The Proximal Lilly Collection: Mapping, Exploring and Exploiting Feasible Chemical Space

Abstract

Venturing into the immensity of the small molecule universe to identify novel chemical structure is a much discussed objective of many methods proposed by the chemoinformatics community. To this end, numerous approaches using techniques from the fields of computational de novo design, virtual screening and reaction informatics, among others, have been proposed. Although in principle this objective is commendable, in practice there are several obstacles to useful exploitation of the chemical space. Prime among them are the sheer number of theoretically feasible compounds and the practical concern regarding the synthesizability of the chemical structures conceived using in silico methods. We present the Proximal Lilly Collection initiative implemented at Eli Lilly and Co. with the aims to (i) define the chemical space of small, drug-like compounds that could be synthesized using in-house resources and (ii) facilitate access to compounds in this large space for the purposes of ongoing drug discovery efforts. The implementation of PLC relies on coupling access to available synthetic knowledge and resources with chemo/reaction informatics techniques and tools developed for this purpose. We describe in detail the computational framework supporting this initiative and elaborate on the characteristics of the PLC virtual collection of compounds. As an example of the opportunities provided to drug discovery researchers by easy access to a large, realistically feasible virtual collection such as the PLC, we describe a recent application of the technology that led to the discovery of selective kinase inhibitors.

Accelerating the discovery of materials for clean energy in the era of smart automation

“…High-throughput chemistry, often referred to as automated chemistry, was pioneered by the pharmaceutical industry in the search for efficient screening of their application spaces and for the cost-effective synthesis of new organic compounds 242,243 . In the mid to late 1990s, the first automated laboratory emerged in the field of peptide chemistry 244 .…”

A Perspective on Innovating the Chemistry Lab Bench

“…More recently, a resurgent interest in automated synthesis and high throughput experimentation (Mennen et al, 2019) coupled with dramatic increases in computational performance and advances in synthetic technology provides a unique opportunity particularly when applied to molecules of lower complexity. The possibility that retrosynthetic algorithms can now readily identify disconnections considered trivial by the synthetic practitioner actually makes an interesting case for integrating retrosynthetic analysis with automated chemical synthesis (Nicolaou et al, 2016). It could be possible for such a system to computationally evaluate and triage hundreds if not thousands of possible synthetic targets, identifying those that can be assembled via simple automated transformations whilst also sorting out the availability of the raw materials involved and spawning such executions automatically on an appropriately configured platform.…”

ChemOS: An orchestration software to democratize autonomous discovery

“…It allows to obtain information-theoretic driven decisions to maximize knowledge acquisition in order to reach a set of predefined goals, such as maximizing the yield of a reaction, reducing the time of an experiment or minimizing reactants usage. As such, this approach differs from combinatorial chemistry [7][8][9][10] in an essential aspect; in combinatorial chemistry, experimental campaigns are designed prior to starting the experimentation process, whereas the proposed approach has campaigns that adapt at every closed-loop iteration. Although the premise of autonomous research facilities has recently been analyzed, [3,11] a portable, modular and versatile software interfacing researchers, robots, and computational tools to orchestrate and facilitate the deployment of these self-driving laboratories is yet to be designed.…”

“…Automation was pioneered by the industrial sector in search for intensifying chemical and pharmaceutical processes to increase productivity and improve quality. [7,9,10,[12][13][14][15][16] During the last decades, several groups have demonstrated the benefits of automated systems on a variety of chemistries, [9,[17][18][19][20][21][22][23][24][25][26][27][28][29] and a few laboratory automation software packages have been developed. [30][31][32][33][34] One step further, the integration of design of experiment (DoE) [35][36][37] to automation emerged as a first strategic approach to experimentation.…”