Optimal protocol and trajectory visualization for conformational searches of peptides and proteins

Design and synthesis of novel Thiazolo[5,4-b]pyridine derivatives as potent and selective EGFR-TK inhibitors targeting resistance Mutations in non-small cell lung cancer

A novel series of substituted thiazolo[5,4-b]pyridine analogues were rationally designed and synthesized via a multi-step synthetic pathway, including Suzuki cross-coupling reaction. The anticancer activity of all forty-five synthesized derivatives was evaluated against HCC827, H1975, and A549 cancer cell lines utilizing the standard MTT assay. A significant number of the thiazolo[5,4-b]pyridine derivatives exhibited potent anticancer activity. Notably, compounds 10b, 10c, 10h, 10i, and 10k emerged as the most promising anticancer agents. The lead compound, N-(3-(6-(2-aminopyrimidin-5-yl)thiazolo[5,4-b]pyridin-2-yl)-2-methylphenyl)-2,5-difluorobenzenesulfonamide (10k), displayed remarkable potency with IC50 values of 0.010 μM, 0.08 μM, and 0.82 μM against the HCC827, NCI-H1975 and A-549 cancer cell lines, respectively, which were comparable to the clinically approved drug Osimertinib. Importantly, the potent derivatives 10b, 10c, 10h, 10i, and 10k exhibited selective cytotoxicity towards cancer cells and showing no toxicity against the normal BEAS-2B cell line at concentrations exceeding 35 μM. Mechanistic studies revealed that the active compound 10k acts as an EGFR-TK autophosphorylation inhibitor in HCC827 cells. Furthermore, apoptosis assays demonstrated that compound 10k induced substantial early apoptosis (31.9 %) and late apoptosis (8.8 %) in cancer cells, in contrast to the control condition exhibiting only 2.0 % early and 1.6 % late apoptosis. Molecular docking simulations of the synthesized compounds revealed that they formed essential hinge interactions and established hydrogen bonding with Cys797, indicating potential target engagement. These findings highlight the potential of the synthesized thiazolo [(Woodburn, 1999; Zigrossi et al., 2022) 5,45,4-b]pyridine derivatives as promising anticancer agents, warranting further investigation for the development of novel targeted therapies against non-small cell lung cancer.

Principal Component Analysis and Related Methods for Investigating the Dynamics of Biological Macromolecules

Principal component analysis (PCA) is used to reduce the dimensionalities of high-dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high-dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods and their applications for investigating protein dynamics.

Computational Analysis of the SARS-CoV-2 RBD-ACE2-Binding Process Based on MD and the 3D-RISM Theory

The binding process of angiotensin-converting enzyme 2 (ACE2) to the receptor-binding domain (RBD) of the severe acute respiratory syndrome-like coronavirus 2 spike protein was investigated using molecular dynamics simulation and the three-dimensional reference interaction-site model theory. The results suggested that the protein-binding process consists of a protein-protein approaching step, followed by a local structural rearrangement step. In the approaching step, the interprotein interaction energy decreased as the proteins approached each other, whereas the solvation free energy increased. As the proteins approached, the glycan of ACE2 first established a hydrogen bond with the RBD. Thereafter, the number of interprotein hydrogen bonds increased rapidly. The solvation free energy increased because of the desolvation of the protein as it approached its partner. The spatial distribution function of the solvent revealed the presence of hydrogen bonds bridged by water molecules on the RBD-ACE2 interface. Finally, principal component analysis revealed that ACE2 showed a pronounced conformational change, whereas there was no significant change in RBD.

Phenylalkylamines in calcium channels: computational analysis of experimental structures

Experimental 3D structures of calcium channels with phenylalkylamines (PAAs) provide basis for further analysis of atomic mechanisms of these important cardiovascular drugs. In the crystal structure of the engineered calcium channel CavAb with Br-verapamil and in the cryo-EM structure of the Cav1.1 channel with verapamil, the ligands bind in the inner pore. However, there are significant differences between these structures. In the crystal structure the ligand ammonium group is much closer to the ion in the selectivity-filter region Site 3, which is most proximal to the inner pore, than in the cryo-EM structure. Here we used Monte Carlo energy minimizations to dock PAAs in calcium channels. Our computations suggest that in the crystal structure Site 3 is occupied by a water molecule rather than by a calcium ion. Analysis of the published electron density map does not rule out this possibility. In the cryo-EM structures the ammonium group of verapamil is shifted from the calcium ion in Site 3 either along the pore axis, towards the cytoplasm or away from the axis. Our unbiased docking reproduced these binding modes. However, in the cryo-EM structures detergent and lipid molecules interact with verapamil. When we removed these molecules, the nitrile group of verapamil bound to the calcium ion in Site 3. Models of Cav1.2 with different PAAs suggest similar binding modes and direct contacts of the ligands electronegative atoms with the calcium ion in Site 3. Such interactions explain paradoxes in structure-activity relationships of PAAs.

Analysis of molecular dynamics simulations of 10-residue peptide, chignolin, using statistical mechanics: Relaxation mode analysis and three-dimensional reference interaction site model theory

Molecular dynamics simulation is a fruitful tool for investigating the structural stability, dynamics, and functions of biopolymers at an atomic level. In recent years, simulations can be performed on time scales of the order of milliseconds using special purpose systems. Since the most stable structure, as well as meta-stable structures and intermediate structures, is included in trajectories in long simulations, it is necessary to develop analysis methods for extracting them from trajectories of simulations. For these structures, methods for evaluating the stabilities, including the solvent effect, are also needed. We have developed relaxation mode analysis to investigate dynamics and kinetics of simulations based on statistical mechanics. We have also applied the three-dimensional reference interaction site model theory to investigate stabilities with solvent effects. In this paper, we review the results for designing amino-acid substitution of the 10-residue peptide, chignolin, to stabilize the misfolded structure using these developed analysis methods.

Folding pathways of NuG2-a designed mutant of protein G-using relaxation mode analysis

Dynamic analysis methods are important for analyzing long simulations such as folding simulations. Relaxation mode analysis, which approximately extracts slow modes and rates, has been applied in molecular dynamics (MD) simulations of protein systems. Previously, we showed that slow modes are suitable for analyzing simulations in which large conformational changes occur. Here, we applied relaxation mode analysis to folding simulations of a designed mutant of protein G, NuG2, to investigate its folding pathways. The folding simulations of NuG2 were previously performed for this mutant with Anton. In the present study, the free energy surfaces were calculated by projecting the coordinates on the axis of the slow relaxation modes obtained from relaxation mode analysis. We classified various characteristic states such as native, nativelike, intermediate, and random states and clarified two main folding pathways. In the early folding process, the first and second β strands formed an N-terminal β-sheet. After the early folding process, the fourth β strand formed along the first β strand in the same or opposite direction as the native structure; two characteristic intermediate states were identified. Finally, the intermediate structures folded to the native structure in the folding process. Relaxation mode analysis can be applied to folding simulations of complex proteins to investigate their folding processes.

Determination of the structural ensemble of the molten globule state of a protein by computer simulations

We have used computer simulations to investigate the structural nature of the molten globule (MG) state of canine milk lysozyme. To sample the conformational space efficiently, we performed replica-exchange umbrella sampling simulations with the radius of gyration as a reaction coordinate. We applied the Weighted Histogram Analysis Method to the trajectory of the simulations to obtain the potential of mean force, from which we identified representative structures corresponding to local minima in the free energy surface. The representative structures obtained in this way are in accord with the characteristics of the MG state reported previously by experimental studies. We conjecture that the MG state comprises a series of partially structured states undergoing relatively fast conformational interchange.

Relaxation mode analysis for molecular dynamics simulations of proteins

Molecular dynamics simulation is a powerful method for investigating the structural stability, dynamics, and function of biopolymers at the atomic level. In recent years, it has become possible to perform simulations on time scales of the order of milliseconds using special hardware. However, it is necessary to derive the important factors contributing to structural change or function from the complicated movements of biopolymers obtained from long simulations. Although some analysis methods for protein systems have been developed using increasing simulation times, many of these methods are static in nature (i.e., no information on time). In recent years, dynamic analysis methods have been developed, such as the Markov state model and relaxation mode analysis (RMA), which was introduced based on spin and homopolymer systems. The RMA method approximately extracts slow relaxation modes and rates from trajectories and decomposes the structural fluctuations into slow relaxation modes, which characterize the slow relaxation dynamics of the system. Recently, this method has been applied to biomolecular systems. In this article, we review RMA and its improved versions for protein systems.

Observation of helix associations for insertion of a retinal molecule and distortions of helix structures in bacteriorhodopsin

We applied a newly proposed prediction method for membrane protein structures to bacteriorhodopsin that has distorted transmembrane helices in the native structure. This method uses an implicit membrane model, which restricts sampling space during folding in a membrane region, and includes helix bending. Replica-exchange simulations were performed with seven transmembrane helices only without a retinal molecule. Obtained structures were classified into clusters of similar structures, which correspond to local-minimum free energy states. The two lowest free energy states corresponded to a native-like structure with the correct empty space for retinal and a structure with this empty space filled with a helix. Previous experiments of bacteriorhodopsin suggested that association of transmembrane helices enables them to make a room for insertion of a retinal. Our results are consistent with these results. Moreover, distortions of helices in the native-like structures were successfully reproduced. In the distortions, whereas the locations of kinks for all helices were similar to those of Protein Data Bank's data, the amount of bends was more similar for helices away from the retinal than for those close to the retinal in the native structure. This suggests a hypothesis that the amino-acid sequence specifies the location of kinks in transmembrane helices and that the amount of distortions depends on the interactions with the surrounding molecules such as neighboring helices, lipids, and retinal.

Relaxation mode analysis and Markov state relaxation mode analysis for chignolin in aqueous solution near a transition temperature

It is important to extract reaction coordinates or order parameters from protein simulations in order to investigate the local minimum-energy states and the transitions between them. The most popular method to obtain such data is principal component analysis, which extracts modes of large conformational fluctuations around an average structure. We recently applied relaxation mode analysis for protein systems, which approximately estimates the slow relaxation modes and times from a simulation and enables investigations of the dynamic properties underlying the structural fluctuations of proteins. In this study, we apply this relaxation mode analysis to extract reaction coordinates for a system in which there are large conformational changes such as those commonly observed in protein folding/unfolding. We performed a 750-ns simulation of chignolin protein near its folding transition temperature and observed many transitions between the most stable, misfolded, intermediate, and unfolded states. We then applied principal component analysis and relaxation mode analysis to the system. In the relaxation mode analysis, we could automatically extract good reaction coordinates. The free-energy surfaces provide a clearer understanding of the transitions not only between local minimum-energy states but also between the folded and unfolded states, even though the simulation involved large conformational changes. Moreover, we propose a new analysis method called Markov state relaxation mode analysis. We applied the new method to states with slow relaxation, which are defined by the free-energy surface obtained in the relaxation mode analysis. Finally, the relaxation times of the states obtained with a simple Markov state model and the proposed Markov state relaxation mode analysis are compared and discussed.

Analysis of helix-helix interactions of bacteriorhodopsin by replica-exchange simulations

We performed long-time replica-exchange Monte Carlo simulations of bacteriorhodopsin transmembrane helices, which made it possible that wide conformational space was sampled. Using only the helix-helix interactions and starting from random initial configurations, we obtained the nativelike helix arrangement successfully and predicted a part of the configurations (three helices out of seven) precisely. By the principal component analysis we classified low-energy structures into some clusters of similar structures, and we showed that the above nativelike three-helix configuration is reproduced properly in most clusters and that not only the van der Waals interactions but also the electrostatic interactions contributed to the stabilization of the native structures.

Prediction of Ligand Binding Affinity by the Combination of Replica-Exchange Method and Double-Decoupling Method

A prediction method for ligand binding affinities to proteins is proposed. We first predict the structures of protein-ligand complex by the replica-exchange umbrella sampling or its extension. We then calculate ligand binding affinities based on these predicted ligand-protein bound structures by the double-decoupling method. As a test of the effectiveness of the proposed method, we applied it to the system of the oncoprotein MDM2 and a ligand. The value of the predicted binding affinity turned out to be in good agreement with that from experiments.

Lanosterol reverses protein aggregation in cataracts

The human lens is comprised largely of crystallin proteins assembled into a highly ordered, interactive macro-structure essential for lens transparency and refractive index. Any disruption of intra- or inter-protein interactions will alter this delicate structure, exposing hydrophobic surfaces, with consequent protein aggregation and cataract formation. Cataracts are the most common cause of blindness worldwide, affecting tens of millions of people, and currently the only treatment is surgical removal of cataractous lenses. The precise mechanisms by which lens proteins both prevent aggregation and maintain lens transparency are largely unknown. Lanosterol is an amphipathic molecule enriched in the lens. It is synthesized by lanosterol synthase (LSS) in a key cyclization reaction of a cholesterol synthesis pathway. Here we identify two distinct homozygous LSS missense mutations (W581R and G588S) in two families with extensive congenital cataracts. Both of these mutations affect highly conserved amino acid residues and impair key catalytic functions of LSS. Engineered expression of wild-type, but not mutant, LSS prevents intracellular protein aggregation of various cataract-causing mutant crystallins. Treatment by lanosterol, but not cholesterol, significantly decreased preformed protein aggregates both in vitro and in cell-transfection experiments. We further show that lanosterol treatment could reduce cataract severity and increase transparency in dissected rabbit cataractous lenses in vitro and cataract severity in vivo in dogs. Our study identifies lanosterol as a key molecule in the prevention of lens protein aggregation and points to a novel strategy for cataract prevention and treatment.

Affinity comparison of different THCA synthase to CBGA using modeling computational approaches

The Δ^9-Tetrahydrocannabinol (THCA) is the primary psychoactive compound of Cannabis Sativa. It is produced by Δ^1- Tetrahydrocannabinolic acid synthase (THCA) which catalyzes the oxidative cyclization of cannabigerolic acid (CBGA) the precursor of the THCA. In this study, we were interested by the three dimensional structure of THCA synthase protein. Generation of models were done by MODELLER v9.11 and homology modeling with Δ1-tetrahydrocannabinolic acid (THCA) synthase X ray structure (PDB code 3VTE) on the basis of sequences retrieved from GenBank. Procheck, Errat, and Verify 3D tools were used to verify the reliability of the six 3D models obtained, the overall quality factor and the Prosa Z-score were also used to check the quality of the six modeled proteins. The RMSDs for C-alpha atoms, main-chain atoms, side-chain atoms and all atoms between the modeled structures and the corresponding template ranged between 0.290 Å-1.252 Å, reflecting the good quality of the obtained models. Our study of the CBGA-THCA synthase docking demonstrated that the active site pocket was successfully recognized using computational approach. The interaction energy of CBGA computed in ‘fiber types’ proteins ranged between -4.1 95 kcal/mol and -5.95 kcal/mol whereas in the ‘drug type’ was about -7.02 kcal/mol to -7.16 kcal/mol, which maybe indicate the important role played by the interaction energy of CBGA in the determination of the THCA level in Cannabis Sativa L. varieties. Finally, we have proposed an experimental design in order to explore the binding energy source of ligand-enzyme in Cannabis Sativa and the production level of the THCA in the absence of any information regarding the correlation between the enzyme affinity and THCA level production. This report opens the doors to more studies predicting the binding site pocket with accuracy from the perspective of the protein affinity and THCA level produced in Cannabis Sativa.

Prediction of Protein-Ligand Binding Structures by Replica-Exchange Umbrella Sampling Simulations: Application to Kinase Systems

We have applied our prediction method, which is based on the replica-exchange umbrella sampling for protein-ligand binding structures, to two kinase systems (p38 and JNK3) with two different ligand molecules for each kinase. Starting from configurations in which the protein and the ligand are far away from each other, our method predicted the ligand binding structures in excellent agreement with the experimental data from PDB in all four cases, which suggests the general applicability of our method to kinase systems. In addition, the protein flexibility was shown to be essential to predict the correct binding structure for one of the systems, where dihydroquinolinone was bound to p38 alpha kinase (PDB ID: 1OVE ).

The histidine-phosphocarrier protein of the phosphoenolpyruvate: sugar phosphotransferase system of Bacillus sphaericus self-associates

The phosphotransferase system (PTS) is involved in the use of carbon sources in bacteria. Bacillus sphaericus, a bacterium with the ability to produce insecticidal proteins, is unable to use hexoses and pentoses as the sole carbon source, but it has ptsHI genes encoding the two general proteins of the PTS: enzyme I (EI) and the histidine phosphocarrier (HPr). In this work, we describe the biophysical and structural properties of HPr from B. sphaericus, HPr^bs, and its affinity towards EI of other species to find out whether there is inter-species binding. Conversely to what happens to other members of the HPr family, HPr^bs forms several self-associated species. The conformational stability of the protein is low, and it unfolds irreversibly during heating. The protein binds to the N-terminal domain of EI from Streptomyces coelicolor, EIN^sc, with a higher affinity than that of the natural partner of EIN^sc, HPr^sc. Modelling of the complex between EIN^sc and HPr^bs suggests that binding occurs similarly to that observed in other HPr species. We discuss the functional implications of the oligomeric states of HPr^bs for the glycolytic activity of B. sphaericus, as well as a strategy to inhibit binding between HPr^sc and EIN^sc.

Predicting the preferred conformations of luteolin-4'-O-β-D-glucoside in gas phase: a comparison of two computational approaches

A tree-step computational approach has been applied to determine the lowest-energy conformers of luteolin-4'-O-β-D-glucoside (L4'G). Fifty-seven starting structures of the L4'G have been built, and then by performing with density functional theory (DFT) optimizations and second-order Møller-Plesset (MP2) calculations, the preferred conformations of L4'G are predicted. In order to test the accuracy of the computational approach, a hybrid Monte-Carlo multiple minimum (MCMM)/quantum mechanical (QM) approach is applied to determine the favorable conformers of L4'G. The alternative classification is employed to put similar conformations into the same catalogue according to the dihedral angles among the luteolin rings, glycosidic dihedral angles, and the orientations of hydroxyl and hydroxymethyl groups. The low-energy conformations are located after the optimizations at the HF/6-31G(d) and B3LYP/6-311+G(d) levels. Compared with the hybrid MCMM/QM approach, the tree-step computational approach not only remains accurate but also saves a lot of computing resources.

Structure refinement of protein low resolution models using the GNEIMO constrained dynamics method

The challenge in protein structure prediction using homology modeling is the lack of reliable methods to refine the low resolution homology models. Unconstrained all-atom molecular dynamics (MD) does not serve well for structure refinement due to its limited conformational search. We have developed and tested the constrained MD method, based on the generalized Newton-Euler inverse mass operator (GNEIMO) algorithm for protein structure refinement. In this method, the high-frequency degrees of freedom are replaced with hard holonomic constraints and a protein is modeled as a collection of rigid body clusters connected by flexible torsional hinges. This allows larger integration time steps and enhances the conformational search space. In this work, we have demonstrated the use of torsional GNEIMO method without using any experimental data as constraints, for protein structure refinement starting from low-resolution decoy sets derived from homology methods. In the eight proteins with three decoys for each, we observed an improvement of ~2 Å in the rmsd in coordinates to the known experimental structures of these proteins. The GNEIMO trajectories also showed enrichment in the population density of native-like conformations. In addition, we demonstrated structural refinement using a "freeze and thaw" clustering scheme with the GNEIMO framework as a viable tool for enhancing localized conformational search. We have derived a robust protocol based on the GNEIMO replica exchange method for protein structure refinement that can be readily extended to other proteins and possibly applicable for high throughput protein structure refinement.

Relaxation mode analysis of a peptide system: comparison with principal component analysis

This article reports the first attempt to apply the relaxation mode analysis method to a simulation of a biomolecular system. In biomolecular systems, the principal component analysis is a well-known method for analyzing the static properties of fluctuations of structures obtained by a simulation and classifying the structures into some groups. On the other hand, the relaxation mode analysis has been used to analyze the dynamic properties of homopolymer systems. In this article, a long Monte Carlo simulation of Met-enkephalin in gas phase has been performed. The results are analyzed by the principal component analysis and relaxation mode analysis methods. We compare the results of both methods and show the effectiveness of the relaxation mode analysis.

Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA

The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation.

Ab initio prediction of protein-ligand binding structures by replica-exchange umbrella sampling simulations

We have developed a prediction method for the binding structures of ligands with proteins. Our method consists of three steps. First, replica-exchange umbrella sampling simulations are performed along the distance between a putative binding site of a protein and a ligand as the reaction coordinate. Second, we obtain the potential of mean force (PMF) of the unbiased system using the weighted histogram analysis method and determine the distance that corresponds to the global minimum of PMF. Third, structures that have this global-minimum distance and energy values around the average potential energy are collected and analyzed using the principal component analysis. We predict the binding structure as the global-minimum free energy state on the free energy landscapes along the two major principal component axes. As test cases, we applied our method to five protein-ligand complex systems. Starting from the configuration in which the protein and the ligand are far away from each other in each system, our method predicted the ligand binding structures in excellent agreement with the experimental data from Protein Data Bank.

Binding selectivity of RecA to a single stranded DNA, a computational approach

Homologous recombination (HR) is the major DNA double strand break repair pathway which maintains the genomic integrity. It is fundamental for the survivability and functionality of all organisms. One of the initial steps in HR is the formation of the nucleoprotein filament composed by a single stranded DNA chain surrounded by the recombinases protein. The filament orchestrates the search for an undamaged homologue, as a template for the repair process. Our theoretical study was aimed at elucidating the selectivity of the interaction between a monomer of the recombinases enzyme in the Escherichia coli, EcRecA, the bacterial homologue of human Rad51, with a series of oligonucleotides of nine bases length. The complex, equilibrated for 20 ns with Langevian dynamics, was inserted in a periodic box with a 8 Å buffer of water molecules explicitly described by the TIP3P model. The absolute binding free energies are calculated in an implicit solvent using the Poisson-Boltzmann (PB) and the generalized Born (GB) solvent accessible surface area, using the MM-PB(GB)SA model. The solute entropic contribution is also calculated by normal mode analysis. The results underline how a significant contribution of the binding free energy is due to the interaction with the Arg196, a critical amino acid for the activity of the enzyme. The study revealed how the binding affinity of EcRecA is significantly higher toward dT₉ rather than dA₉, as expected from the experimental results.

A new activity of anti-HIV and anti-tumor protein GAP31: DNA adenosine glycosidase--structural and modeling insight into its functions

We report here the high-resolution atomic structures of GAP31 crystallized in the presence of HIV-LTR DNA oligonucleotides systematically designed to examine the adenosine glycosidase activity of this anti-HIV and anti-tumor plant protein. Structural analysis and molecular modeling lead to several novel findings. First, adenine is bound at the active site in the crystal structures of GAP31 to HIV-LTR duplex DNA with 5' overhanging adenosine ends, such as the 3'-processed HIV-LTR DNA but not to DNA duplex with blunt ends. Second, the active site pocket of GAP31 is ideally suited to accommodate the 5' overhanging adenosine of the 3'-processed HIV-LTR DNA and the active site residues are positioned to perform the adenosine glycosidase activity. Third, GAP31 also removes the 5'-end adenine from single-stranded HIV-LTR DNA oligonucleotide as well as any exposed adenosine, including that of single nucleotide dAMP but not from AMP. Fourth, GAP31 does not de-purinate guanosine from di-nucleotide GT. These results suggest that GAP31 has DNA adenosine glycosidase activity against accessible adenosine. This activity is distinct from the generally known RNA N-glycosidase activity toward the 28S rRNA. It may be an alternative function that contributes to the antiviral and anti-tumor activities of GAP31. These results provide molecular insights consistent with the anti-HIV mechanisms of GAP31 in its inhibition on the integration of viral DNA into the host genome by HIV-integrase as well as irreversible topological relaxation of the supercoiled viral DNA.

Determination, prediction, and understanding of structures, using the energy landscapes of chemical systems – Part II

In the past decade, new theoretical approaches have been developed to determine, predict and understand the struc-ture of chemical compounds. The central element of these methods has been the investigation of the energy landscape of chemical systems. Applications range from extended crystalline and amorphous compounds over clusters and molecular crystals to proteins. In this review, we are going to give an introduction to energy landscapes and methods for their investigation, together with a number of examples. These include structure prediction of extended and mo-lecular crystals, structure prediction and folding of proteins, structure analysis of zeolites, and structure determination of crystals from powder diffraction data.

Structure of the disordered C terminus of Rab7 GTPase induced by binding to the Rab geranylgeranyl transferase catalytic complex reveals the mechanism of Rab prenylation

Protein prenylation is a widespread process that involves the transfer of either a farnesyl or a geranylgeranyl moiety to one or more C-terminal cysteines of the target protein. Rab geranylgeranyl transferase (RabGGTase) is responsible for the largest number of individual protein prenylation events in the cell. A decade-long effort to crystallize the catalytic ternary complex of RabGGTase has remained fruitless, prompting us to use a computational approach to predict the structure of this 200-kDa assembly. On the basis of high resolution structures of two sub-complexes, we have generated a composite model where the rigid parts of the protein are represented by precomputed grid potentials, whereas the mobile parts are described in atomic details using Internal Coordinate Mechanics. Selection of the best docking solution of the flexible parts on the grid is followed by explicit atomistic refinement of the lowest energy conformations enabling realistic modeling of complex structures. Using this approach we demonstrate that the flexible C terminus of Rab7 substrate forms a series of progressively weaker and less specific interactions that channel it into the active site of RabGGTase. We have validated the computational model through biochemical experiments and demonstrated that to be prenylated RabGTPase must possess at least nine amino acids between the prenylation motif and the hydrophobic sequence anchoring the beginning of the Rab C terminus on the enzyme. This sequence, known as the C-terminal interacting motif is shown to play a dual role in Rab prenylation by contributing a significant fraction of binding energy to the catalytic complex assembly and by orienting the C terminus of RabGTPase in the vicinity of the active site of RabGGTase. This mechanism is unique to RabGGTase when compared with other prenyltransferases, which encode the specificity for their cognate substrates directly at their active site.

Development of anaplastic lymphoma kinase (ALK) small-molecule inhibitors for cancer therapy

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase (RTK) involved in the genesis of several human cancers; indeed, ALK was initially identified in constitutively activated and oncogenic fusion forms--the most common being nucleophosmin (NPM)-ALK--in a non-Hodgkin's lymphoma (NHL) known as anaplastic large-cell lymphoma (ALCL) and subsequent studies identified ALK fusions in the human sarcomas called inflammatory myofibroblastic tumors (IMTs). In addition, two recent reports have suggested that the ALK fusion, TPM4-ALK, may be involved in the genesis of a subset of esophageal squamous cell carcinomas. While the cause-effect relationship between ALK fusions and malignancies such as ALCL and IMT is very well established, more circumstantial links implicate the involvement of the full-length, normal ALK receptor in the genesis of additional malignancies including glioblastoma, neuroblastoma, breast cancer, and others; in these instances, ALK is believed to foster tumorigenesis following activation by autocrine and/or paracrine growth loops involving the reported ALK ligands, pleiotrophin (PTN) and midkine (MK). There are no currently available ALK small-molecule inhibitors approved for clinical cancer therapy; however, recognition of the variety of malignancies in which ALK may play a causative role has recently begun to prompt developmental efforts in this area. This review provides a succinct summary of normal ALK biology, the confirmed and putative roles of ALK fusions and the full-length ALK receptor in the development of human cancers, and efforts to target ALK using small-molecule kinase inhibitors.

Temperature-dependent downhill unfolding of ubiquitin. II. Modeling the free energy surface

To provide evidence for the interpretation of temperature-dependent unfolding kinetics and the downhill unfolding scenario presented in the accompanying experimental article (Part I), the free energy surface of ubiquitin unfolding is calculated using statistical mechanical models of the Muñoz-Eaton (ME) form. The models allow only two states for each amino acid residue, folded or unfolded, and permutations of these states generate an ensemble of microstates. One-dimensional free energy curves are calculated using the number of folded residues as a reaction coordinate. The proposed sequential unfolding of ubiquitin's beta-sheet is tested by mapping the free energy onto two reaction coordinates inspired by the experiment as follows: the number of folded residues in ubiquitin's stable beta-strands I and II and those of the less stable strands III-V. Although the original ME model successfully captures folding features of zipper-like one-dimensional folders, it misses important tertiary interactions between residues that are far from each other in primary sequence. To take tertiary contacts into account, partially folded microstates based on a spherical growth model are included in the calculation and compared with the original model. By calculating the folding probability of each residue for a given point on the free energy surface, the unfolding pathway of ubiquitin is visualized. At low temperature, thermal unfolding occurs along a sequential unfolding pathway as follows: disruption of the beta-strands III-V followed by unfolding of the strands I and II. At high temperature, multiple unfolding routes are formed. The heterogeneity of the transition state explains the global nonexponential unfolding observed in the T-jump experiment at high temperature. The calculation also reports a high stability for the alpha-helix of ubiquitin.

Small molecules block the polymerization of Z alpha1-antitrypsin and increase the clearance of intracellular aggregates

The Z mutant of alpha1-antitrypsin (Glu342Lys) causes a domain swap and the formation of intrahepatic polymers that aggregate as inclusions and predispose the homozygote to cirrhosis. We have identified an allosteric cavity that is distinct from the interface involved in polymerization for rational structure-based drug design to block polymer formation. Virtual ligand screening was performed on 1.2 million small molecules and 6 compounds were identified that reduced polymer formation in vitro. Modeling the effects of ligand binding on the cavity and re-screening the library identified an additional 10 compounds that completely blocked polymerization. The best antagonists were effective at ratios of compound to Z alpha1-antitrypsin of 2.5:1 and reduced the intracellular accumulation of Z alpha1-antitrypsin by 70% in a cell model of disease. Identifying small molecules provides a novel therapy for the treatment of liver disease associated with the Z allele of alpha1-antitrypsin.

Protein structure prediction aided by geometrical and probabilistic constraints

Database-assisted ab initio protein structure prediction methods have exhibited considerable promise in the recent past, with several implementations being successful in community-wide experiments (CASP). We have employed combinatorial optimization techniques toward solving the protein structure prediction problem. A Monte Carlo minimization algorithm has been employed on a constrained search space to identify minimum energy configurations. The search space is constrained by using radius of gyration cutoffs, the loop backbone dihedral probability distributions, and various secondary structure packing conformations. Simulations have been carried out on several sequences and 1000 conformations have been initially generated. Of these, 50 best candidates have then been selected as probable conformations. The search for the optimum has been simplified by incorporating various geometrical constraints on secondary structural elements using distance restraint potential functions. The advantages of the reported methodology are its simplicity, and modifiability to include other geometric and probabilistic restraints.

Modeling the interaction between aldolase and the thrombospondin-related anonymous protein, a key connection of the malaria parasite invasion machinery

A complex molecular motor empowers substrate-dependent motility and host cell invasion in malaria parasites. The interaction between aldolase and the transmembrane adhesin thrombospondin-related anonymous protein (TRAP) transduces the motor force across the parasite surface. Here, we analyzed this interaction by using state-of-the-art flexible docking. Besides algorithms to account for induced fit in the side-chains of the Plasmodium falciparum aldolase (PfAldo) structure, we used additional in silico receptors modeled upon crystallographic structures of evolutionarily related aldolases to incorporate enzyme backbone flexibility, and to overcome structure inaccuracies due to the relatively low resolution (3.0 A) of the genuine PfAldo structure. Our results indicate that, in spite of multiple intermolecular contacts, only the six C-terminal residues of the TRAP cytoplasmic tail bind in an ordered manner to PfAldo. This portion of TRAP targets the PfAldo active site, with its n-1 Trp residue, which is essential for this interaction, buried within the PfAldo catalytic pocket. Docking of a TRAP peptide bearing a Trp to Ala mutation rendered the lower energy configurations either bound weakly outside the active site or not bound to PfAldo at all. The position of the bound TRAP peptide, and particularly the close proximity between the carbonyl of its n-2 Asp residue and the experimentally determined position of the phosphate-6 group of fructose 1,6-phosphate bound to mammalian aldolases, predicts an inhibitory effect of TRAP on catalysis. Enzymatic and TRAP-binding assays using mutant PfAldo molecules strongly support the overall structural model. These results might provide the initial framework for the identification of novel antiparasitic compounds.

Ab initio prediction of peptide-MHC binding geometry for diverse class I MHC allotypes

Since determining the crystallographic structure of all peptide-MHC complexes is infeasible, an accurate prediction of the conformation is a critical computational problem. These models can be useful for determining binding energetics, predicting the structures of specific ternary complexes with T-cell receptors, and designing new molecules interacting with these complexes. The main difficulties are (1) adequate sampling of the large number of conformational degrees of freedom for the flexible peptide, (2) predicting subtle changes in the MHC interface geometry upon binding, and (3) building models for numerous MHC allotypes without known structures. Whereas previous studies have approached the sampling problem by dividing the conformational variables into different sets and predicting them separately, we have refined the Biased-Probability Monte Carlo docking protocol in internal coordinates to optimize a physical energy function for all peptide variables simultaneously. We also imitated the induced fit by docking into a more permissive smooth grid representation of the MHC followed by refinement and reranking using an all-atom MHC model. Our method was tested by a comparison of the results of cross-docking 14 peptides into HLA-A*0201 and 9 peptides into H-2K(b) as well as docking peptides into homology models for five different HLA allotypes with a comprehensive set of experimental structures. The surprisingly accurate prediction (0.75 A backbone RMSD) for cross-docking of a highly flexible decapeptide, dissimilar to the original bound peptide, as well as docking predictions using homology models for two allotypes with low average backbone RMSDs of less than 1.0 A illustrate the method's effectiveness. Finally, energy terms calculated using the predicted structures were combined with supervised learning on a large data set to classify peptides as either HLA-A*0201 binders or nonbinders. In contrast with sequence-based prediction methods, this model was also able to predict the binding affinity for peptides to a different MHC allotype (H-2K(b)), not used for training, with comparable prediction accuracy.

Improving CAPRI predictions: optimized desolvation for rigid-body docking

The ICM Docking and Interface Side-Chain Optimization (ICM-DISCO) showed promising predictive results during the first CAPRI experiment by successfully finding medium- or high-accuracy models in 3 of the 7 targets. A key factor was the ability to recognize near-native rigid-body geometries in a relatively low number of alternative docking poses, together with the successful refinement of the rigid-body docking interfaces. Since then, we have focused on improving the scoring function to optimally discriminate the near-native rigid-body conformations. For that, we have defined a new desolvation descriptor for rigid-body docking, based on atomic solvation parameters (ASPs) derived from octanol-water transfer experiments. This and other new approaches have been gradually incorporated into our docking procedure during our participation on the second CAPRI experiment. Overall, we produced reasonable models for 8 of the 9 official targets. Especially encouraging were those cases in which a homology model of 1 of the subunits had to be used during the docking simulations. And not less gratifying has been the successful prediction of antibody-antigen targets in a completely automatic, unrestrained fashion. In summary, our success rate (89%) shows a consistent improvement over the previous CAPRI rounds, and suggests that a correct desolvation description is key for improved protein-protein docking predictions.

Molecular basis for the binding polyspecificity of an anti-cholera toxin peptide 3 monoclonal antibody

The onset of autoimmune diseases is proposed to involve binding promiscuity of antibodies (Abs) and T-cells, an often reported yet poorly understood phenomenon. Here, we attempt to approach two questions: first, is binding promiscuity a general feature of monoclonal antibodies (mAbs) and second, what is the molecular basis for polyspecificity? To this end, the anti-cholera toxin peptide 3 (CTP3) mAb TE33 was investigated for polyspecific binding properties. Screening of phage display libraries identified two epitope-unrelated peptides that specifically bound TE33 with affinities similar to or 100-fold higher than the wild-type epitope. Substitutional analyses revealed distinct key residue patterns recognized by the antibody suggesting a unique binding mode for each peptide. A database query with one of the consensus motifs and a subsequent binding study uncovered 45 peptides (derived from heterologous proteins) that bound TE33. To better understand the structural basis of the observed polyspecificity we modeled the new cyclic epitope in complex with TE33. The interactions between this peptide and TE33 suggested by our model are substantially different from the interactions observed in the X-ray structure of the wild-type epitope complex. However, the overall binding conformation of the peptides is similar. Together, our results support the theory of a general polyspecific potential of mAbs.

Design and Synthesis of 5-Aryl-pyridone-carboxamides as Inhibitors of Anaplastic Lymphoma Kinase

Anaplastic lymphoma kinase (ALK) is a promising new target for therapy of certain cancers such as anaplastic large-cell lymphoma (ALCL) and inflammatory myofibroblastic tumor (IMT). We have identified a series of novel pyridones as kinase inhibitors of ALK by application of a stepwise process involving in vitro screening of a novel targeted library followed by iterative template modification based on medicinal chemistry insights and computational ranking of virtual libraries. Using this process, we discovered ALK-selective inhibitors with improved potency and selectivity. Herein the details of the design process and synthesis of these novel pyridones, along with their enzymatic and cell-based activity, are discussed.

On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors

Four of the most well-known, commercially available docking programs, FlexX, GOLD, GLIDE, and ICM, have been examined for their ligand-docking and virtual-screening capabilities. The relative performance of the programs in reproducing the native ligand conformation from starting SMILES strings for 164 high-resolution protein-ligand complexes is presented and compared. Applying only the native scoring functions, the latest versions of these four docking programs were also used to conduct virtual screening for 12 protein targets of therapeutic interest, involving both publicly available structures and AstraZeneca in-house structures. The capability of the four programs to correctly rank-order target-specific active compounds over alternative binders and nonbinders (decoys plus randomly selected compounds) and thereby enrich a small subset of a screening library is compared. Enrichments from the virtual-screening experiments are contrasted with those obtained with alternative 3D shape-matching and 2D similarity database-search methods.

Representing receptor flexibility in ligand docking through relevant normal modes

Inspired by the current representation of the ligand-receptor binding process, a normal-mode-based methodology is presented to incorporate receptor flexibility in ligand docking and virtual screening. However, the systematic representation of the deformation space grows geometrically with the number of modes, and furthermore, midscale loop rearrangements like those found in protein kinase binding pockets cannot be accounted for with the first lowest-frequency modes. We thus introduced a measure of relevance of normal modes on a given region of interest and showed that only very few modes in the low-frequency range are necessary and sufficient to describe loop flexibility in cAMP-dependent protein kinase. We used this approach to generate an ensemble of representative receptor backbone conformations by perturbing the structure along a combination of relevant modes. Each ensemble conformation is complexed with known non-native binders to optimize the position of the binding-pocket side chains through a full flexible docking procedure. The multiple receptor conformations thus obtained are used in a small-scale virtual screening using receptor ensemble docking. We evaluated this algorithm on holo and apo structures of cAMP-dependent protein kinase that exhibit backbone rearrangements on two independent loop regions close to the binding pocket. Docking accuracy is improved, since the ligands considered in the virtual screening docked within 1.5 A to at least one of the structures. The discrimination between binders and nonbinders is also enhanced, as shown by the improvement of the enrichment factor. This constitutes a new step toward the systematic integration of flexible ligand-flexible receptor docking tools in structure-based drug discovery.

Androgen Receptor Mutations Identified in Prostate Cancer and Androgen Insensitivity Syndrome Display Aberrant ART-27 Coactivator Function

The transcriptional activity of the androgen receptor (AR) is modulated by interactions with coregulatory molecules. It has been proposed that aberrant interactions between AR and its coregulators may contribute to diseases related to AR activity, such as prostate cancer and androgen insensitivity syndrome (AIS); however, evidence linking abnormal receptor-cofactor interactions to disease is scant. ART-27 is a recently identified AR N-terminal coactivator that is associated with AR-mediated growth inhibition. Here we analyze a number of naturally occurring AR mutations identified in prostate cancer and AIS for their ability to affect AR response to ART-27. Although the vast majority of AR mutations appeared capable of increased activation in response to ART-27, an AR mutation identified in prostate cancer (AR P340L) and AIS (AR E2K) show reduced transcriptional responses to ART-27, whereas their response to the p160 class of coactivators was not diminished. Relative to the wild-type receptor, less ART-27 protein associated with the AR E2K substitution, consistent with reduced transcriptional response. Surprisingly, more ART-27 associated with AR P340L, despite the fact that the mutation decreased transcriptional activation in response to ART-27. Our findings suggest that aberrant AR-coactivator association interferes with normal ART-27 coactivator function, resulting in suppression of AR activity, and may contribute to the pathogenesis of diseases related to alterations in AR activity, such as prostate cancer and AIS.