A fold-recognition approach to loop modeling

Protein Loop Modeling Using AlphaFold2

The functions of proteins are largely determined by their three-dimensional (3D) structures. Loop modeling tries to predict the conformation of a relatively short stretch of protein backbone and sidechain. It is a difficult problem due to conformational variability. Recently, AlphaFold2 has achieved outstanding results in 3-D protein structure prediction and is expected to perform well on loop modeling. In this paper, we investigate the performances of AlphaFold2 variants on popular loop modeling benchmark datasets and propose an efficient protocol of using AlphaFold2 for loop modeling, called IAFLoop. To predict the structure of a loop region, IAFLoop gives a moderately extended segment of the target loop region as input to AlphaFold2, runs a fast version of AlphaFold2 using a reduced database without ensembling, and uses RMSD based consensus scores to select the final output models. Our experimental results on benchmark datasets show that IAFLoop generated highly accurate loop models. It achieves comparable performance to the original application of AlphaFold2 in terms of RMSD error, and achieving much better results on some targets, while only using half of the time. Compared to the best previous methods, IAFLoop reduces the RMSD error by almost half on the 8-residual loop dataset, and more than 70% on the 12-residual loop dataset.

Large loop conformation sampling using the activation relaxation technique, ART-nouveau method

We present an adaptation of the ART-nouveau energy surface sampling method to the problem of loop structure prediction. This method, previously used to study protein folding pathways and peptide aggregation, is well suited to the problem of sampling the conformation space of large loops by targeting probable folding pathways instead of sampling exhaustively that space. The number of sampled conformations needed by ART nouveau to find the global energy minimum for a loop was found to scale linearly with the sequence length of the loop for loops between 8 and about 20 amino acids. Considering the linear scaling dependence of the computation cost on the loop sequence length for sampling new conformations, we estimate the total computational cost of sampling larger loops to scale quadratically compared to the exponential scaling of exhaustive search methods.

Detection and characterization of a sialoglycosylated bacterial ABC-type phosphate transporter protein from patients with visceral leishmaniasis

We report the discovery and characterization of a glycosylated bacterial ABC-type phosphate transporter isolated from the peripheral blood mononuclear cell (PBMC) fraction of patients with visceral leishmaniasis (VL). Three disease-associated 9-O-acetylated sialoglycoproteins (9-O-AcSGPs) of 19, 56 and 65 kDa, respectively, had been identified and their purity, apparent mass and pI established by SDS-PAGE and isoelectric focusing. Western blot analyses showed that the 9-O-acetylated sialic acid is linked via alpha2-->6 linkage to a subterminal N-acetylgalactosamine. For the 56 kDa protein, N- as well as O-glycosylations were demonstrated by specific glycosidase treatment and found to account for more than 9 kDa of the protein mass. The presence of sialic acids was further confirmed through thin layer chromatography, fluorimetric HPLC and electrospray ionization-mass spectrometry. The protein was identified by mass spectrometry and de novo sequencing of five tryptic fragments as a periplasmic ABC-type phosphate transporter of Pseudomonas aeruginosa. The amino acid sequences of the assigned peptides had 83-100% identity with the NCBI entry for a Pseudomonas transporter protein. Based on the recently reported X-ray structure of a human phosphate-binding protein, we predicted a 3D structural model for the 56 kDa protein using homology and threading methods. The most probable N- and O-glycosylation sites were identified by combinations of sequence motif-searching bioinformatics tools, solvent accessibility calculations, structural environment analyses and mass spectrometric data. This is the first reported glycosylation as well as sialylation of the periplasmic component of an ABC-type phosphate transporter protein and of one of few identified bacterial glycoproteins.

A molecular basis for agonist and antagonist actions at GABA(C) receptors

We modelled the N-terminal ligand-binding domain of the rho1 GABA(C) receptor based on the Lymnaea stagnalis acetylcholine-binding protein (L-AChBP) crystal structure using comparative modelling and validated using flexible docking guided by known mutagenesis studies. A range of known rho1 GABA(C) receptor ligands comprising seven full agonists, 10 partial agonists, 43 antagonists and 12 inactive molecules were used to evaluate and validate the models. Of the 50 models identified, six models that allowed flexible ligand docking in accordance with the experimental data were selected and used to study detailed receptor-ligand interactions. The most refined model to accommodate all known active ligands featured a cavity comprising of a volume of 488 A(3). A detailed analysis of the interaction between the rho1 GABA(C) receptor model and the docked ligands revealed possible H-bonds and cation-pi interactions between the different ligands and binding site residues. Based on quantum mechanical/molecular mechanical (QM/MM) calculations, the model showed distinctive conformations of loop C that provided a molecular basis for agonist and antagonist actions. Agonists elicit loop C closure, while a more open loop C was observed upon antagonist binding. The model differentiates the role for key residues known to be involved in either binding and/or gating.