Combined Crystal Structure of a Type I Cohesin: MUTATION AND AFFINITY BINDING STUDIES REVEAL STRUCTURAL DETERMINANTS OF COHESIN-DOCKERIN SPECIFICITIES*

Cohesin-dockerin interactions orchestrate the assembly of one of nature''s most elaborate multienzyme complexes, the cellulosome. Cellulosomes are produced exclusively by anaerobic microbes and mediate highly efficient hydrolysis of plant structural polysaccharides, such as cellulose and hemicellulose. In the canonical model of cellulosome assembly, type I dockerin modules of the enzymes bind to reiterated type I cohesin modules of a primary scaffoldin. Each type I dockerin contains two highly conserved cohesin-binding sites, which confer quaternary flexibility to the multienzyme complex. The scaffoldin also bears a type II dockerin that anchors the entire complex to the cell surface by binding type II cohesins of anchoring scaffoldins. In Bacteroides cellulosolvens, however, the organization of the cohesin-dockerin types is reversed, whereby type II cohesin-dockerin pairs integrate the enzymes into the primary scaffoldin, and type I modules mediate cellulosome attachment to an anchoring scaffoldin. Here, we report the crystal structure of a type I cohesin from B. cellulosolvens anchoring scaffoldin ScaB to 1.84-Å resolution. The structure resembles other type I cohesins, and the putative dockerin-binding site, centered at β-strands 3, 5, and 6, is likely to be conserved in other B. cellulosolvens type I cohesins. Combined computational modeling, mutagenesis, and affinity-based binding studies revealed similar hydrogen-bonding networks between putative Ser/Asp recognition residues in the dockerin at positions 11/12 and 45/46, suggesting that a dual-binding mode is not exclusive to the integration of enzymes into primary cellulosomes but can also characterize polycellulosome assembly and cell-surface attachment. This general approach may provide valuable structural information of the cohesin-dockerin interface, in lieu of a definitive crystal structure.     

High‐accuracy modeling of antibody structures by a search for minimum‐energy recombination of backbone fragments

Current methods for antibody structure prediction rely on sequence homology to known structures. Although this strategy often yields accurate predictions, models can be stereo‐chemically strained. Here, we present a fully automated algorithm, called AbPredict, that disregards sequence homology, and instead uses a Monte Carlo search for low‐energy conformations built from backbone segments and rigid‐body orientations that appear in antibody molecular structures. We find cases where AbPredict selects accurate loop templates with sequence identity as low as 10%, whereas the template of highest sequence identity diverges substantially from the query's conformation. Accordingly, in several cases reported in the recent Antibody Modeling Assessment benchmark, AbPredict models were more accurate than those from any participant, and the models' stereo‐chemical quality was consistently high. Furthermore, in two blind cases provided to us by crystallographers prior to structure determination, the method achieved <1.5 Ångstrom overall backbone accuracy. Accurate modeling of unstrained antibody structures will enable design and engineering of improved binders for biomedical research directly from sequence. Proteins 2016; 85:30–38. © 2016 Wiley Periodicals, Inc.     

Assessing and enhancing foldability in designed proteins

Recent advances in protein‐design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particularly in design of functional proteins, is low and fundamental goals such as reliable de novo design of efficient enzymes remain beyond reach. Experimental analyses have consistently indicated that a major reason for design failure is inaccuracy and misfolding relative to the design conception. To address this challenge, we describe complementary methods to diagnose and ameliorate suboptimal regions in designed proteins: first, we develop a Rosetta atomistic computational mutation scanning approach to detect energetically suboptimal positions in designs (available on a web server https://pSUFER.weizmann.ac.il); second, we demonstrate that AlphaFold2 ab initio structure prediction flags regions that may misfold in designed enzymes and binders; and third, we focus FuncLib design calculations on suboptimal positions in a previously designed low‐efficiency enzyme, improving its catalytic efficiency by 330‐fold. Furthermore, applied to a de novo designed protein that exhibited limited stability, the same approach markedly improved stability and expressibility. Thus, foldability analysis and enhancement may dramatically increase the success rate in design of functional proteins.     

The structural context of disease-causing mutations in gap junctions

Gap junctions form intercellular channels that mediate metabolic and electrical signaling between neighboring cells in a tissue. Lack of an atomic resolution structure of the gap junction has made it difficult to identify interactions that stabilize its transmembrane domain. Using a recently computed model of this domain, which specifies the locations of each amino acid, we postulated the existence of several interactions and tested them experimentally. We introduced mutations within the transmembrane domain of the gap junction-forming protein connexin that were previously implicated in genetic diseases and that apparently destabilized the gap junction, as evidenced here by the absence of the protein from the sites of cell-cell apposition. The model structure helped identify positions on adjacent helices where second-site mutations restored membrane localization, revealing possible interactions between residue pairs. We thus identified two putative salt bridges and one pair involved in packing interactions in which one disease-causing mutation suppressed the effects of another. These results seem to reveal some of the physical forces that underlie the structural stability of the gap junction transmembrane domain and suggest that abrogation of such interactions bring about some of the effects of disease-causing mutations.     

Antimalarial compounds from Parinari capensis

The antimalarial activity of the raw petroleum ether and dichloromethane extracts of the stems of Parinari capensis (Chrysobalanceae) was determined. Phytochemical investigation of these extracts led to the isolation of three diterpene lactones that possess antimalarial activity with IC(50) values of 0.54, 0.67, and 1.57 microg/mL. Although their antimalarial activity is promising, the toxicity profiles of these diterpene lactones prevent further biological evaluation. They could however be used effectively as lead compounds in the synthesis of novel antimalarial agents.     

Co-evolving residues in membrane proteins

MOTIVATION: The analysis of co-evolving residues has been exhaustively evaluated for the prediction of intramolecular amino acid contacts in soluble proteins. Although a variety of different methods for the detection of these co-evolving residues have been developed, the fraction of correctly predicted contacts remained insufficient for their reliable application in the construction of structural models. Membrane proteins, which constitute between one-fourth and one-third of all proteins in an organism, were only considered in few individual case studies. RESULTS: We present the first general study of correlated mutations in alpha-helical membrane proteins. Using seven different prediction algorithms, we extracted co-evolving residues for 14 membrane proteins having a solved 3D structure. On average, distances between correlated pairs of residues lying on different transmembrane segments were found to be significantly smaller compared to a random prediction. Covariation of residues was frequently found in direct sequence neighborhood to helix-helix contacts. Based on the results obtained from individual prediction methods, we constructed a consensus prediction for every protein in the dataset that combines obtained correlations from different prediction algorithms and simultaneously removes likely false positives. Using this consensus prediction, 53% of all predicted residue pairs were found within one helix turn of an observed helix-helix contact. Based on the combination of co-evolving residues detected with the four best prediction algorithms, interacting helices could be predicted with a specificity of 83% and sensitivity of 42%. AVAILABILITY: http://webclu.bio.wzw.tum.de/helixcorr/     

Inhibition of monoamine oxidase B by selected benzimidazole and caffeine analogues

We have recently reported that a series of (E)-8-styrylcaffeines and (E)-2-styrylbenzimidazoles are moderate to very potent competitive inhibitors of monoamine oxidase B (MAO-B). The most potent member of the series was found to be (E)-8-(3-chlorostyryl)caffeine (CSC) with an enzyme-inhibitor dissociation constant (K(i) value) of 128 nM. In the present study, we have prepared additional caffeine and benzimidazole analogues in an attempt to identify compounds with improved MAO-B inhibition potency while still acting reversibly. The most potent inhibitor among the caffeine analogues was (E)-8-(3,4-dichlorostyryl)caffeine with a K(i) value of 36 nM, approximately 3.5 times more potent than CSC. The most potent inhibitor among the benzimidazole analogues was (E)-2-(4-trifluoromethylstyryl)-1-methylbenzimidazole with a K(i) value of 430 nM. An SAR analysis indicated that the potency of MAO-B inhibition by (E)-2-styryl-1-methylbenzimidazole analogues depended upon the Taft steric parameter (E(s)) of the substituents attached to C-4 of the styryl phenyl ring. Substituents with a large degree of steric hindrance appear to enhance inhibition potency. The proposal that potent MAO-B inhibition by (E)-8-styrylcaffeines and (E)-2-styrylbenzimidazoles can be explained by a mode of binding that involves traversing both the entrance and substrate cavities was supported by the finding that 1-methylbenzimidazole only weakly inhibited MAO-B with a K(i) value of 2084 microM. Without the styryl side chain, 1-methylbenzimidazole is not expected to be able to bind simultaneously to both the entrance and substrate cavities.