Internal organization of large protein families: relationship between the sequence, structure, and function-based clustering

Recent Developments and Applications of Biocatalytic and Chemoenzymatic Synthesis for the Generation of Diverse Classes of Drugs

Biocatalytic and chemoenzymatic biosynthesis are powerful methods of organic chemistry that use enzymes to execute selective reactions and allow the efficient production of organic compounds. The advantages of these approaches include high selectivity, mild reaction conditions, and the ability to work with complex substrates. The utilization of chemoenzymatic techniques for the synthesis of complicated compounds has lately increased dramatically in the area of organic chemistry. Biocatalytic technologies and modern synthetic methods are utilized synergistically in a multi-step approach to a target molecule under this paradigm. Chemoenzymatic techniques are promising for simplifying access to essential bioactive compounds because of the remarkable regio- and stereoselectivity of enzymatic transformations and the reaction diversity of modern organic chemistry. Enzyme kits may include ready-to-use, reproducible biocatalysts. Its use opens up new avenues for the synthesis of active therapeutic compounds and aids in drug development by synthesizing active components to construct scaffolds in a targeted and preparative manner. This study summarizes current breakthroughs as well as notable instances of biocatalytic and chemoenzymatic synthesis. To assist organic chemists in the use of enzymes for synthetic applications, it also provides some basic guidelines for selecting the most appropriate enzyme for a targeted reaction while keeping aspects like cofactor requirement, solvent tolerance, use of whole cell or isolated enzymes, and commercial availability in mind.

Enabling Broader Adoption of Biocatalysis in Organic Chemistry

Biocatalysis is becoming an increasingly impactful method in contemporary synthetic chemistry for target molecule synthesis. The selectivity imparted by enzymes has been leveraged to complete previously intractable chemical transformations and improve synthetic routes toward complex molecules. However, the implementation of biocatalysis in mainstream organic chemistry has been gradual to this point. This is partly due to a set of historical and technological barriers that have prevented chemists from using biocatalysis as a synthetic tool with utility that parallels alternative modes of catalysis. In this Perspective, we discuss these barriers and how they have hindered the adoption of enzyme catalysts into synthetic strategies. We also summarize tools and resources that already enable organic chemists to use biocatalysts. Furthermore, we discuss ways to further lower the barriers for the adoption of biocatalysis by the broader synthetic organic chemistry community through the dissemination of resources, demystifying biocatalytic reactions, and increasing collaboration across the field.

State-of-the-Art Biocatalysis

The use of enzyme-mediated reactions has transcended ancient food production to the laboratory synthesis of complex molecules. This evolution has been accelerated by developments in sequencing and DNA synthesis technology, bioinformatic and protein engineering tools, and the increasingly interdisciplinary nature of scientific research. Biocatalysis has become an indispensable tool applied in academic and industrial spheres, enabling synthetic strategies that leverage the exquisite selectivity of enzymes to access target molecules. In this Outlook, we outline the technological advances that have led to the field's current state. Integration of biocatalysis into mainstream synthetic chemistry hinges on increased access to well-characterized enzymes and the permeation of biocatalysis into retrosynthetic logic. Ultimately, we anticipate that biocatalysis is poised to enable the synthesis of increasingly complex molecules at new levels of efficiency and throughput.

Basis for substrate recognition and distinction by matrix metalloproteinases

Genomic sequencing and structural genomics produced a vast amount of sequence and structural data, creating an opportunity for structure-function analysis in silico [Radivojac P, et al. (2013) Nat Methods 10(3):221-227]. Unfortunately, only a few large experimental datasets exist to serve as benchmarks for function-related predictions. Furthermore, currently there are no reliable means to predict the extent of functional similarity among proteins. Here, we quantify structure-function relationships among three phylogenetic branches of the matrix metalloproteinase (MMP) family by comparing their cleavage efficiencies toward an extended set of phage peptide substrates that were selected from ∼ 64 million peptide sequences (i.e., a large unbiased representation of substrate space). The observed second-order rate constants [k(obs)] across the substrate space provide a distance measure of functional similarity among the MMPs. These functional distances directly correlate with MMP phylogenetic distance. There is also a remarkable and near-perfect correlation between the MMP substrate preference and sequence identity of 50-57 discontinuous residues surrounding the catalytic groove. We conclude that these residues represent the specificity-determining positions (SDPs) that allowed for the expansion of MMP proteolytic function during evolution. A transmutation of only a few selected SDPs proximal to the bound substrate peptide, and contributing the most to selectivity among the MMPs, is sufficient to enact a global change in the substrate preference of one MMP to that of another, indicating the potential for the rational and focused redesign of cleavage specificity in MMPs.

Evolutionary dynamics on protein bi-stability landscapes can potentially resolve adaptive conflicts

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed.

Proteins are essential molecules for performing a majority of functions in all biological systems. These functions often depend on the three-dimensional structures of proteins. Here, we investigate a fundamental question in molecular evolution: how can proteins acquire new advantageous structures via mutations while not sacrificing their existing structures that are still needed? Some authors have suggested that the same protein may adopt two or more alternative structures, switch between them and thus perform different functions with each of the alternative structures. Intuitively, such a protein could provide an evolutionary compromise between conflicting demands for existing and new protein structures. Yet no theoretical study has systematically tackled the biophysical basis of such compromises during evolutionary processes. Here we devise a model of evolution that specifically recognizes protein molecules that can exist in several different stable structures. Our model demonstrates that proteins can indeed utilize multiple structures to satisfy conflicting evolutionary requirements. In light of these results, we identify data from known protein structures that are consistent with our predictions and suggest novel directions for future investigation.