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Biochemistry
Skills for
Drug Discovery
A Biochemical Society position statement | February 2014

Drug skills position statement
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In this paper we seek to identify and discuss some of the most
significant topics in modern drug discovery where young biochemists
can have a major impact
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Introduction
Modern drug design and development is a complex process that brings together numerous
chemical, biological and clinical disciplines
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These range from early involvement in the identification
and validation of potential molecular targets for new drug projects, to key roles in assay
design, troubleshooting and implementation throughout the screening and optimization
stages of both traditional small molecules and biopharmaceutical products
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At a later stage
in new drug research, biochemical assays are needed to evaluate disease models and to
drive biomarker analysis in translational medicine and clinical research
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At a more biophysical
level, biochemists may contribute significantly to computational chemistry and structural
analysis, such as crystallography or other methods employed to demonstrate drug-binding
modes and to predict potential modifications and improvements of lead compounds
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New drug opportunities
provided by various nucleic acid-based disease interventions, including gene replacement,
use of micro RNA gene silencing or exploitation of other novel methods for controlling
gene expression may draw more biochemistry graduates into pharmaceutical and drug
discovery careers
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Key knowledge, skills and
capabilities for biochemists
Any list of key knowledge, skills and capabilities is inevitably dynamic
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Biochemical basics
These should be central to all undergraduate courses in biochemistry
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This
can leave newer generations of students struggling with some basic concepts
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Analytical skills
Accurate identification and precise measurements of biochemical entities supports many
aspects of the life sciences, none more so than in drug design
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g
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The last of these, imaging and high-throughput microscopy, is an area of growth and rapid
change that offers novel approaches to drug screening and creates high content assay
formats that the industry is adopting so researchers with specific training in these areas
will be needed
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Assay design and statistics
Young scientists need to be able to design their own experimental protocols with a clear
understanding of how to ensure they generate data that are fit-for-purpose
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g
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A good grounding in assay design

Drug skills position statement
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Our graduates should be conversant with data analysis and aware of the importance
of understanding data distribution and the differences and relevance of arithmetic and
geometric means and how to use these calculations appropriately
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The relationships and importance of different ways of quantifying
binding interactions and their affinities from concentration/effect curves, kinetic rate
constants or thermodynamic measurements can each have a role in characterizing drug–
target interactions when the biochemists studying these parameters are well informed
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There are many underlying elementary principles that are common to these two protein
types and students should appreciate their similarities and differences
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The nature and impact of rate constants (particularly dissociation
rates) on assay design, the data produced and its interpretation should all be represented in
the core knowledge set
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Frequently, faults or imbalances in a signalling process drive disease
pathology
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A sound knowledge of the messengers and sometimes complex
pathways and networks involved will continue to be one of the most important topics for
young scientists to grasp as they move into careers in medical and drug research
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Molecular pathology
Understanding the biochemical basis of disease pathology is one of drug discovery’s main
challenges and we might anticipate thorough education and training in the techniques and
principles that can be employed will be a cornerstone of drug discovery skills training
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Pharmacokinetics and drug metabolism
Evaluation of drug metabolism requires biochemists who are conversant with some of
the most elementary skills in isolating and identifying reaction products and blood-borne
metabolites
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This requires considerable
skill in designing suitable assays and interpreting their output, but offers greater
opportunity for small drug discovery units to provide predictive data about the likely fate of
their products in vivo without recourse to animal experimentation
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At the early stages of discovery, the
cytotoxicity of potential therapeutics can be assessed against a range of cell types,
including hepatocyte toxicity and phopsholipidosis potential or monitoring interactions
with hERG channels
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Bioinformatics, ’X-omics‘ and ’Big data’
Activities such as the human genome project, genome-wide association studies and
informatics have identified very many potential biochemical targets for new drugs;
elucidating which of these offer authentic potential is an emerging modern challenge
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In particular, it seems timely for graduates to be able to understand the
outlines of analytical approaches and the types of visualization available for such analysis
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proteomic experimentation or from automated high-throughput and high-content assays
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Systems biology
Most of the diseases for which new treatments are now sought are multi-factorial
and medication is often with drug combinations
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The net behaviour of these systems is too complex
to be understood intuitively, arising as it does from non-linear interactions between
multiple components
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Models can
also function to integrate diverse experimental information, including high-throughput
data, enzyme kinetics, inhibition constants and pharmacokinetic data, as well as cellbased assays, animal experimentation and biomarker measurements
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It may also need to take into account the spatio-temporal
concentrations and compartmentalization of the relevant components
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Systems biology
requires a team approach where skills of practical and theoretical biochemistry combine
in creating and testing of models
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Structural biochemistry, crystallography and other physical techniques to
derive structural information, including molecular modellin

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