Efflux Pumps Represent Possible Evolutionary Convergence onto the Beta Barrel Fold

Preprint now published in Structure doi: 10.1016/j.str.2018.06.007There are around 100 types of integral outer membrane proteins in each Gram negative bacteria. All of these proteins have the same fold—an up-down β-barrel. It has been suggested that all membrane β-barrels other than lysins are homologous. Here we suggest that β-barrels of efflux pumps have converged on this fold as well. By grouping structurally-solved outer membrane β-barrels (OMBBs) by sequence we find evidence that the membrane environment may have led to convergent evolution of the barrel fold. Specifically, the lack of sequence linkage to other barrels coupled with distinctive structural differences, such as differences in strand tilt and barrel radius, suggest that efflux pumps have evolutionarily converged on the barrel. Finally, we find a possible ancestor for the OMBB efflux pumps as they are related to periplasmic components of the same pumps

Michael Levitt

Assembling fragments from known protein structures is a widely used approach to construct structural models for new proteins. We describe an application of this idea to an important inverse kinematics problem in structural biology: the loop closure problem. We have developed an algorithm for generating the conformations of candidate loops that fit in a gap of given length in a protein structure framework. Our method proceeds by concatenating small fragments of protein chosen from small libraries of representative fragments. Our approach has the advantages of ab initio methods since we are able to enumerate all candidate loops in the discrete approximation of the conformational space accessible to the loop, as well as the advantages of database search approach since the use of fragments of known protein structures guarantees that the backbone conformations are physically reasonable. We test our approach on a set o

Faster algorithms for optimal multiple sequence alignment based on pairwise comparisons

Abstract—Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal alignment, based on dynamic programming, increases exponentially with the number of input sequences. Hence, many heuristics were suggested for the problem. We consider a version of the MSA problem where the goal is to find an optimal alignment in which matches are restricted to positions in predefined matching segments. We present several techniques for making the dynamic programming algorithm more efficient, while still finding an optimal solution under these restrictions. We prove that it suffices to find an optimal alignment of the predefined sequence segments, rather than single letters, thereby reducing the input size and thus improving the running time. We also identify “shortcuts ” that expedite the dynamic programming scheme. Empirical study shows that, taken together, these observations lead to an improved running time over the basic dynamic programming algorithm by 4 to 12 orders of magnitude, while still obtaining an optimal solution. Under the additional assumption that matches between segments are transitive, we further improve the running time for finding the optimal solution by restricting the search space of the dynamic programming algorithm. Index Terms—Multiple Sequence Alignment, algorithms, dynamic programming, shortest path. Ç

Michael Levitt

Assembling fragments from known protein structures is a widely used approach to construct structural models for new proteins. We describe an application of this idea to an important inverse kinematics problem in structural biology: the loop closure problem. We have developed an algorithm for generating the conformations of candidate loops that fit in a gap of given length in a protein structure framework. Our method proceeds by concatenating small fragments of protein chosen from small libraries of representative fragments. Our approach has the advantages of ab initio methods since we are able to enumerate all candidate loops in the discrete approximation of the conformational space accessible to the loop, as well as the advantages of database search approach since the use of fragments of known protein structures guarantees that the backbone conformations are physically reasonable. We test our approach on a set of 427 loops, varying in length from four residues to 14 residues. The quality of the candidate loops is evaluated in terms of global coordinate root mean square (cRMS). The top predictions vary between 0.3 and 4.2 Å for four-residue loops and between 1.5 and 3.1 Å for 14-residue loops, respectively. KEY WORDS—inverse kinematic problem, loop closure, protein structure, protein fragment librarie

Small libraries of protein fragments model native protein structures accurately

The three-dimensional structure of proteins has been a subject of intense study for several decades. A common way to simplify these complex structures is to consider restrictions on the local mainchai

Faster Algorithms for Optimal Multiple Sequence Alignment based on Pairwise Comparisons ∗

Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal alignment, based on dynamic programming, increases exponentially with the number of input sequences. Hence, several heuristics were suggested for the problem. We present several techniques for making the dynamic programming algorithm more efficient, while still finding an optimal solution. We solve the following version of the MSA problem: In a preprocessing stage pairwise alignments are found for every pair of sequences. The goal is to find an optimal alignment in which matches are restricted to positions that were matched at the preprocessing stage. We prove that it suffices to find an optimal alignment of sequence segments, rather than single letters, thereby reducing the input size and thus improving the running time. We also identify “shortcuts” that expedite the dynamic programming scheme. Under some more assumptions, namely, that matches between segments are transitive, we show how to further improve the running time for finding the optimal solution by restricting the search space of the dynamic programming algorithm. 1