Affinity-based screening techniques for enhancing lead discovery

Contemporary, rational small-molecule lead discovery methods, comprising target identification, assay development, high-throughput screening (HTS), hit characterization and medicinal chemistry optimization, dominate early-stage drug discovery strategies in many pharmaceutical companies. There is a growing disparity between the increasing cost of funding these methods and the decreasing number of new drugs reaching the market. New strategies must be adopted to reverse this trend. The use of genomics- and proteomics-based target discovery efforts can aid the process by dramatically increasing the number of novel, more highly validated targets entering the discovery process, but HTS must meet this increased demand with faster, cheaper technologies. Although activity-based screening strategies are typically efficient, allowing one scientist to interrogate tens of thousands of compounds per day, affinity-based screening strategies can allow much greater efficiency in the overall process. Affinity-based methods can play a role in both facilitating the screening of a greater number of targets and in efficiently characterizing the primary hits discovered.     

Systematic analysis of large screening sets in drug discovery

Each year large pharmaceutical companies produce massive amounts of primary screening data for lead discovery. To make better use of the vast amount of information in pharmaceutical databases, companies have begun to scrutinize the lead generation stage to ensure that more and better qualified lead series enter the downstream optimization and development stages. This article describes computational techniques for end to end analysis of large drug discovery screening sets. The analysis proceeds in three stages: In stage 1 the initial screening set is filtered to remove compounds that are unsuitable as lead compounds. In stage 2 local structural neighborhoods around active compound classes are identified, including similar but inactive compounds. In stage 3 the structure-activity relationships within local structural neighborhoods are analyzed. These processes are illustrated by analyzing two large, publicly available databases.     

Lead optimization strategies as part of a drug metabolism environment

The rapid increase in the rate at which new chemical entities can be synthesized by medicinal chemists and tested in vitro for potency using high-throughput screening has provided opportunities for lead selection and optimization of thousands of compounds in major pharmaceutical companies. This opportunity coincides with the realization that drug metabolism input at the lead optimization stage is crucial for the development of compounds, with increased likelihood of success when tested in preclinical safety studies and in phase I trials. This has led to new discovery and optimization paradigms, in which drug metabolism is playing an important role.     

药物发现过程中人工智能的应用研究进展

人工智能（AI）和机器学习不仅使药物发现和开发实现了质的飞跃,而且帮助药物开发进程进入现代化。机器学习和深度学习算法已应用于药物发现各个阶段,如先导化合物的筛选、多肽合成及小分子药物的发现、最佳给药剂量的确定、类药化合物的设计和药物不良反应的预测、蛋白质间相互作用的预测、虚拟筛选效率的提高、定量构效关系（QSAR）建模和药物重新定位、理化性质和药物靶标亲和力的预测、化合物的结合预测和体内安全性分析、多靶点配体药物分子的设计以及临床试验的设计。简要综述了AI算法和传统化学相结合以提高药物发现的效率以及AI在药物发现过程中的应用研究进展,以期为AI应用于药物发现提供一定参考。     

Pharmacophore-based virtual screening: a review of recent applications

Importance of the field: In research relating to the development of new drugs, hit identification and validations are critical for successful optimization of candidates. To achieve rapid identification of new lead compounds, high-throughput screening assays have been employed in many pharmaceutical companies and laboratories. However, their success depends on the assay system relevant to in?vivo conditions and they are physically limited by the repertoire of compounds. As an alternative or complementary approach to high-throughput screening assays, virtual screening is an efficient method to identify drug candidates in silico from large chemical compound databases. Its usefulness has been verified by current applications that successfully retrieved hit and lead identifications against various disease targets. However, for better application, the scoring functions for distinguishing possible active and inactive compounds must beimproved. Areas covered in this review: In this review, we provide an overview of pharmacophore-based virtual screening methods with a special focus on their successful application towards finding hits against various diseasetargets. What the reader will gain: Readers will rapidly gain insight into the recent successful applications of pharmacophore-based virtual screening. They will acknowledge that this technique is a powerful and cost-effective alternative to high-throughput assays. Take home message: Although there are many hurdles yet to be resolved, virtual screening techniques will emerge as essential infrastructure and as a prerequisite for developing new lead compounds with therapeuticapplications.     

High-throughput screening for stability and inhibitory activity of compounds toward cytochrome P450-mediated metabolism

With the advent of combinatorial chemistry and high-throughput screening technology, thousands of molecules can now be rapidly synthesized and screened for biological activity against large numbers of protein targets, greatly increasing the speed with which lead compounds are identified during the early stages of drug discovery. However, rapid optimization of parameters that determine whether a high-affinity ligand or a potent inhibitor will become a successful drug remains a challenge in improving the efficiency of the drug discovery process. Parameters that define absorption, distribution, metabolism, and excretion properties of drug candidates are important determinants of therapeutic efficacy, and thus should be optimized during early stages of drug discovery. Although the speed with which drugs are screened for properties such as absorption, cytochrome P450 (CYP) inhibition, and metabolic stability has increased over the past several years, the screening rate/capacity is still several orders of magnitude lower than those for high-throughput methods used in lead identification, resulting in a bottleneck in the drug discovery process. This review discusses current methods used in the in vitro screening of drugs for their stability toward CYP-mediated oxidative metabolism. This is a critical screen in the drug discovery process because metabolism by CYP represents an important clearance mechanism for the vast majority of compounds, thus affecting their oral bioavailability and/or duration of action.     

Current topics in computer-aided drug design

The addition of computer-aided drug design (CADD) technologies to the research and drug discovery approaches could lead to a reduction of up to 50% in the cost of drug design. Designing a drug is the process of finding or creating a molecule which has a specific activity on a biological organism. Development and drug discovery is a time-consuming, expensive, and interdisciplinary process whereas scientific advancements during the past two decades have altered the way pharmaceutical research produces new bioactive molecules. Advances in computational techniques and hardware solutions have enabled in silico methods to speed up lead optimization and identification. We will review current topics in computer-aided molecular design underscoring some of the most recent approaches and interdisciplinary processes. We will discuss some of the most efficient pathways and design.     

Prediction of oral drug absorption in humans--from cultured cell lines and experimental animals

BACKGROUND: Over the past decade, the use of drug metabolism and pharmacokinetic (DMPK) parameters to optimize selection of candidates for drug development has become one of the primary focuses of research organizations involved in new drug discovery. OBJECTIVE: This review will focus on the feasibility of predicting human absorption using data from a cultured Caco-2 cell system and non-clinical animals. METHODS: In-house Caco-2 permeability data were compared with human absorption data from the literature. Animal absorption data obtained from current literature were also compared with human data. RESULTS/CONCLUSION: Using a combination of rapid in-vivo and in-vitro DMPK screens on a large array of compounds during the lead optimization process has resulted in the streamlined development of compounds that have acceptable DMPK properties. Since it is well recognized that human intestinal absorption cannot be precisely predicted by a single screening assay, it is important to utilize various in-vitro and in-vivo non-clinical studies during lead optimization in drug discovery.     

Permeability for intestinal absorption: Caco-2 assay and related issues

In vitro permeability assays remain a valuable tool of screening scientists for lead compound optimization. As a majority of discovery projects are focused on the development of orally bioavailable drugs, the need for predictability and correlation of in vitro permeability data to in vivo absorption results has never been greater. For more than a decade, the Caco-2 screening assay has remained a popular, in vitro system to test compounds for intestinal permeability and efflux liability. Despite advances in artificial membrane technology and in silico modeling systems, drug compounds still benefit from testing in cell-based epithelial monolayer assays for lead optimization and SAR. This review discusses the strengths and limitations of the Caco-2 permeability assay, and puts into context the power of combining multiple assays and approaches to improve predictability and rank-ordering for lead compound optimization. Technical information for dealing with some of the most pressing issues with in vitro permeability assays (i.e. low aqueous solubility and low post-assay recovery) is also discussed. Insights are offered to help researchers avoid common pitfalls in the interpretation of in vitro permeability data, which can often lead to the perception of misleading results for correlation to in vivo data. In addition, the advantages of addressing the issue of efflux liability early in the drug development process is discussed, detailing the usefulness of Caco-2 cells for this type of screening paradigm.     

Non-stoichiometric inhibition in integrated lead finding – a literature review

ABSTRACT

Introduction: Non-stoichiometric inhibition summarizes different mechanisms by which low-molecular weight compounds can reproducibly inhibit high-throughput screening (HTS) and other lead finding assays without binding to a structurally defined site on their molecular target. This disqualifies such molecules from optimization by medicinal chemistry, and therefore their rapid elimination from screening hit lists is essential for productive and effective drug discovery.

Areas covered: This review covers recent literature that either investigates the various mechanisms behind non-stoichiometric inhibition or suggests assays and readouts to identify them. In addition, combination of the various methods to distill promising molecules out of raw primary hit lists step-by-step is considered. Emerging technologies to demonstrate target engagement in cells are also discussed.

Expert opinion: Over the last few years, awareness of non-stoichiometric inhibitors within screening libraries and HTS hit lists has considerably increased, not only in the pharmaceutical industry but also in the academic drug discovery community. This has resulted in a variety of methods to detect and handle such compounds. These range from in silico approaches to flag suspicious compounds, and counterassays to measure non-stoichiometric inhibition, to biophysical methods that positively demonstrate stoichiometric binding. In addition, novel technologies to verify target engagement within cells are becoming available. While still a time- and resource-consuming nuisance, non-stoichiometric inhibitors therefore do not fundamentally jeopardize the discovery of low molecular weight lead and drug candidates. Rather, they should be viewed as a manageable issue that with appropriate expertise can be overcome through integration of the above-mentioned approaches.     

Quantum computing's potential for drug discovery: Early stage industry dynamics

Quantum computing (QC) is expected to revolutionize drug research by performing tasks classical supercomputers are not capable of. However, practically useful quantum computation is not yet a reality, and thus it is still unclear when and whether QC will be capable of solving real-world issues in drug discovery. By identifying the QC-related activities of pharmaceutical companies, startups, and academia in the field of drug discovery and development, we show that QC has gained traction across all of these stakeholder groups, that there is focus on developing utilities related to lead optimization and compound screening, and that there is a need for collaboration in the highly dynamic QC ecosystem.     

Optimizing the hit-to-lead process using SPR analysis

Secondary screening and lead optimization, where a large number of "hit" compounds are refined to a viable set of "lead" drug candidates, are considered to be bottlenecks to the drug discovery process and are targets for streamlining. Surface plasmon resonance (SPR) is a nonlabel technology that can generate kinetic data on biomolecular interactions. This allows researchers to quantitate the binding characteristics of lead compounds with their targets in terms of affinity, specificity, and association/dissociation rates in parallel. The latest generation of SPR biosensors integrate the hit-to-lead process and generate a greater depth of information, providing answers that cannot be addressed by traditional end-point assays. This allows users to make more informed choices on the selection of candidate molecules prior to preclinical development. A number of studies have used SPR biosensors in secondary screening, lead optimization, quantitative structure-activity relationship analysis, and predictive adsorption, distribution, metabolism, excretion, and/or toxicity evaluations.     

Accelerating drug discovery: creating the right environment

Technology can help with throughput; new drug discovery, information capture and screening techniques can produce thousands of compounds and speed potential products into preclinical trials. However, quantity and speed do not guarantee quality, uniqueness and therapeutic or commercial potential. Even with state-of-the-art automated systems, innovative and creative scientists are required to evaluate new compounds and to take research in new directions. The author discusses how companies can improve efficiency in new drug discovery without sacrificing creativity and quality of output in today's high-pressure process-driven environment.     

NMR-based approaches for lead discovery

NMR methods have long been used for studying molecular interactions. In the last few years, various NMR approaches have been developed to aid lead discovery. These involve different NMR screening methods to identify initial compounds, which often bind only weakly (in the micro- to millimolar range) to the drug target. Intelligent and focused follow-up strategies enable the development of these compounds into potent, submicromolar drug-like inhibitors for use as leads in drug discovery projects. NMR can be used as both a remarkably reliable screening tool and a structural tool; thus, this technique has unique opportunities for lead discovery.     

药物分子设计的策略：苗头和先导物的品质决定新药的成败

苗头化合物-先导物-候选药物是创制新药的三个重要里程碑，其中候选药物的确定是新药创制的关键环节，将创制过程分成研究和开发两个阶段，并且开发阶段所有环节都取决于候选药物的化学结构，所以决定了临床前和临床研究的命运。候选药物质量的高低又受制于先导化合物的类药性和苗头化合物的品质，苗头化合物演化成先导物是将新药的研究植根于有研发前景的结构上，先导物的优化是将活性化合物转化成候选药物的过程，是在药效、药代、安全性和物化性质等多维空间中的优化操作。本文结合实例讨论了发现苗头、确定先导物、先导物优化和确定候选药物的策略原则。     

Virtual screening: are we there yet?

The cost of pharmaceutical development has increased dramatically in recent years, and many assorted approaches have been developed to decrease both the time and costs associated with bringing a drug to the market. Among these methods is the use of in silico screening of compound databases for potential new lead compounds, commonly referred to as virtual screening (VS). Virtual screening has become an integral part of the early discovery process in pharmaceutical development, readily observed by the large number of methodologies that have been published to date. Other reviews have been published detailing the various types of virtual screening methods in use. This work will review some of the virtual screening approaches and strategies that have been attempted to identify compounds to launch medicinal chemistry campaigns. Understanding trends and drivers in VS should help to set expectations about how and when VS could be used and what it can and cannot deliver and how it can be integrated in a successful screening campaign and used in a complementary fashion to HTS.     

Development of a high throughput equilibrium solubility assay using miniaturized shake-flask method in early drug discovery

Increasingly, pharmaceutical and biotech companies have begun to realize the importance of obtaining solubility information in early drug discovery as it is one of the critical parameters for lead selection and optimization. This report introduces a high-throughput equilibrium solubility (HT-Eq sol) assay using a novel miniaturized shake-flask approach and streamlined HPLC analysis. The new HT-Eq sol assay, validated and optimized via a test set of 85 marketed drugs and Novartis internal compounds, shows an excellent correlation to the conventional shake-flask thermodynamic solubility data generated in-house and the equilibrium solubility results reported in literature. It therefore offers a fast, reliable and cost-effective screening tool for solubility assessment in early drug discovery, allowing for prioritization of drug candidates using aqueous solubility in conjunction with other profiling information and efficacy data. Our work demonstrates that presence of a small amount of DMSO (0.5-5%) will result in significant overstimation of equilibrium solubility (up to 6 folds). In addition, monitoring of drug dissolution process using the current approach as well as the interplay between equilibrium solubility data and those from kinetic solubility are discussed.     

The impact of informatics and computational chemistry on synthesis and screening

High-throughput synthesis and screening technologies have enhanced the impact of computational chemistry on the drug discovery process. From the design of targeted, drug-like libraries to ‘virtual’ optimization of potency, selectivity and ADME/Tox properties, computational chemists are able to efficiently manage costly resources and dramatically shorten drug discovery cycle times. This review will describe some of the successful strategies and applications of state-of-the-art algorithms to enhance drug discovery, as well as key points in the drug discovery process where computational methods can have, and have had, greatest impact.