLpro also brings insights into recognition of ubiquitin-like proteins that may alter innate immune response.

Amyloid-β (Aβ42) Peptide Aggregation Rate and Mechanism on Surfaces with Widely Varied Properties: Insights from Brownian Dynamics Simulations

Amyloid-β (Aβ) plaques, which form by aggregation of harmless Aβ peptide monomers into larger fibrils, are characteristic of neurodegenerative disorders such as Alzheimer's disease. Efforts to treat Alzheimer's disease focus on stopping or reversing the aggregation process that leads to fibril formation. However, effective treatments are elusive due to certain unknown aspects of the process. Many hypotheses point to disruption of cell membranes by adsorbed Aβ monomers or oligomers, but how Aβ behaves and aggregates on surfaces of widely varying properties, such as those present in a cell, is unclear. Elucidating the effects of various surfaces on the dynamics of Aβ and the kinetics of the aggregation process from bulk solution to a surface-adsorbed multimer can help identify what drives aggregation, leading to new methods of intervention by inhibitory drugs or other means. In this work, we used all-atom Brownian dynamics simulations to study the association of two distinct Aβ42 monomer conformations with a surface-adsorbed or free-floating Aβ42 dimer. We calculated the association time, surface interaction energy, surface diffusion coefficient, surface residence time, and the mechanism of association on four different surfaces and two different bulk solution scenarios. In the presence of a surface, the majority of monomers underwent a two-dimensional surface-mediated association that depended primarily on an Aβ42 electrostatic interaction with the self-assembled monolayer (SAM) surfaces. Moreover, aggregation could be inhibited greatly by surfaces with high affinity for Aβ42 and heterogeneous charge distribution. Our results can be used to identify new opportunities for disrupting or reversing the Aβ42 aggregation process.

Inhibiting Matrix Metalloproteinase-2 Activation by Perturbing Protein-Protein Interactions Using a Cyclic Peptide

We report on a cyclic peptide that inhibits matrix metalloproteinase-2 (MMP2) activation with a low-nM-level potency. This inhibitor specifically binds to the D₅₇₀-A₅₈₃ epitope on proMMP2 and interferes with the protein-protein interaction (PPI) between proMMP2 and tissue inhibitor of metalloproteinases-2 (TIMP2), thereby preventing the TIMP2-assisted proMMP2 activation process. We developed this cyclic peptide inhibitor through an epitope-targeted library screening process and validated its binding to proMMP2. Using a human melanoma cell line, we demonstrated the cyclic peptide's ability to modulate cellular MMP2 activities and inhibit cell migration. These results provide the first successful example of targeting the PPI between proMMP2 and TIMP2, confirming the feasibility of an MMP2 inhibition strategy that has been sought after for 2 decades.

Transient States and Barriers from Molecular Simulations and the Milestoning Theory: Kinetics in Ligand-Protein Recognition and Compound Design

This study presents a novel computational approach to study molecular recognition and binding kinetics for drug-like compounds dissociating from a flexible protein system. The intermediates and their free energy profile during ligand association and dissociation processes control ligand-protein binding kinetics and bring a more complete picture of ligand-protein binding. The method applied the milestoning theory to extract kinetics and thermodynamics information from running short classical molecular dynamics (MD) simulations for frames from a given dissociation path. High-dimensional ligand-protein motions (3N-6 degrees of freedom) during ligand dissociation were reduced by use of principal component modes for assigning more than 100 milestones, and classical MD runs were allowed to travel multiple milestones to efficiently obtain ensemble distribution of initial structures for MD simulations and estimate the transition time and rate during ligand traveling between milestones. We used five pyrazolourea ligands and cyclin-dependent kinase 8 with cyclin C (CDK8/CycC) as our model system as well as metadynamics and a pathway search method to sample dissociation pathways. With our strategy, we constructed the free energy profile for highly mobile biomolecular systems. The computed binding free energy and residence time correctly ranked the pyrazolourea ligand series, in agreement with experimental data. Guided by a barrier of a ligand passing an αC helix and activation loop, we introduced one hydroxyl group to parent compounds to design our ligands with increased residence time and validated our prediction by experiments. This work provides a novel and robust approach to investigate dissociation kinetics of large and flexible systems for understanding unbinding mechanisms and designing new small-molecule drugs with desired binding kinetics.

Dynamics and molecular interactions of single-stranded DNA in nucleic acid biosensors with varied surface properties

Electrochemical DNA biosensors utilizing self-assembled monolayers (SAMs) with inserted DNA probes are promising biosensor designs because of their ease of preparation, miniaturization, and tunability. However, much is still unknown about the interactions between biomolecules such as DNA and various surfaces. A fundamental question regarding these sensors concerns the nature of diffusion of target molecules taking place on sensor surfaces and whether it speeds up the molecular recognition process. Lack of understanding of molecular interaction and surface diffusion in addition to questions regarding the behavior of DNA probes immobilized on these surfaces currently limits the rational design of nucleic acid biosensors. Using all-atom unbiased molecular dynamics (MD) simulations we found that single-stranded DNA (ssDNA) behavior on SAMs is drastically altered by different surface chemistries, with ssDNA adopting very different orientations upon adsorption and surface diffusivity varying over an order of magnitude. Probe behavior varies equally broadly as probes are considerably more stable in certain SAMs than others, which affects the accessibility of probes to the target molecules and likely changes DNA hybridization kinetics in multiple ways. We also found that nearby probes can alter each other's orientations substantially, which highlights the importance of surface density control. Our results elucidate nucleic acid biosensor dynamics vital to rational design and offer insights that can aid in the design of surface properties and patterning for specific applications.

Coordinated Network Changes across the Catalytic Cycle of Alpha Tryptophan Synthase

Networks of noncovalent interactions are important for protein structural dynamics. We used nuclear magnetic resonance chemical shift covariance analyses on an inactive variant of the alpha subunit of tryptophan synthase to map amino acid interaction networks across its catalytic cycle. Although some network connections were common to every enzyme state, many of the network connections strengthened or weakened over the catalytic cycle; these changes were highly coordinated. These results suggest a higher level of network organization. Our analyses identified periodic, second-order networks that show highly coordinated interaction changes across the catalytic cycle. These periodic networks may help synchronize the sequence of structural transitions necessary for enzyme function. Molecular dynamics simulations identified interaction changes across the catalytic cycle, including those involving the catalytic residue Glu49, which may help drive other interaction changes throughout the enzyme structure. Similar periodic networks may direct structural transitions and allosteric interactions in other proteins.

Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems

We introduce a new heterogeneous CPU+GPU-enhanced DFTB approach for the routine and efficient simulation of large chemical and biological systems. Compared to homogeneous computing with conventional CPUs, heterogeneous computing approaches exhibit substantial performance with only a modest increase in power consumption, both of which are essential to upcoming exascale computing initiatives. We show that DFTB-based molecular dynamics is a natural candidate for heterogeneous computing, since the computational bottleneck in these simulations is the diagonalization of the Hamiltonian matrix, which is performed several times during a single molecular dynamics trajectory. To thoroughly test and understand the performance of our heterogeneous CPU+GPU approach, we examine a variety of algorithmic implementations, benchmarks of different hardware configurations, and applications of this methodology on several large chemical and biological systems. Finally, to demonstrate the capability of our implementation, we conclude with a large-scale DFTB MD simulation of explicitly solvated HIV protease (3974 atoms total) as a proof-of-concept example of an extremely large/complex system which, to the best of our knowledge, is the first time that an entire explicitly solvated protein has been treated at a quantum-based MD level of detail.

Discovery of CDK8/CycC Ligands with a New Virtual Screening Tool

Selective inhibition of cyclin-dependent kinase 8 and cyclin C (CDK8/CycC) has been suggested as a promising strategy for decreasing mitogenic signals in cancer cells with reduced toxicity toward normal cells. We developed a novel virtual screening protocol for drug development and applied it to the discovery of new CDK8/CycC type II ligands, which is likely to achieve long residence time and specificity. We first analyzed the binding thermodynamics of 11 published pyrazolourea ligands using molecular dynamics simulations and a free-energy calculation method, VM2, and extracted the key binding information to assist virtual screening. The urea moiety was found to be the critical structural contributor of the reference ligands. Starting with the urea moiety, we conducted substructure-based searches with our newly developed superposition and single-point energy evaluation method, followed by free-energy calculations, and singled out three purchasable compounds for bioassay testing. The ranking from the experimental results is completely consistent with the predicted rankings. A potent drug-like compound was found to have a K_d value of 42.5 nm, which is similar to those of the most potent reference ligands; this provided a good starting point for further improvement. This study shows that our novel virtual screening protocol is an accurate and efficient tool for drug development.

Construction of a Sequenceable Protein Mimetic Peptide Library with a True 3D Diversifiable Chemical Space

We present here a library of protein mimetic bicyclic peptides. These nanosized structures exhibit rigid backbones and spatially diversifiable side chains. They present modular amino acids on all three linkages, providing access to a true 3D diversifiable chemical space. These peptides are synthesized through a Cu-catalyzed click reaction and a Ru-catalyzed ring-closing metathesis reaction. Their bicyclic topology can be reduced to a linear one, using Edman degradation and Pd-catalyzed deallylation reactions. The linearization approaches allow de novo sequencing through mass spectrometry methods. We demonstrate the function of a particular peptide that was identified through a high throughput screening against the E₃₆₃-R₃₇₈ epitope on the intrinsically disordered c-Myc oncoprotein. Intracellular delivery of this peptide could interfere with the c-Myc-mediated transcription and inhibit proliferation in a human glioblastoma cell line.

A molecular dynamics investigation of CDK8/CycC and ligand binding: conformational flexibility and implication in drug discovery

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein-ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein-ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.

Immunoproteasome inhibition and bioactivity of thiasyrbactins

A family of macrodilactam natural products, the syrbactins, are known proteasome inhibitors. A small group of syrbactin analogs was prepared with a sulfur-for-carbon substitution to enhance synthetic accessibility and facilitate modulation of their solubility. Two of these compounds surprisingly proved to be inhibitors of the trypsin-like catalytic site, including of the immunoproteasome. Their bound and free conformations suggest special properties of the thiasyrbactin ring are responsible for this unusual preference, which may be exploited to develop drug-like immunoproteasome inhibitors. These compounds show greater selectivity than earlier compounds used to infer phenotypes of immunoproteasome inhibition, like ONX-0914.

Exploring the binding properties and structural stability of an opsin in the chytrid Spizellomyces punctatus using comparative and molecular modeling

Background

Opsin proteins are seven transmembrane receptor proteins which detect light. Opsins can be classified into two types and share little sequence identity: type 1, typically found in bacteria, and type 2, primarily characterized in metazoa. The type 2 opsins (Rhodopsins) are a subfamily of G-protein coupled receptors (GPCRs), a large and diverse class of seven transmembrane proteins and are generally restricted to metazoan lineages. Fungi use light receptors including opsins to sense the environment and transduce signals for developmental or metabolic changes. Opsins characterized in the Dikarya (Ascomycetes and Basidiomycetes) are of the type 1 bacteriorhodopsin family but the early diverging fungal lineages have not been as well surveyed. We identified by sequence similarity a rhodopsin-like GPCR in genomes of early diverging chytrids and examined the structural characteristics of this protein to assess its likelihood to be homologous to animal rhodopsins and bind similar chromophores.

Methods

We used template-based structure modeling, automated ligand docking, and molecular modeling to assess the structural and binding properties of an identified opsin-like protein found in Spizellomyces punctatus, a unicellular, flagellated species belonging to Chytridiomycota, one of the earliest diverging fungal lineages. We tested if the sequence and inferred structure were consistent with a solved crystal structure of a type 2 rhodopsin from the squid Todarodes pacificus.

Results

Our results indicate that the Spizellomyces opsin has structural characteristics consistent with functional animal type 2 rhodopsins and is capable of maintaining a stable structure when associated with the retinaldehyde chromophore, specifically the 9-cis-retinal isomer. Together, these results support further the homology of Spizellomyces opsins to animal type 2 rhodopsins.

Discussion

This represents the first test of structure/function relationship of a type 2 rhodopsin identified in early branching fungal lineages, and provides a foundation for future work exploring pathways and components of photoreception in early fungi.

Mechanism of the Association Pathways for a Pair of Fast and Slow Binding Ligands of HIV-1 Protease

Equilibrium constants, together with kinetic rate constants of binding, are key factors in the efficacy and safety of drug compounds, informing drug design. However, the association pathways of protein-ligand binding, which contribute to their kinetic behaviors, are little understood. In this work, we used unbiased all-atom molecular dynamics (MD) simulations with an explicit solvent model to study the association processes of protein-ligand binding. Using the HIV protease (HIVp)-xk263 and HIVp-ritonavir protein-ligand systems as cases, we observed that ligand association is a multistep process involving diffusion, localization, and conformational rearrangements of the protein, ligand, and water molecules. Moreover, these two ligands preferred different routes of binding, which reflect two well-known binding mechanisms: induced-fit and conformation selection models. Our study shows that xk263 has a stronger capacity for desolvating surrounding water molecules, thereby inducing a semiopen conformation of the HIVp flaps (induced-fit model). In contrast, the slow dehydration characteristic of ritonavir allows for gradual association with the binding pocket of HIVp when the protein's flap conformation is fully open (conformation selection model). By studying the mechanism of ligand association and understanding the role of solvent molecules during the binding event, we can obtain a different perspective on the mechanism of macromolecule recognition, providing insights into drug discovery.

Adaptation of a Genetic Screen Reveals an Inhibitor for Mitochondrial Protein Import Component Tim44

Diverse protein import pathways into mitochondria use translocons on the outer membrane (TOM) and inner membrane (TIM). We adapted a genetic screen, based on Ura3 mistargeting from mitochondria to the cytosol, to identify small molecules that attenuated protein import. Small molecule mitochondrial import blockers of the Carla Koehler laboratory (MB)-10 inhibited import of substrates that require the TIM23 translocon. Mutational analysis coupled with molecular docking and molecular dynamics modeling revealed that MB-10 binds to a specific pocket in the C-terminal domain of Tim44 of the protein-associated motor (PAM) complex. This region was proposed to anchor Tim44 to the membrane, but biochemical studies with MB-10 show that this region is required for binding to the translocating precursor and binding to mtHsp70 in low ATP conditions. This study also supports a direct role for the PAM complex in the import of substrates that are laterally sorted to the inner membrane, as well as the mitochondrial matrix. Thus, MB-10 is the first small molecule modulator to attenuate PAM complex activity, likely through binding to the C-terminal region of Tim44.

Understanding ligand-receptor non-covalent binding kinetics using molecular modeling

Kinetic properties may serve as critical differentiators and predictors of drug efficacy and safety, in addition to the traditionally focused binding affinity. However the quantitative structure-kinetics relationship (QSKR) for modeling and ligand design is still poorly understood. This review provides an introduction to the kinetics of drug binding from a fundamental chemistry perspective. We focus on recent developments of computational tools and their applications to non-covalent binding kinetics.

Analysis of Ligand-Receptor Association and Intermediate Transfer Rates in Multienzyme Nanostructures with All-Atom Brownian Dynamics Simulations

We present the second-generation GeomBD Brownian dynamics software for determining interenzyme intermediate transfer rates and substrate association rates in biomolecular complexes. Substrate and intermediate association rates for a series of enzymes or biomolecules can be compared between the freely diffusing disorganized configuration and various colocalized or complexed arrangements for kinetic investigation of enhanced intermediate transfer. In addition, enzyme engineering techniques, such as synthetic protein conjugation, can be computationally modeled and analyzed to better understand changes in substrate association relative to native enzymes. Tools are provided to determine nonspecific ligand-receptor association residence times, and to visualize common sites of nonspecific association of substrates on receptor surfaces. To demonstrate features of the software, interenzyme intermediate substrate transfer rate constants are calculated and compared for all-atom models of DNA origami scaffold-bound bienzyme systems of glucose oxidase and horseradish peroxidase. Also, a DNA conjugated horseradish peroxidase enzyme was analyzed for its propensity to increase substrate association rates and substrate local residence times relative to the unmodified enzyme. We also demonstrate the rapid determination and visualization of common sites of nonspecific ligand-receptor association by using HIV-1 protease and an inhibitor, XK263. GeomBD2 accelerates simulations by precomputing van der Waals potential energy grids and electrostatic potential grid maps, and has a flexible and extensible support for all-atom and coarse-grained force fields. Simulation software is written in C++ and utilizes modern parallelization techniques for potential grid preparation and Brownian dynamics simulation processes. Analysis scripts, written in the Python scripting language, are provided for quantitative simulation analysis. GeomBD2 is applicable to the fields of biophysics, bioengineering, and enzymology in both predictive and explanatory roles.

Mechanisms of Enhanced Catalysis in Enzyme-DNA Nanostructures Revealed through Molecular Simulations and Experimental Analysis

Understanding and controlling the molecular interactions between enzyme substrates and DNA nanostructures has important implications in the advancement of enzyme-DNA technologies as solutions in biocatalysis. Such hybrid nanostructures can be used to create enzyme systems with enhanced catalysis by controlling the local chemical and physical environments and the spatial organization of enzymes. Here we have used molecular simulations with corresponding experiments to describe a mechanism of enhanced catalysis due to locally increased substrate concentrations. With a series of DNA nanostructures conjugated to horseradish peroxidase, we show that binding interactions between substrates and the DNA structures can increase local substrate concentrations. Increased local substrate concentrations in HRP(DNA) nanostructures resulted in 2.9- and 2.4-fold decreases in the apparent Michaelis constants of tetramethylbenzidine and 4-aminophenol, substrates of HRP with tunable binding interactions to DNA nanostructures with dissociation constants in the micromolar range. Molecular simulations and kinetic analysis also revealed that increased local substrate concentrations enhanced the rates of substrate association. Identification of the mechanism of increased local concentration of substrates in close proximity to enzymes and their active sites adds to our understanding of nanostructured biocatalysis from which we can develop guidelines for enhancing catalysis in rationally designed systems.

Visualizing the tunnel in tryptophan synthase with crystallography: Insights into a selective filter for accommodating indole and rejecting water

Four new X-ray structures of tryptophan synthase (TS) crystallized with varying numbers of the amphipathic N-(4'-trifluoromethoxybenzoyl)-2-aminoethyl phosphate (F6) molecule are presented. These structures show one of the F6 ligands threaded into the tunnel from the β-site and reveal a distinct hydrophobic region. Over this expanse, the interactions between F6 and the tunnel are primarily nonpolar, while the F6 phosphoryl group fits into a polar pocket of the β-subunit active site. Further examination of TS structures reveals that one portion of the tunnel (T1) binds clusters of water molecules, whereas waters are not observed in the nonpolar F6 binding region of the tunnel (T2). MD simulation of another TS structure with an unobstructed tunnel also indicates the T2 region of the tunnel excludes water, consistent with a dewetted state that presents a significant barrier to the transfer of water into the closed β-site. We conclude that hydrophobic molecules can freely diffuse between the α- and β-sites via the tunnel, while water does not. We propose that exclusion of water serves to inhibit reaction of water with the α-aminoacrylate intermediate to form ammonium ion and pyruvate, a deleterious side reaction in the αβ-catalytic cycle. Finally, while most TS structures show βPhe280 partially blocking the tunnel between the α- and β-sites, new structures show an open tunnel, suggesting the flexibility of the βPhe280 side chain. Flexible docking studies and MD simulations confirm that the dynamic behavior of βPhe280 allows unhindered transfer of indole through the tunnel, therefore excluding a gating role for this residue.

Syrbactin Structural Analog TIR-199 Blocks Proteasome Activity and Induces Tumor Cell Death

Multiple myeloma is an aggressive hematopoietic cancer of plasma cells. The recent emergence of three effective FDA-approved proteasome-inhibiting drugs, bortezomib (Velcade®), carfilzomib (Kyprolis®), and ixazomib (Ninlaro®), confirms that proteasome inhibitors are therapeutically useful against neoplastic disease, in particular refractory multiple myeloma and mantle cell lymphoma. This study describes the synthesis, computational affinity assessment, and preclinical evaluation of TIR-199, a natural product-derived syrbactin structural analog. Molecular modeling and simulation suggested that TIR-199 covalently binds each of the three catalytic subunits (β1, β2, and β5) and revealed key interaction sites. In vitro and cell culture-based proteasome activity measurements confirmed that TIR-199 inhibits the proteasome in a dose-dependent manner and induces tumor cell death in multiple myeloma and neuroblastoma cells as well as other cancer types in the NCI-60 cell panel. It is particularly effective against kidney tumor cell lines, with >250-fold higher anti-tumor activities than observed with the natural product syringolin A. In vivo studies in mice revealed a maximum tolerated dose of TIR-199 at 25 mg/kg. The anti-tumor activity of TIR-199 was confirmed in hollow fiber assays in mice. Adverse drug reaction screens in a kidney panel revealed no off-targets of concern. This is the first study to examine the efficacy of a syrbactin in animals. Taken together, the results suggest that TIR-199 is a potent new proteasome inhibitor with promise for further development into a clinical drug for the treatment of multiple myeloma and other forms of cancer.

Protonation states and catalysis: Molecular dynamics studies of intermediates in tryptophan synthase

The importance of protonation states and proton transfer in pyridoxal 5'-phosphate (PLP)-chemistry can hardly be overstated. Although experimental approaches to investigate pKa values can provide general guidance for assigning proton locations, only static pictures of the chemical species are available. To obtain the overall protein dynamics for the interpretation of detailed enzyme catalysis in this study, guided by information from solid-state NMR, we performed molecular dynamics (MD) simulations for the PLP-dependent enzyme tryptophan synthase (TRPS), whose catalytic mechanism features multiple quasi-stable intermediates. The primary objective of this work is to elucidate how the position of a single proton on the reacting substrate affects local and global protein dynamics during the catalytic cycle. In general, proteins create a chemical environment and an ensemble of conformational motions to recognize different substrates with different protonations. The study of these interactions in TRPS shows that functional groups on the reacting substrate, such as the phosphoryl group, pyridine nitrogen, phenolic oxygen and carboxyl group, of each PLP-bound intermediate play a crucial role in constructing an appropriate molecular interface with TRPS. In particular, the protonation states of the ionizable groups on the PLP cofactor may enhance or weaken the attractions between the enzyme and substrate. In addition, remodulation of the charge distribution for the intermediates may help generate a suitable environment for chemical reactions. The results of our study enhance knowledge of protonation states for several PLP intermediates and help to elucidate their effects on protein dynamics in the function of TRPS and other PLP-dependent enzymes.

The paradox of conformational constraint in the design of Cbl(TKB)-binding peptides

Solving the crystal structure of Cbl(TKB) in complex with a pentapeptide, pYTPEP, revealed that the PEP region adopted a poly-L-proline type II (PPII) helix. An unnatural amino acid termed a proline-templated glutamic acid (ptE) that constrained both the backbone and sidechain to the bound conformation was synthesized and incorporated into the pYTPXP peptide. We estimated imposing structural constraints onto the backbone and sidechain of the peptide and preorganize it to the bound conformation in solution will yield nearly an order of magnitude improvement in activity. NMR studies confirmed that the ptE-containing peptide adopts the PPII conformation, however, competitive binding studies showed an order of magnitude loss of activity. Given the emphasis that is placed on imposing structural constraints, we provide an example to support the contrary. These results point to conformational flexibility at the interface, which have implications in the design of potent Cbl(TKB)-binding peptides.

Ligand Binding Pathway Elucidation for Cryptophane Host-Guest Complexes

Modeling binding pathways can provide insight into molecular recognition, including kinetic mechanisms, barriers to binding, and gating effects. This work represents a novel computational approach, Hopping Minima, for the determination of conformational transitions of single molecules as well as binding pathways for molecular complexes. The method begins by thoroughly sampling a set of conformational minima for a molecular system. The natural motions of the system are modeled using the normal modes of the sampled minima. The natural motions are utilized to connect conformational minima and are finally combined to form association/binding pathways in the case of molecular complexes. We provide an implementation and example application of the method using alanine dipeptide and a set of chemical host-guest systems: two cryptophane hosts with two guest cations, trimethylammonium and tetramethylammonium. Our results demonstrate that conformational transitions can be modeled and extended to find binding pathways as well as energetic information relevant to the minimum conformations involved. This approach has advantages over simulation-based methods for studying systems with slow binding processes and can help design molecules with preferred binding kinetics.

Agonist and antagonist binding to the nuclear vitamin D receptor: dynamics, mutation effects and functional implications

Purpose

The thermodynamically favored complex between the nuclear vitamin D receptor (VDR) and 1α,25(OH)₂-vitamin D₃ (1,25D3) triggers a shift in equilibrium to favor VDR binding to DNA, heterodimerization with the nuclear retinoid x receptor (RXR) and subsequent regulation of gene transcription. The key amino acids and structural requirements governing VDR binding to nuclear coactivators (NCoA) are well defined. Yet very little is understood about the internal changes in amino acid flexibility underpinning the control of ligand affinity, helix 12 conformation and function. Herein, we use molecular dynamics (MD) to study how the backbone and side-chain flexibility of the VDR differs when a) complexed to 1α,25(OH)₂-vitamin D₃ (1,25D3, agonist) and (23S),25-dehydro-1α(OH)-vitamin D₃-26,23-lactone (MK, antagonist); b) residues that form hydrogen bonds with the C25-OH (H305 and H397) of 1,25D3 are mutated to phenylalanine; c) helix 12 conformation is changed and ligand is removed; and d) x-ray water near the C1- and C3-OH groups of 1,25D3 are present or replaced with explicit solvent.

Methods

We performed molecular dynamic simulations on the apo- and holo-VDRs and used T-Analyst to monitor the changes in the backbone and side-chain flexibility of residues that form regions of the VDR ligand binding pocket (LBP), NCoA surface and control helix 12 conformation.

Results

The VDR-1,25D3 and VDR-MK MD simulations demonstrate that 1,25D3 and MK induce highly similar changes in backbone and side-chain flexibility in residues that form the LBP. MK however did increase the backbone and side-chain flexibility of L404 and R274 respectively. MK also induced expansion of the VDR charge clamp (i.e. NCoA surface) and weakened the intramolecular interaction between H305---V418 (helix 12) and TYR401 (helix 11). In VDR_FF, MK induced a generally more rigid LBP and stronger interaction between F397 and F422 than 1,25D3, and reduced the flexibility of the R274 side-chain. Lastly the VDR MD simulations indicate that R274 can sample multiple conformations in the presence of ligand. When the R274 is extended, the β-OH group of 1,25D3 lies proximal to the backbone carbonyl oxygen of R274 and the side-chain forms H-bonds with hinge domain residues. This differs from the x-ray, kinked geometry, where the side-chain forms an H-bond with the 1α-OH group. Furthermore, 1,25D3, but not MK was observed to stabilize the x-ray geometry of R274 during the > 30 ns MD runs.

Conclusions

The MD methodology applied herein provides an in silico foundation to be expanded upon to better understand the intrinsic flexibility of the VDR and better understand key side-chain and backbone movements involved in the bimolecular interaction between the VDR and its’ ligands.

Electronic supplementary material

The online version of this article (doi:10.1186/2193-9616-1-2) contains supplementary material, which is available to authorized users.

Insights from free-energy calculations: protein conformational equilibrium, driving forces, and ligand-binding modes

Accurate free-energy calculations provide mechanistic insights into molecular recognition and conformational equilibrium. In this work, we performed free-energy calculations to study the thermodynamic properties of different states of molecular systems in their equilibrium basin, and obtained accurate absolute binding free-energy calculations for protein-ligand binding using a newly developed M2 algorithm. We used a range of Asp-Phe-Gly (DFG)-in/out p38α mitogen-activated protein kinase inhibitors as our test cases. We also focused on the flexible DFG motif, which is closely connected to kinase activation and inhibitor binding. Our calculations explain the coexistence of DFG-in and DFG-out states of the loop and reveal different components (e.g., configurational entropy and enthalpy) that stabilize the apo p38α conformations. To study novel ligand-binding modes and the key driving forces behind them, we computed the absolute binding free energies of 30 p38α inhibitors, including analogs with unavailable experimental structures. The calculations revealed multiple stable, complex conformations and changes in p38α and inhibitor conformations, as well as balance in several energetic terms and configurational entropy loss. The results provide relevant physics that can aid in designing inhibitors and understanding protein conformational equilibrium. Our approach is fast for use with proteins that contain flexible regions for structure-based drug design.

Homology modeling of cannabinoid receptors: discovery of cannabinoid analogues for therapeutic use

Cannabinoids represent a promising class of compounds for developing novel therapeutic agents. Since the isolation and identification of the major psychoactive component Δ(9)-THC in Cannabis sativa in the 1960s, numerous analogues of the classical plant cannabinoids have been synthesized and tested for their biological activity. These compounds primarily target the cannabinoid receptors 1 (CB1) and Cannabinoid receptors 2 (CB2). This chapter focuses on CB1. Despite the lack of crystal structures for CB1, protein-based homology modeling approaches and molecular docking methods can be used in the design and discovery of cannabinoid analogues. Efficient synthetic approaches for therapeutically interesting cannabinoid analogues have been developed to further facilitate the drug discovery process.

Gating and Intermolecular Interactions in Ligand-Protein Association: Coarse-Grained Modeling of HIV-1 Protease

Most biological processes are initiated or mediated by the association of ligands and proteins. This work studies multistep, ligand-protein association processes by Brownian dynamics simulations with coarse-grained models for HIV-1 protease (HIVp) and its neutral ligands. We report the average association times when the ligand concentration is 100 μM. The influence of crowding on the simulated binding time was also studied. HIVp has flexible loops that serve as a gate during the ligand binding processes. It is believed that the flaps are partially closed most of the time in its free state. To accelerate our simulations, we fixed a part of the HIVp and reparameterized our coarse-grained model, using atomistic molecular dynamics simulations, to reproduce the "gating" motions of HIVp. HIVp-ligand interactions changed the gating behavior of HIVp and helped ligands diffuse on HIVp surface to accelerate binding. The structural adjustment of the ligand toward its final stable state was the limiting step in the binding processes, which is highly system dependent. The intermolecular attraction between the ligands and crowder proteins contributes the most to the crowding effects. The results highlight broader implications in recognition pathways under more complex environment that considers molecular dynamics and conformational changes. This work brings insights into ligand-protein associations and is helpful in the design of targeted ligands.

Mechanism of PhosphoThreonine/Serine Recognition and Specificity for Modular Domains from All-atom Molecular Dynamics

Background

Phosphopeptide-binding domains mediate many vital cellular processes such as signal transduction and protein recognition. We studied three well-known domains important for signal transduction: BRCT repeats, WW domain and forkhead-associated (FHA) domain. The first two recognize both phosphothreonine (pThr) and phosphoserine (pSer) residues, but FHA has high specificity for pThr residues. Here we used molecular dynamics (MD) simulations to reveal how FHA exclusively chooses pThr and how BRCT and WW recognize both pThr/pSer. The work also investigated the energies and thermodynamic information of intermolecular interactions.

Results

Simulations carried out included wide-type and mutated systems. Through analysis of MD simulations, we found that the conserved His residue defines dual loops feature of the FHA domain, which creates a small cavity reserved for only the methyl group of pThr. These well-organized loop interactions directly response to the pThr binding selectivity, while single loop (the 2nd phosphobinding site of FHA) or in combination with α-helix (BRCT repeats) or β-sheet (WW domain) fail to differentiate pThr/pSer.

Conclusions

Understanding the domain pre-organizations constructed by conserved residues and the driving force of domain-phosphopeptide recognition provides structural insight into pThr specific binding, which also helps in engineering proteins and designing peptide inhibitors.

Binding pathways of ligands to HIV-1 protease: coarse-grained and atomistic simulations

Multiscale simulations (coarse-grained Brownian dynamics simulations and all-atom molecular dynamics simulations in implicit solvent) were applied to reveal the binding processes of ligands as they enter the binding site of the HIV-1 protease. The initial structures used for the molecular dynamics simulations were generated based on the Brownian dynamics trajectories, and this is the first molecular dynamics simulation of modeling the association of a ligand with the protease. We found that a protease substrate successfully binds to the protein when the flaps are fully open. Surprisingly, a smaller cyclic urea inhibitor (XK263) can reach the binding site when the flaps are not fully open. However, if the flaps are nearly closed, the inhibitor must rearrange or binding can fail because the inhibitor cannot attain proper conformations to enter the binding site. Both the peptide substrate and XK263 can also affect the protein's internal motion, which may help the flaps to open. Simulations allow us to efficiently study the ligand binding processes and may help those who study drug discovery to find optimal association pathways and to design those ligands with the best binding kinetics.