Laboratory of Molecular Biology

About: Laboratory of Molecular Biology is a facility organization based out in Cambridge, Cambridgeshire, United Kingdom. It is known for research contribution in the topics: Gene & RNA. The organization has 19395 authors who have published 24236 publications receiving 2101480 citations.

Protein 3D structure computed from evolutionary sequence variation.

Abstract: The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing. In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy. We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues., including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7–4.8 A Cα-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org). This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of protein structures, new strategies in protein and drug design, and the identification of functional genetic variants in normal and disease genomes.

Man-made cell-like compartments for molecular evolution

Abstract: Cellular compartmentalization is vital for the evolution of all living organisms. Cells keep together the genes, the RNAs and proteins that they encode, and the products of their activities, thus linking genotype to phenotype. We have reproduced this linkage in the test tube by transcribing and translating single genes in the aqueous compartments of water-in-oil emulsions. These compartments, with volumes close to those of bacteria, can be recruited to select genes encoding catalysts. A protein or RNA with a desired catalytic activity converts a substrate attached to the gene that encodes it to product. In other compartments, substrates attached to genes that do not encode catalysts remain unmodified. Subsequently, genes encoding catalysts are selectively enriched by virtue of their linkage to the product. We demonstrate the linkage of genotype to phenotype in man-made compartments using a model system. A selection for target-specific DNA methylation was based on the resistance of the product (methylated DNA) to restriction digestion. Genes encoding HaeIII methyltransferase were selected from a 10 7 -fold excess of genes encoding another enzyme.