Biomedical subjects

Buyong Ma

Publications and source records attributed to Buyong Ma.

At least 37 records · Page 2Linked to original sources

PubMed2004

Release factors eRF1 and RF2: a universal mechanism controls the large conformational changes.

Class I release factors 1 and 2 (RF1 and RF2) terminate protein synthesis by recognizing stop codons on the mRNA via their conserved amino acid motifs (NIKS in eRF1 and SPF in RF2) and by the conserved tripeptide (GGQ) interactions with the ribosomal peptidyltransferase center. Crystal structures of eRF1 and RF2 do not fit their ribosomal binding pocket (approximately 73 angstroms). Cryoelectron microscopy indicates large conformational changes in the ribosome-bound RF2. Here, we investigate the conformational dynamics of the eRF1 and RF2 using molecular dynamics simulation, structural alignment, and electrostatic analysis of domain interactions. We show that relaxed eRF1 has a shape remarkably similar to the ribosome-bound RF2 observed by cryoelectron microscopy. The similarity between the two release factors is as good as between elongation factor G and elongation factor Tu-guanosine-5'(beta,gamma-imido)triphosphate-tRNA. Further, the conformational transitions and dynamics of eRF1 and RF2 between the free and ribosome-bound states are most likely controlled by protonation of conserved histidines. For eRF1, the distance between the NIKS and GGQ motifs shrinks from 97.5 angstroms in the crystal to 70-80 angstroms. For RF2, the separation between SPF and GGQ elongates from 32 angstroms in the crystal to 50 angstroms. Coulombic interaction strongly favors the open conformation of eRF1; however, solvation and histidine protonation modulate the domain interactions, making the closed conformation of eRF1 more accessible. Thus, RF1 and RF2 function like molecular machines, most likely fueled by histidine protonation. The unified conformational control and the shapes of eRF1 and RF2 support the proposition that the termination of protein synthesis involves similar mechanisms across species.

Amino Acid Motifs↗

PubMed2004

Characterization of the conformational state and flexibility of HIV-1 glycoprotein gp120 core domain.

gp120 is key to the human immunodeficiency virus type 1 viral cell entry. Knowledge of the detailed conformational states of gp120 is crucial to intervention, yet the unbound form is still resistant to structural characterization probably because of its flexibility. Toward this goal, we performed molecular dynamics simulations on the wild type gp120 core domain extracted from its ternary crystal structure and on a modeled mutant, S375W, that experimentally has a significantly different phenotype from the wild type. Although the mutant retained a bound-like conformation, the wild type drifted to a different conformational state. The wild type beta strands 2 and 3 of the bridging sheet were very mobile and partially unfolded, and the organization among the inner and outer domains and beta strands 20 and 21 of the bridging sheet, near the mutation site, was more open than in the bound form, although the overall structure was maintained. These differences were apparently a result of the strengthening of the hydrophobic core in the mutant. This stabilization further explains the experimentally significantly different thermodynamic properties between the wild type and the mutant. Taken together, our results suggest that the free form, although different from the bound state, shares many of the bound structural features. The observed loss of freedom near the binding site, rather than the previously hypothesized more dramatic conformational transition from the unbound to the bound state, appears to be the major contributor to the large entropy cost for the CD4 binding to the wild type.

Amino Acid Motifs↗

PubMed2004

Insights into amyloid structural formation and assembly through computational approaches.

Amyloids are long, insoluble ordered fibers. Due to their insolubility, to date the determination of an amyloid structure with an atomic scale resolution has proven to be a difficult task. Under such circumstances, computational approaches are a preferred option, providing the means to build likely models, test their stabilities and figure out the chemistry of their prevailing interactions. Computational models can be validated by targeted experiments, such as introducing mutations and testing for amyloid formation. Computations further provide vehicles for the comprehension of the mechanisms of amyloid seed formation and oligomer toxicity. Nevertheless, computations face an immense hurdle, the outcome of the time scales involved in amyloid formation and the immense sizes of the systems. In an attempt to overcome these, we adopt a strategy that encompasses (1) bioinformatics studies of native proteins containing beta-sheet structures; (2) simulations of shorter peptides; and finally (3) construction of potential oligomeric models and tests of their stabilities. The results are correlated with experimental data where available. Here, we describe the computational methods in simple terms and present an overview of the results. The systems derive from amyloidogenic, disease-related proteins, including gelsolin, beta2-microglobulin, and peptides derived from the prion, Alzheimer's Abeta, IAPP and human calcitonin. Ultimately, obtaining molecular structures should facilitate efforts to therapy and drug design.

Amyloid↗

PubMed2004

Side chain interactions determine the amyloid organization: a single layer beta-sheet molecular structure of the calcitonin peptide segment 15-19.

In this paper we present a detailed atomic model for a protofilament, the most basic organization level, of the amyloid fibre formed by the peptide DFNKF. This pentapeptide is a segment derived from the human calcitonin, a natural amyloidogenic protein. Our model, which represents the outcome of extensive explicit solvent molecular dynamics (MD) simulations of different strand/sheet organizations, is a single beta-sheet filament largely without a hydrophobic core. Nevertheless, this structure is capable of reproducing the main features of the characteristic amyloid fibril organization and provides clues to the molecular basis of its experimental aggregation behaviour. Our results show that the side chains' chemical diversity induces the formation of a complex network of interactions that finally determine the microscopic arrangement of the strands at the protofilament level. This network of interactions, consisting of both side chain-side chain and backbone-side chain interactions, confers on the final single beta-sheet arrangement an unexpected stability, both by enhancing the association of related chemical groups and, at the same time, by shielding the hydrophobic segments from the polar solvent. The chemical physical characterization of this protofilament provides hints to the possible thermodynamical basis of the supra molecular organization that allows the formation of the filaments by lateral association of the preformed protofibrils. Its regular, highly polarized structure shows how other protofilaments can assemble. In terms of structural biology, our results clearly indicate that an amyloid organization implies a degree of complexity far beyond a simple nonspecific association of peptide strands via amide hydrogen bonds.

Amino Acid Sequence↗

PubMed2004

From computational quantum chemistry to computational biology: experiments and computations are (full) partners.

Computations are being integrated into biological research at an increasingly fast pace. This has not only changed the way in which biological information is managed; it has also changed the way in which experiments are planned in order to obtain information from nature. Can experiments and computations be full partners? Computational chemistry has expanded over the years, proceeding from computations of a hydrogen molecule toward the challenging goal of systems biology, which attempts to handle the entire living cell. Applying theories from ab initio quantum mechanics to simplified models, the virtual worlds explored by computations provide replicas of real-world phenomena. At the same time, the virtual worlds can affect our perception of the real world. Computational biology targets a world of complex organization, for which a unified theory is unlikely to exist. A computational biology model, even if it has a clear physical or chemical basis, may not reduce to physics and chemistry. At the molecular level, computational biology and experimental biology have already been partners, mutually benefiting from each other. For the perception to become reality, computation and experiment should be united as full partners in biological research.

Chemical Phenomena↗

PubMed2004

In silico protein design by combinatorial assembly of protein building blocks.

Utilizing concepts of protein building blocks, we propose a de novo computational algorithm that is similar to combinatorial shuffling experiments. Our goal is to engineer new naturally occurring folds with low homology to existing proteins. A selected protein is first partitioned into its building blocks based on their compactness, degree of isolation from the rest of the structure, and hydrophobicity. Next, the protein building blocks are substituted by fragments taken from other proteins with overall low sequence identity, but with a similar hydrophobic/hydrophilic pattern and a high structural similarity. These criteria ensure that the designed protein has a similar fold, low sequence identity, and a good hydrophobic core compared with its native counterpart. Here, we have selected two proteins for engineering, protein G B1 domain and ubiquitin. The two engineered proteins share approximately 20% and approximately 25% amino acid sequence identities with their native counterparts, respectively. The stabilities of the engineered proteins are tested by explicit water molecular dynamics simulations. The algorithm implements a strategy of designing a protein using relatively stable fragments, with a high population time. Here, we have selected the fragments by searching for local minima along the polypeptide chain using the protein building block model. Such an approach provides a new method for engineering new proteins with similar folds and low homology.

Amino Acid Sequence↗

PubMed2004

The stability and dynamics of the human calcitonin amyloid peptide DFNKF.

The stability and dynamics of the human calcitonin-derived peptide DFNKF (hCT(15-19)) are studied using molecular dynamics (MD) simulations. Experimentally, this peptide is highly amyloidogenic and forms fibrils similar to the full length calcitonin. Previous comparative MD studies have found that the parallel beta-stranded sheet is a stable organization of the DFNKF protofibril. Here, we probe the stability and dynamics of the small parallel DFNKF oligomers. The results show that even small DFNKF oligomers, such as trimers and tetramers, are stable for a sufficient time in the MD simulations, indicating that the crucial nucleus seed size for amyloid formation can be quite small. The simulations also show that the stability of DFNKF oligomers increases with their sizes. The small but stable seed may reflect the experimental rapid formation of the DFNKF fibrils. Further, a noncooperative process of parallel beta-sheet formation from the out-of-register trimer is observed in the simulations. In general, the residues of DFNKF peptides near the N-/C-termini are more flexible, whereas the interior residues are more stable. Simulations of mutants and capped peptides show that both interstrand hydrophobic and electrostatic interactions play important roles in stabilizing the DFNKF parallel oligomers. This study provides insights into amyloid formation.

Amyloid↗

PubMed2003

Triggering loops and enzyme function: identification of loops that trigger and modulate movements.

Enzyme function often involves a conformational change. There is a general agreement that loops play a vital role in correctly positioning the catalytically important residues. Nevertheless, predicting the functional loops and most importantly their role in enzyme function remains a difficult task. A major reason for this difficulty is that loops that undergo conformational change are frequently not well conserved in their primary sequence. beta1,4-Galactosyltransferase is one such enzyme. There, the amino acid sequence of a long loop that undergoes a large conformational change upon substrate binding is not well conserved. Our molecular dynamics simulations show that the large conformational change in the long loop is brought about by a second, interacting loop. Interestingly, while the structural change of the second loop is much smaller than that of the long loop, its sequence (particularly glycine residues) is highly conserved. We further examine the generality of the proposition that there are loops that trigger movements but nevertheless show little or no structural changes in crystals. We focus on two other enzymes, enolase and lipase. We chose these enzymes, since they too undergo conformational change upon ligand binding, however, they have different folds and different functions. Through multiple sets of simulations we show that the conformational change of the functional loop(s) is brought about through communication of flexibility by triggering loops that have several glycine residues. We further propose that similar to the conservation of common favorable fold types and structural motifs, evolution has also conserved common "skillful" mechanisms. Mechanisms may be conserved across different folds, sequences and functions, with adaptation to specific enzymatic roles.

Apoenzymes↗

PubMed2003

Protein-protein interactions: structurally conserved residues distinguish between binding sites and exposed protein surfaces.

Polar residue hot spots have been observed at protein-protein binding sites. Here we show that hot spots occur predominantly at the interfaces of macromolecular complexes, distinguishing binding sites from the remainder of the surface. Consequently, hot spots can be used to define binding epitopes. We further show a correspondence between energy hot spots and structurally conserved residues. The number of structurally conserved residues, particularly of high ranking energy hot spots, increases with the binding site contact size. This finding may suggest that effectively dispersing hot spots within a large contact area, rather than compactly clustering them, may be a strategy to sustain essential key interactions while still allowing certain protein flexibility at the interface. Thus, most conserved polar residues at the binding interfaces confer rigidity to minimize the entropic cost on binding, whereas surrounding residues form a flexible cushion. Furthermore, our finding that similar residue hot spots occur across different protein families suggests that affinity and specificity are not necessarily coupled: higher affinity does not directly imply greater specificity. Conservation of Trp on the protein surface indicates a highly likely binding site. To a lesser extent, conservation of Phe and Met also imply a binding site. For all three residues, there is a significant conservation in binding sites, whereas there is no conservation on the exposed surface. A hybrid strategy, mapping sequence alignment onto a single structure illustrates the possibility of binding site identification around these three residues.

Amino Acid Sequence↗

PubMed2003

Interdependence of backbone flexibility, residue conservation, and enzyme function: a case study on beta1,4-galactosyltransferase-I.

Beta1,4-galactosyltransferase-I (beta4Gal-T1) catalyzes the transfer of a galactose from UDP-galactose to N-acetylglucosamine. A recent crystal structure determination of the substrate-bound enzyme reveals a large conformational change, which creates binding sites for the oligosaccharide and alpha-lactalbumin, when compared to the ligand-free structure. The conformational changes take place in a 21-residue-long loop (I345-H365) and in a smaller loop containing a tryptophan residue (W314) flanked by glycines (Y311-G316; Trp loop). A series of molecular dynamics simulations carried out with an implicit solvent model and with explicit water successfully identify flexibility in the two loops and in another interacting loop. These observations are confirmed by limited proteolysis experiments that reveal an intrinsic flexibility of the long loop. The multiple simulation runs starting with the substrate-free structure show that the long loop moves toward its conformation in the ligand-bound structure; however, it gets stabilized in an intermediate position. The Trp loop moves in the opposite direction to that of the long loop, making contacts with residues in the long loop. Remarkably, when the Trp loop is restrained in its starting conformation, no large conformational change takes place in the long loop, indicating residue communication of flexibility. Sequence and structural analysis of the beta4Gal-T1 family with 37 known sequences reveals that in contrast to the unconserved long loop, which undergoes a much larger conformational change, the Trp loop including the glycines is highly conserved. These observations lead us to propose a new functional mechanism that may be conserved by evolution to perform a variety of functions.

Amino Acid Sequence↗

PubMed2003

Binding interactions between the core central domain of 16S rRNA and the ribosomal protein S15 determined by molecular dynamics simulations.

The goal of the current study is to utilize molecular dynamic (MD) simulations to investigate the dynamic behavior of 16S rRNA in the presence and absence of S15 and to identify the binding interactions between these two molecules. The simulations show that: (i) 16S rRNA remains in a highly folded structure when it is bound to S15; (ii) in the absence of S15, 16S rRNA significantly alters its conformation and transiently forms conformations that are similar to the bound structure that make it available for binding with S15; (iii) the unbound rRNA spends the majority of its time in extended conformations. The formation of the extended conformations is a result of the molecule reaching a lower electrostatic energy and the formation of the highly folded, crystal-like conformation is a result of achieving a lower solvation energy. In addition, our MD simulations show that 16S rRNA and S15 bind across the major groove of helix 22 (H22) via electrostatic interactions. The negatively charged phosphate groups of G658, U740, G741 and G742 bind to the positively charged S15 residues Lys7, Arg34 and Arg37. The current study provides a dynamic view of the binding of 16S rRNA with S15.

Base Sequence↗

PubMed2003

Short peptide amyloid organization: stabilities and conformations of the islet amyloid peptide NFGAIL.

Experimentally, short peptides have been shown to form amyloids similar to those of their parent proteins. Consequently, they present useful systems for studies of amyloid conformation. Here we simulate extensively the NFGAIL peptide, derived from the human islet amyloid polypeptide (residues 22-27). We simulate different possible strand/sheet organizations, from dimers to nonamers. Our simulations indicate that the most stable conformation is an antiparallel strand orientation within the sheets and parallel between sheets. Consistent with the alanine mutagenesis, we find that the driving force is the hydrophobic effect. Whereas the NFGAIL forms stable oligomers, the NAGAIL oligomer is unstable, and disintegrates very quickly after the beginning of the simulation. The simulations further identify a minimal seed size. Combined with our previous simulations of the prion-derived AGAAAAGA peptide, AAAAAAAA, and the Alzheimer Abeta fragments 16-22, 24-36, 16-35, and 10-35, and the solid-state NMR data for Abeta fragments 16-22, 10-35, and 1-40, some insight into the length and the sequence matching effects may be obtained.

Amino Acid Sequence↗

PubMed2003

Molecular dynamics simulations of the unfolding of beta(2)-microglobulin and its variants.

In this study, we examined the unfolding processes of native beta(2)-microglobulin and two related variants, one with an N-terminal hexapeptide deletion DeltaN6 and another with Lys57-Asp58 cleavage, by high-temperature molecular dynamics simulations. Three simulation models were used, molecular dynamics (MD) simulations with explicit water solvation, MD simulations with the CHARMM EEF1 force field and Langevin dynamics with the CHARMM EEF1 force field. Our simulations reproduce many of the experimentally observed structural changes. The most striking agreement is in the beta-strands to alpha-helix transition. In our simulations, strands beta(3), beta(4) and beta(5) consistently change to alpha-helix, whereas beta(8) changes to an alpha-helix only briefly. Through comparisons of the conformational behavior of the native, the DeltaN6 and the Lys-cut beta(2)-m, using the three simulation methods, we identified the consensus conformational changes that differentiate between the native beta(2)-m and its two variants. We found that the main effect of the removal of the N-terminal hexapeptide is to increase the separation between strands beta(2) and beta(6) and to facilitate the beta to alpha transition. On the other hand, the lysine cleavage only increases the flexibility of strand beta(5) and does not affect the interactions between strands beta(2) and beta(6). These conformational changes may relate to polymerization tendencies of these variants.

Amyloidosis↗

PubMed2003

Energy landscape and dynamics of the beta-hairpin G peptide and its isomers: Topology and sequences.

We have investigated free energy landscape [MM/PBSA + normal modes entropy] of permutations in the G peptide (41-56) from the protein G B1 domain by studying six isomers corresponding to moving the hydrophobic cluster along the beta-strands (toward the turn: T1, AGEWTYDDKTFTVTET; T2, GEDTWDYATFTVTKTE; T3, GEDDWTYATFTVTKTE; toward the end: E1, WTYDDAGETKTFTVT; E2, WEYTGDDATKTETFTV; E3, WTYEGDDATKTETFTV). The free energy terms include molecular mechanics energy, Poisson-Boltzmann electrostatic solvation energy, surface area solvation energy, and conformational entropy estimated by using normal mode analysis. From the wild type to T1, then T3, and finally T2, we see a progressively changing energy landscape, toward a less stable beta-hairpin structure. Moving the hydrophobic cluster outside toward the end region causes a greater change in the energy landscape. alpha-Helical instead of a beta-hairpin structure was the most stable form for the E2 isomer. However, no matter how much the sequence changes, for all variants studied, ideal "native" beta-hairpin topologies remain as minima (regardless of whether global or local) in the energy landscape. In general, we find that the energy landscape is dependent on the hydrophobic cluster topology and on the sequence. Our present study indicates that the key is the relative conformational energies of the different conformations. Changes in the sequence strongly modulate the relative stabilities of topologically similar regions in the energy landscape, rather than redefine the topology space. This finding is consistent with a population redistribution in the process of protein folding. The limited variation of topological space, compared with the number of possible sequence changes, may relate to the observation that the number of known protein folds are far less than the sequential allowance.

Amino Acid Sequence↗

PubMed2002

Stabilities and conformations of Alzheimer's beta -amyloid peptide oligomers (Abeta 16-22, Abeta 16-35, and Abeta 10-35): Sequence effects.

Previously, we have studied the minimal oligomer size of an aggregate amyloid seed and the mechanism of seed growth with a multilayer beta-sheet model. Under high temperature simulation conditions, our approach can test the stability of possible amyloid forms. Here, we report our study of oligomers of Alzheimer's amyloid beta-peptide (Abeta) fragments 16-22, 16-35, and 10-35 (abbreviated Abeta(16-22), Abeta(16-35), and Abeta(10-35), respectively). Our simulations indicate that an antiparallel beta-sheet orientation is the most stable for the Abeta(16-22), in agreement with a solid state NMR-based model [Balbach, J. J., Ishii, Y., Antzutkin, O. N., Leapman, R. D., Rizzo, N. W., et al. (2000) Biochemistry 39, 13748-13759]. A model with twenty-four Abeta(16-22) strands indicates a highly twisted fibril. Whereas the short Abeta(16-22) and Abeta(24-36) may exist in fully extended form, the linear parallel beta-sheets for Abeta(16-35) appear impossible, mainly because of the polar region in the middle of the 16-35 sequence. However, a bent double-layered hairpin-like structure (called hook) with the polar region at the turn forms parallel beta-sheets with higher stability. An intra-strand salt-bridge (D23-K28) stabilizes the bent hairpin-like hook structure. The bent double-beta-sheet model for the Abeta(10-35) similarly offers oligomer stability.

Alzheimer Disease↗

PubMed2002

Principles of docking: An overview of search algorithms and a guide to scoring functions.

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.

Algorithms↗

PubMed2002

Thermal unfolding molecular dynamics simulation of Escherichia coli dihydrofolate reductase: thermal stability of protein domains and unfolding pathway.

Temperature induced unfolding of Escherichia coli dihydrofolate reductase was carried out by using molecular dynamic simulations. The simulations show that the unfolding generally involves an initial end-to-end collapse of the adenine binding domain into partially extended loops, followed by a gradual breakdown of the remaining beta sheet core structure. The core, which consists of beta strands 5-7, was observed to be the most resistant to thermal unfolding. This region, which is made up of part of the N terminus domain and part of the large domain of the E. coli dihydrofolate reductase, may constitute the nucleation site for protein folding and may be important for the eventual formation of both domains. The unfolding of different domains at different stages of the unfolding process suggests that protein domains vary in stability and that the rate at which they unfold can affect the overall outcome of the unfolding pathway. This observation is compared with the recently proposed hierarchical folding model. Finally, the results of the simulation were found to be consistent with a previous experimental study (Frieden, Proc Natl Acad Sci USA 1990;87:4413-4416) which showed that the folding process of E. coli dihydrofolate reductase involves sequential formation of the substrate binding sites.

Computer Simulation↗

PubMed2002

Multiple diverse ligands binding at a single protein site: a matter of pre-existing populations.

Here, we comment on the steadily increasing body of data showing that proteins with specificity actually bind ligands of diverse shapes, sizes, and composition. Such a phenomenon is not surprising when one considers that binding is a dynamic process with populations in equilibrium and that the shape of the binding site is strongly influenced by the molecular partner. It derives implicitly from the concept of populations. All proteins, specific and nonspecific, exist in ensembles of substates. If the library of ligands in solution is large enough, favorably matching ligands with altered shapes and sizes can be expected to bind, with a redistribution of the protein populations. Point mutations at spatially distant sites may exert large conformational rearrangements and hinge effects, consistent with mutations away from the binding site leading to population shifts and (cross-)drug resistance. A similar effect is observed in protein superfamilies, in which different sequences with similar topologies display similar large-scale dynamic motions. The hinges are frequently at analogous sites, yet with different substrate specificity. Similar topologies yield similar conformational isomers, although with different distributions of population times, owing to the change in the conditions, that is, the change in the sequences. In turn, different distributions relate to binding of different sizes and shapes. Hence, the binding site shape and size are defined by the ligand. They are not independent entities of fixed proportions and cannot be analyzed independently of the binding partner. Such a proposition derives from viewing proteins as dynamic distributions, presenting to the incoming ligands a range of binding site shapes. It illustrates how presumably specific binding molecules can bind multiple ligands. In terms of drug design, the ability of a single receptor to recognize many dissimilar ligands shows the need to consider more diverse molecules. It provides a rationale for higher affinity inhibitors that are not derived from substrates at their transition states and indicates flexible docking schemes.

Binding Sites↗